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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

Exploring the Relationship Between Cyberchondria and Suicidal Ideation: Cross-Sectional Mediation Analysis

Exploring the Relationship Between Cyberchondria and Suicidal Ideation: Cross-Sectional Mediation Analysis

Pearson correlation coefficients (r) were used to determine associations between variables, with r≥0.3 and r≥0.5 indicating moderate and large effects, respectively [26]. We used a backward elimination approach with the linear regression model to examine the direct association between cyberchondria and suicidal ideation, and standardized coefficients (β) and 95% CIs were calculated. The hypothesized model was assessed using SEM analysis with the maximum likelihood estimation method.

Richard Huan Xu, Xiao Liang, Vladan Starcevic

J Med Internet Res 2025;27:e72414

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

The Monthly Cycling of Food Insecurity in Latinas at Risk for Diabetes: Methods, Retention, and Sample Characteristics for a Microlongitudinal Design

The Monthly Cycling of Food Insecurity in Latinas at Risk for Diabetes: Methods, Retention, and Sample Characteristics for a Microlongitudinal Design

Results of Spearman’s correlations show that higher number of assessments completed was associated with having internet in the home (r=0.27, p=.01) and there was a statistical trend for having a tablet in the home (r=-0.20, p=.07). CONSORT diagram for the food insecurity cycling microlongitudinal study Hartford, Connecticut, enrollment 2021‐2023. Demographic characteristics (n=87). The main findings reported here are that the study successfully recruited and retained a sample of the target population.

Angela Bermúdez-Millán, Rafael Pérez-Escamilla, Sofia Segura-Pérez, James Grady, Richard S Feinn VI, Hanako Agresta, Dean Kim, Julie Ann Wagner

JMIR Form Res 2025;9:e66970