Traduction française, adaptation culturelle et évaluation des propriétés psychométriques préliminaires de l’échelle des stratégies de protection comportementale liées à la consommation de cannabis
Bibliographic record
Abstract
OBJECTIVE: Young adults (18- to 24-year-olds) constitute the age group with the highest proportion of cannabis users. In the context of legalization, it is important to promote lower-risk cannabis use. The Protective Behavioral Strategies for Marijuana Scale (PBSM-17) identifies strategies used by consumers. However, this scale is not available in French and is not adapted to the Canadian context. This article presents the process that led to the translation, cultural adaptation and evaluation of the preliminary psychometric properties of PBSM-17. METHOD: The methodological study was carried out in six steps. The first four steps led to the translation towards French and adaptation of the scale. A validation among 12 young people contributed to establish the criterion equivalency (step 5). The evaluation of psychometric properties (step 6) was carried out among 211 bilingual university students (61 % women; mean age 22 years old). RESULTS: The French version presents satisfactory preliminary psychometric properties: internal consistency is acceptable (α = 0.88); criterion equivalency was established between the French and the original English version (t (210) = 1.04, p = 0.30; 95% CI [-0.20, 0.63]). The scores obtained on both versions by the same participant were found to be strongly correlated (r = 0.95, p <0.001). CONCLUSION: The results support the use of the French version of PBSM-17. The proposed protective strategies can be used as a measurement tool and represent behaviors that can be targeted in a lower-risk cannabis use context.
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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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".