Compassion as a guiding framework for digital mental health implementation: an interview study with clients and professionals
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Background
Digital mental health interventions are often described in terms of their contribution to cost-effectiveness or innovation. Instead, many clients and professionals in mental healthcare seem to value the human connection highly. To implement technology in ways that align with values held by clients and professionals, a value-based framework for technology use in mental healthcare could be promising. The current study explores whether values of clients and professionals in mental healthcare match a framework of compassion, and whether this framework could be a suitable foundation for the implementation of digital mental health interventions.
Method
We conducted semi-structured interviews with 5 (former) clients and 15 professionals in mental healthcare. Values of both clients and professionals were analyzed inductively, and deductively linked to a compassion framework. Professionals were asked whether their values were congruent with their organization’s approach to technology. We coded their answers as matches and mismatches, and described the themes identified in both categories.
Results
Values held by clients and professionals showed many connections with the compassion framework. Clients highly valued feeling heard and understood, humanity, and openness from the professional. Professionals highly valued helping people, personalization, and offering transparency. Examples of how technology use could enhance or detract from compassion according to participants were also identified. Professionals experienced a match with their values if they felt that their organizations focused the adoption of technology on the client’s autonomy or meeting treatment needs. They experienced a mismatch if they felt that their organizations were more focused on financial benefit or a technology push.
Conclusion
Compassion seems a promising framework for integrating technology in mental healthcare in value-sensitive ways.
