Mental Health Status and Participation in an Economic Livelihoods Intervention: A case study of the SHAZ! Project for adolescent orphan girls in Zimbabwe
- Author(s): Kang Dufour, Mi-Suk Julie;
- Advisor(s): Padian, Nancy;
- et al.
It is widely recognized that poverty is a driver of adverse health. Thus, programs that address economic status as a means to improve health and wellbeing have garnered increasing attention in recent years. These interventions, sometimes referred to as "livelihoods opportunities" interventions, encompass a range of strategies to improve economic status and earning potential. Research has demonstrated positive impacts of economic interventions on reproductive outcomes, the health and wellbeing of children and reductions in violence. However, not all findings from these interventions are positive. There is also a lack of rigorous evaluation of the health outcomes for many economically based interventions.
Populations suffering social and economic disadvantage are often populations also suffering from increased mental health morbidity. Mental health issues such as depression, anxiety and lack of hope for the future may prevent these populations from participating fully in interventions and may reduce intervention effectiveness, unless mental health care is incorporated into the interventions. Conversely, it may be that opportunities made available through intervention programs can create a sense of hope and self efficacy and, thus, lead to improvement in mental health status overall.
This dissertation uses the Shaping the Health of Adolescents in Zimbabwe (SHAZ!) project as a case study of the role mental health plays in intervention participation and the impact of economic livelihoods interventions on mental health. For this case study, several analyses were undertaken. First the characteristics of the instrument used to measure mental health in this population were described. Secondly an estimation of the potential for intervention to affect mental health was conducted using population intervention models based on the baseline data. Finally the longitudinal data were explored using causal inference based methods to estimate average treatment effects for each component of the intervention on mental health status and for each measure of mental health status over time on intervention completion.
The Shona Symptom Questionnaire, which was used to measure symptoms of common mental disorders, was found to have reasonable measurement characteristics in this population. Potential for intervention to impact mental health was demonstrated in the population intervention models. Using these models for the baseline and screening data, self efficacy, social support and general health had the largest estimates of potential changes in population mental health.
In this case study, as hypothesized, poor mental health had a negative impact on intervention participation and conversely, the livelihoods intervention had a positive impact on mental health status. There was not enough support in the data from this small case study to estimate all the parameters of interest. However, statistically significant results showed an average treatment effect on mental health of over 20 percent for participation in the Red Cross component of the intervention. Being symptomatic for mental health distress at baseline was also significantly associated with a reduction in completion of the Red Cross component of training.
Applying novel methods to intervention evaluations allows a more nuanced understanding of multi-component interventions. These results suggest that incorporating mental health support, particularly at baseline may have important benefits in terms of intervention impacts in disadvantaged populations. As always further research is needed to confirm these findings, but the results of these dissertation analyses are an exciting first step in understanding these relationships and improving future work in this field.