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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

Evaluation of an Online-Based Self-Help Program for Patients With Panic Disorder: Randomized Controlled Trial

Evaluation of an Online-Based Self-Help Program for Patients With Panic Disorder: Randomized Controlled Trial

The number of cases was calculated using the R-tool (Michael C. Donohue) longpower [48]. For the secondary outcomes, we calculated a minimal detectable effect size of Cohen d=–0.46 with 80% power and an α level of .0125 (Bonferroni-Holm adjustment) based on a post hoc power analysis of the WSAS with simr (Peter Green) [49]. Randomization in 1:1 ratio without stratification or blocks was done automatically by a computer-generated code. Participants were automatically informed of their group via email.

Christopher Lalk, Teresa Väth, Sofie Hanraths, Luise Pruessner, Christina Timm, Steffen Hartmann, Sven Barnow, Julian Rubel

J Med Internet Res 2025;27:e54062

Impact of Digital Engagement on Weight Loss Outcomes in Obesity Management Among Individuals Using GLP-1 and Dual GLP-1/GIP Receptor Agonist Therapy: Retrospective Cohort Service Evaluation Study

Impact of Digital Engagement on Weight Loss Outcomes in Obesity Management Among Individuals Using GLP-1 and Dual GLP-1/GIP Receptor Agonist Therapy: Retrospective Cohort Service Evaluation Study

All statistical analyses were performed using R (version 4.3.1; R Foundation for Statistical Computing) and its statistical packages. A significance level of P A sample size calculation was performed to estimate the number of participants required to detect a significant difference in weight loss between engaged and nonengaged groups.

Hans Johnson, David Huang, Vivian Liu, Mahmoud Al Ammouri, Christopher Jacobs, Austen El-Osta

J Med Internet Res 2025;27:e69466

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

Stress and Hypertension Among African American Female Family Caregivers of Persons Living With Alzheimer Disease and Related Dementias: Protocol for a Pilot Internet-Based Randomized Controlled Trial

Stress and Hypertension Among African American Female Family Caregivers of Persons Living With Alzheimer Disease and Related Dementias: Protocol for a Pilot Internet-Based Randomized Controlled Trial

Further, the scale correlates well with the Krieger Experiences of Discrimination (r=0.51), a measure of societal discrimination. Hair cortisol will be used as a proxy for chronic stress. To collect the hair samples, approximately 25-75 mg of hair (approximate width of shoelace tip when bunched) will be cut from the posterior vertex region of the scalp as close to the scalp as possible. The posterior vertex has the lowest variation in cortisol levels, making it the preferred area for sampling.

Kathy D Wright, Ingrid K Richards Adams, Nathan P Helsabeck, Karen M Rose, Karen O Moss, Donya Nemati, Navia Palmer, Bohyun Kim, Sunita Pokhrel Bhattarai, Christopher Nguyen, Daniel Addison, Maryanna D Klatt

JMIR Res Protoc 2025;14:e66975