An examination of the role of emotional intelligence in work and family conflict *.

Control Variables. Consistent with prior research, martial status was considered a control variable (Bruck and Allen, 2003; Carlson, 1999; Cooke and Rousseau, 1984). In addition, work satisfaction (Netermeyer et al., 1996) and importance of work (Rothbard, 2001) were controlled for since these have been found to have a significant influence on work-family conflict, Emotional Intelligence and/ or well-being--a finding that is replicated in this study (Table 1).

Dependent Variable. The General Well-Being scale (GWB), developed in 1970 for the National Center for Health Statistics, was used to measure the dependent variable of well-being. The GWB is a structured instrument for assessing self-representations of subjective well-being. Scale scores run from 14 (lowest well-being) to 110 (highest well-being) for the first 18 items as described by Fazio (1977). This measure has been validated and shown to have good psychometric properties (Fazio, 1977). Mean scores for the first 18 items of the schedule were 75 for men and 71 for women (SD = 15 and 18, respectively). An example of an item from this scale is "Have you been under or felt you were under any strain, stress, or pressure during the past month?" The internal reliability, as measured by Cronbach's alpha, for this study was .89, an acceptable level based on Nunnally's (1978) criteria of .70.

Independent Variables

Work-Family Conflict. In this study, Work-Family Conflict (WFC) was measured using an eight-item scale. The first four items in the scale measure work-interfering with family (WIF), as developed by Kopelman, Greenhaus and Connolly (1983). The last four items were developed by Burley (1989) to assess family-interfering with work (FlW). This study analyzed both directions of work-family conflict (work interfering with family (WIF) and family interfering with work (FIW) as a combined measured of overall conflict. The internal reliability for this study, as measured by Cronbach's alpha, was .89. In addition, the work-family conflict variable means and standard deviations were comparable to those found in previous work-family conflict studies.

An example of an item from the WIF scale is "On the job I have so much work to do it takes away from my personal interests." An example from the FIW scale is "I'm often too tired at work because of the things I have to do at home." These eight items have been used in other work-family conflict research (Adams et al., 1996; Judge et al., 1994).

Emotional Intelligence. The Schutte Emotional Intelligence Scale (EIS), a self-report measure, was used in this study to measure Emotional Intelligence. This scale is based on the model of Salovey and Mayer (1990), which has been labeled as the standard for "scholarly discourse" (Jordan et al., 2003). As Schutte et al. (1998) stated in the defining article of the EIS, it is a reliable, valid measure of Emotional Intelligence as conceptualized by Salovey and Mayer (1990). The EIS represents the following categories which are consistent with the Mayer and Salovey (1997) conceptualization of Emotional Intelligence: appraisal and expression of emotion in oneself and others, regulation of emotion in self and others, and utilization of emotions solving problems.

The EIS is a scale of a trait measure of Emotional Intelligence that was developed through factor analysis which showed good reliability with two different samples. Two-week test-retest reliability indicated that the scores were fairly stable over time. The EIS reported internal consistency was between .87 and .90 (Schutte et al., 1998). It consists of 33 items which assess to which extent individuals perceive, understand, regulate and harness emotions adaptively. On a five-point Likert scale (1 = strongly disagree, 5 = strongly agree) respondents rate their agreement with such items as "I am aware of my emotions as I experience them," and "I help other people feel better when they are down." The sum of all items constitutes the total score, which can range from 33-165 (higher scores indicate greater Emotional Intelligence). The internal reliability for this study, as measured by Cronbach's alpha, was .90.

Analysis

To test hypotheses 1, 2 and 3, a two-way ANOVA was used with the independent variables being Emotional Intelligence (low and high) and WFC (low and high), and the dependent variable was well-being. The independent variables were dichotomized using median splits to conduct the 2 x 2 analysis of variance on well-being. The dichotomization of the variables is consistent with prior research (Nikolaou and Tsaousis, 2002; Hammer et al., 2004). Since job satisfaction and job importance were found to be significantly correlated with the dependent variable, factorial analysis of covariance (ANCOVA) was carried out, with job satisfaction and job importance as covariates, along with marital status since prior research suggested its impact on well-being (Bruck and Allen, 2003; Carlson, 1999; Cooke and Rousseau, 1984). As covariates in the ANCOVA, any variability attributed to these variables was partialled out of the dependent variable, well-being.

RESULTS

The correlations between the three primary scales (Emotional Intelligence, work-family conflict, and well-being) and the selected variables including the control variables as well as the reliability estimates are presented in Table 1. Emotional Intelligence (M = 123.7, SD = 13.5) was correlated with well-being (r = .36), importance of work (r = .17) and negatively correlated with work-family conflict (r = -.27). Work-family conflict (M = 19.53, SD = 5.8) was also negatively correlated with well-being (r = -.35), age (r = -.15), satisfaction with work (r = -.23), and importance of work (r = -.19). Work-family conflict was significantly yet slightly correlated with number of hours the respondent worked (r = .16). In addition, well-being was positively correlated with work satisfaction (r = .33), and importance of work (r = .24).

Table 2 displays the analysis of covariance for well-being, based on Emotional Intelligence and work-family conflict. The covariates included marital status, work satisfaction, and importance of work. The overall model was significant (p < .001), accounting for 30.7% of the variance in well-being. Both main effects (Emotional Intelligence and work-family conflict) were significant (p < .001), with Emotional Intelligence accounting for 10.8% of the variance in well-being and work-family conflict accounting for 7.4% of the variance. In addition, the interaction of Emotional Intelligence and work-family conflict was also significant (p < .05).

Inspection of the means and standard errors in Table 3 found the group with high Emotional Intelligence coupled with low work-family conflict to have the highest mean for well-being (M = 81.13). In addition, respondents with low Emotional Intelligence and high work-family conflict had the lowest level of well-being (M = 63.36). Figure I provides a graph of the interaction of Emotional Intelligence and work-family conflict. Based on the results indicated in Tables 2 and 3 and Figure I, hypotheses 1, 2 and 3 could not be rejected. (1)

[FIGURE I OMITTED]

DISCUSSION

As shown, the hypotheses advanced in this study on the influence of work-family conflict and Emotional Intelligence on well-being could not be rejected. The results showed that the variables of Emotional Intelligence and work-family conflict (hypotheses 1 and 2) had significant influence on the dependent variable of well-being. Similarly, results from testing Hypothesis 3 showed a significant interaction effect between Emotional Intelligence and work-family conflict on well-being.

The results presented in this study suggest that Emotional Intelligence acts as a protector variable in the impact of work-family conflict on one's well-being. Higher Emotional Intelligence positively influenced well-being. Specifically, those individuals in this sample who had high Emotional Intelligence with low work-family conflict reported the highest well-being while those with low Emotional Intelligence and high work-family conflict reported the lowest well-being. Additionally, the results of this study showed that low Emotional Intelligence and low work-family conflict yielded similar well-being scores as those with high Emotional Intelligence and high work-family conflict. Thus, in situations where one experiences a significant amount of work-family conflict, the possession of high Emotional Intelligence will protect their well-being. This study showed that for these people, their well-being scores were very similar to those who experience low work-family conflict. Consequently, it seems that possession of high Emotional Intelligence is more important when facing work-family conflict.

This finding is consistent with past research that has theorized that high Emotional Intelligence leads to greater feelings of well-being (Goleman, 1995; Saarni, 1999; Salovey and Mayer, 1990; Salovey et al., 1995; Schutte et al., 2002). The ability to be aware of one's emotions and capable of managing them successfully will enhance one's well-being when facing work-family conflict. To help illustrate this effect, one may think of Emotional Intelligence as something one can develop to help protect them against the stress of meeting demands in both domains. It is something in one's "bag-of-tricks," if you will, that can be utilized to maintain a healthy well-being.