Angela Sorgente, Rossella Caliciuri, Matteo Robba, Margherita Lanz, Bruno D Zumbo
{"title":"心理学中潜在阶级分析的系统回顾:检查指南与研究实践之间的差距。","authors":"Angela Sorgente, Rossella Caliciuri, Matteo Robba, Margherita Lanz, Bruno D Zumbo","doi":"10.3758/s13428-025-02812-1","DOIUrl":null,"url":null,"abstract":"<p><p>Latent class analysis (LCA) can help identify unobserved classes of individuals in a population based on collected categorical data. It is commonly used in psychology to test hypotheses about sources of heterogeneity and class characteristics. However, careful decision-making is required in the modeling process. Its flexibility may explain why it is becoming more commonly used in psychology; however, it also highlights that there are many decision points in the modeling process, thus warranting a systematic literature review to document the use of LCA in psychology, mapping both the prevalence and quality of LCA studies. This systematic review followed the PRISMA guidelines and involved a comprehensive search across multiple databases, yielding 7,580 records related to latent class analysis. After removing duplicates and selecting a representative subsample, 377 documents were assessed for eligibility. Of these, 251 publications (comprising 313 LCAs) met the inclusion and exclusion criteria and were reviewed for this study. Each study was meticulously coded to map how the authors performed and reported each step of the LCA. Our analysis of these studies, in comparison with published guidelines, revealed notable discrepancies in how LCA is applied and reported. To support researchers in enhancing the quality of future LCA applications, we summarize key recommendations in a final section that outlines best practices for future LCA applications. The findings indicate a growing use of LCA in psychology but also highlight the need for greater methodological rigor and transparency in its implementation.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 11","pages":"301"},"PeriodicalIF":3.9000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12494633/pdf/","citationCount":"0","resultStr":"{\"title\":\"A systematic review of latent class analysis in psychology: Examining the gap between guidelines and research practice.\",\"authors\":\"Angela Sorgente, Rossella Caliciuri, Matteo Robba, Margherita Lanz, Bruno D Zumbo\",\"doi\":\"10.3758/s13428-025-02812-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Latent class analysis (LCA) can help identify unobserved classes of individuals in a population based on collected categorical data. It is commonly used in psychology to test hypotheses about sources of heterogeneity and class characteristics. However, careful decision-making is required in the modeling process. Its flexibility may explain why it is becoming more commonly used in psychology; however, it also highlights that there are many decision points in the modeling process, thus warranting a systematic literature review to document the use of LCA in psychology, mapping both the prevalence and quality of LCA studies. This systematic review followed the PRISMA guidelines and involved a comprehensive search across multiple databases, yielding 7,580 records related to latent class analysis. After removing duplicates and selecting a representative subsample, 377 documents were assessed for eligibility. Of these, 251 publications (comprising 313 LCAs) met the inclusion and exclusion criteria and were reviewed for this study. Each study was meticulously coded to map how the authors performed and reported each step of the LCA. Our analysis of these studies, in comparison with published guidelines, revealed notable discrepancies in how LCA is applied and reported. To support researchers in enhancing the quality of future LCA applications, we summarize key recommendations in a final section that outlines best practices for future LCA applications. The findings indicate a growing use of LCA in psychology but also highlight the need for greater methodological rigor and transparency in its implementation.</p>\",\"PeriodicalId\":8717,\"journal\":{\"name\":\"Behavior Research Methods\",\"volume\":\"57 11\",\"pages\":\"301\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12494633/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Behavior Research Methods\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.3758/s13428-025-02812-1\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behavior Research Methods","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.3758/s13428-025-02812-1","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
A systematic review of latent class analysis in psychology: Examining the gap between guidelines and research practice.
Latent class analysis (LCA) can help identify unobserved classes of individuals in a population based on collected categorical data. It is commonly used in psychology to test hypotheses about sources of heterogeneity and class characteristics. However, careful decision-making is required in the modeling process. Its flexibility may explain why it is becoming more commonly used in psychology; however, it also highlights that there are many decision points in the modeling process, thus warranting a systematic literature review to document the use of LCA in psychology, mapping both the prevalence and quality of LCA studies. This systematic review followed the PRISMA guidelines and involved a comprehensive search across multiple databases, yielding 7,580 records related to latent class analysis. After removing duplicates and selecting a representative subsample, 377 documents were assessed for eligibility. Of these, 251 publications (comprising 313 LCAs) met the inclusion and exclusion criteria and were reviewed for this study. Each study was meticulously coded to map how the authors performed and reported each step of the LCA. Our analysis of these studies, in comparison with published guidelines, revealed notable discrepancies in how LCA is applied and reported. To support researchers in enhancing the quality of future LCA applications, we summarize key recommendations in a final section that outlines best practices for future LCA applications. The findings indicate a growing use of LCA in psychology but also highlight the need for greater methodological rigor and transparency in its implementation.
期刊介绍:
Behavior Research Methods publishes articles concerned with the methods, techniques, and instrumentation of research in experimental psychology. The journal focuses particularly on the use of computer technology in psychological research. An annual special issue is devoted to this field.