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Needs and Preferences of Swedish Young Adults for a Digital App Promoting Mental Health Literacy, Occupational Balance, and Peer Support: Qualitative Interview Study

Needs and Preferences of Swedish Young Adults for a Digital App Promoting Mental Health Literacy, Occupational Balance, and Peer Support: Qualitative Interview Study

The young adults were asked whether they were interested in participating or whether they could forward the invitation to someone else who met the inclusion criteria. If the young adult was interested, they were provided with an information letter outlining the key aspects of their participation. At the end of each interview, participants were asked whether they knew any peers who might be interested in taking part in the study.

Martin Karaba Bäckström, Sonya Girdler, Ben Milbourn, Annika Lexén

JMIR Form Res 2025;9:e71563

A Health Service Research Study on a Low-Threshold Hearing Screening Program for Childhood Cancer Survivors in Switzerland: Protocol for the HEAR Study

A Health Service Research Study on a Low-Threshold Hearing Screening Program for Childhood Cancer Survivors in Switzerland: Protocol for the HEAR Study

Eligible for the HEAR study were childhood cancer survivors registered in the Ch CR, who had been diagnosed with childhood cancer between 1976 and 2019, had survived ≥2 years since their diagnosis, were aged ≥18 years at the start of the study, and were at risk for hearing loss (Figure 1).

Philippa Jörger, Carina Nigg, Luzius Mader, Sven Strebel, Martin Kompis, Zuzana Tomášiková, Christina Schindera, Gisela Michel, Nicolas Xavier von der Weid, Marc Ansari, Nicolas Waespe, Claudia Elisabeth Kuehni

JMIR Res Protoc 2025;14:e63627

Evaluating the Accuracy and Reliability of Real-World Digital Mobility Outcomes in Older Adults After Hip Fracture: Cross-Sectional Observational Study

Evaluating the Accuracy and Reliability of Real-World Digital Mobility Outcomes in Older Adults After Hip Fracture: Cross-Sectional Observational Study

Data were collected between July 2020 and March 2022. The participants after hip fracture were recruited from the Robert Bosch Foundation for Medical Research (Germany) and Kiel University (Germany). The participants were recruited within 13 months of surgical treatment (fixation or arthroplasty) for a low-energy fracture of the proximal femur (International Classification of Diseases, 10th Revision, diagnosis codes S72.0, S72.1, and S72.2), as diagnosed through x-rays of the hip and pelvis.

Martin A Berge, Anisoara Paraschiv-Ionescu, Cameron Kirk, Arne Küderle, Encarna Micó-Amigo, Clemens Becker, Andrea Cereatti, Silvia Del Din, Monika Engdal, Judith Garcia-Aymerich, Karoline B Grønvik, Clint Hansen, Jeffrey M Hausdorff, Jorunn L Helbostad, Carl-Philipp Jansen, Lars Gunnar Johnsen, Jochen Klenk, Sarah Koch, Walter Maetzler, Dimitrios Megaritis, Arne Müller, Lynn Rochester, Lars Schwickert, Kristin Taraldsen, Beatrix Vereijken

JMIR Form Res 2025;9:e67792

Machine Learning Model for Predicting Coronary Heart Disease Risk: Development and Validation Using Insights From a Japanese Population–Based Study

Machine Learning Model for Predicting Coronary Heart Disease Risk: Development and Validation Using Insights From a Japanese Population–Based Study

From 1989 to 1999, a total of 7672 men and women aged 30-84 years who did not have a previous history of cardiovascular disease were recruited for the study. Participants were selected from the population registry of the municipality and were followed up every 2 years for an average of 15 years until their first occurrence of stroke, myocardial infarction (MI), death, or relocation.

Thien Vu, Yoshihiro Kokubo, Mai Inoue, Masaki Yamamoto, Attayeb Mohsen, Agustin Martin-Morales, Research Dawadi, Takao Inoue, Jie Ting Tay, Mari Yoshizaki, Naoki Watanabe, Yuki Kuriya, Chisa Matsumoto, Ahmed Arafa, Yoko M Nakao, Yuka Kato, Masayuki Teramoto, Michihiro Araki

JMIR Cardio 2025;9:e68066

Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Univariate TFT and ARIMA models that took depression incidence as the single output variable were also fitted for model comparison. The testing accuracies of the various models on all the 10-year sub-timeseries samples were measured by symmetric mean absolute percentage error (SMAPE) between the forecasted results and actual value. Features of all the models are shown in Table S1 in Multimedia Appendix 1.

Deliang Yang, Yiyi Tang, Vivien Kin Yi Chan, Qiwen Fang, Sandra Sau Man Chan, Hao Luo, Ian Chi Kei Wong, Huang-Tz Ou, Esther Wai Yin Chan, David Makram Bishai, Yingyao Chen, Martin Knapp, Mark Jit, Dawn Craig, Xue Li

J Med Internet Res 2025;27:e67156

Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study

Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study

Participants in this study were not recruited but were existing users of the commercially available DDF app. Data were collected from users who voluntarily engaged with the app as part of their normal use, and all data analyzed were deidentified entries made during the first 30 days of app use. DDF is a freely accessible web-based app with a subscription option [13].

Michelle R Jospe, Martin Kendall, Susan M Schembre, Melyssa Roy

JMIR Form Res 2025;9:e65368

Improving Recruitment Through Social Media and Web-Based Advertising to Evaluate the Genetic Risk and Long-Term Complications in Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis: Community-Based Survey

Improving Recruitment Through Social Media and Web-Based Advertising to Evaluate the Genetic Risk and Long-Term Complications in Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis: Community-Based Survey

Advertisements were introduced on the Vanderbilt University Medical Center (VUMC) Facebook and Instagram pages using flyers, and 60-second SJS/TEN survivor video vignettes were later added. Next, we launched a nationwide Google Ad campaign. Advertisement-derived interest surveys identified potential participants who were then contacted by phone. Interest surveys reported the mode of recruitment through a single-choice answer of “a website,” “Facebook,” “Instagram,” “Google,” “referral,” or “other.”

Elizabeth A Williams, Michelle D Martin-Pozo, Alexis H Yu, Krystyna Daniels, Madeline Marks, April O'Connor, Elizabeth J Phillips

J Med Internet Res 2025;27:e63712

Benefits and Limitations of Teledermatology in German Correctional Facilities: Cross-Sectional Analysis

Benefits and Limitations of Teledermatology in German Correctional Facilities: Cross-Sectional Analysis

After geocoding and referencing the locations, they were loaded and mapped in a geographic information system in Arc GIS v. 10.8.1 (ESRI). As a proxy for accessibility, physician density was compared to correctional facility locations. Data were provided by Kassenaerztliche Bundesvereinigung (KBV; data status 2022).

Brigitte Stephan, Kathrin Gehrdau, Christina Sorbe, Matthias Augustin, Martin Scherer, Anne Kis

JMIR Med Inform 2025;13:e58712

Systematic Identification of Caregivers of Patients Living With Dementia in the Electronic Health Record: Known Contacts and Natural Language Processing Cohort Study

Systematic Identification of Caregivers of Patients Living With Dementia in the Electronic Health Record: Known Contacts and Natural Language Processing Cohort Study

The final 75 were completed independently by AED. Issues with data, such as misspelled names, were discussed as a team. 100% of the text samples with known contacts identified by the algorithm (n=50) were verified to contain names of known contacts. Of the text sample without identified known contacts (n=50), 1 note (2%) was manually verified to contain the name of a known contact, and 2 notes (4%) contained references to possible caregiver names that were not matched to known contacts.

Daniel Martin, Jason Lyons, J David Powers, Andrea E Daddato, Rebecca S Boxer, Elizabeth Bayliss, Jennifer Dickman Portz

J Med Internet Res 2025;27:e63654