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Improving Early Dementia Detection Among Diverse Older Adults With Cognitive Concerns With the 5-Cog Paradigm: Protocol for a Hybrid Effectiveness-Implementation Clinical Trial

Improving Early Dementia Detection Among Diverse Older Adults With Cognitive Concerns With the 5-Cog Paradigm: Protocol for a Hybrid Effectiveness-Implementation Clinical Trial

The PMIS (Pearson r=−0.76; P As we examined the sensitivity and specificity data to choose cut scores, we chose to favor sensitivity to minimize missing individuals with true disease in this sample of patients considered high risk because of their cognitive concerns. The cut scores for a positive result on the 5-Cog components were as follows: PMIS ≤6 (range 0-8), Symbol Match ≤25 (range 0-65), and s MCR >5 (range 0-7).

Rachel Beth Rosansky Chalmer, Emmeline Ayers, Erica F Weiss, Nicole R Fowler, Andrew Telzak, Diana Summanwar, Jessica Zwerling, Cuiling Wang, Huiping Xu, Richard J Holden, Kevin Fiori, Dustin D French, Celeste Nsubayi, Asif Ansari, Paul Dexter, Anna Higbie, Pratibha Yadav, James M Walker, Harrshavasan Congivaram, Dristi Adhikari, Mairim Melecio-Vazquez, Malaz Boustani, Joe Verghese

JMIR Res Protoc 2025;14:e60471

Extended Reality–Enhanced Mental Health Consultation Training: Quantitative Evaluation Study

Extended Reality–Enhanced Mental Health Consultation Training: Quantitative Evaluation Study

All data analyses were performed in R (version 4.2.2) using RStudio (version 2022.12.0.353; Posit). All experts, across both VR and AR systems (n=9, 100%), felt actively involved and in charge of the situation. The simulation software responded adequately and did not lag according to 8 of the experts, while all 9 experts reported that it was easy to learn how to interact with the software. Notably, all were interested in the progress of events throughout the simulation, suggesting high engagement.

Katherine Hiley, Zanib Bi-Mohammad, Luke Taylor, Rebecca Burgess-Dawson, Dominic Patterson, Devon Puttick-Whiteman, Christopher Gay, Janette Hiscoe, Chris Munsch, Sally Richardson, Mark Knowles-Lee, Celia Beecham, Neil Ralph, Arunangsu Chatterjee, Ryan Mathew, Faisal Mushtaq

JMIR Med Educ 2025;11:e64619

Mental Health Professionals’ Technology Usage and Attitudes Toward Digital Health for Psychosis: Comparative Cross-Sectional Survey Study

Mental Health Professionals’ Technology Usage and Attitudes Toward Digital Health for Psychosis: Comparative Cross-Sectional Survey Study

Descriptive statistics, including frequencies and percentages, and data visualization, were performed using R program (R Foundation for Statistical Computing) [36] to analyze quantitative data. The proportion of missing rates for each question were summarized and reported in the results. Free-text answers were summarized narratively using Nvivo (version 12, Lumivero) [37].

Xiaolong Zhang, Natalie Berry, Daniela Di Basilio, Cara Richardson, Emily Eisner, Sandra Bucci

JMIR Ment Health 2025;12:e68362

Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study

Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study

The application of this mapping to the data was performed using R version 4.3.2 (R Foundation for Statistical Computing). The full list of diagnosis names corresponding to ADRD diagnosis categories is provided in Multimedia Appendix 1. To assess associations between clusters and sex, as well as ADRD diagnoses, we used the chi-square test.

Matthew West, You Cheng, Yingnan He, Yu Leng, Colin Magdamo, Bradley T Hyman, John R Dickson, Alberto Serrano-Pozo, Deborah Blacker, Sudeshna Das

JMIR Aging 2025;8:e65178

Evaluating a Digital Health Tool Designed to Improve Low Sexual Desire in Women: Mixed-Methods Implementation Science Study

Evaluating a Digital Health Tool Designed to Improve Low Sexual Desire in Women: Mixed-Methods Implementation Science Study

Data presented are means and SDs based on 8 participants who provided full data. a SIDI: Sexual Interest and Desire Inventory. b FSDS-R: Female Sexual Distress Scale-Revised. c SWLS: Satisfaction With Life Scale. d SWSL: Satisfaction With Sex Life Scale. Participants’ satisfaction with e Sense was evaluated in various ways. We measured satisfaction with the experience of having versus not having a treatment navigator.

Lori A Brotto, Kyle R Stephenson, Nisha Marshall, Mariia Balvan, Yaroslava Okara, Elizabeth A Mahar

J Med Internet Res 2025;27:e69828