Rise & Thrive: Community-Engagement Intervention for Stress and Depression in Youth.

Allostatic Load, Depressive Symptoms, Metabolic Syndrome

mental health, youth intervention, allostatic load, stress, depressive symptoms, depression, metabolic syndrome, prevention

American youth and young adults face persistent and chronic stressors, which have contributed to a mental health crisis in the United States. Four in 10 American high school students experience chronic feelings of sadness and hopelessness, 2 in 10 report suicidal ideation, and 1 in 10 attempt suicide. For adolescents and young adults, chronic stress translates to weathering, or wear and tear on the mind and body. Chronic stress in youth contributes to psychological distress, elevated allostatic load, and an elevated risk for chronic diseases and premature death. While the connection between chronic stress and health is well documented, few studies provide evidence on innovative, non-medication strategies to reduce stress and mitigate the consequences of chronic stress on psychological and physiological outcomes. Thus, there is a critical need to rigorously test interventions that prevent the negative influence of chronic stress on mental and physical health, beginning in adolescence. The specific aims of the study are to 1) Determine whether a community-engagement, peer-based behavioral intervention reduces depressive symptoms in adolescents and young adults, 2) Determine whether a community-engagement behavioral intervention lowers allostatic load scores in adolescents and young adults, and 3) Identify factors that help sustain or inhibit community-engagement and intervention effects for adolescents and young adults. To accomplish these aims, the team will conduct a phase II community-engaged, peer group-based, multi-component randomized behavioral clinical trial. We will collect psychological and physiological measures at baseline, then at 6-month intervals for 2 years post-community-engaged, skills training.

Detailed Description: The investigators will conduct a phase II group-based, multi-component, and multi-level randomized behavioral clinical trial. The investigators will recruit and enroll 300 participants aged 15-20 (N=150 intervention and N=150 control) in Chicago, Illinois. After enrollment, participants will be randomized using a block-stratified randomization technique to ensure balance regarding race, ethnicity, and gender. Once participants are recruited, the investigators will use a computer-generated random number sequence to assign participants to the intervention group (Rise Community Engagement) or control group (Adulting 101: Life Skills Training). Participants assigned to the intervention arm will participate in 5 half-day, peer-based, interactive sessions teaching community engagement principles. Participants will be assigned to the control arm and will participate in 5 half-day interactive sessions teaching life skills training. Participants in the control arm will undergo life skills training with the same number of sessions and duration as the intervention arm. Participants in both the intervention and control arms will report depressive symptoms on a clinically relevant measure (e.g., Patient Health Questionnaire-9) at baseline and then \<1-, 6-, 12-, 18-, and 24- months post-initial 5-day community engagement or life skills training. In addition to depressive symptoms, the investigators will measure other aspects of psychological distress, including anxiety and stress, as secondary outcomes. Participants in both groups will have biometric samples, like blood draws, and clinical measurements of allostatic load at baseline and then 6-,12-, and 24- months post-initial 5-day community engagement or life skills training. The proposed project will use a cluster randomized trial, which involves complete groups of individuals randomized to conditions (i.e., intervention, control), with clustering occurring in both arms. All of our statistical analyses will appropriately model the dependency among observations, which is a hallmark of multi-level modeling.

No related papers found yet.