A health profile of New Zealand youth who attend secondary school.
Bibliographic record
Abstract
AIM: To determine the prevalence of selected health behaviours and protective factors in a representative population of New Zealand youth who attend secondary school. METHODS: The study sample comprised 12 934 Year 9 to 13 youth from 133 randomly selected secondary schools across New Zealand in 2001. A cross-sectional, anonymous, self-report survey was conducted, incorporating 523 questions in a multimedia computer assisted self-interview (M-CASI) format. RESULTS: The school response rate was 85.7% and the student response rate was 75.0%, resulting in an overall response rate of 64.3%. The final dataset comprised 9570 students (males 46.2%, females 53.8%) belonging to diverse ethnic groups (Maori 24.7%, NZ European 55.3%, Pacific 8.2%, and Asian 7.2%). Most students (males 94.2%, females 90.3%) rate their health as good or better, and 90% report the presence of a caring adult in their family or at school. More than one quarter of students (males 27.2%, females 27.6%) report riding in a car driven by a potentially intoxicated driver within the last four weeks. Students report high levels of suicidal thoughts (males 16.9%, females 29.2%), suicide attempts (males 4.7%, females 10.6%), and depressive symptoms (males 8.9%, females 18.3%). CONCLUSIONS: This survey finds that most school students are healthy, but there are areas of serious concern including driving behaviours and mental health. Students report a high prevalence of positive connections with family and school; these connections are known sources of resiliency in the lives of young people. Findings of the current study support the implementation of the New Zealand Government's newly released youth policies: the Youth Development Strategy Aotearoa and the Youth Health Action Plan.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".