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Record W2099472309 · doi:10.1177/0193945909331430

Organizational Traits, Care Processes, and Burnout Among Chronic Hemodialysis Nurses

2009· article· en· W2099472309 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

VenueWestern Journal of Nursing Research · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsUniversity of Toronto
FundersNational Institute of Nursing Research
KeywordsBurnoutStaffingWorkloadNursingAttritionMedicineHemodialysisPatient safetyGovernment (linguistics)PsychologyHealth careClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

In light of evidence linking registered nurse (RN) staffing levels to patient outcomes in chronic hemodialysis facilities, U.S. government regulations have set minimum RN staffing requirements during dialysis. Consequently, facility administrators are focused on decreasing nurse attrition in this crucial practice setting. This study used a cross-sectional, correlational design to investigate the effects of workload, practice environment, and care processes on burnout among nurses in U.S. chronic hemodialysis centers and to determine the association between burnout and nurses' intentions to leave their jobs. Findings indicate that predictors were associated with an increased likelihood of nurse burnout and that nurses experiencing burnout were more likely to be planning to leave their jobs. Findings have important implications for retention of nurses, enhancement of patient safety, and adherence to new federal staffing requirements in chronic hemodialysis units.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.090
GPT teacher head0.493
Teacher spread0.403 · 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