Over the past several decades, the concept of emotional intelligence has once again become popular (Cherniss, 2010). Social intelligence was defined by Thorndike (1920) as “the ability to understand and manage men and women, boys and girls, and to act wisely in human relations” (p. 48). Those initial studies helped contribute to the development of the concept of emotional intelligence. Gardner (1993) proposed a multiple intelligence theory with seven intelligence domains, two of which were interpersonal and intrapersonal intelligence.

Salovey and Mayer (1989) defined emotional intelligence (EI) as “the subset of social intelligence that involves the ability to monitor one’s own and others’ feelings and emotions, to discriminate among them and to use this information to guide one’s thinking and actions” (p. 189). Since then multiple complementary definitions of EI have been proposed (Ciarrochi, Chan, & Caputi, 2000). Although research definitions are not immune to overinclusiveness, the majority of attempts to operationalize EI have begun from some conceptual analysis of the construct. The four-branch model developed by Mayer, Salovey, and Caruso (2000a) is the best-known and most influential conceptualization of this kind. Mayer, Salovey, and Caruso (2000b) separated ability models, in which EI is viewed as a standard intelligence, from mixed models, in which EI is more broadly defined as a package of personal qualities, including both abilities and personality traits that facilitate expression of EI. A further conceptualization is trait EI (Petrides & Furnham, 2003), in which EI is embedded exclusively within the personality domain, and, thus, EI is separated rather sharply from abilities as usually defined.

Instruments commonly used to measure EI include the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT; Mayer, Salovey, & Caruso, 2002), Emotional Quotient Inventory (EQ-I; Bar-On, 1997), Emotional Competence Inventory (ECI; Goleman, 1998), Emotional Intelligence Appraisal (EIA; Bradberry et al., 2003), Work Profile Questionnaire–Emotional Intelligence Version (WPQ; Jordan, Ashkanasy, Härtel, & Hooper, 2002), Levels of Emotional Awareness Scale (LEAS; Lane, Quinlan, Schwartz, Walker, & Zeitlin, 1990), and Self-Report Emotional Intelligence Test (SREIT; Schutte et al., 1998). The MSCEIT is a performance-based measure in which specific tasks are used to measure the level of ability of each branch of the EI model developed by Mayer, Salovey, and Caruso (2000a). Bar-On (1997) used 133 self-report items to measure total intelligence quotient and the five components of his EI model in the EQ-I. The ECI is another self-report measure, developed by Goleman (1995). It is a multirater instrument in which ratings are provided on a series of behavioral indicators of EI. Goleman devised two main measures of EI – the EIA and WPQ – to measure the four components of his EI model.

Although there is some evidence supporting the reliability and validity of these commonly used instruments (Zeidner, Roberts, & Matthews, 2008), some basic limitations and shortcomings have been reported by researchers, including weak content validity, unstable factor structures, and lack of empirical support for either divergent or convergent validity (Conte, 2005; Matthews, Emo, Roberts, & Zeidner, 2006). Recently, the cross-cultural adaptability of the EI tests has been the subject of much attention (Gunkel, Schlägel, & Engle, 2014; Wong, Wong, & Law, 2007), as researchers have suggested that the best known EI questionnaires, such as the MSCEIT, may lack cultural adaptability. As Wong, Law, and Wong (2004) observed: “First, cultural norms may affect the individual’s selections in performance tests. For example, the Asian culture places a cultural emphasis on emotional suppression and regulation, while Westerners are more likely to express their emotions. Thus, in a conflict scenario with authority in the workplace, a high EI response in the Chinese culture would entail a nonreactive response, while an argumentative or active dialogue may be more tolerated in the Western culture. Secondly, the correct item scores depend on the reference group or experts on EI, and the selection of either could be biased by the social desirability of the cultural norms” (p. 538). The cultural dimension of individualism–collectivism could be used to illustrate emotional intelligence skills differences between China and Western countries. For example, emotional expression is more important than emotional differentiation (a determinant of interpersonal sensitivity) in interpersonal relations in individualistic cultures, while in collectivistic cultures like China, people are more likely to display a nonconfrontational, indirect attitude towards conflict (Kang, Shaver, Sue, Min, & Jing, 2003). In light of these considerations, an EI measure that is developed in China would successfully facilitate EI research in China and other Asian countries.

Wong et al. (2004) developed a 40-item forced-choice EI scale that they called Wong’s Emotional Intelligence Scale (WEIS), for use with Chinese people. The WEIS is based on the definition of EI in four domains (Davies, Stankov, & Roberts, 1998). These domains are: (a) self emotional appraisal (SEA), which reflects the ability of an individual to both perceive and freely communicate his/her own emotions. Individuals with high SEA scores are well connected to their emotional state; (b) other’s emotional appraisal (OEA), reflecting the ability of an individual to perceive and understand the emotions of others. People with high OEA scores are highly attuned to the emotional state of those around them and can anticipate others’ thoughts, feelings, and needs; (c) regulation of emotion (ROE), reflecting the ability of an individual to responsibly manage his/her emotional state, particularly after intensive stress. Individuals with high ROE are able to more quickly return to a normal state from emotional climax and distress and can maintain behavior even in the midst of distress or extreme moods; (d) use of emotion (UOE), which reflects the ability of an individual to direct his/her emotions to constructive activities and personal performance. A person with high UOE mostly maintains positive emotions and can use his/her emotional state to achieve success in professional and personal aspects of his or her life.

Wong et al (2004) showed that the WEIS has acceptable reliability, and convergent and discriminant validity. However, previous researchers have focused on Hong Kong Chinese employees in a workplace setting only (Wong et al., 2007) and further evidence is required to test the validity in other samples in China.

Our purpose in this study was to evaluate the reliability and validity of the WEIS with a sample of Chinese nurses. EI plays a much more significant role in high-emotional-labor jobs, such as nursing, compared with low-emotional-labor jobs, such as assembly-line workers. In the current literature researchers have demonstrated that EI concepts are relevant to nursing practice, and EI might impact decision making and analysis in this workplace setting. Leaders who are proficient in EI have an impact on their employees, and, in the setting of nursing, on patient care and patient outcomes (Bulmer Smith, Profetto-McGrath, & Cummings, 2009). Shanta and Gargiulo (2014) suggested that EI is a crucial component in the nurse’s ability to provide holistic care for patients, peers, and themselves. Sharif, Rezaie, Keshavarzi, Mansoori, and Ghadakpoor (2013) showed that teaching EI improved the general health of nurses working in an intensive care unit. China has the highest population of any country in the world, and the nurse population in China is approximately 2.24 million. Many researchers have shown that EI plays a very important role in the process of nursing practice in China and in the health of the nurses themselves (Li, Chen, & Chen, 2012; Tao & Song, 2012). Thus, whether or not the WEIS can be applied to Chinese nurses is important for the study of the nursing profession and human resource practice in China.

Wong and Law (2002) developed the Wong and Law EI Scale (WLEIS), a self-report EI instrument that was demonstrated to have good validity and utility in studies conducted in mainland China and Hong Kong (Law, Wong, Huang, & Li, 2008). However, as a self-report instrument to measure EI, the WLEIS suffers from weaknesses in practical utility because of potentially biased responses (Wong et al., 2007). In the current study, our aim was to verify the convergent validity of the WLEIS. As questionnaire measures for EI were criticized for overlapping with standard measures of personality traits, such as the five-factor model of personality (Davies et al., 1998; Matthews, Zeidner, & Roberts, 2002), we expected that the WEIS score would have moderate correlations with the Big Five personality dimensions. We examined the predictive validity of the WEIS on related job outcomes, such as burnout (Lee & Ok, 2012) and job satisfaction (Abraham, 2000; Wong et al., 2004), after controlling for the Big Five personality dimensions and other relevant variables. We also tested the construct validity and reliability of the WEIS with a sample of Chinese nurses.

Method

Sample

The respondents in this study were 271 nurses employed at two large hospitals in the Hunan Province in China. The nurses ranged from 19 to 53 years old, with a mean age of 30.3 ± 7.2 years. Almost all of the nurses (98.2%) were female. In terms of education level, 43.2% held high school diplomas as their highest educational qualification, 45.8% held undergraduate diplomas, and 10.3% held postgraduate diplomas (data were missing for two respondents). Nearly two-thirds (64.9%) of the nurses had worked for more than 5 years in the hospital in which they were currently employed as a nurse, 29.2% for between 1 and 5 years, and 5.9% for 1 year or less. Data were collected under the instruction of trained researchers. Before the distribution of the survey forms, we contacted the nursing departments and obtained their consent. Potential respondents received an envelope containing information on the study purpose and were advised that participation was completely voluntary. Within 5 days after distribution the researchers retrieved the envelopes containing the completed surveys.

Measures

Wong’s Emotional Intelligence Scale (Wong et al., 2004). The WEIS consists of two sections. In the first part, respondents are presented with 20 situations and asked to select their likely reaction in each scenario. In the second section, respondents are presented with 20 ability pairs and asked to indicate which of the two best represents their strength. For each ability pair, one is related to EI and the other reflects another intelligence dimension. Each part is a measure of the four dimensions of EI as classified by Davies et al. (1998). The alpha coefficient of the scale in our study was .73.

Wong and Law Emotional Intelligence Scale (Wong & Law, 2002). The WLEIS contains 16 items with responses rates on a 7-point Likert-type scale (1 = totally disagree, 7 = totally agree). This scale is also based on the four-dimensional definition of EI as classified by Davies et al. (1998). The 16 items are presented in four groups of four questions to measure the different dimensions of EI: SEA, OEA, ROE, and UOE. The alpha coefficient of the scale in this study was .89.

The Minnesota Satisfaction Questionnaire (MSQ; Weiss, Dawis, & England, 1967). The MSQ is a well-regarded measure of job satisfaction. The short form of the MSQ consists of 20 items to establish the level of satisfaction that participants have about various components of their jobs. Items are rated on a 5-point Likert scale (1 = very dissatisfied to 5 = very satisfied). In the present study we employed a Chinese version of the MSQ that has been found to have good reliability and validity (Chen & Fahr, 2001; Wang, 2007). The alpha coefficient of the scale in our study was .93.

The Big Five Adjective Scale. This scale was developed by McCrae and Costa (1987). To control the length of the survey, we randomly selected six items for each of the Big Five personality dimensions from the original 80-item scale, resulting in a 30-item measure. As the original scale was in English, we used a Chinese version that went through a translation and back-translation procedure between English and Chinese. The internal consistencies ranged from .72 to .80 for the subscales in this study.

The Chinese Maslach Burnout Inventory (CMBI; Li, Zhang, & Zhao, 2004). The CMBI was translated from the original Maslach Burnout Inventory (Maslach & Jackson, 1986) and consists of 15 items divided across three subscales representing emotional exhaustion (EX; five items, e.g., “Working all day is really a strain for me,” 0 = never, 6 = every day); cynicism (CY; five items, e.g., “I doubt the significance of my work,” 0 = never, 6 = every day); and professional efficacy (PE, five reverse-scored items, e.g., “I have accomplished many worthwhile things in this job,” 0 = never, 6 = every day). The higher the CMBI score, the greater the degree of job burnout. The alpha coefficient of the scale in our study was .83.

Control variables. We controlled for some demographic variables that we speculated might affect the results, including age, marital status, and job tenure (in terms of years). Educational level was used as a proxy for academic ability (with 1, 2, and 3 indicating high school, undergraduate, and postgraduate qualifications, respectively).

Results

Reliability and Structure Validity

The descriptive statistics and correlation analysis of all the variables are presented in Table 1. The coefficient a of the 40 EI items appeared to be acceptable. To examine the structural validity of the WEIS, we conducted confirmatory factor analysis (CFA) on the 40 items (Wong et al., 2004). We created three indicators for each EI dimension by summarizing three to four items with which to measure each respective dimension. The results of calculation of the goodness-of-fit index (GFI), incremental fit index (IFI), and root mean square error of approximation (RMSEA) showed that the four-factor model did not fit well (χ² = 166.93, df = 48, GFI = .77, IFI = .78, RMSEA = .09).

Convergent, Discriminant, and Incremental Validity

As shown in Table 1, the WEIS had moderate convergence with the WLEIS, and the correlations between the WEIS scores and personality dimensions were relatively small. The average correlation of the 40 EI items and the Big Five personality dimensions ranged from .16 to .20, with an average of .18. There were no correlations between the 40 EI items and educational level. These results are similar to those of Wong et al. (2004) and indicate that the 40-item EI measure has good discriminant validity in terms of the personality dimensions and as an academic ability proxy. There were also no correlations between the 40 EI items and age.

To test the incremental predictive validity of our EI measure in relation to the Big Five personality dimensions, we performed hierarchical regressions with job satisfaction and burnout as dependent variables. Age, job tenure, marital status, and educational level were first entered into the equation as control variables. The Big Five personality dimensions were then entered, followed by EI. The results are shown in Table 2.

Discussion

EI merits increased research attention because of its impact on a variety of outcomes, including creativity, professional success, and mental and physical health (Bar-On & Parker, 2000). Most EI measurement tools have been developed in Western countries. Although the WEIS was developed and validated with samples from Hong Kong (Wong et al., 2004), its applicability to other mainland China samples has yet to be confirmed. Here we provided evidence of the validity of the WEIS in a sample of Chinese nurse from mainland China.

The results of confirmatory factor analysis of the WEIS in our study did not fit the four-factor structure applied by Wong et al. (2004). During the development of the WEIS and testing on the Hong Kong sample, Wong et al. (2004) reported factor analyses fit indices, including root mean square residual (RMR), as follows: χ² = 179.76, df = 48, GFI = .90, RMR = .051. According to Kline (1998), an χ²/df ratio smaller than 3:1 indicates that the fit of the hypothesized model is favorable, and an RMR smaller than .05 is judged as a good fit (Byrne, 2001). Thus, it can be seen that the original results also were not a very good fit for the four-factor structure. The WEIS consists of two parts, the first part of which is similar to a self-report inventory whereas the second is similar to performance-based measures. Whether or not the WEIS could measure the same structure when the two different methods of assessment are combined may need more discussion. Furthermore, just like the MSCEIT, the factor structure stability of performance-based measures has been a subject of ongoing controversy (Palmer, Gignac, Manocha, & Stough, 2005; Roberts et al., 2006). For these reasons, much more evidence on the factor structure of the WEIS may be needed before it is applied to Chinese nurses or other samples.

Our results showed that the WEIS had good convergent validity, and that EI was a much better predictor of job satisfaction than were both the Big Five personality dimensions and education level (a proxy for academic ability), which is generally consistent with the findings of Wong et al. (2004, 2007). The incremental variance of job satisfaction explained by EI was 3%. This increase in additional variance that accounted for job satisfaction is understandable because EI is moderately correlated with the Big Five personality dimensions. In addition, the correlation between job satisfaction and the personality dimensions was quite large. There are limited additional variances to be accounted for by EI. We found that EI was also a good predictor of burnout. Together, these data demonstrate that the WEIS had good predictive validity for use in a sample of Chinese nurses.

There are some limitations in our study. First, compared with the huge population of Chinese nurses, our sample size was relatively small. Future researchers could also examine the structural validity of the WEIS for occupations other than nursing. Second, we did not examine the extent of the influence of social desirability in the practical application of the WEIS. Wong et al. (2004) originally developed this measure to facilitate future EI research or assist with EI-related human resources practices in Asia. Although our results demonstrate that the WEIS had good predictive validity in the setting of a nursing workplace, social desirability is a very significant problem in practical workplace situations, such as personnel selection. One of the important advantages of the forced-choice scale over the Likert-type scale is the ability for the researcher to avoid the influences of social desirability or the participants falsifying their responses. Thus, further studies should be conducted in which the social desirability of the 80 choices is examined in the context of samples in different workplaces. Finally, evidence of cross-cultural validity in Asian countries other than China is also needed.

In conclusion, more evidence is required regarding the factor structure of the WEIS. Given its importance to job-related outcomes in workplaces in China, our findings in the present study demonstrate the potential for practical applications of the WEIS in human resource practices.

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This research was supported by the Hunan Provincial Natural Science Foundation of China (14JJ3118)

the Hunan Provincial Social Science Foundation of China (12YBA244)

the National Natural Science Foundation of China (81371492)

and the Social Science Foundation of the Ministry of Education of China (14YJCZH197).

Guangrong Xie, Department of Psychiatry, The Second Xiangya Hospital, Central South University, 86 Mid-Ren min Road, Changsha, Hunan 410011, People’s Republic of China. Email: [email protected]