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Expression of Concern: Evaluating the Clinical Efficacy of an Exergame-Based Training Program for Enhancing Physical and Cognitive Functions in Older Adults With Mild Cognitive Impairment and Dementia Residing in Rural Long-Term Care Facilities: Randomized Controlled Trial

Expression of Concern: Evaluating the Clinical Efficacy of an Exergame-Based Training Program for Enhancing Physical and Cognitive Functions in Older Adults With Mild Cognitive Impairment and Dementia Residing in Rural Long-Term Care Facilities: Randomized Controlled Trial

The publisher expresses concern regarding the following article: Evaluating the Clinical Efficacy of an Exergame-Based Training Program for Enhancing Physical and Cognitive Functions in Older Adults With Mild Cognitive Impairment and Dementia Residing in Rural Long-Term Care Facilities: Randomized Controlled Trial [1]. This article is under investigation for potential peer review irregularities. Readers are advised to interpret the findings with caution pending the outcome of this inquiry.

JMIR Editorial Office

J Med Internet Res 2025;27:e75355

Large Language Models for Thematic Summarization in Qualitative Health Care Research: Comparative Analysis of Model and Human Performance

Large Language Models for Thematic Summarization in Qualitative Health Care Research: Comparative Analysis of Model and Human Performance

Qualitative studies in health care shed light on the perceptions, narratives, and discourses that underlie human behavior. This approach enhances understanding of both clinicians and patients’ experiences and expectations, thereby informing decision-making for health policy [1]. Traditionally, these studies involved data collection through face-to-face interviews, observation or artifact analysis, transcription, and manual human coding for sense-making.

Arturo Castellanos, Haoqiang Jiang, Paulo Gomes, Debra Vander Meer, Alfred Castillo

JMIR AI 2025;4:e64447

Health Care Professionals' Engagement With Digital Mental Health Interventions in the United Kingdom and China: Mixed Methods Study on Engagement Factors and Design Implications

Health Care Professionals' Engagement With Digital Mental Health Interventions in the United Kingdom and China: Mixed Methods Study on Engagement Factors and Design Implications

Both hospitals are publicly funded, and are among the largest ones in the local regions, providing comprehensive medical care to a high volume of patients, making them representative of large urban health care institutions in their respective countries. Although health care systems in China and the United Kingdom operate differently, some systematic challenges across the 2 hospitals are similar, such as staff shortages, increasing workload, and high burnout levels [27-30].

Zheyuan Zhang, Sijin Sun, Laura Moradbakhti, Andrew Hall, Celine Mougenot, Juan Chen, Rafael A Calvo

JMIR Ment Health 2025;12:e67190

Patient and Clinician Perspectives on Alert-Based Remote Monitoring–First Care for Cardiovascular Implantable Electronic Devices: Semistructured Interview Study Within the Veterans Health Administration

Patient and Clinician Perspectives on Alert-Based Remote Monitoring–First Care for Cardiovascular Implantable Electronic Devices: Semistructured Interview Study Within the Veterans Health Administration

Patients were informed that similar data were obtained through RM as in-person visits; they may need in-person visits for abnormalities identified on remote transmissions; they could still contact their device clinic; and their other visits, such as with primary care, would continue. Patients were asked about the travel burden to VHA, how their care may have changed during the COVID-19 pandemic, and any concerns about reducing routine in-person CIED clinic visits.

Allison Kratka, Thomas L Rotering, Scott Munson, Merritt H Raitt, Mary A Whooley, Sanket S Dhruva

JMIR Cardio 2025;9:e66215

Mobile Apps and Wearable Devices for Cardiovascular Health: Narrative Review

Mobile Apps and Wearable Devices for Cardiovascular Health: Narrative Review

This has contributed to a lack of awareness regarding women’s cardiovascular risks, resulting in delayed diagnoses and suboptimal care [5].

Gauri Kumari Chauhan, Patrick Vavken, Christine Jacob

JMIR Mhealth Uhealth 2025;13:e65782

Using a Hybrid of AI and Template-Based Method in Automatic Item Generation to Create Multiple-Choice Questions in Medical Education: Hybrid AIG

Using a Hybrid of AI and Template-Based Method in Automatic Item Generation to Create Multiple-Choice Questions in Medical Education: Hybrid AIG

While addressing a critical issue in item development for a non–health care setting, its direct application to medical education is challenging due to the inherent complexities of health professions education. Furthermore, this approach integrates AI only into generating unique sentences based on rules imposed by experts, leaving the essential cognitive work dependent on expert input, which remains inefficient for medical education.

Yavuz Selim Kıyak, Andrzej A Kononowicz

JMIR Form Res 2025;9:e65726

Multilevel Factors and Indicators of Atypical Neurodevelopment During Early Infancy in Japan: Prospective, Longitudinal, Observational Study

Multilevel Factors and Indicators of Atypical Neurodevelopment During Early Infancy in Japan: Prospective, Longitudinal, Observational Study

The M-CHAT—a parent-completed dichotomous questionnaire designed for children aged 16‐30 months—is an effective primary screening tool for ASD and other developmental concerns in the general population [3,5]. In our study, we aimed to identify children showing potential developmental concerns at an earlier stage, specifically at 12 months of age.

Daigo Kato, Akiko Okuno, Tetsuo Ishikawa, Shoji Itakura, Shinji Oguchi, Yoshiyuki Kasahara, Kenji Kanenishi, Yuzo Kitadai, Yoshitaka Kimura, Naoki Shimojo, Kazushige Nakahara, Akiko Hanai, Hiromichi Hamada, Haruta Mogami, Seiichi Morokuma, Kazuhiro Sakurada, Yukuo Konishi, Eiryo Kawakami

JMIR Pediatr Parent 2025;8:e58337

Effect of Home-Based Virtual Reality Training on Upper Extremity Recovery in Patients With Stroke: Systematic Review

Effect of Home-Based Virtual Reality Training on Upper Extremity Recovery in Patients With Stroke: Systematic Review

In home-based settings, routine care often lacks sufficient intensity and task-specific training, which are critical for motor learning and functional recovery [3]. Similarly, traditional therapies at home may suffer from limited professional supervision, reduced patient motivation, and lower adherence rates compared to hospital-based programs [5,6].

Jiaqi Huang, Yixi Wei, Ping Zhou, Xiaokuo He, Hai Li, Xijun Wei

J Med Internet Res 2025;27:e69003

Modernizing the Staging of Parkinson Disease Using Digital Health Technology

Modernizing the Staging of Parkinson Disease Using Digital Health Technology

Furthermore, with the increased opportunity for users’ participation on their own devices and the ability of the clinician to collect and analyze enhanced objective datasets, the continued development and integration of mobile health technologies into the routine assessment and care of patients with PD can allow for more sophisticated characterization of patients’ function, better tailoring of symptomatic therapy, greater patient engagement and self-assessment, and overall improved health care outcomes [40].

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

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

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

Artificial intelligence (AI) has rapidly emerged as a transformative force in health care, offering unprecedented opportunities to enhance patient care, optimize clinical workflows, and address pressing challenges, such as workforce shortages and escalating costs [1-3]. In nursing, AI applications span a broad spectrum—from predictive analytics and clinical decision support systems to web-based assistants and robotic caregivers—poised to revolutionize how nurses deliver care and interact with patients [4].

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

J Med Internet Res 2025;27:e69881