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Identifying Optimal Testing Modalities to Increase COVID-19 Testing Access in Baltimore, Maryland: Protocol for a Household Randomized Controlled Trial

Identifying Optimal Testing Modalities to Increase COVID-19 Testing Access in Baltimore, Maryland: Protocol for a Household Randomized Controlled Trial

We hypothesize that, compared with the standard-of-care (SOC) arm, those randomized to the community-based, mobile van testing arm (arm 2) and the self-collection, home-based testing arm (arm 3) will be more likely to receive a COVID-19 PCR test than those assigned to the SOC arm (arm 1).

Jessica Duchen, Alexandra K Mueller, Saifuddin Ahmed, Jamie Perin, Courtney Borsuk, Joshua Trowell, Kelly Lowensen, Steven Huettner, Andy Peytchev, Jason E Farley, Shruti H Mehta, Jacky M Jennings

JMIR Res Protoc 2025;14:e68600


Feasibility, Acceptability, and Preliminary Outcomes of a Mobile Adaptation of a Relational Savoring Intervention to Prevent Loneliness in College Students: Mixed Methods Pilot Study

Feasibility, Acceptability, and Preliminary Outcomes of a Mobile Adaptation of a Relational Savoring Intervention to Prevent Loneliness in College Students: Mixed Methods Pilot Study

With 38% of US teenagers and young adults reporting that they already use mobile apps for well-being [26], there is reason to believe that the development of effective mobile-based interventions for loneliness may be feasible, familiar, and cost-effective.

Brenda Nguyen, Jocelyn Lai, Hana Qureshi, Christopher Marcotullio, Sina Labbaf, Yuning Wang, Salar Jafarlou, Nikil Dutt, Amir M Rahmani, Jessica L Borelli

JMIR Form Res 2025;9:e70528


Cardiac Implantable Electronic Device Educational Application for Cardiac Anesthesiology Trainees: Tutorial on App Development

Cardiac Implantable Electronic Device Educational Application for Cardiac Anesthesiology Trainees: Tutorial on App Development

Mobile learning (m-learning) is a learning mode that uses a mobile device or tablet. It allows self-directed asynchronous learning at the pace of the learner and hence frees the learner of time and physical constraints. M-learning was shown to be associated with higher learning gains compared with conventional learning in a multitude of medical specialty education [7-10].

Ahmed Zaky, Aisha Waheed, Brittany Hatter, Srilakshmi Malempati, Sai Hemanth Maremalla, Ragib Hasan, Yuliang Zheng, Scott Snyder

JMIR Med Educ 2025;11:e60087


Evaluating Tailored Learning Experiences in Emergency Residency Training Through a Comparative Analysis of Mobile-Based Programs Versus Paper- and Web-Based Approaches: Feasibility Cross-Sectional Questionnaire Study

Evaluating Tailored Learning Experiences in Emergency Residency Training Through a Comparative Analysis of Mobile-Based Programs Versus Paper- and Web-Based Approaches: Feasibility Cross-Sectional Questionnaire Study

At the same time, advances in mobile technology are reshaping both medical education and clinical practice [5-11]. Mobile learning has emerged as a cost-effective, accessible approach that supports context-driven, real-time learning and continuous feedback—despite challenges like technical limitations and potential distractions [5].

Hsin-Ling Chen, Chen-Wei Lee, Chia-Wen Chang, Yi-Ching Chiu, Tzu-Yao Hung

JMIR Med Educ 2025;11:e57216


Understanding Patient and Physiotherapist Requirements for a Personalized Automated Smartphone Telemonitored App for Posttotal Knee Arthroplasty Rehabilitation: Qualitative Study

Understanding Patient and Physiotherapist Requirements for a Personalized Automated Smartphone Telemonitored App for Posttotal Knee Arthroplasty Rehabilitation: Qualitative Study

In contrast, a telemonitored physiotherapy program that is automated yet personalized through the ubiquitous and powerful mobile phone offers a promising, scalable solution for the majority of patients, reducing manpower demands while improving access to care. Bahadori et al [11] emphasize that the development of TKA-related apps often fails to incorporate patient input, which can undermine the effectiveness of these interventions.

Eleanor Shuxian Chew, Aileen Eugenia Scully, Samanth Shi-Man Koh, Ee-Lin Woon, Juanita Krysten Miao-Shi Low, Yu-Heng Kwan, John Wei-Ming Tan, Yong-Hao Pua, Celia Ia-Choo Tan, Luke Jonathan Haseler

JMIR Rehabil Assist Technol 2025;12:e59688


Evaluating User Engagement With a Real-Time, Text-Based Digital Mental Health Support App: Cross-Sectional, Retrospective Study

Evaluating User Engagement With a Real-Time, Text-Based Digital Mental Health Support App: Cross-Sectional, Retrospective Study

For instance, Baumel et al [13] calculated usage metrics (eg, number of user sessions and minutes of daily use) for mobile apps— including 2 apps with peer support as a primary technique (and 7 apps with peer support as a cotechnique, for a total of 9), where the support could be “through chat or messaging services (synchronous and asynchronous...)” ([13], Appendix 2)—with at least 10,000 installs; Booth et al [14] calculated interactions by the hour and other engagement metrics for a chatbot; and Raue et al

Edward Coffield, Khadeja Kausar

JMIR Form Res 2025;9:e66301


Impact of a Mobile Money–Based Conditional Cash Transfer Intervention on Health Care Utilization in Southern Madagascar: Mixed-Methods Study

Impact of a Mobile Money–Based Conditional Cash Transfer Intervention on Health Care Utilization in Southern Madagascar: Mixed-Methods Study

One technology that stands out is mobile money, which allows the creation of bank accounts and enables financial transactions using unstructured supplementary service data codes without requiring an internet connection [1]. The use of mobile money has seen an unprecedented rise in SSA over the past years, with over 781 million users in 2022 [2].

Mara Anna Franke, Anne Neumann, Kim Nordmann, Daniela Suleymanova, Onja Gabrielle Ravololohanitra, Julius Valentin Emmrich, Samuel Knauss

JMIR Mhealth Uhealth 2025;13:e60811


Web-Based, Algorithm-Guided Insulin Titration in Insulin-Treated Type 2 Diabetes: Pre-Post Intervention Study

Web-Based, Algorithm-Guided Insulin Titration in Insulin-Treated Type 2 Diabetes: Pre-Post Intervention Study

Several web-based programs and mobile apps have been developed to overcome some of the abovementioned challenges. Instead of manual recording of SMBG and then providing feedback to their provider in person, these programs allow patients to record and transmit SMBG data directly via the app, reducing the frequency of face-to-face visits [15-17].

Nishanth Thiagarajan, Hong Chang Tan, Suresh Rama Chandran, Phong Ching Lee, Yun Ann Chin, Wanling Zeng, Emily Tse Lin Ho, David Carmody, Su-Yen Goh, Yong Mong Bee

JMIR Form Res 2025;9:e68914


Enhancing Methodological Rigor in Mobile Health Care Research

Enhancing Methodological Rigor in Mobile Health Care Research

Tang et al’s recent study published in JMIR Human Factors [1], titled “The Use of Mobile Health Care Among Medical Professionals in the Sichuan-Chongqing Region: Cross-Sectional Survey Study,” captured my attention. Their analysis of mobile health (m Health) device use and influencing factors, using chi-square and multivariable logistic regression analyses, revealed a significant association between age and m Health use. This study provides valuable insights from China’s western region.

Shuhan Tang

JMIR Hum Factors 2025;12:e68243


Evaluation of a New Mobile Virtual Reality Setup to Alter Pain Perception: Pilot Development and Usability Study in Healthy Participants

Evaluation of a New Mobile Virtual Reality Setup to Alter Pain Perception: Pilot Development and Usability Study in Healthy Participants

In this pilot study, our primary goal was to evaluate an easy-to-use, telerehabilitation-friendly, mobile setup, that reduces the setup complexity significantly by using a stand-alone head-mounted display (HMD) for the visualization and a smartwatch to detect the heartbeats using photoplethysmography (PPG). We hypothesized that participants report a high level of usability and a low number of side effects, allowing for the setup to be tested in a larger randomized clinical trial.

Samuel E J Knobel, Raphael Oberson, Jonas Räber, Narayan Schütz, Niklaus Egloff, Angela Botros, Stephan M Gerber, Tobias Nef, Lukas Heydrich

JMIR Serious Games 2024;12:e52340