Towards a Semantic Data Model for Representing, Storing, and Retrieving Knowledge about Coping Strategies for Use in Digital Mental Health Interventions

Digital interventions including apps, chatbots, and algorithms often provide psychoeducational material to support the mental health literacy of people. This may include helpful coping strategies. However, there can be a myriad of coping strategies that can be used for different scenarios by different people. To promote engagement, adherence and efficacy, development of such interventions faces the challenge of tailoring such coping strategies to the user’s individual needs and preferences. This study proposes a comprehensive machine-readable taxonomy to semantically structure everyday coping strategies. We provide digital pro-forma that allows for the knowledge engineering of machine-readable representations of coping strategies by mental health experts. The proforma outlines a coping strategy in lay terms, then semantically classifies it using three different taxonomies; (i) either ‘emotion’ or ‘problem’ focussed, (ii) the 15 detailed categories within the Lazarus & Folkman theoretical framework(e.g. whether the strategy is related to self-distraction and/or is a form of positive reframing etc.), and (iii) the peer reviewed research evidence outlining consideration of the coping strategy across different contexts (e.g. mental health conditions such as depression, anxiety etc.). A final section will also allow experts to add semantic concepts and textual labels (e.g., keywords) to textually describe the coping strategy, to facilitate intelligent search functions by later users. As an example of applying the proforma, the presentation outlines the characterisation of seven different everyday coping strategies. This demonstrates the generalisability of the overall model (to a degree). The proforma is discussed in terms of how interdisciplinary research between psychologists and computer scientists is crucial for defining these semantic data models to query and present empirical coping strategies at the point of need to users. If such models are standardised, open and interoperable, then numerous digital interventions may use this knowledge base to deliver high quality evidence-based content.