Screening and Treatment for Anxiety & Depression (S.T.A.N.D): Alacrity Center Signature Project on Triaging and Adapting to Level of Care

Brief Summary

Detailed Description

Community colleges provide a critical pathway for workforce development and socio-economic gain, but this opportunity is mitigated by unmet need for mental health services, particularly for depression and anxiety, and particularly for racial/ethnic minority students. A scalable and effective system of care that manages mental health needs in concert with social mental health determinants is sorely needed. The Alacrity Center aims to implement the STAND system of care, which screens and treats anxiety and depression, for a highly diverse community college population. STAND triages to various level of care, ranging from self-guided online prevention, to coach-guided online cognitive behavioral therapy (CBT), to clinician-delivered care. After initial triaging, STAND makes adaptations to level of care throughout the entire time of study enrollment (e.g., moved up to a higher level of care during acute treatment). These triaging and adaptation decisions currently are based on current symptom severity. Such decisions can be optimized by comprehensive data-driven algorithms that predict the need for a particular level of care and for adaptation to level of care throughout treatment, and especially algorithms that are suited to the needs of underserved community college students who face substantial life stressors. The overarching aim of the Signature Project is to evaluate clinical decision-making algorithms for (a) triaging to level of care and (b) adapting level of care in a low income, highly diverse sample of community college students at East Los Angeles College (ELAC). The end goal is to improve the effectiveness of STAND and to advance the science of personalized mental health. To do this, we will compare the standard approach that relies solely upon symptom severity to a data-driven approach to decision making that uses multivariate predictive algorithms comprised of baseline static and time-varying features from four overlapping and mutually reinforcing theoretical constructs: (1) social determinants of mental health (employment, income, housing \& food security, discrimination, social support, race/ethnicity, acculturation, immigration status, gender, sexual orientation); (2) early adversity and life stressors; (3) predisposing, enabling and need influences upon health services use; and (4) comprehensive mental health status (depression, anxiety and suicide severity, comorbidities, neurocognitive functioning, emotion dysregulation, regulatory strategy use, treatment history and preferences, social, occupational, home and academic functioning). The overarching design is to randomize ELAC students to either symptom severity decision-making (SSD) or data-driven decision-making (DDD), and evaluate whether DDD improves adherence to treatment, symptoms, and functioning. Other aims of this project are to (a) identify distal and proximal risk factors for suicide and self-harm and (b) examine effects of the decision-making condition (SSD, DDD) on suicidality and self-harm outcomes. Participants will be enrolled through recruitment efforts at ELAC. The target enrollment is 200 participants per year over five years (n = 1000 total). Participants are current ELAC student between the ages of 18-40. Predictors and outcomes will be assessed at baseline and either weekly or every 8 weeks until week 40. Multivariate prediction models will be used for initial level of care triaging and later adaptations of level of care based on a comprehensive set of variables that have been shown to drive current mental health needs. Participants will complete computerized assessments and self-report questionnaires. The total length of participation is 40 weeks. Embedded components: Component 1 to evaluate interventions aimed at improving STAND uptake: In October 2025 an embedded randomized component was launched within this parent trial to evaluate approaches for improving initial uptake and engagement with STAND at ELAC. Participants consented to the parent trial are additionally randomized 1:1:1 to receive one of 3 engagement intervention conditions: either 1) fotonovela 2) peer-led engagement navigator 3) enrollment as usual. There is no separate consent process nor additional eligibility criteria for this embedded component. Only participants consented to the Signature project are enrolled in this additional component. Component 2 to evaluate evaluate a technology-enhanced suicide prevention intervention (TE-SPI): In July 2025 the project launched an embedded RCT to evaluate a technology-enhanced suicide prevention intervention (TE-SPI) that includes treatment components with demonstrated benefits in prior research (safety planning, BRITE app, caring contacts to support safety plan use, hope, and reasons for living) and leverages mobile technology to deliver just-in-time adaptive interventions when intervention is most needed. Using Tier II and Tier III participants consented to the Signature Project, which include students for whom additional intervention for SU/SH risk is indicated, this work will use a rapid prototyping and testing model to develop and test an adaptation of the existing BRITE app plus safety planning for the primarily Latinx ELAC population. We are randomizing consented Tier II and Tier III assigned Signature Project participants to evaluate 1) TE-SPI with STAND usual risk management protocol (URM) compared to 2) STAND URM alone. We hypothesize that TE-SPI will a) lead to increased treatment engagement/contacts (i.e. app, STAND); b) demonstrate safety as indicated by low levels of self-harm related adverse events (e.g. hospitalizations, ED visits); c) be associated with fewer SU/SH events and greater improvement in suicidality, compared to URM; and d) that intervention engagement/dose received will lead to reduced SU/SH behavior.

Primary Outcomes

Secondary Outcomes

• Longitudinal trajectory of substance use(Up to 40 weeks)
• Language(Baseline)
• Major discrimination experiences(Baseline)
• Longitudinal trajectory of employment status(Up to 40 weeks)
• Early adversity(Baseline)
• Perceived need(Baseline)
• Acculturative Stress(Baseline)
• Longitudinal trajectory of housing/food security and financial stress(Up to 40 weeks)
• Longitudinal trajectory of perceived life stress(Up to 40 weeks)
• Insurance status(Baseline)
• Visuospatial information processing(Baseline)
• Demographic background(Baseline)
• Longitudinal trajectory of social support(Up to 40 weeks)
• Life stress exposure(Baseline)
• Beliefs about mental health treatment and stigma(Baseline)
• Willingness to pay(Baseline)
• Longitudinal trajectory of sleep quality(Up to 40 weeks)
• Other medical conditions(Baseline)
• Mental health treatment preference(Baseline)
• Longitudinal trajectory of daily discrimination experiences(Up to 40 weeks)
• Other mental conditions(Baseline)
• Emotion dysregulation(Baseline)
• Cognitive response(Baseline)
• Selective attention(Baseline)
• Abstract reasoning(Baseline)
• Socioemotional information processing(Baseline)
• Verbal ability(Baseline)
• Processing speed(Baseline)
• Mental health treatment history(Baseline)
• Longitudinal trajectory of regulatory strategy use(Up to 40 weeks)