Screening Adolescents for Risk Factors for Development of Non-Communicable Diseases
Bibliographic record
Abstract
This study was done to find the prevalence of risk factors for non-communicable diseases (NCDs) in school going adolescents. Secondary data analysis was done of the data collected for development of questionnaire for adolescents. The data was collected from the adolescents (10-19 years of age) attending OPD of Kalawati Saran Children’s Hosp[ital, New Delhi or attending schools. The data related to NCD risk factors were analyzed and is presented here. Total 672 adolescents were included in the study. Six questions were asked on risk factors for NCDs. Nearly 2/3 adolescents are not active enough physically, only half were having fruits and vegetables in diet 5 times a week, and about a quarter were genetically predisposed for NCDs. About 10% adolescents had thoughts of ending life in the previous month and nearly half of it made at least one attempt to end life. NCDs begin during adolescence and the risk factors can be identified early. This gives an opportunity to modify risk factors to avoid or delay the NCDs in adults.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".