Improving adoption of mental health interventions among low-income university students in Brazil
Lead Research Organisation:
London School of Economics and Political Science
Department Name: Care Policy and Evaluation Centre
Abstract
Mental health conditions are the leading cause of disability among youth worldwide. These problems are more common among youth living in poverty. Mental health problems can have short- and long-term impacts on physical and mental health, education, employment and relationships. University students living in poverty have high rates of mental health problems and limited support. These students face strong pressures to perform and succeed and to support their families. These pressures also emerge during a life stage where there is greater potential to engage in risky behaviour, and increased pressure for academic achievement - which can further increase risk of mental health problems.
Effective support for vulnerable students could improve their mental health and future life chances. Most youth, however, receive no care or support. In Brazil, around 80% of youth with mental health conditions receive no care and fewer receive evidence-based treatment. Although there is a great deal of evidence for effectiveness of psychotherapy (such as cognitive behavioural therapy [CBT]) for preventing and treating youth mental health problems, lack of services and trained providers significantly limits access. Moreover, barriers such as transportation, cost and stigma further limit access. These barriers are greater for poor vs. non-poor youth. Use of digital interventions could improve access to care. They are lower cost and could reduce stress on health systems and reach more users. They could also address stigma given they are more private. However, many digital interventions fail to engage users and sustain involvement. This limits their potential to improve the user's mental health.
This research would test whether combining a digital mental health intervention with peer support and/or a conditional cash transfer (CCT) (i.e., monetary incentive conditional on intervention participation) could increase participation and engagement among low-income university students. Research suggests CCTs can increase healthy behaviours and promote engagement by enabling students to purchase books and food, thereby avoiding food insecurity, reducing financial stress to enable focus on intervention, and reduce shame. Other research shows peer support can reduce stigma and increase participation particularly among vulnerable populations.
First, we would adapt and pilot a digital mental health intervention (e-CBT), shown to be effective among university students, in combination with CCT and/or peer support in collaboration with low-income university students. Following refinement, we would see whether combining the e-CBT with: (1) CCT; (2) peer support or (3) CCT+peer support improves participation and engagement. We would use innovative methods to explore longer-term social and economic impacts of the intervention in combination with CCT and peer support.
Effective support for vulnerable students could improve their mental health and future life chances. Most youth, however, receive no care or support. In Brazil, around 80% of youth with mental health conditions receive no care and fewer receive evidence-based treatment. Although there is a great deal of evidence for effectiveness of psychotherapy (such as cognitive behavioural therapy [CBT]) for preventing and treating youth mental health problems, lack of services and trained providers significantly limits access. Moreover, barriers such as transportation, cost and stigma further limit access. These barriers are greater for poor vs. non-poor youth. Use of digital interventions could improve access to care. They are lower cost and could reduce stress on health systems and reach more users. They could also address stigma given they are more private. However, many digital interventions fail to engage users and sustain involvement. This limits their potential to improve the user's mental health.
This research would test whether combining a digital mental health intervention with peer support and/or a conditional cash transfer (CCT) (i.e., monetary incentive conditional on intervention participation) could increase participation and engagement among low-income university students. Research suggests CCTs can increase healthy behaviours and promote engagement by enabling students to purchase books and food, thereby avoiding food insecurity, reducing financial stress to enable focus on intervention, and reduce shame. Other research shows peer support can reduce stigma and increase participation particularly among vulnerable populations.
First, we would adapt and pilot a digital mental health intervention (e-CBT), shown to be effective among university students, in combination with CCT and/or peer support in collaboration with low-income university students. Following refinement, we would see whether combining the e-CBT with: (1) CCT; (2) peer support or (3) CCT+peer support improves participation and engagement. We would use innovative methods to explore longer-term social and economic impacts of the intervention in combination with CCT and peer support.
Technical Summary
This project would test two implementation strategies for increasing adoption of an existing evidence-based digital mental health intervention (e-CBT) among low-income university students in Brazil. Digital interventions can increase access to care in a scalable and low cost way and reduce burden on health systems; however, a key limitation is their ability to engage users over a sustained period. We hypothesise that combining the digital intervention with: i) a conditional cash transfer (CCT) intervention and (ii) peer support would facilitate implementation outcomes.
Methods
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 different intervention implementation strategies relative to e-CBT 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.
Methods
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 different intervention implementation strategies relative to e-CBT 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.
