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Record W3208788531 · doi:10.3390/nursrep11040079

Work Environment Characteristics and Emotional Intelligence as Correlates of Nurses’ Compassion Satisfaction and Compassion Fatigue: A Cross-Sectional Survey Study

2021· article· en· W3208788531 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNursing Reports · 2021
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsUniversity of New BrunswickUniversité de Moncton
Fundersnot available
KeywordsCompassion fatigueCompassionPsychologyCross-sectional studyEmotional intelligenceJob satisfactionEmpathyBurnoutApplied psychologyClinical psychologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

This cross-sectional survey study examined the relationship between Canadian nurses’ work environment characteristics, emotional intelligence, compassion fatigue and compassion satisfaction (n = 1271). Psychological demands, decision latitude, supervisor and coworker support, and emotional intelligence (EI) were significantly correlated with nurses’ compassion satisfaction and compassion fatigue, except for two EI subscales. Furthermore, these relationships were stronger for compassion satisfaction than compassion fatigue, suggesting that they are influenced by different factors. Our results highlight the importance of creating reasonable psychological demands, empowering nurses to make decisions in their jobs, supportive relationships at work, and fostering the development of nurses’ EI.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.074
GPT teacher head0.390
Teacher spread0.315 · 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