Only one-third of adolescents access treatment for depression, and many fail to interact with clinic-based mental health resources. Sexual and gender minority youth (SGMY) are at greater risk for severe mental health disorders and suicidality but even less likely to access mental health services, even when access is available.
Widespread factors - stigma, negative beliefs about treatment, lack of mental health knowledge - contribute to not seeking services. Mainstream mental health interventions fail to address unique factors to SGMY that inhibit help-seeking: double stigma (stigma around mental health as well as internalized homophobia and transphobia), concern about revealing SGM status, low family support, lack of access to SGM affirming mental health professionals.
Despite being hard-to-reach, SGMY at risk for depression are quite active online. Yet SGMY-specific evidence-based online interventions are lacking and community interventions do not enhance mental health help-seeking. Targeted online interventions are needed to address unique factors which prevent help-seeking but are themselves usable and engaging. The current proposal will use a user-informed efficient approach to technology intervention design considering the heterogeneity and specific needs of SGMY. The investigators will use the Behavioral Intervention Technology Model to design and study several intervention principles (IPs), or theoretical concepts including intervention aims and behavioral strategies, to understand which mechanisms of action hold promise while being iterating design and potential modalities.
The investigators will use human computer interaction (HCI) framework, Discover, Design/Build, and Test to develop and study several IPs. Specifically, will use HCI techniques to develop initial prototypes and seek iterative user feedback and evaluate 4 finalized low-fidelity prototypes using a factorial trial to understand each IP prototype's individual and combined feasibility, usability, acceptability, and change in help-seeking intention in an online sample of diverse (racially, ethnically, age, gender identity, sexual orientation) SGMY.
This will inform the development of a high-fidelity intervention which may include different components for specific SGMY subgroups to be evaluated in a larger clinical trial. The PI, Dr. Radovic, is a physician researcher in adolescent medicine and has conducted years of research using stakeholder-informed methods and HCI techniques to inform intervention development. By working with experts in SGM health, stakeholder engagement, intervention design, qualitative analysis, HCI design, and BIT development and testing, the investigators have an exciting opportunity to bridge the gap for SGM adolescents with depression and suicidality to motivate and equip adolescents with the tools needed to access treatment.
This proposal is responsive to NOT-MH-18-031 by conducting nimble iterative testing and NOT-MD-19-001 - testing stigma reduction interventions. Adolescents who are sexual and gender minority (or LGBTQ) have rising rates of depression, anxiety, and suicidality but are less likely to get mental health treatment than other adolescents due to stigma and low family support. These adolescents are quite active online. This study aims to understand what types of technology interventions are most promising for helping them to seek mental health help when indicated.
Due to the exploratory nature of this clinical trial, we originally considered multiple secondary outcomes. As we proceeded with the study and obtained formative information from qualitative interviews to inform initial prototypes, we further clarified our conceptual model regarding our interests in the main outcome of mental health help-seeking and subsequent improvement in depression and anxiety symptoms. This help-seeking we hypothesized may be influenced by help-seeking intention, social support, internalized stigmatization of identity (internalized homophobia, internalized transphobia), confidentiality concerns, and expectations of rejection by mental healthcare providers. These measures therefore remained as secondary outcomes which we examined, and all others were moved to Other Pre-specified outcome measures.
With regards to statistical analysis, due to limitations in sample size, and non-normality of data, we used non-parametric tests of statistical significance within the primary outcome of mental health help-seeking intention between each intervention compared to not that intervention and adjusted for multiple tests using false-discovery rate q-value calculated with the Yekutieli method in Stata.
