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Temporal Dynamics of Subtle Cognitive Change: Validation of a User-Friendly Multidomain Digital Assessment Using an Alcohol Challenge

Temporal Dynamics of Subtle Cognitive Change: Validation of a User-Friendly Multidomain Digital Assessment Using an Alcohol Challenge

(A) “Symbol Swap” DSST analog; (B) “Memory Match” visual associative learning task; (C) “Double-Take” N-back; and (D) “Rapid Response” simple reaction time test. DSST: Digit Symbol Substitution Task. Screenshots of the tablet app, including nontask elements. (A) Post-log-in landing screen; (B) task list view, showing the current/next task to be completed; (C) 1 of 5 instructions screens before Symbol Swap; (D) 1 of 4 instructions screens before Memory Match.

John Frederick Dyer, Florentine Marie Barbey, Ayan Ghoshal, Ann Marie Hake, Bryan J Hansen, Md Nurul Islam, Judith Jaeger, Rouba Kozak, Hugh Marston, Mark Moss, Viet Nguyen, Rebecca Louise Quinn, Leslie A Shinobu, Elizabeth Tunbridge, Brian Murphy, Niamh Kennedy

J Med Internet Res 2025;27:e55469

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Feasibility and Usability of a Web-Based Peer Support Network for Care Partners of People With Serious Illness (ConnectShareCare): Observational Study

Feasibility and Usability of a Web-Based Peer Support Network for Care Partners of People With Serious Illness (ConnectShareCare): Observational Study

We used statistical process control c Charts [18] to identify changes in enrollment and engagement over time. We used descriptive statistics to summarize categorical information from survey responses. We conducted descriptive statistics with SPSS (version 28; IBM Corp). Subgroup analyses were not conducted due to the small sample size. Missing data were excluded on an analysis-by-analysis basis.

Aricca D Van Citters, Megan M Holthoff, Colleen Young, Sarah M Eck, Amelia M Cullinan, Stephanie Carney, Elizabeth A O'Donnell, Joel R King, Malavika Govindan, David Gustafson, Stephanie C Tomlin, Anne B Holmes, Ann D Bradley, Brant J Oliver, Matthew M Wilson, Eugene C Nelson, Amber E Barnato, Kathryn B Kirkland

JMIR Form Res 2025;9:e70206

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mindLAMPVis as a Co-Designed Clinician-Facing Data Visualization Portal to Integrate Clinical Observations From Digital Phenotyping in Schizophrenia: User-Centered Design Process and Pilot Implementation

mindLAMPVis as a Co-Designed Clinician-Facing Data Visualization Portal to Integrate Clinical Observations From Digital Phenotyping in Schizophrenia: User-Centered Design Process and Pilot Implementation

A, B, and C indicate feature-controls, canvas, and feature-parameter-controls, respectively, and the subscripts L and R indicate the left and right panels, respectively. The left and right panels have the same design with clean lines. These charts in the screenshot are generated from the anonymized data of a patient from the Bangalore cohort collected during 2021-2022 in the SHARP project [5]. L: left; R: right; SHARP: Smartphone Health Assessment for Relapse Prevention.

Karthik Sama, Jaya Sreevalsan-Nair, Soumya Choudhary, Srilakshmi Nagendra, Preethi V Reddy, Asher Cohen, Urvakhsh Meherwan Mehta, John Torous

JMIR Form Res 2025;9:e70073

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Idiographic Lapse Prediction With State Space Modeling: Algorithm Development and Validation Study

Idiographic Lapse Prediction With State Space Modeling: Algorithm Development and Validation Study

Note that this approach is inherently personalized, as the parameters a, b, c, d, and noise variance are estimated separately for each participant rather than for the overall population. All participants have the same linear-Gaussian model structure, but the parameters are estimated individually to create a personalized model that best explains their observed behavior.

Eric Pulick, John Curtin, Yonatan Mintz

JMIR Form Res 2025;9:e73265

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