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Record W2123551521 · doi:10.1016/j.burn.2014.03.002

New nurses burnout and workplace wellbeing: The influence of authentic leadership and psychological capital

2014· article· en· W2123551521 on OpenAlexafffund
Heather K. Spence Laschinger, Roberta Fida

Bibliographic record

VenueBurnout Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsWestern University
FundersOntario Ministry of Health and Long-Term Care
KeywordsBurnoutAuthentic leadershipPsychologySocial psychologyCapital (architecture)Positive psychological capitalApplied psychologyWork engagementClinical psychologyWork (physics)

Abstract

fetched live from OpenAlex

The detrimental effects of burnout on nurses’ health and wellbeing are well documented and positive leadership has been shown to be an important organizational resource for discouraging the development of burnout. Intrapersonal resources also play a protective role against workplace stressors. This study investigated the influence of authentic leadership, an organizational resource, and psychological capital, an intrapersonal resource, on new graduate burnout, occupational satisfaction, and workplace mental health over the first year of employment (n = 205). Results supported the protective role of organizational and intrapersonal resources against burnout, job dissatisfaction, and mental health.

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)0.008
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.183
GPT teacher head0.495
Teacher spread0.312 · 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

Citations343
Published2014
Admission routes2
Has abstractyes

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