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Record W3118846061 · doi:10.1177/0844562120986032

The National Standard of Psychological Health and Safety in the Workplace: A Psychometric and Descriptive Study of the Nursing Workforce in British Columbia Hospitals

2021· article· en· W3118846061 on OpenAlexafffundvenueabout
Farinaz Havaei, Minjeong Park, Oscar L. Olvera Astivia

Bibliographic record

VenueCanadian Journal of Nursing Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsWorkforceDescriptive statisticsMental healthPsychologyCommissionNursingStructural equation modelingWork (physics)MedicinePsychiatryStatisticsMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: In 2013, the Mental Health Commission of Canada created a National Standard that includes 13 workplace factors associated with employee mental health. PURPOSE: This study (a) examined the psychometric properties of Guarding Minds at Work (GMW), the instrument used to measure the Standard's 13 workplace factors and (b) assessed BC nurses' workplace risk factors. METHODS: A province-wide survey study of 3,077 direct care nurses working in acute care settings was conducted. RESULTS: Subscale internal consistencies were acceptable. For most items, the original alphas were greater than the alpha-if-item-deleted. All corrected item-subtotal correlations were moderate to high. The 13-factor structure showed an adequate model fit based on absolute fit indices (SRMR = 0.057 and RMSEA = 0.054) but the relative fit indices were lower than the recommended cutoff (CFI = 0.827 and TLI = 0.815). Nurses identified nine of the 13 GMW factors as serious or significant concern in their workplace. CONCLUSIONS: The findings were consistent with a plethora of evidence pointing to shortcomings in nurses' work environments. This was the first study partially supporting the reliability and validity of the GMW. More work is required to refine the GMW and gain a better understanding of its psychometric properties.

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)0.010
metaresearch head score (Gemma)0.002
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 score0.496
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.001
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 head0.124
GPT teacher head0.451
Teacher spread0.327 · 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

Citations11
Published2021
Admission routes4
Has abstractyes

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