Prevalence and correlates of psychological distress among 13–14 year old adolescent girls in North Karnataka, South India: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Mental health disorders among adolescents have emerged as a major public health issue in many low and middle-income countries, including India. There is a paucity of research on the determinants of psychological distress, particularly among the poorest girls in the poorest communities. The purpose of this study was to assess the prevalence and correlates of different indicators of psychological distress among 13-14 year old low caste girls in rural, south India. METHODS: Cross-sectional survey of 1191 low caste girls in two districts in north Karnataka, conducted as part of a cluster randomised-control trial. Bivariate and multivariate logistic regression analysis assessed correlates of different indicators of psychological distress. RESULTS: More than one third of girls (35.1%) reported having no hope for the future. 6.9% reported feeling down, depressed or hopeless in the past 2 weeks. 2.1% reported thinking they would be better off dead or of hurting themselves in some way in the past 2 weeks. 1.6% reported sexual abuse, 8.0% rrecent eve teasing and 6.3% having no parental emotional support. Suicidal ideation was independently associated with sexual abuse (AOR 11.9 (3.0-47.0)) and a lack of parental emotional support (AOR 0.2 (0.1-0.5)). Feeling down, depressed or hopeless was independently associated with recent eve-teasing (AOR 2.9 (1.6-5.4)), a harassing or abusive school environment (AOR 3.9 (1.8-8.2)), being frequently absent (AOR 2.8 (1.5-5.5)) or having dropped out of school (AOR 2.1 (1.0-4.3)), and living in Vijayapura district (AOR 2.5 (1.6-4.1)). Having no hope for the future was independently associated with a range of factors, including recent "eve-teasing" (AOR 1.5 (1.0-2.4)), being engaged (AOR 2.9 (0.9-9.7)), not participating in groups (AOR 0.5 (0.4-0.6)) and a lack of emotional support (AOR 0.6 (0.4-0.7)). CONCLUSIONS: Rather than being a time of optimism, a third of low caste girls in rural north, Karnataka have limited hope for the future, with some contemplating suicide. As well as having important development benefits, interventions that address the upstream structural and gender-norms based determinants of poor mental health, and provide adolescent services for girls who require treatment and support, should have important benefits for girls' psychological wellbeing. TRIAL REGISTRATION: Prospectively registered at ClinicalTrials.GovNCT01996241 . November 27, 2013.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".