A latent profile analysis of trait emotional intelligence to identify beneficial and risk profiles in well-being and job performance: a study among Japanese eldercare nurses

Toyama, Hiroyuki; Mauno, Saija

doi:10.1504/ijwoe.2016.081841

Cited by 5 publications

(8 citation statements)

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“…However, profile similarity analyses indicated that the levels and shapes were quite different. Thus, we echo previous findings demonstrating the relevance of investigating how the specific emotional intelligence dimensions differ quantitatively and qualitatively (Gohm & Clore, 2002; Keefer et al, 2012; Toyama & Mauno, 2016), especially (Gerits et al, 2005). For the women, we observed the emergence of a first Low interpersonal profile characterized by low levels of self-focused emotion appraisal and regulation and very low levels of other-focused emotion appraisal and regulation.…”

Section: Discussionsupporting

confidence: 90%

“…The results indicated that having a profile with low levels on emotional intelligence dimensions was associated with a probability of degree non-completion. Finally, Toyama and Mauno (2016) also investigated emotional intelligence using LPA and found 6 profiles based on intrapersonal, interpersonal, and situational emotional intelligence dimensions. Most profiles were low, on average, or high on the three dimensions.…”

Section: Profiles Of Emotional Intelligencementioning

confidence: 99%

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Emotional Intelligence Profiles and Job Search Correlates in the Context of the School-to-Work Transition

Pirsoul¹,

Parmentier

Nils³

2022

Journal of Career Development

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The current study adopted a person-centered approach to explore emotional intelligence profiles among 1582 university students and investigated whether different combinations of self-focused (i.e., intrapersonal) and other-focused (i.e., interpersonal) emotion appraisal and regulation emerged between women and men. We also examined the relations of these profiles with job search self-efficacy and job search clarity. Four distinct profiles emerged for the women and men that differed in terms of level and shape. Furthermore, these profiles predicted job search self-efficacy significantly for the women and men, but they predicted only job search clarity among the men. These results provide evidence about the importance of differentiating profiles of emotional intelligence between women and men and to be particularly attentive to gender stereotypes. Second, these results open new avenues for tailor-made career counseling interventions for university students facing the school-to-work transition.

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Section: Discussionsupporting

confidence: 90%

Section: Profiles Of Emotional Intelligencementioning

confidence: 99%

Emotional Intelligence Profiles and Job Search Correlates in the Context of the School-to-Work Transition

Pirsoul¹,

Parmentier

Nils³

2022

Journal of Career Development

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“…Psychological resources are mental and emotional assets that foster positive outcomes. We identified 29 psychological resources including psychological capital (Bonner, 2016), trait competitiveness (Karatepe & Olugbade, 2009), psychological empowerment (Quiñones et al, 2013), emotional intelligence (Toyama & Mauno, 2016), pride (Hakanen, Perhoniemi, & Toppinen-Tanner, 2008), and compassion (Mauno et al, 2016). Psychological capital is a developable and positive psychological state that has four facets: self-efficacy (confidence), optimism, resilience, and hope (Luthans, Youssef, & Avolio, 2007).…”

Section: Identifying Resources: Findingsmentioning

confidence: 99%

What Is a Resource: Toward a Taxonomy of Resources for Employee Engagement

Lee

Rocco

Shuck

2019

Human Resource Development Review

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Research detailing employee engagement has reliably stated that resources are significant to fostering engagement. Notwithstanding, no previous work has attempted to make meaning of those resources through a review of the existing literature. To better understand how the engagement literature positions and defines resources, we reviewed the resources term across 137 articles. The results of our structured literature review revealed that 216 distinct resources were mentioned across literature streams, and five distinct categories from macro to micro levels could be identified. The categories include (a) organizational resources, (b) social resources, (c) job resources, (d) home resources, and (e) personal resources. In addition to detailing our method and each category of resources, we explore implications for human resource development theory and practice.

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“…For example, Toyama and Mauno (2016) found that the highest overall scores on the emotional intelligence dimensions trait were associated with higher well-being and job performance profiles, while the group with lower emotional intelligence showed negative outcomes. Likewise, Ayala et al (2017) found that overqualification characterizes the unhappy-productive pattern, and Abdi et al (2019) showed that higher levels of job importance and lower levels of role ambiguity mainly differentiate the satisfied-healthy pattern.…”

Section: Review Of the Patterns Of The Relationships Reported In The mentioning

confidence: 99%

Meta-analysis and Scientific Mapping of Well-being and Job Performance

Gutiérrez¹,

Polo²,

Zambrano³

et al. 2020

Span. J. Psychol.

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In this article, we present a meta-analysis and a scientific mapping about the relationship between different types of well-being and job performance. We followed The PRISMA statement for reporting systematic reviews and meta-analyses (Moher et al., 2009), and conduct the search in Web of Science, SCOPUS, Ebscohost, Proquest, and Jstor databases. We identified 43 studies from 1994 to early 2020 that represent 45 independent samples, 34,221 participants, and 77 correlations between four types of well-being and six of job performance. Meta-analysis results show that are different forms of relations between types and there is not only one form to explain the happy-productive worker hypothesis. The scientific mapping shows that there are seven clusters of topics about well-being and job performance in the Web of Science base articles: (I) Burnout and axiety, (II) Stress and depression, (III) Individual resources, (IV) Work context, (V) Work engagement and commitment, (VI) Justice, and (VII) Human resources practices. We organize the topics from each cluster in the different groups of variables of the contextual model of individual work, well-being and performance (van Veldhoven & Peccei, 2015) to explain their impact in well-being and job performance. We included the observations of our analysis and identified the future key directions for the field.

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A latent profile analysis of trait emotional intelligence to identify beneficial and risk profiles in well-being and job performance: a study among Japanese eldercare nurses

Cited by 5 publications

References 50 publications

Emotional Intelligence Profiles and Job Search Correlates in the Context of the School-to-Work Transition

Emotional Intelligence Profiles and Job Search Correlates in the Context of the School-to-Work Transition

What Is a Resource: Toward a Taxonomy of Resources for Employee Engagement

Meta-analysis and Scientific Mapping of Well-being and Job Performance

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