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Record W2230106482 · doi:10.1177/2165079915576931

Occupational Stress Management and Burnout Interventions in Nursing and Their Implications for Healthy Work Environments

2015· review· en· W2230106482 on OpenAlexaffabout
Behdin Nowrouzi‐Kia, Nancy Lightfoot, Michael Larivière, Lorraine Carter, Ellen Rukholm, Robert J. Schinke, Diane Belanger-Gardner

Bibliographic record

VenueWorkplace Health & Safety · 2015
Typereview
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsHealth Sciences NorthNipissing UniversityLaurentian University
Fundersnot available
KeywordsBurnoutPsychological interventionNursingOccupational stressWorkplace health promotionStress managementPromotion (chess)Intervention (counseling)DistressPsychologyWork (physics)Occupational burnoutMedicineHealth promotionEmotional exhaustionPublic healthClinical psychologyPolitical science

Abstract

fetched live from OpenAlex

This article reports on a literature review of workplace interventions (i.e., creating healthy work environments and improving nurses' quality of work life [QWL]) aimed at managing occupational stress and burnout for nurses. A literature search was conducted using the keywords nursing, nurses, stress, distress, stress management, burnout, and intervention. All the intervention studies included in this review reported on workplace intervention strategies, mainly individual stress management and burnout interventions. Recommendations are provided to improve nurses' QWL in health care organizations through workplace health promotion programs so that nurses can be recruited and retained in rural and northern regions of Ontario. These regions have unique human resources needs due to the shortage of nurses working in primary 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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.140
GPT teacher head0.504
Teacher spread0.364 · 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 designOther design
Domainnot available
GenreReview

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

Citations122
Published2015
Admission routes2
Has abstractyes

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