Online Education Improves Canadian Dietitians’ Attitudes and Knowledge Regarding Recommending and Ordering Multivitamin/Mineral Supplements
Bibliographic record
Abstract
PURPOSE: To determine the attitudes and knowledge of Fraser Health registered dietitians (RDs) regarding recommending and ordering multivitamin/mineral supplements prior to and following an online education module. METHODS: The educational intervention consisted of narrated slides with electronic resources. After undergoing external review for face and content validity, 6 attitude questions and a 15-item knowledge test were administered pre- and postintervention. The attitude questionnaire utilized a 5-point Likert scale and had a maximum summative score of 30 points. The knowledge test was worth a maximum of 15 points. RESULTS: Of the eligible RDs (n = 123), 57 (46.3%) completed the study and 55 participants were included in the final analyses. Summative attitude scores were higher on the post-intervention questionnaire compared with the preintervention questionnaire (t = 92.5, P < 0.001). The proportion of correctly answered knowledge questions pre- (78.0% ± 10.0%) to postintervention (mean = 87.4% ± 6.0%) increased significantly (t = 7.16, P < 0.001). CONCLUSIONS: Postintervention, RD attitudes and knowledge improved confirming that the education strategy was effective. Future work should focus on optimizing the module and knowledge questions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".