The effect of a low intensity intervention on the wellbeing of children in the juvenile justice system in India: Results from a pilot study
Bibliographic record
Abstract
OBJECTIVE: Children in the Juvenile Justice System (JJS) face multiple adversities that may predispose them to developing mental health (MH) problems. Interventions that enhance the MH and well-being of these children while providing access to appropriate MH care are needed. This study examines the effect of a multipronged, low-intensity intervention on adolescents' well-being, stress levels, MH knowledge, and stigma perceptions in Childcare Institutions (CCIs) across Odisha and Tamil Nadu, India. METHODS: Implemented in 7 CCIs, the intervention aimed to enhance the MH Literacy (MHL) and well-being of children in the CCIs through the Youth-Friendly Spaces (YFS) using experiential methods. It also sought to improve the MHL of the staff and administration within the JJS and provide access to MH care by linking CCIs to available local resources. Information using validated scales was obtained at baseline and six months. RESULTS: Only 180 of the 310 children for whom baseline data was available remained in the CCI at six months. A statistically significant improvement in well-being (34.5 +13.7-55.9 +12.2, p < 0.001), stress (18.5 +6.8-17 +6.1, p = 0.044) and stigma (32 +11.9-29.4 +11.4, p = 0.023) scores were observed. Adjusted linear regression analysis showed significant differences across genders, sites, and child types. DISCUSSION: This intervention, comprising YFS creation, MHL enhancement, and referral system development, is significantly associated with improved well-being of children in CCIs. The results underscore the need for tailored interventions based on gender, location, and child type. The study highlights the potential scalability of such programs in resource-constrained settings for vulnerable children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".