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Uncovering Social States in Healthy and Clinical Populations Using Digital Phenotyping and Hidden Markov Models: Observational Study

Uncovering Social States in Healthy and Clinical Populations Using Digital Phenotyping and Hidden Markov Models: Observational Study

(F) Lower socially active dwell time in AD versus HCs, and an interaction between socially active dwell time and AD when predicting social functioning, were observed. AD: Alzheimer disease; HC: healthy control; SCC: subjective cognitive complaints; SZ: schizophrenia; S1: state 1; S2: state 2; zt: hidden state at time point, t. Where we use “1-hot” encoding for the latent variable, such that ztn=1 if the latent variable at time t belongs to the class n, and 0 otherwise.

Imogen E Leaning, Andrea Costanzo, Raj Jagesar, Lianne M Reus, Pieter Jelle Visser, Martien J H Kas, Christian F Beckmann, Henricus G Ruhé, Andre F Marquand

J Med Internet Res 2025;27:e64007

The Comprehensive Adaptive Multisite Prevention of University Student Suicide Trial: Protocol for a Randomized Controlled Trial

The Comprehensive Adaptive Multisite Prevention of University Student Suicide Trial: Protocol for a Randomized Controlled Trial

The primary goal of aim 1 is to identify the most effective ATS among the 4 embedded strategies (A+B, A+C, D+E, or D+F, as shown in Table 2) that leads to the greatest reduction in STB. This aim focuses on finding the best-performing ATS rather than testing a hypothesis. The sample size of 480 was found to ensure an 80% probability of correctly identifying the ATS with the lowest mean outcome, assuming that such a strategy exists.

Kyla Blalock, Jacqueline Pistorello, Shireen L Rizvi, John R Seeley, Francesca Kassing, James Sinclair, Linda A Oshin, Robert J Gallop, Cassidy M Fry, Ted Snyderman, David A Jobes, Jennifer Crumlish, Hannah R Krall, Susan Stadelman, Filiz Gözenman-Sapin, Kate Davies, David Steele, David B Goldston, Scott N Compton

JMIR Res Protoc 2025;14:e68441

Detecting Sleep/Wake Rhythm Disruption Related to Cognition in Older Adults With and Without Mild Cognitive Impairment Using the myRhythmWatch Platform: Feasibility and Correlation Study

Detecting Sleep/Wake Rhythm Disruption Related to Cognition in Older Adults With and Without Mild Cognitive Impairment Using the myRhythmWatch Platform: Feasibility and Correlation Study

From the extended-cosine models, we extracted measures of 24-hour robustness (pseudo-F statistic, indicating how well the observed data fits the 24-hour curve); activity onset time (up-mesor, the time which the modeled activity level passes the middle modeled rhythm height prior to the peak); and activity offset time (down-mesor or the time which the modeled activity level passes the middle modeled rhythm height prior to the nadir).

Caleb D Jones, Rachel Wasilko, Gehui Zhang, Katie L Stone, Swathi Gujral, Juleen Rodakowski, Stephen F Smagula

JMIR Aging 2025;8:e67294