Abstract
Background/Objectives: Depressive disorders are among the most prevalent mental illnesses worldwide. Digital health interventions offer potential to improve access, efficiency, and outcomes in depression care. However, their sustainable integration into routine clinical practice remains limited. This study explored individual, organizational, external and contextual factors influencing digital health interventions implementation from the perspective of health professionals. Methods: Semi-structured interviews with health professionals (n = 9) were analyzed using a hybrid qualitative approach. First, structuring content analysis following Kuckartz was applied to systematically code and categorize the transcripts. Second, the resulting codes were mapped onto four domains of the Consolidated Framework for Implementation Research (Outer Setting, Inner Setting, Process, and Characteristics of Individuals) to identify implementation-relevant barriers and facilitators. This combined approach ensured a transparent, theory-informed, and reproducible analysis of factors influencing digital health intervention implementation in depression care. Results: Key individual-level enablers included openness to innovation, motivation, and prior experience with digital tools. Organizational factors such as leadership support, designated facilitators, time, training, and IT infrastructure were critical. External factors included data protection, clear regulatory frameworks, reimbursement mechanisms, and scientific validation. Barriers involved limited digital skills, ambiguous responsibilities, and concerns about misuse or risks. Conclusions: The successful implementation of digital health interventions in depression care requires alignment with organizational structures, provider capabilities, and patient needs. Supportive leadership, tailored training, and clear external frameworks can enhance acceptance and sustainability. As complementary tools, digital health interventions can help optimize mental health services and improve patient outcomes.