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Development of a Cocreated Decision Aid for Patients With Depression—Combining Data-Driven Prediction With Patients’ and Clinicians’ Needs and Perspectives: Mixed Methods Study

Development of a Cocreated Decision Aid for Patients With Depression—Combining Data-Driven Prediction With Patients’ and Clinicians’ Needs and Perspectives: Mixed Methods Study

In cases with more than two measurements, the last score within 365 days was used (see Section C in Multimedia Appendix 1). Prediction modeling was based on validated Dutch OQ-45 cutoff scores to assess a clinically relevant decrease in symptoms between two measurements (reliable change index: a decrease of at least 14 points in total score) [45,47].

Kaying Kan, Frederike Jörg, Klaas J Wardenaar, Frank J Blaauw, Maarten F Brilman, Ellen Visser, Dennis Raven, Dwayne Meijnckens, Erik Buskens, Danielle C Cath, Bennard Doornbos, Robert A Schoevers, Talitha L Feenstra

J Particip Med 2025;17:e67170

Reducing Methamphetamine Use in Aboriginal and Torres Strait Islander Communities With the “We Can Do This” Web App: Qualitative Evaluation of Acceptability and Feasibility

Reducing Methamphetamine Use in Aboriginal and Torres Strait Islander Communities With the “We Can Do This” Web App: Qualitative Evaluation of Acceptability and Feasibility

The following codes are used to identify: P=person with experience, also referred to as “clients”; C=clinician; and W=peer worker. Affective attitude refers to how a participant feels about the program being evaluated. There were several examples of positive affect. As one clinician stated: I had a good feeling that there was this kind of app out there available for clients. So going through it, I was like “Yeah, this is looking pretty good.”

Leda Sivak, Rachel Reilly, Shani Crumpen, Carla Treloar, Rebecca McKetin, Julia Butt, Yvette Roe, Nadine Ezard, Brendan Quinn, Jack Nagle, Wade Longbottom, Clifford Warrior, James Ward

JMIR Form Res 2025;9:e58369

Regulatory Insights From 27 Years of Artificial Intelligence/Machine Learning–Enabled Medical Device Recalls in the United States: Implications for Future Governance

Regulatory Insights From 27 Years of Artificial Intelligence/Machine Learning–Enabled Medical Device Recalls in the United States: Implications for Future Governance

The Guidance of Initiation of Voluntary Recalls Under 21 CFR Part 7, Subpart C mentions referencing 21 CFR 820.100(a)(2), which requires procedures for implementing corrections or preventive actions to include an investigation of the causes for nonconformities related to the product, processes, and quality systems.

Wei-Pin Chen, Wei-Guang Teng, C Benson Kuo, Yu-Jui Yen, Jian-Yu Lian, Matthew Sing, Peng-Ting Chen

JMIR Med Inform 2025;13:e67552