This project tackles the challenges of designing effective, scalable digital mental health care solutions by integrating psychological research with human-computer interaction (HCI) principles. An exploration of self-care technologies (SCTs) for mental health is conducted to highlight challenges to comparative analysis, due to fragmented research outcomes and insufficient theoretical grounding.

A theoretical framework in clinical psychology is adapted to bridge the gap between psychological science and HCI. A methodology for conducting standardized, structured comparative analysis of mental health interventions is identified. The identified methodology is used to demonstrate the analysis of a conventional in-person social anxiety intervention. This is followed by an analysis of a corresponding, digitized social anxiety intervention, which highlights how interventions can change through digitization. Further, the influence of intervening third variables is observed, and plausible solutions to implementation challenges are suggested. The discussion further illustrates the importance of HCI principles in improving the utilization of interventions through user engagement and provides theoretical grounding for incorporating principles into interventions. A replicable model for designing future mental health interventions is presented, and offers actionable steps to close the gap between theoretical promise and real-world impact in digital mental health care.

Since further research on digital health technologies is needed, this work provides a structure for conducting future investigations. This first-principles approach can improve mental health care interventions and support targeted development of precise solutions through digital health tools.