MétaCan
Menu
Back to cohort
Record W2149961365 · doi:10.1111/medu.12017

How core competencies are taught during clinical supervision: participatory action research in family medicine

2012· article· en· W2149961365 on OpenAlexaff
Danielle Saucier, Line Paré, Luc Côté, Lucie Baillargeon

Bibliographic record

VenueMedical Education · 2012
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCore competencyMedical educationParticipatory action researchCitizen journalismAction (physics)MedicinePsychologySociologyPolitical scienceManagement

Abstract

fetched live from OpenAlex

OBJECTIVES: The development of professional competence is the main goal of residency training. Clinical supervision is the most commonly used teaching and learning method for the development of core competencies (CCs). The literature provides little information on how to encourage the learning of CCs through supervision. We undertook an exploratory study to describe if and how CCs were addressed during supervision in a family medicine residency programme. METHODS: We selected a participatory action research design to engage participants in exploring their precepting practices. Eleven volunteer faculty staff and six residents from a large family medicine residency programme took part in a 9-month process which included three focus group encounters alternating with data gathering during supervision. We used mostly qualitative methods for data collection and analysis, with thematic content analysis, triangulation of sources and of researchers, and member checking. RESULTS: Participants realised that they addressed all CCs listed as programme outcomes during clinical supervision, albeit implicitly and intuitively, and often unconsciously and superficially. We identified a series of factors that influenced the discussion of CCs: (i) CCs must be both known and valued; (ii) discussion of CCs occurs in a constant adaptation to numerous contextual factors, such as residents' characteristics; (iii) the teaching and learning of CCs is influenced by six challenges in the preceptor-resident interaction, such as residents' active engagement, and (iv) coherence with other curricular elements contributes to learning about CCs. Differences between residents' and preceptors' perspectives are discussed. CONCLUSIONS: This is the first descriptive study focusing on the teaching of CCs during clinical supervision, as experienced in a family medicine residency programme. Content and process issues were equally influential on the discussion of CCs. Our findings led to a representation of factors determining the teaching and learning of CCs in supervision, and suggest directions for research, for faculty development, and for interventions with learners.

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)0.008
metaresearch head score (Gemma)0.019
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 score0.161
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.388
GPT teacher head0.543
Teacher spread0.156 · 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

Citations34
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueMedical EducationSame topicInnovations in Medical EducationFrench-language works237,207