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Annual Review of Clinical Psychology

Volume 19, 2023

Machine Learning and the Digital Measurement of Psychological Health

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.

Keyword(s): digital biomarkers, digital phenotyping, machine learning, psychometrics
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/content/journals/10.1146/annurev-clinpsy-080921-073212
2023-05-09
2024-12-10
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/content/journals/10.1146/annurev-clinpsy-080921-073212
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Machine Learning and the Digital Measurement of Psychological Health
Annual Review of Clinical Psychology 19, 133 (2023); https://doi.org/10.1146/annurev-clinpsy-080921-073212
/content/journals/10.1146/annurev-clinpsy-080921-073212
/content/journals/10.1146/annurev-clinpsy-080921-073212
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