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Record W3087266268 · doi:10.1080/10401334.2020.1789466

Facilitating Learner-Centered Transition to Residency: A Scoping Review of Programs Aimed at Intrinsic Competencies

2020· review· en· W3087266268 on OpenAlex
Aliya Kassam, Leslie Nickell, Helen Pethrick, Margo Mountjoy, Maureen Topps, Diane Lorenzetti

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTeaching and Learning in Medicine · 2020
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsHamilton Health SciencesMedical Council of CanadaHealth Sciences CentreUniversity of TorontoUniversity of Calgary
Fundersnot available
KeywordsCompetence (human resources)StakeholderMedical educationScholarshipPsychological interventionInclusion (mineral)MEDLINEMedicinePsychologyNursingPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Phenomenon: There is currently a move to provide residency programs with accurate competency-based assessments of their candidates, yet there is a gap in knowledge regarding the role and effectiveness of interventions in easing the transition to residency. The impact of key stakeholder engagement, learner-centeredness, intrinsic competencies, and assessment on the efficacy of this process has not been examined. The objective of this scoping review was to explore the nature of the existing scholarship on programs that aim to facilitate the transition from medical school to residency. Approach: We searched MEDLINE and EMBASE from inception to April 2020. Programs were included if they were aimed at medical students completing undergraduate medical training or first year residents and an evaluative component. Two authors independently screened all abstracts and full text articles in duplicate. Data were extracted and categorized by type of program, study design, learner-centeredness, key stakeholder engagement, the extent of information sharing about the learner to facilitate the transition to residency, and specific program elements including participants, and program outcomes. We also extracted data on intrinsic (non-Medical Expert) competencies, as defined by the CanMEDS competency framework. Findings: Of the 1,006 studies identified, 55 met the criteria for inclusion in this review. The majority of the articles that were eligible for inclusion were from the United States (n = 31, 57%). Most of the studies (n = 47, 85%) employed quantitative, or mixed method research designs. Positive outcomes that were commonly reported included increased self-confidence, competence in being prepared for residency, and satisfaction with the transition program. While a variety of learner-centered programs that focus on specific intrinsic competencies have been implemented, many (n = 29, 52%) did not report engaging learners as key stakeholders in program development. Insights: While programs that aim to ease the transition from medical school to residency can enhance both Medical Expert and other intrinsic competencies, there is much room for novel transition programs to define their goals more broadly and to incorporate multiple areas of professional development. The existing literature highlights various gaps in approaches to easing the transition from medical school to residency, particularly with respect to key stakeholder engagement, addressing intrinsic CanMEDS competencies, and focusing on individual learners’ needs.

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.

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)0.007
metaresearch head score (Gemma)0.027
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.731
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.076
GPT teacher head0.409
Teacher spread0.333 · 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