Factorial Validity and Consistency of the MBI-GS Across Occupational Groups in Norway

Brief Report Factorial Validity and Consistency of the MBI-GS Across Occupational Groups in Norway Astrid M. Richardsen Norwegian School of Management Monica Martinussen University of Tromsø The present study tested the factorial validity of the Maslach Burnout Inventory General Survey (MBI-GS) among 694 participants from 4 different occupational groups. Confirmatory factor analyses of the total sample, as well as multigroup analyses and analyses of each of the 4 occupational groups separately, indicated that the original 3-factor model of the MBI-GS provided a good fit to the data. Internal consistencies of the subscales of the MBI-GS were acceptable, and test retest reliability indicated relative stability of scores over a 6-month interval. These results indicate that the proposed 3-factor structure of the MBI-GS, based on 16 items, can be replicated in the total sample as well as across different occupational groups in Norway. Keywords: Maslach Burnout Inventory; test validity; occupational stress; confirmatory factor analysis; measurement The original version of the Maslach Burnout Inventory (Human Services Survey; MBI-HSS) was developed as a measure of professional burnout in human service professions (Maslach & Jackson, 1986). The Astrid M. Richardsen, Department of Leadership and Organisational Management, Norwegian School of Management, Oslo, Norway; Monica Martinussen, Department of Psychology, University of Tromsø, Tromsø, Norway. This research was supported financially by the Norwegian Research Council, the Psychiatric Research Center for Northern Norway, and the Department of Psychology at the University of Tromsø, Norway. Correspondence concerning this article should be addressed to Astrid M. Richardsen, Department of Leadership and Organisational Management, Norwegian School of Management, Nydalsveien 37, N-1302 Oslo N-0442, Norway. E-mail: astrid.richardsen@bi.no 289 International Journal of Stress Management Copyright 2005 by the Educational Publishing Foundation 2005, Vol. 12, No. 3, 289 297 1072-5245/05/$12.00 DOI: 10.1037/1072-5245.12.3.289

290 Richardsen and Martinussen scale has a strong and explicit focus on emotional demands and rewards arising from social relationships with service recipients (Leiter & Schaufeli, 1996), and research has shown that, with few exceptions, the factor structure of the scale is stable when it is used within human service occupations. Evidence for the stability of factor structure across cultures has also been shown (see, e.g., Enzmann, Schaufeli, & Girault, 1995; Richardsen & Martinussen, 2004). However, the use of the Maslach Burnout Inventory (MBI) in other occupational groups has shown that the differentiation of the three subscales is not always maintained (Maslach, Jackson, & Leiter, 1996). Several researchers have argued that the focus on social relationships as a source of stress was too narrow (Leiter & Schaufeli, 1996), and eventually this led to the construction of the Maslach Burnout Inventory General Survey (MBI-GS; Schaufeli, Leiter, Maslach, & Jackson, 1996) for use in occupations other than human services professions. The MBI-GS has three subscales that parallel those of the MBI-HSS, named Exhaustion (Ex), Cynicism (Cy), and Professional Efficacy (Pe). The Ex items have less emphasis on emotions and are without reference to recipients. The Cy items reflect indifference or a distant attitude toward the work itself and represent dysfunctional coping in response to exhausting demands (Leiter & Schaufeli, 1996). Cynicism is thought to diminish a job s potential for building professional efficacy, which is defined as encompassing both social and nonsocial aspects of occupational accomplishments. The Pe subscale focuses to a large degree on an individual s expectations of continued effectiveness at work (Leiter & Schaufeli, 1996). Since the MBI-GS was introduced in 1996, it has been used in a number of studies and in many different professions. Nevertheless, relatively few studies have investigated the factorial validity and psychometric properties of the scale. In general, these studies have found confirmation for the threefactor structure cross-nationally and across occupations and have found some differences in levels of burnout across nations and occupational groups (Leiter & Schaufeli, 1996; Schaufeli, Salanova, González-Romá, & Bakker, 2002; Schutte, Toppinen, Kalimo, & Schaufeli, 2000; Taris, Schreurs, & Schaufeli, 1999). Only one study so far has investigated the validity of the final version of the scale in other Scandinavian countries (Schutte et al., 2000), and the factor structure of the MBI-GS has never been investigated in Norway. The purpose of this study was to investigate the factorial validity and consistency of the MBI-GS in a Norwegian sample of four occupational groups (police officers, air traffic controllers, journalists, and construction managers), thus building on previous work as well as extending knowledge about applicability.

Maslach Burnout Inventory 291 METHOD Procedure Data were collected with questionnaires, which were completed anonymously. Envelopes containing a questionnaire, a cover letter, a stamped return envelope addressed to the University of Tromsø, and a consent letter for those who wished to take part in a follow-up were sent to 2,642 participants in total. After 2 3 weeks, a reminder letter went out to all participants. Participants The participants at Time 1 were 694 respondents to the questionnaire survey about burnout and work-related variables (Richardsen & Martinussen, 2004). The sample consisted of four different occupational groups, including 221 police officers (173 men and 48 women), 209 air traffic controllers (181 men and 28 women), 93 journalists (55 men and 38 women), and 171 construction managers (170 men and 1 woman). Two participants did not indicate their sex. Ages ranged from 21 to 72 years (M 39.9, SD 9.9), and the participants had an average of 5.5 years (SD 2.1) of education after primary school. Eighty percent were married or living with a partner, 12% were single, and 8% were divorced or widowed. The response rates for the four occupational groups were 44% for police officers, 42% for air traffic controllers, 34% for journalists, and 13% for construction managers. The relative absence of women and short-tenured respondents among construction managers is an accurate reflection of both the construction industry and the length of time typically required to achieve executive leadership positions. A total of 530 respondents (76%) wanted to participate in the follow-up survey, and, of these, 375 returned questionnaires at Time 2 (149 police officers, 78 air traffic controllers, 61 journalists, and 87 construction managers). This constituted a response rate of 54%. Measures Demographic and Work Characteristics Personal demographic variables included age, marital status, education, and income. Work characteristics included length of employment, job title,

292 Richardsen and Martinussen tenure in present position, level of management, hours worked, and overtime work. Burnout Burnout was assessed by the MBI-GS (Maslach et al., 1996). Permission to translate and copy the questionnaire was obtained from Consulting Psychologists Press. The questionnaire was translated to Norwegian and then back to English. The MBI-GS consists of 16 items rated on a 7-point scale ranging from 0 (never in the past year) to6(every day). The Ex subscale consists of 5 items, the Cy subscale consists of 5 items, and the Pe subscale consists of 6 items. Statistical Analyses Two analyses were conducted in addition to the confirmatory factor analysis (CFA). First, the skewness and kurtosis for individual items were investigated. According to Byrne (2001), if the skewness of individual items exceeds the critical value of 2.0 and the kurtosis exceeds the value of 7.0, indicating a nonnormal distribution, the chi-square goodness-of-fit statistic is likely to become excessively large. Second, the reliability for the subscales was assessed in two ways. Cronbach s alphas were calculated to assess internal consistency, and test retest reliabilities were assessed by Pearson correlations between subscales at Time 1 and Time 2. We used structural equation modeling (SEM) via the Amos 4.0 program (Arbuckle & Wothke, 1999) to test the fit of the factor analytic model. Following the analysis procedures of several other studies (e.g., Schaufeli et al., 2002; Schutte et al., 2000), we tested the fit of several increasingly less restricted models on the total sample and then tested the fit of the best model across occupational groups. We first estimated a null model (Model 0), in which all constructs were hypothesized to be uncorrelated and measured without error. This model served as a basis for comparison with five alternative models. In Model 1, we tested a one-factor model, in accordance with a one-dimensional view of burnout proposed by some authors (Pines & Aronson, 1988). Models 2a and 2b assumed a two-factor model in which a core of burnout dimension, suggested by Green, Walkey, and Taylor (1991), consisted of a combined Ex and Cy along with the Pe factor. In Model 2a, the two factors were assumed to be independent, whereas in Model 2b the two factors were allowed to correlate. Model 3a represents a three-factor model in which Ex and Cy were allowed to correlate, and Model 3b represents a model in which all three subfactors were allowed to correlate. Finally, Model

Maslach Burnout Inventory 293 3c is a respecified model in which the errors of two item pairs (Cy Items 4 and 5 and Pe Items 4 and 5) were also allowed to correlate. We used multigroup CFA to test the invariance of the respecified three-factor structure across the four occupations. Multigroup analysis only provides overall fit indices, and we therefore decided to conduct the same series of CFAs for each occupational group separately to see how well the model fit in each subsample. We examined the covariance matrix of the items using the maximumlikelihood method. The SEM analysis assesses the factor structure with the overall chi-square value as an index of model fit (Byrne, 2001). However, in large samples, the chi-square statistic is very powerful and may produce significant differences even when the model fit is quite good, and other fit indices that are not substantially affected by sample size were also provided in the analyses. The factor structure was also assessed with the goodnessof-fit index, which is a measure of the relative amount of variance and covariance in the sample data that is jointly explained by the hypothesized model, and the root-mean-square error of approximation (RMSEA), which is an estimate of the discrepancy between the hypothesized model and the true population model that takes into account the errors of approximation in the population (Byrne, 2001). In addition, we used the Tucker Lewis index and the comparative fit index (CFI) as indices of the discrepancy between the hypothesized model and the baseline model. In general, models with fit indices of.90 or greater and with an RMSEA less than.06 indicate a good fit (Byrne, 2001). RESULTS Frequency Distribution The analysis indicated that none of the items were skewed and no item had a kurtosis above the critical value. It is therefore unlikely that the chi-square goodness-of-fit statistic is inflated. Internal Consistency and Test Retest Reliability Mean values, standard deviations, internal consistencies, and test retest reliabilities are presented in Table 1. Cronbach s alphas calculated for each of the subscales at Time 1 were higher than the recommended criterion of.70 (Nunnally & Bernstein, 1994) for all three scales in the total sample as well as for all the occupational groups.

294 Richardsen and Martinussen Table 1. Means, Standard Deviations, Cronbach s Alphas, and Test Retest Reliabilities of Maslach Burnout Inventory General Survey Subscales Exhaustion (5 items) Cynicism (5 items) Professional Efficacy (6 items) Sample M SD r M SD r M SD r Total (N 694) 1.93 1.42.89.72 1.67 1.33.78.61 4.70 0.92.76.58 Police officers (n 221) 1.37 1.44.86.64 1.48 1.30.80.62 4.71 0.97.79.61 Air traffic controllers (n 209) 1.71 1.34.91.83 1.59 1.31.78.74 4.75 0.92.76.53 Journalists (n 93) 2.62 1.47.86.57 2.00 1.56.86.64 4.57 0.91.79.66 Construction managers (n 171) 2.55 1.44.88.68 1.81 1.23.73.44 4.67 0.85.76.49 Test retest reliability estimates indicated that Ex at Time 1 and Time 2 for the total sample were highly stable over a period of 6 months (r.72), whereas the correlations for Cy and Pe were somewhat lower (rs.61 and.58, respectively). Factorial Validity The results of the CFA are presented in Table 2 and show that each of the less restrictive factor models provided a progressively better fit compared Table 2. Indices of Overall Fit for Alternative Factor Structures of the Maslach Burnout Inventory Professional group 2 df GFI RMSEA TLI CFI Total sample (N 694) Model 0 5,186.89 120 Model 1 2,072.42 104.67.16.55.61 Model 2a 1,578.93 104.76.14.66.71 Model 2b 1,491.90 103.76.14.68.73 Model 3a 920.94 103.85.11.81.84 Model 3b 820.49 101.87.10.83.86 Model 3c 491.53 99.92.08.91.92 Multigroup (N 694) 845.76 396.87.04.89.91 Journalists (n 93) 150.13 99.83.07.91.93 Building constructors (n 171) 180.61 99.88.07.90.92 Police officers (n 221) 241.40 99.88.08.89.91 Air traffic controllers (n 209) 273.41 99.86.09.88.90 Note. Model 0 null model; Model 1 one-dimensional model; Model 2a twodimensional uncorrelated model with (Ex Cy) and Pe; Model 2b two-dimensional correlated model; Model 3a three-dimensional model with Ex and Cy correlated; Model 3b three-dimensional correlated model with Ex, Cy, and Pe; Model 3c respecified Model 3b (for explanation see text). All chi-square values and all reported decrements in chi-square for the increasingly less constrained models are significant at p.05. GFI goodness-of-fit index; RMSEA root-mean-square error of approximation; TLI Tucker Lewis index; CFI comparative fit index; Ex Exhaustion; Cy Cynicism; Pe Professional Efficacy.

Maslach Burnout Inventory 295 with the null model (Model 0) in the total sample. The original three-factor model of the MBI-GS (Model 3b), in which the three subscales were allowed to correlate, provided a reasonable fit to the data. However, none of the fit indices reached.90, which has been considered the minimum value (Byrne, 2001), and the RMSEA was.10, which is above the upper limit for reasonable errors of approximation in the population. However, on inspection of residuals and modification index (MI) values, we found that there were cross-loadings on two item pairs: between Cy Item 4 (i.e., I have become more cynical about whether my work contributes anything ) and Cy Item 5 (i.e., I doubt the significance of my work ), and between Pe Item 4 (i.e., I feel exhilarated when I accomplish something at work ) and Pe Item 5 (i.e., I have accomplished many worthwhile things in this job ). As a result, we respecified Model 3b by allowing the errors of these two item pairs to correlate. The respecified model (Model 3c) showed an excellent fit to the data, with all the fit indices above.90 and an RMSEA of.08, which is acceptable. These results are in agreement with the proposed factor structure of the MBI-GS (Schaufeli et al., 1996), and no further modifications were needed. The results of the multigroup analysis (which tested the fit of Model 3c) for the four occupational groups also showed a good fit to the data, with the CFI at.91 and the RMSEA at.04. The fit indices of the models tested for each subsample separately indicated similar results, and in all cases the tested model represented an acceptable fit to the data. DISCUSSION Results from this study confirm the original three-factor structure of the MBI-GS in a sample of four occupational groups in a Norwegian context. The factor structure has been confirmed in a number of recent studies using multiple groups or comparing various national samples (Bakker, Demerouti, & Schaufeli, 2002; Leiter & Schaufeli, 1996; Schutte et al., 2000), and thus our study contributes more evidence in support of the factorial validity of the scale. The results from the analyses of the total sample and the multigroup analyses are both indicative of a good fit of the proposed three-factor structure. The indices were somewhat lower for the multigroup analyses; however, the RMSEA value decreased from.08 in the total sample to.04 in the multigroup analysis, which is well within the recommended range for a good fit. The slightly adjusted three-factor model showed a good fit both globally and across occupations. In the respecified model, the error terms of two item pairs within subscales were allowed to correlate. The improvement in model

296 Richardsen and Martinussen fit in the total sample suggests that the expected factor structure, which uses all 16 items, was preferable to a modified scale with items with crossloadings removed. Schutte et al. (2000) also found significant improvement in model fit when the error terms of the same item pairs (Cy Items 4 and 5; Pe Items 4 and 5) were allowed to correlate. The fit indices for the total sample are comparable to those found in other studies carried out in different cultures. In terms of the psychometric properties of the MBI-GS, the internal consistencies all met the standard of.70 that Nunnally and Bernstein (1994) recommended. The test manual (Schaufeli et al., 1996) reported internal consistencies within the same range as those found in our study for different occupational groups and also reported similar test retest reliabilities over an interval of 1 year for a sample of Dutch civil servants. Studies that have used test intervals of 6 months to 1 year have generally found test retest values for the MBI in human services samples that are comparable to the results in our study (Jackson, Schwab, & Schuler, 1986; Lee & Ashforth, 1996; Leiter, 1990). This suggests that there is a high degree of consistency within each subscale that does not change markedly over a period of a year. Although there were some differences among the four occupational groups in this study in terms of test retest correlation coefficients, the overall picture supports the stability of subscale scores over a period of 6 months. In conclusion, this study provides support for the three-factor structure of the MBI-GS in a Norwegian sample of four different professions. Evidence for the invariance of factor structure across occupational groups is provided, as well as indications that the subscales are associated with a high degree of consistency over time. Internal consistency estimates are acceptable. In addition, the results strongly suggest that, for the most valid results in a Norwegian population, the original 16-item scale should be used. REFERENCES Arbuckle, J. L., & Wothke, W. (1999). Amos 4.0 user s guide. Chicago: Small Waters. Bakker, A. B., Demerouti, E., & Schaufeli, W. B. (2002). Validation of the Maslach Burnout Inventory General Survey: An Internet study. Anxiety, Stress and Coping, 15, 245 260. Byrne, B. M. (2001). Structural equation modeling with Amos: Basic concepts, applications and programming. Hillsdale, NJ: Erlbaum. Enzmann, D., Schaufeli, W. B., & Girault, N. (1995). The validity of the Maslach Burnout Inventory in three national samples. In L. Bennet, D. Miller, & M. Ross (Eds.), Health workers and AIDS: Research, intervention and current issues in burnout and response (pp. 131 150). London: Harwood. Green, D. E., Walkey, F., & Taylor, A. J. W. (1991). The three-factor structure of the Maslach Burnout Inventory: A multicultural, multinational confirmatory study. Journal of Social Behavior and Personality, 6, 453 472.

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