types of research studies psychology

Psychological Research Methods: Types and Tips

Categories Research Methods

Psychological research methods are the techniques used by scientists and researchers to study human behavior and mental processes. These methods are used to gather empirical evidence.

The goal of psychological research methods is to obtain objective and verifiable data collected through scientific experimentation and observation. 

The research methods that are used in psychology are crucial for understanding how and why people behave the way they do, as well as for developing and testing theories about human behavior.

Table of Contents

Reasons to Learn More About Psychological Research Methods

One of the key goals of psychological research is to make sure that the data collected is reliable and valid.

• Reliability means that the data is consistent and can be replicated
• Validity refers to the accuracy of the data collected

Researchers must take great care to ensure that their research methods are reliable and valid, as this is essential for drawing accurate conclusions and making valid claims about human behavior.

High school and college students who are interested in psychology can benefit greatly from learning about research methods. Understanding how psychologists study human behavior and mental processes can help students develop critical thinking skills and a deeper appreciation for the complexity of human behavior.

Having an understanding of these research methods can prepare students for future coursework in psychology, as well as for potential careers in the field.

Quantitative vs. Qualitative Psychological Research Methods

Psychological research methods can be broadly divided into two main types: quantitative and qualitative. These two methods differ in their approach to data collection and analysis.

Quantitative Research Methods

Quantitative research methods involve collecting numerical data through controlled experiments, surveys, and other objective measures.

The goal of quantitative research is to identify patterns and relationships in the data that can be analyzed statistically.

Researchers use statistical methods to test hypotheses, identify significant differences between groups, and make predictions about future behavior.

Qualitative Research Methods

Qualitative research methods, on the other hand, involve collecting non-numerical data through open-ended interviews, observations, and other subjective measures.

Qualitative research aims to understand the subjective experiences and perspectives of individuals and groups.

Researchers use methods such as content analysis and thematic analysis to identify themes and patterns in the data and to develop rich descriptions of the phenomenon under study.

How Quantitative and Qualitative Methods Are Used

While quantitative and qualitative research methods differ in their approach to data collection and analysis, they are often used together to gain a more complete understanding of complex phenomena.

For example, a researcher studying the impact of social media on mental health might use a quantitative survey to gather numerical data on social media use and a qualitative interview to gain insight into participants’ subjective experiences with social media.

Types of Psychological Research Methods

There are several types of research methods used in psychology, including experiments, surveys, case studies, and observational studies. Each method has its strengths and weaknesses, and researchers must choose the most appropriate method based on their research question and the data they hope to collect.

Case Studies

A case study is a research method used in psychology to investigate an individual, group, or event in great detail. In a case study, the researcher gathers information from a variety of sources, including:

• Observation
• Document analysis

These methods allow researchers to gain an in-depth understanding of the case being studied.

Case studies are particularly useful when the phenomenon under investigation is rare or complex, and when it is difficult to replicate in a laboratory setting.

Surveys are a commonly used research method in psychology that involve gathering data from a large number of people about their thoughts, feelings, behaviors, and attitudes.

Surveys can be conducted in a variety of ways, including:

• In-person interviews
• Online questionnaires
• Paper-and-pencil surveys

Surveys are particularly useful when researchers want to study attitudes or behaviors that are difficult to observe directly or when they want to generalize their findings to a larger population.

Experimental Psychological Research Methods

Experimental studies are a research method commonly used in psychology to investigate cause-and-effect relationships between variables. In an experimental study, the researcher manipulates one or more variables to see how they affect another variable, while controlling for other factors that may influence the outcome.

Experimental studies are considered the gold standard for establishing cause-and-effect relationships, as they allow researchers to control for potential confounding variables and to manipulate variables in a systematic way.

Correlational Psychological Research Methods

Correlational research is a research method used in psychology to investigate the relationship between two or more variables without manipulating them. The goal of correlational research is to determine the extent to which changes in one variable are associated with changes in another variable.

In other words, correlational research aims to establish the direction and strength of the relationship between two or more variables.

Naturalistic Observation

Naturalistic observation is a research method used in psychology to study behavior in natural settings, without any interference or manipulation from the researcher.

The goal of naturalistic observation is to gain insight into how people or animals behave in their natural environment without the influence of laboratory conditions.

Meta-Analysis

A meta-analysis is a research method commonly used in psychology to combine and analyze the results of multiple studies on a particular topic.

The goal of a meta-analysis is to provide a comprehensive and quantitative summary of the existing research on a topic, in order to identify patterns and relationships that may not be apparent in individual studies.

Tips for Using Psychological Research Methods

Here are some tips for high school and college students who are interested in using psychological research methods:

Understand the different types of research methods: 

Before conducting any research, it is important to understand the different types of research methods that are available, such as surveys, case studies, experiments, and naturalistic observation.

Each method has its strengths and limitations, and selecting the appropriate method depends on the research question and variables being investigated.

Develop a clear research question: 

A good research question is essential for guiding the research process. It should be specific, clear, and relevant to the field of psychology. It is also important to consider ethical considerations when developing a research question.

Use proper sampling techniques: 

Sampling is the process of selecting participants for a study. It is important to use proper sampling techniques to ensure that the sample is representative of the population being studied.

Random sampling is considered the gold standard for sampling, but other techniques, such as convenience sampling, may also be used depending on the research question.

Use reliable and valid measures:

It is important to use reliable and valid measures to ensure the data collected is accurate and meaningful. This may involve using established measures or developing new measures and testing their reliability and validity.

Consider ethical issues:

It is important to consider ethical considerations when conducting psychological research, such as obtaining informed consent from participants, maintaining confidentiality, and minimizing any potential harm to participants.

In many cases, you will need to submit your study proposal to your school’s institutional review board for approval.

Analyze and interpret the data appropriately : 

After collecting the data, it is important to analyze and interpret the data appropriately. This may involve using statistical techniques to identify patterns and relationships between variables, and using appropriate software tools for analysis.

Communicate findings clearly: 

Finally, it is important to communicate the findings clearly in a way that is understandable to others. This may involve writing a research report, giving a presentation, or publishing a paper in a scholarly journal.

Clear communication is essential for advancing the field of psychology and informing future research.

Frequently Asked Questions

What are the 5 methods of psychological research.

The five main methods of psychological research are:

• Experimental research : This method involves manipulating one or more independent variables to observe their effect on one or more dependent variables while controlling for other variables. The goal is to establish cause-and-effect relationships between variables.
• Correlational research : This method involves examining the relationship between two or more variables, without manipulating them. The goal is to determine whether there is a relationship between the variables and the strength and direction of that relationship.
• Survey research : This method involves gathering information from a sample of participants using questionnaires or interviews. The goal is to collect data on attitudes, opinions, behaviors, or other variables of interest.
• Case study research : This method involves an in-depth analysis of a single individual, group, or event. The goal is to gain insight into specific behaviors, attitudes, or phenomena.
• Naturalistic observation research : This method involves observing and recording behavior in natural settings without any manipulation or interference from the researcher. The goal is to gain insight into how people or animals behave in their natural environment.

What is the most commonly used psychological research method?

The most common research method used in psychology varies depending on the research question and the variables being investigated. However, correlational research is one of the most frequently used methods in psychology.

This is likely because correlational research is useful in studying a wide range of psychological phenomena, and it can be used to examine the relationships between variables that cannot be manipulated or controlled, such as age, gender, and personality traits. 

Experimental research is also a widely used method in psychology, particularly in the areas of cognitive psychology , social psychology , and developmental psychology .

Other methods, such as survey research, case study research, and naturalistic observation, are also commonly used in psychology research, depending on the research question and the variables being studied.

How do you know which research method to use?

Deciding which type of research method to use depends on the research question, the variables being studied, and the practical considerations involved. Here are some general guidelines to help students decide which research method to use:

• Identify the research question : The first step is to clearly define the research question. What are you trying to study? What is the hypothesis you want to test? Answering these questions will help you determine which research method is best suited for your study.
• Choose your variables : Identify the independent and dependent variables involved in your research question. This will help you determine whether an experimental or correlational research method is most appropriate.
• Consider your resources : Think about the time, resources, and ethical considerations involved in conducting the research. For example, if you are working on a tight budget, a survey or correlational research method may be more feasible than an experimental study.
• Review existing literature : Conducting a literature review of previous studies on the topic can help you identify the most appropriate research method. This can also help you identify gaps in the literature that your study can fill.
• Consult with a mentor or advisor : If you are still unsure which research method to use, consult with a mentor or advisor who has experience in conducting research in your area of interest. They can provide guidance and help you make an informed decision.

Scholtz SE, de Klerk W, de Beer LT. The use of research methods in psychological research: A systematised review . Front Res Metr Anal . 2020;5:1. doi:10.3389/frma.2020.00001

Palinkas LA. Qualitative and mixed methods in mental health services and implementation research . J Clin Child Adolesc Psychol . 2014;43(6):851-861. doi:10.1080/15374416.2014.910791

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011;11(1):100. doi:10.1186/1471-2288-11-100

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Understanding Methods for Research in Psychology

A Psychology Research Methods Study Guide

Types of Research in Psychology

• Cross-Sectional vs. Longitudinal Research
• Reliability and Validity

Glossary of Terms

Research in psychology focuses on a variety of topics , ranging from the development of infants to the behavior of social groups. Psychologists use the scientific method to investigate questions both systematically and empirically.

Research in psychology is important because it provides us with valuable information that helps to improve human lives. By learning more about the brain, cognition, behavior, and mental health conditions, researchers are able to solve real-world problems that affect our day-to-day lives.

At a Glance

Knowing more about how research in psychology is conducted can give you a better understanding of what those findings might mean to you. Psychology experiments can range from simple to complex, but there are some basic terms and concepts that all psychology students should understand.

Start your studies by learning more about the different types of research, the basics of experimental design, and the relationships between variables.

Research in Psychology: The Basics

The first step in your review should include a basic introduction to psychology research methods . Psychology research can have a variety of goals. What researchers learn can be used to describe, explain, predict, or change human behavior.

Psychologists use the scientific method to conduct studies and research in psychology. The basic process of conducting psychology research involves asking a question, designing a study, collecting data, analyzing results, reaching conclusions, and sharing the findings.

The Scientific Method in Psychology Research

The steps of the scientific method in psychology research are:

• Make an observation
• Ask a research question and make predictions about what you expect to find
• Test your hypothesis and gather data
• Examine the results and form conclusions
• Report your findings

Research in psychology can take several different forms. It can describe a phenomenon, explore the causes of a phenomenon, or look at relationships between one or more variables. Three of the main types of psychological research focus on:

Descriptive Studies

This type of research can tell us more about what is happening in a specific population. It relies on techniques such as observation, surveys, and case studies.

Correlational Studies

Correlational research is frequently used in psychology to look for relationships between variables. While research look at how variables are related, they do not manipulate any of the variables.

While correlational studies can suggest a relationship between two variables, finding a correlation does not prove that one variable causes a change in another. In other words, correlation does not equal causation.

Experimental Research Methods

Experiments are a research method that can look at whether changes in one variable cause changes in another. The simple experiment is one of the most basic methods of determining if there is a cause-and-effect relationship between two variables.

A simple experiment utilizes a control group of participants who receive no treatment and an experimental group of participants who receive the treatment.

Experimenters then compare the results of the two groups to determine if the treatment had an effect.

Cross-Sectional vs. Longitudinal Research in Psychology

Research in psychology can also involve collecting data at a single point in time, or gathering information at several points over a period of time.

Cross-Sectional Research

In a cross-sectional study , researchers collect data from participants at a single point in time. These are descriptive type of research and cannot be used to determine cause and effect because researchers do not manipulate the independent variables.

However, cross-sectional research does allow researchers to look at the characteristics of the population and explore relationships between different variables at a single point in time.

Longitudinal Research

A longitudinal study is a type of research in psychology that involves looking at the same group of participants over a period of time. Researchers start by collecting initial data that serves as a baseline, and then collect follow-up data at certain intervals. These studies can last days, months, or years. 

The longest longitudinal study in psychology was started in 1921 and the study is planned to continue until the last participant dies or withdraws. As of 2003, more than 200 of the partipants were still alive.

The Reliability and Validity of Research in Psychology

Reliability and validity are two concepts that are also critical in psychology research. In order to trust the results, we need to know if the findings are consistent (reliability) and that we are actually measuring what we think we are measuring (validity).

Reliability

Reliability is a vital component of a valid psychological test. What is reliability? How do we measure it? Simply put, reliability refers to the consistency of a measure. A test is considered reliable if we get the same result repeatedly.

When determining the merits of a psychological test, validity is one of the most important factors to consider. What exactly is validity? One of the greatest concerns when creating a psychological test is whether or not it actually measures what we think it is measuring.

For example, a test might be designed to measure a stable personality trait but instead measures transitory emotions generated by situational or environmental conditions. A valid test ensures that the results accurately reflect the dimension undergoing assessment.

Review some of the key terms that you should know and understand about psychology research methods. Spend some time studying these terms and definitions before your exam. Some key terms that you should know include:

• Correlation
• Demand characteristic
• Dependent variable
• Hawthorne effect
• Independent variable
• Naturalistic observation
• Placebo effect
• Random assignment
• Replication
• Selective attrition

Erol A.  How to conduct scientific research ?  Noro Psikiyatr Ars . 2017;54(2):97-98. doi:10.5152/npa.2017.0120102

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies .  Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Curtis EA, Comiskey C, Dempsey O. Importance and use of correlational research .  Nurse Res . 2016;23(6):20-25. doi:10.7748/nr.2016.e1382

Wang X, Cheng Z. Cross-sectional studies: Strengths, weaknesses, and recommendations .  Chest . 2020;158(1S):S65-S71. doi:10.1016/j.chest.2020.03.012

Caruana EJ, Roman M, Hernández-Sánchez J, Solli P. Longitudinal studies .  J Thorac Dis . 2015;7(11):E537-E540. doi:10.3978/j.issn.2072-1439.2015.10.63

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The Use of Research Methods in Psychological Research: A Systematised Review

Salomé elizabeth scholtz.

1 Community Psychosocial Research (COMPRES), School of Psychosocial Health, North-West University, Potchefstroom, South Africa

Werner de Klerk

Leon t. de beer.

2 WorkWell Research Institute, North-West University, Potchefstroom, South Africa

Research methods play an imperative role in research quality as well as educating young researchers, however, the application thereof is unclear which can be detrimental to the field of psychology. Therefore, this systematised review aimed to determine what research methods are being used, how these methods are being used and for what topics in the field. Our review of 999 articles from five journals over a period of 5 years indicated that psychology research is conducted in 10 topics via predominantly quantitative research methods. Of these 10 topics, social psychology was the most popular. The remainder of the conducted methodology is described. It was also found that articles lacked rigour and transparency in the used methodology which has implications for replicability. In conclusion this article, provides an overview of all reported methodologies used in a sample of psychology journals. It highlights the popularity and application of methods and designs throughout the article sample as well as an unexpected lack of rigour with regard to most aspects of methodology. Possible sample bias should be considered when interpreting the results of this study. It is recommended that future research should utilise the results of this study to determine the possible impact on the field of psychology as a science and to further investigation into the use of research methods. Results should prompt the following future research into: a lack or rigour and its implication on replication, the use of certain methods above others, publication bias and choice of sampling method.

Introduction

Psychology is an ever-growing and popular field (Gough and Lyons, 2016 ; Clay, 2017 ). Due to this growth and the need for science-based research to base health decisions on (Perestelo-Pérez, 2013 ), the use of research methods in the broad field of psychology is an essential point of investigation (Stangor, 2011 ; Aanstoos, 2014 ). Research methods are therefore viewed as important tools used by researchers to collect data (Nieuwenhuis, 2016 ) and include the following: quantitative, qualitative, mixed method and multi method (Maree, 2016 ). Additionally, researchers also employ various types of literature reviews to address research questions (Grant and Booth, 2009 ). According to literature, what research method is used and why a certain research method is used is complex as it depends on various factors that may include paradigm (O'Neil and Koekemoer, 2016 ), research question (Grix, 2002 ), or the skill and exposure of the researcher (Nind et al., 2015 ). How these research methods are employed is also difficult to discern as research methods are often depicted as having fixed boundaries that are continuously crossed in research (Johnson et al., 2001 ; Sandelowski, 2011 ). Examples of this crossing include adding quantitative aspects to qualitative studies (Sandelowski et al., 2009 ), or stating that a study used a mixed-method design without the study having any characteristics of this design (Truscott et al., 2010 ).

The inappropriate use of research methods affects how students and researchers improve and utilise their research skills (Scott Jones and Goldring, 2015 ), how theories are developed (Ngulube, 2013 ), and the credibility of research results (Levitt et al., 2017 ). This, in turn, can be detrimental to the field (Nind et al., 2015 ), journal publication (Ketchen et al., 2008 ; Ezeh et al., 2010 ), and attempts to address public social issues through psychological research (Dweck, 2017 ). This is especially important given the now well-known replication crisis the field is facing (Earp and Trafimow, 2015 ; Hengartner, 2018 ).

Due to this lack of clarity on method use and the potential impact of inept use of research methods, the aim of this study was to explore the use of research methods in the field of psychology through a review of journal publications. Chaichanasakul et al. ( 2011 ) identify reviewing articles as the opportunity to examine the development, growth and progress of a research area and overall quality of a journal. Studies such as Lee et al. ( 1999 ) as well as Bluhm et al. ( 2011 ) review of qualitative methods has attempted to synthesis the use of research methods and indicated the growth of qualitative research in American and European journals. Research has also focused on the use of research methods in specific sub-disciplines of psychology, for example, in the field of Industrial and Organisational psychology Coetzee and Van Zyl ( 2014 ) found that South African publications tend to consist of cross-sectional quantitative research methods with underrepresented longitudinal studies. Qualitative studies were found to make up 21% of the articles published from 1995 to 2015 in a similar study by O'Neil and Koekemoer ( 2016 ). Other methods in health psychology, such as Mixed methods research have also been reportedly growing in popularity (O'Cathain, 2009 ).

A broad overview of the use of research methods in the field of psychology as a whole is however, not available in the literature. Therefore, our research focused on answering what research methods are being used, how these methods are being used and for what topics in practice (i.e., journal publications) in order to provide a general perspective of method used in psychology publication. We synthesised the collected data into the following format: research topic [areas of scientific discourse in a field or the current needs of a population (Bittermann and Fischer, 2018 )], method [data-gathering tools (Nieuwenhuis, 2016 )], sampling [elements chosen from a population to partake in research (Ritchie et al., 2009 )], data collection [techniques and research strategy (Maree, 2016 )], and data analysis [discovering information by examining bodies of data (Ktepi, 2016 )]. A systematised review of recent articles (2013 to 2017) collected from five different journals in the field of psychological research was conducted.

Grant and Booth ( 2009 ) describe systematised reviews as the review of choice for post-graduate studies, which is employed using some elements of a systematic review and seldom more than one or two databases to catalogue studies after a comprehensive literature search. The aspects used in this systematised review that are similar to that of a systematic review were a full search within the chosen database and data produced in tabular form (Grant and Booth, 2009 ).

Sample sizes and timelines vary in systematised reviews (see Lowe and Moore, 2014 ; Pericall and Taylor, 2014 ; Barr-Walker, 2017 ). With no clear parameters identified in the literature (see Grant and Booth, 2009 ), the sample size of this study was determined by the purpose of the sample (Strydom, 2011 ), and time and cost constraints (Maree and Pietersen, 2016 ). Thus, a non-probability purposive sample (Ritchie et al., 2009 ) of the top five psychology journals from 2013 to 2017 was included in this research study. Per Lee ( 2015 ) American Psychological Association (APA) recommends the use of the most up-to-date sources for data collection with consideration of the context of the research study. As this research study focused on the most recent trends in research methods used in the broad field of psychology, the identified time frame was deemed appropriate.

Psychology journals were only included if they formed part of the top five English journals in the miscellaneous psychology domain of the Scimago Journal and Country Rank (Scimago Journal & Country Rank, 2017 ). The Scimago Journal and Country Rank provides a yearly updated list of publicly accessible journal and country-specific indicators derived from the Scopus® database (Scopus, 2017b ) by means of the Scimago Journal Rank (SJR) indicator developed by Scimago from the algorithm Google PageRank™ (Scimago Journal & Country Rank, 2017 ). Scopus is the largest global database of abstracts and citations from peer-reviewed journals (Scopus, 2017a ). Reasons for the development of the Scimago Journal and Country Rank list was to allow researchers to assess scientific domains, compare country rankings, and compare and analyse journals (Scimago Journal & Country Rank, 2017 ), which supported the aim of this research study. Additionally, the goals of the journals had to focus on topics in psychology in general with no preference to specific research methods and have full-text access to articles.

The following list of top five journals in 2018 fell within the abovementioned inclusion criteria (1) Australian Journal of Psychology, (2) British Journal of Psychology, (3) Europe's Journal of Psychology, (4) International Journal of Psychology and lastly the (5) Journal of Psychology Applied and Interdisciplinary.

Journals were excluded from this systematised review if no full-text versions of their articles were available, if journals explicitly stated a publication preference for certain research methods, or if the journal only published articles in a specific discipline of psychological research (for example, industrial psychology, clinical psychology etc.).

The researchers followed a procedure (see Figure 1 ) adapted from that of Ferreira et al. ( 2016 ) for systematised reviews. Data collection and categorisation commenced on 4 December 2017 and continued until 30 June 2019. All the data was systematically collected and coded manually (Grant and Booth, 2009 ) with an independent person acting as co-coder. Codes of interest included the research topic, method used, the design used, sampling method, and methodology (the method used for data collection and data analysis). These codes were derived from the wording in each article. Themes were created based on the derived codes and checked by the co-coder. Lastly, these themes were catalogued into a table as per the systematised review design.

Systematised review procedure.

According to Johnston et al. ( 2019 ), “literature screening, selection, and data extraction/analyses” (p. 7) are specifically tailored to the aim of a review. Therefore, the steps followed in a systematic review must be reported in a comprehensive and transparent manner. The chosen systematised design adhered to the rigour expected from systematic reviews with regard to full search and data produced in tabular form (Grant and Booth, 2009 ). The rigorous application of the systematic review is, therefore discussed in relation to these two elements.

Firstly, to ensure a comprehensive search, this research study promoted review transparency by following a clear protocol outlined according to each review stage before collecting data (Johnston et al., 2019 ). This protocol was similar to that of Ferreira et al. ( 2016 ) and approved by three research committees/stakeholders and the researchers (Johnston et al., 2019 ). The eligibility criteria for article inclusion was based on the research question and clearly stated, and the process of inclusion was recorded on an electronic spreadsheet to create an evidence trail (Bandara et al., 2015 ; Johnston et al., 2019 ). Microsoft Excel spreadsheets are a popular tool for review studies and can increase the rigour of the review process (Bandara et al., 2015 ). Screening for appropriate articles for inclusion forms an integral part of a systematic review process (Johnston et al., 2019 ). This step was applied to two aspects of this research study: the choice of eligible journals and articles to be included. Suitable journals were selected by the first author and reviewed by the second and third authors. Initially, all articles from the chosen journals were included. Then, by process of elimination, those irrelevant to the research aim, i.e., interview articles or discussions etc., were excluded.

To ensure rigourous data extraction, data was first extracted by one reviewer, and an independent person verified the results for completeness and accuracy (Johnston et al., 2019 ). The research question served as a guide for efficient, organised data extraction (Johnston et al., 2019 ). Data was categorised according to the codes of interest, along with article identifiers for audit trails such as authors, title and aims of articles. The categorised data was based on the aim of the review (Johnston et al., 2019 ) and synthesised in tabular form under methods used, how these methods were used, and for what topics in the field of psychology.

The initial search produced a total of 1,145 articles from the 5 journals identified. Inclusion and exclusion criteria resulted in a final sample of 999 articles ( Figure 2 ). Articles were co-coded into 84 codes, from which 10 themes were derived ( Table 1 ).

Journal article frequency.

Codes used to form themes (research topics).

These 10 themes represent the topic section of our research question ( Figure 3 ). All these topics except, for the final one, psychological practice , were found to concur with the research areas in psychology as identified by Weiten ( 2010 ). These research areas were chosen to represent the derived codes as they provided broad definitions that allowed for clear, concise categorisation of the vast amount of data. Article codes were categorised under particular themes/topics if they adhered to the research area definitions created by Weiten ( 2010 ). It is important to note that these areas of research do not refer to specific disciplines in psychology, such as industrial psychology; but to broader fields that may encompass sub-interests of these disciplines.

Topic frequency (international sample).

In the case of developmental psychology , researchers conduct research into human development from childhood to old age. Social psychology includes research on behaviour governed by social drivers. Researchers in the field of educational psychology study how people learn and the best way to teach them. Health psychology aims to determine the effect of psychological factors on physiological health. Physiological psychology , on the other hand, looks at the influence of physiological aspects on behaviour. Experimental psychology is not the only theme that uses experimental research and focuses on the traditional core topics of psychology (for example, sensation). Cognitive psychology studies the higher mental processes. Psychometrics is concerned with measuring capacity or behaviour. Personality research aims to assess and describe consistency in human behaviour (Weiten, 2010 ). The final theme of psychological practice refers to the experiences, techniques, and interventions employed by practitioners, researchers, and academia in the field of psychology.

Articles under these themes were further subdivided into methodologies: method, sampling, design, data collection, and data analysis. The categorisation was based on information stated in the articles and not inferred by the researchers. Data were compiled into two sets of results presented in this article. The first set addresses the aim of this study from the perspective of the topics identified. The second set of results represents a broad overview of the results from the perspective of the methodology employed. The second set of results are discussed in this article, while the first set is presented in table format. The discussion thus provides a broad overview of methods use in psychology (across all themes), while the table format provides readers with in-depth insight into methods used in the individual themes identified. We believe that presenting the data from both perspectives allow readers a broad understanding of the results. Due a large amount of information that made up our results, we followed Cichocka and Jost ( 2014 ) in simplifying our results. Please note that the numbers indicated in the table in terms of methodology differ from the total number of articles. Some articles employed more than one method/sampling technique/design/data collection method/data analysis in their studies.

What follows is the results for what methods are used, how these methods are used, and which topics in psychology they are applied to . Percentages are reported to the second decimal in order to highlight small differences in the occurrence of methodology.

Firstly, with regard to the research methods used, our results show that researchers are more likely to use quantitative research methods (90.22%) compared to all other research methods. Qualitative research was the second most common research method but only made up about 4.79% of the general method usage. Reviews occurred almost as much as qualitative studies (3.91%), as the third most popular method. Mixed-methods research studies (0.98%) occurred across most themes, whereas multi-method research was indicated in only one study and amounted to 0.10% of the methods identified. The specific use of each method in the topics identified is shown in Table 2 and Figure 4 .

Research methods in psychology.

Research method frequency in topics.

Secondly, in the case of how these research methods are employed , our study indicated the following.

Sampling −78.34% of the studies in the collected articles did not specify a sampling method. From the remainder of the studies, 13 types of sampling methods were identified. These sampling methods included broad categorisation of a sample as, for example, a probability or non-probability sample. General samples of convenience were the methods most likely to be applied (10.34%), followed by random sampling (3.51%), snowball sampling (2.73%), and purposive (1.37%) and cluster sampling (1.27%). The remainder of the sampling methods occurred to a more limited extent (0–1.0%). See Table 3 and Figure 5 for sampling methods employed in each topic.

Sampling use in the field of psychology.

Sampling method frequency in topics.

Designs were categorised based on the articles' statement thereof. Therefore, it is important to note that, in the case of quantitative studies, non-experimental designs (25.55%) were often indicated due to a lack of experiments and any other indication of design, which, according to Laher ( 2016 ), is a reasonable categorisation. Non-experimental designs should thus be compared with experimental designs only in the description of data, as it could include the use of correlational/cross-sectional designs, which were not overtly stated by the authors. For the remainder of the research methods, “not stated” (7.12%) was assigned to articles without design types indicated.

From the 36 identified designs the most popular designs were cross-sectional (23.17%) and experimental (25.64%), which concurred with the high number of quantitative studies. Longitudinal studies (3.80%), the third most popular design, was used in both quantitative and qualitative studies. Qualitative designs consisted of ethnography (0.38%), interpretative phenomenological designs/phenomenology (0.28%), as well as narrative designs (0.28%). Studies that employed the review method were mostly categorised as “not stated,” with the most often stated review designs being systematic reviews (0.57%). The few mixed method studies employed exploratory, explanatory (0.09%), and concurrent designs (0.19%), with some studies referring to separate designs for the qualitative and quantitative methods. The one study that identified itself as a multi-method study used a longitudinal design. Please see how these designs were employed in each specific topic in Table 4 , Figure 6 .

Design use in the field of psychology.

Design frequency in topics.

Data collection and analysis —data collection included 30 methods, with the data collection method most often employed being questionnaires (57.84%). The experimental task (16.56%) was the second most preferred collection method, which included established or unique tasks designed by the researchers. Cognitive ability tests (6.84%) were also regularly used along with various forms of interviewing (7.66%). Table 5 and Figure 7 represent data collection use in the various topics. Data analysis consisted of 3,857 occurrences of data analysis categorised into ±188 various data analysis techniques shown in Table 6 and Figures 1 – 7 . Descriptive statistics were the most commonly used (23.49%) along with correlational analysis (17.19%). When using a qualitative method, researchers generally employed thematic analysis (0.52%) or different forms of analysis that led to coding and the creation of themes. Review studies presented few data analysis methods, with most studies categorising their results. Mixed method and multi-method studies followed the analysis methods identified for the qualitative and quantitative studies included.

Data collection in the field of psychology.

Data collection frequency in topics.

Data analysis in the field of psychology.

Results of the topics researched in psychology can be seen in the tables, as previously stated in this article. It is noteworthy that, of the 10 topics, social psychology accounted for 43.54% of the studies, with cognitive psychology the second most popular research topic at 16.92%. The remainder of the topics only occurred in 4.0–7.0% of the articles considered. A list of the included 999 articles is available under the section “View Articles” on the following website: https://methodgarden.xtrapolate.io/ . This website was created by Scholtz et al. ( 2019 ) to visually present a research framework based on this Article's results.

This systematised review categorised full-length articles from five international journals across the span of 5 years to provide insight into the use of research methods in the field of psychology. Results indicated what methods are used how these methods are being used and for what topics (why) in the included sample of articles. The results should be seen as providing insight into method use and by no means a comprehensive representation of the aforementioned aim due to the limited sample. To our knowledge, this is the first research study to address this topic in this manner. Our discussion attempts to promote a productive way forward in terms of the key results for method use in psychology, especially in the field of academia (Holloway, 2008 ).

With regard to the methods used, our data stayed true to literature, finding only common research methods (Grant and Booth, 2009 ; Maree, 2016 ) that varied in the degree to which they were employed. Quantitative research was found to be the most popular method, as indicated by literature (Breen and Darlaston-Jones, 2010 ; Counsell and Harlow, 2017 ) and previous studies in specific areas of psychology (see Coetzee and Van Zyl, 2014 ). Its long history as the first research method (Leech et al., 2007 ) in the field of psychology as well as researchers' current application of mathematical approaches in their studies (Toomela, 2010 ) might contribute to its popularity today. Whatever the case may be, our results show that, despite the growth in qualitative research (Demuth, 2015 ; Smith and McGannon, 2018 ), quantitative research remains the first choice for article publication in these journals. Despite the included journals indicating openness to articles that apply any research methods. This finding may be due to qualitative research still being seen as a new method (Burman and Whelan, 2011 ) or reviewers' standards being higher for qualitative studies (Bluhm et al., 2011 ). Future research is encouraged into the possible biasness in publication of research methods, additionally further investigation with a different sample into the proclaimed growth of qualitative research may also provide different results.

Review studies were found to surpass that of multi-method and mixed method studies. To this effect Grant and Booth ( 2009 ), state that the increased awareness, journal contribution calls as well as its efficiency in procuring research funds all promote the popularity of reviews. The low frequency of mixed method studies contradicts the view in literature that it's the third most utilised research method (Tashakkori and Teddlie's, 2003 ). Its' low occurrence in this sample could be due to opposing views on mixing methods (Gunasekare, 2015 ) or that authors prefer publishing in mixed method journals, when using this method, or its relative novelty (Ivankova et al., 2016 ). Despite its low occurrence, the application of the mixed methods design in articles was methodologically clear in all cases which were not the case for the remainder of research methods.

Additionally, a substantial number of studies used a combination of methodologies that are not mixed or multi-method studies. Perceived fixed boundaries are according to literature often set aside, as confirmed by this result, in order to investigate the aim of a study, which could create a new and helpful way of understanding the world (Gunasekare, 2015 ). According to Toomela ( 2010 ), this is not unheard of and could be considered a form of “structural systemic science,” as in the case of qualitative methodology (observation) applied in quantitative studies (experimental design) for example. Based on this result, further research into this phenomenon as well as its implications for research methods such as multi and mixed methods is recommended.

Discerning how these research methods were applied, presented some difficulty. In the case of sampling, most studies—regardless of method—did mention some form of inclusion and exclusion criteria, but no definite sampling method. This result, along with the fact that samples often consisted of students from the researchers' own academic institutions, can contribute to literature and debates among academics (Peterson and Merunka, 2014 ; Laher, 2016 ). Samples of convenience and students as participants especially raise questions about the generalisability and applicability of results (Peterson and Merunka, 2014 ). This is because attention to sampling is important as inappropriate sampling can debilitate the legitimacy of interpretations (Onwuegbuzie and Collins, 2017 ). Future investigation into the possible implications of this reported popular use of convenience samples for the field of psychology as well as the reason for this use could provide interesting insight, and is encouraged by this study.

Additionally, and this is indicated in Table 6 , articles seldom report the research designs used, which highlights the pressing aspect of the lack of rigour in the included sample. Rigour with regards to the applied empirical method is imperative in promoting psychology as a science (American Psychological Association, 2020 ). Omitting parts of the research process in publication when it could have been used to inform others' research skills should be questioned, and the influence on the process of replicating results should be considered. Publications are often rejected due to a lack of rigour in the applied method and designs (Fonseca, 2013 ; Laher, 2016 ), calling for increased clarity and knowledge of method application. Replication is a critical part of any field of scientific research and requires the “complete articulation” of the study methods used (Drotar, 2010 , p. 804). The lack of thorough description could be explained by the requirements of certain journals to only report on certain aspects of a research process, especially with regard to the applied design (Laher, 20). However, naming aspects such as sampling and designs, is a requirement according to the APA's Journal Article Reporting Standards (JARS-Quant) (Appelbaum et al., 2018 ). With very little information on how a study was conducted, authors lose a valuable opportunity to enhance research validity, enrich the knowledge of others, and contribute to the growth of psychology and methodology as a whole. In the case of this research study, it also restricted our results to only reported samples and designs, which indicated a preference for certain designs, such as cross-sectional designs for quantitative studies.

Data collection and analysis were for the most part clearly stated. A key result was the versatile use of questionnaires. Researchers would apply a questionnaire in various ways, for example in questionnaire interviews, online surveys, and written questionnaires across most research methods. This may highlight a trend for future research.

With regard to the topics these methods were employed for, our research study found a new field named “psychological practice.” This result may show the growing consciousness of researchers as part of the research process (Denzin and Lincoln, 2003 ), psychological practice, and knowledge generation. The most popular of these topics was social psychology, which is generously covered in journals and by learning societies, as testaments of the institutional support and richness social psychology has in the field of psychology (Chryssochoou, 2015 ). The APA's perspective on 2018 trends in psychology also identifies an increased amount of psychology focus on how social determinants are influencing people's health (Deangelis, 2017 ).

This study was not without limitations and the following should be taken into account. Firstly, this study used a sample of five specific journals to address the aim of the research study, despite general journal aims (as stated on journal websites), this inclusion signified a bias towards the research methods published in these specific journals only and limited generalisability. A broader sample of journals over a different period of time, or a single journal over a longer period of time might provide different results. A second limitation is the use of Excel spreadsheets and an electronic system to log articles, which was a manual process and therefore left room for error (Bandara et al., 2015 ). To address this potential issue, co-coding was performed to reduce error. Lastly, this article categorised data based on the information presented in the article sample; there was no interpretation of what methodology could have been applied or whether the methods stated adhered to the criteria for the methods used. Thus, a large number of articles that did not clearly indicate a research method or design could influence the results of this review. However, this in itself was also a noteworthy result. Future research could review research methods of a broader sample of journals with an interpretive review tool that increases rigour. Additionally, the authors also encourage the future use of systematised review designs as a way to promote a concise procedure in applying this design.

Our research study presented the use of research methods for published articles in the field of psychology as well as recommendations for future research based on these results. Insight into the complex questions identified in literature, regarding what methods are used how these methods are being used and for what topics (why) was gained. This sample preferred quantitative methods, used convenience sampling and presented a lack of rigorous accounts for the remaining methodologies. All methodologies that were clearly indicated in the sample were tabulated to allow researchers insight into the general use of methods and not only the most frequently used methods. The lack of rigorous account of research methods in articles was represented in-depth for each step in the research process and can be of vital importance to address the current replication crisis within the field of psychology. Recommendations for future research aimed to motivate research into the practical implications of the results for psychology, for example, publication bias and the use of convenience samples.

Ethics Statement

This study was cleared by the North-West University Health Research Ethics Committee: NWU-00115-17-S1.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Ch 2: Psychological Research Methods

Have you ever wondered whether the violence you see on television affects your behavior? Are you more likely to behave aggressively in real life after watching people behave violently in dramatic situations on the screen? Or, could seeing fictional violence actually get aggression out of your system, causing you to be more peaceful? How are children influenced by the media they are exposed to? A psychologist interested in the relationship between behavior and exposure to violent images might ask these very questions.

The topic of violence in the media today is contentious. Since ancient times, humans have been concerned about the effects of new technologies on our behaviors and thinking processes. The Greek philosopher Socrates, for example, worried that writing—a new technology at that time—would diminish people’s ability to remember because they could rely on written records rather than committing information to memory. In our world of quickly changing technologies, questions about the effects of media continue to emerge. Is it okay to talk on a cell phone while driving? Are headphones good to use in a car? What impact does text messaging have on reaction time while driving? These are types of questions that psychologist David Strayer asks in his lab.

Watch this short video to see how Strayer utilizes the scientific method to reach important conclusions regarding technology and driving safety.

You can view the transcript for “Understanding driver distraction” here (opens in new window) .

How can we go about finding answers that are supported not by mere opinion, but by evidence that we can all agree on? The findings of psychological research can help us navigate issues like this.

Introduction to the Scientific Method

Learning objectives.

• Explain the steps of the scientific method
• Describe why the scientific method is important to psychology
• Summarize the processes of informed consent and debriefing
• Explain how research involving humans or animals is regulated

Scientists are engaged in explaining and understanding how the world around them works, and they are able to do so by coming up with theories that generate hypotheses that are testable and falsifiable. Theories that stand up to their tests are retained and refined, while those that do not are discarded or modified. In this way, research enables scientists to separate fact from simple opinion. Having good information generated from research aids in making wise decisions both in public policy and in our personal lives. In this section, you’ll see how psychologists use the scientific method to study and understand behavior.

The Scientific Process

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see the behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This module explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

Process of Scientific Research

Scientific knowledge is advanced through a process known as the scientific method. Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on.

The basic steps in the scientific method are:

• Observe a natural phenomenon and define a question about it
• Make a hypothesis, or potential solution to the question
• Test the hypothesis
• If the hypothesis is true, find more evidence or find counter-evidence
• If the hypothesis is false, create a new hypothesis or try again
• Draw conclusions and repeat–the scientific method is never-ending, and no result is ever considered perfect

In order to ask an important question that may improve our understanding of the world, a researcher must first observe natural phenomena. By making observations, a researcher can define a useful question. After finding a question to answer, the researcher can then make a prediction (a hypothesis) about what he or she thinks the answer will be. This prediction is usually a statement about the relationship between two or more variables. After making a hypothesis, the researcher will then design an experiment to test his or her hypothesis and evaluate the data gathered. These data will either support or refute the hypothesis. Based on the conclusions drawn from the data, the researcher will then find more evidence to support the hypothesis, look for counter-evidence to further strengthen the hypothesis, revise the hypothesis and create a new experiment, or continue to incorporate the information gathered to answer the research question.

Basic Principles of the Scientific Method

Two key concepts in the scientific approach are theory and hypothesis. A theory is a well-developed set of ideas that propose an explanation for observed phenomena that can be used to make predictions about future observations. A hypothesis is a testable prediction that is arrived at logically from a theory. It is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests.

Other key components in following the scientific method include verifiability, predictability, falsifiability, and fairness. Verifiability means that an experiment must be replicable by another researcher. To achieve verifiability, researchers must make sure to document their methods and clearly explain how their experiment is structured and why it produces certain results.

Predictability in a scientific theory implies that the theory should enable us to make predictions about future events. The precision of these predictions is a measure of the strength of the theory.

Falsifiability refers to whether a hypothesis can be disproved. For a hypothesis to be falsifiable, it must be logically possible to make an observation or do a physical experiment that would show that there is no support for the hypothesis. Even when a hypothesis cannot be shown to be false, that does not necessarily mean it is not valid. Future testing may disprove the hypothesis. This does not mean that a hypothesis has to be shown to be false, just that it can be tested.

To determine whether a hypothesis is supported or not supported, psychological researchers must conduct hypothesis testing using statistics. Hypothesis testing is a type of statistics that determines the probability of a hypothesis being true or false. If hypothesis testing reveals that results were “statistically significant,” this means that there was support for the hypothesis and that the researchers can be reasonably confident that their result was not due to random chance. If the results are not statistically significant, this means that the researchers’ hypothesis was not supported.

Fairness implies that all data must be considered when evaluating a hypothesis. A researcher cannot pick and choose what data to keep and what to discard or focus specifically on data that support or do not support a particular hypothesis. All data must be accounted for, even if they invalidate the hypothesis.

Applying the Scientific Method

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later module, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

Remember that a good scientific hypothesis is falsifiable, or capable of being shown to be incorrect. Recall from the introductory module that Sigmund Freud had lots of interesting ideas to explain various human behaviors (Figure 5). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Link to Learning

Why the scientific method is important for psychology.

The use of the scientific method is one of the main features that separates modern psychology from earlier philosophical inquiries about the mind. Compared to chemistry, physics, and other “natural sciences,” psychology has long been considered one of the “social sciences” because of the subjective nature of the things it seeks to study. Many of the concepts that psychologists are interested in—such as aspects of the human mind, behavior, and emotions—are subjective and cannot be directly measured. Psychologists often rely instead on behavioral observations and self-reported data, which are considered by some to be illegitimate or lacking in methodological rigor. Applying the scientific method to psychology, therefore, helps to standardize the approach to understanding its very different types of information.

The scientific method allows psychological data to be replicated and confirmed in many instances, under different circumstances, and by a variety of researchers. Through replication of experiments, new generations of psychologists can reduce errors and broaden the applicability of theories. It also allows theories to be tested and validated instead of simply being conjectures that could never be verified or falsified. All of this allows psychologists to gain a stronger understanding of how the human mind works.

Scientific articles published in journals and psychology papers written in the style of the American Psychological Association (i.e., in “APA style”) are structured around the scientific method. These papers include an Introduction, which introduces the background information and outlines the hypotheses; a Methods section, which outlines the specifics of how the experiment was conducted to test the hypothesis; a Results section, which includes the statistics that tested the hypothesis and state whether it was supported or not supported, and a Discussion and Conclusion, which state the implications of finding support for, or no support for, the hypothesis. Writing articles and papers that adhere to the scientific method makes it easy for future researchers to repeat the study and attempt to replicate the results.

Ethics in Research

Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, as you will read in the Tuskegee Syphilis Study, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound. This section presents how ethical considerations affect the design and implementation of research conducted today.

Research Involving Human Participants

Any experiment involving the participation of human subjects is governed by extensive, strict guidelines designed to ensure that the experiment does not result in harm. Any research institution that receives federal support for research involving human participants must have access to an institutional review board (IRB) . The IRB is a committee of individuals often made up of members of the institution’s administration, scientists, and community members (Figure 6). The purpose of the IRB is to review proposals for research that involves human participants. The IRB reviews these proposals with the principles mentioned above in mind, and generally, approval from the IRB is required in order for the experiment to proceed.

An institution’s IRB requires several components in any experiment it approves. For one, each participant must sign an informed consent form before they can participate in the experiment. An informed consent  form provides a written description of what participants can expect during the experiment, including potential risks and implications of the research. It also lets participants know that their involvement is completely voluntary and can be discontinued without penalty at any time. Furthermore, the informed consent guarantees that any data collected in the experiment will remain completely confidential. In cases where research participants are under the age of 18, the parents or legal guardians are required to sign the informed consent form.

While the informed consent form should be as honest as possible in describing exactly what participants will be doing, sometimes deception is necessary to prevent participants’ knowledge of the exact research question from affecting the results of the study. Deception involves purposely misleading experiment participants in order to maintain the integrity of the experiment, but not to the point where the deception could be considered harmful. For example, if we are interested in how our opinion of someone is affected by their attire, we might use deception in describing the experiment to prevent that knowledge from affecting participants’ responses. In cases where deception is involved, participants must receive a full debriefing  upon conclusion of the study—complete, honest information about the purpose of the experiment, how the data collected will be used, the reasons why deception was necessary, and information about how to obtain additional information about the study.

Dig Deeper: Ethics and the Tuskegee Syphilis Study

Unfortunately, the ethical guidelines that exist for research today were not always applied in the past. In 1932, poor, rural, black, male sharecroppers from Tuskegee, Alabama, were recruited to participate in an experiment conducted by the U.S. Public Health Service, with the aim of studying syphilis in black men (Figure 7). In exchange for free medical care, meals, and burial insurance, 600 men agreed to participate in the study. A little more than half of the men tested positive for syphilis, and they served as the experimental group (given that the researchers could not randomly assign participants to groups, this represents a quasi-experiment). The remaining syphilis-free individuals served as the control group. However, those individuals that tested positive for syphilis were never informed that they had the disease.

While there was no treatment for syphilis when the study began, by 1947 penicillin was recognized as an effective treatment for the disease. Despite this, no penicillin was administered to the participants in this study, and the participants were not allowed to seek treatment at any other facilities if they continued in the study. Over the course of 40 years, many of the participants unknowingly spread syphilis to their wives (and subsequently their children born from their wives) and eventually died because they never received treatment for the disease. This study was discontinued in 1972 when the experiment was discovered by the national press (Tuskegee University, n.d.). The resulting outrage over the experiment led directly to the National Research Act of 1974 and the strict ethical guidelines for research on humans described in this chapter. Why is this study unethical? How were the men who participated and their families harmed as a function of this research?

Learn more about the Tuskegee Syphilis Study on the CDC website .

Research Involving Animal Subjects

This does not mean that animal researchers are immune to ethical concerns. Indeed, the humane and ethical treatment of animal research subjects is a critical aspect of this type of research. Researchers must design their experiments to minimize any pain or distress experienced by animals serving as research subjects.

Whereas IRBs review research proposals that involve human participants, animal experimental proposals are reviewed by an Institutional Animal Care and Use Committee (IACUC) . An IACUC consists of institutional administrators, scientists, veterinarians, and community members. This committee is charged with ensuring that all experimental proposals require the humane treatment of animal research subjects. It also conducts semi-annual inspections of all animal facilities to ensure that the research protocols are being followed. No animal research project can proceed without the committee’s approval.

Introduction to Approaches to Research

• Differentiate between descriptive, correlational, and experimental research
• Explain the strengths and weaknesses of case studies, naturalistic observation, and surveys
• Describe the strength and weaknesses of archival research
• Compare longitudinal and cross-sectional approaches to research
• Explain what a correlation coefficient tells us about the relationship between variables
• Describe why correlation does not mean causation
• Describe the experimental process, including ways to control for bias
• Identify and differentiate between independent and dependent variables

Psychologists use descriptive, experimental, and correlational methods to conduct research. Descriptive, or qualitative, methods include the case study, naturalistic observation, surveys, archival research, longitudinal research, and cross-sectional research.

Experiments are conducted in order to determine cause-and-effect relationships. In ideal experimental design, the only difference between the experimental and control groups is whether participants are exposed to the experimental manipulation. Each group goes through all phases of the experiment, but each group will experience a different level of the independent variable: the experimental group is exposed to the experimental manipulation, and the control group is not exposed to the experimental manipulation. The researcher then measures the changes that are produced in the dependent variable in each group. Once data is collected from both groups, it is analyzed statistically to determine if there are meaningful differences between the groups.

When scientists passively observe and measure phenomena it is called correlational research. Here, psychologists do not intervene and change behavior, as they do in experiments. In correlational research, they identify patterns of relationships, but usually cannot infer what causes what. Importantly, with correlational research, you can examine only two variables at a time, no more and no less.

Watch It: More on Research

If you enjoy learning through lectures and want an interesting and comprehensive summary of this section, then click on the Youtube link to watch a lecture given by MIT Professor John Gabrieli . Start at the 30:45 minute mark  and watch through the end to hear examples of actual psychological studies and how they were analyzed. Listen for references to independent and dependent variables, experimenter bias, and double-blind studies. In the lecture, you’ll learn about breaking social norms, “WEIRD” research, why expectations matter, how a warm cup of coffee might make you nicer, why you should change your answer on a multiple choice test, and why praise for intelligence won’t make you any smarter.

You can view the transcript for “Lec 2 | MIT 9.00SC Introduction to Psychology, Spring 2011” here (opens in new window) .

Descriptive Research

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

The three main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research  goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. It aims to determine if one variable directly impacts and causes another. Correlational and experimental research both typically use hypothesis testing, whereas descriptive research does not.

Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in the text, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in very artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

The three main types of descriptive studies are, naturalistic observation, case studies, and surveys.

Naturalistic Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this module: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway (Figure 9).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall, for example, spent nearly five decades observing the behavior of chimpanzees in Africa (Figure 10). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

The greatest benefit of naturalistic observation is the validity, or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize  the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the module on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Case Studies

In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.

The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.

These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).

In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a tremendous amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.

If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 11). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population.

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this chapter: people don’t always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Think It Over

Archival research.

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

Longitudinal and Cross-Sectional Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research  is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.

Another approach is cross-sectional research . In cross-sectional research, a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead of observing a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals make them different from one another.

To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.

Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) (Figure 13).

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition  rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increases over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.

Correlational Research

Did you know that as sales in ice cream increase, so does the overall rate of crime? Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone? There is no question that a relationship exists between ice cream and crime (e.g., Harper, 2013), but it would be pretty foolish to decide that one thing actually caused the other to occur.

It is much more likely that both ice cream sales and crime rates are related to the temperature outside. When the temperature is warm, there are lots of people out of their houses, interacting with each other, getting annoyed with one another, and sometimes committing crimes. Also, when it is warm outside, we are more likely to seek a cool treat like ice cream. How do we determine if there is indeed a relationship between two things? And when there is a relationship, how can we discern whether it is attributable to coincidence or causation?

Correlation Does Not Indicate Causation

Correlational research is useful because it allows us to discover the strength and direction of relationships that exist between two variables. However, correlation is limited because establishing the existence of a relationship tells us little about cause and effect . While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable , is actually causing the systematic movement in our variables of interest. In the ice cream/crime rate example mentioned earlier, temperature is a confounding variable that could account for the relationship between the two variables.

Even when we cannot point to clear confounding variables, we should not assume that a correlation between two variables implies that one variable causes changes in another. This can be frustrating when a cause-and-effect relationship seems clear and intuitive. Think back to our discussion of the research done by the American Cancer Society and how their research projects were some of the first demonstrations of the link between smoking and cancer. It seems reasonable to assume that smoking causes cancer, but if we were limited to correlational research , we would be overstepping our bounds by making this assumption.

Unfortunately, people mistakenly make claims of causation as a function of correlations all the time. Such claims are especially common in advertisements and news stories. For example, recent research found that people who eat cereal on a regular basis achieve healthier weights than those who rarely eat cereal (Frantzen, Treviño, Echon, Garcia-Dominic, & DiMarco, 2013; Barton et al., 2005). Guess how the cereal companies report this finding. Does eating cereal really cause an individual to maintain a healthy weight, or are there other possible explanations, such as, someone at a healthy weight is more likely to regularly eat a healthy breakfast than someone who is obese or someone who avoids meals in an attempt to diet (Figure 15)? While correlational research is invaluable in identifying relationships among variables, a major limitation is the inability to establish causality. Psychologists want to make statements about cause and effect, but the only way to do that is to conduct an experiment to answer a research question. The next section describes how scientific experiments incorporate methods that eliminate, or control for, alternative explanations, which allow researchers to explore how changes in one variable cause changes in another variable.

Watch this clip from Freakonomics for an example of how correlation does  not  indicate causation.

You can view the transcript for “Correlation vs. Causality: Freakonomics Movie” here (opens in new window) .

Illusory Correlations

The temptation to make erroneous cause-and-effect statements based on correlational research is not the only way we tend to misinterpret data. We also tend to make the mistake of illusory correlations, especially with unsystematic observations. Illusory correlations , or false correlations, occur when people believe that relationships exist between two things when no such relationship exists. One well-known illusory correlation is the supposed effect that the moon’s phases have on human behavior. Many people passionately assert that human behavior is affected by the phase of the moon, and specifically, that people act strangely when the moon is full (Figure 16).

There is no denying that the moon exerts a powerful influence on our planet. The ebb and flow of the ocean’s tides are tightly tied to the gravitational forces of the moon. Many people believe, therefore, that it is logical that we are affected by the moon as well. After all, our bodies are largely made up of water. A meta-analysis of nearly 40 studies consistently demonstrated, however, that the relationship between the moon and our behavior does not exist (Rotton & Kelly, 1985). While we may pay more attention to odd behavior during the full phase of the moon, the rates of odd behavior remain constant throughout the lunar cycle.

Why are we so apt to believe in illusory correlations like this? Often we read or hear about them and simply accept the information as valid. Or, we have a hunch about how something works and then look for evidence to support that hunch, ignoring evidence that would tell us our hunch is false; this is known as confirmation bias . Other times, we find illusory correlations based on the information that comes most easily to mind, even if that information is severely limited. And while we may feel confident that we can use these relationships to better understand and predict the world around us, illusory correlations can have significant drawbacks. For example, research suggests that illusory correlations—in which certain behaviors are inaccurately attributed to certain groups—are involved in the formation of prejudicial attitudes that can ultimately lead to discriminatory behavior (Fiedler, 2004).

We all have a tendency to make illusory correlations from time to time. Try to think of an illusory correlation that is held by you, a family member, or a close friend. How do you think this illusory correlation came about and what can be done in the future to combat them?

Experiments

Causality: conducting experiments and using the data, experimental hypothesis.

In order to conduct an experiment, a researcher must have a specific hypothesis to be tested. As you’ve learned, hypotheses can be formulated either through direct observation of the real world or after careful review of previous research. For example, if you think that children should not be allowed to watch violent programming on television because doing so would cause them to behave more violently, then you have basically formulated a hypothesis—namely, that watching violent television programs causes children to behave more violently. How might you have arrived at this particular hypothesis? You may have younger relatives who watch cartoons featuring characters using martial arts to save the world from evildoers, with an impressive array of punching, kicking, and defensive postures. You notice that after watching these programs for a while, your young relatives mimic the fighting behavior of the characters portrayed in the cartoon (Figure 17).

These sorts of personal observations are what often lead us to formulate a specific hypothesis, but we cannot use limited personal observations and anecdotal evidence to rigorously test our hypothesis. Instead, to find out if real-world data supports our hypothesis, we have to conduct an experiment.

Designing an Experiment

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group  gets the experimental manipulation—that is, the treatment or variable being tested (in this case, violent TV images)—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

In our example of how violent television programming might affect violent behavior in children, we have the experimental group view violent television programming for a specified time and then measure their violent behavior. We measure the violent behavior in our control group after they watch nonviolent television programming for the same amount of time. It is important for the control group to be treated similarly to the experimental group, with the exception that the control group does not receive the experimental manipulation. Therefore, we have the control group watch non-violent television programming for the same amount of time as the experimental group.

We also need to precisely define, or operationalize, what is considered violent and nonviolent. An operational definition is a description of how we will measure our variables, and it is important in allowing others understand exactly how and what a researcher measures in a particular experiment. In operationalizing violent behavior, we might choose to count only physical acts like kicking or punching as instances of this behavior, or we also may choose to include angry verbal exchanges. Whatever we determine, it is important that we operationalize violent behavior in such a way that anyone who hears about our study for the first time knows exactly what we mean by violence. This aids peoples’ ability to interpret our data as well as their capacity to repeat our experiment should they choose to do so.

Once we have operationalized what is considered violent television programming and what is considered violent behavior from our experiment participants, we need to establish how we will run our experiment. In this case, we might have participants watch a 30-minute television program (either violent or nonviolent, depending on their group membership) before sending them out to a playground for an hour where their behavior is observed and the number and type of violent acts is recorded.

Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which child was in which group, it might influence how much attention they paid to each child’s behavior as well as how they interpreted that behavior. By being blind to which child is in which group, we protect against those biases. This situation is a single-blind study , meaning that one of the groups (participants) are unaware as to which group they are in (experiment or control group) while the researcher who developed the experiment knows which participants are in each group.

In a double-blind study , both the researchers and the participants are blind to group assignments. Why would a researcher want to run a study where no one knows who is in which group? Because by doing so, we can control for both experimenter and participant expectations. If you are familiar with the phrase placebo effect, you already have some idea as to why this is an important consideration. The placebo effect occurs when people’s expectations or beliefs influence or determine their experience in a given situation. In other words, simply expecting something to happen can actually make it happen.

The placebo effect is commonly described in terms of testing the effectiveness of a new medication. Imagine that you work in a pharmaceutical company, and you think you have a new drug that is effective in treating depression. To demonstrate that your medication is effective, you run an experiment with two groups: The experimental group receives the medication, and the control group does not. But you don’t want participants to know whether they received the drug or not.

Why is that? Imagine that you are a participant in this study, and you have just taken a pill that you think will improve your mood. Because you expect the pill to have an effect, you might feel better simply because you took the pill and not because of any drug actually contained in the pill—this is the placebo effect.

To make sure that any effects on mood are due to the drug and not due to expectations, the control group receives a placebo (in this case a sugar pill). Now everyone gets a pill, and once again neither the researcher nor the experimental participants know who got the drug and who got the sugar pill. Any differences in mood between the experimental and control groups can now be attributed to the drug itself rather than to experimenter bias or participant expectations (Figure 18).

Independent and Dependent Variables

In a research experiment, we strive to study whether changes in one thing cause changes in another. To achieve this, we must pay attention to two important variables, or things that can be changed, in any experimental study: the independent variable and the dependent variable. An independent variable is manipulated or controlled by the experimenter. In a well-designed experimental study, the independent variable is the only important difference between the experimental and control groups. In our example of how violent television programs affect children’s display of violent behavior, the independent variable is the type of program—violent or nonviolent—viewed by participants in the study (Figure 19). A dependent variable is what the researcher measures to see how much effect the independent variable had. In our example, the dependent variable is the number of violent acts displayed by the experimental participants.

We expect that the dependent variable will change as a function of the independent variable. In other words, the dependent variable depends on the independent variable. A good way to think about the relationship between the independent and dependent variables is with this question: What effect does the independent variable have on the dependent variable? Returning to our example, what effect does watching a half hour of violent television programming or nonviolent television programming have on the number of incidents of physical aggression displayed on the playground?

Selecting and Assigning Experimental Participants

Now that our study is designed, we need to obtain a sample of individuals to include in our experiment. Our study involves human participants so we need to determine who to include. Participants  are the subjects of psychological research, and as the name implies, individuals who are involved in psychological research actively participate in the process. Often, psychological research projects rely on college students to serve as participants. In fact, the vast majority of research in psychology subfields has historically involved students as research participants (Sears, 1986; Arnett, 2008). But are college students truly representative of the general population? College students tend to be younger, more educated, more liberal, and less diverse than the general population. Although using students as test subjects is an accepted practice, relying on such a limited pool of research participants can be problematic because it is difficult to generalize findings to the larger population.

Our hypothetical experiment involves children, and we must first generate a sample of child participants. Samples are used because populations are usually too large to reasonably involve every member in our particular experiment (Figure 20). If possible, we should use a random sample   (there are other types of samples, but for the purposes of this section, we will focus on random samples). A random sample is a subset of a larger population in which every member of the population has an equal chance of being selected. Random samples are preferred because if the sample is large enough we can be reasonably sure that the participating individuals are representative of the larger population. This means that the percentages of characteristics in the sample—sex, ethnicity, socioeconomic level, and any other characteristics that might affect the results—are close to those percentages in the larger population.

In our example, let’s say we decide our population of interest is fourth graders. But all fourth graders is a very large population, so we need to be more specific; instead we might say our population of interest is all fourth graders in a particular city. We should include students from various income brackets, family situations, races, ethnicities, religions, and geographic areas of town. With this more manageable population, we can work with the local schools in selecting a random sample of around 200 fourth graders who we want to participate in our experiment.

In summary, because we cannot test all of the fourth graders in a city, we want to find a group of about 200 that reflects the composition of that city. With a representative group, we can generalize our findings to the larger population without fear of our sample being biased in some way.

Now that we have a sample, the next step of the experimental process is to split the participants into experimental and control groups through random assignment. With random assignment , all participants have an equal chance of being assigned to either group. There is statistical software that will randomly assign each of the fourth graders in the sample to either the experimental or the control group.

Random assignment is critical for sound experimental design. With sufficiently large samples, random assignment makes it unlikely that there are systematic differences between the groups. So, for instance, it would be very unlikely that we would get one group composed entirely of males, a given ethnic identity, or a given religious ideology. This is important because if the groups were systematically different before the experiment began, we would not know the origin of any differences we find between the groups: Were the differences preexisting, or were they caused by manipulation of the independent variable? Random assignment allows us to assume that any differences observed between experimental and control groups result from the manipulation of the independent variable.

Issues to Consider

While experiments allow scientists to make cause-and-effect claims, they are not without problems. True experiments require the experimenter to manipulate an independent variable, and that can complicate many questions that psychologists might want to address. For instance, imagine that you want to know what effect sex (the independent variable) has on spatial memory (the dependent variable). Although you can certainly look for differences between males and females on a task that taps into spatial memory, you cannot directly control a person’s sex. We categorize this type of research approach as quasi-experimental and recognize that we cannot make cause-and-effect claims in these circumstances.

Experimenters are also limited by ethical constraints. For instance, you would not be able to conduct an experiment designed to determine if experiencing abuse as a child leads to lower levels of self-esteem among adults. To conduct such an experiment, you would need to randomly assign some experimental participants to a group that receives abuse, and that experiment would be unethical.

Introduction to Statistical Thinking

Psychologists use statistics to assist them in analyzing data, and also to give more precise measurements to describe whether something is statistically significant. Analyzing data using statistics enables researchers to find patterns, make claims, and share their results with others. In this section, you’ll learn about some of the tools that psychologists use in statistical analysis.

• Define reliability and validity
• Describe the importance of distributional thinking and the role of p-values in statistical inference
• Describe the role of random sampling and random assignment in drawing cause-and-effect conclusions
• Describe the basic structure of a psychological research article

Interpreting Experimental Findings

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this experiment 100 times, we would expect to find the same results at least 95 times out of 100.

The greatest strength of experiments is the ability to assert that any significant differences in the findings are caused by the independent variable. This occurs because random selection, random assignment, and a design that limits the effects of both experimenter bias and participant expectancy should create groups that are similar in composition and treatment. Therefore, any difference between the groups is attributable to the independent variable, and now we can finally make a causal statement. If we find that watching a violent television program results in more violent behavior than watching a nonviolent program, we can safely say that watching violent television programs causes an increase in the display of violent behavior.

Reporting Research

When psychologists complete a research project, they generally want to share their findings with other scientists. The American Psychological Association (APA) publishes a manual detailing how to write a paper for submission to scientific journals. Unlike an article that might be published in a magazine like Psychology Today, which targets a general audience with an interest in psychology, scientific journals generally publish peer-reviewed journal articles aimed at an audience of professionals and scholars who are actively involved in research themselves.

A peer-reviewed journal article is read by several other scientists (generally anonymously) with expertise in the subject matter. These peer reviewers provide feedback—to both the author and the journal editor—regarding the quality of the draft. Peer reviewers look for a strong rationale for the research being described, a clear description of how the research was conducted, and evidence that the research was conducted in an ethical manner. They also look for flaws in the study’s design, methods, and statistical analyses. They check that the conclusions drawn by the authors seem reasonable given the observations made during the research. Peer reviewers also comment on how valuable the research is in advancing the discipline’s knowledge. This helps prevent unnecessary duplication of research findings in the scientific literature and, to some extent, ensures that each research article provides new information. Ultimately, the journal editor will compile all of the peer reviewer feedback and determine whether the article will be published in its current state (a rare occurrence), published with revisions, or not accepted for publication.

Peer review provides some degree of quality control for psychological research. Poorly conceived or executed studies can be weeded out, and even well-designed research can be improved by the revisions suggested. Peer review also ensures that the research is described clearly enough to allow other scientists to replicate it, meaning they can repeat the experiment using different samples to determine reliability. Sometimes replications involve additional measures that expand on the original finding. In any case, each replication serves to provide more evidence to support the original research findings. Successful replications of published research make scientists more apt to adopt those findings, while repeated failures tend to cast doubt on the legitimacy of the original article and lead scientists to look elsewhere. For example, it would be a major advancement in the medical field if a published study indicated that taking a new drug helped individuals achieve a healthy weight without changing their diet. But if other scientists could not replicate the results, the original study’s claims would be questioned.

Dig Deeper: The Vaccine-Autism Myth and the Retraction of Published Studies

Some scientists have claimed that routine childhood vaccines cause some children to develop autism, and, in fact, several peer-reviewed publications published research making these claims. Since the initial reports, large-scale epidemiological research has suggested that vaccinations are not responsible for causing autism and that it is much safer to have your child vaccinated than not. Furthermore, several of the original studies making this claim have since been retracted.

A published piece of work can be rescinded when data is called into question because of falsification, fabrication, or serious research design problems. Once rescinded, the scientific community is informed that there are serious problems with the original publication. Retractions can be initiated by the researcher who led the study, by research collaborators, by the institution that employed the researcher, or by the editorial board of the journal in which the article was originally published. In the vaccine-autism case, the retraction was made because of a significant conflict of interest in which the leading researcher had a financial interest in establishing a link between childhood vaccines and autism (Offit, 2008). Unfortunately, the initial studies received so much media attention that many parents around the world became hesitant to have their children vaccinated (Figure 21). For more information about how the vaccine/autism story unfolded, as well as the repercussions of this story, take a look at Paul Offit’s book, Autism’s False Prophets: Bad Science, Risky Medicine, and the Search for a Cure.

Reliability and Validity

Dig deeper:  everyday connection: how valid is the sat.

Standardized tests like the SAT are supposed to measure an individual’s aptitude for a college education, but how reliable and valid are such tests? Research conducted by the College Board suggests that scores on the SAT have high predictive validity for first-year college students’ GPA (Kobrin, Patterson, Shaw, Mattern, & Barbuti, 2008). In this context, predictive validity refers to the test’s ability to effectively predict the GPA of college freshmen. Given that many institutions of higher education require the SAT for admission, this high degree of predictive validity might be comforting.

However, the emphasis placed on SAT scores in college admissions has generated some controversy on a number of fronts. For one, some researchers assert that the SAT is a biased test that places minority students at a disadvantage and unfairly reduces the likelihood of being admitted into a college (Santelices & Wilson, 2010). Additionally, some research has suggested that the predictive validity of the SAT is grossly exaggerated in how well it is able to predict the GPA of first-year college students. In fact, it has been suggested that the SAT’s predictive validity may be overestimated by as much as 150% (Rothstein, 2004). Many institutions of higher education are beginning to consider de-emphasizing the significance of SAT scores in making admission decisions (Rimer, 2008).

In 2014, College Board president David Coleman expressed his awareness of these problems, recognizing that college success is more accurately predicted by high school grades than by SAT scores. To address these concerns, he has called for significant changes to the SAT exam (Lewin, 2014).

Statistical Significance

Does drinking coffee actually increase your life expectancy? A recent study (Freedman, Park, Abnet, Hollenbeck, & Sinha, 2012) found that men who drank at least six cups of coffee a day also had a 10% lower chance of dying (women’s chances were 15% lower) than those who drank none. Does this mean you should pick up or increase your own coffee habit? We will explore these results in more depth in the next section about drawing conclusions from statistics. Modern society has become awash in studies such as this; you can read about several such studies in the news every day.

Conducting such a study well, and interpreting the results of such studies requires understanding basic ideas of statistics , the science of gaining insight from data. Key components to a statistical investigation are:

• Planning the study: Start by asking a testable research question and deciding how to collect data. For example, how long was the study period of the coffee study? How many people were recruited for the study, how were they recruited, and from where? How old were they? What other variables were recorded about the individuals? Were changes made to the participants’ coffee habits during the course of the study?
• Examining the data: What are appropriate ways to examine the data? What graphs are relevant, and what do they reveal? What descriptive statistics can be calculated to summarize relevant aspects of the data, and what do they reveal? What patterns do you see in the data? Are there any individual observations that deviate from the overall pattern, and what do they reveal? For example, in the coffee study, did the proportions differ when we compared the smokers to the non-smokers?
• Inferring from the data: What are valid statistical methods for drawing inferences “beyond” the data you collected? In the coffee study, is the 10%–15% reduction in risk of death something that could have happened just by chance?
• Drawing conclusions: Based on what you learned from your data, what conclusions can you draw? Who do you think these conclusions apply to? (Were the people in the coffee study older? Healthy? Living in cities?) Can you draw a cause-and-effect conclusion about your treatments? (Are scientists now saying that the coffee drinking is the cause of the decreased risk of death?)

Notice that the numerical analysis (“crunching numbers” on the computer) comprises only a small part of overall statistical investigation. In this section, you will see how we can answer some of these questions and what questions you should be asking about any statistical investigation you read about.

Distributional Thinking

When data are collected to address a particular question, an important first step is to think of meaningful ways to organize and examine the data. Let’s take a look at an example.

Example 1 : Researchers investigated whether cancer pamphlets are written at an appropriate level to be read and understood by cancer patients (Short, Moriarty, & Cooley, 1995). Tests of reading ability were given to 63 patients. In addition, readability level was determined for a sample of 30 pamphlets, based on characteristics such as the lengths of words and sentences in the pamphlet. The results, reported in terms of grade levels, are displayed in Figure 23.

• Data vary . More specifically, values of a variable (such as reading level of a cancer patient or readability level of a cancer pamphlet) vary.
• Analyzing the pattern of variation, called the distribution of the variable, often reveals insights.

Addressing the research question of whether the cancer pamphlets are written at appropriate levels for the cancer patients requires comparing the two distributions. A naïve comparison might focus only on the centers of the distributions. Both medians turn out to be ninth grade, but considering only medians ignores the variability and the overall distributions of these data. A more illuminating approach is to compare the entire distributions, for example with a graph, as in Figure 24.

Figure 24 makes clear that the two distributions are not well aligned at all. The most glaring discrepancy is that many patients (17/63, or 27%, to be precise) have a reading level below that of the most readable pamphlet. These patients will need help to understand the information provided in the cancer pamphlets. Notice that this conclusion follows from considering the distributions as a whole, not simply measures of center or variability, and that the graph contrasts those distributions more immediately than the frequency tables.

Finding Significance in Data

Even when we find patterns in data, often there is still uncertainty in various aspects of the data. For example, there may be potential for measurement errors (even your own body temperature can fluctuate by almost 1°F over the course of the day). Or we may only have a “snapshot” of observations from a more long-term process or only a small subset of individuals from the population of interest. In such cases, how can we determine whether patterns we see in our small set of data is convincing evidence of a systematic phenomenon in the larger process or population? Let’s take a look at another example.

Example 2 : In a study reported in the November 2007 issue of Nature , researchers investigated whether pre-verbal infants take into account an individual’s actions toward others in evaluating that individual as appealing or aversive (Hamlin, Wynn, & Bloom, 2007). In one component of the study, 10-month-old infants were shown a “climber” character (a piece of wood with “googly” eyes glued onto it) that could not make it up a hill in two tries. Then the infants were shown two scenarios for the climber’s next try, one where the climber was pushed to the top of the hill by another character (“helper”), and one where the climber was pushed back down the hill by another character (“hinderer”). The infant was alternately shown these two scenarios several times. Then the infant was presented with two pieces of wood (representing the helper and the hinderer characters) and asked to pick one to play with.

The researchers found that of the 16 infants who made a clear choice, 14 chose to play with the helper toy. One possible explanation for this clear majority result is that the helping behavior of the one toy increases the infants’ likelihood of choosing that toy. But are there other possible explanations? What about the color of the toy? Well, prior to collecting the data, the researchers arranged so that each color and shape (red square and blue circle) would be seen by the same number of infants. Or maybe the infants had right-handed tendencies and so picked whichever toy was closer to their right hand?

Well, prior to collecting the data, the researchers arranged it so half the infants saw the helper toy on the right and half on the left. Or, maybe the shapes of these wooden characters (square, triangle, circle) had an effect? Perhaps, but again, the researchers controlled for this by rotating which shape was the helper toy, the hinderer toy, and the climber. When designing experiments, it is important to control for as many variables as might affect the responses as possible. It is beginning to appear that the researchers accounted for all the other plausible explanations. But there is one more important consideration that cannot be controlled—if we did the study again with these 16 infants, they might not make the same choices. In other words, there is some randomness inherent in their selection process.

Maybe each infant had no genuine preference at all, and it was simply “random luck” that led to 14 infants picking the helper toy. Although this random component cannot be controlled, we can apply a probability model to investigate the pattern of results that would occur in the long run if random chance were the only factor.

If the infants were equally likely to pick between the two toys, then each infant had a 50% chance of picking the helper toy. It’s like each infant tossed a coin, and if it landed heads, the infant picked the helper toy. So if we tossed a coin 16 times, could it land heads 14 times? Sure, it’s possible, but it turns out to be very unlikely. Getting 14 (or more) heads in 16 tosses is about as likely as tossing a coin and getting 9 heads in a row. This probability is referred to as a p-value . The p-value represents the likelihood that experimental results happened by chance. Within psychology, the most common standard for p-values is “p < .05”. What this means is that there is less than a 5% probability that the results happened just by random chance, and therefore a 95% probability that the results reflect a meaningful pattern in human psychology. We call this statistical significance .

So, in the study above, if we assume that each infant was choosing equally, then the probability that 14 or more out of 16 infants would choose the helper toy is found to be 0.0021. We have only two logical possibilities: either the infants have a genuine preference for the helper toy, or the infants have no preference (50/50) and an outcome that would occur only 2 times in 1,000 iterations happened in this study. Because this p-value of 0.0021 is quite small, we conclude that the study provides very strong evidence that these infants have a genuine preference for the helper toy.

If we compare the p-value to some cut-off value, like 0.05, we see that the p=value is smaller. Because the p-value is smaller than that cut-off value, then we reject the hypothesis that only random chance was at play here. In this case, these researchers would conclude that significantly more than half of the infants in the study chose the helper toy, giving strong evidence of a genuine preference for the toy with the helping behavior.

Drawing Conclusions from Statistics

Generalizability.

One limitation to the study mentioned previously about the babies choosing the “helper” toy is that the conclusion only applies to the 16 infants in the study. We don’t know much about how those 16 infants were selected. Suppose we want to select a subset of individuals (a sample ) from a much larger group of individuals (the population ) in such a way that conclusions from the sample can be generalized to the larger population. This is the question faced by pollsters every day.

Example 3 : The General Social Survey (GSS) is a survey on societal trends conducted every other year in the United States. Based on a sample of about 2,000 adult Americans, researchers make claims about what percentage of the U.S. population consider themselves to be “liberal,” what percentage consider themselves “happy,” what percentage feel “rushed” in their daily lives, and many other issues. The key to making these claims about the larger population of all American adults lies in how the sample is selected. The goal is to select a sample that is representative of the population, and a common way to achieve this goal is to select a r andom sample  that gives every member of the population an equal chance of being selected for the sample. In its simplest form, random sampling involves numbering every member of the population and then using a computer to randomly select the subset to be surveyed. Most polls don’t operate exactly like this, but they do use probability-based sampling methods to select individuals from nationally representative panels.

In 2004, the GSS reported that 817 of 977 respondents (or 83.6%) indicated that they always or sometimes feel rushed. This is a clear majority, but we again need to consider variation due to random sampling . Fortunately, we can use the same probability model we did in the previous example to investigate the probable size of this error. (Note, we can use the coin-tossing model when the actual population size is much, much larger than the sample size, as then we can still consider the probability to be the same for every individual in the sample.) This probability model predicts that the sample result will be within 3 percentage points of the population value (roughly 1 over the square root of the sample size, the margin of error. A statistician would conclude, with 95% confidence, that between 80.6% and 86.6% of all adult Americans in 2004 would have responded that they sometimes or always feel rushed.

The key to the margin of error is that when we use a probability sampling method, we can make claims about how often (in the long run, with repeated random sampling) the sample result would fall within a certain distance from the unknown population value by chance (meaning by random sampling variation) alone. Conversely, non-random samples are often suspect to bias, meaning the sampling method systematically over-represents some segments of the population and under-represents others. We also still need to consider other sources of bias, such as individuals not responding honestly. These sources of error are not measured by the margin of error.

Cause and Effect

In many research studies, the primary question of interest concerns differences between groups. Then the question becomes how were the groups formed (e.g., selecting people who already drink coffee vs. those who don’t). In some studies, the researchers actively form the groups themselves. But then we have a similar question—could any differences we observe in the groups be an artifact of that group-formation process? Or maybe the difference we observe in the groups is so large that we can discount a “fluke” in the group-formation process as a reasonable explanation for what we find?

Example 4 : A psychology study investigated whether people tend to display more creativity when they are thinking about intrinsic (internal) or extrinsic (external) motivations (Ramsey & Schafer, 2002, based on a study by Amabile, 1985). The subjects were 47 people with extensive experience with creative writing. Subjects began by answering survey questions about either intrinsic motivations for writing (such as the pleasure of self-expression) or extrinsic motivations (such as public recognition). Then all subjects were instructed to write a haiku, and those poems were evaluated for creativity by a panel of judges. The researchers conjectured beforehand that subjects who were thinking about intrinsic motivations would display more creativity than subjects who were thinking about extrinsic motivations. The creativity scores from the 47 subjects in this study are displayed in Figure 26, where higher scores indicate more creativity.

In this example, the key question is whether the type of motivation affects creativity scores. In particular, do subjects who were asked about intrinsic motivations tend to have higher creativity scores than subjects who were asked about extrinsic motivations?

Figure 26 reveals that both motivation groups saw considerable variability in creativity scores, and these scores have considerable overlap between the groups. In other words, it’s certainly not always the case that those with extrinsic motivations have higher creativity than those with intrinsic motivations, but there may still be a statistical tendency in this direction. (Psychologist Keith Stanovich (2013) refers to people’s difficulties with thinking about such probabilistic tendencies as “the Achilles heel of human cognition.”)

The mean creativity score is 19.88 for the intrinsic group, compared to 15.74 for the extrinsic group, which supports the researchers’ conjecture. Yet comparing only the means of the two groups fails to consider the variability of creativity scores in the groups. We can measure variability with statistics using, for instance, the standard deviation: 5.25 for the extrinsic group and 4.40 for the intrinsic group. The standard deviations tell us that most of the creativity scores are within about 5 points of the mean score in each group. We see that the mean score for the intrinsic group lies within one standard deviation of the mean score for extrinsic group. So, although there is a tendency for the creativity scores to be higher in the intrinsic group, on average, the difference is not extremely large.

We again want to consider possible explanations for this difference. The study only involved individuals with extensive creative writing experience. Although this limits the population to which we can generalize, it does not explain why the mean creativity score was a bit larger for the intrinsic group than for the extrinsic group. Maybe women tend to receive higher creativity scores? Here is where we need to focus on how the individuals were assigned to the motivation groups. If only women were in the intrinsic motivation group and only men in the extrinsic group, then this would present a problem because we wouldn’t know if the intrinsic group did better because of the different type of motivation or because they were women. However, the researchers guarded against such a problem by randomly assigning the individuals to the motivation groups. Like flipping a coin, each individual was just as likely to be assigned to either type of motivation. Why is this helpful? Because this random assignment  tends to balance out all the variables related to creativity we can think of, and even those we don’t think of in advance, between the two groups. So we should have a similar male/female split between the two groups; we should have a similar age distribution between the two groups; we should have a similar distribution of educational background between the two groups; and so on. Random assignment should produce groups that are as similar as possible except for the type of motivation, which presumably eliminates all those other variables as possible explanations for the observed tendency for higher scores in the intrinsic group.

But does this always work? No, so by “luck of the draw” the groups may be a little different prior to answering the motivation survey. So then the question is, is it possible that an unlucky random assignment is responsible for the observed difference in creativity scores between the groups? In other words, suppose each individual’s poem was going to get the same creativity score no matter which group they were assigned to, that the type of motivation in no way impacted their score. Then how often would the random-assignment process alone lead to a difference in mean creativity scores as large (or larger) than 19.88 – 15.74 = 4.14 points?

We again want to apply to a probability model to approximate a p-value , but this time the model will be a bit different. Think of writing everyone’s creativity scores on an index card, shuffling up the index cards, and then dealing out 23 to the extrinsic motivation group and 24 to the intrinsic motivation group, and finding the difference in the group means. We (better yet, the computer) can repeat this process over and over to see how often, when the scores don’t change, random assignment leads to a difference in means at least as large as 4.41. Figure 27 shows the results from 1,000 such hypothetical random assignments for these scores.

Only 2 of the 1,000 simulated random assignments produced a difference in group means of 4.41 or larger. In other words, the approximate p-value is 2/1000 = 0.002. This small p-value indicates that it would be very surprising for the random assignment process alone to produce such a large difference in group means. Therefore, as with Example 2, we have strong evidence that focusing on intrinsic motivations tends to increase creativity scores, as compared to thinking about extrinsic motivations.

Notice that the previous statement implies a cause-and-effect relationship between motivation and creativity score; is such a strong conclusion justified? Yes, because of the random assignment used in the study. That should have balanced out any other variables between the two groups, so now that the small p-value convinces us that the higher mean in the intrinsic group wasn’t just a coincidence, the only reasonable explanation left is the difference in the type of motivation. Can we generalize this conclusion to everyone? Not necessarily—we could cautiously generalize this conclusion to individuals with extensive experience in creative writing similar the individuals in this study, but we would still want to know more about how these individuals were selected to participate.

Statistical thinking involves the careful design of a study to collect meaningful data to answer a focused research question, detailed analysis of patterns in the data, and drawing conclusions that go beyond the observed data. Random sampling is paramount to generalizing results from our sample to a larger population, and random assignment is key to drawing cause-and-effect conclusions. With both kinds of randomness, probability models help us assess how much random variation we can expect in our results, in order to determine whether our results could happen by chance alone and to estimate a margin of error.

So where does this leave us with regard to the coffee study mentioned previously (the Freedman, Park, Abnet, Hollenbeck, & Sinha, 2012 found that men who drank at least six cups of coffee a day had a 10% lower chance of dying (women 15% lower) than those who drank none)? We can answer many of the questions:

• This was a 14-year study conducted by researchers at the National Cancer Institute.
• The results were published in the June issue of the New England Journal of Medicine , a respected, peer-reviewed journal.
• The study reviewed coffee habits of more than 402,000 people ages 50 to 71 from six states and two metropolitan areas. Those with cancer, heart disease, and stroke were excluded at the start of the study. Coffee consumption was assessed once at the start of the study.
• About 52,000 people died during the course of the study.
• People who drank between two and five cups of coffee daily showed a lower risk as well, but the amount of reduction increased for those drinking six or more cups.
• The sample sizes were fairly large and so the p-values are quite small, even though percent reduction in risk was not extremely large (dropping from a 12% chance to about 10%–11%).
• Whether coffee was caffeinated or decaffeinated did not appear to affect the results.
• This was an observational study, so no cause-and-effect conclusions can be drawn between coffee drinking and increased longevity, contrary to the impression conveyed by many news headlines about this study. In particular, it’s possible that those with chronic diseases don’t tend to drink coffee.

This study needs to be reviewed in the larger context of similar studies and consistency of results across studies, with the constant caution that this was not a randomized experiment. Whereas a statistical analysis can still “adjust” for other potential confounding variables, we are not yet convinced that researchers have identified them all or completely isolated why this decrease in death risk is evident. Researchers can now take the findings of this study and develop more focused studies that address new questions.

Explore these outside resources to learn more about applied statistics:

• Video about p-values:  P-Value Extravaganza
• Interactive web applets for teaching and learning statistics
• Inter-university Consortium for Political and Social Research  where you can find and analyze data.
• The Consortium for the Advancement of Undergraduate Statistics
• Find a recent research article in your field and answer the following: What was the primary research question? How were individuals selected to participate in the study? Were summary results provided? How strong is the evidence presented in favor or against the research question? Was random assignment used? Summarize the main conclusions from the study, addressing the issues of statistical significance, statistical confidence, generalizability, and cause and effect. Do you agree with the conclusions drawn from this study, based on the study design and the results presented?
• Is it reasonable to use a random sample of 1,000 individuals to draw conclusions about all U.S. adults? Explain why or why not.

How to Read Research

In this course and throughout your academic career, you’ll be reading journal articles (meaning they were published by experts in a peer-reviewed journal) and reports that explain psychological research. It’s important to understand the format of these articles so that you can read them strategically and understand the information presented. Scientific articles vary in content or structure, depending on the type of journal to which they will be submitted. Psychological articles and many papers in the social sciences follow the writing guidelines and format dictated by the American Psychological Association (APA). In general, the structure follows: abstract, introduction, methods, results, discussion, and references.

• Abstract : the abstract is the concise summary of the article. It summarizes the most important features of the manuscript, providing the reader with a global first impression on the article. It is generally just one paragraph that explains the experiment as well as a short synopsis of the results.
• Introduction : this section provides background information about the origin and purpose of performing the experiment or study. It reviews previous research and presents existing theories on the topic.
• Method : this section covers the methodologies used to investigate the research question, including the identification of participants , procedures , and  materials  as well as a description of the actual procedure . It should be sufficiently detailed to allow for replication.
• Results : the results section presents key findings of the research, including reference to indicators of statistical significance.
• Discussion : this section provides an interpretation of the findings, states their significance for current research, and derives implications for theory and practice. Alternative interpretations for findings are also provided, particularly when it is not possible to conclude for the directionality of the effects. In the discussion, authors also acknowledge the strengths and limitations/weaknesses of the study and offer concrete directions about for future research.

Watch this 3-minute video for an explanation on how to read scholarly articles. Look closely at the example article shared just before the two minute mark.

https://digitalcommons.coastal.edu/kimbel-library-instructional-videos/9/

Practice identifying these key components in the following experiment: Food-Induced Emotional Resonance Improves Emotion Recognition.

In this chapter, you learned to

• define and apply the scientific method to psychology
• describe the strengths and weaknesses of descriptive, experimental, and correlational research
• define the basic elements of a statistical investigation

Putting It Together: Psychological Research

Psychologists use the scientific method to examine human behavior and mental processes. Some of the methods you learned about include descriptive, experimental, and correlational research designs.

Watch the CrashCourse video to review the material you learned, then read through the following examples and see if you can come up with your own design for each type of study.

You can view the transcript for “Psychological Research: Crash Course Psychology #2” here (opens in new window).

Case Study: a detailed analysis of a particular person, group, business, event, etc. This approach is commonly used to to learn more about rare examples with the goal of describing that particular thing.

• Ted Bundy was one of America’s most notorious serial killers who murdered at least 30 women and was executed in 1989. Dr. Al Carlisle evaluated Bundy when he was first arrested and conducted a psychological analysis of Bundy’s development of his sexual fantasies merging into reality (Ramsland, 2012). Carlisle believes that there was a gradual evolution of three processes that guided his actions: fantasy, dissociation, and compartmentalization (Ramsland, 2012). Read   Imagining Ted Bundy  (http://goo.gl/rGqcUv) for more information on this case study.

Naturalistic Observation : a researcher unobtrusively collects information without the participant’s awareness.

• Drain and Engelhardt (2013) observed six nonverbal children with autism’s evoked and spontaneous communicative acts. Each of the children attended a school for children with autism and were in different classes. They were observed for 30 minutes of each school day. By observing these children without them knowing, they were able to see true communicative acts without any external influences.

Survey : participants are asked to provide information or responses to questions on a survey or structure assessment.

• Educational psychologists can ask students to report their grade point average and what, if anything, they eat for breakfast on an average day. A healthy breakfast has been associated with better academic performance (Digangi’s 1999).
• Anderson (1987) tried to find the relationship between uncomfortably hot temperatures and aggressive behavior, which was then looked at with two studies done on violent and nonviolent crime. Based on previous research that had been done by Anderson and Anderson (1984), it was predicted that violent crimes would be more prevalent during the hotter time of year and the years in which it was hotter weather in general. The study confirmed this prediction.

Longitudinal Study: researchers   recruit a sample of participants and track them for an extended period of time.

• In a study of a representative sample of 856 children Eron and his colleagues (1972) found that a boy’s exposure to media violence at age eight was significantly related to his aggressive behavior ten years later, after he graduated from high school.

Cross-Sectional Study:  researchers gather participants from different groups (commonly different ages) and look for differences between the groups.

• In 1996, Russell surveyed people of varying age groups and found that people in their 20s tend to report being more lonely than people in their 70s.

Correlational Design:  two different variables are measured to determine whether there is a relationship between them.

• Thornhill et al. (2003) had people rate how physically attractive they found other people to be. They then had them separately smell t-shirts those people had worn (without knowing which clothes belonged to whom) and rate how good or bad their body oder was. They found that the more attractive someone was the more pleasant their body order was rated to be.
• Clinical psychologists can test a new pharmaceutical treatment for depression by giving some patients the new pill and others an already-tested one to see which is the more effective treatment.

American Cancer Society. (n.d.). History of the cancer prevention studies. Retrieved from http://www.cancer.org/research/researchtopreventcancer/history-cancer-prevention-study

American Psychological Association. (2009). Publication Manual of the American Psychological Association (6th ed.). Washington, DC: Author.

American Psychological Association. (n.d.). Research with animals in psychology. Retrieved from https://www.apa.org/research/responsible/research-animals.pdf

Arnett, J. (2008). The neglected 95%: Why American psychology needs to become less American. American Psychologist, 63(7), 602–614.

Barton, B. A., Eldridge, A. L., Thompson, D., Affenito, S. G., Striegel-Moore, R. H., Franko, D. L., . . . Crockett, S. J. (2005). The relationship of breakfast and cereal consumption to nutrient intake and body mass index: The national heart, lung, and blood institute growth and health study. Journal of the American Dietetic Association, 105(9), 1383–1389. Retrieved from http://dx.doi.org/10.1016/j.jada.2005.06.003

Chwalisz, K., Diener, E., & Gallagher, D. (1988). Autonomic arousal feedback and emotional experience: Evidence from the spinal cord injured. Journal of Personality and Social Psychology, 54, 820–828.

Dominus, S. (2011, May 25). Could conjoined twins share a mind? New York Times Sunday Magazine. Retrieved from http://www.nytimes.com/2011/05/29/magazine/could-conjoined-twins-share-a-mind.html?_r=5&hp&

Fanger, S. M., Frankel, L. A., & Hazen, N. (2012). Peer exclusion in preschool children’s play: Naturalistic observations in a playground setting. Merrill-Palmer Quarterly, 58, 224–254.

Fiedler, K. (2004). Illusory correlation. In R. F. Pohl (Ed.), Cognitive illusions: A handbook on fallacies and biases in thinking, judgment and memory (pp. 97–114). New York, NY: Psychology Press.

Frantzen, L. B., Treviño, R. P., Echon, R. M., Garcia-Dominic, O., & DiMarco, N. (2013). Association between frequency of ready-to-eat cereal consumption, nutrient intakes, and body mass index in fourth- to sixth-grade low-income minority children. Journal of the Academy of Nutrition and Dietetics, 113(4), 511–519.

Harper, J. (2013, July 5). Ice cream and crime: Where cold cuisine and hot disputes intersect. The Times-Picaune. Retrieved from http://www.nola.com/crime/index.ssf/2013/07/ice_cream_and_crime_where_hot.html

Jenkins, W. J., Ruppel, S. E., Kizer, J. B., Yehl, J. L., & Griffin, J. L. (2012). An examination of post 9-11 attitudes towards Arab Americans. North American Journal of Psychology, 14, 77–84.

Jones, J. M. (2013, May 13). Same-sex marriage support solidifies above 50% in U.S. Gallup Politics. Retrieved from http://www.gallup.com/poll/162398/sex-marriage-support-solidifies-above.aspx

Kobrin, J. L., Patterson, B. F., Shaw, E. J., Mattern, K. D., & Barbuti, S. M. (2008). Validity of the SAT for predicting first-year college grade point average (Research Report No. 2008-5). Retrieved from https://research.collegeboard.org/sites/default/files/publications/2012/7/researchreport-2008-5-validity-sat-predicting-first-year-college-grade-point-average.pdf

Lewin, T. (2014, March 5). A new SAT aims to realign with schoolwork. New York Times. Retreived from http://www.nytimes.com/2014/03/06/education/major-changes-in-sat-announced-by-college-board.html.

Lowry, M., Dean, K., & Manders, K. (2010). The link between sleep quantity and academic performance for the college student. Sentience: The University of Minnesota Undergraduate Journal of Psychology, 3(Spring), 16–19. Retrieved from http://www.psych.umn.edu/sentience/files/SENTIENCE_Vol3.pdf

McKie, R. (2010, June 26). Chimps with everything: Jane Goodall’s 50 years in the jungle. The Guardian. Retrieved from http://www.theguardian.com/science/2010/jun/27/jane-goodall-chimps-africa-interview

Offit, P. (2008). Autism’s false prophets: Bad science, risky medicine, and the search for a cure. New York: Columbia University Press.

Perkins, H. W., Haines, M. P., & Rice, R. (2005). Misperceiving the college drinking norm and related problems: A nationwide study of exposure to prevention information, perceived norms and student alcohol misuse. J. Stud. Alcohol, 66(4), 470–478.

Rimer, S. (2008, September 21). College panel calls for less focus on SATs. The New York Times. Retrieved from http://www.nytimes.com/2008/09/22/education/22admissions.html?_r=0

Rothstein, J. M. (2004). College performance predictions and the SAT. Journal of Econometrics, 121, 297–317.

Rotton, J., & Kelly, I. W. (1985). Much ado about the full moon: A meta-analysis of lunar-lunacy research. Psychological Bulletin, 97(2), 286–306. doi:10.1037/0033-2909.97.2.286

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grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing

well-developed set of ideas that propose an explanation for observed phenomena

(plural: hypotheses) tentative and testable statement about the relationship between two or more variables

an experiment must be replicable by another researcher

implies that a theory should enable us to make predictions about future events

able to be disproven by experimental results

implies that all data must be considered when evaluating a hypothesis

committee of administrators, scientists, and community members that reviews proposals for research involving human participants

process of informing a research participant about what to expect during an experiment, any risks involved, and the implications of the research, and then obtaining the person’s consent to participate

purposely misleading experiment participants in order to maintain the integrity of the experiment

when an experiment involved deception, participants are told complete and truthful information about the experiment at its conclusion

committee of administrators, scientists, veterinarians, and community members that reviews proposals for research involving non-human animals

research studies that do not test specific relationships between variables

research investigating the relationship between two or more variables

research method that uses hypothesis testing to make inferences about how one variable impacts and causes another

observation of behavior in its natural setting

inferring that the results for a sample apply to the larger population

when observations may be skewed to align with observer expectations

measure of agreement among observers on how they record and classify a particular event

observational research study focusing on one or a few people

list of questions to be answered by research participants—given as paper-and-pencil questionnaires, administered electronically, or conducted verbally—allowing researchers to collect data from a large number of people

subset of individuals selected from the larger population

overall group of individuals that the researchers are interested in

method of research using past records or data sets to answer various research questions, or to search for interesting patterns or relationships

studies in which the same group of individuals is surveyed or measured repeatedly over an extended period of time

compares multiple segments of a population at a single time

reduction in number of research participants as some drop out of the study over time

relationship between two or more variables; when two variables are correlated, one variable changes as the other does

number from -1 to +1, indicating the strength and direction of the relationship between variables, and usually represented by r

two variables change in the same direction, both becoming either larger or smaller

two variables change in different directions, with one becoming larger as the other becomes smaller; a negative correlation is not the same thing as no correlation

changes in one variable cause the changes in the other variable; can be determined only through an experimental research design

unanticipated outside factor that affects both variables of interest, often giving the false impression that changes in one variable causes changes in the other variable, when, in actuality, the outside factor causes changes in both variables

seeing relationships between two things when in reality no such relationship exists

tendency to ignore evidence that disproves ideas or beliefs

group designed to answer the research question; experimental manipulation is the only difference between the experimental and control groups, so any differences between the two are due to experimental manipulation rather than chance

serves as a basis for comparison and controls for chance factors that might influence the results of the study—by holding such factors constant across groups so that the experimental manipulation is the only difference between groups

description of what actions and operations will be used to measure the dependent variables and manipulate the independent variables

researcher expectations skew the results of the study

experiment in which the researcher knows which participants are in the experimental group and which are in the control group

experiment in which both the researchers and the participants are blind to group assignments

people's expectations or beliefs influencing or determining their experience in a given situation

variable that is influenced or controlled by the experimenter; in a sound experimental study, the independent variable is the only important difference between the experimental and control group

variable that the researcher measures to see how much effect the independent variable had

subjects of psychological research

subset of a larger population in which every member of the population has an equal chance of being selected

method of experimental group assignment in which all participants have an equal chance of being assigned to either group

consistency and reproducibility of a given result

accuracy of a given result in measuring what it is designed to measure

determines how likely any difference between experimental groups is due to chance

statistical probability that represents the likelihood that experimental results happened by chance

Psychological Science is the scientific study of mind, brain, and behavior. We will explore what it means to be human in this class. It has never been more important for us to understand what makes people tick, how to evaluate information critically, and the importance of history. Psychology can also help you in your future career; indeed, there are very little jobs out there with no human interaction!

Because psychology is a science, we analyze human behavior through the scientific method. There are several ways to investigate human phenomena, such as observation, experiments, and more. We will discuss the basics, pros and cons of each! We will also dig deeper into the important ethical guidelines that psychologists must follow in order to do research. Lastly, we will briefly introduce ourselves to statistics, the language of scientific research. While reading the content in these chapters, try to find examples of material that can fit with the themes of the course.

To get us started:

• The study of the mind moved away Introspection to reaction time studies as we learned more about empiricism
• Psychologists work in careers outside of the typical "clinician" role. We advise in human factors, education, policy, and more!
• While completing an observation study, psychologists will work to aggregate common themes to explain the behavior of the group (sample) as a whole. In doing so, we still allow for normal variation from the group!
• The IRB and IACUC are important in ensuring ethics are maintained for both human and animal subjects

Psychological Science: Understanding Human Behavior Copyright © by Karenna Malavanti is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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1.2 Scientific Research in Psychology

Learning objectives.

• Describe a general model of scientific research in psychology and give specific examples that fit the model.
• Explain who conducts scientific research in psychology and why they do it.
• Distinguish between basic research and applied research.

A Model of Scientific Research in Psychology

Figure 1.2 “A Simple Model of Scientific Research in Psychology” presents a more specific model of scientific research in psychology. The researcher (who more often than not is really a small group of researchers) formulates a research question, conducts a study designed to answer the question, analyzes the resulting data, draws conclusions about the answer to the question, and publishes the results so that they become part of the research literature. Because the research literature is one of the primary sources of new research questions, this process can be thought of as a cycle. New research leads to new questions, which lead to new research, and so on. Figure 1.2 “A Simple Model of Scientific Research in Psychology” also indicates that research questions can originate outside of this cycle either with informal observations or with practical problems that need to be solved. But even in these cases, the researcher would start by checking the research literature to see if the question had already been answered and to refine it based on what previous research had already found.

Figure 1.2 A Simple Model of Scientific Research in Psychology

The research by Mehl and his colleagues is described nicely by this model. Their question—whether women are more talkative than men—was suggested to them both by people’s stereotypes and by published claims about the relative talkativeness of women and men. When they checked the research literature, however, they found that this question had not been adequately addressed in scientific studies. They conducted a careful empirical study, analyzed the results (finding very little difference between women and men), and published their work so that it became part of the research literature. The publication of their article is not the end of the story, however, because their work suggests many new questions (about the reliability of the result, about potential cultural differences, etc.) that will likely be taken up by them and by other researchers inspired by their work.

Scientific research has confirmed that cell phone use impairs a variety of driving behaviors.

Indiana Stan – CC BY-NC 2.0.

As another example, consider that as cell phones became more widespread during the 1990s, people began to wonder whether, and to what extent, cell phone use had a negative effect on driving. Many psychologists decided to tackle this question scientifically (Collet, Guillot, & Petit, 2010). It was clear from previously published research that engaging in a simple verbal task impairs performance on a perceptual or motor task carried out at the same time, but no one had studied the effect specifically of cell phone use on driving. Under carefully controlled conditions, these researchers compared people’s driving performance while using a cell phone with their performance while not using a cell phone, both in the lab and on the road. They found that people’s ability to detect road hazards, reaction time, and control of the vehicle were all impaired by cell phone use. Each new study was published and became part of the growing research literature on this topic.

Who Conducts Scientific Research in Psychology?

Scientific research in psychology is generally conducted by people with doctoral degrees (usually the doctor of philosophy [PhD] ) and master’s degrees in psychology and related fields, often supported by research assistants with bachelor’s degrees or other relevant training. Some of them work for government agencies (e.g., the National Institute of Mental Health), for nonprofit organizations (e.g., the American Cancer Society), or in the private sector (e.g., in product development). However, the majority of them are college and university faculty, who often collaborate with their graduate and undergraduate students. Although some researchers are trained and licensed as clinicians—especially those who conduct research in clinical psychology—the majority are not. Instead, they have expertise in one or more of the many other subfields of psychology: behavioral neuroscience, cognitive psychology, developmental psychology, personality psychology, social psychology, and so on. Doctoral-level researchers might be employed to conduct research full-time or, like many college and university faculty members, to conduct research in addition to teaching classes and serving their institution and community in other ways.

Of course, people also conduct research in psychology because they enjoy the intellectual and technical challenges involved and the satisfaction of contributing to scientific knowledge of human behavior. You might find that you enjoy the process too. If so, your college or university might offer opportunities to get involved in ongoing research as either a research assistant or a participant. Of course, you might find that you do not enjoy the process of conducting scientific research in psychology. But at least you will have a better understanding of where scientific knowledge in psychology comes from, an appreciation of its strengths and limitations, and an awareness of how it can be applied to solve practical problems in psychology and everyday life.

Scientific Psychology Blogs

A fun and easy way to follow current scientific research in psychology is to read any of the many excellent blogs devoted to summarizing and commenting on new findings. Among them are the following:

• Child-Psych, http://www.child-psych.org
• PsyBlog, http://www.spring.org.uk
• Research Digest, http://bps-research-digest.blogspot.com
• Social Psychology Eye, http://socialpsychologyeye.wordpress.com
• We’re Only Human, http://www.psychologicalscience.org/onlyhuman

You can also browse to http://www.researchblogging.org , select psychology as your topic, and read entries from a wide variety of blogs.

The Broader Purposes of Scientific Research in Psychology

People have always been curious about the natural world, including themselves and their behavior. (In fact, this is probably why you are studying psychology in the first place.) Science grew out of this natural curiosity and has become the best way to achieve detailed and accurate knowledge. Keep in mind that most of the phenomena and theories that fill psychology textbooks are the products of scientific research. In a typical introductory psychology textbook, for example, one can learn about specific cortical areas for language and perception, principles of classical and operant conditioning, biases in reasoning and judgment, and people’s surprising tendency to obey authority. And scientific research continues because what we know right now only scratches the surface of what we can know.

Scientific research is often classified as being either basic or applied. Basic research in psychology is conducted primarily for the sake of achieving a more detailed and accurate understanding of human behavior, without necessarily trying to address any particular practical problem. The research of Mehl and his colleagues falls into this category. Applied research is conducted primarily to address some practical problem. Research on the effects of cell phone use on driving, for example, was prompted by safety concerns and has led to the enactment of laws to limit this practice. Although the distinction between basic and applied research is convenient, it is not always clear-cut. For example, basic research on sex differences in talkativeness could eventually have an effect on how marriage therapy is practiced, and applied research on the effect of cell phone use on driving could produce new insights into basic processes of perception, attention, and action.

Key Takeaways

• Research in psychology can be described by a simple cyclical model. A research question based on the research literature leads to an empirical study, the results of which are published and become part of the research literature.
• Scientific research in psychology is conducted mainly by people with doctoral degrees in psychology and related fields, most of whom are college and university faculty members. They do so for professional and for personal reasons, as well as to contribute to scientific knowledge about human behavior.
• Basic research is conducted to learn about human behavior for its own sake, and applied research is conducted to solve some practical problem. Both are valuable, and the distinction between the two is not always clear-cut.
• Practice: Find a description of an empirical study in a professional journal or in one of the scientific psychology blogs. Then write a brief description of the research in terms of the cyclical model presented here. One or two sentences for each part of the cycle should suffice.
• Practice: Based on your own experience or on things you have already learned about psychology, list three basic research questions and three applied research questions of interest to you.

Collet, C., Guillot, A., & Petit, C. (2010). Phoning while driving I: A review of epidemiological, psychological, behavioural and physiological studies. Ergonomics, 53 , 589–601.

Research Methods in Psychology Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Study types and definitions. These are searchable by methodology in PsycInfo.

Types of Research Studies

These terms and definitions were taken from the apa style jars supplemental glossary  (2019)., click on each type of research study to see a research article example..

• Case-control (clinical trial) study a research investigation that evaluates the effects of one or more health-related interventions on health outcomes by prospectively and randomly assigning people to experimental conditions. Also known as "case-control design," "case-clinical trial," "case-referent study."
• Cohort study a nonexperimental design that can be prospective or retrospective. In a prospective cohort study, participants are enrolled before the potential causal event has occurred. In a retrospective cohort study, the study begins after the dependent event occurs. See also "longitudinal study."
• Cross-sectional design study an experimental design in which multiple measures are collected over a period of time from two or more groups of different ages (birth cohorts), ethnicities, or other factos. These designs combine aspects of longitudinal design and cohort-sequential design.
• Literature review a narrative summary and evaluation of the findings or theories within a literature base. Also known as "narrative literature review."
• Longitudinal study a study that involves the observation of a variable or group of variables in the same cases or individuals using the same set of measurements (or attributes) over a period of time (i.e., at multiple times or occasions). A longitudinal study that evaluates a group of randomly chosen individuals is referred to as a panel study, whereas a longitudinal study that evaluates a group of individuals possessing some common characteristic (usually age) is referred to as a cohort study. This multiple observational structure may be combined with almost any other research design—ones with and without experimental manipulations, randomized clinical trials, or any other study type. Also known as "longitudinal research," "longitudinal design."
• Prospective sampling (cohort) a sampling method in which cases are selected for inclusion in experiments or other research based on their exposure to a risk factor. Participants are then followed to see if a condition of interest develops.
• Qualitatiive research study approaches to research used to generate knowledge about human experience and/or action, including social processes. These research methods typically produce descriptive (non-numerical) data, such as observations of behavior or personal accounts of experiences. The goal of gathering qualitative data is to examine how individuals perceive the world from different vantage points. Also known as "qualitative design," "qualitative inquiry," "qualitative method," "qualitative study." more... less... Qualitative methods share four central characteristics: Involve the analysis of natural language and other forms of human expression rather than the translation of meaning into numbersCentralize an iterative process in which data are analyzed and meanings are generated in a circular and self-correcting process of checking and refining findingsSeek to present findings in a manner that emphasizes the study's context and situation in timeRecursively combine inquiry with methods that require researchers' reflexivity (i.e., self-examination) about their influence upon the research process.
• Qualitative meta analysis study a form of inquiry in which qualitative research findings about a process or experience are aggregated or integrated across research studies. Aims can involve synthesizing qualitative findings across primary studies, generating new theoretical or conceptual models, identifying gaps in research, or generating new questions.
• Quantitative research study approaches to research in which observed outcomes are numerically represented. These research methods rely on measuring variables using a numerical system, analyzing measurements using statistical models, and reporting relationships and associations among the studied variables. The goal of gathering quantitative data is to understand, describe, and predict the nature of a phenomenon, particularly through the development of models and theories. Also known as "quantitative design," "quantitative inquiry," "quantitative method," "quantitative study."
• Quantitative Meta analysis a technique for synthesizing the results of multiple studies of a phenomenon by combining the effect size estimates from each study into a single estimate of the combined effect size or into a distribution of effect sizes. Effect size estimates from individual studies are the inputs to the analyses. Although meta-analyses are ideally suited for summarizing a body of literature in terms of impact, limitations, and implications, they are limited by having no required minimum number of studies or participants. Information of potential interest may also be missing from the original research reports upon which the procedure must rely.
• Randomized controlled (clinical) trial an experimental design in which patients are randomly assigned to a group that will receive an experimental treatment, such as a new drug, or to one that will receive a comparison treatment, a standard-of-care treatment, or a placebo. The random assignment occurs after recruitment and assessment of eligibility but before the intervention. There may be multiple experimental and comparison groups, but each patient is assigned to one group only.
• Retrospective cohort study (sampling) the study begins after the dependent event occurs; a technique in which participants or cases from the general population are selected for inclusion in experiments or other research based on their previous exposure to a risk factor or the completion of some particular process. Participants are then examined in the present to see if a particular condition or state exists, often in comparison to others who were not exposed to the risk or who did not complete the particular process.

Please consult the following sources for more information on these types of studies and terminology related to the studies.

• APA Style JARS Supplemental Glossary This webpage provides supplemental information on the terms used in APA Style JARS. This glossary is meant to supplement Chapter 3 of the Publication Manual of the American Psychological Association, Seventh Edition. It is not an exhaustive list of all terms employed in quantitative, qualitative, or mixed methods research, nor does it include all possible definitions for each term; definitions in addition to or different from those reported in this glossary may be found in other sources.
• APA Dictionary of Psychology More than 25,000 authoritative entries across 90 subfields of psychology.
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5 types of psychological research that everyone should know.

Psychology is a varied field. At any time, there is a range of psychology research methods that can be used in a variety of circumstances. 

Which method to use depends on the research conducted and the research subjects involved. Often, more than one psychology research method will be used, especially when validating previous research.

Here are five popular psychology research methods and some of their most successful applications.

Naturalistic observation

As the name suggests, this psychology research method involves observing something in its natural environment. 

Naturalistic observation is often used when the research subject’s environment can’t be recreated in a lab setting. So, this research method is commonly used when the subjects being studied are in classrooms or workplaces. Another common use of naturalistic observation is to support the validity of other psychology research methods.

One of the major disadvantages of naturalistic observation is that people tend to behave differently when being observed. This drawback was highlighted by the Hawthorne studies which set out to determine whether workers were more productive in brighter light. 

Using naturalistic observation, the researchers found that workers more productive as the light got brighter – until the study stopped. Even though the lights stayed up, without the attention of the researchers, workers went back to their old, low production ways.

If the first question on a survey was, ‘have you ever answered a survey?’, chances are we would get 100 per cent positive results. Surveys are one of the most popular ways to find out what people think and one of the most common research methods in psychology.

The key to lifting the survey from a marketing tool to psychology research method is the random sample . This is a subset of the entire population being studied, chosen at random, to represent the general population better.

A random sample needs the best chance of demonstrating the entire population. To do that, it must be weighted to have the same characteristics of that population. For example, if you wanted to research postgraduate students who read blog posts, you wouldn’t include postgraduate students who don’t read blog posts in your random sample.

Experimental methods

Experimental psychology research methods start with a hypothesis that the researcher hopes to prove, attained  by manipulating one independent variable while measuring the result on another dependent variable. 

Ideally, these experiments will be conducted in a lab, where other variables are controlled. If that’s possible, then the experiment can be reproduced in other labs for validation. 

Both naturalistic observation and surveys, as well as other psychology research methods, can be used as part of an experimental method.

Experimental research can also be conducted in the field, with a limited ability to control other variables. The Good Samaritan experiment of 1973 used this method to determine how likely people are to stop and help when they pass an injured person. 

To control outside variables, they told the volunteers in their random sample that the study was about religious education and vocations. They gave them a survey then asked them to walk to another building to deliver a talk. It was on their way that they encountered an injured person – where only 40 per cent of them stopped to help.

Correlational Studies

When it’s not possible to run an experiment, correlational studies can be an effective psychology research method. Correlational studies also make use of naturalistic observation and surveys, as well as archival research. The idea here is to look at two or more variables to identify a relationship between them.

The most important thing to remember is that correlation does not always equal causation. Correlational studies make it possible to study variables that we can’t control, but they don’t provide enough information to establish a cause-and-effect relationship. For this reason, correlational studies are often used in the early stages of a research project.

Correlational studies had a massive impact on every kitchen in the United Kingdom during the 1960s. In the decade prior, ‘town gas’ for cooking was produced locally from coal and delivered by regional gas companies. At the same time, the suicide rate was rising, and it was increasing faster for women than men.

A researcher by the name of Sainsbury identified a relationship between the suicides and ‘town gas’ which contained poisonous carbon monoxide. In this case, correlation was found to be causation.

Throughout the 1960s a massive operation was undertaken to replace ‘town gas’ with natural gas across the United Kingdom. Natural gas has no poisonous carbon monoxide. 

In ten years, the suicide rate from carbon monoxide poisoning dropped by around 80 per cent, while the overall suicide rate dropped by about 30 per cent.

All of these psychology research methods can be used as part of a case study , which focuses on one individual or a group – usually over a long period of time. Because only one case is involved, it’s difficult to extrapolate this type of research to broader populations. It also raises ethical issues around the long-term participation of those involved.

When Henry Molaison lost the ability to create new memories after a botched operation to cure epilepsy, he became a case study for over 100 psychologists and neurologists. Suzanne Corkin was one neurologist who spent 46 years working with Molaison until his death in 2008. When Henry died, he donated his brain to research. Corkin describes viewing the ‘tofu-like’ object for the first time with a mix of fascination and human loss for a dear friend.

Before her death in 2016, Corkin was accused of unethical practices during her case study that included shredding source material and not revealing Henry’s pre-existing conditions. This highlights the risk of bias with case study research. Researchers are at risk of bias as they come to know their research subjects – and because they invest so much of their time and effort into the project.

To help you avoid such a predicament, JCU’s Graduate Diploma of Psychology (Bridging) provides a deep understanding of the ethical issues around this and other study methods.

Learn more about our online postgraduate courses . Get in touch with our Enrolment team on 1300 535 919.

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Psychologenie

An Introduction to the Types Of Psychological Research Methods

The types of research methods in psychology are diverse, and here we provide you with an overview of the ways in which these methods are utilized.

Research is central to the field of psychology, without which no advances can be made, and no results or theories concluded. Because the field is so diverse and studies are based primarily on the function and effect of various factors on the human mind, several methods of research have been designed to help us narrow down a study and help draw a conclusion from it. Research is conducted by studying only one group, by studying multiple groups and correlating the results, by conducting experiments, and by the means of surveys, to arrive at answers. In some cases, one method of research must be used to supplement the other, in order to attain conclusive results. So what are the types of research methods used in this diverse field? Let’s take a look.

Types of Research Methods in Psychology

In any of the following methods, while the subjects/participants may be the same, the method of executing research may vary considerably. Psychological research can be divided into quantitative research (that is conducted by collecting data and through statistical analysis) and qualitative research (that is conducted by carrying out studies in natural settings, without any quantitative methods). The following methods of psychological research fall into both categories.

A case study is conducted by observing one participant (human being)/subject (animal), or a group of participants or subjects in maximum detail. For instance, if research wanted to be conducted on the understanding of language in animals, any one animal who had already been exposed to such an environment where it was spoken to in a particular language would be observed, and then its comprehension of this language would be much understood. Moreover, by thoroughly studying one case, a lot of conclusions may be drawn by this method, based on which further research may be carried out. The only con of this method of psychological research is that generalizing these results may be difficult because of the in-depth study of only one subject. What is applicable to one subject may not be applicable to another subject, and results may vary. As such, concrete conclusions cannot be drawn by this psychological research method. A case study is a method of qualitative research.

Survey/Questionnaire

Questionnaires are given to a group of people who are required to answer questions that have been designed to understand their thought process, attitudes, values, or any other factor that is to be studied. For instance, considering that this is a common research method used particularly in the field of social psychology, this method will allow researchers to analyze the thinking patterns of a specific group of people in relation to the society they belong to. Questionnaires provide somewhat conclusive results when they are directed toward a specific group of people (say all women, all men, all upper class, or classified based on any one such factor). This group then becomes a sample, which is a representative of people belonging to these groups. However, it should also be noted that in order to understand diverse views regarding a particular (social) concept, it is important to pick out a random group of people, who are then participants of a random sample. The benefit of using a questionnaire is that it enables the researcher to generalize results at a better level than does a case study. It also provides a window to the diverse viewpoints that may exist among a general group. However, this very factor is a great disadvantage as unless a majority in a particular pattern is not seen, every other response may be dismissed as an exception. Moreover, the way people tend to comprehend a particular question is different, which is when responses to these questions may also change.

Correlation

Correlation is a measure of the relation between an independent variable and a dependent variable. For instance, if psychologists were to study the relation between stress and lack of sleep, we can point out that stress is the independent variable, while lack of sleep is the variable dependent on stress. So you can develop a thesis that says the greater the stress level, the more difficult it is for people to get quality sleep. This would be a case of positive correlation, because as the intensity of one variable increases, so does that of the other. On the other hand, in a case of negative correlation, the value of one variable decreases as that of the other increases. As such, if your study were to be on the number of hours spent playing video games on student grades, you would assume that as kids spend more time playing video games, their grades worsen. This is an example of negative correlation. Carrying out research based on correlation helps us conclude our assumptions. For instance, we know that stress can cause mental disturbance and affect sleep, which is when we decide to carry out research and understand the intensity of this effect. On the negative side, research conducted through correlation does not allow us to specifically establish the cause behind the situation. For instance, when we assume that playing video games affects children’s grades, we do not take into account the other factors that may be contributing to poor grades, such as family environment, lack of interest in studies, or the inability to retain large chunks of information, leading to poor grades. Therefore, the cause and relation effect cannot be established with this method.

Filling the gap that correlation leaves behind, by conducting experiments we can understand the cause and effect relation between any two variables. As such, to understand whether it is really the number of hours spent playing video games that is causing poor grades, controlled experiments may be carried out where children are made to play video games for a certain number of hours every day, and their grades are be monitored over a period of days. By taking into consideration this hypothesis, and establishing results to prove whether or not it is true is what is achieved by experimentation. Experiments are usually carried out among varied groups of subjects or participants. These groups are called treatment groups (where participants are being manipulated to study the effects of this manipulation) and controlled groups (where participants are not manipulated in order to draw a comparison between the controlled and treatment groups). This is perhaps the best method of research as it helps us establish results after carrying out experimentation, unlike the aforementioned methods. The disadvantage of this method lies in the fact that every variable or factor cannot be controlled and manipulated thereby affecting the final result. Moreover, an experiment can help establish only one cause and effect relationship at a time, because every variable is controlled.

Psychological research is also termed based on the time it takes to carry out research. For instance, these are popular research methods in developmental psychology, specifically known as cross-sectional research and longitudinal research . The former refers to research that is carried out at one point in time where data, variables, and all other necessary elements are available at the same point, whereas longitudinal research is carried out over a period of time where data is gathered over this time and variables are studied thereafter or at the same time.

We can say that one research method may be more accurate than the other, but it cannot be established that any one method is completely accurate. However, results obtained in a majority can help provide conclusive insight into the research. Psychological research and the methods used are vast. This overview should have given you a fair idea of how the process is carried out to obtain results.

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The Basic Types Of Research Methods Used In Psychology

Psychology is an extremely wide field made up of a variety of areas. It is therefore unsurprising that psychology research is conducted in a number of ways. This article will briefly outline some of the basic types of methods used in psychology research of all types, and also present some examples of these methods.

Case studies

Case studies, which we wrote about recently , are the first type of research method we will describe here. A case study involves examining one person’s specific situation, either with or without any intervention from the researcher(s). For example, a case study might investigate one person with a rare disease and their reaction to an experimental treatment. Case studies can also examine multiple people, though typically not enough for any effect to be demonstrated.

Bloch-Elkouby et al. (2019) is a recent example of a case study in psychology.

Correlational studies

Correlational studies examine the relationships among different variables between different groups without any sort of experimental intervention. For example, a correlational study might investigate differences between people who grew up watching TV a lot and people who grew up without watching TV a lot. In such a case, the researchers would not have intervened in any way, but simply surveyed people who had different prior experiences. Correlational studies are good for certain situations (as one example, you would not want to experimentally impose an abusive childhood on a participant), though it is harder to ascribe any results to the difference being examined, since no controlled experiment was conducted.

Matthews et al. (2018) is a recent example of a correlational study in psychology.

Experimental studies

Experimental studies are the ones that are most likely to come to mind when one thinks of a “psychology study”. An experimental study examines the relationships among different variables between different groups with some experimental intervention. For example, an experimental study might assign participants into two groups (let us say, with one group drinking tea and one group drinking coffee), and examine the differences between these two groups. Generally, in experimental studies, the researchers will attempt to ensure that the participants in the two groups are similar, so that any results can be ascribed to the experimental intervention.

Lee et al. (2019) is a recent example of an experimental study in psychology.

Meta-analyses/reviews

Finally, meta-analyses/reviews generally do not involve original research, as they instead survey a large number of prior studies. For example, a review might examine 50 different studies that have previously examined the effects of playing video games in an attempt to synthesize all of the different results that have been obtained. Meta-analyses/reviews are excellent ways to overview a topic, but it is always a good idea to look at the original studies being discussed to verify that the results are being described accurately.

Kozhuharova et al. (2019) is an example of a meta-analysis/review.

Wrapping up

These four basic types of research methods are all useful in different situations, and they are all crucial aspects of psychology research. However, some of these methods are more appropriate for certain research questions than others. When designing a study, it is important to consider the nature of the question of interest to select the best option with which to investigate that question.

Bloch-Elkouby, S., Eubanks, C.F., Knopf, L., Gorman, B.S., Muran, J.C. (2019). The Difficult Task of Assessing and Interpreting Treatment Deterioration: An Evidence-Based Case Study. Frontiers in Psychology, 10(1), 1180. doi: 10.3389/fpsyg.2019.01180.

Kozhuharova, P., Dickson, H., Tully, J., Blackwood, N. (2019). Impaired processing of threat in psychopathy: A systematic review and meta-analysis of factorial data in male offender populations. PLoS One, 14(10), e0224455. doi: 10.1371/journal.pone.0224455.

Lee, D.J., Jung, H., Loui, P. (2019). Attention Modulates Electrophysical Responses to Simultaneous Music and Language Syntax Processing. Brain Sciences, 9(11), E305. doi: 10.3390/brainsci9110305.

Matthews, E.B., Stanhope, V., Choy-Brown, M., Doherty, M. (2018). Do Providers Know What They Do Not Know? A Correlational Study of Knowledge Acquisition and Person-Centered Care. Community Mental Health Journal, 54(5), 514-520. doi: 10.1007/s10597-017-0216-6.

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Six research-tested ways to study better

Psychology’s latest insights for preparing students for their next exams.

• Learning and Memory

Many students are missing a lesson in a key area that can help guarantee their success: how to study effectively. 

It’s common for students to prepare for exams by re-reading class notes and cramming textbook chapters—study techniques that hinge on the assumption that memories are like recording devices that can play back memories during an exam. “But the storage and retrieval operations of human memory differ from recording devices in almost every way possible,” says psychology professor Robert Bjork, PhD, co-director of the Learning and Forgetting Lab at University of California, Los Angeles. 

What does help our brains retain information? Study strategies that require the brain to work to remember information—rather than passively reviewing material. 

Bjork coined the term “desirable difficulty” to describe this concept, and psychologists are homing in on exactly how students can develop techniques to maximize the cognitive benefits of their study time.  

Here are six research-tested strategies from psychology educators. 

1. Remember and repeat

Study methods that involve remembering information more than once—known as repeated retrieval practice—are ideal because each time a memory is recovered, it becomes more accessible in the future, explains Jeffrey Karpicke, PhD, a psychology researcher at Purdue University in Indiana who studies human learning and memory. 

The benefits of this technique were evident when Karpicke conducted a study in which students attempted to learn a list of foreign language words. Participants learned the words in one of four ways: 

• Studying the list once.
• Studying until they had successfully recalled each word once.
• Studying until they had successfully recalled each word three times consecutively.
• Studying until they had recalled each word three times spaced throughout the 30-minute learning session. 

In the last condition, the students would move on to other words after correctly recalling a word once, then recall it again after practicing other words.

A week later, the researchers tested the students on the words and discovered that participants who had practiced with repeated spaced retrieval—the last condition—far outperformed the other groups. Students in this group remembered 80% of the words, compared to 30% for those who had recalled the information three times in a row—known as massed retrieval practice—or once. The first group, which involved no recall, remembered the words less than 1% of the time ( Journal of Experimental Psychology: Learning, Memory, and Cognition , Vol. 37, No. 5, 2011).

Many students assume that recalling something they’ve learned once is proof that they’ve memorized it. But, says Karpicke, just because you can retrieve a fact in a study session doesn’t mean you will remember it later on a test. “Just a few repeated retrievals can produce significant effects, and it’s best to do this in a spaced fashion.” 

2. Adapt your favorite strategies

Other research finds support for online flashcard programs, such as Study Stack or Chegg, to practice retrieving information—as long as students continue retesting themselves in the days leading up to the test, says John Dunlosky, PhD, who studies self-regulated learning at Kent State University in Ohio. For flashcards with single-word answers, the evidence suggests that thinking of the answer is effective, but for longer responses like definitions, students should type, write down, or say aloud the answers, Dunlosky says. If the answer is incorrect, then study the correct one and practice again later in the study session. “They should continue doing that until they are correct, and then repeat the process in a couple more days,” he says. 

Concept mapping — a diagram that depicts relationships between concepts—is another well-known learning technique that has become popular, but cognitive psychology researchers caution students to use this strategy only if they try to create a map with the book closed. Karpicke demonstrated this in a study in which students studied topics by creating concept maps or by writing notes in two different conditions: with an open textbook or with the textbook closed. With the closed textbook, they were recalling as much as they could remember. One week later, the students took an exam that tested their knowledge of the material, and students who had practiced retrieving the information with the book closed had better performances ( Journal of Educational Psychology , Vol. 106, No. 3, 2014).

“Concept maps can be useful, as long as students engage in retrieval practice while using this strategy,” Karpicke says. 

3. Quiz yourself

Students should also take advantage of quizzes—from teachers, in textbooks or apps like Quizlet—to refine their ability to retain and recall information. It works even if students answer incorrectly on these quizzes, says Oregon State University psychology professor Regan Gurung, PhD. “Even the process of trying and failing is better than not trying at all,” he says. “Just attempting to retrieve something helps you solidify it in your memory.”

Gurung investigated different approaches to using quizzes in nine introductory psychology courses throughout the country. In the study, the researchers worked with instructors who agreed to participate in different conditions. Some required students to complete chapter quizzes once while others required them to take each quiz multiple times. Also, some students were told to complete all the chapter quizzes by one deadline before the exam, while others were expected to space their quizzes by meeting deadlines throughout the course. The students who spaced their quizzes and took them multiple times fared the best on the class exams ( Applied Cognitive Psychology , Vol. 33, No. 5, 2019).

Although trying and failing on practice quizzes may be an effective study strategy, psychology professor Nate Kornell, PhD, of Williams College in Massachusetts, was skeptical that students would choose to learn this way because many people inherently do not like getting things wrong. He was eager to explore whether it was possible to create a retrieval practice strategy that increased the odds of students getting the right answer without sacrificing the quality of learning. To test this possibility, he led a study in which participants tried to remember word pairs, such as “idea: seeker.” The goal was to remember the second word after seeing only the first one. The students could choose to practice by restudying all the pairs or by self-testing with different options for hints—seeing either two or four letters of the second word in the pair, or no letters at all ( Cognitive Research: Principles and Implications , Vol. 4, 2019).

Most of the students preferred self-testing over restudying, and the results showed that even with hints, the self-testing group performed better on the final test of the words than the restudying group. “It’s a win-win situation because the technique that worked most effectively was also the one that they enjoyed the most,” says Kornell. 

Even more important, students think they are learning more effectively when they answer correctly while practicing, which means they’ll be even more motivated to try retrieval practice if hints are available, says Kornell. To apply this strategy, he suggests adding hints to self-generated flash cards or quizzes, such as the first letter of the answer or one of the words in a definition.

4. Make the most of study groups

Many students also enjoy studying with classmates. But when working in groups, it’s important for students to let everyone have an opportunity to think of the answers independently, says Henry Roediger, III, PhD, a professor in the psychology department at Washington University in St. Louis. One study highlighted the importance of this: Participants tried to learn words in a foreign language by either answering aloud or by listening to their partners give the answers ( Journal of Experimental Psychology: Applied (PDF, 426KB) , Vol. 24, No. 3, 2018). As expected, those who had answered aloud outperformed the listeners on a test two days later. The researchers also compared participants who answered aloud with partners who silently tried to recall the answers. Everyone received feedback about whether they had gotten the correct answer. Both groups had comparable performances. “Waiting for others to think of answers may slow down the process, but it produces better retention for everyone because it requires individual effort,” Roediger says. 

5. Mix it up

Researchers have also investigated the potential benefits of “interleaving,” or studying for different courses in one study session ( Journal of Experimental Psychology: Applied , Vol. 23, Nov. 4, 2017). For example, rather than dedicating two hours to studying for a psychology exam, students could use that time to study for exams in psychology, biology and statistics courses. A few days later, students could study for the same courses again during another block of time. “This strategy, versus blocking one’s study by course, naturally introduces spacing, so students practice retrieving information over time,” Bjork says. 

But the research on interleaving has had mixed results, says Aaron Richmond, PhD, a professor of educational psychology and human development at Metropolitan State University in Denver. “If the concepts from two subjects overlap too closely, then this could interfere with learning,” says Richmond. “But chemistry and introduction to psychology are so different that this doesn’t create interference.”

6. Figure out what works for you

The ability to effectively evaluate one’s approach to learning and level of attainment is known as metacognitive ability. Research has shown that “when people are new to learning about a topic, their subjective impressions of how much they know are the most inflated,” says Paul Penn, PhD, a senior lecturer in the psychology department at East London University and author of the 2019 book “The Psychology of Effective Studying.” 

“If your impression of your learning is inflated, you have little incentive to look at the way you're approaching learning,” he says.

To increase awareness about the value of sound study strategies, administrators at Samford University in Alabama invited psychology professor Stephen Chew, PhD, to talk to first-year students about this topic during an annual convocation each fall semester. Though an assessment study, he realized that the lecture prompted immediate changes in beliefs and attitudes about studying, but long-term change was lacking. “Students forgot the specifics of the lecture and fell back into old habits under the stress of the semester,” Chew says. 

To provide an accessible resource, he launched a series of five 7-minute videos on the common misconceptions about studying, how to optimize learning and more. Professors throughout the school assign the videos as required classwork, and the videos have been viewed 3 million times throughout the world by high school, college and medical students. 

While this form of campus-wide education about studying is somewhat rare, psychology researchers are optimistic that this could become more common in the coming years. “There is a lot more discussion now than even 10 years ago among teachers about the science of learning,” Karpicke says. “Most students do not know how to study effectively, and teachers are increasingly eager to change that.” 

Further reading

• Improving Self-Regulated Learning with a Retrieval Practice Intervention. Ariel, R., Karpicke, J.D., Journal of Experimental Psychology: Applied , 2018.
• Practice Tests, Spaced Practice, and Successive Relearning: Tips for Classroom Use and for Guiding Students’ Learning (PDF, 53KB) . Scholarship of Teaching and Learning in Psychology , Dunlosky, J. & Rawson, K.A., 2015.
• Performance Bias: Why Judgments of Learning Are not Affected by Learning . Kornell, N. and Hausman, H., Memory & Cognition , 2017.

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Beginner’s Guide to Research

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Last updated : July 18, 2024

Consider keeping a printed copy to have when writing and revising your resume!  If you have any additional questions, make an appointment or email us at [email protected] !

Most professors will require the use of academic (AKA peer-reviewed) sources for student writing. This is because these sources, written for academic audiences of specific fields, are helpful for developing your argument on many topics of interest in the academic realm, from history to biology. While popular sources like news articles also often discuss topics of interest within academic fields, peer-reviewed sources offer a depth of research and expertise that you cannot find in popular sources. Therefore, knowing how to (1) identify popular vs. academic sources, (2) differentiate between primary and secondary sources, and (3) find academic sources is a vital step in writing research. Below are definitions of the two ways scholars categorize types of sources based on when they were created (i.e. time and place) and how (i.e. methodology):

Popular vs. academic sources:

• Popular sources are publicly accessible periodicals–newspapers, magazines, and blogs–such as The Washington Post or The New Yorker . These sources are most often written for non-academic audiences, but can be helpful for finding general information and a variety of opinions on your topic.
• Academic sources , known also as peer reviewed or scholarly articles, are those that have undergone peer review before being published. Typically, these articles are written for other scholars in the field and are published in academic journals, like Feminist Studies or The American Journal of Psychology . Literature reviews, research projects, case studies, and notes from the field are common examples.

Primary vs. secondary sources:

• Primary sources are articles written by people directly involved in what they were writing about, including: News reports and photographs, diaries and novels, films and videos, speeches and autobiographies, as well as original research and statistics.
• Secondary sources , on the other hand, are second hand accounts written about a topic based on primary sources. Whether a journal article or other academic publication is considered a secondary source depends on how you use it.

How to Find Academic Sources

Finding appropriate academic sources from the hundreds of different journal publications can be daunting. Therefore, it is important to find databases –digital collections of articles–relevant to your topic to narrow your search. Albertson’s Library has access to several different databases, which can be located by clicking the “Articles and Databases” tab on the website’s homepage, and navigating to “Databases A-Z” to refine your search. Popular databases include: Academic Search Premier and Proquest Central (non-specific databases which include a wide variety of articles), JSTOR (humanities and social sciences, from literature to history), Web of Science (formal sciences and natural sciences such as biology and chemistry), and Google Scholar (a web search engine that searches scholarly literature and academic sources). If you are unable to access articles from other databases, make sure you’re signed in to Alberton’s Library through Boise State!

Performing a Database Search

Databases include many different types of sources besides academic journals, however, including book reviews and other periodicals. Using the search bar , you can limit search results to those containing specific keywords or phrases like “writing center” or “transfer theory.” Utilizing keywords in your search–names of key concepts, authors, or ideas–rather than questions is the most effective way to find articles in databases. When searching for a specific work by title, placing the title in quotation marks will ensure your search includes only results in that specific word order. In the example below, search terms including the author (“Virginia Woolf”) and subject (“feminism”) are entered into the popular database EBSCOhost:

Refining Your Search Results

Many databases have a bar on the left of the screen where you can further refine your results. For example, if you are only interested in finding complete scholarly articles, or peer-reviewed ones, you can toggle these different options to further limit your search. These options are located under the “Refine Results” bar in EBSCOhost, divided into different sections, with a display of currently selected search filters and filter options to refine your search based on your specific needs, as seen in the figure below:

Search results can also be limited by subject : If you search “Romeo and Juliet” on Academic Search Premier to find literary analysis articles for your English class, you’ll find a lot of other sources that include this search term, such as ones about theater production or ballets based on Shakespeare’s play. However, if you’re writing a literary paper on the text of the play itself, you might limit your search results to “fiction” to see only articles that discuss the play within the field of literature. Alternatively, for a theater class discussing the play, you might limit your search results to “drama.”

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Major Branches of Psychology: A Comprehensive Guide

Academically reviewed by Bettina Shapira, Ph.D

Psychology is a fascinating field, with different branches exploring various parts of human behavior and how the mind works. Whether you’re interested in understanding how people learn, delving into the depths of the unconscious mind, or helping people navigate life’s challenges, psychology offers many diverse avenues to explore. In this guide, we’ll examine the major branches of psychology, providing insights into each area and highlighting the unique contributions they make to our understanding of the human experience.

Table of Contents

Overview of psychology, history of psychology, two major areas of psychology, psychology branches and career paths, exploring careers in psychology.

Psychology focuses on comprehending the complexities of the mind and behavior, aiming to understand thoughts, emotions, and actions both individually and among groups. It covers a variety of topics, from brain function to social interactions and mental health. By exploring these areas, psychologists aim to improve our understanding of human nature and apply this knowledge to solve real-world problems, enhancing well-being and promoting psychological well-being. Within the field, it’s important to distinguish between psychologists and psychiatrists ; while both professions are dedicated to mental health, their training and approaches can differ significantly.

The field of psychology has a rich and varied history. While iconic figures such as Sigmund Freud , who explored the mysteries of the unconscious mind, and B.F. Skinner, renowned for his behaviorist theories, are widely recognized, the history of psychology encompasses much more than the discoveries of these prominent individuals and dates back even further.

Psychology began as a branch of philosophy before evolving into a distinct scientific discipline in the late 19th century. Over the years, psychology has grown to include numerous theories and practices, each contributing to our grasp of the mind and behavior. From the early days of introspection to the modern focus on neuroscience and cognitive science, the journey of psychology is marked by continuous discovery and advancement.

Experimental Psychology (Research): This area focuses on conducting research and experiments to understand various aspects of human behavior and mental processes. Experimental psychologists study a wide range of topics, including perception, memory, learning, motivation, and emotion. Their research often forms the basis for theories and practices in other branches of psychology.

Applied Psychology (Practice): This area involves the practical application of psychological principles and research to solve real-world problems. Applied psychologists work in various settings, such as clinical, counseling, educational, forensic, health, and industrial-organizational psychology, using their knowledge to help individuals and organizations improve their well-being and performance.

Psychology is rich in specialized areas, from clinical and cognitive psychology to behavioral and developmental psychology, offering unique insights and applications. If you’re passionate about uncovering the mysteries of the mind and contributing to the well-being of others, a career in psychology can be both fulfilling and impactful. Let’s dive into the different psychological disciplines and the career paths they present.

Personality Psychology

Behavioral psychology, cognitive psychology, developmental psychology, clinical psychology, counseling psychology, forensic psychology, abnormal psychology, health psychology, industrial–organizational psychology, sports psychology, school psychology, integrative psychology.

Personality psychology is all about acknowledging what makes each of us unique. This branch investigates individual differences in behavior, emotions, and thought patterns. By studying traits like introversion, extraversion, openness, and conscientiousness, personality psychologists aim to decipher the patterns that shape our personalities. This field combines research and real-world applications, helping us better grasp why we think and act the way we do. According to the American Psychological Association , personality is defined as the individual differences in a person’s thinking, feeling, and behavior patterns.

Potential careers in personality psychology include working as a researcher, professor, or clinician. You might conduct studies on how personality traits impact various aspects of life or help people understand their personalities to improve their mental health and relationships. This field offers a variety of roles that allow you to make a real difference by helping people understand and embrace their unique qualities. 

If you’re curious about what makes people tick and want to help others understand themselves better, personality psychology could be the perfect fit for you. With opportunities in research, teaching, and clinical practice, this field offers a variety of roles to match your interests and strengths.

Abnormal psychology centers on understanding and addressing atypical patterns of behavior, cognition, and emotion. This area of psychology studies mental disorders such as depression, anxiety, schizophrenia, and obsessive-compulsive disorder (OCD). By learning more about these conditions, abnormal psychologists aim to develop effective treatments and interventions to help people lead healthier, more fulfilling lives.

Potential careers in abnormal psychology include working as a clinical psychologist, therapist, or counselor. These professionals diagnose and treat mental health disorders, providing support and strategies to help people manage their conditions. This field offers the opportunity to make a significant impact on people’s lives by helping them overcome challenges and improve their psychological well-being. If you’re passionate about helping others and interested in comprehending mental health disorders, abnormal psychology could be a rewarding career path for you. 

Behavioral psychology, or behaviorism, concentrates on examining observable behaviors and understanding how they are acquired and modified. This branch of psychology is based on the idea that all behaviors are developed through conditioning and can be changed and modified through various techniques. 

Potential careers in behavioral psychology include working as a behavior analyst, therapist, or counselor. These professionals often work with people facing behavioral challenges, such as children with autism or adults with addiction problems, using techniques like positive reinforcement to help change behaviors. This field offers the chance to create positive changes in people’s lives by helping them develop healthier behaviors.

If you’re interested in how behavior is learned and changed and enjoy working with people to improve their lives, a career in behavioral psychology might be perfect for you. With opportunities in therapy, counseling, and research, this field provides various roles that can make a significant impact.

Cognitive psychology investigates the mental processes related to knowledge, thought, and understanding. This discipline examines how people perceive, remember, solve problems, and make decisions. By understanding these processes, cognitive psychologists aim to improve educational methods, enhance memory, and develop strategies to support mental health. 

A cognitive psychologist might conduct experiments to understand memory and perception, work in educational settings to develop better learning techniques, or assist in designing user-friendly technology. If you’re fascinated by how the mind works and want to investigate the intricacies of human thought, cognitive psychology could be the right path for you. 

Developmental psychology studies the growth and changes people undergo throughout their lives, spanning from infancy to old age. This area of psychology looks at the physical, cognitive, social, and emotional development that occurs at different life stages. Developmental psychologists seek to understand how people evolve over time and what factors influence their growth and development. They often work in educational settings, healthcare facilities, or research institutions, studying the influence of genetics, parenting, education, and culture on human development.

These professionals might assess developmental delays, design educational programs, or study the long-term effects of early childhood experiences. If you’re passionate about acknowledging the growth process and helping people achieve their full potential, a career in developmental psychology could be a perfect fit. For more information on pursuing this field, check out the Master’s Degree in Child and Adolescent Developmental Psychology program at National University.

Clinical psychology centers on identifying and managing mental, emotional, and behavioral disorders. This field blends psychological science with the treatment of complex human issues, making it one of the most hands-on areas of psychology.

Professionals often work directly with clients to address anxiety, depression, trauma, and other mental health conditions. Clinical psychologists might also perform research to develop new treatment methods or work in academic settings to train future psychologists. National University offers a Master of Science in Clinical Mental Health Counseling program for those interested in a career that makes a considerable impact on people’s lives by helping them overcome mental wellness challenges. 

Counseling psychology aims to assist people in enhancing their well-being, alleviating stress, and managing personal crises. This field focuses on the strengths of clients and offers support for various personal and relationship issues throughout their lives. Counseling psychologists work in many different settings, such as schools, private practices, and community agencies, providing guidance and strategies to help people handle life’s challenges.

If you choose a career in counseling psychology, you might work as a school counselor, marriage and family therapist, or career counselor. These roles involve offering valuable support and guidance to help those with both personal and professional issues, aiding them in developing effective coping strategies and reaching their goals. If you’re passionate about helping others and want to pursue a career that makes a difference, consider the Master of Arts in Counseling Psychology program at National University. Please note that this program is offered in California only. We also offer certificates in Psychology, including the Post-Baccalaureate Certificate in Psychology and the Post-Master’s Certificate in Psychology . Start your journey toward a rewarding career in therapy today. Discover the essential steps and insights needed to become a therapist by visiting our comprehensive guide .

Forensic psychology is where psychology meets the legal system. This field involves understanding criminal behavior, providing psychological assessments for court cases, and working with law enforcement agencies. Forensic psychologists might evaluate the mental state of defendants, offer expert testimony in court, or work with victims and offenders to provide counseling and rehabilitation services. 

A career in forensic psychology could be perfect for those interested in the legal system and allow practitioners to use their psychology skills in a unique way. You could work as a criminal profiler, expert witness, or consultant for legal cases, playing a vital role in helping the legal system understand the psychological aspects of cases. If this area of study fascinates you, check out the Master of Science in Forensic Psychology program at National University to start your journey.

Health psychology examines the impact of thoughts, behaviors, and cultural factors on physical health and wellness. This field aims to understand how people manage their health, cope with illness, and make health-related decisions. If this is something you’d be interested in pursuing, National University offers a Master of Science in Health Psychology program to get you started on this path. 

Health psychologists work to promote healthier lifestyles, improve healthcare systems, and support patients dealing with chronic illnesses. You could work as a health educator, clinical health psychologist, or public health advisor, helping people lead healthier lives and developing programs to support wellness. 

Industrial-organizational (I-O) psychology applies psychological principles to the workplace to improve productivity, employee satisfaction, and an organization’s overall effectiveness. This field involves studying workplace behavior, developing training programs, and implementing policies to enhance the work environment. Check out the Master of Science in Industrial-Organizational Psychology program at National University for more information on this dynamic approach to psychology.

I-O psychologists might work on improving hiring practices, designing employee development programs, or conducting research on workplace dynamics. You could work as a human resources specialist, organizational consultant, or corporate trainer, using psychological insights to create better workplaces. 

Sports psychology studies the influence of psychological factors on athletic performance and how sports and exercise participation impact psychological and physical well-being. This field involves working with athletes to enhance their performance, motivation, and mental resilience. Sports psychologists might help athletes cope with pressure, recover from injuries, or improve their focus and teamwork. 

If you love sports and want to help athletes succeed, check out the Bachelor of Arts in Sport Psychology program at National University. You could work as a sports psychologist for professional teams, a mental skills coach, or a consultant for athletic programs, providing support to help athletes achieve their best. 

School psychology is dedicated to fostering the academic, social, and emotional development of students within educational environments. School psychologists work with students, teachers, and parents to create supportive learning environments and address any issues that may affect a student’s ability to succeed. This field involves assessing students’ needs, developing intervention plans, and providing counseling and guidance. For more information, check out the Master of Science in School Psychology with PPSP Credential program at National University, available in California.

According to the American Psychological Association , Integrative psychology merges various psychological approaches and practices to develop a comprehensive understanding of human behavior. Integrative psychologists might draw from cognitive-behavioral, humanistic, psychodynamic, and other approaches to provide comprehensive treatment plans tailored to individual needs. If you’re interested in a holistic approach to psychology that values multiple perspectives, a career in integrative psychology could be a great fit.

You could work as a therapist, counselor, or consultant, using an assortment of skills and techniques to help people achieve mental and emotional well-being. To explore this field, consider the Bachelor of Arts in Integrative Psychology program at National University. Other options at the National University include a  Master of Arts in Consciousness, Psychology, and Transformation  and a  Graduate Certificate in Consciousness, Psychology, and Transformative Studies .

Psychology is an intriguing and multifaceted field with numerous branches, each offering unique opportunities to make a significant impact in the lives of others. Whether you’re interested in understanding criminal behavior through forensic psychology, promoting health and wellness in health psychology, improving workplace environments in industrial-organizational psychology, or supporting athletes in sports psychology, there’s a path for you.

For those passionate about making a difference in educational settings, school psychology offers the chance to help students thrive. If you prefer a holistic approach, integrative psychology combines various therapeutic techniques to address the complexities of human behavior. Each of these fields provides a rewarding career that allows you to help others and contribute to our understanding of the human mind. Ready to take the next step in your psychology career?

Explore the different branches of psychology and the wide range of psychology programs offered at National University by visiting our Social Sciences and Psychology Degrees page. Find the program that aligns with your interests and start your journey toward a fulfilling career in psychology.

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• Open access
• Published: 20 July 2024

Understanding the public stigma of mental illness: a mixed-methods, multi-level, exploratory triangulation study

• Daniel Walsh 1 &
• Juliet Foster 2  

BMC Psychology volume  12 , Article number:  403 ( 2024 ) Cite this article

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This study examines the role of themata in understanding mental health-related stigma. It is motivated by the need for alternative theoretical-methodological approaches beyond the dominant frameworks in education and contact-based anti-stigma public health efforts, which have shown mixed effects. Specifically, it addresses the need for a more nuanced framework in stigma research, one that is sensitive to the dialogues through which people relate themselves to mental health and stigma in context.

The research employs an exploratory mixed-methods approach, including the analysis of 529 news reports, 20 focus group discussions, and 19 one-to-one interviews, all concerning representations of shared living arrangements with someone perceived to have experiences of mental illness. Thematic analysis and natural language processing are used within a convergent triangulation design to analyze the data.

We found that mental health and illness were communicated through an overarching Self/Other thema and five subordinate themata: normal/abnormal, harm/non-harm, bounded/non-bounded, and moral/immoral. Despite familiarity with psychological distress and ‘modern’ explanations of mental illness, concerns about social identity motivated representations of mental illness as a predominantly permanent, negative form of personhood marked by abnormality, harm, distance, and immorality. Additionally, concerns about personal vulnerability, including historically rooted fears of contagion, motivated distancing representations of mental illness, rather than neutral portrayals.

Conclusions

Themata have under-developed theoretical and methodological potential for addressing mental health-related stigma, particularly in their ability to describe the dynamic ways in which culture motivates people to both resist and reproduce stigma, partly through ambivalences, absences, tensions, and ambiguities in representation. A critical discussion is provided on how themata may support ecological strategies in mental health campaigns over generic models, emphasizing the need to understand group knowledge and contact dynamics to mitigate adverse effects. Themata Public Health Unintended Consequences Mixed Methods Behaviour Change Natural Language Processing.

Peer Review reports

Introduction

A new approach to mental health-related stigma is needed because current dominant strategies do not adequately address the public’s desire to avoid intimate or sensitive forms of contact (e.g., in the home) with individuals with experiences of mental illness. This is despite increases in opinions concerning the unacceptability of stigma and greater familiarity with professional psychiatric terminology (e.g., depression, schizophrenia) and biomedical explanations (e.g., genetics, neurochemicals) [ 1 ]. This is a serious issue, as current models for alleviating mental health-related stigma assume that increasing public knowledge will linearly improve attitudes toward mental illness and reduce social distance [ 1 ]. Education and contact are the dominant strategies used to address public stigma [ 2 , 3 , 4 , 5 ]. These approaches aim to address the long-standing public perception that mental illness is ‘unfamiliar’ or ‘unknown’ [ 1 ]. However, education-focused strategies, particularly those that emphasize a bio-genetic basis for mental illness, unfortunately correlate with increased desires for social distance [ 3 , 6 ]. Social distance is a dynamic concept that refers to the felt sense of affinity or dissonance between perceived groups. It is often communicated through descriptions of the perceived non-familiarity and incomprehensibility of experiences of mental illness [ 1 , 3 ]. Similarly, contact-based interventions often have mixed or no effects [ 7 ]. This may be due to the complex mix of positive and negative experiences people have with ‘contact’ related to mental ill-health, as well as the various ways contact can occur with representations of mental illness (e.g., personal thoughts, conversations with friends and family, media) [ 1 , 8 ].

In this paper, we present an alternative framework for conceptualizing stigma, which centers on representation and communication. ‘Mental illness’ is communicated in society through various forms, from media portrayals and conversations with friends to personal reflections [ 1 , 8 ]. These communications are not neutral or consistent [ 1 ]; they are replete with feelings and opinions [ 1 , 8 ]. To explain ‘mental illness’ to ourselves and others, we draw on shared understandings. For example, while we might not agree with certainty about what constitutes contact with mental illness, we can oppose the perceived ‘harms’ of contact and the perceived ‘safety’ of no contact. From this perspective, we can think about mental illness in terms of dialogues grounded in shared oppositions or themata (e.g., Self/Other; Harm/Safe; Pure/Impure) that societies employ to maintain, develop, and challenge representations of social issues [ 9 , 10 ].

Themata are dialogical units with an oppositional structure [ 9 ]. Studies of everyday thinking find that people rarely hold complete or secure beliefs about health and illness [ 8 ]. Instead, they offer partial explanations, often referring to stories of their own experiences or those of friends and family. In these explanations, people often argue against themselves or leave them partial or open-ended [ 1 ]. These dialogues are underpinned by taken-for-granted oppositions latent in communication, such as comparisons of the perceived relative ‘normality’ of experiences of sadness or anxiety compared to the ‘abnormalities’ presented by perceived mental illnesses such as ‘schizophrenia’ [ 1 , 4 , 5 ]. In other words, we understand ourselves in relation to mental illness by opposing ‘normal’ with ‘abnormal’ [ 8 ]. These oppositions are dynamic, meaning that what is accepted as ‘normal’ in one social context (e.g., shared public spaces) may be perceived differently in ‘private’ spaces [ 1 ].

This emphasis on themata could pave the way for potential advancements in public anti-stigma efforts: identifying these relational units of communication allows for an exploration of the dynamic manners in which individuals make sense of mental health-related stigma in various contexts. For instance, a review of three decades of population research suggests that the degree of pro-social feelings (e.g., the felt need to help) and anti-social feelings (e.g., fear, anger) varies with the perceived differences in forms of social contact (e.g., subtenant vs. neighbour) as well as the presence and ‘type’ of diagnostic label (e.g., schizophrenia vs. depression), in comparison to non-labelled symptoms [ 11 ]. Furthermore, identifying themata might offer insights into the motivated aspects of stigma. This approach helps us understand how people represent ‘mental illness’ (for example, seeing it as dangerous) and the motivations underpinning why they have these representations (such as thinking that mental illness is something that happens to others, not themselves). National studies consistently find strong negative reactions to close contact with people with mental illness, especially in intimate settings like the home, even though stigmatizing them is recognized as wrong [ 12 ]. These negative views often draw on longstanding stereotypes, such as associating ‘madness’ with violence [ 13 , 14 ].

In the subsequent sections, drawing on the literature concerning mental health-related anti-stigma programs, we will discuss the challenges in addressing the public’s motivations that perpetuate mental health-related stigma. We will also further elucidate the benefits of emphasizing themata over conventional methods for social research in health and stigma, and the opportunities for drawing on advances in natural language processing to draw out the latent aspects of communication.

Mental health-related anti-stigma campaigns

Over the last decade, concern over the limited and unintended consequences of anti-stigma efforts has focused attention on the assumptions underpinning mental health-related anti-stigma campaigns [ 1 , 3 , 4 ]. Predominantly, efforts to challenge public stigma—"the contextual climate of prejudice and discrimination" ([ 14 ], p. 94)—employ a deficit model of public understanding [ 15 ]. This model conceptualizes lay understanding as largely derived from professional knowledge [ 1 , 16 ].

Practitioners primarily employ educational strategies to remediate this perceived deficit, often combined with elements of social contact, especially in high-income countries [ 1 , 2 , 6 , 17 ]. For a discussion of variability in change strategies, see [ 1 ]. In line with the deficit model, practitioners hope that promoting professionalized knowledge to the public will translate into positive attitudes and behaviours towards individuals with experiences of mental illness [ 1 , 16 ]. Unfortunately, despite evidence that interventions improve positive attitudes in the short term and that these attitudinal changes may be attenuated, it is unlikely that current interventions challenge the contact taboos foundational to the reproduction of stigma in society [ 9 , 18 , 19 , 20 , 21 , 22 , 23 ]. For example, an ethnographic study found that families hosting a lodger with a mental illness, despite being in regular contact with psychiatric professionals for advice on managing mental illness, maintained several rituals to avoid intimate contact, such as separating eating utensils [ 18 ]. A contact taboo is a rule that forbids certain actions toward perceived out-groups because they are believed to be either too sacred or too dangerous for ‘normal’ people [ 18 ]. Contact taboos frequently encompass implicit beliefs regarding the risks (to the in-group) associated with proximity to mental illness. For instance, in the British media, although the Mental Health Bill of 2002 was broadly portrayed as unduly restrictive—given its potential to mandate compulsory treatment and detainment under an expanded definition of ‘mental disorder’—there was also an implication that individuals with a history of mental ill-health are predisposed to criminal violence likely reproducing the public’s felt need for social distance [ 16 ].

Mental Illness as other

Anti-stigma efforts have done little to challenge, and may have even sustained, public representations of mental illness as "Other" [ 1 , 3 , 24 , 25 ]. To "Other" means to represent an out-group as profoundly and undesirably different from oneself and one’s in-group [ 26 ]. While it was hoped that by making incremental improvements to dominant change strategies, such as a greater focus on group or curriculum, might displace a representation of mental illness as "Other", public motivations to "Other" go beyond what's considered in generic change programs. Indeed, "Othering" likely constitutes a ‘wicked problem’ ([ 4 ], p. 1158) and is sustained by power inequalities in the social order [ 1 , 3 ]. When close attention is paid to linguistic practices, such as symbol, metaphor, and imagery, findings suggest "Othering" profoundly constrains ways of understanding mental illness, even through anti-stigma campaigns [ 16 , 27 , 28 ].

Our study is derived in response to the ineffectiveness of public mental health anti-stigma campaigns in England, particularly the ongoing tendency of the public to "Other" mental illness. Time to Change (TTC), the leading anti-stigma campaign from 2007 to 2021, was associated with moderate increases in professional knowledge, positive attitudes, and slight decreases in a desire for social distance [ 29 ]. However, "Othering" remained prevalent [ 25 , 27 , 30 ]. Public motivations to "Other" experiences of mental illness meant the content promoted through the TTC campaign, especially in its first phase (2007 – 2011), did not fundamentally change public understanding but likely refashioned stigma [ 16 ]. Initially, social marketing campaigns emphasized a biomedical and neurogenetic basis for mental illness, often in the form of ‘myth busting’ [ 3 , 16 ]. Campaigners hoped that increases in professional knowledge would decrease public associations between responsibility and mental illness [ 3 , 16 ]. Yet, the emphasis on bio-genetic and neurochemical causes did little to challenge the divisive ‘us vs them’ narrative [ 3 , 16 , 30 ]. It also likely reinforced an association between mental illness and permanence [ 1 , 24 ].

To address contact fears, the later stages of the TTC campaign increasingly used para-social contact, such as stories of empathy and humor in friendships between individuals with and without potential experiences of mental ill-health [ 29 , 31 ]. However, instead of displacing stigma, "Othering" was likely latent and nuanced [ 1 , 30 , 60 ]. Although there was a notable reduction of ‘bad news’ tweets from the UK national press, especially regarding service provision, "Othering" was likely perpetuated through the continued use of sensationalist imagery [ 27 ] and differentiation in public sympathy, perceptions of dangerousness, and unpredictability related to mood and psychosis ([ 1 , 14 , 32 ], 2020 edition). Stories of criminal cases involving individuals with experiences of mental illness, especially schizophrenia, continued to be over-represented in the British media [ 16 , 27 ]. These narratives likely affirmed public beliefs of dangers associated with mental illness, and through their regular emotive context, bias lay thinking towards violence over mundane negotiations of mental health and illness in everyday life [ 16 , 27 ]. Moreover, the notion that the public lacked ‘contact’ was misleading, especially since public experiences of psychological distress are widespread [ 1 ]. Indeed, this approach further differentiated representations of what one or those similar could experience (e.g., feelings of sadness) from the perceived "Otherness" of mental illness [ 1 , 30 ].

Themes and themata

Practitioners may benefit from increased sensitivity to the public’s motivated ways of understanding mental health and illness, especially considering their robust capacity to “Other” [ 29 ]. However, prevailing methods for describing public comprehension do not adequately capture how people maintain mental health-related stigma in their daily lives [ 33 ]. In this paper, we propose themata—a concept developed in the history of science by Gerald Holton [ 9 ]—as a methodological innovation better suited for understanding how people relate to mental health-related stigma. We also explore the possibilities of using natural language processing to address the subtle linguistic features of representation.

In contrast to regular operations of public mental health research, which focus on evaluating variance in discrete and largely fixed components of public understandings of mental illness (e.g., attitudes, knowledge, belief), themata acknowledge that in natural communication, people regularly argue against themselves regarding what constitutes ‘mental illness’ and the perceived risks it poses to them [ 1 ]. This is important because by focusing on units through which representations are ambiguously developed and contested (e.g., familiar/non-familiar; moral/immoral), we have a framework to consider the reasons why we see inconsistencies in public behaviour towards mental health-related stigma [ 1 ]. For instance, it is a recurring finding that mental illness is perceived as foreign, unknown, or unfamiliar. Yet, this perception often coincides with the acknowledgment of the familiarity of depression, which serves to affirm the perceived fundamental incomprehensibility of schizophrenia, thereby reinforcing a unified representation of mental illness as ‘Other’ [ 34 ]. Similarly, while progressive narratives of mental health stigma frequently include discussions of mental health challenges faced by close friends and family members, this is often done to delineate a ‘good’ type of mental illness that is acceptable to be associated with, thereby reinforcing the desire to distance oneself from a ‘bad’ or Othered form of mental illness [ 35 ].

Clustering algorithms, as part of natural language processing (NLP), offer the opportunity to highlight the words around which other words cluster [ 33 ]. This is an important advancement, as in the regular practice of identifying repeated patterns, as is common in thematic analysis, we can overlook the subtle but important ways people relate to mental illness, relying on what is more easily recognizable to us as researchers, such as discrete labels of diagnoses (e.g., schizophrenia), emotions (e.g., fear), and causes (e.g., genetics) [ 33 ]. Yet, focused readings of the text can reveal overlooked public uncertainties and concerns about mental illness, such as metaphors that represent mental illness as a ‘maze’ or images that represent mental illness as ‘dirty’ [ 27 , 32 , 33 ]. Clustering algorithms can be helpful in spotlighting the words around which other words cluster, suggesting latent meanings in the text [ 33 ].

In this paper, we pay special attention to the communications between Self and Other, which has been proposed as an epistemological thema in representations of risk and social identity [ 36 , 37 ]. We understand social identity as the "processes of interpersonal communication" ([ 38 ], p.2), which influence the structure and content of social categorization [ 9 , 39 ]. A Self/Other thema has been found to organize lay representations of various perceived risks in health and stigma, including communicable diseases, organ donation and transplantation, and mental health and illness [ 15 , 37 , 40 , 41 ]. In all these cases, the perceived risk is linked to the Self, instinctively shaping certain ways of 'knowing' the object of concern [ 9 , 10 ]. Specifically, the perceived risk is associated with the affected marginalized out-group (e.g., HIV/AIDS and gay men), limiting alternative forms of social identity [ 15 , 37 , 40 ]. Moreover, the implicit dialogues between Self and Other are inclined to blame out-groups for their marginalization, perpetuating societal stigma [ 15 , 37 , 40 ]. The emphasis on a Self/Other thema aligns with the concept of discourse in their shared rejection of the idea that people have a fixed, asocial self [ 9 ]. Instead, it is through our relations with society that we understand ourselves as capable of psychological experience [ 9 ]. However, the two are not synonymous in relation to power, especially regarding opportunities for minority groups to express agency and creativity in representation beyond self-regulatory processes, which hold the potential to reshape themselves and wider society [ 9 ].

A theoretical-methodological concern advanced in this introductory section has been the challenges in researching why people may disavow stigma and draw on professional knowledge to explain it, but maintain subtle prohibitions on intimate forms of contact, such as within the home or with perceived vulnerable groups [ 1 ]. For this reason, we use the context of students’ shared living arrangements. We explore how, in this perceived contact, people formulate representations of themselves in relation to the perceived Otherness of mental illness, a practice that may include comparing mental illness diagnostic labels (e.g., schizophrenia vs. depression) [ 18 , 33 ].

Interim summary and contributions

Dominant educational and contact-based interventions aimed at addressing mental health-related stigma are found to yield limited and unintended outcomes. We propose that themata can function as a theoretical-methodological framework to overcome significant limitations inherent in current anti-stigma efforts. Specifically, they offer a means to articulate the motivated ambivalences in contact and knowledge that perpetuate stigma within society, in particular the latent perceived risks posed to the Self posed by contact with the ‘Otherness’ of mental illness. In the remainder of this paper, we will present an empirical example illustrating the themata through which mental health-related stigma is maintained in the context of students’ shared living situations.

We will outline three principal contributions to the literature. First, we will demonstrate how a natural language clustering algorithm can reveal potential latent meanings within text. Specifically, while confirming established findings that public apprehension about social contact is driven by fears of harm, our application of natural language processing suggests that these concerns may also include subtle fears of harm through contagion, a concept historically linked with madness [ 3 , 18 ]. Second, our novel methodological approach will identify key empirical contributions, notably in pinpointing absences and ambivalences in representation. This encompasses the public’s ambivalent concerns about social contact. These concerns arise from both perceived non-familiarity and similarities to experiences deemed relatable to the Self, along with the underlying belief that the risk associated with mental illness is enduring. Third, the relational analysis of communication, facilitated by the identification of themata, allows for a nuanced development of alternative anti-stigma strategies. Specifically, as our analysis will demonstrate the interdependencies between themata, such as Self/Other and harm/non-harm, we will critically examine how efforts to change public understanding through one-dimensional interventions (e.g., education that individuals with mental illness are not inherently violent) fail to address the negative emotions (e.g., fear, disgust) within the Self, and suggest the need for ecological interventions that address beliefs about the Self in context.

This paper will present novel analyses conducted on partially published datasets [ 32 , 33 ]. We employed a mixed-method convergent triangulation design [ 42 ] to explore representations of mental illness of health and illness [ 32 , 33 ]. The study involved three forms of data: news reports ( N  = 529), small focus groups ( N  = 20), and one-to-one interviews ( N  = 19) (Tables  1 and 2 ).

We will now briefly summarise materials and methods to support comprehension. To limit data recycling and focus on the novel contributions themata might make to mental health-related anti-stigma efforts, please see [ 33 ] for a full account of the construction of datasets. All interview (LRS-18/19-9068) and focus group (LRS-19/20-14053) participants gave written informed consent, and the study was approved by the King’s College London college Ethics Committee.

News reports

We used three groups of search terms to develop the corpora. They included ‘mental’, ‘depression’, or ‘schizophrenia’; ‘student’, ‘university’, or ‘college’; and ‘housing’, ‘accommodation’, or ‘flat’. The search terms were written in English and covered publications from 01/01/2010 to 01/01/2020. A corpus of 529 news reports was compiled. The selection of news outlets was determined by the 10 news brands regularly self-reported, via any platform, as read by 16-24-year-olds in the UK, and included a range of the political spectrum, broadsheets versus tabloids (e.g., The Guardian for left-wing readership and broadsheet, and the Daily Mail for right-wing readership and tabloid). The corpora of news reports was rich and multi-media, encompassing news reports with both text and imagery [ 32 , 33 ].

Interviews & focus groups

All interviews and focus groups were conducted between 2019 and 2020, and interview questions have been published previously in [ 33 ]. Transcriptions of focus group discussions and interviews were produced verbatim [ 32 , 33 ]. All datasets concerned students’ representations of mental health and illness related to shared accommodation. We focused on students’ representations as they are considered an important group to target on account of their increased likelihood of personal and close contact with experiences of psychological distress [ 3 , 44 ] and focusing intimate forms of contact commonly provide insight into the latent forms of lay representation [ 19 , 40 ]. All students self-reported having no history of mental illness, as previous studies suggest that experiences of mental illness differentiate representation [ 45 ], although we found expressions of psychological distress were common in the sample [ 32 , 33 ]. Students studying psychological and health sciences compromised roughly half the sample ( N  = 17/39).

Analytic procedures

Clustering & network analysis.

We duplicated the three datasets and applied standard data processing techniques in TextEditor for compatibility with Python3 [ 32 , 33 ]. We analyzed the text from each dataset as a network of related words using a clustering coefficient (CC) algorithm as part of NLP. This algorithm measures how often and how close words appear together [ 33 , 46 ]. The CC scores help us understand what concepts contained in the text. By looking at these scores alongside direct quotes, we can see how meanings gather around key concepts [ 33 , 47 ]. For each dataset, we ranked the top 10 CC scores and provided illustrative direct quotes for each ranked word, following the conventions of mixed-methods research [ 33 ].

Thematic analysis

Each corpus was independently subjected to themata analysis supported by natural processing. Themata analysis was not solely the product of natural language processing but enriched by it. Specifically, words indicated by the clustering were used to keyword search the texts and support the researcher’s exploration into the themata utilised in sense making.

Identifying themata was a progressive, iterative process of open, axial, and selective coding. Open coding involved a thorough reading of the text. The open codes generated encompassed both semantics and pragmatics. Specifically, we paid close attention to the use of quantifiers (e.g., all, many) and logical connectives (e.g., not, if) used to represent mental illness, along with symbols (‘lock’ as protection), metaphors (e.g., ‘spiral’ as degeneration), and affects (e.g., fear, unease). We also focused on how language was used in context, coding elements that were strongly implied but not explicitly vocalized, potentially reflecting concerns about social desirability. These codes were generated through the authors’ close manual reading of the text, and through a keyword-in-context approach, indicated by words with high cluster coefficient scores (e.g., contagion). The initial open codes were then subjected to axial coding, where they were grouped into working categories and sub-categories. Finally, selective coding was applied to identify the themata or dialogical units. While this was a progressive process, it was particularly during selective coding that selective absences were commonly realized (e.g., recovery), often necessitating further open coding. After selective coding was complete, an uncoded sample was reviewed using the coding book to ensure consistency. It is in this final stage that is central to the differentiation between producing themata rather than themes. Whereas both involve clustering qualitative data, the identification of themes is concerned with repeated patterns, often interpreted as beliefs or opinions [ 47 ]. In contrast, the relational quality of themata focuses on the possible tensions in meaning-making, enabling the description of both resistance and reproduction of stigma through the same thema.

Triangulation

The themata analysis outcomes, bolstered by natural language processing, included three thematic coding books and three tables of cluster coefficient rank scores. We carefully reviewed the findings, paying special attention to the mixed feelings and opinions expressed in each situation and noting any differences between various situations. We refrained from imposing a rigid structure on the data. Instead, we critically assessed the ambivalence of understandings conveyed through the themata, explaining potential ambiguities by considering the role these understandings played within their communicative contexts. Our confidence in the findings was reinforced through triangulation of qualitative and quantitative data and by adopting a dialogical method to establish validity [ 42 , 48 ].

First, we will briefly summarize the results to help with understanding, which will be detailed later. Participants understood mental health and illness through a main thema of Self/Other. This main theme influenced five sub-themata: normal/abnormal, harm/non-harm, bounded/non-bounded, moral/immoral, and permanent/impermanent. These sub-themata helped shape people’s feelings and opinions on mental health and illness, reinforcing social identities. Understanding was often unclear and incomplete, based on symbols and images rather than solid knowledge. Tables  1 , 2 and 3 show the top 10 keywords with a direct quote for each from the data. These keywords and quotes help us highlight potential meanings in the text, which will be discussed in terms of themes in the rest of this Results section [ 33 ].

Self/other thema

A Self/Other theme was fundamental in maintaining mental health-related stigma in society. Through this theme, participants reinforced the idea that mental illness is different and separate from themselves. This perspective limited their full understanding of mental illness in several ways. A common approach was to view people with mental illness as part of an out-group, blaming them for their marginalization.

“They want to be closed up , but deep down , they’re just unhappy with themselves. That’s why they’re closing themselves up , I think. For me , I’m happy in myself , I’m confident… I choose to be closed off. They choose to be as well , but like– I don’t know how to describe it. I’m happy that I’m closed off.” ( IP1).

IP1 represented mental illness as a negative form of personhood valanced against positive Self-attributions. IP1 fluidly uses words such as ‘they’ and ‘them’ to convey their perception that individuals with experiences of mental illness choose separation and sadness. Rather than representation being external or primary to personal experience, through the Self, people engaged in a motivated representation of mental illness as Other or ‘not-me’.

The relations between Self and Other were partially phenomenological. For example, in table one, we can identify expressions of ‘fear’ and ‘worry’ and even ‘dread’ and ‘despair’. Similarly, in the interviews, expressions of fear were common (Table  3 ). Whilst fear was also referenced in the focus groups (Table  4 ), its expression was less pronounced, and participants were oriented towards feelings of frustration or moral anger.

In addition, we found an emphasis on Otherness in perception. For example, in the media, the language was of ‘discovery’, in which the public ‘dreaded’ finding more ‘dead’ students (Table  5 ). Conversely, the conceived threat posed by mental illness was its perceived imperceptibility. FG4P1 (Table  4 ) leaves open-ended the statement: “ you don’t notice anything when they—” . Still, and in often subtle ways, representations of the Other were as much about the Self as they were about understanding mental illness. Whilst it was very much in evidence that people feared the Other, mental illness was also feared for what it might reveal about the Self. For example, IP3 explains: “ fear. You might discover some like you don’t know about , some negative things like—like you don’t want to admit you have like this negative trait in you ” (Table 3 ).

Rather than a fundamental lack of knowledge about mental illness, we found that comprehension of mental illness through contact was perceived as risky. This is highlighted by IP7 (see Table 3 ). While there was clear evidence of fear stemming from the unfamiliarity with mental illness, IP7 was also concerned about the implications of symbolically sharing space with individuals who have mental illness experiences. Sharing space was seen as a threat to their own uniqueness, making students want to keep a clear separation between themselves and the perceived Otherness of mental illness. Specifically, understanding mental illness through contact generated discomfort in individuals, which in turn motivated the perpetuation of a representation of mental illness as ‘Other.’

Normal/abnormal thema

An important way of knowing was through comparison between perceived normal and abnormal behaviour. Yet, as mental illness was believed to relate to differences in daily living and causes beyond in-group perception (e.g., contagion (Table  5 )) and to have a broad range of symptoms and signs partially shared with ‘normal’ psychological distress, ambiguities were pervasive in a normal/abnormal thema. However, at the level of representation, ambiguity was not a source of tension. Instead, through beliefs of alterity, participants used mental illness as an identity marker to distinguish normal and abnormal behaviour.

How alterity related to a normal/abnormal thema varied between communicative contexts. In focus groups, students particularised understandings to affirm mental illness’ associations with abnormality. For example, FG3P2 used the word ‘interpret’ (Table  4 ) to explain how a multitude of factors, such as contact with the unknown ( “you meet someone you don’t know” ), can ‘trigger’ persistent abnormal processes in the Self. Similarly, FG5P1 contends that groups with ‘mental health’ may be more inclined to feel ‘overwhelmed’ than ‘healthy’ people (Table  4 ). Abnormality was also implied through symbolic imagery. The image of a ‘petri-dish’ and ‘growth’ (Table  5 ) were common in constructions of mental illness, and normality was represented in contrast to a nightmarish ‘infestation’ of ‘rodents’ (Table 5 ); imagery commonly used to Other groups associated with socially undesirable illnesses (Sontag, 1978).

In the personal context of a one-to-one interview, students explained how the perceived abnormalities associated with mental illness differed from their personal daily experiences. IP10 imagined ‘poor mental health’ as personally experienceable ‘simple’ and ‘negative’ ‘day-to-day’ situations (Table  3 ). Yet, their understandings of how they, or those like them, would experience these situations were related to perceived Otherness of mental illness. Namely, a ‘lack’ of ‘emotional’ self-control, or the orientation towards a ‘pessimistic’ type of perception, rendered the experience of common situations different for those with a ‘strong’ mental health compared to those with ‘poor mental health’ (Table  3 ).

In summary, Participants understood mental illness through comparisons of perceived normal and abnormal experiences. This understanding varied by context, with focus groups emphasizing abnormality through symbolic imagery and personal interviews highlighting differences in daily experiences based on perceptions of emotional control and outlook. We will now see that the practices of dividing ‘normal’ and ‘abnormal’ experiences were linked to perceptions of harm.

Harm/non-harm

The strong association of mental illness with harm instinctively reinforced negative perceptions of group differences. Harms were broadly defined and included fears of contagion, social isolation, physical violence, and undue burden, depending on the context of communication.

In the media, repeated sensationalised stories of death in student accommodation firmly associated mental illness with incomprehensible harm. Contagious, inquest, and coroner had the top-three CC scores (Table  5 ). For example, in Birmingham Live (Table  5 ), through the ‘inquest’, the author ‘revealed’ to the public what occurred at the ‘hall of residence’. However, reaffirming a representation of mental illness as uncertain and unknown, the author highlights how the “coroner said she could not be sure … Sam Croydon intended to kill himself or if it was a cry for help” (Table  5 ). Similarly, a reporter described how “that sense of dread is known across the Kimberley” (Table  5 ), suggesting that these ‘unknown’ harms are already developed in representation.

Students described multiple personal experiences of psychological distress to associate mental illness with a loss of Self. In focus groups, students especially focused on the perceived risks of undue dependency. For example, in Focus Group 3 (Table 4 ), ‘spending time’ with someone with a mental illness was represented as a ‘strain’ or ‘burden’ on the Self, and willingness for intergroup contact was conditional upon “how much it affects you” (Table 4 ). IP4 described how what is harmful about depression is that it ‘withdraws’ you ‘from society’ and ‘day-to-day life’ (Table 3 ). Similarly, although retaining distance from perceived Otherness of mental illness, students commonly referenced their own experiences of psychological distress and social isolation.

“For a while now , when I’m with my friends , and I’m having fun , I just randomly feel guilty for no reason. I just feel like I just couldn’t fully put all my energy into it. I just felt so far away from everybody in that sense… you’re just feeling really empty inside.” (IP5) .

For IP5, what was considered harmful about mental ill-health is it ‘isolates’ the self from one’s in-group. This was experienced in terms of ‘emptiness’, loss of ‘energy’, and ‘random’ or reasonless feelings of ‘guilt’.

These perceptions of harm and dependency illustrate the complex ways in which students navigate their understanding of mental illness and its impact on social relationships. We will now describe how students manage concerns for these harms by placing boundaries on intimate forms of contact.

Bounded/non-bounded

Participants ambiguously used ‘boundaries’ to associate intergroup contact with risk. Rather than contact solely relating to a material space, contact was also located in in-group perception and was related to using symbolic language and social identity.

Contact taboos held a Self-protective function. IP3 also used the symbol ‘lock’ to describe how if they were to live with someone with a mental illness, they would ‘lock’ away personal spaces: “ Somebody with like crazy hair , like sore red-eye , and probably locked up in a hospital or someplace “(IP3). They also used ‘lock’ to describe how mental illness was distanced to ‘strange’ spaces. At the same time, people believed that risks like contagion and social devaluation were not fully protected against through boundaries and separation. In their account of ‘contagion’ (Table 5 ), the BBC discusses how ‘Emma’ on account of her ‘bipolar disorder’, ‘self-harm’ and ‘suicide’ was removed from school. However, when Emma tried to go back to school, she was isolated by teachers and friends by ‘judgements’ and their fear of ‘contagion’.

Concern for contagion likely limited the formation of intergroup trust. Whilst students commonly discussed contact experiences, rather than contact constituting a consistent change mechanism, as contact was associated with risk and harm, through contact student reaffirmed Otherness and maintained social distance.

“Someone’s mood can affect yours and like your mental health. It could end up , yes , I don’t know , just bringing you down as well , like by default.” (IP14).

“I can’t be around that for too long because it starts to affect me , and everything’s all good if it doesn’t affect me , but it once it does , I’m like , [laughs] ‘Bye.’” (FG4P1).

These examples suggest that rather than contact displacing public understanding, through contact people maintain understandings of mental health and illness, including historically rooted contact taboos, such as contagion beliefs [ 19 , 44 , 49 , 50 , 51 ], and canonic concerns for in-group safety were likely reimagined in the modern vernacular of ‘mental health’ or ‘mood’ [ 40 ].

Moral/immoral

Self-Other dialogues reproduced a taken-for-granted belief that contact with mental illness challenges in-group social identity. We will now describe how representations of the Other degenerated the moral life of individuals with experiences of mental illness.

In the focus groups, a moral/immoral thema was implicitly communicated through expressions of discomfort and moral anger, along with discussions of fairness, responsibility, and burden. Intergroup contact was represented as unfairly bringing the Self into contact with the conceived Otherness of mental illness. FG4P2 explains that contact risks feeling unduly “responsible for that person … which can have a like a really more negative effect on you than you realise” (Table 4 ). Similarly, FG3P1 explained how students have a normative desire to not “spend time with this person because it feels like a big strain” (Table 4 ). FG3P1 also described how they “didn’t ask for that… responsibility” (Table 4 ) and blames individuals with experiences of mental illness for being a ‘burden’.

A review of media and interview CC rank scores (Tables 1 , 2 and 3 ) suggested that mental illness was associated with something being ‘wrong’ or ‘bad’, especially when they felt mental illness was ‘too close’. Our close examination of the texts suggested that students held differentiated representations of social distance and morality. For example, IP11 distinguishes moral responsibilities based on felt closeness, showing that contact with others follows existing kinship and friendship patterns rather than being a single mechanism for change.

She’s not my close friend… She’s not my boyfriend , or my sister , or anything. So boundaries it’s just sometimes I tell her I need space , and she just listened for that moment but won’t take it in—She understands for the moment but will do the same later.” (IP11) .

IP11 experienced living with a friend with depression as a loss of power. Having their boundaries transgressed made them feel angry and constrained. Furthermore, moral involved complex representations of social distance. Unlike a ‘boyfriend’ or ‘sister’, IP11 was not ‘close’ to the friend in an emotional sense of the word and so felt they didn’t have responsibility for her welfare. Yet, the fact that the friend was perceived to transgress IP11’s ‘boundaries’ and entered IP11’s ‘space’ meant that the friend was likely materially close.

Permanent/non-permanent

A discourse of permanence was largely developed through media through emotionally compelling accounts of violence perpetrated by individuals with experiences of mental illness against perceived vulnerable groups:

“The 20-year-old university student … was in shock as to how the only person she’s ever loved would do that to her. The effect on her was severe and the trauma likely to be lifelong.” (Cornwall Live via Google News, 15.11.2019).

In the public’s imagination, these articles likely reinforce the belief that contact with mental illness carries the risk of extreme violence and ‘life-long’ negative impacts on one’s mental health. This is not to downplay the necessity for criminal justice. Rather, it aims to emphasize how a selective and disproportionate emphasis on depicting mental illness through the lens of criminal proceedings likely perpetuates a belief among the public of assumed permanent risks associated with such contact.

The media’s portrayal of mental illness as a permanent risk is likely mirrored in the notable paucity of discussions about recovery in the interviews and focus groups. Permanence, as a theme, is only once explicitly indicated in the CC rank scores tables (seven). FG3P3 stated, “there’s nothing that they can change … it’s this association of , um , permanence and of severity in how much it affects you.” . We found a taken-for-granted belief that mental illness has permanent negative effects on the Self.

Beliefs of permanence were instead implied when students compared between perceived category groups:

“I guess the implication of the word like illness being used is a bit harsher , like someone could have both like mental health problems and a mental health illness. But I guess like a mental problem does seem like , just like a symptom , like a thing that’s wrong that’s like even more easily solved. I feel like mental illness is kind of more like chronic or like diagnosed.” (FG1P2).

In this example, FG1P2 compares ‘mental health problems’ and ‘mental illness’ to express a belief that issues which are not ‘chronic’ or ‘diagnosed’ feel less ‘harsh’. This comparison subtly suggests that the impossibility of recovery is not explicitly mentioned but is implied in representation. FG1P2 stated, ‘even more easily solved’. While this statement does not fully capture recovery as living to one’s ‘full human potential’ [ 10 ], it implies that achieving recovery is seen as relatively more attainable for individuals without a ‘mental illness’.

A Self/Other themata likely underpinned these seemingly neutral comparisons. Students commonly Othered mental illness to distinguish it from their personal experiences of distress.

“I know from personal experience , I’ve gone through periods where , weeks at time capping in up to after two months , I can feel like utter trash , and it starts to impact my daily life… But this is something that’s being caused by something.” (IP8).

In the example above, IP8, whilst acknowledging that they have for ‘weeks at a time’ felt like ‘utter trash’, felt categorically different from mental illness. To do so, they represented themselves in terms of having poor mental health. However, what rendered themselves different to mental illness was their recovery and comprehensibility.

In summary, we found that the media often portrays mental illness through emotionally charged accounts of violence, reinforcing the belief that mental illness is associated with permanent, severe risks and negatively impacting the perception of recovery. This perception is reflected in the interviews and focus groups, where students differentiate between ‘mental health problems’ and ‘mental illness,’ implying that recovery is more achievable for less severe issues and that mental illness carries an assumed permanence.

Overall we found that concerns for a loss of Self sustained a representation of mental illness as Other or ‘not-me’ [ 32 , 40 ]. Concerns for the Self also shaped meaning-making in sub-themata, such that the public largely assumed mental illness to be a permanent negative form of personhood, characterised by abnormality, harm, distance, and immorality [ 11 , 18 , 32 , 40 , 48 , 52 , 53 ], alternative to sustaining positive Self beliefs [ 15 , 54 ]. Mental health-related stigma was in part sustained by latent communications [ 15 , 27 , 33 , 55 ]. Unlike logical decision-making models, people’s understanding of mental illness wasn't about having complete knowledge or no understanding at all. Instead, it was naturally shaped by their social identity and their perceptions of how society is organized [ 15 , 54 ]. The novel theoretical-methodological approach, centering on themata, underscored selective absences [ 27 ] and the differentiation between 'types' of mental illness [ 32 , 40 ]. These ambiguities played a significant role in enabling people to resist acknowledging the similarities between comprehensible forms of public psychological distress and mental illness. Yet, the differences between the Self and the Other were insecure. The negative feelings related to contact probably stemmed from the public's hidden worries about their own risk of developing mental illness [ 15 , 54 ].

Given the complexity of mental health and illness representations and the tenacity with which the public 'Others' mental illness, we foresee limited value in continued focus on refining abstract and generic educational models for change. Researchers have commonly responded to the limited effects of knowledge-based interventions by recommending alternative curriculums, such as exploring the benefits of continuum and/or social models of mental health and illness, and emphasizing recovery [ 3 , 10 , 56 ]. In the short term, these are likely an advance on the categorical and biomedical models that dominate anti-stigma efforts, especially in lower- and middle-income countries [ 1 , 2 , 16 ]. However, since stigma is so ingrained in the largely intuitive process of developing understanding and is linked to negative affects in the Self [ 32 ], there is little evidence to support the continuation of knowledge-based strategies for change. Moreover, students with more exposure to professional knowledge concerning mental illness, such as those studying psychological and health sciences, who comprised roughly half the sample, were no less stigmatizing than assumed in public health campaigns. Instead of lacking knowledge about mental illness, we found that these students creatively used contemporary mental health-related language (e.g., 'mood') to 'Other' mental illness, sometimes even drawing on professional terminology [ 32 ].

Similarly, our results caution against the current overall preference for social contact as a generic model for change [ 1 , 7 , 26 ]. While it was evident that knowledge-contact beliefs were central to the maintenance of mental health-related stigma, when contact was undesired or felt to be threatening, this motivated the reproduction of a representation of mental illness as 'Other'. While we did find conditional expressions of empathy, these were for individuals who already felt close (e.g., a sister), and overall representations of contact with individuals with experiences of mental illness were negative. Rather than contact being an ingredient for change, attention to themata suggests that people experience contact in such a way that affirms its perceived 'Otherness,' such as by associating mental illness with historically rooted concerns for contagion, violence, and moral degeneration [ 18 , 44 , 49 ], while also holding a self-protective generative function [ 54 ]. We found a Self/Other thema informed representations of contact; through contact, people reproduced a positive social identity as different and distant from individuals with experiences of mental illness, whilst also being cognizant of harm incurred when feeling isolated [ 57 ].

We acknowledge the desire to propose general recommendations to limit the unintended consequences of current educational models and contact-based approaches for anti-stigma change. However, given the diverse and ambivalent ways in which people maintain the ‘otherness’ of mental illness, we argue that themata provides an alternative methodological-theoretical framework to describe in context the latent and varied ways individuals relate to mental illness, and likely has the potential to elucidate the uncertain processes through which change is communicated to oneself and others. This would present a significant change in approach to mental health-related stigma. Rather than assuming mental health-related knowledge is caused by a lack or deficiency in knowledge, it opens the possibility for practitioners to be in sustained communication with the public, continually evaluating possible benefits and unintended consequences throughout the change process.

Instead, of proposing corrections to reduce the unintended consequences of anti-stigma programs, we propose that the researchers should engage with a thoroughly socio-ecological understanding of stigma and employ themata as a theoretical methodological-framework for describing the forms of understanding which groups maintain mental health-related stigma in context. By adopting an ecological approach, we move beyond the uni-directional limitations of previous campaigns. These campaigns predominantly focused on rectifying a perceived deficit in knowledge within a specific area, such as the misconception that mental illness is uncommon (and therefore abnormal). Instead, we acknowledge that the belief in the rarity of mental illness is closely linked to the motivated perception that mental illness is ‘Other’ and not related to oneself.

To do so practitioners may benefit from learning from aligned studies because there has been limited research into the policy implications of public mental health-related themata. Bertoldo & colleagues (2015) presents a pertinent case study. They conducted a longitudinal mixed-method research project to explore how groups developed representations of smart meters during a pilot project [ 58 ]. They found citizens embodied practices towards smart meters themselves, as well as sustainable consumption in general (e.g., public transportation in rural areas), and daily life events were organised through three themata: collective vs. individual (daily life); private (my behaviour) vs. public spheres (others’ behaviours); and consumption: individualist vs. collectivist [ 58 ]. Policymakers could propose ways to respond to current ecological changes and public beliefs and behaviours identified in earlier research [ 58 ]. By iteratively revealing lay themata in their complexity, policymakers could comprehend their citizen’s needs and proactively respond to implementation barriers before a full project rollout [ 58 ]. Moreover, identifying themata supported alternative ways of knowing, in particular, a reconsideration of sustainable consumption from being an individual issue to a societal one [ 58 ].

Exploring the themata through which policymakers themselves comprehend mental health and related stigma may provide a basis to align the ways policymakers comprehend the issue with how the lay public represents it [ 36 , 58 ]. Moreover, themata may support sustainable behaviour change strategies, as themata focus attention on the historically enduring aspects of public understanding, such as representations of Otherness [ 33 , 39 , 41 ], and support solutions responsive to the ambiguities present in public understanding [ 39 , 41 ], rather than developing solutions responsive to just one theme (e.g., responsibility in the first stage of the Time-to-Change Campaign). This could hopefully foreground communications which promote public trust that challenging mental health-related stigma does not challenge positive in-group forms of social identity [ 7 ], a possible innovation in challenging the motivations that sustain representations of Otherness and reproduce mental health-related stigma in society [ 1 , 33 ]. Furthermore, we should highlight the direction of travel in British universities' approach to mental health and illness [ 59 ]. Whole-university approaches are being advanced in higher education systems, emphasizing the need to consider the university as a site for the reproduction of psychological distress beyond individual clinical symptoms [ 59 ]. Although, to our knowledge, none have specifically piloted themata as a means of stigma alleviation in the university context, these approaches are aligned in their emphasis on the need for socio-ecological approaches to mental health and illness and the centrality of communication processes [ 59 ].

Anti-stigma social and behavioural change strategies would likely benefit from paying greater attention to public communication patterns and the vital role themata have in constraining and generating ways of knowing mental health and illness.

In this study, mental health and illness was represented in a way which sustained positive Self and in-group representations. We found public Self/Other dialogues to motivate and constrain comprehension, such that representations of mental illness were characterised by abnormality, harm, immorality, distance, and permanence. Our research also showed that these views can be inconsistent. Rather than expressing coherent explanations for the perceived differences between themselves and mental illness, we found people used ambiguity and absence of Other mental illnesses.

Unfortunately, our focus on latent aspects of communication found little to recommend continuing dominant change strategies. Indeed, the felt need to Other was likely instinctive [ 9 , 10 ], and education and contact-based strategies suffer profound issues in problem conceptualisation [ 1 ]. We hope that our exploration into lay mental health-related themata will provide practitioners with an alternative basis for addressing public understanding and, in particular, support them in challenging the identity protective functions of stigma.

Availability of data and materials

No datasets were generated or analysed during the current study.

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Research supported by King’s College London Ph.D. Stipend (K1891793). The funder had no specific role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.

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Conceptualization, D.W. and J.F.; methodology, D.W. and J.F.; software, D.W.; validation, D.W. and J.F.; formal analysis, D.W. and J.F.; investigation, D.W. and J.F.; resources, D.W. and J.F.; data curation, D.W. and J.F.; writing—original draft preparation, D.W.; writing—review and editing, D.W. and J.F.; visualization, D.W.; supervision, J.F.; project administration, D.W. and J.F. All authors have read and agreed to the published version of the manuscript.

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Walsh, D., Foster, J. Understanding the public stigma of mental illness: a mixed-methods, multi-level, exploratory triangulation study. BMC Psychol 12 , 403 (2024). https://doi.org/10.1186/s40359-024-01887-3

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Typed Versus Handwritten Lecture Notes and College Student Achievement: A Meta-Analysis

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• Abraham E. Flanigan   ORCID: orcid.org/0000-0002-2874-4824 1 ,
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Many college students prefer to type their lecture notes rather than write them by hand. As a result, the number of experimental and quasi-experimental studies comparing these two note-taking mediums has flourished over the past decade. The present meta-analytic research sought to uncover trends in the existing studies comparing achievement and note-taking outcomes among college students. Results from 24 separate studies across 21 articles revealed that taking and reviewing handwritten notes leads to higher achievement (Hedges’ g  = 0.248; p  < 0.001), even though typing notes benefits note-taking volume (Hedges’ g  = 0.919; p  < 0.001), among college students. Furthermore, our binomial effect size display shows that taking handwritten lecture notes is expected to produce higher course grades than typing notes among college students. We conclude that handwritten notes are more useful for studying and committing to memory than typed notes, ultimately contributing to higher achievement for college students.

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Flanigan, A.E., Wheeler, J., Colliot, T. et al. Typed Versus Handwritten Lecture Notes and College Student Achievement: A Meta-Analysis. Educ Psychol Rev 36 , 78 (2024). https://doi.org/10.1007/s10648-024-09914-w

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Branches of Psychology

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Psychology is a science in which behavioral and other evidence is used to understand the mind and behavior of humans (Eysenck, 2004).

It encompasses various aspects of human behavior, such as thought, emotions, cognition, personality, social behavior, and brain function.

Throughout the years, people have used multiple research methods to understand this complicated subject, and have divided this subject into various branches to better study human behavior. So far, there can be as many as 22 branches of psychology.

To better categorize the branches of psychology, this article will be dividing the branches into basic and applied psychology (Guilford & Anastasi, 1950).

• Basic psychology, or theoretical psychology, aims to extend and improve human knowledge. Basic psychology aims to discover or establish instances of universal similarity and trace their origin or development to explain their causal connections.
• Applied psychology, or practical psychology, aims to extend and improve the condition and phases of human life and conduct. Its goal is to analyze responses and situations and create interventions to address real-life concerns and challenges individuals face (Thomas, 2022).

However, it is crucial to remember that psychology classification could vary, and many psychologists work in both basic and applied psychology sections throughout their careers.

Moreover, basic and applied fields of psychology complement one another, and together help form a deeper understanding of human mind and behavior.

Basic Psychology

Basic psychology seeks to understand the fundamental principles of behavior and mind, focusing on generating knowledge. It seeks to answer the question “Why does this occur?”.

1. Biological psychology

The origin of biological psychology is greatly influenced by “Origin of Species” written by Charles Darwin, whose views on evolution greatly impacted the psychological world.

Psychologists started analyzing the role of heredity in influencing human behavior. Biological psychology focuses on studying physiological processes within the human body, often including the study of neurotransmitters (chemical messengers that transmit messages from one neuron to the next) and hormones.

One approach used in biological psychology is studying how different sets of genes influence behavior, personality, and intelligence.

Twin studies – the study of monozygotic twins with the exact set of genes and the study of dizygotic twins who share half of each other’s genomes – are often used for this purpose.

The biological branch of psychology is especially important because processes studied by it are virtually involved in almost all human behavior (Eysenck, 2004).

2. Abnormal psychology

Abnormal psychology is also known as psychopathology . It focuses on understanding the causes, treatment, and nature of mental disorders, and helps produce effective therapy for patients who have mental disorders, such as Major Depressive Disorder, Autism, Schizophrenia, and much more (Hooley et al., 2019).

This is considered basic psychology because understanding the etiology of a mental health condition can help applied psychologists develop effective interventions.

In the past, the treatment of people who deviated from the norm involved brutal treatments such as trephination and exorcism that aimed to “drive away” the evil spirits that people claimed to be possessing the ill.

Patients were kept in the bedlams inside asylums, and most people with mental illness died tragically. The development of psychoanalysis , CBT , and mindfulness-based therapies , has led to improvements in therapy and reduced the pain and suffering of patients (Eysenck, 2004).

3. Cognitive Psychology

The study of cognitive psychology focuses on the process of thinking. It includes areas such as memory, problem-solving, learning, attention, and language.

This approach to psychology is important because the human brain is tied to multiple other branches of psychology, such as social, abnormal, and developmental psychology. 

Theoretical topics of cognitive psychology would include the study of memory, perception, attention, etc.

Moreover, the insights provided by cognitive psychologists have led to profound impacts on the development of practical applications across diverse fields, whereby professionals from unrelated domains effectively utilized this knowledge to create things such as computer and gaming systems that are easy for humans to use.

The study of cognitive psychology also benefited the well-being of many patients who experienced brain damage , and they were able to get surgery to regain back some of their lost cognitive skills (Eysenck, 2004).

4. Developmental Psychology

Developmental psychology studies how individuals change over time, especially during the childhood period.

Psychologists spend decades studying people’s childhood development of thinking processes and behavioral changes, looking at how childhood experiences may impact adult behavior.

It includes topics such as the physical, cognitive, emotional, and social changes that occur from infancy to elderly life.

This branch is essential to helping children develop good social skills and address developmental challenges, as well as understanding factors influencing adult behaviors (Eysenck, 2004).

5. Behavioral Psychology

Behaviorism , also known as behavioral learning theory, is a theoretical perspective in psychology that emphasizes the role of learning and observable behaviors in understanding human and animal actions.

Behaviorism is a theory of learning that states all behaviors are learned through conditioned interaction with the environment. Thus, behavior is simply a response to environmental stimuli.

The behaviorist theory is only concerned with observable stimulus-response behaviors, as they can be studied in a systematic and observable manner.

Some of the key figures of the behaviorist approach include B.F. Skinner, known for his work on operant conditioning, and John B. Watson, who established the psychological school of behaviorism.

6. Social Psychology

Social psychology covers numerous topics that focus on society as a whole, including the observation and study of social behavior and intergroup relations.

Topics would include things such as the study of attitudes , social influences , prejudice , etc. Humans are known to be social animals that interact with one another.

Every day we encounter different people and must use social knowledge to make sense of the social group that we are all living in and make decisions.

Social psychology is thus used to reveal the many biases and misconceptions humans have, as well as how people’s behaviors are deeply influenced by one another (Eysenck, 2004).

7. Comparative Psychology

Comparative psychology is the study of similarities and differences between humans and animals. It is said to be originated by George Romanes, a British psychologist who wrote “Animal Intelligence” in 1882.

In short, it compares humans with other animals, including both qualitative and quantitative observations. 

It is especially useful to use animal models to study behaviors and psychological phenomena because they may otherwise be challenging or unethical to study in humans.

Animal models provide researchers with a way to examine the effects of stress, addiction, learning, and memory on behavior.

Since animals may function in similar ways as humans, psychologists study animals and draw analogies with human beings to arrive at conclusions (Greenberg, 2012). Famous studies of comparative psychology would include Harlow’s monkeys and Lorenz’s geese .

8. Experimental Psychology

Experimental psychology encompasses the scientific research methods that other branches of psychology rely on. Psychologists use a scientific approach to understanding behavior, and their findings are based on scientific evidence accumulated through research.

Examples of what is involved in an experiment would be the different types of research methods (qualitative versus quantitative), the use of data analysis, correlation and causation, and hypothesis testing.

It is generally said to emerge as a branch of psychology in the 19 th century led by Wilhelm Wundt , who introduced mathematical expressions and calculations into the psychology field (Boring, 1950).

This is important because humans’ commonsense beliefs about behaviors are unreliable, and the explanations derived from them could be deceiving.

Experimental psychology ensures that psychological conclusions are not limited in their accuracy and generalizability (Myers & Hansen, 2011).

9. Child Psychology

Child psychology examines the developmental changes within the different domains of child development (Hetherington et al., 1999).

It first started with Jean Piaget , a French psychologist whose research interests were highly focused on child development, including how they think, acquire knowledge, and interact with those around them (Schwartz, 1972). 

It primarily focuses on the understanding of children’s emotional, cognitive, social, and behavioral development during these early stages of life.

Child psychology also assesses and diagnoses developmental disorders or psychological conditions that may affect children and provide interventions and treatments to support their psychological well-being and development.

10. Cross-Cultural Psychology

Cross-Cultural Psychology is a branch of psychology that studies how cultural factors influence human behavior, thoughts, and emotions.

It examines psychological differences and similarities across various cultures and ethnic groups, aiming to understand how cultural context can shape individual and group psychological processes.

11. Personality Psychology

The personality branch of psychology studies the patterns of thoughts, feelings, and behaviors that make an individual unique. It explores the traits and characteristics that define a person’s temperament, interactions, and consistent behaviors across various situations.

Theories in this field range from Freud’s psychoanalytic perspective to trait theories and humanistic approaches.

The goal is to understand the complexities of individual differences, the factors that shape personality development, and how personality influences life outcomes.

The Big Five and Myers-Briggs are both models used to describe and measure personality traits, but they differ significantly in their origins, components, and scientific validation:

• The Big Five : Often referred to as the Five-Factor Model, it identifies five broad dimensions of personality: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism (often remembered by the acronym OCEAN). This model is backed by extensive empirical research and is widely accepted in the academic community.
• Myers-Briggs Type Indicator (MBTI) : This typological approach categorizes individuals into 16 personality types based on four dichotomies: Extraversion/Introversion, Sensing/Intuition, Thinking/Feeling, and Judging/Perceiving.

Applied psychology

Applied psychology takes these foundational understandings and applies them to solve real-world problems, enhancing well-being and performance in various settings. Applied psychology asks “How can we use this knowledge practically?”.

12. Clinical Psychology

The American Psychological Association defines clinical psychology as a field of psychology that “integrates science, theory, and practice to understand, predict, and alleviate maladjustment, disability, and discomfort as well to promote human adaptation, adjustment, and personal development” (American Psychological Association, Division 12, 2012).

In simplified terms, it is a branch of psychology focusing on understanding mental illness and looking for the best ways of providing care for individuals, families, and groups.

Through strong research, clinical psychologists offer ongoing and comprehensive mental and behavioral healthcare for individuals, couples, families, and all sorts of different groups.

They also provide consultation services to agencies and communities, as well as training, education, supervision, and research-based practice.

The work of a clinical psychologist thus includes assessing patients’ health status, performing psychotherapy, teaching, researching, consulting, and more (Kramer et al., 2019). The branch would also understand the diagnostic criteria of mental illness.

13. Educational Psychology

Educational psychology is a branch of psychology that focuses on understanding how people learn and develop in educational settings.

It uses psychological science to enhance the learning process of students and applies psychological findings to promote educational success in a classroom (Lindgren & Suter, 1967).

Educational psychologists do things such as improve teaching techniques, develop specialized learning materials, and monitor educational outcomes.

Psychologists have argued that education is a tripolar process involving the interaction between the educator and the student, as well as the educator and the student understanding oneself and acting accordingly in an educational or social setting.

The social environment, on the other hand, provides subtle influences on both sides. Educational psychology aims to understand and enhance education through understanding these interactions (Aggarwal, 2010).

Under this branch of psychology, there is also school psychology. School psychology is defined as the general practice of psychology involving learners of all ages, and the process of schooling.

For instance, psychological assessments, interventions, and preventions, as well as mental health promotion programs focusing on the development processes of youth in the context of the school system are all considered to be part of school psychology.

School psychologists access the school environment to ensure and promote positive learning outcomes for youth, and ensure healthy psychological development of students.

Other than students, they also support the families, teachers, and other professionals who work to support the students (Merrell et al., 2011).

14. Counseling Psychology

Counseling psychology is defined as a holistic healthcare specialty that employs diverse information (such as culture) and methodologies (such as motivational interviewing and cognitive behavioral therapy) to enhance an individual’s mental well-being and reduce maladaptive behaviors.

The aim is to help individuals cope with various life challenges, emotions, mental health symptoms, etc. People who seek counseling explore their thoughts and behaviors with a counselor and seek to improve their wellbeing and develop coping strategies.

Counseling psychologists work with people of all cultural backgrounds, and conduct activities such as crisis intervention, trauma management, diagnosing mental disorders, treatment evaluation, and consulting (Oetting, 1967).

15. Forensic Psychology

Forensic psychology is the branch of applied psychology that focuses on collecting, examining, and presenting evidence for judicial purposes.

Psychologists in this branch work on court cases in assessing behavioral problems and psychological disorders in criminal profiles , determining the mental status of criminals, and whether or not compensation could be awarded for “psychological damage”.

Researchers in this branch also investigate false confessions and psychological vulnerabilities in criminals, together with methods of improving societal bias and police practice (Gudjonsson & Haward, 2016).

16. Health Psychology

Health psychology has been widely defined using Matarazzo’s definition, summarized as any activity of psychology that involves any aspect of health or the healthcare system.

It includes areas ranging from prevention to treatment of illness and the analysis and diagnosis of health-related dysfunctions. It often promotes healthy lifestyles and disease prevention.

Health psychology emphasizes the health system and how patients as well as psychologists interact within the system, having the goal of optimizing communication and treatment at the same time.

Health psychologists look at problems such as the cost of healthcare, chronic psychological illness, as well as political and economic needs (Feuerstein et al., 1986).

This is different from clinical psychology, which concentrates more on treating and diagnosing mental, emotional, and behavioral disorders, providing therapy and strategies for managing mental health issues.

17. Sports Psychology

Sports psychology is in general seen as a field of study where principles of psychology are used or applied to sport. In history, many different perspectives have been taken in determining the definition of sports psychology.

For example, when seen as a branch of psychology, this study focuses on understanding psychological theories when applied to sports.

When seen more as a subdiscipline of sport science, this branch of psychology focuses on enhancing and explaining behavior in the sports context (Horn, 2008).

Overall, sports psychology is crucial in optimizing athletes’ performance by addressing their sports’ emotional and physical aspects, such as arousal regulation, pre-performance routines, goal-setting techniques, etc.

18. Community Psychology

Community psychology focuses on thinking about human behavior within the context of a community.

It requires a shift in perspective since it operates to prevent a problem from occurring and promoting healthy functioning for the community rather than treating individual problems after they arise.

Research under this branch examines factors on the macro neighborhood and community level that either enhances or impedes the psychological health of a community rather than internal psychological processes of an individual (Kloos, 2012).

19. Industrial-organizational psychology

Industrial-organizational psychology is the branch of psychology that studies how principles of psychology act on human beings who are operating within the business and industry context.

The definition has evolved over time to include more wide-ranged work-related topics, and looks at interactions between people and institutions.

Psychologists in this field center around enhancing productivity, staff well-being, and organizational work performance.

They utilize scientific methodologies and concepts to tackle workplace predicaments such as staff recruitment, training, appraisal, inspiration, job contentment, and workplace culture (Forces, 2003).

20. Family Psychology

Family psychology is considered a clinical science that focuses on discovering the truth behind families and the individuals inside them while improving the well-being of families.

It includes research in biological systems such as how genetics contributes to mental disorders and larger scopes of how community resources could be used to strengthen family relationships.

Through understanding family dynamics and supporting family relationships, this branch of psychology helps families navigate the complexities that arise in their relationships, promoting healthy relationships and overall wellbeing (Pinsof & Lebow, 2005).

21. Media Psychology

Media psychology refers to the use of psychology in the usage and production of media.

It includes areas such as making new technologies more user-friendly, using media to enhance clinical psychology, and studying how media may contribute to sociological and psychological phenomena in society (Luskin & Friedland, 1998).

The field has also evolved to include more emerging technologies and applications, such as interactive media, internet, and video games.

22. Environmental Psychology

Environmental psychology looks at the interrelationship between human behavior and environments. It examines how people’s behavior, emotions, and well-being are influenced by natural and built surroundings, such as homes, workplaces, urban spaces, and natural landscapes.

With models in the psychological field in mind, environmental psychologists work to protect, manage, and design environments that enhance human behavior, and diagnose any problems that occur in the process.

Some common topics have included the effects of environmental stress on human performance and how humans process information in an unfamiliar environment (De Young, 1999).

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