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Record W6989467281

BC Paramedics and the Shift They Deal With: Levels of Fatigue, Sleep Quality, Mental Health, Medical Error, and Safety Associated With Their Shift Work Patterns

2021· other· en· W6989467281 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsShift workAffect (linguistics)Mental healthSleep (system call)Work (physics)Sleep patternsOccupational safety and healthWork hoursQuality (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

Fatigue and poor sleep quality have previously been documented to be common among paramedics around the world and have been associated with several factors - including precursors such as the timing and duration of shift work, and outcomes such as mental health problems, medical errors, and safety issues. While these factors have been studied in paramedics across Canada, little is currently known in the scientific literature about the degree to which they affect paramedics specifically in British Columbia (BC). Also, the majority of BC paramedics work on-call shifts which, due to their low pay and typically remote rural locations, may increase factors during off hours that are known to exacerbate fatigue and sleep problems, such as the need to work multiple jobs and make long commutes. The purpose of this study is to use previously validated questionnaires to assess the levels of fatigue, sleep quality, mental health, medical error, and safety in BC paramedics and to examine the associations of these factors with their shift work patterns.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.700
Threshold uncertainty score0.597

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.035
GPT teacher head0.306
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

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