Validation of the 5-item doctor-patient communication competency instrument for medical students (DPCC-MS) using two years of assessment data
Bibliographic record
Abstract
BACKGROUND: Medical students on clinical rotations have to be assessed on several competencies at the end of each clinical rotation, pointing to the need for short, reliable, and valid assessment instruments of each competency. Doctor patient communication is a central competency targeted by medical schools however, there are no published short (i.e. less than 10 items), reliable and valid instruments to assess doctor-patient communication competency. The Faculty of Medicine of Laval University recently developed a 5-item Doctor-Patient Communication Competency instrument for Medical Students (DPCC-MS), based on the Patient Centered Clinical Method conceptual framework, which provides a global summative end-of-rotation assessment of doctor-patient communication. We conducted a psychometric validation of this instrument and present validity evidence based on the response process, internal structure and relation to other variables using two years of assessment data. METHODS: We conducted the study in two phases. In phase 1, we drew on 4991 student DPCC-MS assessments (two years). We conducted descriptive statistics, a confirmatory factor analysis (CFA), and tested the correlation between the DPCC-MS and the Multiple Mini Interviews (MMI) scores. In phase 2, eleven clinical teachers assessed the performance of 35 medical students in an objective structured clinical examination station using the DPCC-MS, a 15-item instrument developed by Côté et al. (published in 2001), and a 2-item global assessment. We compared the DPCC-MS to the longer Côté et al. instrument based on internal consistency, coefficient of variation, convergent validity, and inter-rater reliability. RESULTS: Phase 1: Cronbach's alpha was acceptable (.75 and .83). Inter-item correlations were positive and the discrimination index was above .30 for all items. CFA supported a unidimensional structure. DPCC-MS and MMI scores were correlated. Phase 2: The DPCC-MS and the Côté et al. instrument had similar internal consistency and convergent validity, but the DPCC-MS had better inter-rater reliability (mean ICC = .61). CONCLUSIONS: The DPCC-MS provides an internally consistent and valid assessment of medical students' communication with patients.
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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 | 0.034 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".