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Research Dissemination Strategies in Pediatric Emergency Care Using a Professional Twitter (X) Account: A Mixed Methods Developmental Study of a Logic Model Framework

Research Dissemination Strategies in Pediatric Emergency Care Using a Professional Twitter (X) Account: A Mixed Methods Developmental Study of a Logic Model Framework

Navigating nodes with equity or balance (AR) Getting the word out within PECARN equitably (BF) Presentations to the PECARN Steering Committee including updates to increase awareness (BG) Encouraging researcher engagement (AT, V1) Becoming aware of new publications (AS) Anticipating events or bursts of demand (AE) Establishing credibility on Twitter (AP) Assumptions Peer review of tweets for credibility or trustworthiness (H) No gold standard for analytics makes measuring impact or effectiveness difficult (N)

Gwendolyn C Hooley, Julia N Magana, Jason M Woods, Shyam Sivasankar, Lauren VonHoltz, Anita R Schmidt, Todd P Chang, Michelle Lin

JMIR Form Res 2025;9:e59481

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Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach

Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach

Baseline characteristics of participants by social interaction frequency (N=99). a SCD: subjective cognitive decline. b MCI: mild cognitive impairment. c Some missing data. d K-MMSE-2: Korean Mini-Mental State Examination, second edition. e SCD-Q: Subjective Cognitive Decline Questionnaire. f K-IADL: Korean Instrumental Activities of Daily Living. g FPQ: Frailty Phenotype Questionnaire. h SGDS-K: Korean version of the Short Form-Geriatric Depression Scale. i K-GAI: Korean version of the Geriatric Anxiety Inventory. j MBI-C

Bada Kang, Min Kyung Park, Jennifer Ivy Kim, Seolah Yoon, Seok-Jae Heo, Chaeeun Kang, SungHee Lee, Yeonkyu Choi, Dahye Hong

J Med Internet Res 2025;27:e69379

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Integrating Mobile Health App Data Into Electronic Medical or Health Record Systems and Its Impact on Health Care Delivery and Patient Health Outcomes: Scoping Review

Integrating Mobile Health App Data Into Electronic Medical or Health Record Systems and Its Impact on Health Care Delivery and Patient Health Outcomes: Scoping Review

The main features of the apps and EMR/EHR systems can be categorized as tracking or recording health data (n=19), app data integrated into EMR/EHR systems (n=19), app data being summarized or presented on EMR/EHR interface (n=19), communicating with the health care team (n=12), providing reminders or alerts (n=10), synchronizing with other apps or devices such as “wearables” (n=8), offering educational resources (n=4), and using existing portal credentials to app access (n=2) (Multimedia Appendix 3).

Jialing Lin, Shona Marie Bates, Luke N Allen, Michael Wright, Limin Mao, Michael Kidd

JMIR Mhealth Uhealth 2025;13:e66650

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Sleep, Health Care–Seeking Behaviors, and Perceptions Associated With the Use of Sleep Wearables in Canada: Results From a Nationally Representative Survey

Sleep, Health Care–Seeking Behaviors, and Perceptions Associated With the Use of Sleep Wearables in Canada: Results From a Nationally Representative Survey

Respondents in this study endorsed monitoring their physical activity, nutrition, and sleep patterns as the main reasons for engaging in self-tracking, and over 65% reported that this had allowed them to be better informed of their general health (n=387/580, 66.6%) and to maintain or improve their health condition (n=398/580, 68.5%).

Karianne Dion, Meggan Porteous, Tetyana Kendzerska, Ashley Nixon, Elliott Lee, Massimiliano de Zambotti, Sheila N Garland, Mandeep Singh, Gino De Luca, Samuel Gillman, Andrée-Ann Baril, Dave Gallson, Rebecca Robillard, Canadian Sleep Research Consortium

J Med Internet Res 2025;27:e68816

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Evaluating a Mobile Digital Therapeutic for Vasomotor and Behavioral Health Symptoms Among Women in Midlife: Randomized Controlled Trial

Evaluating a Mobile Digital Therapeutic for Vasomotor and Behavioral Health Symptoms Among Women in Midlife: Randomized Controlled Trial

In total, 149 participants were randomly assigned to either the active DCP (n=112) or the control group (n=37). Figure 2 shows the consort diagram with details of the group allocation and follow-up. Study flowchart according to CONSORT. CONSORT: Consolidated Standards of Reporting Trials; GAD-7: Generalized Anxiety Disorder-7; PHQ-8: Patient Health Questionnaire Depression Scale-8; PSQI: Pittsburgh Sleep Quality Index; RCT: randomized controlled trial.

Jennifer Duffecy, Arfa Rehman, Scott Gorman, Yong Lin Huang, Heide Klumpp

JMIR Mhealth Uhealth 2025;13:e58204

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