Evaluation of Communication Skills Among Physicians: A Systematic Review of Existing Assessment Tools
Bibliographic record
Abstract
OBJECTIVE: The importance of physician training in communication skills for motivating patients to adopt a healthy life-style and optimize clinical outcomes is increasingly recognized. This study inventoried and systematically reviewed the psychometric properties of, and the skills assessed by, existing assessment tools used to evaluate communication skills among physicians. METHODS: This review was conducted in accordance with the PRISMA guidelines (PROSPERO: CRD42018091932). Four databases (PUBMED, EMBASE, PsychINFO, and SCOPUS) were searched up to December 2018, generating 3902 unique articles, which were screened by two authors. A total of 57 articles met the inclusion criteria and underwent full data extraction. RESULTS: Forty-five different assessment tools were identified. Only 47% of the studies mentioned underlying theories or models for designing the tool. Fifteen communication skills were assessed across the tools, the five most prevalent were information giving (46%) or gathering (40%), eliciting patients' perspectives (44%), planning/goal setting (37%), and closing the session (32%). Most tools (93%) assessed communication skills using in-person role play exercises with standardized (61%) or real (32%) patients, but only 54% described the expertise of the raters who performed the evaluations. Overall, reporting of the psychometric properties of the assessment tools was poor-moderate (4.5 ± 1.3 out of 9). CONCLUSIONS: Despite identifying several existing physician communication assessment tools, a high degree of heterogeneity between these tools, in terms of skills assessed and study quality, was observed, and most have been poorly validated. Research is needed to rigorously develop and validate accessible, convenient, "user-friendly," and easy to administer and score communication assessment tools.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".