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Record W4402433592 · doi:10.1093/pch/pxae046

Unintended consequences of a night float system in Paediatric Residency

2024· article· en· W4402433592 on OpenAlexafffund
Ali Al Maawali, Allan Puran, Susanna Talarico, Zia Bismilla

Bibliographic record

VenuePaediatrics & Child Health · 2024
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsHospital for Sick Children
FundersHospital for Sick Children
KeywordsFloat (project management)Unintended consequencesResidency trainingMedical educationAeronauticsMedicineEngineeringEconomicsPolitical scienceManagementContinuing education

Abstract

fetched live from OpenAlex

Objectives: Many residency programs implement 'night float' (NF) systems as alternatives to a traditional 24-h call model in an attempt to comply with duty-hour regulations. Research evaluating NF systems has focused primarily on the perspective of the resident with respect to fatigue and quality of life. Understanding the broader consequences of NF models from both trainee and faculty points of view is essential to creating effective and sustainable systems to comply with duty-hour regulations while maximizing patient care, education, and quality of life (QoL). Methods: This study used qualitative thematic analysis situated in a constructivist paradigm to explore the experience of an NF system by residents and faculty. Semi-structured interviews were conducted with 15 trainees and 3 faculty members at a large academic pediatric hospital to understand their perceptions of an NF call structure compared to the traditional 24-h call schedule. Results: Three themes were identified: (i) Implications for resident; (ii) Implications for patient and family; and (iii) Implications for curriculum. Eight sub-themes were identified, highlighting both intended and unintended consequences of the NF system. Conclusions: The NF system resulted in the intended outcomes of decreased fatigue and improved continuity of patient care. Unintended outcomes also occurred, however, including negative effects on assessment and feedback, lack of integration of competencies, and mixed results on resident quality of life. These areas require special attention when designing and implementing NF systems.

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)0.000
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 score0.506
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.294
Teacher spread0.279 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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