Evaluation of cognitive and behavioral effects of personality-based substance use prevention in Canada
Bibliographic record
Abstract
This study evaluated the effectiveness of the Preventure program with students in a medium sized school district in Western Canada.Preventure is a selective prevention program that screens students on four distinct personality types: sensation-seeking (SS), anxiety sensitivity (AS), negative thinking (NT), and impulsivity IMP).Each of these traits is linked to both the risk of early substance use and subsequent onset of mental health concerns.The tested program tailors a brief intervention to reduce cognitive and behavioral risks in higher risk students based on their personality.Method: At the start of the study, 576 grade eight students were screened using the Substance Use Risk Profile scale (SURPS) to assess the four personality traits.Of these students, 268 students (46.2%) exceed risk criteria on one or more of the personality types.For the evaluation, two of the four schools were randomly assigned to receive training immediately (Trained Schools) with the other two schools receiving delayed implementation the following year (Untrained Schools).In the two training schools, 94 students were invited to participate in Preventure training groups with 44 students completing the training.During the following year, all students took part in three health surveys that included questions about substance use and measures of their substance use cognitions (i.e., expectancies and memory associations).Results: The substance use measures were analyzed over three time points using zero-inflated negative binomial tests.Students who received Preventure training or who attended schools that had the training were significantly less likely to begin using tobacco, vapes, cannabis, and illicit drugs and used cannabis less frequently than those in Untrained Schools.Cannabis cognitive associations were also lower in Trained Schools and fully mediated differences in Trained versus Untrained schools.Past year alcohol use and initiation of alcohol use were unaffected.Conclusions: These findings support other international findings for the efficacy of Preventure in reducing substance use in teens.Cognitive mediation analysis suggests that reductions in risky associations partially mediate positive treatment effects on Cannabis use.This finding is the first to reveal one possible cognitive mechanism for the effects of Preventure.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".