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Record W2164632976 · doi:10.3109/0142159x.2013.806791

Encouraging residents to seek feedback

2013· article· en· W2164632976 on OpenAlexaff
Dianne Delva, Joan Sargeant, Stephen G. Miller, Joanna Holland, Peggy Alexiadis Brown, Constance LeBlanc, Kathryn Lightfoot, Karen Mann

Bibliographic record

VenueMedical Teacher · 2013
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsSaint John Regional HospitalDalhousie UniversityUniversity of Toronto
Fundersnot available
KeywordsPsychologyMedical educationMEDLINEMedicinePolitical science

Abstract

fetched live from OpenAlex

AIM: To explore resident and faculty perceptions of the feedback process, especially residents' feedback-seeking activities. METHODS: We conducted focus groups of faculty and residents exploring experiences in giving and receiving feedback, feedback-seeking, and suggestions to support feedback-seeking. Using qualitative methods and an iterative process, all authors analyzed the transcribed audiotapes to identify and confirm themes. RESULTS: Emerging themes fit a framework situating resident feedback-seeking as dependent on four central factors: (1) learning/workplace culture, (2) relationships, (3) purpose/quality of feedback, (4) emotional responses to feedback. Residents and faculty agreed on many supports and barriers to feedback-seeking. Strengthening the workplace/learning culture through longitudinal experiences, use of feedback forms and explicit expectations for residents to seek feedback, coupled with providing a sense of safety and adequate time for observation and providing feedback were suggested. Tensions between faculty and resident perceptions regarding feedback-seeking related to fear of being found deficient, the emotional costs related to corrective feedback and perceptions that completing clinical work is more valued than learning. CONCLUSION: Resident feedback-seeking is influenced by multiple factors requiring attention to both faculty and learner roles. Further study of specific influences and strategies to mitigate the tensions will inform how best to support residents in seeking feedback.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0430.006

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 head0.017
GPT teacher head0.332
Teacher spread0.316 · 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

Citations115
Published2013
Admission routes1
Has abstractyes

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