Improving Digital Mental Health Interventions: ENGAGEment as Mechanism of Impact

ongoing

Millions of people struggle with mental health issues, such as depression and anxiety. Effective treatments exist but are not within reach of everyone due to limited resources. Digital Mental Health Interventions (DMHIs), in which treatments are delivered by using technology via the Internet and apps, can be a solution. However, high rates of drop-out and large individual differences in outcomes make them not yet an adequate solution. Due to scarce process research, with a largely mono-disciplinary focus and reliance on group-level studies, we have limited insight into how to match DMHI components to individuals. In ENGAGE, I tackle these issues by proposing that engagement is the mechanism of impact that provides the missing link between the intervention components and individual outcomes. Earlier research has shown that engagement is a multidimensional and interdisciplinary concept consisting of behaviour, cognition, and affect. I have developed a first scale to measure engagement, shown individual differences and have shown individual engagement is predictive of outcomes. However, the developed scale is a rudimentary way of measuring engagement using self-report at fixed time-points and as a one-dimensional construct. Consequently, we have only a basic understanding of engagement which does not do justice to its complex multidimensional nature. ENGAGE will yield the following insights and outcomes: A fine-grained understanding and measurement of real-time engagement, showing the relationship between the dimensions, both on an individual level and over time. Expanding the toolbox of intervention designers to directly influence the individual mechanism of impact, by identifying and analysing the effect of strategies which influence individual engagement with DMHIs. Verification of engagement as mechanism of impact within DMHIs, by studying the relationship between intervention components, engagement, and outcomes within personalised and adaptive DMHIs.