Adapting the personality‐targeted<i><scp>P</scp>reventure</i>program to prevent substance use and associated harms among high‐risk<scp>A</scp>ustralian adolescents
Bibliographic record
Abstract
AIM: Substance use among adolescents is of significant concern and the need for preventive interventions is clear. Although universal prevention programs have shown to reduce substance use among Australian adolescents, no effective selective program has been developed for high-risk youth in Australia. Preventure is a personality-targeted intervention that has shown to be effective in the UK and Canada and is yet to be trialled in Australia. Before doing so, it is necessary to ensure the content is relevant for the Australian setting. This study reports data collected to update and adapt the UK-based Preventure program for use in Australia. METHODS: Eight focus groups were conducted with 69 students from three secondary schools in Sydney, Australia. Students who screened high risk for early-onset substance misuse were invited to participate in focus groups specific to their personality profile and provide feedback. Written feedback was also obtained from 12 teachers and health professionals. RESULTS: Students, teachers and experts recommended specific changes to the content, language, scenarios and graphics of the Preventure manuals. The majority of teachers and experts believed that the educational content of the program was appropriate for students and that it would be effective in reducing substance use in this population. CONCLUSIONS: The information obtained in the current study was used to update the Preventure program for use with Australian adolescents. It is expected that this modified Preventure program will demonstrate similar effects in reducing alcohol and drug use among high-risk youth in Australia, as it did in the UK and Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".