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Record W2331741456 · doi:10.1097/jnr.0000000000000106

The Psychometric Properties and the Development of the Indicators of Quality Nursing Work Environments in Taiwan

2015· article· en· W2331741456 on OpenAlex
Chiou-Fen Lin, Meei-Shiow Lu, Hsiu-Ying Huang

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Nursing Research · 2015
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsContent validityConstruct validityNursingQuality (philosophy)Test (biology)Reliability (semiconductor)Work (physics)Nursing shortagePsychologyValidityMedicinePsychometricsNurse educationPatient satisfactionClinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The nursing shortage in medical institutions in Taiwan averaged 9% in 2012, considerably higher than the 5% indicated in the literature. As a result, many hospitals have been forced to close wards or reduce beds. Despite the acute need, the percentage of registered nurses who are employed as nurses in Taiwan (60.4%) is considerably lower than those in Canada or the United States. This low rate may be because of the poor working environment for nurses in Taiwan. PURPOSE: This study aimed to develop a set of nursing work environment quality indicators for Taiwan and to test the reliability and validity of the resulting survey tool. METHODS: Multiple methods were used in this study. In Phase 1, we organized an expert panel, reviewed the literature, and conducted seven rounds of expert panel discussion and six focus group discussions with nursing directors. The goal was to draft indicators representing a quality nursing work environment to fit current conditions in Taiwan. In Phase 2, we conducted an expert review for content validity, held three public hearings, and conducted a survey. Four hundred twenty-seven questionnaires were sent out, with 381 returned. The goal was to test the content validity, construct validity, and internal consistency reliability. RESULTS: The study produced a set of indicators of a quality nursing work environment with eight dimensions and 65 items. The content validity index for importance and suitability dimensions were 1.0, whereas the internal consistency was 0.91. The eight dimensions were safe practice environment (16 items), quality and quantity of staff (four items), salary and welfare (seven items), professional specialization and teamwork (seven items), work simplification (five items), informatics (five items), career development (nine items), and support and caring (12 items). The overall load for the indicators was 77.57%. CONCLUSIONS/IMPLICATIONS FOR PRACTICE: The developed indicators may be used to evaluate the quality of nursing work environments. Furthermore, the indicators may be used in hospital surveys to establish baseline conditions and for outcome research that measures improvement in nursing work environments after interventions.

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)0.011
metaresearch head score (Gemma)0.001
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 score0.833
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.221
GPT teacher head0.448
Teacher spread0.227 · 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