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Team OSCEs: evaluation methodology or educational encounter?

2008· article· en· W1965625798 on OpenAlexaff
Pippa Hall, Alan Taniguchi

Bibliographic record

VenueMedical Education · 2008
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFormative assessmentCurriculumMedical educationTeamworkContext (archaeology)Health careInterprofessional educationObjective structured clinical examinationMedicinePsychologyProblem-based learningNursingPedagogy

Abstract

fetched live from OpenAlex

Context and setting Two university faculties of health sciences piloted the team objective structured clinical examination (TOSCE) format in 2006 to interprofessional undergraduate health sciences students. Most of these students were medical students, but the sample included students drawn from social work, chaplaincy, nursing and occupational therapy (OT) curricula. Subsequently, three TOSCE stations have been delivered over a half-day, conducted every 6 weeks, to medical students at one university since January 2007 as part of the mandatory clerkship curriculum. Other health care students participate as an elective. Both interprofessional groups (medical and nursing students, or social work, OT and chaplaincy students) and uniprofessional groups (medical students, who role-play the roles of other team members) have thus participated in the TOSCE experience at this university for over 16 months. Why the idea was necessary Current interest in interprofessional education for collaborative patient-centred practice (IECPCP) raises challenges of defining the competencies necessary for teamwork and how to teach and then evaluate them. There is little medical education literature that directs curriculum designers to evaluation methods or formative educational assessment tools for IECPCP. What was done Stations for the OSCE were created based on clinical scenarios that require a team approach to care (hence ‘team OSCEs’ [TOSCEs]). Stations are 30 minutes in length and teams of five or six students work through scenarios, depicted by a standardised patient (SP) or a video clip, to determine an interprofessional care plan for the patient involved. Students are evaluated on a set of clinical competencies in an area of focus which varies from station to station (e.g. palliative care), and a set of standardised interprofessional competencies that are consistent across each station. Each station has two evaluators; one is an MD faculty member and one is a faculty member from another allied health profession such as nursing, social work, OT or chaplaincy. Each station includes 10 minutes for feedback given by the SP and the evaluators. Evaluation of results and impact Students and evaluators complete extensive surveys at the end of each TOSCE day. Both students (n = 141) and evaluators (n = 38) have reported a high degree of acceptability of the TOSCE, with 81–100% of respondents responding with ‘agree’ or ‘strongly agree’ to a series of acceptability questions. Similarly, the majority of both student and evaluator respondents (79–100%) agreed or strongly agreed that the TOSCE format was quite feasible. Of note, the students felt the 10 minutes of feedback following each station was amongst the most useful learning they had received in their training. Three more TOSCE stations are being introduced to evaluate the reliability and validity of the TOSCE. Student TOSCE scores are being compared with those on multiple-choice question tests and clinical application exercises in the same content areas. Thirty students will complete six TOSCE stations as part of this evaluation, which will include randomisation so that the effect of the group versus the individual can be investigated. The TOSCE holds promise for learners at all levels for a variety of clinical scenarios where both health care content and team-based skills are necessary. At the least, it is a formative educational tool, and current reliability and validity data will determine its effectiveness as an evaluation methodology.

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0720.002

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 head0.165
GPT teacher head0.578
Teacher spread0.412 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations15
Published2008
Admission routes1
Has abstractyes

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