Informing Web-Based Communication Curricula in Veterinary Education: A Systematic Review of Web-Based Methods Used for Teaching and Assessing Clinical Communication in Medical Education
Bibliographic record
Abstract
We determined the Web-based configurations that are applied to teach medical and veterinary communication skills, evaluated their effectiveness, and suggested future educational directions for Web-based communication teaching in veterinary education. We performed a systematic search of CAB Abstracts, MEDLINE, Scopus, and ERIC limited to articles published in English between 2000 and 2012. The review focused on medical or veterinary undergraduate to clinical- or residency-level students. We selected studies for which the study population was randomized to the Web-based learning (WBL) intervention with a post-test comparison with another WBL or non-WBL method and that reported at least one empirical outcome. Two independent reviewers completed relevancy screening, data extraction, and synthesis of results using Kirkpatrick and Kirkpatrick's framework. The search retrieved 1,583 articles, and 10 met the final inclusion criteria. We identified no published articles on Web based communication platforms in veterinary medicine; however, publications summarized from human medicine demonstrated that WBL provides a potentially reliable and valid approach for teaching and assessing communication skills. Student feedback on the use of virtual patients for teaching clinical communication skills has been positive,though evidence has suggested that practice with virtual patients prompted lower relation-building responses.Empirical outcomes indicate that WBL is a viable method for expanding the approach to teaching history taking and possibly to additional tasks of the veterinary medical interview.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".