descriptive research design is also known as

Demystifying the research process: understanding a descriptive comparative research design

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Demystifying the research process often involves understanding research terminology, the rationale for the selection of a research design, and the known benefits and consequences in the selection of a design. This commentary discusses the major aspects of a well-known and used quantitative research design in nursing research used by Tourigny, Clendinneng, Chartrand, and Gaboury (2011) to evaluate the utility of a virtual education tool for pediatric patients undergoing same-day surgery. The rationale for why this design was chosen by these nurse researchers and its advantages and disadvantages are discussed.

A research design is the overall plan for answering research questions and hypotheses. The design spells out strategies the researcher adopts to gather accurate, objective, and interpretable information (Polit & Beck, 2007). Tourigny et al. (2011) used a non-experimental, quantitative research design known as a descriptive, comparative design. It is also known as casual comparative research and pre-experimental research. The basic purpose of these designs is to determine the relationship among variables. The most important distinctions between these designs and experimental designs are no control (manipulation) of the independent variable (IV) and no random assignment of study subjects to the intervention or control group. These designs are frequently used in nursing research studies because nurse researchers are often faced with these specific limitations.

In summary, the known properties of descriptive, comparative research studies are 1) no manipulation of an independent variable, 2) no random assignment to groups, and 3) often inclusion of a control or comparison group. The paradigm for these studies is diagrammed in Figure 1.

In this diagram (see Figure 1), the researcher hypothesizes that "X" is related to and a determinant (cause) of "Y," but the presumed causes are not manipulated, and subjects are not randomly assigned to groups (LoBiondo-Wood & Haber, 2010). Rather, a group of subjects who has experienced "X" in a natural situation is located, and a control group of subjects who has not experienced "X" is chosen. The behavior performance or condition of the two groups is compared to determine whether the exposure to "X" had an effect predicted by the hypothesis (LoBiondo-Wood & Haber, 2010). Tourigny et al. (2011) hypothesized a determinant of study participants' level of knowledge about hospital equipment and procedures, and their emotional state would differ based upon whether or not they viewed the Surgery Virtual Tour presentation. In this study, the exposed group resulted from participants choosing to view the Surgery Virtual Tour. These researchers then compared this group with a group at the same institution who did not view the Surgery Virtual Tour presentation.

Tourigny et al. (2011) noted that the Surgery Virtual Tour was posted on the hospital's Web site and available to all children, adolescents, and parents being cared for at this institution. Thus, these researchers had no control over which study participants viewed or did not view the educational program. Prohibiting access of this educational program to some participants for the purposes of conducting this research study would have violated these children's, adolescents', and parents' ethical right to fair treatment. The right to fair treatment is based on the ethical principle of justice that each person should be treated fairly and should receive what he or she is due or owed (Burns & Grove, 2005).

An important criterion in determining a research design's rigor is its potential to generate findings that are interpretable. The term interpretable relates to the credibility and dependability of data generated by a study, and is based on the study's design to sufficiently test "cause and effect" relationships. The term "causality" implies that a systematic relationship exists between the independent variable (IV), which is the "cause" or intervention of the study design, and the dependent variable(s) (DV) or the outcome(s) of the study. In other words, confidence that the outcome of a research study is a consequence of the effects of the intervention must exist.

There are three criteria for causality: 1) the cause (the IV) must precede the effect (the DV) in time, such that the IV had to occur before the DV); 2) an empirical relationship exists between the IV and DV, meaning that a relationship that is measurable must exist between the presumed cause and effect; and 3) the relationship between the IV and DV cannot be explained by a third variable. Of these three criteria, researchers are most concerned about ensuring results of their study are due to the experimental treatment and not due to the characteristics of the subjects or other competing explanations for the results. Characteristics of the subjects or other competing explanations are known as internal validity threats.

There are several limitations in the design used by Tourigny et al. (2011) that threaten the confidence in their study's findings, specifically having no control over the internal validity and characteristics of the subjects influencing the outcome of the study. The internal validity threat due to characteristics of the subjects is known as selection bias and is always a threat if random assignment to groups does not occur. Researchers are cautioned to be aware that when intact groups are compared, differences existing between the two groups before the start of the experiment could have affected the outcome of the study. People "self-select" to a group based on personal characteristics and preferences, and these personal characteristics and preferences can influence the outcome of a study. Tourigny et al. (2011) addressed this potential threat operating in their study's findings by measuring selected differences in sociodemographic variables that could have accounted for dissimilarities between the groups. There were no significant differences in socio-demographic variables between participants who viewed or did not view the Virtual Tour, with the exception that families who took the Tour were more likely to have access to the Internet at home (Tourigny et al., 2011). These findings provide some evidence that these socio-demographic variables can be ruled out as internal validity threats operating in this study; however, it remains unknown if characteristics not measured by Tourigny and colleagues could be operating as threats to the study's interal validity. It is not feasible to measure an exhaustive list of socio-demographic characteristics that could pose every possible internal validity threat related to study participants' characteristics, but researchers carefully select known factors from previous studies and their clinical experiences as was done by Tourigny et al.

Another strategy used by Tourigny et al. (2011) to increase the internal validity of their study was to establish inclusion and exclusion criteria to determine the study's sample. Inclusion and exclusion criteria are guidelines or the standards determining who can or cannot be in the study. Population descriptors, also known as important characteristics of a population, are criteria that set the standards. These characteristics can also operate as internal validity threats in a study. In their study, Tourigny et al. identified the inclusion criteria for their study as only allowing children and adolescents 6 to 18 years of age, able to understand or read and write in English, be at a schoolage cognitive level, and who gave an assent or written consent to be in the study. They also excluded children with any developmental or physical state that could prevent them from completing the questionnaires. These criteria placed more control over potential internal validity threats operating in the study, but as a consequence of doing so, the external validity of the study's findings was decreased. External validity addresses the ability to generalize the findings of the study to other groups. The findings generated by Tourigny et al. are not generalizable to children younger than 6 years, who are unable to understand or read and write in English, are not at a school-age cognitive level, or have a developmental or physical impairment. Internal and external validity have an inverse relationship; the more internal validity control a study design employs, the more likely its external validity will be limited.

In summary, Tourigny and colleagues (2011) selected a feasible research design; its implementation protected research participants' ethical rights, tested the identified intervention, and generated interpretable findings. A researcher's choice in selecting a research design is dependent on many factors, and researchers usually make conscious decisions in their selection to augment some aspects of rigor in their study while foregoing others. Selection of a research design requires creativity to maximize interpretable findings within known limitations in conducting the investigation.

Burns, S., & Groves, S.K. (2004). Understanding nursing research (3rd ed.). Philadelphia: Saunders.

LoBiondo-Wood, G., & Haber, J. (2010). Nursing research: Methods and critical appraisal for evidence-based practice (7th ed.). St. Louis, MO: Elsevier.

Polit, D.F., & Beck, C.T. (2007). Nursing research: Generating and assessing evidence for nursing practice (8th ed.). Philadelphia: Lippincott Williams & Wilkins.

Figure 1 . Seeing a police car behind you would probably affect your driving behavior. (credit: Michael Gil)

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 1).

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 2). 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).

Figure 2 . (a) Jane Goodall made a career of conducting naturalistic observations of (b) chimpanzee behavior. (credit “Jane Goodall”: modification of work by Erik Hersman; “chimpanzee”: modification of work by “Afrika Force”/Flickr.com)

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 handwashing 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.

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 3). 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.

Figure 3 . Surveys can be administered in a number of ways, including electronically administered research, like the survey shown here. (credit: Robert Nyman)

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 module: 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).

Archival Data and Case Studies

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students (Figure 4).

Figure 4 . A researcher doing archival research examines records, whether archived as a (a) hardcopy or (b) electronically. (credit “paper files”: modification of work by “Newtown graffiti”/Flickr; “computer”: modification of work by INPIVIC Family/Flickr)

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.

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A good test will aid researchers in assessing a particular psychological construct. What is a good test? Researchers want a test that is standardized, reliable, and valid. A standardized test is one that is administered, scored, and analyzed in the same way for each participant. This minimizes differences in test scores due to confounding factors, such as variability in the testing environment or scoring process, and assures that scores are comparable. Reliability refers to the consistency of a measure. Researchers consider three types of consistency: over time (test-retest reliability), across items (internal consistency), and across different researchers (interrater reliability). Validity is the extent to which the scores from a measure represent the variable they are intended to. When a measure has good test-retest reliability and internal consistency, researchers should be more confident that the scores represent what they are supposed to.

There are various types of tests used in psychological research. Self-report measures are those in which participants report on their own thoughts, feelings, and actions, such as the Rosenberg Self-Esteem Scale or the Big Five Personality Test. Some tests measure performance, ability, aptitude, or skill, like the Stanford-Binet Intelligence Scale or the SATs.There are also tests that measure physiological states, including electrical activity or blood flow in the brain.

Video 2.  Methods of Data Collection  explains various means for gathering data for quantitative and qualitative research. A closed-captioned version of this video is available here .

Studying Changes over Time

Sometimes, especially in developmental research, the researcher is interested in examining changes over time and will need to consider a research design that will capture these changes. Remember,  research methods  are tools that are used to collect information, while r esearch design  is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how. There are three types of developmental research designs: cross-sectional, longitudinal, and sequential.

Video 3.  Developmental Research Designs

Cross-Sectional Design

The majority of developmental studies use cross-sectional designs because they are less time-consuming and less expensive than other developmental designs.  Cross-sectional research  designs are used to examine behavior in participants of different ages who are tested at the same point in time. Let’s suppose that researchers are interested in the relationship between intelligence and aging. They might have a hypothesis that intelligence declines as people get older. The researchers might choose to give a particular intelligence test to individuals who are 20 years old, individuals who are 50 years old, and individuals who are 80 years old at the same time and compare the data from each age group. This research is cross-sectional in design because the researchers plan to examine the intelligence scores of individuals of different ages within the same study at the same time; they are taking a “cross-section” of people at one point in time. Let’s say that the comparisons find that the 80-year-old adults score lower on the intelligence test than the 50-year-old adults, and the 50-year-old adults score lower on the intelligence test than the 20-year-old adults. Based on these data, the researchers might conclude that individuals become less intelligent as they get older. Would that be a valid (accurate) interpretation of the results?

Figure 5. Example of cross-sectional research design

No, that would not be a valid conclusion because the researchers did not follow individuals as they aged from 20 to 50 to 80 years old. One of the primary limitations of cross-sectional research is that the results yield information about age  differences  not necessarily  changes  over time. That is, although the study described above can show that the 80-year-olds scored lower on the intelligence test than the 50-year-olds, and the 50-year-olds scored lower than the 20-year-olds, the data used for this conclusion were collected from different individuals (or groups). It could be, for instance, that when these 20-year-olds get older, they will still score just as high on the intelligence test as they did at age 20. Similarly, maybe the 80-year-olds would have scored relatively low on the intelligence test when they were young; the researchers don’t know for certain because they did not follow the same individuals as they got older.

With each cohort being members of a different generation, it is also possible that the differences found between the groups are not due to age, per se, but due to cohort effects. Differences between these cohorts’ IQ results could be due to differences in life experiences specific to their generation, such as differences in education, economic conditions, advances in technology, or changes in health and nutrition standards, and not due to age-related changes.

Another disadvantage of cross-sectional research is that it is limited to one time of measurement. Data are collected at one point in time, and it’s possible that something could have happened in that year in history that affected all of the participants, although possibly each cohort may have been affected differently.

Longitudinal Research Design

Longitudinal research designs are used to examine behavior in the same individuals over time. For instance, with our example of studying intelligence and aging, a researcher might conduct a longitudinal study to examine whether 20-year-olds become less intelligent with age over time. To this end, a researcher might give an intelligence test to individuals when they are 20 years old, again when they are 50 years old, and then again when they are 80 years old. This study is longitudinal in nature because the researcher plans to study the same individuals as they age. Based on these data, the pattern of intelligence and age might look different than from the cross-sectional research; it might be found that participants’ intelligence scores are higher at age 50 than at age 20 and then remain stable or decline a little by age 80. How can that be when cross-sectional research revealed declines in intelligence with age?

Figure 6. Example of a longitudinal research design

Since longitudinal research happens over a period of time (which could be short term, as in months, but is often longer, as in years), there is a risk of attrition.  Attrition  occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, die, or simply become disinterested in participating over time. Researchers should account for the possibility of attrition by enrolling a larger sample into their study initially, as some participants will likely drop out over time. There is also something known as  selective attrition— this means that certain groups of individuals may tend to drop out. It is often the least healthy, least educated, and lower socioeconomic participants who tend to drop out over time. That means that the remaining participants may no longer be representative of the whole population, as they are, in general, healthier, better educated, and have more money. This could be a factor in why our hypothetical research found a more optimistic picture of intelligence and aging as the years went by. What can researchers do about selective attrition? At each time of testing, they could randomly recruit more participants from the same cohort as the original members to replace those who have dropped out.

The results from longitudinal studies may also be impacted by repeated assessments. Consider how well you would do on a math test if you were given the exact same exam every day for a week. Your performance would likely improve over time, not necessarily because you developed better math abilities, but because you were continuously practicing the same math problems. This phenomenon is known as a practice effect. Practice effects occur when participants become better at a task over time because they have done it again and again (not due to natural psychological development). So our participants may have become familiar with the intelligence test each time (and with the computerized testing administration).

Another limitation of longitudinal research is that the data are limited to only one cohort. As an example, think about how comfortable the participants in the 2010 cohort of 20-year-olds are with computers. Since only one cohort is being studied, there is no way to know if findings would be different from other cohorts. In addition, changes that are found as individuals age over time could be due to age or to time of measurement effects. That is, the participants are tested at different periods in history, so the variables of age and time of measurement could be confounded (mixed up). For example, what if there is a major shift in workplace training and education between 2020 and 2040, and many of the participants experience a lot more formal education in adulthood, which positively impacts their intelligence scores in 2040? Researchers wouldn’t know if the intelligence scores increased due to growing older or due to a more educated workforce over time between measurements.

Sequential Research Design

Sequential research  designs include elements of both longitudinal and cross-sectional research designs. Similar to longitudinal designs, sequential research features participants who are followed over time; similar to cross-sectional designs, sequential research includes participants of different ages. This research design is also distinct from those that have been discussed previously in that individuals of different ages are enrolled into a study at various points in time to examine age-related changes, development within the same individuals as they age, and to account for the possibility of cohort and/or time of measurement effects

Consider, once again, our example of intelligence and aging. In a study with a sequential design, a researcher might recruit three separate groups of participants (Groups A, B, and C). Group A would be recruited when they are 20 years old in 2010 and would be tested again when they are 50 and 80 years old in 2040 and 2070, respectively (similar in design to the longitudinal study described previously). Group B would be recruited when they are 20 years old in 2040 and would be tested again when they are 50 years old in 2070. Group C would be recruited when they are 20 years old in 2070, and so on.

Figure 7. Example of sequential research design

Studies with sequential designs are powerful because they allow for both longitudinal and cross-sectional comparisons—changes and/or stability with age over time can be measured and compared with differences between age and cohort groups. This research design also allows for the examination of cohort and time of measurement effects. For example, the researcher could examine the intelligence scores of 20-year-olds at different times in history and different cohorts (follow the yellow diagonal lines in figure 3). This might be examined by researchers who are interested in sociocultural and historical changes (because we know that lifespan development is multidisciplinary). One way of looking at the usefulness of the various developmental research designs was described by Schaie and Baltes (1975): cross-sectional and longitudinal designs might reveal change patterns while sequential designs might identify developmental origins for the observed change patterns.

Since they include elements of longitudinal and cross-sectional designs, sequential research has many of the same strengths and limitations as these other approaches. For example, sequential work may require less time and effort than longitudinal research (if data are collected more frequently than over the 30-year spans in our example) but more time and effort than cross-sectional research. Although practice effects may be an issue if participants are asked to complete the same tasks or assessments over time, attrition may be less problematic than what is commonly experienced in longitudinal research since participants may not have to remain involved in the study for such a long period of time.

Comparing Developmental Research Designs

When considering the best research design to use in their research, scientists think about their main research question and the best way to come up with an answer. A table of advantages and disadvantages for each of the described research designs is provided here to help you as you consider what sorts of studies would be best conducted using each of these different approaches.

Table 1.  Advantages and disadvantages of different research designs

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Descriptive Research Design

• September 29, 2021

Voxco’s Descriptive Research guide helps uncover the how, when, what, and where questions in a research problem

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When conducting a study, researchers generally try to find an explanation for the existence of a phenomenon. They want to understand “why” the phenomenon occurred. 

However, before identifying why a phenomenon occurred, it is integral to answer other questions first. You need to have answers to the “what,” “when,” “how,” and “where” before you can understand the “why.” This is where descriptive research comes in.

The descriptive research design involves using a range of qualitative and quantitative research methods to collect data that aids in accurately describing a research problem.

What is Descriptive Research Design?

Descriptive research design is a type of research design that aims to systematically obtain information to describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem rather than the why. 

A researcher can conduct this research using various methodologies. It predominantly employs quantitative data, although qualitative data is sometimes used for descriptive purposes. 

It is important to note that in the descriptive research method, the researcher does not control or manipulate any variables, unlike in experimental research. Instead, the variables are only identified, observed, and measured. 

Surveys and observation are the most used method to conduct this research design. You can leverage online survey tools or offline survey tools to gather data as per your research objective.

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What are the Characteristics of Descriptive Research Design?

Let’s take a look at the defining characteristics of the descriptive research design:

1. Quantitative in nature 

Descriptive research involves the collection of quantifiable and systematic data that can be used for the statistical analysis of the research problem. 

2. Uncontrolled variables

One of the most prominent characteristics of descriptive research is that, unlike in experimental research, the variables are not controlled or manipulated. Instead, they are simply identified, observed, and measured.

3. A basis for further research

The data collected in descriptive research provides a base for further research as it helps obtain a comprehensive understanding of the research question so that it can be answered appropriately. 

4. Cross-sectional studies

The descriptive research method is generally carried out through cross-sectional studies. A cross-sectional study is a type of observational study that involves gathering information on various variables at the individual level at a given point in time.

Example of Descriptive Research Design

To gain a deeper understanding of the descriptive method of research, let’s consider the following descriptive design research example: 

Company XYZ is a girls’ shoe brand catering to girls, specifically between the ages of 4 to 14. 

They want to start selling shoes for boys of the same age group as well and therefore want to gather information on the kind of shoes boys want to wear. They decide to conduct market research & choose the observational method to learn about different shoes boys wear nowadays. 

Naturalistic observation can be conducted by observing boys’ shoes in schools, malls, playgrounds, and other public spaces. 

This will help company XYZ identify the kind of shoe boys wear nowadays so that they can create the kind of products that will appeal to this audience.

Why use Descriptive Research Design?

A descriptive approach to research allows researchers to thoroughly investigate the background of a research problem before further research can be carried out. It can be used in social science research to explore and document the nature and scope of a problem, to identify trends and patterns, and to provide a basis for subsequent research. 

The findings of descriptive research can help inform decision-making, policy development, and program planning.

There are many different contexts in which the use of a descriptive research design is beneficial. Here are some important uses of descriptive research design:

1. To measure data trends 

The descriptive method of research can be used to measure changes in variables over a period of time, allowing trends to be identified and analyzed. 

2. To compare variables

Descriptive research can be used to compare different variables and how different demographics respond to different variables. 

3. To define the characteristics of subjects

It can also be used to determine the different characteristics of the subjects. This can include characteristics such as opinions, traits, behavior, etc. 

4. To verify or validate existing conditions 

Descriptive research can prove to be a useful tool when trying to test the validity of an existing condition as it involves conducting an in-depth analysis of every variable before drawing conclusions.

What Are Some Examples of Descriptive Research Questions?

Here are some examples of descriptive research questions that can be addressed using a descriptive research design include:

• What are the demographic characteristics of a particular population?
• What is the prevalence of a particular health condition or risk factor?
• What are the attitudes and beliefs of a particular group towards a particular issue?
• What are the behaviors and experiences of individuals who have been exposed to a particular intervention or treatment?

What Are the Advantages of Descriptive Research Design?

The following are a few advantages of using a descriptive research design: 

1. Multiple methods of data collection

Research can use a wide range of methods for data collection, such as case studies, observational, and survey methods. They can also decide how they want to collect the data, online, offline, or via phone. 

2. Fast and cost-effective

As the descriptive research design often employs the use of surveys, data can be collected from a very large sample size quickly and cost-effectively. 

Researchers aiming to conduct market research using this research design should leverage integrated market research software . It will enable them to conduct product, customer, brand, and market research using suitable channels. 

3. Comprehensive

Descriptive research often uses quantitative and qualitative research in amalgamation, providing a more holistic understanding of the research topic. 

4. External validity

Results obtained through the descriptive method of research often have high external validity as research is conducted in the respondent’s natural environment and no variables are manipulated.

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What Are the Disadvantages of Descriptive Research Design?

The following are a few disadvantages of using a descriptive research design:

1. Cannot test or verify the research question

The descriptive method of research cannot be used to test or verify the research problem as the data collected does not help explain the cause of the phenomena being studied. 

2. Lack of reliability

If the research problem isn’t formulated well, then the data collected may not be entirely reliable. This also makes it more tedious to carry out a credible investigation. 

3. Risk of untrue responses

Descriptive research relies on the responses of people, especially when conducted using surveys. There may be instances when people provide false responses, compromising the validity of the data collected and the research results. 

4. Risk of sampling error

The descriptive research method generally employs random sampling while selecting a sample group. The randomness may lead to sampling error if the sample group isn’t representative of the larger population. Sampling error would lead to unreliable and inaccurate results.

What Are the Different Methods of Descriptive Research Design?

There are three most important descriptive research design methods:

In survey research, questionnaires or polls are used to collect information on a specific topic from respondents. Surveys should involve a mix of closed-ended and open-ended questions, as both have their own advantages. 

Online survey tools allow multiple data collection channels such as email, website, and SMS surveys. 

They are also popularly used in market research to collect customer feedback to optimize products and strategies and improve customer experience (CX). Some popular market research surveys are Net Promoter Score® (NPS®) surveys , brand tracking surveys , and conjoint analysis surveys . 

2. Case Studies 

The case study method involves the in-depth research of individuals or groups of individuals. Case studies involve gathering detailed data on a narrowly defined subject rather than gathering a large volume of data to identify correlations and patterns. 

Therefore, this method is often used to describe a specific subject’s different characteristics rather than generalizable facts. 

Case studies allow researchers to create hypotheses that can widen the scope of evaluation while studying the phenomenon. However, it is important to note that case studies cannot be used to outline the cause-and-effect relationship between variables as they cannot make accurate predictions due to the risk of researcher bias.

3. Observations method

In this method, researchers observe respondents in their natural environment, from a distance, and therefore do not influence the variables being studied. This allows them to gather information on the behaviors and characteristics being studied without having to rely on respondents for honest and accurate responses. 

The observational method is considered the most effective method for carrying out descriptive research. It involves the collection of both qualitative and quantitative data. You can leverage offline survey tools to gather data digitally, even without the Internet. 

Quantitative observation should be related to or understood in terms of quantity and can be analyzed with the use of statistical data analysis methods. A few examples of quantitative observations include age, weight, height, etc. 

Qualitative observations, on the other hand, involve monitoring variables whose values do not need to be related to numerical measurements. 

When employing this research method, the researcher can choose to be a complete observer, an observer as a participant, a participant as an observer, or a full participant. 

The observational method is generally used in psychological, social, and market research to obtain data that explains how people behave in real-life settings.

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What Are the Types of Descriptive Research Design Surveys?

The following are the different types of descriptive survey studies:

1. Census survey

A census survey is a kind of survey where information is gathered from all units of a population. Data collected through a census study is highly generalizable to the population as all or most units of the population are sampled. 

2. Sample survey 

A sample survey involves gathering information from a small subgroup of the entire population. When selecting a sample, the aim is to select a group of individuals representing the target population so that the data collected can be generalized to the larger population. Sample groups allow research to be conducted in a fast and cost-effective way. 

3. Cross-sectional survey 

In this type of survey, standardized data is collected from a cross-section of the pre-determined population at a given point in time. There are two main types of cross-sectional surveys ; those with a single variable and those with two or more variables. 

4. Longitudinal survey

Longitudinal surveys are used in longitudinal studies where the same variables are observed over a long period of time. This allows researchers to investigate the status of variables at different points in time. There are three main types of longitudinal studies ; trend, panel, and cohort.

5. Comparative survey

Comparative surveys are used to compare the status of two or more variables. The variables are compared using specific criteria that must be delineated as criterion variables. 

6. Evaluative survey

An evaluative survey is generally used to evaluate a program, policy, or curriculum. It involves gathering information that can be used to rate the effectiveness and worthwhileness of a program or policy, or institution. 

7. Documentary survey

A documentary survey involves gathering and analyzing information using pre-existing data that is already available. This data can be research papers, review articles, books, official records, etc. In documentary studies, the researcher evaluates the available literature on the research topic.

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How to Conduct a Descriptive Research Design

Use the following steps to conduct a study using the descriptive method of research:

Step-1: Outline the research objective

The first step is to identify and outline the objectives of your research and then translate these objectives into criteria of investigation. You must clearly identify the different issues and questions in the context of which the knowledge of the situation must be surveyed. 

This must be framed in the form of objectives. Once you’ve clearly stated your criteria and objectives, you must also specify the nature of the data that must be gathered. 

Step-2: Determine the tools and techniques to be used for data collection

In this step, you must determine the tools you will employ for the data collection process. Some examples of different tools that can be used are interviews, questionnaires, observation schedules, reaction scales, etc. 

In this stage, you will have to identify which tools and techniques are relevant and valid to your study. Leverage robust survey software that offers you multiple channels, thus enabling you to utilize various channels to gather insights. 

Step-3: Define​​ the target population and sample group

In the fourth step, you will have to outline your target population. The target population is the group of individuals that you are examining in your research study. Additionally, unless you are conducting a census study and collecting data from the entire population, you must select a sample group.

You can also use an audience panel to accelerate your research. A survey panel gives you access to diverse respondents so you can create your ideal panel. 

Additional read: Types of sampling methods .

Step-4: Select a method for data collection

In the data collection stage, you must have a clear plan of how your data will be collected. This involves clearly outlining the type of data you require, the tools that will be used to gather it, the level of training required by researchers to collect the data, the time required for data collection and fieldwork, and so on. 

As you collect data, keep your research question and objectives in mind and aim to gather authentic and objective data without personal bias. 

Step-5: Analyse the data collected

Once you’ve collected your data, you reach the sixth stage of descriptive research: data analysis. In this stage, you will have to evaluate all the data collected from all your different sources, quantify and qualify them, and then categorize them component-wise. 

If you are working with quantitative and qualitative data, you must employ a range of different quantitative and qualitative analysis techniques to analyze the data collected. 

Leverage survey analytics software that allows you to run statistical analysis and observe data on a live dashboard.  

Step-6: Write the report

The final step of survey research involves writing the report. As survey research involves working with extensive data, it is important to keep the focus of the investigation in mind. The report must be precise and objective-oriented.

Why Use Voxco for Descriptive Research Design?

Voxco being an omnichannel survey software , can be a valuable tool in descriptive research design. It can provide its users with a convenient and efficient means of collecting data from a large number of respondents. 

It allows researchers to design and distribute surveys to a targeted sample of participants, collect data in a standardized format, and analyze the results.

Here are some ways in which Voxco helps with descriptive research design:

• Customizable surveys: Voxco lets its users design surveys with a range of question types and themes. 
• Ease of distribution: With a range of distribution integration, Voxco makes it easy for users to distribute surveys easily via email, SMS, social media, etc. It helps the surveys reach a larger number of respondents. 
• Data analysis: Voxco not only helps researchers gather survey data but also analyzes the survey feedback, which allows researchers to get actionable insights on a visual dashboard. 

Overall, Voxco survey software is an effective tool for conducting descriptive research design, as it provides a streamlined and efficient way to gather, measure, and analyze survey data.

Wondering what will be the cost of conducting a survey using Voxco?

This sums up our article on descriptive research design. This research method helps uncover the hidden element of a customer’s behavior. It helps you create a foundation for your research by helping you create an outline of your research subject.

Begin your descriptive research with a free step-by-step guide to descriptive research

What is descriptive research?

Descriptive research design is a type of research methodology that researchers mostly use to analyze and document the behaviors and characteristics of a particular group of people. It gives a detailed analysis of a situation to explore the relation between two variables.

What is descriptive research study used for?

A descriptive research study is a type of observational research and is used for exploring and documenting the nature and scope of a problem, identifying its trends and patterns, and providing a basis for subsequent research. The outcome of a descriptive study is helpful in making decisions, developing policies, and planning social programs.

It is primarily concerned with describing the current state of a given phenomenon rather than explaining why it exists or how it came to be.

Why is descriptive research design used?

Descriptive research design can be used for a variety of reasons, including

• To describe and document a phenomenon of a particular population
• To identify patterns and trends
• To generate hypotheses for further research
• To inform decision-making and policy development

What is an example of a descriptive method?

A case study that examines the experiences of a small business run by women can be an example of a descriptive method of research. Let’s 

For instance, a researcher may conduct a case study of a small business solely run by women that have successfully implemented sustainable business practices in their food cloth manufacturing business. 

The case study could involve interviews with the owners of the business, observation of their business practices, and analysis of their financial data to document the costs and benefits of sustainability initiatives.

The researchers can then use the findings of the case study to provide a detailed account of the business’s approach to sustainability and to identify best practices that could be applied to other businesses.

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Chapter 3. Psychological Science

3.2 Psychologists Use Descriptive, Correlational, and Experimental Research Designs to Understand Behaviour

Learning objectives.

• Differentiate the goals of descriptive, correlational, and experimental research designs and explain the advantages and disadvantages of each.
• Explain the goals of descriptive research and the statistical techniques used to interpret it.
• Summarize the uses of correlational research and describe why correlational research cannot be used to infer causality.
• Review the procedures of experimental research and explain how it can be used to draw causal inferences.

Psychologists agree that if their ideas and theories about human behaviour are to be taken seriously, they must be backed up by data. However, the research of different psychologists is designed with different goals in mind, and the different goals require different approaches. These varying approaches, summarized in Table 3.2, are known as research designs . A research design  is the specific method a researcher uses to collect, analyze, and interpret data . Psychologists use three major types of research designs in their research, and each provides an essential avenue for scientific investigation. Descriptive research  is research designed to provide a snapshot of the current state of affairs . Correlational research  is research designed to discover relationships among variables and to allow the prediction of future events from present knowledge . Experimental research  is research in which initial equivalence among research participants in more than one group is created, followed by a manipulation of a given experience for these groups and a measurement of the influence of the manipulation . Each of the three research designs varies according to its strengths and limitations, and it is important to understand how each differs.

Descriptive Research: Assessing the Current State of Affairs

Descriptive research is designed to create a snapshot of the current thoughts, feelings, or behaviour of individuals. This section reviews three types of descriptive research : case studies , surveys , and naturalistic observation (Figure 3.4).

Sometimes the data in a descriptive research project are based on only a small set of individuals, often only one person or a single small group. These research designs are known as case studies — descriptive records of one or more individual’s experiences and behaviour . Sometimes case studies involve ordinary individuals, as when developmental psychologist Jean Piaget used his observation of his own children to develop his stage theory of cognitive development. More frequently, case studies are conducted on individuals who have unusual or abnormal experiences or characteristics or who find themselves in particularly difficult or stressful situations. The assumption is that by carefully studying individuals who are socially marginal, who are experiencing unusual situations, or who are going through a difficult phase in their lives, we can learn something about human nature.

Sigmund Freud was a master of using the psychological difficulties of individuals to draw conclusions about basic psychological processes. Freud wrote case studies of some of his most interesting patients and used these careful examinations to develop his important theories of personality. One classic example is Freud’s description of “Little Hans,” a child whose fear of horses the psychoanalyst interpreted in terms of repressed sexual impulses and the Oedipus complex (Freud, 1909/1964).

Another well-known case study is Phineas Gage, a man whose thoughts and emotions were extensively studied by cognitive psychologists after a railroad spike was blasted through his skull in an accident. Although there are questions about the interpretation of this case study (Kotowicz, 2007), it did provide early evidence that the brain’s frontal lobe is involved in emotion and morality (Damasio et al., 2005). An interesting example of a case study in clinical psychology is described by Rokeach (1964), who investigated in detail the beliefs of and interactions among three patients with schizophrenia, all of whom were convinced they were Jesus Christ.

In other cases the data from descriptive research projects come in the form of a survey — a measure administered through either an interview or a written questionnaire to get a picture of the beliefs or behaviours of a sample of people of interest . The people chosen to participate in the research (known as the sample) are selected to be representative of all the people that the researcher wishes to know about (the population). In election polls, for instance, a sample is taken from the population of all “likely voters” in the upcoming elections.

The results of surveys may sometimes be rather mundane, such as “Nine out of 10 doctors prefer Tymenocin” or “The median income in the city of Hamilton is $46,712.” Yet other times (particularly in discussions of social behaviour), the results can be shocking: “More than 40,000 people are killed by gunfire in the United States every year” or “More than 60% of women between the ages of 50 and 60 suffer from depression.” Descriptive research is frequently used by psychologists to get an estimate of the prevalence (or incidence ) of psychological disorders.

A final type of descriptive research — known as naturalistic observation — is research based on the observation of everyday events . For instance, a developmental psychologist who watches children on a playground and describes what they say to each other while they play is conducting descriptive research, as is a biopsychologist who observes animals in their natural habitats. One example of observational research involves a systematic procedure known as the strange situation , used to get a picture of how adults and young children interact. The data that are collected in the strange situation are systematically coded in a coding sheet such as that shown in Table 3.3.

The results of descriptive research projects are analyzed using descriptive statistics — numbers that summarize the distribution of scores on a measured variable . Most variables have distributions similar to that shown in Figure 3.5 where most of the scores are located near the centre of the distribution, and the distribution is symmetrical and bell-shaped. A data distribution that is shaped like a bell is known as a normal distribution .

A distribution can be described in terms of its central tendency — that is, the point in the distribution around which the data are centred — and its dispersion, or spread . The arithmetic average, or arithmetic mean , symbolized by the letter M , is the most commonly used measure of central tendency . It is computed by calculating the sum of all the scores of the variable and dividing this sum by the number of participants in the distribution (denoted by the letter N ). In the data presented in Figure 3.5 the mean height of the students is 67.12 inches (170.5 cm). The sample mean is usually indicated by the letter M .

In some cases, however, the data distribution is not symmetrical. This occurs when there are one or more extreme scores (known as outliers ) at one end of the distribution. Consider, for instance, the variable of family income (see Figure 3.6), which includes an outlier (a value of $3,800,000). In this case the mean is not a good measure of central tendency. Although it appears from Figure 3.6 that the central tendency of the family income variable should be around $70,000, the mean family income is actually $223,960. The single very extreme income has a disproportionate impact on the mean, resulting in a value that does not well represent the central tendency.

The median is used as an alternative measure of central tendency when distributions are not symmetrical. The median  is the score in the center of the distribution, meaning that 50% of the scores are greater than the median and 50% of the scores are less than the median . In our case, the median household income ($73,000) is a much better indication of central tendency than is the mean household income ($223,960).

A final measure of central tendency, known as the mode , represents the value that occurs most frequently in the distribution . You can see from Figure 3.6 that the mode for the family income variable is $93,000 (it occurs four times).

In addition to summarizing the central tendency of a distribution, descriptive statistics convey information about how the scores of the variable are spread around the central tendency. Dispersion refers to the extent to which the scores are all tightly clustered around the central tendency , as seen in Figure 3.7.

Or they may be more spread out away from it, as seen in Figure 3.8.

One simple measure of dispersion is to find the largest (the maximum ) and the smallest (the minimum ) observed values of the variable and to compute the range of the variable as the maximum observed score minus the minimum observed score. You can check that the range of the height variable in Figure 3.5 is 72 – 62 = 10. The standard deviation , symbolized as s , is the most commonly used measure of dispersion . Distributions with a larger standard deviation have more spread. The standard deviation of the height variable is s = 2.74, and the standard deviation of the family income variable is s = $745,337.

An advantage of descriptive research is that it attempts to capture the complexity of everyday behaviour. Case studies provide detailed information about a single person or a small group of people, surveys capture the thoughts or reported behaviours of a large population of people, and naturalistic observation objectively records the behaviour of people or animals as it occurs naturally. Thus descriptive research is used to provide a relatively complete understanding of what is currently happening.

Despite these advantages, descriptive research has a distinct disadvantage in that, although it allows us to get an idea of what is currently happening, it is usually limited to static pictures. Although descriptions of particular experiences may be interesting, they are not always transferable to other individuals in other situations, nor do they tell us exactly why specific behaviours or events occurred. For instance, descriptions of individuals who have suffered a stressful event, such as a war or an earthquake, can be used to understand the individuals’ reactions to the event but cannot tell us anything about the long-term effects of the stress. And because there is no comparison group that did not experience the stressful situation, we cannot know what these individuals would be like if they hadn’t had the stressful experience.

Correlational Research: Seeking Relationships among Variables

In contrast to descriptive research, which is designed primarily to provide static pictures, correlational research involves the measurement of two or more relevant variables and an assessment of the relationship between or among those variables. For instance, the variables of height and weight are systematically related (correlated) because taller people generally weigh more than shorter people. In the same way, study time and memory errors are also related, because the more time a person is given to study a list of words, the fewer errors he or she will make. When there are two variables in the research design, one of them is called the predictor variable and the other the outcome variable . The research design can be visualized as shown in Figure 3.9, where the curved arrow represents the expected correlation between these two variables.

One way of organizing the data from a correlational study with two variables is to graph the values of each of the measured variables using a scatter plot . As you can see in Figure 3.10 a scatter plot  is a visual image of the relationship between two variables . A point is plotted for each individual at the intersection of his or her scores for the two variables. When the association between the variables on the scatter plot can be easily approximated with a straight line , as in parts (a) and (b) of Figure 3.10 the variables are said to have a linear relationship .

When the straight line indicates that individuals who have above-average values for one variable also tend to have above-average values for the other variable , as in part (a), the relationship is said to be positive linear . Examples of positive linear relationships include those between height and weight, between education and income, and between age and mathematical abilities in children. In each case, people who score higher on one of the variables also tend to score higher on the other variable. Negative linear relationships , in contrast, as shown in part (b), occur when above-average values for one variable tend to be associated with below-average values for the other variable. Examples of negative linear relationships include those between the age of a child and the number of diapers the child uses, and between practice on and errors made on a learning task. In these cases, people who score higher on one of the variables tend to score lower on the other variable.

Relationships between variables that cannot be described with a straight line are known as nonlinear relationships . Part (c) of Figure 3.10 shows a common pattern in which the distribution of the points is essentially random. In this case there is no relationship at all between the two variables, and they are said to be independent . Parts (d) and (e) of Figure 3.10 show patterns of association in which, although there is an association, the points are not well described by a single straight line. For instance, part (d) shows the type of relationship that frequently occurs between anxiety and performance. Increases in anxiety from low to moderate levels are associated with performance increases, whereas increases in anxiety from moderate to high levels are associated with decreases in performance. Relationships that change in direction and thus are not described by a single straight line are called curvilinear relationships .

The most common statistical measure of the strength of linear relationships among variables is the Pearson correlation coefficient , which is symbolized by the letter r . The value of the correlation coefficient ranges from r = –1.00 to r = +1.00. The direction of the linear relationship is indicated by the sign of the correlation coefficient. Positive values of r (such as r = .54 or r = .67) indicate that the relationship is positive linear (i.e., the pattern of the dots on the scatter plot runs from the lower left to the upper right), whereas negative values of r (such as r = –.30 or r = –.72) indicate negative linear relationships (i.e., the dots run from the upper left to the lower right). The strength of the linear relationship is indexed by the distance of the correlation coefficient from zero (its absolute value). For instance, r = –.54 is a stronger relationship than r = .30, and r = .72 is a stronger relationship than r = –.57. Because the Pearson correlation coefficient only measures linear relationships, variables that have curvilinear relationships are not well described by r , and the observed correlation will be close to zero.

It is also possible to study relationships among more than two measures at the same time. A research design in which more than one predictor variable is used to predict a single outcome variable is analyzed through multiple regression (Aiken & West, 1991).  Multiple regression  is a statistical technique, based on correlation coefficients among variables, that allows predicting a single outcome variable from more than one predictor variable . For instance, Figure 3.11 shows a multiple regression analysis in which three predictor variables (Salary, job satisfaction, and years employed) are used to predict a single outcome (job performance). The use of multiple regression analysis shows an important advantage of correlational research designs — they can be used to make predictions about a person’s likely score on an outcome variable (e.g., job performance) based on knowledge of other variables.

An important limitation of correlational research designs is that they cannot be used to draw conclusions about the causal relationships among the measured variables. Consider, for instance, a researcher who has hypothesized that viewing violent behaviour will cause increased aggressive play in children. He has collected, from a sample of Grade 4 children, a measure of how many violent television shows each child views during the week, as well as a measure of how aggressively each child plays on the school playground. From his collected data, the researcher discovers a positive correlation between the two measured variables.

Although this positive correlation appears to support the researcher’s hypothesis, it cannot be taken to indicate that viewing violent television causes aggressive behaviour. Although the researcher is tempted to assume that viewing violent television causes aggressive play, there are other possibilities. One alternative possibility is that the causal direction is exactly opposite from what has been hypothesized. Perhaps children who have behaved aggressively at school develop residual excitement that leads them to want to watch violent television shows at home (Figure 3.13):

Although this possibility may seem less likely, there is no way to rule out the possibility of such reverse causation on the basis of this observed correlation. It is also possible that both causal directions are operating and that the two variables cause each other (Figure 3.14).

Still another possible explanation for the observed correlation is that it has been produced by the presence of a common-causal variable (also known as a third variable ). A common-causal variable  is a variable that is not part of the research hypothesis but that causes both the predictor and the outcome variable and thus produces the observed correlation between them . In our example, a potential common-causal variable is the discipline style of the children’s parents. Parents who use a harsh and punitive discipline style may produce children who like to watch violent television and who also behave aggressively in comparison to children whose parents use less harsh discipline (Figure 3.15)

In this case, television viewing and aggressive play would be positively correlated (as indicated by the curved arrow between them), even though neither one caused the other but they were both caused by the discipline style of the parents (the straight arrows). When the predictor and outcome variables are both caused by a common-causal variable, the observed relationship between them is said to be spurious . A spurious relationship  is a relationship between two variables in which a common-causal variable produces and “explains away” the relationship . If effects of the common-causal variable were taken away, or controlled for, the relationship between the predictor and outcome variables would disappear. In the example, the relationship between aggression and television viewing might be spurious because by controlling for the effect of the parents’ disciplining style, the relationship between television viewing and aggressive behaviour might go away.

Common-causal variables in correlational research designs can be thought of as mystery variables because, as they have not been measured, their presence and identity are usually unknown to the researcher. Since it is not possible to measure every variable that could cause both the predictor and outcome variables, the existence of an unknown common-causal variable is always a possibility. For this reason, we are left with the basic limitation of correlational research: correlation does not demonstrate causation. It is important that when you read about correlational research projects, you keep in mind the possibility of spurious relationships, and be sure to interpret the findings appropriately. Although correlational research is sometimes reported as demonstrating causality without any mention being made of the possibility of reverse causation or common-causal variables, informed consumers of research, like you, are aware of these interpretational problems.

In sum, correlational research designs have both strengths and limitations. One strength is that they can be used when experimental research is not possible because the predictor variables cannot be manipulated. Correlational designs also have the advantage of allowing the researcher to study behaviour as it occurs in everyday life. And we can also use correlational designs to make predictions — for instance, to predict from the scores on their battery of tests the success of job trainees during a training session. But we cannot use such correlational information to determine whether the training caused better job performance. For that, researchers rely on experiments.

Experimental Research: Understanding the Causes of Behaviour

The goal of experimental research design is to provide more definitive conclusions about the causal relationships among the variables in the research hypothesis than is available from correlational designs. In an experimental research design, the variables of interest are called the independent variable (or variables ) and the dependent variable . The independent variable  in an experiment is the causing variable that is created (manipulated) by the experimenter . The dependent variable  in an experiment is a measured variable that is expected to be influenced by the experimental manipulation . The research hypothesis suggests that the manipulated independent variable or variables will cause changes in the measured dependent variables. We can diagram the research hypothesis by using an arrow that points in one direction. This demonstrates the expected direction of causality (Figure 3.16):

Research Focus: Video Games and Aggression

Consider an experiment conducted by Anderson and Dill (2000). The study was designed to test the hypothesis that viewing violent video games would increase aggressive behaviour. In this research, male and female undergraduates from Iowa State University were given a chance to play with either a violent video game (Wolfenstein 3D) or a nonviolent video game (Myst). During the experimental session, the participants played their assigned video games for 15 minutes. Then, after the play, each participant played a competitive game with an opponent in which the participant could deliver blasts of white noise through the earphones of the opponent. The operational definition of the dependent variable (aggressive behaviour) was the level and duration of noise delivered to the opponent. The design of the experiment is shown in Figure 3.17

Two advantages of the experimental research design are (a) the assurance that the independent variable (also known as the experimental manipulation ) occurs prior to the measured dependent variable, and (b) the creation of initial equivalence between the conditions of the experiment (in this case by using random assignment to conditions).

Experimental designs have two very nice features. For one, they guarantee that the independent variable occurs prior to the measurement of the dependent variable. This eliminates the possibility of reverse causation. Second, the influence of common-causal variables is controlled, and thus eliminated, by creating initial equivalence among the participants in each of the experimental conditions before the manipulation occurs.

The most common method of creating equivalence among the experimental conditions is through random assignment to conditions, a procedure in which the condition that each participant is assigned to is determined through a random process, such as drawing numbers out of an envelope or using a random number table . Anderson and Dill first randomly assigned about 100 participants to each of their two groups (Group A and Group B). Because they used random assignment to conditions, they could be confident that, before the experimental manipulation occurred, the students in Group A were, on average, equivalent to the students in Group B on every possible variable, including variables that are likely to be related to aggression, such as parental discipline style, peer relationships, hormone levels, diet — and in fact everything else.

Then, after they had created initial equivalence, Anderson and Dill created the experimental manipulation — they had the participants in Group A play the violent game and the participants in Group B play the nonviolent game. Then they compared the dependent variable (the white noise blasts) between the two groups, finding that the students who had viewed the violent video game gave significantly longer noise blasts than did the students who had played the nonviolent game.

Anderson and Dill had from the outset created initial equivalence between the groups. This initial equivalence allowed them to observe differences in the white noise levels between the two groups after the experimental manipulation, leading to the conclusion that it was the independent variable (and not some other variable) that caused these differences. The idea is that the only thing that was different between the students in the two groups was the video game they had played.

Despite the advantage of determining causation, experiments do have limitations. One is that they are often conducted in laboratory situations rather than in the everyday lives of people. Therefore, we do not know whether results that we find in a laboratory setting will necessarily hold up in everyday life. Second, and more important, is that some of the most interesting and key social variables cannot be experimentally manipulated. If we want to study the influence of the size of a mob on the destructiveness of its behaviour, or to compare the personality characteristics of people who join suicide cults with those of people who do not join such cults, these relationships must be assessed using correlational designs, because it is simply not possible to experimentally manipulate these variables.

Key Takeaways

• Descriptive, correlational, and experimental research designs are used to collect and analyze data.
• Descriptive designs include case studies, surveys, and naturalistic observation. The goal of these designs is to get a picture of the current thoughts, feelings, or behaviours in a given group of people. Descriptive research is summarized using descriptive statistics.
• Correlational research designs measure two or more relevant variables and assess a relationship between or among them. The variables may be presented on a scatter plot to visually show the relationships. The Pearson Correlation Coefficient ( r ) is a measure of the strength of linear relationship between two variables.
• Common-causal variables may cause both the predictor and outcome variable in a correlational design, producing a spurious relationship. The possibility of common-causal variables makes it impossible to draw causal conclusions from correlational research designs.
• Experimental research involves the manipulation of an independent variable and the measurement of a dependent variable. Random assignment to conditions is normally used to create initial equivalence between the groups, allowing researchers to draw causal conclusions.

Exercises and Critical Thinking

• There is a negative correlation between the row that a student sits in in a large class (when the rows are numbered from front to back) and his or her final grade in the class. Do you think this represents a causal relationship or a spurious relationship, and why?
• Think of two variables (other than those mentioned in this book) that are likely to be correlated, but in which the correlation is probably spurious. What is the likely common-causal variable that is producing the relationship?
• Imagine a researcher wants to test the hypothesis that participating in psychotherapy will cause a decrease in reported anxiety. Describe the type of research design the investigator might use to draw this conclusion. What would be the independent and dependent variables in the research?

Image Attributions

Figure 3.4: “ Reading newspaper ” by Alaskan Dude (http://commons.wikimedia.org/wiki/File:Reading_newspaper.jpg) is licensed under CC BY 2.0

Aiken, L., & West, S. (1991).  Multiple regression: Testing and interpreting interactions . Newbury Park, CA: Sage.

Ainsworth, M. S., Blehar, M. C., Waters, E., & Wall, S. (1978).  Patterns of attachment: A psychological study of the strange situation . Hillsdale, NJ: Lawrence Erlbaum Associates.

Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life.  Journal of Personality and Social Psychology, 78 (4), 772–790.

Damasio, H., Grabowski, T., Frank, R., Galaburda, A. M., Damasio, A. R., Cacioppo, J. T., & Berntson, G. G. (2005). The return of Phineas Gage: Clues about the brain from the skull of a famous patient. In  Social neuroscience: Key readings.  (pp. 21–28). New York, NY: Psychology Press.

Freud, S. (1909/1964). Analysis of phobia in a five-year-old boy. In E. A. Southwell & M. Merbaum (Eds.),  Personality: Readings in theory and research  (pp. 3–32). Belmont, CA: Wadsworth. (Original work published 1909).

Kotowicz, Z. (2007). The strange case of Phineas Gage.  History of the Human Sciences, 20 (1), 115–131.

Rokeach, M. (1964).  The three Christs of Ypsilanti: A psychological study . New York, NY: Knopf.

Stangor, C. (2011). Research methods for the behavioural sciences (4th ed.). Mountain View, CA: Cengage.

Long Descriptions

Figure 3.6 long description: There are 25 families. 24 families have an income between $44,000 and $111,000 and one family has an income of $3,800,000. The mean income is $223,960 while the median income is $73,000. [Return to Figure 3.6]

Figure 3.10 long description: Types of scatter plots.

• Positive linear, r=positive .82. The plots on the graph form a rough line that runs from lower left to upper right.
• Negative linear, r=negative .70. The plots on the graph form a rough line that runs from upper left to lower right.
• Independent, r=0.00. The plots on the graph are spread out around the centre.
• Curvilinear, r=0.00. The plots of the graph form a rough line that goes up and then down like a hill.
• Curvilinear, r=0.00. The plots on the graph for a rough line that goes down and then up like a ditch.

[Return to Figure 3.10]

Introduction to Psychology - 1st Canadian Edition Copyright © 2014 by Jennifer Walinga and Charles Stangor is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Chapter 5: Qualitative descriptive research

Darshini Ayton

Learning outcomes

Upon completion of this chapter, you should be able to:

• Identify the key terms and concepts used in qualitative descriptive research.
• Discuss the advantages and disadvantages of qualitative descriptive research.

What is a qualitative descriptive study?

The key concept of the qualitative descriptive study is description.

Qualitative descriptive studies (also known as ‘exploratory studies’ and ‘qualitative description approaches’) are relatively new in the qualitative research landscape. They emerged predominantly in the field of nursing and midwifery over the past two decades. 1 The design of qualitative descriptive studies evolved as a means to define aspects of qualitative research that did not resemble qualitative research designs to date, despite including elements of those other study designs. 2

Qualitative descriptive studies  describe  phenomena rather than explain them. Phenomenological studies, ethnographic studies and those using grounded theory seek to explain a phenomenon. Qualitative descriptive studies aim to provide a comprehensive summary of events. The approach to this study design is journalistic, with the aim being to answer the questions who, what, where and how. 3

A qualitative descriptive study is an important and appropriate design for research questions that are focused on gaining insights about a poorly understood research area, rather than on a specific phenomenon. Since qualitative descriptive study design seeks to describe rather than explain, explanatory frameworks and theories are not required to explain or ‘ground’ a study and its results. 4 The researcher may decide that a framework or theory adds value to their interpretations, and in that case, it is perfectly acceptable to use them. However, the hallmark of genuine curiosity (naturalistic enquiry) is that the researcher does not know in advance what they will be observing or describing. 4 Because a phenomenon is being described, the qualitative descriptive analysis is more categorical and less conceptual than other methods. Qualitative content analysis is usually the main approach to data analysis in qualitative descriptive studies. 4 This has led to criticism of descriptive research being less sophisticated because less interpretation is required than with other qualitative study designs in which interpretation and explanation are key characteristics (e.g. phenomenology, grounded theory, case studies).

Diverse approaches to data collection can be utilised in qualitative description studies. However, most qualitative descriptive studies use semi-structured interviews (see Chapter 13) because they provide a reliable way to collect data. 3 The technique applied to data analysis is generally categorical and less conceptual when compared to other qualitative research designs (see Section 4). 2,3 Hence, this study design is well suited to research by practitioners, student researchers and policymakers. Its straightforward approach enables these studies to be conducted in shorter timeframes than other study designs. 3 Descriptive studies are common as the qualitative component in mixed-methods research ( see Chapter 11 ) and evaluations ( see Chapter 12 ), 1 because qualitative descriptive studies can provide information to help develop and refine questionnaires or interventions.

For example, in our research to develop a patient-reported outcome measure for people who had undergone a percutaneous coronary intervention (PCI), which is a common cardiac procedure to treat heart disease, we started by conducting a qualitative descriptive study. 5 This project was a large, mixed-methods study funded by a private health insurer. The entire research process needed to be straightforward and achievable within a year, as we had engaged an undergraduate student to undertake the research tasks. The aim of the qualitative component of the mixed-methods study was to identify and explore patients’ perceptions following PCI. We used inductive approaches to collect and analyse the data. The study was guided by the following domains for the development of patient-reported outcomes, according to US Food and Drug Administration (FDA) guidelines, which included:

• Feeling: How the patient feels physically and psychologically after medical intervention
• Function: The patient’s mobility and ability to maintain their regular routine
• Evaluation: The patient’s overall perception of the success or failure of their procedure and their perception of what contributed to it. 5(p458)

We conducted focus groups and interviews, and asked participants three questions related to the FDA outcome domains:

• From your perspective, what would be considered a successful outcome of the procedure?

Probing questions: Did the procedure meet your expectations? How do you define whether the procedure was successful?

• How did you feel after the procedure?

Probing question: How did you feel one week after and how does that compare with how you feel now?

• After your procedure, tell me about your ability to do your daily activities?

Prompt for activities including gardening, housework, personal care, work-related and family-related tasks.

Probing questions: Did you attend cardiac rehabilitation? Can you tell us about your experience of cardiac rehabilitation? What impact has medication had on your recovery?

• What, if any, lifestyle changes have you made since your procedure? 5(p459)

Data collection was conducted with 32 participants. The themes were mapped to the FDA patient-reported outcome domains, with the results confirming previous research and also highlighting new areas for exploration in the development of a new patient-reported outcome measure. For example, participants reported a lack of confidence following PCI and the importance of patient and doctor communication. Women, in particular, reported that they wanted doctors to recognise how their experiences of cardiac symptoms were different to those of men.

The study described phenomena and resulted in the development of a patient-reported outcome measure that was tested and refined using a discrete-choice experiment survey, 6 a pilot of the measure in the Victorian Cardiac Outcomes Registry and a Rasch analysis to validate the measurement’s properties. 7

Advantages and disadvantages of qualitative descriptive studies

A qualitative descriptive study is an effective design for research by practitioners, policymakers and students, due to their relatively short timeframes and low costs. The researchers can remain close to the data and the events described, and this can enable the process of analysis to be relatively simple. Qualitative descriptive studies are also useful in mixed-methods research studies. Some of the advantages of qualitative descriptive studies have led to criticism of the design approach, due to a lack of engagement with theory and the lack of interpretation and explanation of the data. 2

Table 5.1. Examples of qualitative descriptive studies

Qualitative descriptive studies are gaining popularity in health and social care due to their utility, from a resource and time perspective, for research by practitioners, policymakers and researchers. Descriptive studies can be conducted as stand-alone studies or as part of larger, mixed-methods studies.

• Bradshaw C, Atkinson S, Doody O. Employing a qualitative description approach in health care research. Glob Qual Nurs Res. 2017;4. doi:10.1177/2333393617742282
• Lambert VA, Lambert CE. Qualitative descriptive research: an acceptable design. Pac Rim Int J Nurs Res Thail. 2012;16(4):255-256. Accessed June 6, 2023. https://he02.tci-thaijo.org/index.php/PRIJNR/article/download/5805/5064
• Doyle L et al. An overview of the qualitative descriptive design within nursing research. J Res Nurs. 2020;25(5):443-455. doi:10.1177/174498711988023
• Kim H, Sefcik JS, Bradway C. Characteristics of qualitative descriptive studies: a systematic review. Res Nurs Health. 2017;40(1):23-42. doi:10.1002/nur.21768
• Ayton DR et al. Exploring patient-reported outcomes following percutaneous coronary intervention: a qualitative study. Health Expect. 2018;21(2):457-465. doi:10.1111/hex.1263
• Barker AL et al. Symptoms and feelings valued by patients after a percutaneous coronary intervention: a discrete-choice experiment to inform development of a new patient-reported outcome. BMJ Open. 2018;8:e023141. doi:10.1136/bmjopen-2018-023141
• Soh SE et al. What matters most to patients following percutaneous coronary interventions? a new patient-reported outcome measure developed using Rasch analysis. PLoS One. 2019;14(9):e0222185. doi:10.1371/journal.pone.0222185
• Hiller RM et al. Coping and support-seeking in out-of-home care: a qualitative study of the views of young people in care in England. BMJ Open. 2021;11:e038461. doi:10.1136/bmjopen-2020-038461
• Backman C, Cho-Young D. Engaging patients and informal caregivers to improve safety and facilitate person- and family-centered care during transitions from hospital to home – a qualitative descriptive study. Patient Prefer Adherence. 2019;13:617-626. doi:10.2147/PPA.S201054

Qualitative Research – a practical guide for health and social care researchers and practitioners Copyright © 2023 by Darshini Ayton is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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• Open access
• Published: 28 August 2024

Perspectives of midwives on the use of Kaligutim (local oxytocin) for induction of labour among pregnant women in the government hospitals in Tamale

• Ahmad Sukerazu Alhassan 1 ,
• Shivera Dakurah 2 &
• Joseph Lasong 1  

BMC Pregnancy and Childbirth volume  24 , Article number:  561 ( 2024 ) Cite this article

Metrics details

The use of herbal medicine and/or its products is common throughout the world. In Tamale Metropolis, pregnant women frequently use local oxytocin to induce labour, as shown by the fact that 90% of midwives reported managing patients who used kaligutim (local oxytocin) to speed up labour. Early career midwives are also aware of this and have personally observed it being used by their clients. The purpose of the study was to assess midwives’ opinions on pregnant women’s use of the well-known kaligutim (local oxytocin) for labour induction in the Tamale Metropolis.

A facility-based, quantitative, cross-sectional research design was used for the study. A total of 214 working midwives from Tamale’s three main public hospitals participated. Data for the study were gathered through a standardized questionnaire. For the analysis and presentation of the data, descriptive and analytical statistics, such as basic frequencies, percentages, Fisher’s exact test, chi square test and multivariate analysis, were employed.

According to the findings of this study, the safety, dosages, and contraindications of kaligutim during pregnancy and labour are unknown. The cessation of contractions was reported by 44 (22.4%) of the respondents whose clients used local oxytocin. The study also revealed that women in Tamale metropolis use “walgu”, a spiritual form of oxytocin, to induce and augment labour. Respondents who responded, “yes” to baby admission to the new-born care unit were 25% more likely to use kaligutim (local oxytocin) than were those who responded, “no” to baby admission to the new-born care unit (AOR = 0.25 95% CI (0.01, 0.53), P  = 0.021).

Conclusions

It can be concluded that using kaligutim to start labour has negative effects on both the mother and the foetus. Additional research is required to evaluate the efficacy, effectiveness, biochemical makeup, and safety of these herbal medicines, particularly during pregnancy and delivery, as well as the spiritual significance of kaligutim (Walgu) and its forms.

Peer Review reports

Introduction

Herbal medicines, traditional treatments, and traditional practitioners are the main source of health care for many millions of people, and sometimes the only source of care [ 1 ]. Herbal medicines include herbs, herbal materials, herbal preparations and finished herbal products, that contain as active ingredients parts of plants, or other plant materials, or combinations [ 1 , 2 ]. Women in both developed and developing countries use herbal medicine before pregnancy and during pregnancy and delivery, which has several consequences [ 3 ]. The use of herbal medicine has a long history, tracing its roots back to ancient and biblical days when there was no Orthodox medicine. Currently, both developed and developing countries use herbal medicine due to the presence of many traditional medicine practitioners [ 4 ].

Many cultures worldwide use herbal medicine to induce or accelerate labour, and the incidence of labour induction to shorten the duration of labour is on the rise. Most herbal medicine users are pregnant women who have no formal education, who have a low level of income and who mostly stay far from health facilities [ 5 ]. The majority of pregnant women use herbal medicine through the oral route and have confidence in its efficacy, safety and effectiveness [ 6 ]. Herbal medicine is used by women for maternal health-related issues, such as to induce abortion and labour, to correct infertility, for the treatment of pregnancy-related issues, for breast milk secretion and for general wellbeing during pregnancy [ 5 ].

Women who use herbal medicine during pregnancy and/or labour usually have a high risk of postpartum complications [ 7 ]. The use of herbal uterotonics can lead to hyperstimulation of the uterus, foetal asphyxia and several other adverse effects of labour [ 8 ]. Moreover, traditional medicine used by pregnant women is associated with several complications, including a ruptured uterus, a fresh still birth, a macerated still birth, a caesarean section and even death [ 9 ]. These herbal medicines have both uterotonic and nonuterotonic effects on labour and delivery and are mostly used to induce or augment labour in prolonged labour or postdate or to relax or widen the pelvis for delivery [ 8 ].

Maternal and neonatal deaths are still major challenges for most developing countries, with obstetric complications, especially postpartum haemorrhage (P.P.H.) being the major cause of maternal mortality [ 10 ]. The delivery of healthcare services is still poor quality in developing nations [ 11 ]. Maternal and foetal mortality and morbidity have remained high due to inadequate health services and inadequate emergency obstetric treatment. Childbirth is accompanied by numerous customs that are subject to ethnological research and are often rooted in traditional medicine or religion. Cultural influences and sociodemographic characteristics play an important role in a woman’s decision to seek maternal and child health services.

The induction of labour is the process of artificially starting labour by stimulating the uterus with oxytocin or manually through the rupture of amniotic membranes. This process is usually not risk free, and most women find it to be uncomfortable [ 12 ]. The induction of labour is an obstetric procedure recommended when the benefits to the baby and mother outweigh the benefits of continuing the pregnancy. The procedure usually involves complications and failures and must be performed under close monitoring, proper selection of clients and good preparation [ 13 ].

Labour induction also changes the normal physiological processes that accompany childbirth and increases the risk of adverse pregnancy outcomes such as postpartum haemorrhage, neonatal mortality, foetal distress, uterine rapture and premature birth [ 14 ]. Oxytocin is a natural hormone produced by the hypothalamus and is responsible for the activation of sensory nerves during labour and breastfeeding [ 15 ]. Clinically, commercially manufactured synthetic oxytocin is administered to commence or increase uterine activity to reduce the duration of labour [ 16 ].

The induction of labour is not free from risk and must be performed with caution because the procedure involves hyperstimulation of the uterus and foetal distress. Herbal medicine used by pregnant women has long-term effects on both mothers and babies [ 17 ]. Many pregnant women in the Tamale Metropolis use prepackaged herbal medicine before and during pregnancy [ 18 ]. Health-related factors such as cost, distance, access and unavailability of medications influence the utilization of herbal medicine by pregnant women [ 17 ].

All women should be given a prophylactic dose of oxytocin as soon as they give birth. If they start to haemorrhage, they should also be given a treatment dose of oxytocin, which is greater than the prophylactic dose [ 19 ]. There is also a traditional manufactured form of oxytocin (kaligutim) that pregnant women use to start labour. Kaligutim is the local name for the mixture of some special plant parts or a combination of plants prepared and given to pregnant women to start or accelerate the process of labour in the northern part of Ghana [ 17 ].

Ideally, women should take medical drugs during pregnancy (folic acid and fersolate) to help prevent birth defects and congenital malformations such as neural tube defects of the foetus and spinal bifida during pregnancy [ 20 ]. However, in recent decades, women worldwide have used herbal medications during pregnancy and labour, with some taking both herbal medicine and orthodox medicine at the same time [ 21 ]. However, little is known about the use and safety of these medicines, especially during pregnancy, and their dosages, indications and contraindications are not known [ 22 ].

There are studies on herbal medicine use by women during pregnancy and labour, but there is currently no literature on the use of Kaligutim (local oxytocin) for labour induction among pregnant women in Ghana, but similar studies have been conducted in Uganda, Malawi, Tanzania, and Nigeria. Despite the efforts of the government and other nongovernmental organizations to ensure maximum coverage of skilled delivery to help reduce maternal and neonatal mortalities, women still use locally prepared oxytocin to induce labour. Although herbal medicine is commonly used by pregnant women, healthcare providers, especially midwives, are often unprepared to communicate effectively with patients or make proper decisions concerning complementary and alternative medicine use, especially during pregnancy and labour [ 23 ].

It is well known that herbs have played a vital role since the precolonial era during pregnancy, delivery and postpartum care in many parts of the country, but there are still few data on the use of herbs among pregnant women in Ghana [ 24 ]. Towards the end of pregnancy, many women are tired and eager to welcome their babies into the world. Moreover, as the expected date of delivery approaches, these women are given local oxytocin by their mothers’ in-laws, grandmothers, mothers, or TBAs or even by the women themselves to start labour at home before going to the health facility [ 25 ].

Medicinal plants that are used to hasten or speed up labour are mostly taken towards the end of pregnancy or the beginning of labour [ 26 ]. Even after delivery, these herbs may be found in small amounts in the mother’s breast, and some may cross the placental barrier and have harmful effects on the baby. The use of herbal medication by pregnant women is inevitable given that up to 80% of people who live in developing nations rely on traditional medicine for their healthcare needs [ 18 ].

The situation in Ghana, especially Northern Ghana, is not different, as pregnant women continue to use herbs despite the availability of health facilities [ 24 ]. The use of herbal medicine (kaligutim) among the Ghanaian population is alarming. Pregnant women in Tamale use herbal products at a rate of 42.5% prior to pregnancy and 52.7% during pregnancy [ 27 ]. Residents of Tamales who seek healthcare services in hospitals or herbal clinics are therefore at a greater risk of experiencing adverse consequences from drug-herb interactions [ 28 ].

Herbal product manufacturers should clearly state that pregnancy is a contraindication, and vendors should use caution when selling these items to pregnant women [ 27 ]. The use of Kaligutim (local oxytocin) by pregnant women is a maternal and child health problem. Herbal medicine used by pregnant women has long-term effects on both mothers and babies [ 17 ]. Unfortunately, maternal, and neonatal deaths may occur, and hence, there is a need to examine midwives’ perspectives on local oxytocin use during labour, its effects on the progress and outcome of labour, and the relationship between kaligutim use and birth outcomes among pregnant women in the three major government hospitals in Tamale Metropolis.

Theoretical foundation

This study adopted and adapted Andersen’s (1968) behavioural model of healthcare service utilization (use and nonuse of health services [ 29 ]. Andersen’s healthcare utilization model is a conceptual model aimed at demonstrating the factors that lead to the use/nonuse of health services [ 29 ]. This study was guided by Andersen’s behavioural model of health service use as a theoretical framework to identify the effects of Kaligutim on the progress and outcome of labour and to establish the relationship between the use of Kaligutim and nonuse of kaligutim and birth outcomes. The behavioural model is a multilevel model that incorporates both individual and contextual determinants of health service use.

Conceptual framework

Many people rely on products made from medicinal plants to maintain their health or treat illness, and current general development trends in developing and developed countries suggest that the consumption of medicinal plants is unlikely to decline in the short to medium term because of the benefits to consumers, producers, and society as a whole [ 29 ]. Therefore, there is a need to increase our understanding of what motivates the consumption of medicinal plants, despite the barriers to the establishment of solid evidence on the safety and efficacy of herbal medicines and related products [ 29 ].

This unified conceptual framework offers a step towards establishing a comprehensive approach to understanding the experiences midwives encounter when their clients use herbal medicine to induce their labour. The exposure variable in this study refers to kaligutim (local oxytocin) used by pregnant women in the three major government hospitals to induce labour through several routes, including oral, rectal, and vaginal routes, among others. When oxytocin is used by pregnant women, it can produce several results that can be immediate or late.

The results elicited on labour are termed the outcome variables, which can be immediate outcomes (the progress of labour) or outcomes after delivery (the outcome of labour). The progression of labour includes three stages: progressive dilatation of the cervix from 1 cm to 10 cm, delivery of the baby and expulsion of the placenta. Several factors can be used to determine the progress of labour (obstructed labour, prolonged labour, nature of uterine contractions, precipitated labour, foetal distress, and poor progress of labour).

The outcome of labour on the hand refers to what happens during the delivery of the baby, how the baby was delivered, foetal conditions and maternal conditions. The following factors were used for the purpose of this study to determine the outcome of labour (mode of delivery, postpartum haemorrhage, ruptured uterus, cervical tear, birth asphyxia, uterine atony, maternal mortality, and neonatal mortality). This study focused on the immediate effects of Kaligutim (on labour progress) and the effects of Kaligutim after delivery (on labour outcomes) and the relationship between the use of Kaligutim and birth outcomes.

The study was carried out in Tamale, which is the capital city of the northern region of Ghana. According to the 2021 World Urbanization Review, Tamales has an estimated population of 671,812 people. Tamale still has a blend of typical rural and urban communities, although it has attained the status of a metropolitan area. There are three major government hospitals in Tamale: Tamale Central Hospital, Tamale West Hospital and Tamale Teaching Hospital. The Tamale Teaching Hospital is the only tertiary facility in the northern region and serves as the main reference centre for the five regions of the north.

Study population

The main study population was midwives working in Tamale Metropolis. The sampling frame was all midwives practicing in the three major hospitals in Tamale Metropolis who were willing to participate in the study.

Study design

A facility-based cross-sectional research design was used for this study. A cross-sectional study is a type of observational study design carried out at one point in time or over a short period of time to estimate the prevalence of the outcome of interest for a given population for the purpose of public health planning [ 30 ]. This study adopted a quantitative research approach to obtain information.

Sampling technique

A purposive sampling technique was used for this study. Purposive sampling is a nonprobability sampling method in which participants are selected for inclusion in the sample based on their characteristics, knowledge, or experiences. This is because of the midwives’ knowledge, experiences, and objective of the study.

Sample size calculation

Total number of midwives = 458

Yamane formula (1967) was used with a confidence interval of 95% and a margin of error of 5%.

N = population size (458).

n = the sample size (?)

e = margin of error (5%).

n \(\:=\frac{N}{1\:+N\left(e\right)2}\)

n= \(\:\frac{458}{1\:+458\left(0.05\right)2}\)

n  = 214.01 = 214.

Sample size = 214 midwives.

Inclusion criteria

All midwives practicing in the three major government hospitals in Tamale Metropolis who were willing to participate in the study were included.

All midwives in the three-government hospital with experience with kaligutim use during labour were also included in the study.

Exclusion criteria

All midwives who were not practising at the three major government hospitals in Tamale Metropolis were excluded from the study.

Midwives who were practicing at the three major government hospitals in Tamale and who were not willing to participate in the study were also excluded from the study.

All midwives who did not have experience with kaligutim use for the induction of labour were excluded from the study.

Data collection instrument

The data collection tool that was used for the study was a standardized questionnaire. The questionnaire was constructed by reviewing various documents, including existing questionnaires that have been used in previous research. Close-ended questions with few open-ended questions were used as the question format. It was designed in line with the objectives of the study to help obtain the necessary information needed for the study. The questionnaire was pretested with midwives before the actual data collection took place.

Data management and analysis

Data collected from the field were coded, cleaned, and entered into the Statistical Package for Social Services (SPSS) version 21.0. Descriptive and analytical statistics, including simple frequencies and percentages, were used for the analysis and presentation of the data. The relationships between predictor and outcome variables were assessed by means of bivariate (chi-square test) analysis to determine potential predictors of kaligutim (local oxytocin) at p values less than 0.05. Adjusted odds ratios were reported, and p values less than 0.05 were deemed to indicate statistical significance at the 95% confidence level after multivariate analysis.

Ethical consideration

The following ethical principles guided this study: respect for persons, beneficence, and justice for all. These principles are based on the human rights that must be protected during any research project, including the right to self-determination, privacy, anonymity, confidentiality, fair treatment and protection from discomfort and harm. First, an introductory letter was obtained from the University for Development Studies authorities. This letter was then presented to the authorities of the three major government hospitals in Tamale, namely, Tamale West Hospital (T.W.H.), Tamale Central Hospital (T.C.H.) and Tamale Teaching Hospital (TTH.), to seek permission to undertake the study. Ethical clearance was also obtained from the Kwame Nkrumah University of Science and Technology (KNUST) (CHRPE/AP/332/22).

Permission was once sought through a consent form to which participants were asked to consent if they were willing to participate in the study. The participants were assured of the confidentiality of all the information they were going to provide. They were also encouraged to participate in the study as much as they could but were also made aware that the study was voluntary and that they could withdraw at any point in time during the process if needed. There was no compensation for the study participants.

The study revealed that 45% of the respondents were between the ages of 20 and 30. Most of the respondents were in their twenties or thirties. Those who were in the first half of their work life constituted 73% of the respondents, while 17% were in the second half of their working life. The majority of the respondents were diploma midwives, representing 48% of the respondents; post basic midwives, constituting 32%; and degree and master’s holders, representing 19% and 1%, respectively. Staff midwives composed the largest group of respondents, while Principal Midwifery officers composed the group with the lowest participation in the study. The lowest rank in midwifery practice in the study was staff midwives, and the highest was principal midwifery officers. This is presented in Table  1 .

The experience of using local oxytocin to induce labour

Approximately 90% of the respondents have prior knowledge or heard that some of their clients take local oxytocin at home to start labour, and only 10% of respondents have no prior knowledge of that. Approximately 63.4% of the respondents encountered local oxytocin cases more than three times every week. This is presented in Fig.  1 .

Average number of local oxytocin cases per week

Approximately 72.9% of the respondents said that their clients had ever induced labour during the previous C/S, and 59.6% of the respondents said that they met clients who also induced their labour during twin pregnancy. Another 64.5% of the respondents said that they also met clients with large babies who also induced labour using local oxytocin, while 86.2% of the respondents said that they also met clients who induced labour with local oxytocin even when they had grand multiparity. Another 11.3% of the respondents said that they met clients who used local oxytocin to induce labour during transverse lies, and 15.3% of the respondents said that they had experienced when clients with mal presentations used local oxytocin to induce labour. This is presented in Fig.  2 .

Induction of labour by clients through local oxytocin under certain conditions

The study additionally asked midwives to report on how pregnant women who had taken local oxytocin to induce labour coped during their care. Midwives were expected to respond whether the women they cared for experienced good, difficult, bad, painful, life-threatening, terrible, or normal labour. As shown in Fig.  3 , generally, the experience that pregnant women experience when they use local oxytocin to induce labour is not good. A total of 93.5% of the respondents said that the women who used local oxytocin had very bad experiences.

Experience of using local oxytocin to induce labour

The study further revealed that 15.2% of the respondents had experienced situations where some pregnant women died because of the use of local oxytocin.

Effects of local oxytocin on the progress of labour

The effects of local oxytocin (Kaligutim) on the progress of labour were diverse. The study revealed that the effects of Kaligutim on the progress of labour are negative, as it causes prolonged labour for some, obstructed labour for others, precipitated labour, and poor progress of labour for others. With obstructed labour being the leading effect of kaligutim on the progress of labour, most of the respondents chose caesarean section as the preferred delivery for most clients who used kaligutim at birth. The use of local oxytocin also has some effect on the amniotic fluid of pregnant women, as 99% of the midwives who responded to the study said that there were some levels of stain of the amniotic fluid, and only 1% said it was clear. It is evident from the study that for most pregnant women who use local oxytocin, there is hyperstimulation of the uterus, as most of the midwives confirmed this for the study. Most pregnant women who use kaligutim suffer excessive contractions, which could have an effect on both mothers and babies. Again, more than half (53.75) of the respondents also said that their foetal heart rate was above 160 bpm. The majority (77.65) of the respondents said that there was no cessation of the contractions for those who took the local oxytocin. The results are presented in Table  2 .

Impact of local oxytocin on the outcome of labour

To understand how local oxytocin impacts labour, the study went further to ask participants what the mode of delivery was for those who used Kaligutim. According to the data, caesarean section is the mode of delivery for most women (56.5%) who use local oxytocin, and most are unable to achieve spontaneous delivery. This has contributed to the increasing number of caesarean sections recorded daily. Most of the babies had an Apgar score of 4/10 to 6/10. Many babies born to mothers who used herbal oxytocin were born with moderate birth asphyxia (69.6%) and severe birth asphyxia (24%). The study also reported that 20.8% of midwives reported that hysterectomy was carried out on their clients who had used herbal preparations to induce or hasten labour. This is alarming because many women have their uterus removed as a result of herbal oxytocin (kaligutm) usage. Most clients who used Kaligutim experienced postpartum haemorrhage after delivery. It was also evident that some pregnant women (34.5%) had uterine atony, although it cannot be said that Kaligutim was the cause of uterine atony. Several pregnant women (65.3 years old) who used Kaligutim also developed a ruptured uterus. See Table  3 .

Relationship between kaligutim (local oxytocin) use and birth outcome

Table  4 shows the associations between kaligutim (local oxytocin) use and birth outcomes among the respondents. Fisher’s exact test and the chi-square test showed that several birth outcome variables were significantly associated with kaligutim (local oxytocin). Do women who go through the normal process of labour and those who use kaligutim to induce their labour have the same birth outcome? (P value = 0.021), what was the foetal wellbeing? (P value = 0.041), When do most neonates whose mothers have taken Kaligutim die? (P value = 0.038), was baby admitted at the Newborn Care Unit? (P value = 0.001), were significantly associated with kaligutim. Additionally, having recorded a maternal death because of the use of Kaligutim (p value = 0.002) was also significantly associated with kaligutim, as presented in Table  4 .

Multivariate analysis of birth outcome predictors of Kaligutim (local oxytocin) among pregnant women in three major government hospitals in Tamale metropolis

In Table  5 , three birth outcome variables strongly depicted kaligutim use among the respondents: foetal wellbeing, admission to the new-born care unit, and death of most neonates because of the use of Kaligutim by their mothers. Respondents who responded, “yes” to baby admission to the Newborn Care Unit were 25% more likely to use kaligutim (local oxytocin) than were those who responded “no” to baby admission to the Newborn Care Unit [(AOR = 0.25 95% CI (0.01, 0.53), P  = 0.021)].

Discussions

Although the respondents cut across with regard to the number of years of experience, most of the respondents were early career midwives. The fact that these early career midwives are familiar with and have experienced the use of local oxytocin by their clients shows that it is widely used by pregnant women in the Tamale metropolis. Approximately 90% of respondents were aware of the usage of kaligutim (local oxytocin) for inducing labour at home before going to the hospital for delivery. However, a study conducted in the Ashanti region of Ghana revealed that midwives and other healthcare professionals lack proper knowledge about herbal medicine usage among pregnant women, even though this information is urgently needed so that appropriate action may be taken to address the issue [ 31 ]. The study findings also demonstrated that pregnant women frequently utilize local oxytocin and that many of them are unaware of the potential negative effects that these herbs may have on them in certain circumstances. Figure  2 shows that the use of local oxytocin was not limited to only one condition. These findings further show that the use of local oxytocin by pregnant women is widespread and that pregnant women do not know the effect that local oxytocin can have on them when they have certain conditions. Additionally, pregnant women are ignorant of the fact that local oxytocin can be contraindicated under certain conditions and must be avoided. Hence, it may put the life of the pregnant mother and her baby in danger.

Although herbal medicines are natural, not all herbs are safe to use while pregnant. Thus, expectant mothers should consult their midwives for guidance before taking herbal remedies. The experience that pregnant women have when they use local oxytocin to induce labour is not a positive one. A total of 188 respondents, or 93.5% of the respondents, stated that the women who used local oxytocin had a very unpleasant experience. This is supported by additional research results showing that between 50 and 80% of pregnant women use traditional plant remedies, which could have adverse perinatal effects [ 32 ]. The statistics indicate that local oxytocin is frequently used by pregnant women in the Tamale Metropolis. Most of the midwives reported seeing these cases virtually daily. This finding supports a study conducted in Ghana’s Ashanti region (Kumasi), which revealed that knowledge of herbal medicine is widely shared and that there is evidence of an increase in the usage of herbs [ 33 ].

The study revealed that local oxytocin (Kaligutim) has a diverse range of effects on the progress of labour, including precipitating labour, prolonging labour, obstructing labour, and slowing labour. The partograph is a great tool for keeping track of labour progress and serving as a warning system for abnormalities in normal labour, which helps to prevent obstructed labour and improves maternal and foetal outcomes [ 34 ]. This is supported by the study’s findings, which indicate that using a partograph to monitor labour progress and identify any deviations is essential [ 34 ].

According to this study, most midwives, who make up 65.2% of the respondents, also claimed that pregnant women who use local oxytocin (Kaligutim) have excessive contractions, while only 71 of them, or 34.8% of the respondents, claimed that they do not notice excessive contractions in their clients. This is supported by research performed in Zambia, which revealed that these herbal medicines also elicit greater than normal uterine contractions [ 26 ].

Most pregnant women who use kaligutim experience excessive contractions, which may have an impact on both the mother and the unborn child. Similarly, other authors have also claimed that using herbal remedies during labour causes stronger and more frequent uterine contractions, which do not necessarily result in cervical dilatation [ 35 ]. This was confirmed in the study’s findings, which also noted that herbal oxytocin not only produces excessive uterine contractions but also may cause contractions to cease, as 44 (22.4%) of the respondents reported that those who took local oxytocin had a halt in contractions. Intravenous fluids such as normal saline and Ringer’s lactate are used to flush out the local oxytocin in the system and CS in the case of an emergency. Nifedipine is also given in certain circumstances to prevent contractions.

According to the study, 121 midwives, or 59.6% of the respondents, stated that caesarean sections were the preferred method of delivery for women who used kaligutim to induce labour. Both [ 36 ] in South Africa and [ 34 ] in Western Uganda reported these findings. Moderate birth asphyxia (69.6%) and severe birth asphyxia (23%) are common in newborns whose mothers utilize herbal oxytocin. According to the survey, 20.8% of midwives said they had performed hysterectomy procedures on clients who had utilized herbal induction or hastening methods to induce labour.

One of the main causes of maternal deaths worldwide, including in Ghana, is postpartum haemorrhage [ 10 ]. 91% of midwives said that when their patients use herbal oxytocin during labour, more of them suffer from postpartum haemorrhage. This is corroborated by research by Frank (2018), who found a connection between postpartum haemorrhage and the use of herbal medications during labour [ 37 ]. In contrast, other studies [ 38 ] have shown that using herbal medication during childbirth is linked to a lower risk of postpartum haemorrhage. Individuals who experienced postpartum haemorrhage were managed with uterine massage, intravenous fluids, Cytotec, repairs to tears, expulsion of retained products, blood transfusions, cervical repairs, and catheter use.

This report supports the findings of a study conducted in the Ugandan village of Kiganda, where the researcher [ 37 ] reported that the use of herbal medicines has been linked to labour induction, which can cause significant birth canal tearing, postpartum haemorrhage, uterine atony, a raptured uterus, and, if untreated, maternal mortality. Medical experts who are aware of the dangers of herbal remedies and who are obliged to advise patients against using them do so themselves. The majority of women who use herbal preparations during pregnancy have a high school education or higher, according to evidence showing that more than 57.5% of pregnant women who use herbs have a high school diploma or higher, which is consistent with findings from Saudi Arabia by [ 39 ] that show that formal education cannot even prevent women from taking herbs during pregnancy and labour.

Kaligutim also causes excessive uterine contractions, foetal discomfort, excessive uterine stimulation, uterine atony, PPH, birth hypoxia, and premature bearing down, claims this study. This is supported by the results of a study carried out in Europe, where researchers [ 40 ] found that the majority of herbal drugs taken by pregnant women have undesirable side effects. An Iranian study, however, revealed that utilizing herbal treatments during labour can lessen discomfort, speed up the process, and enhance both the quality of a woman’s delivery experience and her odds of having a healthy baby [ 41 ].

According to the study’s findings, three birth outcome variables strongly affected kaligutim (local oxytocin) use among the respondents: foetal wellbeing, admission to the newborn care unit, and death of most neonates as a result of the use of Kaligutim by their mothers. Respondents who responded, “yes to baby” and were admitted to the new-born care unit were 25% more likely to use kaligutim (local oxytocin) than were those who responded, “no to baby” and were admitted to the new-born care unit (AOR = 0.25 95% CI (0.01, 0.53), P  = 0.021). This is probably one of the effects of taking local oxytocin. These infants were hospitalized for a variety of reasons, including asphyxia, respiratory distress, and low Apgar scores.

Additionally, the study results indicated that respondents who responded that a still birth outcome affected foetal wellbeing were 1.9 times more likely to use kaligutim (local oxytocin) than those who responded no to having live births were (AOR = 1.9 95% CI (0.01, 1.21), P  = 0.047)]. This finding is consistent with findings from a sub-Saharan African study that showed that herbal medications used to speed up and induce labour have uterotonic effects and increase the risk of neonatal asphyxia attributable to uterine hyperstimulation [ 42 ]. This could be ascribed to the fact that the respondents wanted fast and easy delivery, which subsequently caused this effect.

Another interesting finding was that respondents who responded that having a birth asphyxia outcome to foetal wellbeing were 0.16 times more likely to use kaligutim (local oxytocin) than were those who responded no to having live births (AOR = 0.16, 95% CI (0.08, 3.08), P  = 0.047). This result is similar to that of [ 42 ], who conducted their study in sub-Saharan Africa. This could be a result of the effects of kaligutim on foetal well-being, which results in birth asphyxia.

Furthermore, newborns whose mothers used kaligutim during labour and who died within the first hour of birth were 3.4 times more likely to use kaligutim (local oxytocin) than those whose mothers used kaligutim during labour [AOR = 3.4 95% CI (0.74, 1.5), P  = 0.045]. In support of the findings from this study, a study on the consumption of herbal drugs among pregnant women in rural Malawi revealed that consumption was linked to pregnancy-related issues and that users had a greater risk of neonatal mortality/morbidity within the first hour of life than nonusers [ 14 ]. This could be attributed to the dangers this herb poses to the foetus during delivery.

Newborns whose mothers used kaligutim during labor and who died within the first week of life were 2.23 times more likely to use kaligutim (local oxytocin) than those whose mothers used intrauterine kaligutim [(AOR = 2.23 95% CI (0.00, 0.02), P  = 0.045)]. This is supported by findings from a Malawian study that revealed that the use of labour-inducing plants during pregnancy has negative effects on obstetric and labour outcomes, such as uterine rapture, which can cause neonatal mortality and morbidity [ 35 ]. This could be attributed to the fact that PPH, uterine rapture, cervical tear, DIC, and hypoxia were the main causes of death.

Every life matter, which is why mothers’ lives and that of their newborn babies must be safeguarded at all costs. A sufficient level of knowledge is always vital since it exacerbates doubt. Therefore, it is crucial that people are informed of their rights, their health, and the services they can utilize to maintain and improve health to have a healthy increasing population. Although herbal medicine could be effective in treating certain ailments associated with pregnancy and delivery and is easily accessible to pregnant women, especially in rural communities, the possibility of overdose, drug-herb interactions, contraindications, and the unhygienic conditions under which they are prepared may influence both maternal and neonatal conditions.

The results showed that the use of kaligutim by pregnant women in Tamale Metropolis is on the rise. This means that much needs to be done to do away with the use of kaligutim, and this must start with midwives. Pregnancies and births can be improved with a healthy and qualified midwifery care model in improving and protecting women’s and newborn health in Tamale.

It can be concluded that the use of this herbal medicine (Kaligutim) poses a greater long-term health challenge for mothers and their babies. Midwives and other healthcare workers in the Tamale Metropolis must therefore intensify their public health campaigns against the use of Kaligutim for labour induction.

Recommendations

The findings of the study have important implications for maternal and child health. The nonuse of kaligutim (local oxytocin) for the induction of labour is the best option for pregnant women. Pregnant women should visit the hospital for all their health needs during the entire pregnancy. This will help prevent adverse pregnancy and labour outcomes as well as maternal and neonatal mortalities and morbidities.

Future researchers should perform further studies on the spiritual aspects of kaligutim (Walgu) and its types. Like synthetic oxytocin, an Islamic form of oxytocin is prepared by Mallams and causes uterine contractions and dilates the cervix.

However, studies should also be conducted on the efficiency, effectiveness and biochemical composition of these herbal preparations and their safety, especially during pregnancy and delivery. Samples of these herbal preparations should be taken for laboratory investigations.

Data availability

All data generated or analysed during this study are included in this article and its supplementary information files are available from the corresponding author on reasonable request.

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Acknowledgements

We thank the Management and Healthcare Staff of the Tamale West Hospital (T.W.H), Tamale Central Hospital (T.C.H) and Tamale Teaching Hospital (TTH) for their support throughout the data collection process. We acknowledge the contributions of all the midwives who shared their knowledge and experiences with us, your efforts are well appreciated.

No funding was available for the study.

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Contributions

ASA and SD conceptualised and drafted the research proposal. ASA, SD, and JL performed the statistical analysis, assisted with interpretation of the results, and co-drafted the manuscript. All authors contributed to the discussion of the paper, read, and approved the final manuscript.

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Correspondence to Ahmad Sukerazu Alhassan .

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An introductory letter from the University for Development Studies was presented to the three government hospitals, Tamale West Hospital (T.W.H), Tamale Central Hospital (T.C.H) and Tamale Teaching Hospital (TTH) to seek for permission to undertake the study. Ethical clearance was also obtained from the Kwame Nkrumah University of Science and Technology (KNUST) with reference number (CHRPE/AP/332/22). Permission was also sought through a consent form of which participants were asked to consent to if they were willing to participate in the study. They were assured of confidentiality of every information they were going to provide. All other methods were performed in accordance with relevant guidelines and regulations on subject selection and participation.

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Alhassan, A.S., Dakurah, S. & Lasong, J. Perspectives of midwives on the use of Kaligutim (local oxytocin) for induction of labour among pregnant women in the government hospitals in Tamale. BMC Pregnancy Childbirth 24 , 561 (2024). https://doi.org/10.1186/s12884-024-06745-z

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Received : 15 April 2024

Accepted : 08 August 2024

Published : 28 August 2024

DOI : https://doi.org/10.1186/s12884-024-06745-z

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• Local oxytocin
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