Improving adoption of mental health interventions among low-income university students in Brazil by combining a tailored e-mental health intervention with a conditional cash transfer and peer support

Background

Mental health conditions are the leading cause of disability among youth worldwide and are disproportionately experienced by those living in poverty. Although there is a great deal of evidence that cognitive behavioural therapy (CBT) is effective for indicated prevention and treatment of youth mental health problems, only a minority of Brazilian youth with mental health conditions receive any care or support. Moreover, although poverty is strongly associated with mental health, youth living in poverty face greater barriers to care compared to those who are non-poor.

University students living in poverty face particular challenges given so many come from families where neither parent attended university and where pressures on the students are great to help elevate the socio-economic positions of their entire families. These pressures also emerge during a life stage where there is greater potential to engage in risky behaviours and increased pressure for academic achievement –all of which can further increase the risk of mental health problems.

Aims

To test whether adoption and engagement of a digital CBT-focused intervention could be increased among low-income university students in Brazil by delivering it via a (i) conditional cash transfer (CCT) intervention, (ii) integrated peer support model or (iii) both. Implementation outcomes will be compared using an effectiveness-implementation hybrid type 3 trial design.

Project plan

First, we will adapt an existing evidence-based digital group based CBT intervention and associated implementation strategies (CCT and / or peer support) for use with low-income university students in Brazil. To ensure implementation strategies are maximally congruent to culture and context, we will utilise the “what matters most” approach to optimise these implementation strategies’ impacts upon implementation outcomes by focusing adaptation of implementation strategies to what is “most valued” by low-income university students.

Following adaptation, we will undertake a four-arm cluster effectiveness-implementation hybrid type 3 RCT among 1958 low-income students (4 arms/cluster). Participants will be randomised to: 1) digital mental health intervention only, 2) e-CBT+CCT, 3) e-CBT+peer support, or 4) e-CBT+CCT+peer support.

We would then model potential mid to longer term mental health and associated social and economic impacts resulting from the three different intervention implementation strategies relative to the e-CBT intervention only. We would construct decision analytic models to estimate potential economic costs and benefits from increasing adoption/engagement and reducing mental health problems relative to costs of intervention implementation from a societal perspective.

Funding organisations

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