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Record W4292523143 · doi:10.1002/nop2.1314

Psychometric evaluation of the acute care nurses' job satisfaction <scp>scale‐revised</scp>

2022· article· en· W4292523143 on OpenAlexfundno aff
Yasin M. Yasin, Vahe Kehyayan, Fadi Khraim, Badriya Al Lenjawi

Bibliographic record

VenueNursing Open · 2022
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
FundersUniversity of Calgary
KeywordsJob satisfactionScale (ratio)Acute carePsychologyNursingApplied psychologyMedicineHealth careSocial psychologyGeography

Abstract

fetched live from OpenAlex

AIM: The aim of this study was to validate a job satisfaction scale among acute care nurses in the context of Qatar. DESIGN: Cross-sectional correlational survey. METHODS: A convenience sampling technique was used to recruit 295 acute care nurses between June 2021-September 2021. Exploratory factor analysis followed by confirmatory factor analysis was used for item reduction and convergent and discriminant validity evaluation. Pearson's correlations were conducted to evaluate the concurrent and convergent validity of the revised scale. Reliability was tested using several internal consistency indicators. RESULTS: A revised scale was proposed, the Acute Care Nurses Job Satisfaction Scale-Revised (ACNJSS-R) scale; it is composed of 13 items loaded on five factors. The composite reliability and the maximal reliability were >.7 for all factors. The study provides empirical support for the validity and reliability of the ACNJSS-R scale.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.382
Teacher spread0.338 · 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.

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

Citations7
Published2022
Admission routes1
Has abstractyes

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