The role of empathy and emotional intelligence in nurses’communication attitudes using regression models andfuzzy-set qualitative comparative analysis models

dc.contributor.authorGiménez Espert, María del Carmen
dc.contributor.authorPrado Gascó, Vicente Javier
dc.date.accessioned2018-10-29T17:24:35Z
dc.date.available2018-10-29T17:24:35Z
dc.date.issued2018
dc.description.abstractAims and objectives: To analyse link between empathy and emotional intelligence as a predictor of nurses' attitudes towards communication while comparing the contribution of emotional aspects and attitudinal elements on potential behaviour. Background: Nurses' attitudes towards communication, empathy and emotional intelligence are key skills for nurses involved in patient care. There are currently no studies analysing this link, and its investigation is needed because attitudes may influence communication behaviours. Design: Correlational study. Method: To attain this goal, self-reported instruments (attitudes towards communication of nurses, trait emotional intelligence (Trait Emotional Meta-Mood Scale) and Jefferson Scale of Nursing Empathy (Jefferson Scale Nursing Empathy) were collected from 460 nurses between September 2015-February 2016. Two different analytical methodologies were used: traditional regression models and fuzzy-set qualitative comparative analysis models. Results: The results of the regression model suggest that cognitive dimensions of attitude are a significant and positive predictor of the behavioural dimension. The perspective-taking dimension of empathy and the emotional-clarity dimension of emotional intelligence were significant positive predictors of the dimensions of attitudes towards communication, except for the affective dimension (for which the association was negative). The results of the fuzzy-set qualitative comparative analysis models confirm that the combination of high levels of cognitive dimension of attitudes, perspective-taking and emotional clarity explained high levels of the behavioural dimension of attitude. Conclusions: Empathy and emotional intelligence are predictors of nurses' attitudes towards communication, and the cognitive dimension of attitude is a good predictor of the behavioural dimension of attitudes towards communication of nurses in both regression models and fuzzy-set qualitative comparative analysis. In general, the fuzzy-set qualitative comparative analysis models appear to be better predictors than the regression models are. Relevance to clinical practice: To evaluate current practices, establish intervention strategies and evaluate their effectiveness. The evaluation of these variables and their relationships are important in creating a satisfied and sustainable workforce and improving quality of care and patient health.spa
dc.description.filiationUEVspa
dc.description.impact1.757 JCR (2018) Q1, 28/120 Nursingspa
dc.description.impact0.768 SJR (2018) Q1, 18/152 Nursing (miscellaneous); Q2, 836/2844 Medicine (miscellaneous)spa
dc.description.impactNo data IDR 2018spa
dc.description.sponsorshipSin financiaciónspa
dc.identifier.citationGiménez Espert, M. C., & Prado Gascó, V. J. (2018). The role of empathy and emotional intelligence in nurses’ communication attitudes using regression models and fuzzy‐set qualitative comparative analysis models. Journal of Clinical Nursing, 27(13-14), 2661-2672. https://doi.org/10.1111/jocn.14325spa
dc.identifier.doi10.1111/jocn.14325
dc.identifier.issn0962-1067
dc.identifier.issn1365-2702
dc.identifier.urihttp://hdl.handle.net/11268/7527
dc.language.isoengspa
dc.peerreviewedSispa
dc.relation.publisherversionhttp://ezproxy.universidadeuropea.es/login?url=http://dx.doi.org/10.1111/jocn.14325spa
dc.rights.accessRightsrestricted accessspa
dc.subject.uemInteligencia emocionalspa
dc.subject.uemEmpatíaspa
dc.subject.uemEnfermeríaspa
dc.subject.unescoComunicación interpersonalspa
dc.subject.unescoPersonal paramédicospa
dc.titleThe role of empathy and emotional intelligence in nurses’communication attitudes using regression models andfuzzy-set qualitative comparative analysis modelsspa
dc.typejournal articlespa
dspace.entity.typePublication

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