A Confirmatory Factor Analysis of Dutch Work Addiction Scale (DUWAS)

Abstract

The current study contributes to the existing literature by examining the psychometric properties of Dutch Work Addiction Scale (DUWAS). Confirmatory factor analysis was carried out on the responses of public and private sector employees working in various sectors of service industries of Jammu region (India) using AMOS 16 Software package against the various dimensions of DUWAS. The results provide support for the first-order a priori 3-factor, 20-item DUWAS scale which collectively comprised second order factor called workaholism.

Keywords

Confirmatory Factor Analysis Dutch Work Addiction Scale (DUWAS)working excessively working compulsively overwork workaholism

Introduction

In today’s era, work is considered as the positive value for a person. But due to change in the nature of work brought about by technology, complex business practices, cut-throat competition from the competitors and menacing globalization, the scenario has totally changed. Employees are facing a lot of rapid and multifarious changes characterized by day-to-day challenges, extended working hours, and so on. The expansion of typical working hours due to national and international 24-hour marketplace (White et al., 2003) is adding fuel to the workaholic tendency of those employees who have propensity to work more.

The concept of workaholism introduced by Oates in 1968 is described as the compulsion or the uncontrollable need to work incessantly. This description entails two core elements of workaholism: working excessively hard and the existence of a strong, irresistible inner drive (McMillan et al., 2003). The former points to the fact that workaholics tend to allocate an exceptional amount of time to work and they work beyond what is reasonably expected to meet organizational or economic requirements. The latter recognizes that workaholics persistently and frequently think about work even when they are not working, which suggests that workaholics feel obsessed with their work. However, the research concerning workaholism has contrasting views regarding workaholism. Robinson (2000), for example, has described workaholism as a condition, when a person prefers to work and not think about emotional and personal aspects of life. While Machlowitz (1980) in her study found workaholics very satisfied and productive individuals. In the same manner, Furnham (1997) pointed out that workaholism is frequently lauded, praised, expected and even demanded. The above discussion on workaholism has indicated mixed feelings concerning workaholism. Although, workaholism has gained greater relevance in the modern society, scientific research on workaholism is still lacking and the reason for this is the insufficiency of consensus about its conceptualization and measurement (Libano et al., 2010).

In order to measure workaholism, commonly used measures highlighted by various researchers are Work Addiction Risk Test (WART), Workaholism Battery (WorkBAT) and Dutch Work Addiction Scale (DUWAS) developed by Robinson (1999), Spence and Robbins (1992) and Schaufeli et al. (2004), respectively (Kanai et al., 1996; Taris et al., 2005). In line with the conceptualization and validation of these scales, the construct reliability and validity of the same have been carried out in various settings. In this direction, studies conducted by researchers like Flowers and Robinson (2002) and Taris et al., (2005) are worth mentioning, who have made an attempt to look at the factorial structure of WART (Work Addiction Risk Test), which comprised five dimensions, namely, compulsive tendencies, control, impaired communication and self absorption, inability to delegate and self-worth. The reliability of compulsive tendencies and control tendencies were acceptable but the reliability of other subscales, namely, impaired communication and self absorption, inability to delegate and self-worth were found to be much lower than the satisfactory level and therefore, the subscales were identified as unreliable for further assessment of its psychometric properties. Moreover, no confirmatory information about its psychometric characteristics was obtainable (Burke, 2000). Further, Libano et al. (2010) also identified the items of WART misleading as the items of the scale refer to working hard without giving any reference to underlying motivation. In the same direction, Andreassen et al. (2007) examined the psychometric properties of Spence and Robbins’ measure on Norwegian employees with the components of workaholism, namely, drive to work, enjoyment of work and work involvement. The results exhibited poor fit with the original three-factor structure and confirmed only two measures, i.e., drive and enjoyment of work excluding the work involvement due to low internal consistency and insufficient factor loadings. These two dimensions met the reliability and validity with high internal consistency and moderate inter-correlations. In a similar vein of conceptualization of construct of workaholism, studies on factorial validity of Workaholism Battery (WorkBAT) has also failed to confirm three-factor model of workaholism that included work involvement, work enjoyment and drive to work (Kanai et al., 1996; McMillan et al., 2002). However, Dutch Work Addiction Scale (DUWAS) did not include work enjoyment because the scale excluded good forms of workaholism, i.e., work engagement, which is characterized by enjoyment of work, as various studies contributing to the understanding of concept of workaholism have viewed it as a negative construct (Burke, 1999; Kanai et al., 1996; McMillan and O’Driscoll, 2004). Thus, DUWAS, which is a combination of working excessively, working compulsively and overwork, is one of the most promising tools and has been preferred over these two workaholism scales, namely, Work Addiction Risk Test developed by Robinson (1999) and the Workaholism Battery developed by Spence and Robbins in 1992 (Miralles, 2011). In another attempt, Libano et al. (2010) conducted confirmatory factor analyses to measure the psychometric properties of working excessively and working compulsively constructs of DUWAS on a sample of 2,714 employees from Netherlands and Spain, separately. The results confirmed the factor structure of workaholism, i.e., working excessively and working compulsively and the two dimensions met the reliability and validity with high internal consistency which ranged from 0.75 to 0.85 and emphasized on considering these factors of workaholism for theoretical and research purpose irrespective of the country involved.

The above discussion entails that studies have upheld the use of DUWAS scale to assess the workaholism among individuals as compared to other existing measures of workaholism considering it as more stable in terms of psychometric properties apart from its alignment with the true meaning of concept of workaholism which has viewed workaholism as a negative construct essentially due to internal drive. The studies carried out in some parts of the world in different settings as discussed earlier, to validate the factor structure of DUWAS has also indicated about its applicability there. However, to the best of knowledge of researchers, hardly any study has been conducted to investigate the construct validity of DUWAS in the Indian context. The availability of limited empirical evidence regarding the identification of psychometric properties of the three-factorial structure of DUWAS does not lend strong support for usability of the instrument in Indian context. Moreover, the acceptance of DUWAS as standardized instrument requires confirmation that it explains and measures the workaholic characteristics in individuals in different settings. With this realization, the study responds to such call and partially fills in the extant literature on workaholism by utilizing a rigorous approach in investigating the psychometric properties of workaholism measure of DUWAS in terms of convergent and discriminant validity in relation to the Indian culture. A confirmatory analytical procedure has been used in order to complete DUWAS instrument validation research cycle by gathering new data in new setting to test the validity and reliability of the measure with the expectation that the structure of DUWAS will be similar in India as it is the role of internal factors which cause the development of workaholic tendencies rather than the influence of external factors which may provide additional fuel to the internal tendencies of workaholism.

Database and Research Methodology

Sample Design and Procedure

The present study is based on primary data collected with the help of a well-structured, pre-tested questionnaire from the employees engaged in both frontline and back-end operations of various sectors of service organizations. The reason for focusing on service sector is that the sector has undergone rapid and striking changes like globalization, liberalization, increasing competition, downsizing, introduction of new technologies, etc. (Bala, 2010) and today has been categorized as the largest and fastest growing sector globally, contributing more to the global output and employing more people than any other sector. Therefore, employees working in both public and private sectors face work pressures when they are required to meet targets (Suri and Arora, 2009; McHugh and Brennan, 1994) and this competitive nature of work has further contributed to the development of workaholism tendencies in employees (Fassel, 1990). Moreover, with the aim to provide the support for generalizability of findings, the different sub-sectors, namely, insurance, banking, education, hotel and restaurants, health services and telecom industries were considered in the present attempt. However, in order to prepare a micro-level and an empirical perspective for validity of workaholism, the present study has been confined to a particular part of the country of India. Specifically the employees of Jammu region (India) have been targeted for the present study. Accordingly, structured questionnaire was distributed personally to 620 employees, who were contacted during the period December 2010–June 2011 at their workplace personally in order to take their anonymous responses. The frequent reminders and visits to the employees’ workplace for survey helped in yielding 600 responses (96 per cent response rate). The univariate and multivariate outliers and missing values were searched in the dataset. In view of this, 70 responses were identified as outliers and eliminated. This resulted in 530 usable service sector employees’ responses for the final analysis. Data normality was also checked using skewness (ranges between 0.792 to –0.055 in the present case), kurtosis (ranges between 0.615 to –1.228 in the present case). These values were all within the level recommended for a CFA with maximum-likelihood estimation (skewness maximum 2 and kurtosis maximum 7 as mentioned by West et al., 1995 and Curran et al., 1996), supporting the normality assumption. The maximum likelihood approach to Confirmatory Factor Analysis was used to assess the validity of the model.

Workaholism Scale

A standardized four-point DUWAS ranging from ‘almost never’ to ‘almost always’ comprising 20 statements developed by Schaufeli et al. (2004) is used for measuring the construct validity. The scale is a combination of three constructs, namely, working compulsively including seven statements, working excessively with nine statements and overwork comprising four statements (refer Table 1).

Table 1.

DUWAS and its Dimensions

S.No.	Titles	Statements
1	Overwork (OW)	I dislike overwork.
2	Working Compulsively (WC)	I wish I weren’t so committed to my work.
3	Working Excessively (WE)	I seem to be in a hurry and racing against the clock.
4	Working Excessively (WE)	I find myself continuing to work after my co-workers have called it quits.
5	Working Compulsively (WC)	It’s important to me to work hard even when I don’t enjoy what I’m doing.
6	Working Compulsively (WC)	I stay busy and keep many irons in the fire.
7	Working Compulsively (WC)	I find myself thinking about work even when I want to get away from it for a while.
8	Working Excessively (WE)	I overly commit myself by biting off more than I can chew.
9	Working Compulsively (WC)	I have to do something, whether I want to or not.
10	Overwork (OW)	I go to work while feeling ill.
11	Working Excessively (WE)	I tend to put myself under pressure with self-imposed deadlines when I work.
12	Working Compulsively (WC)	I feel that there’s something inside me that drives me to work hard.
13	Working Excessively (WE)	I spend more time working than on socializing with friends, on hobbies or on leisure activities.
14	Working Excessively (WE)	I feel guilty when I am not working on something.
15	Working Compulsively (WC)	I feel obliged to work hard, even when it’s not enjoyable.
16	Overwork (OW)	I work on weekends.
17	Working Excessively (WE)	I find myself doing two or three things at one time such as eating lunch and writing a memo, while talking on the telephone.
18	Working Compulsively (WC)	I feel guilty when I take time off work.
19	Working Excessively (WE)	It is hard for me to relax when I’m not working.
20	Overwork (OW)	I take work home.

Source: Schaufeli (2004). http://www.schaufeli.com

Methodology

Consistent with theoretical arguments made earlier, the concept of workaholism was operationalized as a second-order construct manifested in three related dimensions, i.e., working excessively, a behavioural dimension; working compulsively, a cognitive dimension; and overwork, working to fulfil economic needs. Figure 1 shows the second-order construct of workaholism, as well as its first-order constructs and indicators. The responses of the respondents were analyzed by using AMOS 16 software package. Confirmatory factor analysis (CFA) with maximum likelihood estimation method was employed to examine the reliability and construct validity of the instrument. It is one of the most commonly employed tools used to measure the construct validity of the developed instrument (Hair et al., 2008; Tourangeau et al., 2006). It requires a priori designation of plausible factor patterns from previous theoretical or empirical work which are then explicitly tested statistically against sample data. The model was tested by examining the path coefficients and their significance.

Figure 1.

Source: Authors’ calculation.

Demographic Profile of Participants

The demographic profile of the focal group reveal that the sample is predominantly of males (54 per cent), married (70 per cent), mostly are graduates (42 per cent) with monthly salary ranging from ₹ 20000–35000 (34 per cent) working in different sub-sectors of service sector. About 26 per cent of the respondents work in education sector, 18 per cent work in banking and telecom sector, 16 per cent, 12 per cent and 10 per cent belong to Hotel/Resturant, Hospital and Insurance, respectively. About 53 per cent are from public sector and 47 per cent are from private sector.

Results

Reliability Assessment

To empirically assess the constructs just theorized, a confirmatory factor analysis by fitting measurement model was done. With all standardized factor loadings significant (p < 0.01), and greater than 0.49 the convergent validity is established (Onyeizugbo and Nwafor, 2010). The average variance extracted (AVE) estimated the amount of common variance among the latent constructs and variance extracted of greater than the minimum of 0.50 is supportive for the variance extraction (Chau, 1996; Karim and Weisz, 2010; Rivard et al., 2003). The value of Average Variance Extracted (AVE) estimated among latent construct indicators ranged from 67.10 per cent to 51 per cent (refer Table 2) which also lends support for convergent validity of the measure. It means that more than 50 per cent of the variances observed in the items were accounted by their hypothesized constructs. To evaluate composite construct reliability, Cronbach’s α was calculated for each construct, namely, working excessively, working compulsively and overwork and it proved to be satisfcatory ranging from 0.60 to 0.883. The alpha scores for each factor were more than 0.5 and were supported by Nunnally’s (1978) and Ancarani et al. (2009) who suggested cut-off value of 0.5 to be appropriate for measuring the internal consistency. Corrected item-to-total correlations and Cronbach’s alpha statistics were also employed to see if the removal of any item could increase the value of Cronbach’s alpha. However, a glance at the values of ‘cronbach alpha item if deleted’ for every item of scale reveals that no statement was identified as the potential candidate for deletion whose deletion could have increased the overall value of cronbach’s alpha of different constructs. It specifies that the reliability of each of the three first-order a priori factors is acceptable. Besides, correlation among the three constructs is moderate (from 0.56 to 0.754). In case of correlations, up to 0.90 components are regarded as independent (Gold et al., 2001). Besides, average variance extracted is greater than square of inter-construct correlation illustrating that the factors are clearly distinguishable from each other (Fornell and Larcker, 1981; Hammer et al., 2011; Saade and Bahli, 2005). Thus, the value of discriminant validity measure also provided an acceptable fit to the data (see Table 3). The nomological validity of the model provided an acceptable fit to the data due to the positive correlation between the factor scores for each construct (Spretitzer, 1995; Yang et al., 2004) and has theoretically supported relationships (Hair et al., 2008) (Table 3). Further, as expected the moderate to high correlation among three factors has indicated that working excessively, working compulsively and overwork are all correlated, suggesting the possibility of second-order workaholism factor. The application of second-order factor exhibited that the three-dimensional model, namely, working excessively, working compulsively and overwork congregate into a second-order factor structure (workaholism), connote a satisfactory fit to the data (Table 4).

Table 2.

Measurement Model: Factor Loadings and Reliability

Constructs	Number of Indicators	Range of Standardized Factor Loadings^#	Composite Reliability	Average Variance Extracted (AVE)
Working Excessively	9	0.58–0.77	0.88	67.10
Working Compulsively	7	0.52–0.732	0.83	64.34
Overwork	4	0.50–0.51	0.60	51.0

Source: Authors’ calculation.

Note: # All Factor Loadings are significant at p<0.01 level.

Table 3.

Results of Inter-Construct Correlations

Inter-Construct Correlations		Constructs
	WE	WC	OW
WE	1	–	–
WC	0.75(0.56)	1	–
OW	0.59(0.35)	0.56(0.31)	1

Source: Authors’ calculation.

Note: Figures in parenthesis represent the squared correlations.

Table 4.

Measurement Model: Second Order Construct of Workaholism

Second Order Construct	First Order Constructs	Factor Loadings	t-Static	Composite Reliability
Workaholism	Working Excessively	0.89^#	–	0.83
	Working Compulsively	0.86	13.30*
	Overwork	0.51	8.74*

Source: Authors’ calculation.

Notes: 1. ^# Loadings are specified as fixed in order to make model identified.

2. *significant at 1 per cent level of significance.

Estimation and Fit Criterion

The measurement model was observed for overall fitness by referring to other fit indices. Figure 1 depicts the factor loadings to explain the relationship among the first-order factors, namely, working excessively, working compulsively and overwork, and all these dimensions with second-order factor called workaholism.

The items of the constructs, namely, working excessively, working compulsively and overwork reveal positive correlation and these dimensions converged into a second-order factor called workaholism. Though the chi-square statistic is significant, whose significance indicates about the non-validity of the model, but due to its sensitivity in case of large sample as pointed by Hartwick and Barki (1981), Hair et al. (2008), Siedlecki et al. (2008) and Daniel (1998), it provides a sensitive statistical test but not a practical test for model fit. In fact the present sample size is relatively large (effective n = 530) which has likely inflated the small difference between the models. Thus, in the case of sufficiently large sample, the literature suggests to use chi-square/degrees of freedom as one of the criteria of model fit. Accordingly, the value of chi-square/df used to assess the model fitness is 4.671 in present case (refer Table 5), which is below the cut-off value suggested by Wheaton et al. (1977), Bentler and Bonnet (1980) and Marsh and Hocevar (1988) as indicative of model fit. Besides, various other models fit the criteria to investigate the adequacy of measurement model is also seen. Comparative Fit Index (CFI) whose acceptable range is 0–1, with a larger value indicating better model fit (Libano et al., 2010). The value of CFI displayed satisfactory fit with a value of 0.87. The Root Mean Square Error (RMSEA) is related to the residual in the model and the acceptable model fit is ≤ 0.08 (Adams et al., 1992; Harpaz and Xuanning, 2002; Henry and Stone 1994; Hong et al., 2006). In the study, the value of RMSEA exhibit satisfactory fit to the data with value equal to 0.08 as it fulfills the lower limit of acceptability. For the Adjusted Goodness-of-Fit Index (AGFI), the recommended level of value is 0.80 or above (Astrid et al., 2005; Hair et al., 2008; Khan et al., 2011) which specifies that only a relatively small amount of variance remains unexplained by the model (Harvey et al., 1985). The model fit indices depicted that the value of AGFI revealed satisfactory fit to the factor structure. Though in a few cases results may not seem to be sounding, yet on the whole these parameters estimate and goodness-of-fit indexes together with the internal consistency reliabilities provide reasonable support for the first-order a priori 3-factor, 20-item DUWAS scale, which collectively comprised second-order factor called workaholism. Estimates of item validity and reliability are not sensitive to the addition of a second-order factor (Doll et al., 1994), thus conclusions concerning the validity and reliability of the 20-item would be the same. In studying the validity of the present three-factor model, the fit to competing model was also studied. Accordingly, results for single factor model were also seen. The results indicated the value of CMIN/df = 6.070; GFI = 0.47; AGFI = 0.39; CFI = 0.42; RMSEA = 0.188. The chi-square test and other model fit indices demonstrated that the three-factor model is superior to the single-factor model. Moreover, significant differences obtained between the single factor and three-factor model (∆χ² = 248.44, df = 3, p < 0.001) substantiates the superiority of three-factor model over one-factor model. However, due to the limitations in the use of chi-square test (Hong et al., 2003; Yuan and Bentler, 2004), Akaike Information Criterion Information Criterion (AIC) was also used to compare the two models in order to determine which model explains the given data better (Gefen et al., 2003). The smaller the AIC value, better the model approximates the true process (Hong et al., 2006, Milfont and Duckitt, 2004). The value of AIC favour the three-factor model as AIC value for three-factor model, i.e., 869.455 is lower than AIC of 1-factor model, i.e., 941.821. Moreover, the difference between AIC of the hypothesized model and rival model was also substantial (∆AIC = 72.36, p < 0.001). Further, Cheung and Rensvold (2002) suggested using the CFI (Bentler, 1990) to compare the degree-of-fit of models. These researchers have recommended that a difference of 0.01 or larger in CFI indicates that rival model does not fit as well as the original model. Applying the criteria in the present case, the difference in CFI between models was 0.45, which is considerably larger than suggested cut-off providing additional support that three-construct model is more parsimonious than one-construct model.

Table 5.

Model Fit Indices

Fit Indices	Measurement Model
CFI	0.87
AGFI	0.81
GFI	0.85
RMSEA	0.08
NNFI	0.85
Normed χ²/df	4.671
AIC	869.455

Source: Authors’ calculation.

The present study also conducted Harman’s single-factor test using confirmatory factor analysis to determine the potential threat of common method bias. This test is based on the assumption that common method bias is a serious problem when a single latent factor will account for more than 50 per cent of the total variance of the measures (Podsakoff et al., 2003). The single-factor model accounted for only 32 per cent of the total variance. Consequently, common method bias was not identified as a critical threat to the magnitudes of the hypothesized relationships and put on display that the variables are related but different.

Conclusions

The aim of the current study was to attend to the limitation existing in literature regarding the application of DUWAS in Indian culture by providing evidence for robustness of DUWAS instrument in terms of construct validity and utility of the scale. The study validates the multidimensionality of DUWAS and confirms its significance for the employees working in the service sector of Jammu region, India. The initial model checked the three first-order factors, namely, working excessively, working compulsively and overwork and further the incorporation of these three dimensions into a second-order factor termed as workaholism. The results of the present contribution got endorsement from various model fit indices and three-factor model was identified as superior to one-factor model also. The theoretical findings are notably imperative and are in consensus with the previous results obtained by the different researchers about the construct validity of DUWAS. The results of the measurement model were found to be valid with the three factors, namely, working excessively, which is a behavioural dimension and refers to the tendency to work hard, while working compulsively, a cognitive dimension, indicates the obsession with work whereas overwork is the dimension when workaholics work beyond what is expected from them to meet the organizational or economic requirements (Schaufeli et al., 2004) and therefore, offers opportunity to continue with the study of workaholism from a more applied perspective pertaining to Indian work culture. Importantly, the three-dimension model of DUWAS is proven to be a useful and valuable instrument in the Indian context, particularly in the service sector setting. Thus findings of the present study enhance the applicability of DUWAS as a measure of workaholism. Moreover, it coincides with the perspective of some studies that exhibit workaholism as the intercorrelation between excessive working, compulsive working and overwork (Schaufeli et al., 2006, 2008) and thus conceives workaholism as a tri-dimensional construct. Furthermore, the results of the study also authenticate the proposition given by the Libano et al. (2010) that DUWAS can be used to study the workaholic dimensions irrespective of the country or work-setting involved. Therefore, the study has advanced both the knowledge and understanding of the literature present with the confirmation that workaholism may be measured with tri-dimensional approach. From the practical viewpoint, the results presented also indicate that working excessively, working compulsively and overwork has direct effect on workaholism construct and are important indicators to measure the characteristics of workaholic in an individual. This makes it an important instrument for screening the workaholics’ characteristic in individuals. With this tri-dimensional approach of the construct measurement provides coherent benefits because it uses different measures that allow researchers to understand workaholics from a broader perspective.

Limitations and Directions for Future Research

The findings of the study are limited by use due to its focusing on service sector employees of Jammu region (India) only. Moreover, the findings should be interpreted with caution as values of fit-indices in some cases are fulfilling the lower limit of acceptability. This warrants the replication of results in different kinds of samples to develop a more compelling construct validity argument and for robustness of the model. Therefore, another way to build on this research would be to adopt the model and approach to different occupations in different regions. Furthermore, the score of an employee on DUWAS can be validated by studying the responses from their peers, family members, friends, etc. Besides, future research can be planned to check the validity of the DUWAS through the lens of qualitative research methods also, which can provide more authenticity to its usage as a measure of workaholism.

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