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Record W2565839370 · doi:10.1515/joim-2016-0008

The Effects of Personal and Organizational Resources on Work and Well-Being Outcomes among Turkish Nurses

2016· article· en· W2565839370 on OpenAlexaff
Ronald J. Burke, Mustafa Koyuncu, Lisa Fıksenbaum, Şevket Yirik, Kadife Koynncu

Bibliographic record

VenueJournal of Intercultural Management · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsYork University
Fundersnot available
KeywordsOptimismFeelingPsychologyWork engagementTurkishJob satisfactionEmpowermentWork (physics)Multilevel modelNursingSample (material)Social psychologyMedicine

Abstract

fetched live from OpenAlex

Abstract This exploratory research examined the relationship of a personal and an organizational resource, optimism and levels of hospital support respectively, on a variety of work and well-being outcomes in a sample of nurses in Turkey. Data were collected from 212 nurses using anonymously completed questionnaires. Feelings of psychological empowerment was positioned as a mediator between resources and work and well-being outcomes which included job satisfaction, work engagement, affective hospital commitment, work-family conflict, family-work conflict, and intent to quit. The sample scored at moderate levels on the measures of resources and work outcomes, though scoring higher of feelings of psychological empowerment. These data indicate potential room for improvement in the work experiences of our nursing respondents. Hierarchical regression analyses controlling for personal demographics indicated that levels of hospital support were significantly and positively associated with most work and well-being outcomes, with levels of optimism significantly and positively associated with fewer of these outcomes. Practical implications of the findings are offered. Hospital efforts to increase levels of optimism and hospital support are described.

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)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.011
GPT teacher head0.331
Teacher spread0.320 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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