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Skip search results from other journals and go to results- 273 Journal of Medical Internet Research
- 227 JMIR Research Protocols
- 100 JMIR Formative Research
- 75 JMIR mHealth and uHealth
- 47 Online Journal of Public Health Informatics
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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)
JMIR Form Res 2025;9:e59481
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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).
JMIR Mhealth Uhealth 2025;13:e66650
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Preventing Urgent Pediatric Readmissions: The Need for and Promise of Real-Time Monitoring
JMIR Pediatr Parent 2025;8:e60802
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They used preprocessing techniques, n-gram tokenization, and polarity scoring to extract sentiments, followed by a probabilistic latent Dirichlet allocation model for review aggregation. They applied various ML models and evaluated the performance of the models in understanding patient perspectives.
Nair et al [30] focused on creating a drug review classification system to label user reviews into multiple classes, such as positive, negative, and neutral, by using publicly available datasets from drugs.com.
JMIR Infodemiology 2025;5:e70525
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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%).
J Med Internet Res 2025;27:e68816
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In this phase, an e-survey (n=300) will be used to collect data on the participants’ demographic (age, racial and ethnic identities, immigration status, educational status, SES, gender identity, housing, neighborhood, employment, relationship status, and household income along with obstetric information including gestational age at birth (full or preterm), admission to neonatal intensive care unit, and infant health issues or concerns.
JMIR Res Protoc 2025;14:e70076
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Among the participants who dropped out, the reasons included loss of contact (n=3) and hospitalization (n=1; see Figure 1). The overall intervention completion rate in the integrative m Health intervention group was nearly 80% (134/170, 78.8%). The average completion rates for individual components were as follows: workshop attendance, 63 out of 68 (93%); self-reported adherence to unsupervised outdoor practice sessions, 36 out of 51 (71%); and self-reported mobile app engagement, 35 out of 51 (69%).
JMIR Mhealth Uhealth 2025;13:e69259
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