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A Reminder App to Optimize Bladder Filling During Radiotherapy for Patients With Prostate Cancer (REFILL-PAC): Protocol for a Prospective Trial

Dirk Rades, Jan-Dirk Küter, Michael von Staden, Ahmed Al-Salool, Stefan Janssen, Carmen Timke, Marciana Nona Duma, Tobias Bartscht, Christine Vestergård Madsen, Charlotte Kristiansen, Florian Cremers

JMIR Res Protoc 2025;14:e68179

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Modernizing the Staging of Parkinson Disease Using Digital Health Technology

John Michael Templeton, Christian Poellabauer, Sandra Schneider, Morteza Rahimi, Taofeek Braimoh, Fhaheem Tadamarry, Jason Margolesky, Shanna Burke, Zeina Al Masry

J Med Internet Res 2025;27:e63105

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The Role of AI in Nursing Education and Practice: Umbrella Review

Gonzalez-Garcia et al [45] demonstrated meticulous attention to detail, using dual independent data extraction and rigorous appraisal methods. Similarly, Yasin et al [41] leveraged PRISMA-Sc R (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines to enhance reliability. In contrast, Seibert et al [43] and Rony et al [46] provided limited details on the appraisal of included studies, raising questions about the reliability of their findings.

Rabie Adel El Arab, Omayma Abdulaziz Al Moosa, Fuad H Abuadas, Joel Somerville

J Med Internet Res 2025;27:e69881

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Epidemiological Characteristics of Intestinal Protozoal Infections and Their Risk Factors in Malaysia: Systematic Review and Meta-Analysis Protocol

The following electronic databases of scientific literature that have been peer-reviewed, as recommended by Siddaway et al [17], will be carefully searched without language restrictions and limited to human research only: Pub Med/MEDLINE, Scopus, Pro Quest, Web of Science, Science Direct, Google Scholar, and Cochrane Library databases. A manual search of reference lists of identified papers will be added to the electronic searches.

Nor Shazlina Mizan, Hassanain Al-Talib, Seok Mui Wang

JMIR Res Protoc 2025;14:e66350

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Infoveillance of COVID-19 Infections in Dentistry Using Platform X: Descriptive Study

Alghalia Al-Mansoori, Ola Al Hayk, Sharifa Qassmi, Sarah M Aziz, Fatima Haouari, Tawanda Chivese, Faleh Tamimi, Alaa Daud

J Med Internet Res 2025;27:e54650

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Authors’ Reply: Citation Accuracy Challenges Posed by Large Language Models

Mohamad-Hani Temsah, Ayman Al-Eyadhy, Amr Jamal, Khalid Alhasan, Khalid H Malki

JMIR Med Educ 2025;11:e73698

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Impact of Digital Engagement on Weight Loss Outcomes in Obesity Management Among Individuals Using GLP-1 and Dual GLP-1/GIP Receptor Agonist Therapy: Retrospective Cohort Service Evaluation Study

For example, a meta-analysis by Beleigoli et al [53] found that web-based interventions resulted in modest but significant additional weight loss compared with standard care. Moreover, our findings broaden the current literature on digital weight loss interventions that incorporate pharmacotherapy, building on recent work by Richards et al [29,30] which demonstrated that a remotely delivered, semaglutide-supported weight management program is both effective and efficacious in the short term.

Hans Johnson, David Huang, Vivian Liu, Mahmoud Al Ammouri, Christopher Jacobs, Austen El-Osta

J Med Internet Res 2025;27:e69466

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Applying Critical Discourse Analysis to Cross-Cultural Mental Health Recovery Research

For instance, based on corpus methods, Hunt and Brookes [7] shed light on discussions surrounding anorexia, depression, and diabulimia, while Jones et al [8] appraise the experiences of individuals with psychosis and bipolar disorder. Corpus-informed CDA is actively used to identify patterns of language use in large text-data collections, which deepens understanding of how language shapes our perceptions of mental health and illness.

Yasuhiro Kotera, Riddhi Daryanani, Oliver Skipper, Jonathan Simpson, Simran Takhi, Merly McPhilbin, Benjamin-Rose Ingall, Mariam Namasaba, Jessica Jepps, Vanessa Kellermann, Divya Bhandari, Yasutaka Ojio, Amy Ronaldson, Estefania Guerrero, Tesnime Jebara, Claire Henderson, Mike Slade, Sara Vilar-Lluch

JMIR Form Res 2025;9:e64087

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Perceptions and Earliest Experiences of Medical Students and Faculty With ChatGPT in Medical Education: Qualitative Study

Banerjee et al [11] reported that postgraduate trainee doctors have an overall positive perception of the impact of AI on clinical training; however, they found that AI will eventually reduce the trainees’ clinical judgment and practical skills. In line with that, the faculty participants were concerned about students’ self-reliance on AI applications on the cost of traditional teaching methods, which might deprive them from skills best learned in person or group teaching.

Noura Abouammoh, Khalid Alhasan, Fadi Aljamaan, Rupesh Raina, Khalid H Malki, Ibraheem Altamimi, Ruaim Muaygil, Hayfaa Wahabi, Amr Jamal, Ali Alhaboob, Rasha Assad Assiri, Jaffar A Al-Tawfiq, Ayman Al-Eyadhy, Mona Soliman, Mohamad-Hani Temsah