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Record W3110821302 · doi:10.1186/s12909-020-02402-z

An interpretive phenomenological analysis of formative feedback in anesthesia training: the residents’ perspective

2020· article· en· W3110821302 on OpenAlexafffund
Krista Ritchie, Ana Sjaus, Allana Munro, Ronald B. George

Bibliographic record

VenueBMC Medical Education · 2020
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMount Saint Vincent UniversityCapital District Health AuthorityIzaak Walton Killam Health CentreDalhousie University
FundersDalhousie University
KeywordsFormative assessmentMedical educationInterpretative phenomenological analysisContext (archaeology)Peer feedbackFocus groupPerspective (graphical)Set (abstract data type)Lifelong learningCornerstonePsychologySocial constructivismQuality (philosophy)MedicinePedagogyQualitative researchComputer scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Consistent formative feedback is cornerstone to competency-by-design programs and evidence-based approaches to teaching and learning processes. There has been no published research investigating feedback from residents' perspectives. We explored the value residents place on feedback in routine operating room settings, their experiences, and understanding of the role of feedback in their training and developing professional identity. METHODS: Interpretive phenomenological analysis of residents' experiences with feedback received in clinical settings involved two focus groups with 14 anesthesia residents at two time points. Analysis was completed in the context of a teaching hospital adapting to new practices to align with nationally mandated clinical competencies. Focus group conversations were transcribed and interpreted through the lens of a social constructivist approach to learning as a dynamic inter- and intra-personal process, and evidence-based assessment standards set by the International Test Commission (ITC). RESULTS: Residents described high quality feedback as consistent, effortful, understanding of residents' thought processes, and containing actionable advice for improvement. These qualities of effective evaluation were equally imperative for informal and formal evaluations. Residents commented that highest quality feedback was received informally, and formal evaluations often lacked what they needed for their professional development. CONCLUSION: Residents have a deep sense of what promotes their learning. Structured feedback tools were seen positively, although the most important determinants of their impact were faculty feedback- and broader evaluation-skills and motivations for both formal and informal feedback loops.

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)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.379
Teacher spread0.337 · 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 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

Citations14
Published2020
Admission routes2
Has abstractyes

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