Validity evidence for communication skills assessment in health professions education: a scoping review
Bibliographic record
Abstract
OBJECTIVE: Communication skills assessment (CSA) is essential for ensuring competency, guiding educational practices and safeguarding regulatory compliance in health professions education (HPE). However, there appears to be heterogeneity in the reporting of validity evidence from CSA methods across the health profession that complicates our interpretation of the quality of assessment methods. Our objective was to map reliability and validity evidence from scores of CSA methods that have been reported in HPE. DESIGN: Scoping review. DATA SOURCES: MEDLINE, Embase, PsycINFO, CINAHL, ERIC, CAB Abstracts and Scopus databases were searched up to March 2024. ELIGIBILITY CRITERIA: We included studies, available in English, that reported validity evidence (content-related, internal structure, relationship with other variables, response processes and consequences) for CSA methods in HPE. There were no restrictions related to date of publication. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers completed data extraction and assessed study quality using the Medical Education Research Study Quality Instrument. Data were reported using descriptive analysis (mean, median, range). RESULTS: A total of 146 eligible studies were identified, including 98 394 participants. Most studies were conducted in human medicine (124 studies) and participants were mostly undergraduate students (85 studies). Performance-based, simulated, inperson CSA was most prevalent, comprising 115 studies, of which 68 studies were objective structured clinical examination-based. Other types of methods that were reported were workplace-based assessment; asynchronous, video-based assessment; knowledge-based assessment and performance-based, simulated, virtual assessment. Included studies used a diverse range of communications skills frameworks, rating scales and raters. Internal structure was the most reported source of validity evidence (130 studies (90%), followed by content-related (108 studies (74%), relationships with other variables (86 studies (59%), response processes (15 studies (10%) and consequences (16 studies (11%). CONCLUSIONS: This scoping review identified gaps in the sources of validity evidence related to assessment method that have been used to support the use of CSA methods. These gaps could be addressed by studies explicitly defining the communication skill construct(s) assessed, clarifying the validity source(s) reported and defining the intended purpose and use of the scores (ie, for learning and feedback, for decision making purposes). Our review provides a map where targeted CSA development and support are needed. Limitations of the evidence come from score interpretation being constrained by the heterogeneity of the definition of communication skills across the health professions and the reporting quality of the studies.
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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 | 0.151 | 0.552 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.042 | 0.031 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".