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Record W2151595152 · doi:10.1007/s40037-015-0209-5

Putting performance in context: the perceived influence of environmental factors on work-based performance

2015· article· en· W2151595152 on OpenAlexaff
Lynfa Stroud, M. P. Bryden, Bochra Kurabi, Shiphra Ginsburg

Bibliographic record

VenuePerspectives on Medical Education · 2015
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsThe Wilson CentreSunnybrook HospitalUniversity of TorontoUniversity Health NetworkSunnybrook Health Science Centre
Fundersnot available
KeywordsCompetence (human resources)PerceptionPsychologyContext (archaeology)Applied psychologyMedical educationMedicineSocial psychology

Abstract

fetched live from OpenAlex

INTRODUCTION: Context shapes behaviours yet is seldom considered when assessing competence. Our objective was to explore attending physicians' and trainees' perceptions of the Internal Medicine Clinical Teaching Unit (CTU) environment and how they thought contextual factors affected their performance. METHOD: 29 individuals recently completing CTU rotations participated in nine level-specific focus groups (2 with attending physicians, 3 with senior and 2 with junior residents, and 2 with students). Participants were asked to identify environmental factors on the CTU and to describe how these factors influenced their own performance across CanMEDS roles. Discussions were analyzed using constructivist grounded theory. RESULTS: Five major contextual factors were identified: Busyness, Multiple Hats, Other People, Educational Structures, and Hospital Resources and Policies. Busyness emerged as the most important, but all factors had a substantial perceived impact on performance. Participants felt their performance on the Manager and Scholar roles was most affected by environmental factors (mostly negatively, due to decreased efficiency and impact on learning). CONCLUSIONS: In complex workplace environments, numerous factors shape performance. These contextual factors and their impact need to be considered in observations and judgements made about performance in the workplace, as without this understanding conclusions about competency may be flawed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.560

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)0.0000.000

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 head0.015
GPT teacher head0.303
Teacher spread0.289 · 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.

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

Citations8
Published2015
Admission routes1
Has abstractyes

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