Prevalence and correlates of addictive behaviours among adolescents in Chandigarh, North India
Bibliographic record
Abstract
Objective The objective of the present study was to determine the prevalence of addictive behaviors among in-school and out-of-school adolescents of age 13–19 years in Chandigarh, India.Methods Problem Behavior Theory (PBT) was used to identify the risk and protective factors for addictive problem behaviors among adolescents.Results A total of 1634 adolescents were included from in-school (n = 1134) and out-of-school (n = 500) categories. The prevalence of addictive behaviors was 19.1% (current smoking 6%, alcohol drinking 6.1%, and drug use 7%) among adolescents aged 13 to 19. Significant predictors of smoking were being male (aOR = 4.43; 95%CI: 1.92,10.20; p < .001) and having a working father (aOR = 3.19; 95%CI: 1.10, 9.20; p < .05). Total protective score [smoking: aOR = 0.99; 95% CI:0.97, 0.99: p < .05; alcohol use: aOR:0.98;95% CI:0.97,0.99; p < .01; drug use: OR:0.99, 95%CI: 0.98,0.99; p < .05] and total risk score [smoking: aOR = 1.14; 95%CI:1.11, 1.17: p < .001; alcohol use: aOR:1.10;95% CI:1.07,1.12; p < .001; drug use: aOR:1.05, 95%CI: 1.04,1.06 p < .001] were significantly associated with all three addictive behaviors.Conclusions The current study’s findings can inform the development of intervention programs focusing on both adolescents and communities (social environment surrounding adolescents) to enhance the protection of adolescents at risk for addictive behaviors.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".