Abstract

Engagement is a key metric that researchers can use to assess whether participants received the intended dose of a digital health intervention. However, the prevailing approach has predominantly focused on individual paradata metrics, resulting in a fragmented understanding of overall engagement. To address this limitation, our study utilizes person-centered approaches that allow for the simultaneous capture of multiple engagement metrics within imi–a web application specifically designed to support the mental health of lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority youth (LGBTQ+ youth). This person-centered approach enabled us to explore the association between engagement patterns and stress appraisal outcomes within the imi intervention arm. Utilizing latent profile analysis, we classified users into two engagement forms: overall engagement (total number of sessions, pages visited, and external links clicked and their cumulative time spent using imi) and content engagement (number of pages viewed across imi's four core guides: gender, stress, queerness, and stigma). We identified two profiles for each form: a “high engagement” profile and an “average engagement” profile, with the majority of participants assigned to the “average engagement” profile. Our analyses revealed a significant association between overall engagement profiles and stress appraisals, with the “high engagement” profile demonstrating higher challenge appraisals and marginal improvements in threat appraisals compared to the “average engagement” profile. However, no such associations were observed for content engagement profiles and stress appraisal outcomes. The two person-centered approaches used were consistent with prior results utilizing a variable-centered approach, indicating a stronger intervention effect among individuals who exhibit higher engagement in digital health interventions. Although both methods yielded comparable findings, the person-centered approach mitigates concerns related to multi-collinearity and adds additional nuance and context to the study of digital engagement.

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