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Record W3092107483

Unit Managers’ Authentic Leadership, Staff Nurses’ Work Attitudes and Behaviours, and Outcomes of Care: A Structural Equation Model

2020· article· en· W3092107483 on OpenAlexaboutno aff
Lisa M. Giallonardo

Bibliographic record

VenueScholarship@Western (Western University) · 2020
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStructural equation modelingAuthentic leadershipWork (physics)Unit (ring theory)PsychologyNursingMedical educationSocial psychologyMedicineEngineeringMathematics educationMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

Nursing leadership is fundamental in the development of positive work attitudes and behaviours among staff nurses, and the provision of high quality patient care. Although direct empirical links were well established, there was a lack of research testing the indirect effects of leadership on nurses and patients. As such, it was proposed that the concept of authentic leadership could help explain the complex psychological processes that mediated relationships between nurse managers’ leadership, staff nurses’ work attitudes and behaviours, and outcomes of care.\nThe purpose of the present study was to test a model of authentic leadership in a sample of registered nurses, working in acute care hospitals, in Ontario (n=264). The hypothesized model was analyzed using multiple regression and latent variable path analysis. Results did not support the moderating effect of psychological safety; therefore, it was removed from subsequent analysis. Although the structural model achieved good fit in the first iteration [c2 MLR(182)= 295.041, p= <0.001, RMSEA=.049, 90% CI= .038 and .058, SRMR=.083, CFI= .957], the direct effects of authentic leadership on professional identification, professional identification on voice behaviour, and voice behaviour on missed nursing care were non-significant (p>.05). Model modifications were made in a step-wise manner and all non-significant paths were deleted. The final structural model achieved good fit [c2 MLR(131)= 203.829, p= <0.001, RMSEA=.046, 90% CI= .033 and .058, SRMR=.073, CFI= .969] and supported the direct effects of authentic leadership on voice behaviour and job satisfaction, while missed nursing care had significant direct effects on job satisfaction, nurse-assessed quality, and adverse events (p< .001). An alternative model was also tested which achieved good fit [c2 MLR(184)= 272.249, p= <0.001, RMSEA=.043, 90% CI= .031 and .053, SRMR=.078, CFI= .966] and supported the direct effect of authentic leadership on psychological safety and indirect effect of authentic leadership on voice behaviour through psychological safety (β= .188, p< .001).\nFindings highlighted the importance of developing unit manager’s authentic leadership, thereby nurturing staff nurses’ psychological safety, voice behaviour, and job satisfaction. In addition, attention to the antecedents of missed nursing care may increase nurses’ job satisfaction, decrease adverse events, and improve the quality of patient care.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.190
Threshold uncertainty score0.377

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0020.002
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 head0.169
GPT teacher head0.372
Teacher spread0.203 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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