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Record W2605270275 · doi:10.1177/2165079916680366

Linking Incidents in Long-Term Care Facilities to Worker Activities

2017· article· en· W2605270275 on OpenAlexaff
Rose McCloskey, Cindy Donovan, Alicia Donovan

Bibliographic record

VenueWorkplace Health & Safety · 2017
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsOccupational safety and healthIncident reportMedicineExploratory researchMedical emergencyHealth careLong-term careWork (physics)NursingPatient safetyForensic engineering

Abstract

fetched live from OpenAlex

This article reports on a study examining staff activities being performed when incidents were reported to have occurred. The risk for injury among health care providers who engage in patient handling activities is widely acknowledged. For those working in long-term care, the risk of occupational injury is particularly high. Although injuries and injury prevention have been widely studied, the work has generally focused on incident rates and the impact of specific assistive devices on worker safety. The purpose of this study was to examine reported staff incidents in relation to staff activities. A multicenter cross-sectional exploratory study used retrospective data from reported staff incidents (2010, 2011, and 2012) and prospective data from 360 hours of staff observations in five long-term care facilities during 2013. Descriptive statistics were used to analyze data. A total of 898 staff incidents were reviewed from the facilities. Incidents were most likely to occur in resident rooms. Resident aides were more likely to be engaged in high-risk activities than other care providers. Times when staff incidents were reported to have occurred were not associated with periods of high staff-to-resident contact. Safe handling during low and moderate risk activities should be promoted. Education on what constitutes a reportable incident and strategies to ensure compliance with reporting policies and procedures may be needed to ensure accuracy and completeness of incident data.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.066
GPT teacher head0.472
Teacher spread0.406 · 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
Published2017
Admission routes1
Has abstractyes

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