Personalization Strategies for Increasing Engagement With Digital Mental Health Resources: Sequential Multiple Assignment Randomized Trial.

Background: Although web-based mental health resources have the potential to assist millions, particularly those who face barriers to treatment, most mental health website visitors disengage before accessing resources that can help improve their mental health. Objective: We used a sequential multiple assignment randomized trial to test whether personalized tailoring improved engagement on a self-guided mental health website. Methods: Data were collected via voluntary response sampling on the Mental Health America website. Inclusion criteria included residing in the United States and viewing a postscreening survey after completing the Patient Health Questionnaire-9 (PHQ-9). Participants were randomized to 1 of 2 postscreening survey conditions: the demographics survey or the Next Steps survey, which included additional tailoring questions assessing perceived need and participants' intended next steps. Participants who viewed the following screening results page were subsequently randomized to 1 of 5 conditions that displayed nontailored or tailored messages and featured resources, as well as persistent general resources that did not vary by condition. Data were analyzed using logistic regressions predicting disengagement and clicks on featured resources (versus persistent general resources) by condition. Results: Adding questions to inform tailoring significantly increased the odds of disengaging by 14% (demographics survey: 25%; Next Steps survey: 27.5%; odds ratio [OR] 1.14, 95% CI 1.11-1.16; P<.001). Among participants who viewed a postscreening survey (n=169,647), 87,712 participants were randomized to the demographics survey condition, and 81,935 participants were randomized to the Next Steps survey condition. Among participants who submitted the demographics survey (n=38,490), tailoring resources to demographics reduced the odds of disengaging by 10% (OR 0.90, 95% CI 0.87-0.94; P<.001) and, among those who engaged, increased the odds of clicking a featured resource versus a persistent general resource by 90% (OR 1.90, 95% CI 1.79-2.01; P<.001). Among participants who submitted the Next Steps survey (n=34,204), tailoring messages to perceived need (P=.33), tailoring resources to intended next steps (P=.51), and a combination of both (P=.52) did not significantly reduce the odds of disengaging compared with the nontailored condition. However, tailoring resources to intended next steps and combining a tailored message to perceived need with tailored resources to intended next steps increased the odds of clicking a featured resource by 25% (OR 1.25, 95% CI 1.14-1.37; P<.001) and 34% (OR 1.34, 95% CI 1.23-1.47; P<.001), respectively. Tailoring resources to demographics was significantly more effective in improving engagement than tailoring to perceived need or intended next steps (P≤.004). Conclusions: There was a small but statistically significant cost to engagement from adding tailoring questions assessing perceived need and intended next steps. Among the strategies tested in this study, tailoring resources to demographics was the most effective strategy for increasing engagement among visitors who viewed their screening results. This study demonstrates how personalization may increase engagement with mental health websites and provides design implications for future research.