Alcohol use among high school learners in rural areas of Limpopo province
Bibliographic record
Abstract
Background: Alcohol use is a serious public health concern among youth in South Africa and worldwide. Aim: To determine the factors contributing to alcohol use among high school learners in the rural areas of Limpopo province. Setting : The Greater Marble-Hall municipality, Sekhukhune district in Limpopo province. Method: A quantitative, cross-sectional study design was conducted on 314 learners from three high schools in a rural area in Limpopo. A stratified random sampling technique was used to select learners from 11 to 25 years of age. The drinking behaviour was classified according to predetermined Alcohol Use Disorders Identification Test (AUDIT). Data were analysed using SPSS Software v23.0. Results: More than half of the respondents were consuming alcohol 169 (53.8%). Also, 173 (55.1%) of respondents had parents who consume alcohol and 204 (65%) had friends who drank alcohol. Most respondents were classified as low-risk drinkers (AUDIT score < 8) and a quarter of the respondents were classified as almost dependent on alcohol (AUDIT score > 13). Significant associations were found between learners’ alcohol consumption and parents and friends who drank alcohol ( p = 0.000; p = 0.000, respectively). Conclusion: Alcohol use was prevalent among high school learners in the area under investigation. Also, learners who had parents and friends who consume alcohol were more likely to consume alcohol. Further, learners who were classified as almost dependent on alcohol needed urgent intervention as their health-related quality of life was likely to be poor.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".