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Psykologtidningen

Sveriges Psykologförbund

Studiemetod som ger svar på individnivå

12 mars 2020 publicerad av Peter Örn

Medan RCT-studier ger genomsnittliga svar för gruppen visar single case-studier förändringar för en unik individ i en specifik kontext. Metoden överbryggar klyftan mellan forskning och klinik och den får nu allt större uppmärksamhet inom psykologisk forskning skriver psykologiforskarna Rikard Wicksell och Johan W.S Vlaeyen.

Vården blir alltmer individualiserad. Genombrott inom genetiken har banat väg för personalized medicine utifrån idén att varje patient är unik och att förmågan att anpassa behandlingen till de unika behoven är avgörande för behandlingseffekten. Lättillgängliga data skapar också förutsättningar för att involvera patienten mer i besluts- och förändringsprocesser.

Randomiserade kontrollerade studier (RCT) har under lång tid ansetts vara gold standard för att utvärdera behandlingseffekter och verksamma mekanismer. Men de flesta av våra evidensbaserade behandlingar har endast en moderat effekt och dessutom med en stor individuell variation. Utan att förringa betydelsen av RCT som utvärderingsmetod finns uppenbara svårigheter att dra meningsfulla slutsatser om effekter på en enskild individ. Geriatrikern John Evans sammanfattade kärnfullt dilemmat med gruppbaserade jämförelser: »Managers and trialists may be happy for treatments to work on average patient’s doctors expect to do better than that” [1].

I takt med att en mer nyanserad bild av RCT:s betydelse växt fram har många forskare lyft dilemmat med att den »genomsnittliga personen« inte existerar och att resultaten (effekten av interventionen på gruppnivå) därför inte kan anses vara ett riktmärke för hur en enskild individ kan förväntas svara på behandlingen. Dessutom är det väl känt att denna typ av studier vanligtvis har studiekriterier som gör att komplexa patienter exkluderas exempelvis patienter med samsjuklighet. Den kanske allra mest uppenbara svårigheten är behovet av och tillgången till stora forskningssampel. Detta skapar ofta betydande problem både avseende tid och kostnad för att genomföra studien.

Sammantaget har generaliserbarheten (och därmed validiteten) av stora randomiserade kliniska prövningar ifrågasatts. För att studera sambandet mellan intervention och förändring för en enskild individ behövs en annan modell. Det har gjort att SCED på senare tid har fått allt större uppmärksamhet inte minst i psykologisk behandlingsforskning.

Single-case experimental designs (SCED)

SCED (betecknas ibland n=1 och N-of-1) bygger enkelt uttryckt på en serie av observationer under en fördefinierad period som innefattar en baslinje med randomiserad längd och (minst) en experimentell manipulation (interventionen).

Under lång tid har SCED haft en framträdande roll i psykologisk och medicinsk forskning där studier av ett fåtal individer lagt grunden för avgörande kunskapsutveckling. Ett av de mest kända exemplen är Pavlovs studier som byggde på observationer av reaktionsmönster hos enskilda individer vilka validerades genom att replikera fynden med andra deltagare [2]. SCED är i dag ett väletablerat och tillförlitligt sätt att utvärdera förändringen för en enskild enhet (en patient, en grupp, en familj ett sjukhus, en region etcetera). Metodens betydelse har nyligen lyfts fram i tidskriften Nature. I en artikel om »imprecision medicine« beskrivs att de vanligaste förskrivna läkemedlen i USA hjälper en bråkdel av de som använder dem (4–25 procent). Artikelförfattarens budskap är att precision medicine kräver något mer än klassiska kliniska prövningar (RCT) och argumenterar för att lösningen är: »transforming everyday cli-nical care into solid N-of-1 trials« [3].

SCED har flera viktiga fördelar jämfört med gruppbaserade studier. Framförallt ges möjligheten att studera förändring för en unik individ i en specifik kontext vilket klargör de förutsättningar som råder när en intervention fungerar. Kontinuerlig information om utvecklingen ger också möjligheten till grafisk visualisering i realtid.

Genom dessa möjligheter överbryggar SCED också klyftan mellan forskning och klinik. Skillnaderna mellan vetenskapliga studier och väl genomförd behandling minskar när data på individnivå används systematiskt för såväl kunskapsutveckling som beslut i sjukvården. Både för kliniska ändamål och forskning utgör SCED en värdefull metod för att exempelvis följa utvecklingen av bieffekter i fall när klinikern känner sig osäker på lämpligheten av en viss behandling eller när teamet kring patienten inte är överens. En kontinuerlig insamling av data och monitorering av effekterna skapar en tydlighet som är gynnsam både för patienten och för teamet.

Bakgrunden till SCED

Utvecklingen av SCED är besläktad med ambitionen att skapa en yrkesroll för psykologer som sammanför det vetenskapliga förhållningssättet med den kliniska uppgiften. Konferensen i Boulder i Colorado 1949 arrangerades av American Psychological Association (APA) i en efterkrigstid där psykisk ohälsa ökade som en effekt av hemvändande soldater. Under två veckor diskuterades professionsfrågor som utbildning licens samarbete med andra professioner och etiska aspekter. Konferensen mest framträdande slutsats var definitionen av psykologen som en scientist-practitioner med träning både i vetenskaplig metod och kliniska färdigheter och som naturligt och systematiskt samlar in och analyserar data för att fatta beslut förbättra de kliniska metoderna utveckla professionen och bidra till kunskapsutvecklingen.

I dag 70 år senare kan konstateras att vi har en bit kvar men trots allt är på rätt väg. Klyftan mellan klinik och forskning är dock tydlig inom psykologin såväl som inom andra ämnesområden av relevans för hälso- och sjukvård [4].

Varför RCT och inte SCED som gold standard?

Psykologin är i grunden en lära om individen. Trots detta så är merparten av den kunskap vi har om psykologiska faktorer baserad på data från grupper. Hur kommer det sig att vi styrt bort från traditionen att orientera analysen utifrån den enskilde patienten till förmån för utvärderingar som bygger på gruppdata och avvikelser från medelvärden?

I början av 1900-talet inspirerad av Darwins studier om evolutionen fanns en allt ökande trend att studera individuella skillnader och avvikelser från den »genomsnittlige« individen. Detta lade grunden för metodologin (inklusive statistiska modeller) bakom gruppbaserad forskning. En viktig representant för denna nya inriktning var Sir Ronald Fisher vars engage-mang bland annat rörde huruvida studier på enskilda sampel kan generera kunskap av betydelse för en hel population. Med utvecklingen av sofistikerade statistiska test kom Fisher att bana väg för en ökande andel gruppbaserad forskning som över tid kom att etablera randomiserade kontrollerade studier som den optimala modellen en »gold standard« [5]. Gruppbaserad forskning var dock inte lösningen på alla problem och genererade dessutom en del nya som att det unika hos individen och kontexten fick mindre uppmärksamhet.

I juni 2000 samlades kliniska forskare vid the Institute of Medicine för att diskutera den allt ökande farhågan för att viktiga forskningsfynd ofta inte nådde hela vägen fram till en till-lämpning där tydliga nyttoeffekter på individer och samhället kan identifieras. Detta bidrog till en ökad angelägenhet kring det som kommit att kallas translational science att överföra nya fynd och metoder från grundforskning till förbättrade modeller för den kliniska användningen. Två typer av translationell forskning kan identifieras. Dels studier som görs i grundforskningsmiljöer där forskare eftersträvar att fynden ska kunna omsättas i praktiska metoder dels kliniska studier där nya rön från grundforskningen ligger till grund för exempelvis nya interventioner som testas i kliniska prövningar med verkliga patienter.

På senare tid har argumenterats för att samhällets forskningsresurser i alltför stor utsträckning ägnas åt den första typen vilket är bekymmersamt av flera skäl. Förutom att grundforskningsfynd ofta fastnar på den långa och krokiga vägen mot förbättrade kliniska metoder som förbättrar folkhälsan finns i dag också en medvetenhet om att sjukvården skulle ha större nytta av att studera hur existerande (evidensbaserade) metoder kan tillgängliggöras och användas än att utveckla nya metoder.

Behovet av den kliniska forskningen är således skriande och bör klargöra hur verkliga patienter snarare än den »genomsnittlige individen« svarar på behandlingen vilket med tydlighet indikerar värdet av SCED.

Visuella analyser

Den huvudsakliga uppgiften i kliniska studier är att bedöma om en förändring har skett. Inom SCED har visuella analysmetoder förespråkats under lång tid. I den enklaste modellen jämförs en baslinje (A) med en förändringsfas (B) där en tydlig effekt bör kunna åskådliggöras genom en graf.

Tre aspekter är av särskild betydelse för att generera tydliga effekter: robusta mått (exempelvis frekvensen av beteenden) som är känsliga för den förändring som utvärderas en stabil baslinje (ej för stor variation) samt en tydlig och helst snabb effekt. Detta är inte alltid enkelt. En tydlig idé om behandlingsmekanismer och måttens känslighet för förändring blir därför viktigt.

En systematisk visuell analys ger en stor mängd relevant information som är svåråtkomlig i gruppdata hur stabil baslinjedata är om någon uppenbar förändring skett när den upp-stått och hur stabil denna effekt är. För att underlätta den visuella analysen och värdera resultaten finns användbara riktlinjer för tolkning [6].

Statistiska metoder när visuell analys inte räcker

Även om det i många fall kan vara tillräckligt med visuella analysmetoder så finns tillfällen då statistiska svar efterfrågas. Enkla statistiska tillvägagångssätt kan användas som komplement till visuella analyser för att bedöma storleken på effekten som att räkna antalet observationer i förändringsfasen (B) ovanför baslinjefasens (A) medelvärde. Men även mer avancerade statistiska analyser har sin plats inom SCED. För drygt 40 år sedan skrev Donald Hartmann en betydelsefull artikel där han poängterade att av statistiska analyser som är utvecklade för användning på gruppdata medför stora begränsningar och tolkningsproblem när de används för enskilda individer. Han pekade i riktning mot andra modeller som sedan dess vidare-utvecklats och med framgång använts för SCED [7].

Utöver robusta statistiska modeller finns användarvänliga digitala lösningar som möjliggör analyser av individdata exempelvis Shiny som utvecklats vid universitetet i Leuven och er-bjuds via the Open Science Framework vid universitetet i Barcelona https://osf.io/t6ws6/.

Sammanställa data och dra slutsatser

Antalet SCED-studier inom klinisk psykologi har ökat lavinartat de senaste 50 åren. Dock brister många i metodkvalitet och/eller i hur väl studien har beskrivits vilket inverkar negativt på den vetenskapliga nyttan av studierna. En viktig utveckling skedde för cirka 20 år sedan då CONSORT (Consolidated Standards Of Reporting Trials) Statement formulerades i syfte att klargöra hur en vetenskaplig rapport bör formuleras. Dessa rekommendationer följs världen över och i dag finns tydliga riktlinjer också för SCED bland annat Single-Case Reporting guideline In Behavioural interventions (SCRIBE) [8]. SCRIBE har anammats av American Psychologial Association och består av en checklista med 26 items inom sex områden vilka täcker alla delar av den vetenskapliga studien från titel till metod resultat och diskussion.

Genom riktlinjer för genomförande och rapportering av SCED kan kvaliteten på studierna och dess betydelse för kunskapsutvecklingen successivt öka.

Vägen framåt

SCED har utvecklats väsentligt de senaste decennierna bland annat statistiska modeller och digitala lösningar för datasamling och visualisering av resultat. Dessutom har riktlinjer för genomförande och rapportering förbättrat förutsättningarna för kvalitet transparens och värdering av resultaten. Sedan 2017 finns också ett internationellt nätverk med syftet att tillhan-dahålla kunskap och skapa förutsättningar för diskussion och samarbete relaterat till SCED the International Collaborative Network for N-of-1 Clinical Trials and Single-Case Experimen-tal Designs (ICN) https://nof1andsced.wixsite.com/home.

År 2018 anordnades den första internationella konferensen om SCED genom ett samarbete mellan Karolinska Iinstitutet och KU Leuven University: N=1 Stockholm symposium med nära 250 deltagare från såväl Europa som USA och Kanada. I samband med planeringen av ett specialnummer i tidskriften Psychological records riktades en förfrågan om att skriva en artikel om SCED utifrån symposiet och denna artikel utgör grunden för denna text [9]. Nästa möte hålls den 7–8 april 2020 i Leuven i Belgien.

1. Evans JG (1995). Evidence-based and evidence-biased medicine. Age and Ageing 24(6) 461-463. 2. Barlow DH Nock MK & Hersen M (2009). Single Case Experimental Designs: Strategies for Studying Behavior Change 3rd Edition. New York: Pearson. 3. Schork NJ (2015). Personalized medicine: Time for one-person trials. Nature 520(7549) 609-611. 4. Smith LS & Wilkins N (2018). Mind the Gap: Approaches to Addressing the Research-to-Practice Practice-to-Research Chasm. J Public Health Manag Pract 24 Suppl 1 Suppl Injury and Violence Prevention S6-S11. 5. Grossman J & Mackenzie F J (2005). The randomized controlled trial: gold standard or merely standard? Perspect Biol Med 48(4) 516-534. 6. Morley S (2017). Single Case Methods in Clinical Psychology. A Practical Guide. 7. Manolov R & Moeyaert M (2017). How Can Single-Case Data Be Analyzed? Software Resources Tutorial and Reflections on Analysis. Behav Modif 41(2) 179-228. 8. Tate RL Perdices M Rosenkoetter U et al. (2016). The Single-Case Reporting guideline In Behavioural Interventions (SCRIBE) 2016 Statement. Archives of Scientific Psychology. 4(1) 1-9. 9. Vlaeyen JWS Wicksell RK Simons LE et al. From Boulder to Stockholm in 70 years: Single case experimental designs in health research. Under review.

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Single-Case Studies as Topic

Enkelfallstudier som ämne, engelsk definition.

Trials that consider an individual patient as the sole unit of observation in a study investigating the efficacy or side-effects of different interventions to determine the optimal intervention for an individual patient using objective data-driven criteria.

Svenska synonymer

Enkelfallstudier

Engelska synonymer

Single Case Studies as Topic — N-of-1 Trials as Topic — N of 1 Trials as Topic — Single-Subject Trial — Single Subject Trial — Single-Subject Trials — Trial, Single-Subject — Trials, Single-Subject — Single-Case Study — Single Case Study — Single-Case Studies — Studies, Single-Case — Study, Single-Case — Single-Case Trial — Single Case Trial — Single-Case Trials — Trial, Single-Case — Trials, Single-Case

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• Perspective
• Published: 22 November 2022

Single case studies are a powerful tool for developing, testing and extending theories

• Lyndsey Nickels   ORCID: orcid.org/0000-0002-0311-3524 1 , 2 ,
• Simon Fischer-Baum   ORCID: orcid.org/0000-0002-6067-0538 3 &
• Wendy Best   ORCID: orcid.org/0000-0001-8375-5916 4  

Nature Reviews Psychology volume  1 ,  pages 733–747 ( 2022 ) Cite this article

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Psychology embraces a diverse range of methodologies. However, most rely on averaging group data to draw conclusions. In this Perspective, we argue that single case methodology is a valuable tool for developing and extending psychological theories. We stress the importance of single case and case series research, drawing on classic and contemporary cases in which cognitive and perceptual deficits provide insights into typical cognitive processes in domains such as memory, delusions, reading and face perception. We unpack the key features of single case methodology, describe its strengths, its value in adjudicating between theories, and outline its benefits for a better understanding of deficits and hence more appropriate interventions. The unique insights that single case studies have provided illustrate the value of in-depth investigation within an individual. Single case methodology has an important place in the psychologist’s toolkit and it should be valued as a primary research tool.

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The authors thank all of those pioneers of and advocates for single case study research who have mentored, inspired and encouraged us over the years, and the many other colleagues with whom we have discussed these issues.

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Nickels, L., Fischer-Baum, S. & Best, W. Single case studies are a powerful tool for developing, testing and extending theories. Nat Rev Psychol 1 , 733–747 (2022). https://doi.org/10.1038/s44159-022-00127-y

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On the History of Single-Case Methodology: A Data-Based Analysis

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To provide context surrounding the history of single-case research and to act as a benchmark for which future changes across the fields and disciplines that use single-case methods may be compared, we conducted this study to serve as an update and extension on the trends and prevalence of single-case research in the peer-reviewed literature. Our analytical sample was derived from 20 peer-reviewed journals over a 40-year timespan. Results indicate that since 1978, approximately one in six publications within our examined body of research employed a single-case research design. Exploratory moderator analyses revealed that a journal’s focus on behavior analytic research, and a journal’s impact factor moderated the prevalence of single-case publications within a journal. We discuss our findings in relation to prior studies examining the prevalence and trends of single-case research and future directions for single-case researchers to improve the quality, value, and understanding of single-case methodology ( https://osf.io/fns3m/ ).

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We would like to thank Maddie Calzi, Rachel Jacob, Hannah Keene, Katelyn Nicklow, Kaitlin O’Neil, Meredith Davis, Bryn Handley, and Hannah Dollinger for their assistance with this project.

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Shepley, C., Shepley, S.B. & Spriggs, A.D. On the History of Single-Case Methodology: A Data-Based Analysis. J Behav Educ 33 , 163–183 (2024). https://doi.org/10.1007/s10864-022-09477-2

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Accepted : 13 April 2022

Published : 29 April 2022

Issue Date : March 2024

DOI : https://doi.org/10.1007/s10864-022-09477-2

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