{"title":"Machine Learning and the Digital Measurement of Psychological Health.","authors":"Isaac R Galatzer-Levy, Jukka-Pekka Onnela","doi":"10.1146/annurev-clinpsy-080921-073212","DOIUrl":null,"url":null,"abstract":"<p><p>Since its inception, the discipline of psychology has utilized empirical epistemology and mathematical methodologies to infer psychological functioning from direct observation. As new challenges and technological opportunities emerge, scientists are once again challenged to define measurement paradigms for psychological health and illness that solve novel problems and capitalize on new technological opportunities. In this review, we discuss the theoretical foundations of and scientific advances in remote sensor technology and machine learning models as they are applied to quantify psychological functioning, draw clinical inferences, and chart new directions in treatment.</p>","PeriodicalId":50755,"journal":{"name":"Annual Review of Clinical Psychology","volume":"19 ","pages":"133-154"},"PeriodicalIF":17.8000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Clinical Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1146/annurev-clinpsy-080921-073212","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY","Score":null,"Total":0}
引用次数: 1
Abstract
Since its inception, the discipline of psychology has utilized empirical epistemology and mathematical methodologies to infer psychological functioning from direct observation. As new challenges and technological opportunities emerge, scientists are once again challenged to define measurement paradigms for psychological health and illness that solve novel problems and capitalize on new technological opportunities. In this review, we discuss the theoretical foundations of and scientific advances in remote sensor technology and machine learning models as they are applied to quantify psychological functioning, draw clinical inferences, and chart new directions in treatment.
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.
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