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BackgroundAlthough internet-based cognitive behavior therapy (iCBT) interventions can reduce depression symptoms, large differences in their effectiveness exist.ObjectiveThe aim of this study was to evaluate the effectiveness of an iCBT intervention called Thrive, which was designed to enhance engagement when delivered as a fully automated, stand-alone intervention to a rural community population of adults with depression symptoms.MethodsUsing no diagnostic or treatment exclusions, 343 adults with depression symptoms were recruited from communities using an open-access website and randomized 1:1 to the Thrive intervention group or the control group. Using self-reports, participants were evaluated at baseline and 4 and 8 weeks for the primary outcome of depression symptom severity and secondary outcome measures of anxiety symptoms, work and social adjustment, psychological resilience, and suicidal ideation.ResultsOver the 8-week follow-up period, the intervention group (n=181) had significantly lower depression symptom severity than the control group (n=162; P<.001), with a moderate treatment effect size (d=0.63). Moderate to near-moderate effect sizes favoring the intervention group were observed for anxiety symptoms (P<.001; d=0.47), work/social functioning (P<.001; d=0.39), and resilience (P<.001; d=0.55). Although not significant, the intervention group was 45% less likely than the control group to experience increased suicidal ideation (odds ratio 0.55).ConclusionsThese findings suggest that the Thrive intervention was effective in reducing depression and anxiety symptom severity and improving functioning and resilience among a mostly rural community population of US adults. The effect sizes associated with Thrive were generally larger than those of other iCBT interventions delivered as a fully automated, stand-alone intervention.Trial RegistrationClinicalTrials.gov NCT03244878; https://clinicaltrials.gov/ct2/show/NCT03244878

Community-based participatory research and decolonizing research share some recommendations for best practices for conducting research. One commonality is partnering on all stages of research; co-developing methods of data analysis is one stage with a deficit of partnering examples. We present a novel community-based and developed method for analyzing qualitative data within an Indigenous health study and explain incompatibilities of existing methods for our purposes and community needs. We describe how we explored available literature, received counsel from community Elders and experts in the field, and collaboratively developed a data analysis method consonant with community values. The method of analysis, in which interview/story remained intact, team members received story, made meaning through discussion, and generated a conceptual framework to inform intervention development, is detailed. We offer the development process and method as an example for researchers working with communities who want to keep stories intact during qualitative data analysis.