Research and valid practice in emotional intelligence (EI) have been impeded by lack of theoretical clarity regarding (a) the relative roles of emotion perception, emotion understanding, and emotion regulation facets in explaining job performance; (b) conceptual redundancy of EI with cognitive intelligence and Big Five personality; and (c) application of the EI label to 2 distinct sets of constructs (i.e., ability-based EI and mixed-based EI). In the current article, the authors propose and then test a theoretical model that integrates these factors. They specify a progressive (cascading) pattern among ability-based EI facets, in which emotion perception must causally precede emotion understanding, which in turn precedes conscious emotion regulation and job performance. The sequential elements in this progressive model are believed to selectively reflect Conscientiousness, cognitive ability, and Neuroticism, respectively. "Mixed-based" measures of EI are expected to explain variance in job performance beyond cognitive ability and personality. The cascading model of EI is empirically confirmed via meta-analytic data, although relationships between ability-based EI and job performance are shown to be inconsistent (i.e., EI positively predicts performance for high emotional labor jobs and negatively predicts performance for low emotional labor jobs). Gender and race differences in EI are also meta-analyzed. Implications for linking the EI fad in personnel selection to established psychological theory are discussed.
Recent estimates suggest that although a majority of funds in organizational training budgets tend to be allocated to leadership training (Ho, 2016; O'Leonard, 2014), only a small minority of organizations believe their leadership training programs are highly effective (Schwartz, Bersin, & Pelster, 2014), calling into question the effectiveness of current leadership development initiatives. To help address this issue, this meta-analysis estimates the extent to which leadership training is effective and identifies the conditions under which these programs are most effective. In doing so, we estimate the effectiveness of leadership training across four criteria (reactions, learning, transfer, and results; Kirkpatrick, 1959) using only employee data and we examine 15 moderators of training design and delivery to determine which elements are associated with the most effective leadership training interventions. Data from 335 independent samples suggest that leadership training is substantially more effective than previously thought, leading to improvements in reactions (δ = .63), learning (δ = .73), transfer (δ = .82), and results (δ = .72), the strength of these effects differs based on various design, delivery, and implementation characteristics. Moderator analyses support the use of needs analysis, feedback, multiple delivery methods (especially practice), spaced training sessions, a location that is on-site, and face-to-face delivery that is not self-administered. Results also suggest that the content of training, attendance policy, and duration influence the effectiveness of the training program. Practical implications for training development and theoretical implications for leadership and training literatures are discussed. (PsycINFO Database Record
As the nature of work becomes more complex, teams have become necessary to ensure effective functioning within organizations. The healthcare industry is no exception. As such, the prevalence of training interventions designed to optimize teamwork in this industry has increased substantially over the last 10 years (Weaver, Dy, & Rosen, 2014). Using Kirkpatrick's (1956, 1996) training evaluation framework, we conducted a meta-analytic examination of healthcare team training to quantify its effectiveness and understand the conditions under which it is most successful. Results demonstrate that healthcare team training improves each of Kirkpatrick's criteria (reactions, learning, transfer, results; d = .37 to .89). Second, findings indicate that healthcare team training is largely robust to trainee composition, training strategy, and characteristics of the work environment, with the only exception being the reduced effectiveness of team training programs that involve feedback. As a tertiary goal, we proposed and found empirical support for a sequential model of healthcare team training where team training affects results via learning, which leads to transfer, which increases results. We find support for this sequential model in the healthcare industry (i.e., the current meta-analysis) and in training across all industries (i.e., using meta-analytic estimates from Arthur, Bennett, Edens, & Bell, 2003), suggesting the sequential benefits of training are not unique to medical teams. Ultimately, this meta-analysis supports the expanded use of team training and points toward recommendations for optimizing its effectiveness within healthcare settings. (PsycINFO Database Record
Recent empirical reviews have claimed a surprisingly strong relationship between job performance and self-reported emotional intelligence (also commonly called trait EI or mixed EI), suggesting self-reported/mixed EI is one of the best known predictors of job performance (e.g., ρ = .47; Joseph & Newman, 2010b). Results further suggest mixed EI can robustly predict job performance beyond cognitive ability and Big Five personality traits (Joseph & Newman, 2010b; O'Boyle, Humphrey, Pollack, Hawver, & Story, 2011). These criterion-related validity results are problematic, given the paucity of evidence and the questionable construct validity of mixed EI measures themselves. In the current research, we update and reevaluate existing evidence for mixed EI, in light of prior work regarding the content of mixed EI measures. Results of the current meta-analysis demonstrate that (a) the content of mixed EI measures strongly overlaps with a set of well-known psychological constructs (i.e., ability EI, self-efficacy, and self-rated performance, in addition to Conscientiousness, Emotional Stability, Extraversion, and general mental ability; multiple R = .79), (b) an updated estimate of the meta-analytic correlation between mixed EI and supervisor-rated job performance is ρ = .29, and (c) the mixed EI-job performance relationship becomes nil (β = -.02) after controlling for the set of covariates listed above. Findings help to establish the construct validity of mixed EI measures and further support an intuitive theoretical explanation for the uncommonly high association between mixed EI and job performance--mixed EI instruments assess a combination of ability EI and self-perceptions, in addition to personality and cognitive ability.
This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.