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Record W2006481338 · doi:10.1002/nur.20172

Measuring nurses' practice environments with the revised nursing work index: Evidence from registered nurses in the veterans health administration

2007· article· en· W2006481338 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.

Bibliographic record

VenueResearch in Nursing & Health · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Alberta
FundersHealth Services Research and Development
KeywordsGeneralizability theoryStaffingNursingNurse AdministratorAdministration (probate law)Exploratory factor analysisExploratory researchMedicineSet (abstract data type)Work (physics)Sample (material)PsychologyMEDLINEPsychometricsClinical psychology

Abstract

fetched live from OpenAlex

The Revised Nursing Work Index (NWI-R) is a widely used instrument for evaluating registered nurses' (RNs) practice environments. The existence of multiple subscale sets from the NWI-R raises questions about its generalizability. We tested the validity of the one-, three-, and five-subscale sets from the NWI-R and derived a short-form subscale set using a sample of RNs from the Veterans Health Administration (VHA). The prior sets do not have an excellent fit to these data. Results of exploratory factor analyses suggested a four-factor model with Opportunity for Advancement, Collegial Nurse-Physician Relations, Staffing Adequacy, and Nurse Manager Leadership as the most salient and parsimonious solution. Additional research is needed to corroborate these findings in other nurse samples and settings.

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)0.029
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.004
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 head0.330
GPT teacher head0.560
Teacher spread0.231 · 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