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Assessing the Cultural Fit of a Digital Sleep Intervention for Refugees in Germany: Qualitative Study

Assessing the Cultural Fit of a Digital Sleep Intervention for Refugees in Germany: Qualitative Study

Frequency analyses of positive and negative feedback given by the refugees from (A) Ukraine and (B) other countries of origin participating in the qualitative study in Germany. The numbers of positive and negative feedback are illustrated separately for the adapted version and the nonadapted version of the digital intervention Sleep-e tested in the study. oth: other countries of origin; ukr: Ukraine. You can take a lot from it also. And you can learn easily also. To have the training..., it’s much easier.

Maja Blomenkamp, Andrea Kiesel, Harald Baumeister, Dirk Lehr, Josef Unterrainer, Lasse B Sander, Kerstin Spanhel

JMIR Form Res 2025;9:e65412

Digital Health Resilience and Well-Being Interventions for Military Members, Veterans, and Public Safety Personnel: Environmental Scan and Quality Review

Digital Health Resilience and Well-Being Interventions for Military Members, Veterans, and Public Safety Personnel: Environmental Scan and Quality Review

After completing part A and B, the scores for each item were added up for a total score out of 30 for part A, and 60 for part B. A higher score in part A indicates that the app fits the purpose of the project, is trustworthy, has adequate privacy, and is affordable [37]. A higher score in part B indicates better quality of content and usability of the app [37].

Rashell R Allen, Myrah A Malik, Carley Aquin, Lucijana Herceg, Suzette Brémault-Phillips, Phillip R Sevigny

JMIR Mhealth Uhealth 2025;13:e64098

Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for “Complete Data”: Observational Clinical Data Analysis

Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for “Complete Data”: Observational Clinical Data Analysis

Available percentage of patients’ data upon individually applying all 19 filters in different ethnic subgroups in (A) the Cedars-Sinai dataset, (B) the CUIMC dataset, and (C) the Ao U dataset. The filters are in descending order following the available percentage of the category, all. The points are connected to ease the visualization, but the filters are not cumulative. Stacked bar plots show the ethnicity distribution of the datasets in percentages.

Jose Miguel Acitores Cortina, Yasaman Fatapour, Kathleen LaRow Brown, Undina Gisladottir, Michael Zietz, Oliver John Bear Don't Walk IV, Danner Peter, Jacob S Berkowitz, Nadine A Friedrich, Sophia Kivelson, Aditi Kuchi, Hongyu Liu, Apoorva Srinivasan, Kevin K Tsang, Nicholas P Tatonetti

JMIR Med Inform 2025;13:e67591

Treatment of Substance Use Disorders With a Mobile Phone App Within Rural Collaborative Care Management (Senyo Health): Protocol for a Mixed Methods Randomized Controlled Trial

Treatment of Substance Use Disorders With a Mobile Phone App Within Rural Collaborative Care Management (Senyo Health): Protocol for a Mixed Methods Randomized Controlled Trial

Panel (B) shows the current “To-do List” and also displays the chat icon at the bottom of the panel. Panel (C) shows a behavioral activation task, and panel (D) showcases the points awarded for completing this task. Senyo Health chat feature being displayed from the perspective of the recovery coach. The left is conversations with multiple patients. Once selected, the full conversation appears in the center of the screen, with the recovery coach able to text back and forth.

Tyler S Oesterle, Nicholas L Bormann, Margaret M Paul, Scott A Breitinger, Benjamin Lai, Jamie L Smith, Cindy J Stoppel, Stephan Arndt, Mark D Williams

JMIR Res Protoc 2025;14:e65693