Nurses' role in managing alcohol misuse among adolescents
Bibliographic record
Abstract
Over the past decade, there has been an increase in the amount of alcohol consumed by young people, aged 11-17 years, in the UK and Ireland, which has implications for all health professionals caring for adolescents. Alcohol misuse is increasingly common among adolescents and is a significant concern for families, communities and society. Health professionals need to be aware of the dangers involved with underage drinking, how to recognise the signs of alcohol misuse, and how to intervene appropriately. Over the past few years, there has been a noticeable increase in the number of adolescents presenting to emergency departments (EDs) owing to alcohol-related injuries. This increase means that all nurses and other health professionals are suitably placed to provide education and support to adolescents who are consuming excessive alcohol. Regular alcohol misuse can lead to adverse health outcomes, and therefore nurses need to take an active role in health promotion to ensure that adolescents are aware of the associated dangers. This article summarises the harmful effects of underage drinking, the influencing factors and outlines the current guidelines on alcohol misuse in young people. It discusses strategies that nurses can use in the ED setting, and all healthcare settings, to motivate adolescents to change health-damaging behaviours.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| 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".