Which personality variable is the strongest predictor of employee engagement?

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Abstract

The purposes of this meta-analysis were (1) to examine the associations between work engagement (WE) and the personality dimensions of five-factor model and (2) to determine how much variance in WE is explained by these five factors. We performed a database search for studies related to personality traits and WE, and 36 papers that reported correlation coefficients were selected for the meta-analysis. After correcting for publication bias using the trim-and-fill method, conscientiousness had the strongest association with WE (ρ=0.41), followed by extraversion and openness to experience (0.38), neuroticism (−0.36), and agreeableness (0.27). Moreover, 30% of the WE variance could be explained by the five-factor model (R2=0.33, 95%CI=0.26–0.49) according to a path analysis using the weighted average correlation for unreliability. This proportion was higher than that from a previous meta-analysis of job satisfaction and job performance and was lower than that of personality and WE. Thus, to enhance WE, it is necessary to evaluate both the personality and the psychosocial work environment in detail.

Keywords: Five-factor model, Meta-analysis, Personality, Work engagement, Work environment

Introduction

Recently, the focus of studies relating to occupational stress/well-being has shifted from the prevention of negative mental health to the promotion of positive mental health1–3). This trend seems to be in line with the so-called positive psychology movement4–6), a rapidly growing area of psychology since the beginning of the 21st century. One of the important concepts related to this trend is work engagement (WE), which originated and has been expanded globally by researchers in the Netherlands7). WE is defined as “a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption. Rather than a momentary and specific state, engagement refers to a more persistent and pervasive affective-cognitive state that is not focused on any particular object, event, individual, or behavior”7). Currently, WE is frequently used as a positive indicator for activating not only individual workers but also the entire organization8).

Many studies on occupational stress have examined the improvement of the workplace environment. These studies on job stress are characterized by identifying the association between the workplace environment/job stressors and the mind/body of workers. However, job stress is also known to be associated with individual worker factors (e.g., demographic variables, such as gender, age, and personality), as well as the work environment. For example, in the National Institute of Occupational Safety and Health job stress model, which provides a comprehensive framework of the process from job stressors to illness, individual factors are included as buffers9). Furthermore, in the job demands-resources model, which is relatively new among occupational stress models10–12), individual factors are considered personal resources that relate to workplace resources, such as job autonomy and social support. In discussing occupational stress, therefore, it is important to focus on the individual factors of workers in addition to the workplace environment.

Personality traits have often been examined with work-related variables, and the previous studies have reported the usefulness of personality assessment in mental health measures for workers13–15). Historically, personality research had begun to determine the general or common psychological traits in humans that were relatively stable and did not change with time or environment by examining the human behavior and emotion16, 17). Personality traits reflect pervasive individual differences in emotional style and feelings about oneself, and both have a general influence on emotional responses to features and events in the environment18).

For emotion, there are two dimensions: negative affect (NA) and positive affect (PA)19). NA is a general dimension of subjective distress and unpleasurable engagement that subsumes a variety of aversive mood states, including anger, contempt, disgust, guilt, fear, and nervousness. In contrast, PA is a dimension reflecting one’s level of pleasurable engagement with the environment. High PA reflects enthusiasm, energy level, mental alertness, interest, joy, and determination. These two factors represent affective state dimensions, but they are related to corresponding affective trait dimensions of negative and positive emotionality (individual differences in positive and negative emotional reactivity)19–21). At the trait level, NA is a broad and pervasive predisposition to experience negative emotions that has further influences on cognition, self-concept, and world view20, 21). Trait PA is a corresponding predisposition conducive to positive emotional experience; it reflects a generalized sense of well-being and competence, and of effective interpersonal engagement20, 21). Trait NA and PA roughly correspond to the dominant personality factors of neuroticism and extraversion among five-factor model, respectively19, 20, 22).

The personality factors have been found to be related not only to general emotions such as NA and PA but also to emotional states experienced by working14, 23, 24). For burnout which was defined as a work-related state of mind25), neuroticism consistently and strongly associated with it14, 26). On the other hand, for WE, which has been advocated as an opposite concept of burnout7), the relationship between personality and it has been discussed as well as burnout. Langelaan et al. attempted to distinguish between WE and burnout using personality variables24). The results indicated that burnout was characterized by high neuroticism alone, whereas WE was characterized by low neuroticism with high extraversion and mobility of temperament. Additionally, some personality traits were found to be strongly associated with WE than burnout27, 28). Iwata et al.29), comparing the factor structure of STAI between Japanese and Western individuals, have suggested that positive emotions in Japanese were largely determined by personality traits. In other words, the relationship between positive emotions and personality seems to vary across cultures. Based on the above, work engagement, which reflected positive emotions in related work, would be strongly affected by workers’ personality traits. Therefore, it seemed necessary to estimate the average-level of the relationship between work engagement and personality.

Young et al.30) recently reported a comprehensive meta-analysis specific to the relationships of WE with a wide range of personality measures, such as the five-factor model, positive and negative affectivity, and proactive personality. Young et al.’s results30) reveal that the overall components of these personality traits explain 48.1% of the variance in WE; thus, using personality assessments is recommended as an intervention strategy for enhancing WE. The results are very high compared to meta-analyses that have examined relationships between personality and burnout14). Young et al.’s meta-analysis30) provides fruitful evidence for the relationship between personality and WE; it seems to be overestimated because of the overlapping personality concepts used in the analysis (e.g., correlation between extraversion in the five-factor model and positive affectivity).

Accordingly, in the present study, we perform a meta-analysis on the relationships between the five-factor model only and WE again. There are two reasons for selecting the five-factor model among many personality theories. First, the five-factor model is the most widely used personality theory, and there is consensus among personality researchers that this model can measure overall personality31–34). Second, before WE originated7), the associations of job satisfaction and job performance, which are positive indicators related to work, had been examined using a five-factor model35–38). Young et al.’s30) meta-analysis does not consider the differences between WE and job satisfaction or job performance in light of the association of the personality dimensions, although a statistical analysis of the relationships between five-factor traits and WE is conducted.

In this study, we conduct a meta-analysis of the relationship between the five-factor model and WE and examine how this relationship differs from that between the five-factor model and job satisfaction35, 36) or job performance37, 38) as previously studied. In addition, we clarify the extent to which the five-factor model alone explains the variance in WE and examine mental health measures related to WE improvement from the perspective of personality theory.

The purpose of the present study is twofold:

1. To clarify the relationship between each subfactor of the five factors and WE and to discuss the characteristics of WE from the perspective of personality theory by comparing job satisfaction and job performance, which have been examined in association with the five-factor model.

2. To determine the extent to which the five-factor model explains the overall variance in WE and to discuss effective measures to improve the WE of workers.

Methods

Literature Search and Inclusion Criteria

Although the engagement at work has been conceptualized variously7, 25, 39, 40), we focused on the WE concept proposed by Schaufeli et al.7) in 2002, because of its most frequently used in scientific research fields to date1–3). Therefore, we searched PsycINFO in December 2020 to retrieve articles published from 2002 to 2020. A combination of keywords related to personality and WE was used in this search. For the five-factor personality model, the keywords “five-factor model”, “Big Five”, “neuroticism”, “extraversion”, “conscientiousness”, “agreeableness” and “openness to experience” were used. In the database search, we set two search options: (1) peer-reviewed articles in English and (2) the keyword “workers”. We retrieved 29 papers for the five-factor model, 60 for the Big Five, 40 for neuroticism, 30 for extraversion, 52 for conscientiousness, 21 for agreeableness, and 22 for openness to experience.

All abstracts of these papers were read to perform the meta-analysis. The inclusion criteria were as follows: (1) the correlation coefficient between a personality trait and WE was reported; (2) WE was measured using the Utrecht Work Engagement Scale7), which is the most commonly used tool to measure WE; (3) the survey participants were general workers, not a clinical sample (e.g., workers with cancer); and (4) studies simultaneously measured both personality and WE. We excluded studies that reported only correlations between latent variables in the structural equation modeling. These inclusion criteria yielded a total of 36 papers and 125 correlation coefficients. The number of retrieved correlations varied in terms of the factors because all five factors were not necessarily used in the studies.

Coding

We coded the dispositional correlations of WE. Although WE consists of three subscales7, 8), in the present study, we examine the relationship between the total WE score and personality for the sake of brevity and logical consistency. Therefore, if the correlation coefficients were reported separately for each WE subscale, the mean value of these correlations was entered. Following Kim et al.28), who uses the four subscales of WE, including professional efficacy of burnout, we coded the mean value of the three main subscale correlations after excluding professional efficacy.

Meta-analytic Procedure

To combine the correlations, we used the random effect model, which does not assume homogeneity of effect sizes across studies. The data were combined after the correlation coefficients (r) were transformed to z-values. We used the “metafor” package41) of R. The weighted average correlations were then calculated using Hunter and Schmidt’s method42), which can correct for artifacts using the reliability coefficient of the measurement scale. However, some of the studies included in this meta-analysis do not report the reliability coefficients of the scales. Following Young et al.30), we used Viswesvaran and Ones’ results (i.e., 0.78 for neuroticism, 0.78 for extraversion, 0.78 for conscientiousness, 0.75 for agreeableness, and 0.73 for openness to experience)43) for the five-factor model and Christian et al.’s finding for the WE reliability coefficient (i.e., 0.88)44).

We computed the weighted average correlation between each personality variable and the WE. To examine the effect of publication bias, we also calculated the value corrected using the trim-and-fill method. Using the estimators R0 and L045), we estimated the number of studies excluded in this meta-analysis based on asymmetry in a funnel plot. The L0 indicated that six studies did not publish the correlation between neuroticism and WE; similarly, there was one study for conscientiousness and six studies for openness to experience. Extraversion and agreeableness showed no publication bias. We computed the average effect size by correcting for the publication bias.

Path Analysis using Averaged Effects

Using the weighted average correlations estimated by the meta-analysis, a path analysis was performed to examine how much variance in WE is explained by the five-factor model. The SEM package46) of R was used for the analysis.

First, of the papers included in this meta-analysis, correlations using all the subscales of the five-factor model were extracted (k=18, N=10,197). Then, the weighted average correlations between each subscale of the five-factor model were calculated using the random effect model and Hunter and Schmidt’s method42) following the same procedure described previously. Finally, a path analysis was carried out using two types of weighted average correlations: inter-subscales of the five-factor model and between the five-factor model and WE. We also performed a path analysis using the upper and lower limits of the 95% confidence interval (95%CI). A model comprising the path from the five-factor model to the WE and the intercorrelations between factors was used in the SEM. The sample size was set to N=10,197.

Results

Meta-analysis on the Association of the Five-Factor Model with WE

The results of the meta-analysis of the association of the five factors with WE are shown in Table 1. For all personality traits, the 95%CI of the mean correlations (ρ) do not include zero, indicating that these personality traits are significantly correlated with WE. According to Table 1, conscientiousness has the strongest association with WE (ρ=0.41), followed by extraversion and openness to experience (0.38), neuroticism (−0.36), and agreeableness (0.27).

Table 1.

Meta-analysis for the association of five-factor model to work engagement

kNrSE rρSE ρ95%CI ρQpI 2Neuroticism2615,989-0.280.03-0.360.03-0.43–-0.30203.460.0083.7Extraversion2616,1660.310.040.380.040.30–0.47271.690.0090.1Conscientiousness3418,8240.330.030.410.030.34–0.47225.270.0084.0Agreeableness2012,2150.210.040.270.040.18–0.35145.200.0085.4Openness to experience1910,4210.250.060.380.070.24–0.53459.950.0094.2

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Note 1. k=number of correlations; N=total sample size; r=average-weighted correlation; SE=standard error; ρ=average-weighted correlation corrected for unreliability; CI=confidence interval.

Note 2. ρ for neuroticism, conscientiousness and openness to experience represents the corrected values for publication bias.

Regarding statistical heterogeneity, the Q statistics across all variables are significantly high. All the I2 statistics between the five factors and WE are high, suggesting the existence of significant heterogeneity across all personality variables included in this meta-analysis. Among the five factors, openness to experience is very high.

Path Analysis using Averaged Intercorrelations

The results of the path analysis using the averaged correlation coefficients estimated by the meta-analysis are presented in Table 2. Only the 95%CI of the path coefficients in agreeableness include zeros. The 95%CI of the other path coefficients do not include zero, indicating that the four coefficients are significant. The five-factor model explains 33% of the variance in WE (R2=0.33, 95%CI=0.26–0.49). Of the five components of personality, conscientiousness and openness to experience are the strongest predictors of WE (β=0.25), followed by extraversion (0.17), neuroticism (−0.16), and agreeableness (0.03).

Table 2.

Path coefficients of five-factor model to work engagement (N=10,197)

path coefficient / β95%CINeuroticism−0.16−0.32–−0.02Extraversion0.170.12–0.24Conscientiousness0.250.18–0.31Agreeableness0.03−0.06–0.10Openness to experience0.250.14–0.37

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R 20.330.26–0.49

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Discussion

Association of the Five Factors with WE

Comparing the meta-analysis of the relationships between job satisfaction and the five-factor model35, 36) to the present study, two distinct differences are observed between WE and job satisfaction. First, extraversion shows a stronger association with WE than with job satisfaction. Job satisfaction and WE share a positive effect; however, for the former, it refers to a low-intensity effect (e.g., contentment), whereas for the latter, it refers to a high-intensity effect (e.g., excitement)8). The difference in the associations between WE and extraversion might reflect the difference in the magnitude of the positive effect.

Second, WE is associated with openness to experience, whereas job satisfaction is not35, 36). Our results regarding the association between openness and WE are consistent with those of Schaufeli’s study47). Openness includes active imagination, preference for variety, and intellectual curiosity22, 32). Therefore, individuals with higher openness may be more likely to perceive enjoyment in daily work and experience a sense of significance, enthusiasm, inspiration, and challenge. Additionally, based on the findings of Vaughn et al.48) and Van Beek et al.49), Schaufeli47) reports that engaged employees are likely to look for growth opportunities and have the disposition to be open to experiences. Accordingly, openness might be associated more with WE, indicating higher activation at work than with job satisfaction.

Since Barrick and Mount’s37) and Hurtz and Donovan’s38) studies revealed that conscientiousness is consistently associated with job performance across a variety of occupations, conscientiousness has been regarded as an important factor that predicts success at work34). In addition, the two factors of neuroticism and extraversion are considered to be important factors associated with subjective well-being and life satisfaction, which are positive concepts for life in general50, 51). Considering that WE is associated with job performance and well-being52, 53), conscientiousness, which implies earnestness and planned goal attainment, is an important personality factor associated with WE, along with neuroticism and extraversion.

Variance in WE Explained by the Five-Factor Model

In the present meta-analysis, the five-factor model explains nearly 30% of the variance in WE. This finding is slightly higher than other studies reporting that the five-factor model explains roughly 10%–20% of the variance in job satisfaction35, 36). As for job performance, although it has not been reported directly how much the five-factor model explains the variance of job performance in the papers, it could be calculated that it is less than this study from the correlation coefficients (Barrick and Mount, 1991: ρ for emotional stability=0.08, extraversion=0.13, openness to experience=0.04, agreeableness=0.07, conscientiousness=0.22; Hurtz and Donovan, 2001: emotional stability=0.14, extraversion=0.10, openness to experience=0.07, agreeableness=0.13, conscientiousness=0.22)37, 38). Furthermore, the results of this study are lower than those reported by Young et al.30), which is nearly half for all personality variables used and nearly 40% for the five-factor model only. Thus, WE seems to be more susceptible to personality than the concepts of job satisfaction and job performance, which have been verified to be associated with personality traits. However, WE and personality might not be as associated, as Young et al. argues30).

Young et al. suggests that the use of a personality-based personnel selection system might be effective because a series of intervention strategies that were developed to improve WE have not been effective30, 54). However, a five-year longitudinal study by Wu55) indicates that an increase in time demand for work predicts an increase in neuroticism and a decrease in extraversion and conscientiousness. In addition, it shows that an increase in job control predicts an increase in agreeableness, conscientiousness, and openness to experience. In other words, even if workers are employed using personality indicators related to WE, their personalities may change depending on the work environment. Therefore, it can be said that whether personality indicators related to WE are useful depends on the work environment.

The results of this study show the need to improve WE and evaluate both personality and the psychosocial work environment. Efforts to make job resources abundant for improving WE have led to the use of personal resources related to the WE of workers56). Therefore, it is necessary to examine the association between workers’ personalities and the psychosocial work environment in the future.

Limitations

This study has some limitations. First, it should be noted that the number of correlation coefficients used in our meta-analysis is smaller than Young et al.’s one30). Because in the present meta-analysis, the database used to extract the correlation coefficients is PsycINFO only, and published papers were used only in the analysis. In addition, because there are only a small number of correlations between the subfactors of WE and the five-factor model, their relationships have not been analyzed. Second, we could not examine the causal relationship between personality and WE because the studies analyzed in this meta-analysis employ a cross-sectional design. Third, the results of this meta-analysis show that heterogeneity is high in all personality variables, especially in openness. Finally, because no mediation analysis is conducted in this study, other variables may be involved in the relationship between personality and WE.

In this study, by using a five-factor model, we examined the direct relationship between workers’ personality and WE. However, Bakker et al. reported that, in the job demands-resources model, personality would not only modify the relationship between job demands and stress responses, but also the relationship between job resources and WE11). Therefore, to study the modifying effects of personality, such as strengthening or weakening the relationship between job resources and WE, we need to examine the interaction between personality and job resources in the future.

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Appendix Table 1.

Selected literatures analyzed in this study

No.AuthorsYearJournalCountryWorkers / OccupationnCorrelation Coefficients with WEPersonality Scale · Reliability EstimatesReliability
Estimate of
UWES

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NECAONECAO1Langelaan et al.2006Personality and
Individual DifferencesNetherlandsvarious occupations
(white- and blue-collar workers)572-0.440.41NEO-FFI0.820.780.872Mostert & Rothmann2006Journal of
Criminal JusticeSouth Africapolice1,794-0.290.330.380.26PCI0.800.710.860.810.893Kim et al.2009International Journal of
Hospitality ManagementUnited Statesrestaurant chain187-0.110.090.300.150.02IPIP0.850.860.770.810.800.784Halbesleben et al.2009Journal of
Applied PsychologyUnited Statesa federal fire department800.35IPIP0.890.955Halbesleben et al.2009Journal of
Applied PsychologyUnited Statesvarious occupations
(white- and blue-collar workers)5130.35IPIP0.740.906Halbesleben et al.2009Journal of
Applied PsychologyUnited Stateshairstylists2510.20IPIP0.910.937Joseph et al.2011The International Journal for
the Psychology of ReligionIndiacatholic diocesan priest511-0.500.480.440.48-0.02NEO-FFI0.720.720.810.750.460.898Wefald et al.2011Journal of Leadership &
Organizational StudiesUnited Statesemployees and managers of financial
institution382-0.260.390.330.400.27BFI0.790.850.810.790.800.939*Rossier et al.2012Journal of
Vocational BehaviorSwitzerlandemployees108-0.210.360.450.22-0.07NEO-FF-R0.870.720.750.780.750.9210Bakker et al.2012Journal of
Vocational BehaviorNetherlandschemical industry, consultancy and
personnel agencies, telemarketing,
education, catering service1440.32FFPI0.930.8411Sulea et al.2012Career Development
InternationalRomaniapublic water services and sanitation,
food manufacturing, a city hall2580.39DECAS Personality
Inventory0.710.9012Sulea et al.2012Psihologia
Resurselor UmaneRomaniavarious organization
(education, engineering)2230.25Mowen’s
personality scale0.830.8013Zaidi et al.2013African Journal of
Business ManagementPakistanuniversity teacher399-0.070.240.310.150.44BFI0.78a0.78a0.78a0.75a0.73a0.88b14Woods & Sofat2013Journal of Applied
Social PsychologyUnited Kingdomvarious occupations
(mainly white-collar workers)238-0.310.320.360.240.28BFI-V440.820.830.800.750.780.9215Brock et al.2013International Journal of
Selection and AssessmentUnited Statesemployees446-0.200.280.280.140.06Goldberg’s unipolar
big-five markers0.770.810.780.850.760.9116**Gan & Gan2014Stress HealthChinaIT company160-0.200.210.12NEO-FFI0.78a0.78a0.78a0.7417Vîrga et al.2015Journal of
Personnel PsychologyRomaniawhite-collar
(education, IT, other domain)223-0.140.040.29Mowen’s
Personality Scale0.840.800.830.9118Pocnet et al.2015Swiss Journal of
PsychologySwitzerlandSwiss and foreign workers working
in Switzerland618-0.270.290.290.110.21NEO-FFI-R0.830.750.820.680.720.9319Akhtar et al.2015Personality and
Individual DifferencesUnited Kingdomworkers in a wide range of sectors
(Education, Technology, Health)1,050-0.200.240.200.120.31TIPI0.570.630.470.250.450.9020Zecca et al.2015Revue européenne de
psychologie appliquéeSwitzerlandFrench-speaking employees
(various occupations)450-0.280.360.310.050.06NEO-FFI-R0.790.690.760.740.670.9221Macsinga et al.2015The Journal of PsychologyRomaniaa regional company of public water
services, a manufacturing company
and a city hall2580.280.37DECAS Personality
Inventory0.78a0.78a0.9022Chinelato et al.2015Journal of Work and
Organizational PsychologyBrazillawyers, psychologists, teachers,
public servants,
secretaries, telemarketing, etc477-0.25BFI0.780.9323Bickerton et al.2015Psychology of Religion
and SpiritualityAustraliaministers or chaplains,
cross-cultural workers,
youth workers and others617-0.390.510.310.250.11NEO-FFI0.860.830.850.760.730.7824Bayl-smith & Griffin2015Journal of Vocational BehaviorAustraliawhite- and blue-collar workers4650.26Goldberg’s unipolar
big-five markers0.860.9325*Srivastava et al.2015Information Systems JournalMulti-nationalsenior organizational managers152-0.130.060.210.11-0.01BFI-S, TIPI0.800.780.830.830.770.9426Ozbilir et al.2015Applied PsychologyCanada and
TurkeyCanada) healthcare, administrative/
support services, finance, accounting
Turkey) education/child care,
heathcare, advertising269
(155 Canadan,
114 Turkish)0.36IPIP0.820.9527Schaufeli2016Journal of
Managerial PsychologyNetherlandsvarious companies and occupations1,973-0.290.180.160.180.45Mowen’s
Personality Scale0.810.830.870.780.890.9128Mróz & Kaleta2016International Journal of
Occupational Medicine and
Environmental HealthPolandnurse, waitress, receptionist, seller,
guide, coach, account advisor137-0.150.230.220.060.14NEO-FFI0.750.750.750.750.750.8529Lorenz et al.2016Plos OneGermanyemployees, self-employed workers,
temporary workers202-0.230.310.370.170.33BFI-S0.700.700.550.370.590.9530**Bear et al.2016Stress HealthUnited Statesdelivery driver, lawyer, event planner5090.33HEXACO-600.810.9531Zis et al.2016NeurologyGreeceneurology trainees113-0.25NEO-FFI0.78a0.88b32Yu et al.2017PsyCh JournalChinaemployees from a petrochemical
enterprise263-0.250.170.370.140.21BFI-100.600.660.580.560.540.8633Blatný et al.2018Studia PsychologicaCzech Republicacademic workers2,229-0.240.160.23BFI-100.640.510.440.9134Agarwal & Gupta2018Personal ReviewIndiamanagerial employees1,3020.26BFI0.670.8835Wojtkowska et al.2018Current PsychologyPolandoffice workers200-0.230.140.130.080.19TIPI0.78a0.78a0.78a0.75a0.73a0.9236Burtaverde & Iliescu2019Career Development
InternationalRomaniaemployees from various professional
areas (human resources, sales,
marketing, administration)224-0.400.470.380.410.39BFI0.830.880.830.770.840.9337Peng & Tseng2019The Journal of PsychologyTaiwannurses2340.37IPIP0.950.9138Sørlie et al.2020Military PsychologyNorwayleadership candidates of
the Norwegian armed forces2,264-0.240.350.440.180.15NEO-PI-30.850.790.860.750.720.88

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Note. Bold type correlations are significant at p<0.01. Bold and italic correlations are significant at p<0.05. *: p-value has not been provided. **: at least p<0.05.

aViswesvaran & Ones (2000).

bChristian et al. (2011).

Appendix Table 2.

Average-weighted intercorrelations of five factor personality (N=10,197)

Five factor personality12341. Neuroticism2. Extraversion−0.313. Conscientiousness−0.400.254. Agreeableness−0.350.190.395. Openness to experience−0.140.360.160.22

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Which of the following is the strongest predictor of employee engagement?

Which personality variable is positively related to learning outcomes?

Which of the Big Five personality dimensions is most strongly correlated to job performance?

Which factor in the five factor model of personality is most strongly related to organizational commitment?