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ABSTRACT: Background
Personal sensing may improve digital therapeutics for mental health care by facilitating early screening, symptom monitoring, risk prediction, and personalized adaptive interventions. However, further development and the use of personal sensing requires a better understanding of its acceptability to people targeted for these applications.Objective
We aimed to assess the acceptability of active and passive personal sensing methods in a sample of people with moderate to severe alcohol use disorder using both behavioral and self-report measures. This sample was recruited as part of a larger grant-funded project to develop a machine learning algorithm to predict lapses.Methods
Participants (N=154; n=77, 50% female; mean age 41, SD 11.9 years; n=134, 87% White
SUBMITTER: Wyant K
PROVIDER: S-EPMC10495858 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature