The burden of mental health problems in low- and middle-income countries (LMIC) is substantial. Although the burden associated with these problems is high, the gap between those who suffer from them and those who receive any sort of evidence-based treatment is large. Among the factors associated with this treatment gap in LMIC is the scarcity of trained mental health professionals, leading to the growing movement advocating use of non-specialists in task-sharing models to provide evidence-based treatments. Despite the growing number of rigorous studies showing promising effects of psychotherapeutic interventions provided through task-sharing strategies by non-specialist mental health providers, a gap exists in our knowledge as to modifying factors and demographic characteristics that influence the magnitude of these intervention impacts because the intervention trials have not been powered to examine effects by sub-groups providing little information about which treatments work best for which participants. Study Methods: The proposed study will evaluate the modifying effects of individual, symptom specific and contextual factors on the utilization and impacts of psychotherapy provided by non-specialist providers using data from six randomized controlled trials in LMIC across 4 continents. This synthesis will use integrative data analysis of pooled data (i.e., combining and analyzing individual-level data across numerous studies using coordinated coding and analysis methods that maximize precision of comparisons).
The Specific Aims i nclude Aim 1: building a consolidated database of respondents from the trials which have a combined baseline sample of n=1611. And the following aims which look at different factors that may predict differential utilization and impacts of psychotherapy provided by non-specialist providers:
Aim 2 : Identify individual factors such as sex, age, education, marital status, and trauma exposure;
Aim 3 : Identify factors related to symptoms, disorders, and impairment such as symptom severity, and increased impairment;
Aim 4 : Identify contextual and treatment factors such as degree of insecurity, provider training, provider sex and specific therapy used; and a Secondary Aim: Explore the role of symptom comorbidity. Furthering our understanding of predictors of treatment success, which includes treatment completion, reduced symptomatology, and improved functioning, will identify further adaptations of training and treatment protocols to meet the needs of a wider range of populations in LMIC than is currently able to be treated, an important step for disseminating and scaling up promising treatments, improving the mental health of the population in the LMICs, and reducing the Global Burden of Disease.

Public Health Relevance

Although the burden of mental health problems in low- and middle-income countries (LMIC) is substantial the gap between those who suffer from them and those who receive any sort of evidence-based treatment is large requiring the use of non-specialists in task-sharing models to provide evidence-based treatments. Despite the growing number of studies showing promising effects of interventions provided by non-specialist mental health providers, a gap exists in our knowledge as to modifying factors and demographic characteristics that influence the magnitude of these intervention impacts. Identifying predictors of treatment success will allow for adaptations of training and treatment protocols to meet the needs of a wider range of populations in LMIC than is currently able to be treated.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH105450-03
Application #
9312316
Study Section
Mental Health Services Research Committee (SERV)
Program Officer
Williams, Makeda J
Project Start
2015-09-01
Project End
2019-06-30
Budget Start
2017-07-01
Budget End
2019-06-30
Support Year
3
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Other Health Professions
Type
Schools of Public Health
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205