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Record W3171689892 · doi:10.1007/s40037-021-00671-y

The system, the resident, and the preceptor: a curricular approach to continuity of care training

2021· article· en· W3171689892 on OpenAlexafffund
Allyson Merbaum, Kulamakan Kulasegaram, Rebecca Stoller, Oshan Fernando, Risa Freeman

Bibliographic record

VenuePerspectives on Medical Education · 2021
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsThe Wilson CentreUniversity of TorontoNorth York General Hospital
FundersUniversity of Toronto
KeywordsPreceptorMedical educationMedicinePsychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Continuity of care (CoC) is integral to the practice of comprehensive primary care, yet research in the area of CoC training in residency programs is limited. In light of distributed medical education and evolving accreditation standards, a rigorous understanding of the context and enablers contributing to CoC education must be considered in the design and delivery of residency training programs. APPROACH: At our preceptor-based community academic site, we developed a system-resident-preceptor (SRP) framework to explore factors that influence a resident's perception regarding CoC, and established variables in each area to enhance learning. We then implemented a two-year educational SRP intervention (SRPI) to one cohort of residents and their preceptors to integrate critical education factors and align teaching of continuity of care within curricular goals. EVALUATION: Evaluation of the intervention was based on resident interviews and faculty focus groups, and a qualitative phenomenological approach was used to analyze the data. While some factors identified are inherent to family medicine, the opportunity for reflection is a unique component to inculcate CoC learning. REFLECTION: The SRP innovation provides a unique framework to facilitate residents' understanding and development of CoC competency. Our model can be applied to all residency programs, including traditional academic sites as well as distributed training sites, to enhance CoC education.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.337
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2021
Admission routes2
Has abstractyes

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