World Mental Health Day 2023: Increasing awareness of mental health in India & exciting opportunities for the future
Bibliographic record
Abstract
Background & objectives: In Himachal Pradesh (HP), a comprehensive health survey was conducted to assess the prevalent health affecting habits and issues among young individuals aged 10 to 24 yr. The study was aimed to evaluate key factors such as nutrition, substance use (including tobacco and alcohol), mental health concerns such as anxiety and depression, sexual behaviours and personal hygiene, as well as incidents of violence and injury (including road traffic and other injuries). Methods: A cross-sectional survey was conducted in HP on 2895 individuals aged between 10 and 24 yr. The survey encompassed four districts, namely Shimla, Kinnaur, Kangra, and Sirmaur, and 12 blocks (three in each district). To ensure a representative sample, a stratified multistage cluster sampling approach was used. Districts and blocks were selected purposively so as to represent the diverse sociodemographic and cultural characteristics of this region. Within each block, thirty clusters were chosen using a probability proportional to size method. Clusters were defined as villages in rural areas and wards in urban areas. The World Health Organization 30 × 7 cluster technique was employed to identify households and individuals for the study. Results: Underweight (44.39%), risk of cell phone addiction (19.62%), feeling anxious (15.54%), unintentional injuries (14.72%) and violence (8.19%) were the top five health impacting problems among young people in HP. Interpretation & conclusions: The leading health impacting problems identified are preventable and/or modifiable factors affecting the overall health and development of young people in HP. These need to be addressed as priority health problems for interventions with a focus on maintaining positive health through integrated approaches including care provision, risk reduction and health promotion related to these health impacting behaviours. Such interventions are likely to yield better results towards the overall health and development of young people in HP.
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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 | 0.016 | 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 | 0.000 | 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".