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Record W4385215886 · doi:10.3390/healthcare11142099

Predictors of Nursing Faculty Job and Career Satisfaction, Turnover Intentions, and Professional Outlook: A National Survey

2023· article· en· W4385215886 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealthcare · 2023
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of OttawaUniversity of British ColumbiaMcMaster University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsJob satisfactionPsychologyTurnover intentionTurnoverNursingMedical educationMedicineManagementSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Retaining talented and experienced nurses in clinical practice and academia is crucial for maintaining continuity, ensuring high-quality care and education, and fostering a positive work environment. Although factors influencing nursing staff retention are well documented, little is known about how workplace factors impact nursing faculty retention outcomes. METHODS: A national survey involving 645 nursing faculty across Canada was undertaken. Multivariate regression analysis with interaction effects was conducted to determine the association between work-related factors (i.e., workplace culture and work-life imbalance) and faculty job and career satisfaction, turnover intentions, and professional outlook. RESULTS: Supportive workplace culture positively influenced faculty job and career satisfaction and professional outlook, while it negatively impacted turnover intentions. Conversely, work-life imbalance decreased faculty job and career satisfaction and professional outlook (i.e., confidence in nursing program, profession), and it increased intentions to leave the job. CONCLUSION: Our results offer insights into the work-life experiences of Canadian faculty members and shed light on key factors that impact their job-related outcomes. In the context of competing resources, every effort must be made to improve modifiable workplace factors such as the academic work environment and create targeted interventions and policies to promote faculty retention.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.171
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.117
GPT teacher head0.412
Teacher spread0.296 · 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