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Record W2900364820 · doi:10.1177/0844562118809262

Hospital Nurses in Comparison to Community Nurses: Motivation, Empathy, and the Mediating Role of Burnout

2018· article· en· W2900364820 on OpenAlexvenueaboutno aff
Asnat Dor, Michal Mashiach Eizenberg, Ofra Halperin

Bibliographic record

VenueCanadian Journal of Nursing Research · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyBurnoutPsychologyNursingApplied psychologyMedicineClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Hospital nurses' experience of their profession differs from that of community clinic nurses due to different working conditions and settings. PURPOSE: To compare hospital nurses and community clinic nurses as to the mediating role of burnout on motivation and empathy. METHODS: In this cross-sectional study, 457 nurses completed four questionnaires: Demographic, Motivation Questionnaire, the Maslach Burnout Inventory, and the Toronto Empathy Questionnaire. RESULTS: Emotional exhaustion and depersonalization among hospital nurses were significantly higher than among community nurses. No significant differences were found in personal accomplishment, empathy, and motivation between the groups. Empathy and motivation were more strongly correlated among hospital nurses than among community nurses. Burnout was found to be a significant mediator between empathy and motivation in both groups but in each group by different burnout subscales. CONCLUSIONS: To reduce burnout, leaders in the nursing field must enhance conditions in the hospital nurses' work environment to lower levels of emotional exhaustion and depersonalization; community nurses should be guided to improve their attitudes toward their on-the-job performance to promote their personal accomplishment. Understanding the differences could direct policy makers' desire toward enacting policies that accommodate these differences and focus on the needs of both groups of professionals.

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)0.008
metaresearch head score (Gemma)0.007
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 score0.133
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.137
GPT teacher head0.512
Teacher spread0.375 · 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.

Study designQualitative
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

Citations38
Published2018
Admission routes2
Has abstractyes

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