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To Implement or Not to Implement? A Commentary on the Pitfalls of Judging the Value and Risks of Personalized Prognostic Statistical Models

To Implement or Not to Implement? A Commentary on the Pitfalls of Judging the Value and Risks of Personalized Prognostic Statistical Models

The digital transformation of health care necessitates harvesting insights from massive datasets by exploiting the potential of modern artificial intelligence and machine learning solutions and allowing, among others, the prediction of health outcomes for one specific treatment based on specific patient characteristics. Their medical application has attracted increasing attention and focus on the predictive power of the emerging complex statistical models in medicine [1].

Linda Baumbach, Walter Hötzendorfer, Jan Baumbach

J Med Internet Res 2025;27:e69341


Trends and Shifts in Swedish Telemedicine Consultations During the Pre–COVID-19, COVID-19, and Post–COVID-19 Periods: Retrospective Observational Study

Trends and Shifts in Swedish Telemedicine Consultations During the Pre–COVID-19, COVID-19, and Post–COVID-19 Periods: Retrospective Observational Study

With people older than 65 years expected to comprise 20% of the population of Sweden by 2050, there is a looming lack of health care resources [13]. Sweden therefore needs to deploy telemedicine solutions quickly to meet the needs of an aging population. Telemedicine for remote monitoring and chronic disease treatment is well placed to become a key approach to dealing with this demographic shift.

Adaora Uloma Asomugha, Annamaria Pakai

JMIR Form Res 2025;9:e60294


From E-Patients to AI Patients: The Tidal Wave Empowering Patients, Redefining Clinical Relationships, and Transforming Care

From E-Patients to AI Patients: The Tidal Wave Empowering Patients, Redefining Clinical Relationships, and Transforming Care

While people may not realize the ubiquity of AI, millions interact with AI daily using assistants such as Siri or Alexa and streaming platforms such as Netflix and Spotify [4]. Launched in November 2022, Chat GPT reached 100 million users in 2 months and hundreds of millions of users by March 2024 [5]. This scorching adoption has been faster than for personal computers and the internet. In 2024, a total of 39.4% of US adults aged 18-64 years reported using generative AI, and 32% used it weekly.

Susan S Woods, Sarah M Greene, Laura Adams, Grace Cordovano, Matthew F Hudson

J Particip Med 2025;17:e75794


Exploring Ethics: Understanding the Role of Privacy Policies and Institutional Review Boards in Digital Health Companies

Exploring Ethics: Understanding the Role of Privacy Policies and Institutional Review Boards in Digital Health Companies

As private sector investment in research accelerates, concerns are emerging about whether existing ethical oversight mechanisms are evolving sufficiently to address the complexities of commercial research. A recent paper described how studies involving sensitive data, when conducted without formal ethical review, can lead to public misinformation, erode trust in science, and undermine institutional credibility [4].

Jacqlyn L Yourell, Kelsey L McAlister, Clare C Beatty, Jennifer L Huberty

J Med Internet Res 2025;27:e70711


Leveraging Technology to Engage Supplemental Nutrition Assistance Program Consumers With Children at Farmers Markets: Qualitative Community-Engaged Approach to App Development

Leveraging Technology to Engage Supplemental Nutrition Assistance Program Consumers With Children at Farmers Markets: Qualitative Community-Engaged Approach to App Development

Despite the benefits of nutrition incentives at farmers markets, lack of awareness about these opportunities limits their use. A recent study in Ohio found only 45% of SNAP consumers with access to nutrition incentive programming within 5 miles of their home were using the program; most of the nonusers (>80%) were unaware that the incentive program existed [20]. Yet, 77% of the nonusers said that they were likely to use the program in the next 6 months after learning about the program [20].

Callie Ogland-Hand, Jillian Schulte, Owusua Yamoah, Kathryn Poppe, Timothy H Ciesielski, Regan Gee, Ana Claudia Zubieta, Darcy A Freedman

JMIR Form Res 2025;9:e70104


Benchmarking the Confidence of Large Language Models in Answering Clinical Questions: Cross-Sectional Evaluation Study

Benchmarking the Confidence of Large Language Models in Answering Clinical Questions: Cross-Sectional Evaluation Study

A wide array of LLMs is now accessible, including open-source models, offering solutions that cater to both the public and medical professionals [1,4]. The efficacy of these models has been demonstrated in a variety of tasks, albeit with some limitations [5,6]. For instance, LLMs, such as GPT, have shown promise in providing diagnostic assistance and answering medical queries [5,7-9].

Mahmud Omar, Reem Agbareia, Benjamin S Glicksberg, Girish N Nadkarni, Eyal Klang

JMIR Med Inform 2025;13:e66917


Use of Virtual Reality in the Pediatric Perioperative Setting and for Induction of Anesthesia: Mixed Methods Pilot Feasibility Study

Use of Virtual Reality in the Pediatric Perioperative Setting and for Induction of Anesthesia: Mixed Methods Pilot Feasibility Study

Up to 60% of children experience high levels of anxiety at induction of general anesthesia (GA) [2,3]. This distress is associated with a greater risk of postoperative emergence delirium [4,5], disturbed sleep, and behavioral and emotional disturbances [6]. Previous studies and a meta-analysis have demonstrated the efficacy of preoperative operating room (OR) tours by VR in reducing anxiety [7-18].

Yu Tong Huang, Sofia Addab, Gianluca Bertolizio, Reggie Hamdy, Kelly Thorstad, Argerie Tsimicalis

JMIR Perioper Med 2025;8:e58905


Online Group–Based Dual-Task Training to Improve Cognitive Function of Community-Dwelling Older Adults: Randomized Controlled Feasibility Study

Online Group–Based Dual-Task Training to Improve Cognitive Function of Community-Dwelling Older Adults: Randomized Controlled Feasibility Study

In the development of the cognitive training component, various factors were considered, including the lower education level of the local older adults, the online delivery format of the intervention, the cultural appeal to the local older population, and the effectiveness and safety of the training.

Pui Hing Chau, Denise Shuk Ting Cheung, Jojo Yan Yan Kwok, Wai Chi Chan, Doris Sau Fung Yu

JMIR Aging 2025;8:e67267


Stakeholders and Contextual Factors in the Implementation of Assistive Robotic Arms for Persons With Tetraplegia: Deductive Content Analysis of Focus Group Interviews

Stakeholders and Contextual Factors in the Implementation of Assistive Robotic Arms for Persons With Tetraplegia: Deductive Content Analysis of Focus Group Interviews

Nevertheless, according to the focus group interviews, users’ quality of life was expected to improve with the use of the robotic arm. This is reflected in the observations of Maheu et al [28], where the empowerment of the user enables an improvement in the quality of life, not only of the user but also of the caregiver. This facilitator must be emphasized as an important contribution of the robotic arm [60].

Vera Fosbrooke, Marco Riguzzi, Anja M Raab

JMIR Rehabil Assist Technol 2025;12:e65759


Experience of Using Electronic Inhaler Monitoring Devices for Patients With Chronic Obstructive Pulmonary Disease or Asthma: Systematic Review of Qualitative Studies

Experience of Using Electronic Inhaler Monitoring Devices for Patients With Chronic Obstructive Pulmonary Disease or Asthma: Systematic Review of Qualitative Studies

Plaza et al’s [16] questionnaire survey of 1514 practicing physicians and Giner et al’s [17] cross-sectional study of 1496 nurses both found that only approximately 14% of them possessed adequate knowledge about inhalation therapy, suggesting widespread problems with the use of inhalation equipment and a lack of health literacy related to inhalation techniques among health care professionals.

Jilong Duan, Xia Chen, Di Fan, Haikun Jiang, Xue Zhang, Wenyue Zhang, Zhiping Liu, Hongyan Lu

JMIR Mhealth Uhealth 2025;13:e57645