Tanvi Bahuguna, Jeffrey M. Lating, Ph.D., Sharon Green-Hennessy, Ph.D., Matthew W. Kirkhart, Ph.D.

Examining Psychological Distress & Resilience in Homeless Indian Youth

View the poster >>

Abstract:

This study seeks to explore the effects of homelessness among Indian youth by examining psychological distress and resilience in street and homeless adolescents residing in three shelters and a day-care center in Mumbai, India. It is hypothesized that psychological distress and resilience scores, as assessed by the Kessler Psychological Distress Scale-10 and Connor-Davidson Resilience Scale-10 respectively, will be significantly higher in the current sample than the normative mean scores. It is also hypothesized that psychological distress and resilience scores will be negatively correlated. Additional hypotheses include that psychological distress will be positively correlated with overall duration of homelessness, resilience will be negatively correlated with overall duration of homelessness, resilience will be positively correlated with the number of prosocial and supportive social supports, and for youth residing in shelters (not enrolled in the day-care center), psychological distress will be positively correlated with duration of shelter stay. Finally, it is hypothesized that social supports, resilience, duration of homelessness, and duration of shelter stay will independently predict psychological distress, while social supports, psychological distress, duration of homelessness, and duration of shelter stay will independently predict resilience.

The sample was comprised of 72 Indian adolescents between the ages of 12-17 years conveniently sampled from a local non-governmental organization (NGO), Salaam Baalak Trust. Participants completed a demographic questionnaire, a two-item social support questionnaire, the Kessler Psychological Distress Scale-10 (K-10), and the Connor Davidson Resilience Scale-10 (CD-RISC-10). The hypotheses will be tested using single-sample t-test, Pearson correlation, and by using multivariate, hierarchical multiple regression, and results will be analyzed in April 2022.