Evaluation of the efficacy of a web-based work-related asthma educational tool
Bibliographic record
Abstract
BACKGROUND: Work-related asthma (WRA) has been estimated to account for 15-20% of adult asthma cases. Studies have indicated that a substantial number of asthma patients have inadequate knowledge of work-related effects on their disease, which may contribute to suboptimal asthma control. A Canadian web-based educational tool on WRA was developed to address this knowledge gap in the population. OBJECTIVE: To evaluate the effectiveness of this web-based tool. METHODS: Participants were recruited prior to a routine visit at a tertiary care asthma clinic in Toronto. A brief WRA knowledge questionnaire was developed and administered immediately before and after using of the web-based educational tool, and one year later. RESULTS: The study sample (N = 34) was mostly female (68%) with a mean age of 50.7 (SD, 17.2). Participants demonstrated significant improvement in questionnaire scores following interaction with the tool. The mean score increased from 76% (SEM = 2.1) to 84% (SEM = 1.7) (p = 0.001). On average, scores improved on 12 of the 13 questionnaire items. A 1-year follow-up of a sample of 19 participants demonstrated a slight reduction in mean scores, from 86% (SEM = 1.9) to 84% (SEM = 1.9), but still demonstrated a trend towards a higher score than the baseline (78%; SEM = 2.9; p = 0.08). CONCLUSIONS: Our findings suggest that the educational tool has a positive effect on WRA knowledge, and that knowledge may be retained long-term. Future studies are needed in non-tertiary care clinic populations which may possess less baseline knowledge of WRA.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".