Qualitative Evaluation of Web-Based Digital Intervention to Prevent and Reduce Excessive Alcohol Use and Harm Among Young People Aged 14-15 Years: A “Think-Aloud” Study
Bibliographic record
Abstract
BACKGROUND: In the United Kingdom, despite some downward trends in alcohol use among young people, over one-fifth of young people reported excessive alcohol use in the past month, which is associated with short- and long-term harm to health. Digital interventions to reduce alcohol use, such as websites, among young people present an appealing and cost-effective mode of intervention that can be integrated into the education system. However, relatively few school-based digital alcohol-focused interventions have been developed and evaluated for young people in the United Kingdom. OBJECTIVE: This study aims to develop a novel web-based intervention, Rethink Alcohol, to prevent and reduce excessive alcohol use and related harm among young people aged between 14 and 15 years, and explore the views of young people, teachers, and youth workers in relation to the content, design, and usability of the intervention. METHODS: Intervention development followed the person-based approach, using theories of social norms and social influence. Qualitative "Think-Aloud" interviews, either one-to-one or paired, were conducted while participants perused and worked through the web-based intervention, talking aloud. Participants included 20 young people (12 female, 8 male), 5 youth workers (4 female, 1 male), 3 teachers (2 male, 1 female), and 1 (male) clinical professional, recruited via youth groups and professional networks. Interviews were audio recorded, transcribed verbatim, and analyzed thematically. RESULTS: The prototype web-based intervention included normative feedback, information, a quiz, interactive activities, and scenarios. On a rating scale of impressions from poor (1) to excellent (5), participants gave an average score of 3.6/5. A total of 5 themes were identified: content, credibility of the website, making the website easy to understand, design and navigation, and suitability for the audience. These themes reflected views that the content was interesting, credible, informative, and embodied a neutral and nonjudgmental tone, but stronger messaging was needed regarding social pressures and short-term risks regarding safety and risk behavior alongside clarity around pathways of risk; credibility and trustworthiness of information were critical features, determined in part, by the professionalism of design and referencing of sources of information provided; and messages should be succinct and come to life through design and interactive features. CONCLUSIONS: Together, the data illustrated the importance and challenge of communicating nuanced alcohol-focused public health messages to young people in concise, clear, nonjudgmental, and appealing ways. Young people report interest in clear, credible, neutral, and interactive messages regarding social pressures and short-term risks of alcohol use via a web-based intervention. There is scope for optimization and feasibility testing of the Rethink Alcohol intervention.
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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 | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".