Mental Health Problems Among Indonesian Adolescents: Findings of a Cross-Sectional Study Utilizing Validated Scales and Innovative Sampling Methods

Abstract

Purpose

This study aimed to estimate the prevalence of mental health problems and identify potential risk and protective exposures for adolescents in Indonesia.

Methods

An innovative sampling approach was applied to simultaneously recruit school- and community-based adolescents aged 16–18 years old from Jakarta (urban megacity) and South Sulawesi (remote province). We used multistage cluster sampling for in-school (N = 1,337) and respondent driven sampling for out-of-school (N = 824) adolescents. Mental health was measured using two validated scales: Kessler-10 and Center for Epidemiologic Studies Depression Scale-Revised. Psychiatric interviews were conducted in a subsample (N = 196) of students from Jakarta to validate the self-report scales.

Results

The estimated population prevalence of psychological distress and depression were 24.3% (95% CI = 21.5–27.2) and 12.6% (10.5–14.4) for in-school and 23.7% (20.7–26.7) and 23.5% (20.4–26.5) for out-of-school adolescents, respectively. In participants who completed a psychiatric interview, common psychiatric morbidities were social anxiety, depression, and suicidality. Compared to in-school females, male in-school adolescents reported a lower prevalence of psychological distress (16.9% (13.1–20.7) vs. 30.4% (26.4–34.4)) and depression (10.1% (7.2–13.1) vs. 14.6 (11.4–17.8)). By contrast, for out-of-school adolescents, males reported a higher prevalence of psychological distress (25.2% (21.6–28.9) vs. 20.2% (15.1–25.3)) and depression (26.3% (22.5–30.1) vs. 16.9% (11.8–21.9)). In-school adolescents who did not seek healthcare despite a perceived need were more likely to report psychological distress and depression.

Discussion

Adolescent mental health problems are highly prevalent in Indonesia, with substantial variation by gender, geography, and school enrolment. This study and its approach to sampling and measurement may serve as a model to improving mental health surveillance across other settings.