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Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis

Use of a Medical Communication Framework to Assess the Quality of Generative Artificial Intelligence Replies to Primary Care Patient Portal Messages: Content Analysis

A third option may be to have patients self-select questions to ask Gen AI versus PCPs, so that patients format questions de novo for input into Gen AI, and responses do not suffer from lack of contextual information. Organizations will have to weigh the potential net benefit of these approaches with other potential solutions, such as investing in robust best practices for inbox management [8] or hiring dedicated clinical staff for inbox management. Our report has several key strengths.

Natalie S Lee, Nathan Richards, Jodi Grandominico, Robert M Cronin, Amanda K Hendricks, Ravi S Tripathi, Daniel E Jonas

JMIR Form Res 2025;9:e71966

Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study

Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study

The dataset we built in this work, called D3 TEC (TEC de Monterrey’s Depression Detection Dataset), stands out for providing 2 new types of data previously unavailable in voice depression classification: Spanish recordings and simultaneous recordings using both professional and smartphone microphones. Moreover, audio quality standards are higher than most publicly available voice depression datasets.

Luis F Brenes, Luis A Trejo, Jose Antonio Cantoral-Ceballos, Daniela Aguilar-De León, Fresia Paloma Hernández-Moreno

JMIR Res Protoc 2025;14:e60439

Enhancing Enrollment and Adherence in Long-Term Wearable Research on Dementia: Qualitative Systematic Review and Meta-Synthesis

Enhancing Enrollment and Adherence in Long-Term Wearable Research on Dementia: Qualitative Systematic Review and Meta-Synthesis

Participants understood that data sharing was often necessary to meet the goals of the study, and privacy concerns were ameliorated when researchers established trust around data management: “Both informal caregivers and the nursing staff were not concerned about privacy issues regarding the wearable, as they consider biomedical variables as de-individualized values. The participants trusted the researchers and nursing home regarding good data handling, as they felt well-informed” [61].

Colleen M Peterson, Renée M St Louis, Carol Flannagan

JMIR Aging 2025;8:e63768