{"title":"基于测量和数据的心理治疗。","authors":"Wolfgang Lutz, Brian Schwartz, Jaime Delgadillo","doi":"10.1146/annurev-clinpsy-071720-014821","DOIUrl":null,"url":null,"abstract":"<p><p>Outcome measurement in the field of psychotherapy has developed considerably in the last decade. This review discusses key issues related to outcome measurement, modeling, and implementation of data-informed and measurement-based psychological therapy. First, an overview is provided, covering the rationale of outcome measurement by acknowledging some of the limitations of clinical judgment. Second, different models of outcome measurement are discussed, including pre-post, session-by-session, and higher-resolution intensive outcome assessments. Third, important concepts related to modeling patterns of change are addressed, including early response, dose-response, and nonlinear change. Furthermore, rational and empirical decision tools are discussed as the foundation for measurement-based therapy. Fourth, examples of clinical applications are presented, which show great promise to support the personalization of therapy and to prevent treatment failure. Finally, we build on continuous outcome measurement as the basis for a broader understanding of clinical concepts and data-driven clinical practice in the future.</p>","PeriodicalId":50755,"journal":{"name":"Annual Review of Clinical Psychology","volume":null,"pages":null},"PeriodicalIF":17.8000,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Measurement-Based and Data-Informed Psychological Therapy.\",\"authors\":\"Wolfgang Lutz, Brian Schwartz, Jaime Delgadillo\",\"doi\":\"10.1146/annurev-clinpsy-071720-014821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Outcome measurement in the field of psychotherapy has developed considerably in the last decade. This review discusses key issues related to outcome measurement, modeling, and implementation of data-informed and measurement-based psychological therapy. First, an overview is provided, covering the rationale of outcome measurement by acknowledging some of the limitations of clinical judgment. Second, different models of outcome measurement are discussed, including pre-post, session-by-session, and higher-resolution intensive outcome assessments. Third, important concepts related to modeling patterns of change are addressed, including early response, dose-response, and nonlinear change. Furthermore, rational and empirical decision tools are discussed as the foundation for measurement-based therapy. Fourth, examples of clinical applications are presented, which show great promise to support the personalization of therapy and to prevent treatment failure. Finally, we build on continuous outcome measurement as the basis for a broader understanding of clinical concepts and data-driven clinical practice in the future.</p>\",\"PeriodicalId\":50755,\"journal\":{\"name\":\"Annual Review of Clinical Psychology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":17.8000,\"publicationDate\":\"2022-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review of Clinical Psychology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-clinpsy-071720-014821\",\"RegionNum\":1,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/12/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Clinical Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1146/annurev-clinpsy-071720-014821","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/12/15 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY","Score":null,"Total":0}
Measurement-Based and Data-Informed Psychological Therapy.
Outcome measurement in the field of psychotherapy has developed considerably in the last decade. This review discusses key issues related to outcome measurement, modeling, and implementation of data-informed and measurement-based psychological therapy. First, an overview is provided, covering the rationale of outcome measurement by acknowledging some of the limitations of clinical judgment. Second, different models of outcome measurement are discussed, including pre-post, session-by-session, and higher-resolution intensive outcome assessments. Third, important concepts related to modeling patterns of change are addressed, including early response, dose-response, and nonlinear change. Furthermore, rational and empirical decision tools are discussed as the foundation for measurement-based therapy. Fourth, examples of clinical applications are presented, which show great promise to support the personalization of therapy and to prevent treatment failure. Finally, we build on continuous outcome measurement as the basis for a broader understanding of clinical concepts and data-driven clinical practice in the future.
期刊介绍:
The Annual Review of Clinical Psychology is a publication that has been available since 2005. It offers comprehensive reviews on significant developments in the field of clinical psychology and psychiatry. The journal covers various aspects including research, theory, and the application of psychological principles to address recognized disorders such as schizophrenia, mood, anxiety, childhood, substance use, cognitive, and personality disorders. Additionally, the articles also touch upon broader issues that cut across the field, such as diagnosis, treatment, social policy, and cross-cultural and legal issues.
Recently, the current volume of this journal has transitioned from a gated access model to an open access format through the Annual Reviews' Subscribe to Open program. All articles published in this volume are now available under a Creative Commons Attribution License (CC BY), allowing for widespread distribution and use. The journal is also abstracted and indexed in various databases including Scopus, Science Citation Index Expanded, MEDLINE, EMBASE, CINAHL, PsycINFO, and Academic Search, among others.