Evaluation Outcomes Resulting from an Internet-Based Continuing Professional Development (CPD) Asthma Program: Its Impact on Participants' Knowledge and Satisfaction
Bibliographic record
Abstract
INTRODUCTION: Previous studies have focused on the evaluation of Internet-based continuing professional development (CPD), but few have focused on the clinical area of asthma. Our purpose was to examine the evaluation outcomes related to knowledge and satisfaction that resulted from the provision of an Internet-based CPD program focusing on this clinical area. METHODS: Evaluation methodologies included a pre-/post-knowledge assessment (multiple choice) and a satisfaction survey. Completion of all assessments was voluntary, with the exception of the post-knowledge assessment for which completion was required for credit claim. RESULTS: There were a total of N = 457 unique registrants in the course over 1 year. A total of N = 125 course participants completed both pre- and post-knowledge assessments. An overall mean pre-knowledge score of 11.54 and a post-knowledge score of 16.04 were reported. Paired samples t-test analyses indicated a significant pre- to post-knowledge gain overall and for the majority of professions; 95.8% of the N = 46 satisfaction survey respondents reported that the program addressed their learning needs; 89.1% reported that it was relevant to practice. DISCUSSION: Recent studies focusing specifically on asthma were non-Canadian pilot studies with small sample sizes. The study findings highlight a similar initiative in Canada, which provided health professionals who care for patients with asthma access to relevant CPD with a Canadian perspective. The findings show that course participants were extremely satisfied and that they increased their knowledge in this clinical area. Further development of such Internet-based programs may encourage health professionals to improve their knowledge in a variety of therapeutic areas.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".