Helping family physicians improve their cardiac auscultation skills with an interactive CD-ROM
Bibliographic record
Abstract
INTRODUCTION: There have been few studies of the cardiac auscultation skills of residents and family physicians. This study assessed a group of family physicians' cardiac auscultation skills and use of a computerized self-instructional program to improve these skills. METHODS: Forty-two volunteer family physicians participated in an initial assessment of cardiac auscultation skills using test recordings of 12 common heart sounds. They were provided with a CD-ROM instructional program and were asked to devote 15 hours of self-study to the program and to return in 9 months for reassessment. RESULTS: The 42 family physicians in the initial assessment identified 39% of the heart sounds. Twenty-one returned for reassessment and showed significant improvement. Their initial mean score was 4.3 of 12 (35%), and their final mean score was 8.0 of 12 (67%). They found the CD-ROM program to be a valuable resource. The feature most liked was the unlimited opportunity to review sounds, cases, and tutorials. Most frequent problems related to computer access or skills. Eleven respondents reported using the program to resolve patient problems in their clinical practices. DISCUSSION: The cardiac auscultation skills of a group of volunteer family physicians showed low initial scores that improved significantly after self-study with a CD-ROM instructional program. The program was a valuable self-instructional aid, and physicians used it as a resource in clinical practice. However, only 50% of the initial group completed the self-study and returned for final assessment. Providing more support and assistance in the initial phase, especially with computer use, may enable completion of similar computerized self-study programs.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".