Developing personas to inform the design of digital interventions for perinatal mental health

Digital interventions are increasingly in demand to address mental health concerns, with significant potential to reach populations that disproportionately face barriers to accessing mental health care. Challenges with user engagement, however, persist. The goal of this study was to develop user personas to inform the development of a digital mental health intervention (DMHI) for a perinatal population.

We used participatory User-Centered Design (UCD) methods to generate and validate personas (ie, representative profiles of potential users). We applied this methodology to a case example of an Anxiety Sensitivity Intervention. Phases included (1) Characteristic identification, (2) Persona generation, (3) Persona consolidation, (4) Persona validation, and (5) Persona refinement. Advisory Council members with lived expertise of perinatal mental health conditions generated 6 personas. We used cluster analysis and qualitative analysis to consolidate personas. We used participant interviews with perinatal individuals experiencing depression or anxiety and economic marginalization (n = 12) to qualitatively validate and refine these personas.

We identified 4 user personas with potentially unique design needs that we characterized as being "Resilient," "Lonely," "Overwhelmed," and "Aware."

Personas generated through this process had distinct characteristics and design implications including the need to prioritize (1) content personalization, (2) additional content describing support options and resources (eg, doulas, midwives), (3) careful consideration of the type of information provided by users, and (4) transparent options for information and data sharing.

DMHIs will need to be adapted for relevance for a perinatal population. The personas we developed are suggestive of the need for design considerations specific to distinct potential user groups within this population.