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Record W2070544312 · doi:10.5737/1181912x233162171

Factors influencing job satisfaction of oncology nurses over time

2013· article· en· W2070544312 on OpenAlexafffundvenueabout
Greta G. Cummings, Christy Raymond-Seniuk, Eliza Lo, Elmabrok Masaoud, Debra Bakker, Margaret I. Fitch, Esther Green, Lorna Butler, Michael Conlon

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2013
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsJob satisfactionSupervisorJob attitudeWork (physics)PsychologyNursingQuality (philosophy)PerceptionJob designStructural equation modelingMedicineJob performanceSocial psychologyManagement

Abstract

fetched live from OpenAlex

In this study, we tested a structural equation model to examine work environment factors related to changes in job satisfaction of oncology nurses between 2004 and 2006. Relational leadership and good physician/nurse relationships consistently influenced perceptions of enough RNs to provide quality care, and freedom to make patient care decisions, which, in turn, directly influenced nurses' job satisfaction over time. Supervisor support in resolving conflict and the ability to influence patient care outcomes were significant influences on job satisfaction in 2004, whereas, in 2006, a clear philosophy of nursing had a greater significant influence. Several factors that influence job satisfaction of oncology nurses in Canada have changed over time, which may reflect changes in work environments and work life. These findings suggest opportunities to modify work conditions that could improve nurses' job satisfaction and work life.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.074
GPT teacher head0.436
Teacher spread0.361 · 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 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

Citations16
Published2013
Admission routes4
Has abstractyes

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