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Record W1525205991 · doi:10.1111/medu.12014

Changes in residents’ opportunities for experiential learning over time

2012· article· en· W1525205991 on OpenAlexafffundabout
Adam Peets, Henry T. Stelfox

Bibliographic record

VenueMedical Education · 2012
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsUniversity of CalgaryCentre for Advancing Health OutcomesUniversity of British ColumbiaProvidence Health Care Research InstituteProvidence Health Care
FundersCanadian Institutes of Health Research
KeywordsContext (archaeology)Experiential learningMedicineMedical recordIntensive careElectronic medical recordFamily medicinePsychologyInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

CONTEXT: Learning in the clinical environment is believed to be a crucial component of residency training. However, it remains unclear whether recent changes to postgraduate medical education, including the implementation of work hour limitations, have significantly impacted opportunities for experiential learning. Therefore, we sought to quantify opportunities to gain clinical experience within medical-surgical intensive care units (ICUs) over time. METHODS: Data on the numbers of patients admitted and invasive procedures performed per day between 1 July 2001 and 30 June 2010 within three academic medical-surgical ICUs in Calgary, Alberta, Canada were obtained from electronic medical records. These data were matched to resident doctor on-call schedules and residents' opportunities to admit patients and participate in procedures were calculated and compared over time using Spearman's rho. RESULTS: We found that over a 9-year period, the opportunities afforded to residents (n = 1156) to admit patients (n = 17 189) and perform procedures (n = 52 827) during ICU rotations decreased by 32% (p < 0.001) and 34% (p < 0.001), respectively. CONCLUSIONS: Our results suggest that there has been a significant decrease in residents' clinical experiences in the ICU over time. Further investigations to better understand these changes and how they may impact on performance as residents become independent practising doctors are warranted.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.038
GPT teacher head0.356
Teacher spread0.318 · 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 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

Citations7
Published2012
Admission routes3
Has abstractyes

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