A mixed-methods evaluation of the Tobacco RetailerAdvanced Compliance (TRAC) online training (e-learning)program
Bibliographic record
Abstract
INTRODUCTION: Tobacco vendor training is recognized as an essential element to reduce youth access to tobacco. The TRAC training program was developed utilizing best-practices in tobacco retailer training, adult instruction, and e-learning. The objective of this mixed-methods study is to evaluate the acceptability, usability and knowledge impact of an online tobacco retailer program. METHODS: An interview guide and evaluation questionnaire were used to collect data on usability and acceptability. To test learner knowledge, each module included a final set of 15 questions randomly chosen and posed to participants before and after the training. Content analysis, chi-squared tests, Student's t-tests, and paired tests were utilized for data analysis. The evaluation was conducted in Alberta, Canada in 2020. RESULTS: A total of 128 participants enrolled in the study. The main themes revealed in the qualitative aspect of the evaluation were: the training was easy to navigate, engaging, informative, and beneficial to the staff's daily work. Compared with the pre-training test, a significantly higher post-training test score, mean and (SD), was recorded for clerks who completed the clerk training module [59.1 (12.8) vs 75.5 (11.1), t=8.6378, p<0.001], and managers who completed the managers training module [51.5 (11.1) vs 73.1 (12.3), t=7.6446, p<0.001]. Similarly, a higher number of participants achieved the passing score of 80% in the post-training test in all three groups. CONCLUSIONS: The online training was found to be acceptable and effective in increasing the mean individual score in the knowledge test and in increasing the percentage of participants achieving the passing score. The TRAC training is the first known tobacco retailer training course to employ best practices in tobacco retailer training, adult instruction, and e-learning. Further evaluation of long-term outcomes on employee behavior and on overall compliance with tobacco legislation is recommended.
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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 | 0.040 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".