Do past and present adverse experiences impact the mental health of children? A study among children in the Juvenile Justice System in India
Bibliographic record
Abstract
Background: Children in the Juvenile Justice System (JJS) in India include children who may have engaged in criminal acts and children who cannot be cared for by their families of origin for various reasons. Given the nature of the children in such circumstances, they face multiple challenges growing up. Few studies from India have systematically explored interpersonal experiences, including adverse childhood experiences (ACEs) or bullying experiences, and their effects on these children's mental health. Materials and Methods: A cross-sectional study was conducted using standardized scales to identify the frequencies of and relationships between life experiences and current mental health outcomes (stress, well-being, and psychopathology) faced by children residing in seven child care institutions (CCIs) across two states in India. Results: Of the 278 children who participated in the study, at least one ACE was endorsed by 86.7%, and at least one instance of bullying was experienced by 71.7%. A significant negative correlation was noted between the number of ACEs, bullying experiences, and well-being and a significant positive correlation with stress and psychopathology. Information about the family of origin was significantly associated with lower psychopathology and stress scores. Conclusions: This study highlights the relationship between mental health outcomes, ACEs, and bullying experiences in children in the JJS in India. The study identifies the immediate and ongoing effects of these experiences on children's mental health and, thus, focuses on the need for appropriate interventions to allay the effects of these experiences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".