Perceptions on Drivers of Self-regulated Learning for Shaping Engagement with Digital Health Interventions : An Interview Study with Digital Health Users

Abstract

Abstract Digital health interventions (DHIs) show promise for delivering effective mental health interventions at scale, however significant issues with sustained engagement have been observed. Current efforts to understand, predict, and prevent poor engagement have yielded little success due to the insufficient consideration of how engagement, and the factors driving it, can fluctuate in intensity across the user journey. One under-explored but highly relevant theoretical framework that can be applied in this context is self-regulated learning (SRL), due to the core emphasis on self-guided psychoeducation in digital mental health. SRL refers to the ability to regulate one’s emotions, cognitions, and behaviours to enhance learning outcomes. To investigate the utility and potential of this framework for advancing our knowledge of engagement with DHIs, we conducted semi-structured interviews with digital health users (n = 14) and explored the role of common SRL variables (i.e., drivers) in shaping engagement across the user journey. A template analysis identified four major themes of drivers: (i) motivational beliefs, feelings, and strategies, (ii) metacognitive feedback and control, (iii) emotional experiences, and (iv) physical and social environment. Participants broadly agreed that higher levels across one or more SRL drivers would enhance engagement behaviours, and that the importance of different drivers for shaping engagement can vary temporally. These preliminary findings highlight the relevance of SRL constructs in describing, understanding, and predicting engagement with DHIs, offering insight into potential opportunities for targeted intervention across the user journey to promote engagement. However, further research to quantitatively assess the relationships between SRL drivers and various metrics of engagement in a DHI trial is needed.

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