Summative Assessment of Interprofessional “Collaborative Practice” Skills in Graduating Medical Students: A Validity Argument
Bibliographic record
Abstract
PURPOSE: To describe how the authors developed an objective structured clinical examination (OSCE) station to assess aspects of collaborative practice competency and how they then assessed validity using Kane's framework. METHOD: After piloting the collaborative practice OSCE station in 2015 and 2016, this was introduced at the Cumming School of Medicine in 2017. One hundred fifty-five students from the class of 2017 and 22 students from the class of 2018 participated. To create a validity argument, the authors used Kane's framework that views the argument for validity as 4 sequential inferences on the validity of scoring, generalization, extrapolation, and implications, RESULTS: Scoring validity is supported by psychometric analysis of checklist items and the fact that the contribution of rater specificity to students' ratings was similar to OSCE stations assessing clinical skills alone. The claim of validity of generalization is backed by structural equation modeling and confirmatory factor analysis that identified 5 latent variables, including 3 related to collaborative practice ("provides an effective handover," "provides mutual support," and "shares their mental model"). Validity of extrapolation is argued based upon the correlation between the rating for "shares their mental model" and the rating on in-training evaluations for "relationship with other members of the health care team," in addition to the association between performance on the collaborative practice OSCE station and the subsequent rating of performance during residency. Finally, validity of implications is supported by the fact that pass/fail decisions on the collaborative practice station were similar to other stations and by the observation that ratings on different aspects of collaborative practice associate with pass/fail decisions. CONCLUSIONS: Based upon the validity argument presented, the authors posit that this tool can be used to assess the collaborative practice competence of graduating medical students and the adequacy of training in collaborative practice.
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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 | 0.166 | 0.433 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".