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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

Participant Evaluation of Blockchain-Enhanced Women’s Health Research Apps: Mixed Methods Experimental Study

Participant Evaluation of Blockchain-Enhanced Women’s Health Research Apps: Mixed Methods Experimental Study

For both prototypes A and B, participants’ level of privacy concern (prototype A: r=–0.61; P=.01 and prototype B: r=–0.59; P=.02) and perceived privacy risk (prototype A: r=–0.61; P=.01 and prototype B: r=–0.52; P=.04) were shown to have a good negative correlation with the behavioral intention to use the app.

Madelena Y Ng, Jodi Halpern, Olivia Shane, Tina Teng, Michael Nguyễn, Casey Ryan Alt, Anaïs Barthe Leite, Sean Moss-Pultz, Courtney R Lyles, Coye Cheshire

JMIR Mhealth Uhealth 2025;13:e65747

Prevalence and Correlates of Clinically Elevated Depressive Symptoms in a Nationwide Sample of Transgender, Nonbinary, and Gender Diverse Young Adults in the United States: Cross-Sectional Survey Study

Prevalence and Correlates of Clinically Elevated Depressive Symptoms in a Nationwide Sample of Transgender, Nonbinary, and Gender Diverse Young Adults in the United States: Cross-Sectional Survey Study

The two items were highly correlated (r=0.81; P Sociodemographic variables included age in years (continuous and categorized: 18‐20, 21‐23, 23‐25), race or ethnicity (ie, BIPOC monoracial, BIPOC multiracial, White), gender identity (ie, transgender men, transgender women, nonbinary), US Census region (ie, Northeast, Midwest, South, West), geographic context (ie, urban, suburban, rural), health insurance status (ie, private, public, both, none), and self-identified religion (eg, Agnostic, Atheist, Baptist, Buddhist

Sari Reisner, Yuxin Liu, Regina Tham, Kaiden Kane, S Wilson Cole, Elizabeth R Boskey, Sabra L Katz-Wise, Alex S Keuroghlian, Rena Xu

Interact J Med Res 2025;14:e66630