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Record W2766488665 · doi:10.1186/s12909-017-1026-9

Validation of the 5-item doctor-patient communication competency instrument for medical students (DPCC-MS) using two years of assessment data

2017· article· en· W2766488665 on OpenAlexafffundabout
Jean‐Sébastien Renaud, Luc Côté

Bibliographic record

VenueBMC Medical Education · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversité Laval
FundersUniversité Laval
KeywordsCronbach's alphaSummative assessmentMedical educationDescriptive statisticsConfirmatory factor analysisPsychologyClinical clerkshipObjective structured clinical examinationReliability (semiconductor)MedicinePsychometricsFormative assessmentClinical psychologyCurriculumStructural equation modelingComputer scienceStatisticsMathematics educationPedagogy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0050.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.359
GPT teacher head0.569
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2017
Admission routes3
Has abstractyes

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