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Playful Antisedentary Interactions for Online Meeting Scenarios: A Research Through Design Approach

Playful Antisedentary Interactions for Online Meeting Scenarios: A Research Through Design Approach

To further clarify the insights from the idea cards, we used an affinity diagram to identify common themes, patterns, and relationships among the data points. For the discussion content, we used the conventional qualitative content analysis method outlined by Hsieh and Shannon [59] to examine how the initial design considerations supported participants in formulating their ideas. An illustration of our design process, highlighting the various stages involved. The co-design workshops yielded rich insights.

Jiaqi Jiang, Shanghao Li, Xian Li, Yingxin Xu, Jian Zhao, Pengcheng An

JMIR Serious Games 2025;13:e62778

Evaluation of a Digital Media Campaign to Promote Knowledge and Awareness of the GPFirst Program for Nonurgent Conditions: Repeated Survey Study

Evaluation of a Digital Media Campaign to Promote Knowledge and Awareness of the GPFirst Program for Nonurgent Conditions: Repeated Survey Study

The sample size was determined using the Yamane formula with an error tolerance set at 0.05 [37], resulting in an estimated sample of 400 per study group, 1200 participants per survey, and a total of 2400 participants across both surveys. Data analysis was performed using SPSS (version 27; IBM Corp), with a significance level of .05. Standard descriptive statistics including means, SDs, and frequencies were reported as appropriate.

Rebecca Ong Hui Shan, Hong Choon Oh, Priscilla Goh Sook Kheng, Lyndia Lee Sze Hui, Mas Riza Bte Mohd Razali, Edris Atikah Ahmad, Jagadesan Raghuram, Choon How How, Steven Lim Hoon Chin

JMIR Public Health Surveill 2025;11:e66062

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

Moreover, autonomic nervous system instability affects heart rate variability (HRV); thus, HRV serves as an effective predictor of delirium [30]. A prospective cohort study reported the association between HRV and delirium [31], and a recent study showed that delirium could be predicted using HRV estimated from an ECG [32]. Both the PPG and ECG are typically used to estimate the HRV [33,34], and respiratory waveforms and rates can be incorporated as model inputs, considering their clinical relevance [35].

Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

J Med Internet Res 2025;27:e59520

Efficacy of a Web-Based Integrated Growth Mindset Intervention on Reducing Anxiety Among Social Work and Counseling Practicum Trainees: Protocol for a 2-Arm Randomized Controlled Trial

Efficacy of a Web-Based Integrated Growth Mindset Intervention on Reducing Anxiety Among Social Work and Counseling Practicum Trainees: Protocol for a 2-Arm Randomized Controlled Trial

Practicum is an essential educational component of professional training [1,2], bridging the gap between theory and practice and enhancing the professional capacity and core competence of future practitioners [3,4]. The quality of fieldwork profoundly influences social work trainees’ personal, intellectual, and professional development [4], per communication skills, critical reflection, professional growth, creativity, innovation, and self-efficacy [1,5].

Yongyi Wang, An Xi, Stella S K Wong, Kong Yam, Janet Tsin Yee Leung, Shimin Zhu

JMIR Res Protoc 2025;14:e67234

Evaluating the Effectiveness of a Mobile App for Breast Cancer Self-Management on Self-Efficacy: Nonrandomized Intervention Trial

Evaluating the Effectiveness of a Mobile App for Breast Cancer Self-Management on Self-Efficacy: Nonrandomized Intervention Trial

By incorporating tools that address perceived barriers (eg, educational resource provision) and highlighting the benefits of adherence to treatment and self-care routines, the app was designed to empower patients to take an active role in managing their health [30,31].

Sun Mi Kim, Da Seul Kim, Yoonsung Jang, Min Kyoon Kim, Eun-Seung Yu, Doug Hyun Han, Hee Jun Kim

JMIR Mhealth Uhealth 2025;13:e63989

Machine Learning–Based Explainable Automated Nonlinear Computation Scoring System for Health Score and an Application for Prediction of Perioperative Stroke: Retrospective Study

Machine Learning–Based Explainable Automated Nonlinear Computation Scoring System for Health Score and an Application for Prediction of Perioperative Stroke: Retrospective Study

For instance, an ML-based automated scoring model was developed by integrating the Random Forest (RF) algorithm and logistic regression methods [16]. This model was designed to be easy to understand and apply to various clinical situations, such as in-hospital mortality and out-of-hospital cardiac arrest [16,17]. However, these approaches still rely on scoring methods rooted in traditional statistics, using variables selected by the ML models [16].

Mi-Young Oh, Hee-Soo Kim, Young Mi Jung, Hyung-Chul Lee, Seung-Bo Lee, Seung Mi Lee

J Med Internet Res 2025;27:e58021

Effect of SMS Ward Round Notifications on Inpatient Experience in Acute Medical Settings: Retrospective Cohort Study

Effect of SMS Ward Round Notifications on Inpatient Experience in Acute Medical Settings: Retrospective Cohort Study

For the patient, inpatient ward rounds provide an opportunity for direct patient-clinician communication, sharing of information, and participation in their own care planning [3,4]. Despite the widely recognized importance of ward rounds, an environment conducive to conducting such rounds and effectively communicating with patients is not always achievable, resulting in ineffective communication with and dissatisfaction of patients [5].

Jongchan Lee, Soyeon Ahn, Jung Hun Ohn, Eun Sun Kim, Yejee Lim, Hye Won Kim, Hee-Sun Park, Jae Ho Cho, Sun-wook Kim, Jiwon Ryu, Jihye Kim, Hak Chul Jang, Nak-Hyun Kim

JMIR Hum Factors 2025;12:e57470

Correlation Between Diagnosis-Related Group Weights and Nursing Time in the Cardiology Department: Cross-Sectional Study

Correlation Between Diagnosis-Related Group Weights and Nursing Time in the Cardiology Department: Cross-Sectional Study

In the meantime, studies in China have also shown that DRG systems can be used as an evaluation index for the quality of medical services, work efficiency, operating costs, and performance [11].

Chen Lv, Yi-Hong Gong, Xiu-Hua Wang, Jun An, Qian Wang, Jing Han, Xiao-Feng Chen

JMIR Med Inform 2025;13:e65549

Deep Learning–Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study

Deep Learning–Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study

Electrocardiogram (ECG) is an old tool in clinical medicine but has re-emerged for the prediction of low left ventricular ejection fraction [17], arrhythmia [18], dyskalemia [19], or even longer-term mortality [20].

Shao-Chi Lu, Guang-Yuan Chen, An-Sheng Liu, Jen-Tang Sun, Jun-Wan Gao, Chien-Hua Huang, Chu-Lin Tsai, Li-Chen Fu

J Med Internet Res 2025;27:e67576

Comparative Effectiveness of Wearable Devices and Built-In Step Counters in Reducing Metabolic Syndrome Risk in South Korea: Population-Based Cohort Study

Comparative Effectiveness of Wearable Devices and Built-In Step Counters in Reducing Metabolic Syndrome Risk in South Korea: Population-Based Cohort Study

If any of these 5 health behaviors were not practiced before the program but were adopted afterward, it was considered an improvement in health behaviors.

Kyung-In Joung, Sook Hee An, Joon Seok Bang, Kwang Joon Kim

JMIR Mhealth Uhealth 2025;13:e64527