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Record W2201635978 · doi:10.1371/journal.pone.0138035

Nurses’ Practice Environment and Their Job Satisfaction: A Study on Nurses Caring for Older Adults in Shanghai

2015· article· en· W2201635978 on OpenAlexaff
Ying Wang, Weizhen Dong, Kristen L. Mauk, Peiying Li, Jin Wan, Guang Yang, Lyuying Fang, Huan Wan, Chun Chen, Hao Mo

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsUniversity of Toronto
FundersMinistry of Education of the People's Republic of ChinaNational Office for Philosophy and Social SciencesNational Natural Science Foundation of China
KeywordsJob satisfactionNursingSpecialtyPopulationContext (archaeology)PsychologyJob attitudeHealth carePopulation ageingScale (ratio)MedicineJob performanceFamily medicineEnvironmental healthSocial psychology

Abstract

fetched live from OpenAlex

AIM: To examine the job satisfaction of nurses who are caring for older adults in healthcare settings in Shanghai, and to explore the underlying factors in order to explain and predict nurses' job satisfaction. BACKGROUND: China has the largest elderly population in the world, and its population is aging rapidly. Studies on job satisfaction of nurses providing care for the elderly in China can help to identify problem areas and develop strategies for the improvement of nurses' working conditions. However, to date, this subject matter has not been thoroughly studied in the Chinese context. Previous studies in other countries show that many factors impact nurses' job satisfaction, with the practice environment being a critical factor. There is a serious nursing shortage in China, especially in the big cities such as Shanghai. Given the increasing care demand of the aging population, learning about the job satisfaction level among nurses who are caring for older adults can provide essential information to help attract and retain nurses in this specialty area. METHODS: A cross-sectional survey was conducted among 444 nurses in 22 elderly care institutions in Shanghai. The Chinese version of the Index of Work Satisfaction (IWS) and the Nursing Practice Environment Scale were instruments used. Inferential statistical tests used to analyze the data included Spearman correlation analysis, one-way analysis of variance, and hierarchical regression tests. RESULTS: The average overall IWS (part B) score was 135.21 ± 19.34. Personality, job and organizational characteristics were found to be the most influential factors, and the practice environment was identified as having the strongest impact on job satisfaction (Beta = 0.494). CONCLUSION: Job satisfaction level among nurses who are caring for older adults in Shanghai is moderate, but the data suggest that this could be greatly increased if the nursing practice environment was improved.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.121
GPT teacher head0.406
Teacher spread0.285 · 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

Citations48
Published2015
Admission routes1
Has abstractyes

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