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Analysis of Metabolic and Quality-of-Life Factors in Patients With Cancer for a New Approach to Classifying Walking Habits: Secondary Analysis of a Randomized Controlled Trial

Analysis of Metabolic and Quality-of-Life Factors in Patients With Cancer for a New Approach to Classifying Walking Habits: Secondary Analysis of a Randomized Controlled Trial

At each outpatient clinic visit, the patient’s height and weight were measured using an electronic device, and the recorded values were directly entered into the electronic medical record, where the BMI was automatically calculated. Metabolic parameters (HDL cholesterol, triglycerides, Hb A1c, and FBS) were also collected at each outpatient clinic, and FBS was measured after eight hours of fasting.

Yae Won Tak, Junetae Kim, Haekwon Chung, Sae Byul Lee, In Ja Park, Sei Won Lee, Min-Woo Jo, Jong Won Lee, Seunghee Baek, Yura Lee

J Med Internet Res 2025;27:e52694

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

Online Safety When Considering Self-Harm and Suicide-Related Content: Qualitative Focus Group Study With Young People, Policy Makers, and Social Media Industry Professionals

Online Safety When Considering Self-Harm and Suicide-Related Content: Qualitative Focus Group Study With Young People, Policy Makers, and Social Media Industry Professionals

Given the difficulties accessing high-quality, timely, and age-appropriate mental health support, young people have also identified social media as an accessible, and sometimes preferred, avenue for seeking help or information, especially for stigmatized topics such as self-harm and suicide [16].

Louise La Sala, Amanda Sabo, Maria Michail, Pinar Thorn, Michelle Lamblin, Vivienne Browne, Jo Robinson

J Med Internet Res 2025;27:e66321

Nationwide Trends in Screen Time and Associated Risk Factors by Family Structures Among Adolescents, 2008-2022: Nationwide Cross-Sectional Study

Nationwide Trends in Screen Time and Associated Risk Factors by Family Structures Among Adolescents, 2008-2022: Nationwide Cross-Sectional Study

Administered annually by the Korea Disease Control and Prevention Agency, the survey has consistently maintained an average response rate of 95.7% over the past 15 years. Students voluntarily completed a web-based anonymous questionnaire following a standardized protocol in a computer lab in each school [19]. To ensure the data’s representativeness, sampling weights were determined and applied.

Seokjun Kim, Hyesu Jo, Yejun Son, Min Kyung Shin, Kyeongmin Lee, Jaeyu Park, Hayeon Lee, Lee Smith, Elena Dragioti, Guillaume Fond, Laurent Boyer, Guillermo F López Sánchez, Mark A Tully, Masoud Rahmati, Damiano Pizzol, Selin Woo, Dong Keon Yon

JMIR Public Health Surveill 2025;11:e57962

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

Leveraging Large Language Models for Infectious Disease Surveillance—Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis

Leveraging Large Language Models for Infectious Disease Surveillance—Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis

Reinfection often refers to the phenomenon in which an individual who has recovered from COVID-19 is again infected with the virus [31]. Some researchers [32,33] considered that reinfection is identified when an individual tests positive again through polymerase chain reaction (PCR) testing after a minimum of 90 days of a negative result. However, some studies also suggest this duration should be 30 days [34,35].

Jiacheng Xie, Ziyang Zhang, Shuai Zeng, Joel Hilliard, Guanghui An, Xiaoting Tang, Lei Jiang, Yang Yu, Xiufeng Wan, Dong Xu

J Med Internet Res 2025;27:e63190

Machine Learning Approach to Identifying Wrong-Site Surgeries Using Centers for Medicare and Medicaid Services Dataset: Development and Validation Study

Machine Learning Approach to Identifying Wrong-Site Surgeries Using Centers for Medicare and Medicaid Services Dataset: Development and Validation Study

Precision-recall curves have been considered an effective metric for accessing the model, especially the data is an unbalanced dataset [15,16]. The optimal probability threshold is where a point can achieve high precision score while only sacrificing minimal recall (Figure S1 in Multimedia Appendix 1). By calculating the accurate prediction rate of the AOP model and the rule-based method (right-left and left-right), we can compare the performance between these 2 methods.

Yuan-Hsin Chen, Ching-Hsuan Lin, Chiao-Hsin Fan, An Jim Long, Jeremiah Scholl, Yen-Pin Kao, Usman Iqbal, Yu-Chuan Jack Li

JMIR Form Res 2025;9:e68436

Application of Clinical Department–Specific AI-Assisted Coding Using Taiwan Diagnosis-Related Groups: Retrospective Validation Study

Application of Clinical Department–Specific AI-Assisted Coding Using Taiwan Diagnosis-Related Groups: Retrospective Validation Study

In this study, we have developed an exclusive ICD-10-CM AI-assisted coding module. Coding professionals took part in the research and offered suggestions to improve the efficiency of coding operations.

An-Tai Lu, Chong-Sin Liou, Chia-Hsin Lai, Bo-Tsz Shian, Ming-Ta Li, Chih-Yen Sun, Hao-Yun Kao, Hong-Jie Dai, Ming-Ju Tsai

JMIR Hum Factors 2025;12:e59961