Access point analysis: what do adolescents in South Africa say about tobacco control programmes?
Bibliographic record
Abstract
This paper explores adolescent preferences for the setting, timing, delivery format, provider and key elements of tobacco control programmes. The need for programme sensitivity towards urban/rural, gender and ethnic subgroups is also discussed. Schools were purposively selected from the Southern Cape-Karoo Region, South Africa. Twelve prevention and nine cessation focus group discussions were conducted with Grade 6-8 students and Grade 8-9 smokers and ex-smokers, respectively. Adolescents reported similar preferences for prevention and cessation programmes. Although they were unaware of smoking prevention or cessation programmes, they reported a willingness to participate in such programmes. Programmes should include school-based activities that are supported by out-of-school activities held over weekends and holidays. Non-judgemental and empathetic teachers and peers, as well as ex-smokers were preferred as programme providers. School-based participatory delivery formats should be supported by community-based mass media approaches. Programmes can be jointly presented to boys and girls of diverse ethnic backgrounds with some gender-sensitive sessions. Programme participation and sustainability would be enhanced if it were exciting, fun filled and integrated into their daily lives. School-based programmes must be embedded within comprehensive approaches that involve community- and policy-level interventions.
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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 | 0.004 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".