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Improving Suicidal Ideation Detection in Social Media Posts: Topic Modeling and Synthetic Data Augmentation Approach

Improving Suicidal Ideation Detection in Social Media Posts: Topic Modeling and Synthetic Data Augmentation Approach

Our protocol was developed using the scoping review methodological framework proposed by Arksey and O’Malley [39] and further refined by Peters et al [40]. The central research question guiding this review was as follows: “What are the most frequently reported risk factors associated with suicidal ideation in the psychology and mental health literature?”

Hamideh Ghanadian, Isar Nejadgholi, Hussein Al Osman

JMIR Form Res 2025;9:e63272

Improving Patient Communication by Simplifying AI-Generated Dental Radiology Reports With ChatGPT: Comparative Study

Improving Patient Communication by Simplifying AI-Generated Dental Radiology Reports With ChatGPT: Comparative Study

In a recent meta-analysis by Armache et al [31], the readability of 1124 education materials for patients with head and neck cancer was evaluated that was produced by professional societies, hospitals, and other organizations intended to inform patients, promote their engagement, and enhance their adherence to treatment plans. The mean Flesch-Kincaid grade level of these materials ranged from 8.8 to 14.8, with none of them meeting the recommended sixth-grade readability standard.

Daniel Stephan, Annika S Bertsch, Sophia Schumacher, Behrus Puladi, Matthias Burwinkel, Bilal Al-Nawas, Peer W Kämmerer, Daniel GE Thiem

J Med Internet Res 2025;27:e73337

Empowering Patients and Caregivers to Use Artificial Intelligence and Computer Vision for Wound Monitoring: Nonrandomized, Single-Arm Feasibility Study

Empowering Patients and Caregivers to Use Artificial Intelligence and Computer Vision for Wound Monitoring: Nonrandomized, Single-Arm Feasibility Study

For instance, Labovitz et al [19] demonstrated that, among patients with recently diagnosed ischemic strokes receiving anticoagulants, real-time monitoring via a smartphone-based AI app led to significantly improved medication adherence. This intervention resulted in a 50% increase in adherence rates compared to the standard care control group, as measured by plasma drug concentration levels.

Rose Raizman, José Luis Ramírez-GarciaLuna, Tanmoy Newaz, Sheila C Wang, Gregory K Berry, Ling Yuan Kong, Heba Tallah Mohammed, Robert D J Fraser

J Particip Med 2025;17:e69470

Strategies and Tools for Electronic Health Records and Physician Workflow Alignment: Protocol for a Scoping Review

Strategies and Tools for Electronic Health Records and Physician Workflow Alignment: Protocol for a Scoping Review

Previous studies, such as those by Avendano et al [30] have explored specific EHR-physician alignment strategies, albeit in a limited scope by focusing on only 3 randomly selected strategies. Our scoping review aims to expand on this work by comprehensively identifying all strategies and tools used by organizations to facilitate the alignment of EHR systems with physician workflows.

Oluwakemi Olufunmilayo Oluwole, Nicole Haggerty, Uche Ikenyei, Oluwabambi Tinuoye, Andreawan Honora, Mohammed Abass Issakah

JMIR Res Protoc 2025;14:e60464

An Informatics-Based, Payer-Led, Low-Intensity Multichannel Educational Campaign Designed to Decrease Postdischarge Utilization for Medicare Advantage Members: Retrospective Evaluation

An Informatics-Based, Payer-Led, Low-Intensity Multichannel Educational Campaign Designed to Decrease Postdischarge Utilization for Medicare Advantage Members: Retrospective Evaluation

Bressman et al [20] found that an automated, bi-directional, text-based follow-up intervention from their primary care physician following an index admission translated to 41% lower (adjusted odds ratio) 30-day acute inpatient readmissions or ED visits among 374 patients recently hospitalized (compared with a control, no messaging cohort).

Danica Fernandes, Elise Kokonas, Jai Bansal, Ken Hayashima, Brian Hurley, Annabel Ryu, Snehal Mhatre, Mohammed Ghori, Kelly Jean Craig, Amanda L Zaleski, Lily Vogel, Alena Baquet-Simpson, Daniel Reif

JMIR Hum Factors 2025;12:e63841

Perceptions of Executive Decision Makers on Using Social Media in Effective Health Communication: Qualitative Study

Perceptions of Executive Decision Makers on Using Social Media in Effective Health Communication: Qualitative Study

The participants included senior executives and their deputies from government and private health institutions of the Al-Qassim region of Saudi Arabia. In-depth interviews are purposeful conversations designed to elicit relevant information from the participants, incorporating a semistructured question format. Face-to-face semistructured interviews were conducted between September and December 2023, each lasting up to 30 minutes.

Norah Abdullah Alanazi, Alia Mohammed Almoajel, Shabana Tharkar, Khalid Almutairi, Farha Nazir Ahmad Mohamad, Bader Saud Talak Almatairi

J Med Internet Res 2025;27:e69269

Assessing ChatGPT’s Capability as a New Age Standardized Patient: Qualitative Study

Assessing ChatGPT’s Capability as a New Age Standardized Patient: Qualitative Study

Liu et. al [15] crafted 10 medical histories with Chat GPT, which were then vetted by experienced physicians. Their results highlighted Chat GPT’s promise in clinical education, although some responses came across as robotic [15]. Suarez et.al [16] gathered dental student’s feedback after interacting with an AI chatbot. The majority found the experience valuable, especially those who made a correct diagnosis. This underscores the potential of integrating AI into health sciences training [16].

Joseph Cross, Tarron Kayalackakom, Raymond E Robinson, Andrea Vaughans, Roopa Sebastian, Ricardo Hood, Courtney Lewis, Sumanth Devaraju, Prasanna Honnavar, Sheetal Naik, Jillwin Joseph, Nikhilesh Anand, Abdalla Mohammed, Asjah Johnson, Eliran Cohen, Teniola Adeniji, Aisling Nnenna Nnaji, Julia Elizabeth George

JMIR Med Educ 2025;11:e63353

Using WhatsApp for Nutrition Surveillance Among Children Under 5 Years in West Java, Indonesia: Cross-Sectional Survey and Feasibility Study

Using WhatsApp for Nutrition Surveillance Among Children Under 5 Years in West Java, Indonesia: Cross-Sectional Survey and Feasibility Study

In April and May, fewer results were entered due to Ramadan and Eid al-Fitr affecting how well cadres could input data. Toward the study’s end, a reminder was sent to cadres by DTO-Pusdatin Ministry of Health and village leaders about data entry. The comparison of total CU5 being measured and those reported through Whats App, and the linearity trend of total Whats App data reporting month by month. CU5: children under 5 years.

Dewi Nur Aisyah, Chyntia Aryanti Mayadewi, Astri Utami, Fauziah Mauly Rahman, Nathasya Humaira Adriani, Erlangga Al Farozi, Meldi Hafizh Sayoko, Aulia Chairunisa, Liza Restiana, Logan Manikam, Zisis Kozlakidis

JMIR Pediatr Parent 2025;8:e58752