MétaCan
Menu
Back to cohort
Record W4233868640 · doi:10.21694/2379-2922.19004

Work Environment and Process in Intensive Care: Safety Risks for Professionals and Patients

2019· article· en· W4233868640 on OpenAlexfundno aff

Bibliographic record

VenueAmerican Research Journal of Nursing · 2019
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsPatient safetyWork (physics)Process (computing)NursingRisk analysis (engineering)Process safetyHealth careMedicineBusinessMedical emergencyWork in processComputer scienceEngineeringPolitical science

Abstract

fetched live from OpenAlex

Introduction: Risk situations are considered as being caused by the nature of the jobs and as the result of actions or external factors that increase the probability of changes in the workers' health.Objective: To explore how healthcare professionals in an intensive care unit (ICU) experience safety issues and other safety concerns within their work environment.Methods: The restorative approach in healthcare was used and involved joint identification of the problem and use of a set of visual methods: focus group; photo narration; and photo elicitation. Results:A key finding was that the work conditions and processes pose threats to patients and professionals' safety.Participants discussed risks existing in their work environment and identified solutions to promote a safer workplace for medication management and for themselves. Conclusions:The visual methods helped participants to develop in-depth discussions on the risk factors detected and engaged them in the proposition of solutions to the problems identified in this complex environment.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.179
GPT teacher head0.584
Teacher spread0.405 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Research Journal of NursingSame topicOccupational Health and Safety ResearchFrench-language works237,207