Background: The rapid growth of digital health research, involving wearable devices, mobile apps, and sociotechnical health systems, raises complex ethical, legal, and social considerations. While institutional review boards and research ethics frameworks address some concerns, less is known about how students and trainees in digital health are systematically educated to recognize and navigate these challenges. Understanding the scope and content of ethics training is critical to ensuring the responsible development and application of digital health technologies. Objective: This study investigated how college students are trained to identify and address ethical considerations in digital health research through an analysis of formal curricula and expert perspectives. Methods: Researchers reviewed 132 syllabi from 76 academic programs across 62 universities and conducted semistructured interviews with 6 leading digital health scholars. All syllabi were coded for instructional content and learning objectives. Researchers conducted open coding and collaboratively applied affinity diagramming to organize the data into hierarchical themes. Results: All syllabi included instructional content, and most included explicit learning objectives. Analysis identified 7 key themes, which captured both explicit knowledge imparted through formal instruction and tacit knowledge cultivated through laboratory work, mentorship, and applied experiences. Findings highlighted gaps between formal ethics instruction and the realities of research practice. Conclusions: Ethics education in digital health research develops through the interplay of formal coursework and practice-based training, each fostering complementary skills needed for data-intensive and collaborative environments. Together, these pathways support students in identifying ethical issues, applying principles contextually, anticipating emerging risks, and communicating across disciplines; however, access to experiential learning opportunities remains inconsistent. Strengthening ethics training will require expanding structured early research engagement, cultivating communities of practice, and translating tacit ethical reasoning into accessible resources. Integrating ethical reflection into routine research activities may better prepare future digital health researchers to responsibly design and govern sociotechnical health systems. Trial Registration:
Depression subtype classification from social media posts: few-shot prompting vs. fine-tuning of large language models
BackgroundSocial media provides timely proxy signals of mental health, but reliable tweet-level classification of depression subtypes remains challenging due to short, noisy text, overlapping symptomatology,