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Record W2021470206 · doi:10.1177/0898264306286196

The Role of Conflict Resolution Styles on Nursing Staff Morale, Burnout, and Job Satisfaction in Long-Term Care

2006· article· en· W2021470206 on OpenAlexaff
Julián Montoro‐Rodríguez, Jeff Small

Bibliographic record

VenueJournal of Aging and Health · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBurnoutJob satisfactionNursingPsychologyCoping (psychology)Emotional exhaustionNursing staffMedicineSocial psychologyClinical psychology

Abstract

fetched live from OpenAlex

This study focuses on the ability of nursing staff to interact with residents in a way that affects positively on the nurses' well-being and occupational satisfaction. It investigates the role of coping skills related to staff-resident interactions, in particular, the use of conflict resolution styles and their influence on the level of morale, burnout and job satisfaction of nursing professionals. A self-administered questionnaire was used to collect information from 161 direct care nursing staff. The authors used a multiple regression procedure to examine the influence of predictors on nursing staff outcomes. Multivariate analyses indicated that nurses' psychological morale, occupational stress, and job satisfaction are influenced by conflict resolution styles, after controlling by individual characteristics, work demands, and work resources factors. The findings highlight the importance of considering personal coping abilities to foster positive staff-resident interactions and to increase nurses' morale and job satisfaction.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.339
Teacher spread0.319 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations57
Published2006
Admission routes1
Has abstractyes

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