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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

Identifying Patient-Reported Outcome Measure Documentation in Veterans Health Administration Chiropractic Clinic Notes: Natural Language Processing Analysis

Identifying Patient-Reported Outcome Measure Documentation in Veterans Health Administration Chiropractic Clinic Notes: Natural Language Processing Analysis

For all iterations of NLP model development, evaluation statistics (precision, recall, and F-measure) were calculated based on true positives, false positives, and false negatives for three defined matching tasks: (1) strict-boundary matching, (2) soft-boundary matching, and (3) note categorization. Strict-boundary matching considered only the perfect overlap of the human annotation and NLP target matching methods to be a match in performance metric calculation.

Brian C Coleman, Kelsey L Corcoran, Cynthia A Brandt, Joseph L Goulet, Stephen L Luther, Anthony J Lisi

JMIR Med Inform 2025;13:e66466

An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study

An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study

The demographic features (f) pass directly to the output layer with softmax weightings. GAD-7: Generalized Anxiety Disorder Questionnaire-7; PHQ-9: Patient Health Questionnaire-9. The distribution of the softmax output classes over the N samples , are visualized using Violin plots of the output class probability distribution over the N samples of a single patient prediction. A prediction for a single patient is shown in Figures 2 and 3.

Anthony Kelly, Esben Kjems Jensen, Eoin Martino Grua, Kim Mathiasen, Pepijn Van de Ven

JMIR Med Inform 2025;13:e64617

A Technology System to Help People With Multiple Disabilities Increase Contact With Objects and Control Environmental Stimulation: Single-Case Research Design

A Technology System to Help People With Multiple Disabilities Increase Contact With Objects and Control Environmental Stimulation: Single-Case Research Design

The study complied with the 1964 Helsinki Declaration and its later amendments and was approved by the Ethics Committee of the Lega F. D’Oro, Osimo (AN), Italy (P030820241). Figures 2 reports the data for Liam, Hallie, Logan, and Kali and Figure 3 reports the data for Harper, Jacob, Millie, and Isabel over the different phases of the study. Each data point represents the mean frequency of responses per session over a block (group) of sessions.

Giulio E Lancioni, Gloria Alberti, Chiara Filippini, Nirbhay N Singh, Mark F O'Reilly, Jeff Sigafoos, Valeria Chiariello, Oriana Troccoli

JMIR Rehabil Assist Technol 2025;12:e70378