机器学习和心理健康的数字测量。

IF 17.8 1区心理学 Q1 PSYCHOLOGY Annual Review of Clinical Psychology Pub Date : 2023-05-09 DOI:10.1146/annurev-clinpsy-080921-073212

Isaac R Galatzer-Levy, Jukka-Pekka Onnela

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引用次数: 1

摘要

自成立以来，心理学学科一直利用经验认识论和数学方法从直接观察中推断心理功能。随着新的挑战和技术机会的出现，科学家们再次面临着定义心理健康和疾病的测量范式的挑战，这些范式可以解决新的问题并利用新的技术机会。在这篇综述中，我们讨论了遥感技术和机器学习模型的理论基础和科学进展，因为它们被应用于量化心理功能，得出临床推论，并绘制新的治疗方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Machine Learning and the Digital Measurement of Psychological Health.

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.

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来源期刊

Annual Review of Clinical Psychology 医学-心理学

CiteScore

31.50

自引率

0.50%

发文量

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.