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Each observation was represented by the triplet {X,T,S}, where X⊆Rd is a d-dimensional feature vector, T∈(0,Emax] is an observed event or censoring time over a finite time horizon, and S∈{0,1} indicates whether T is a right-censoring time (S=0) or an event time (S=1). The observed time T is the minimum of the event time E and the right-censoring time C, that is, T=min(E, C).
JMIR AI 2025;4:e62985
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In terms of the aim for the preliminary efficacy evaluation (ie, secondary outcomes of psychosocial and behavioral factors associated with NMUPO), we estimate an effect size according to a previous review on digital interventions for illicit drug use [111] and found small-to-medium effect sizes (Cohen d=–0.17 to –0.34) with a 6-month follow-up assessment. G-power analysis [112] estimated a sample size of 10 to 35 per arm for an RCT (repeated measures analysis of covariance).
JMIR Res Protoc 2025;14:e65847
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Panel (C) shows a behavioral activation task, and panel (D) showcases the points awarded for completing this task.
Senyo Health chat feature being displayed from the perspective of the recovery coach. The left is conversations with multiple patients. Once selected, the full conversation appears in the center of the screen, with the recovery coach able to text back and forth. Surveys, modules, and activation tasks can also be assigned to the participant through the chat.
JMIR Res Protoc 2025;14:e65693
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For example, Megan Doerr argues that building or establishing a “social license” for collecting and using data can be more appropriate and protective than deidentification [47]. A social license represents the informal permission of a community to engage in a specific activity [48,49]. In public health contexts, a social license can legitimize the collection, use, or sharing of data about relevant communities.
J Med Internet Res 2025;27:e70983
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