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«Vera, María; Salanova, Marisa; Martín, Beatriz University faculty and work-related well-being: the importance of the triple work profile Electronic ...»

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“mental distance” toward work (cynicism) and toward fellow workers and the people for whom one works, i.e., clients, students, patients, etc. (depersonalization). We believe that this differentiation is necessary for university faculty members, as they may experience cynicism toward their work as teachers, researchers and managers, but can also suffer depersonalization toward students, coworkers or service staff.

Hypothesis 4: Burnout among our sample of university faculty members will include four dimensions: emotional exhaustion, depersonalization, cynicism, and lack professional efficacy.

Thus, the current study has three objectives. Firstly, and although most university faculty members perform teaching, research and management tasks, not all of them dedicate the same amount of time to each of these tasks. Our first objective, then, is to test whether different work profiles exist among university faculty members, taking into account the percentage of time that they dedicate to teaching, research and management.

Secondly, and once we know how many work profiles there are, we shall go on to test whether different work profiles of university faculty members relate with the experience of well-being at work (i.e., burnout, work engagement, and intrinsic job satisfaction).

Thirdly, we will also test the four-factor structure of job burnout (i.e., emotional exhaustion, depersonalization, cynicism, and lack of professional efficacy).

Method Participants The sample comprised 170 university faculty members of a Spanish university, which represents 18% of the total number of faculty members of this university (N = 955).

Basically, Spanish university faculty may be divided into two large groups:

state employees (tenured lecturers and university professors) and contract faculty (collaborating staff, part-time lecturers, etc.). In our sample population, we studied 102 contract faculty (60%) and 68 state employees (40%), 102 of whom were men (60%) and 68 were women (40%), the mean age was 39 years old (SD = 8.5), 127 were married or living with a partner (74%), and 43 were single or divorced (26%). A total of 87 had children (51%) and 83 did not (49%). The level of academic qualification of the sample Profesorado universitario y su bienestar laboral: la importancia del triple perfil laboral was as follows: 107 were PhDs (63%), 37 had completed the research aptitude period, that is, the first period graduates undertake before obtaining their PhD (22%), 23 had a degree which involves long-cycle studies (13%) and 3 had completed a diploma course involving short-cycle studies (2%). As for work experience, 73 had 5 years’ experience (43%), 49 had between 6 and 10 years (29%), 19 had between 11 and 15 years (12%), 14 had between 16 and 20 years (8%), while 13 had more than 20 years’ experience (8%).

Indeed most of the university faculty members in our sample said they had a triple work profile; specifically, only 6% of the sample had no teaching tasks, 11% had no research tasks, and finally only 16% had no management tasks. The mean amount of time spent on teaching was 50% (SD = 22.6), researching 32% (SD = 21.3) and management 18% (SD = 17.1).


Burnout. Emotional exhaustion, cynicism, and lack of professional efficacy were measured with the Spanish version (Schaufeli et al., 2002) of the Maslach Burnout Inventory (MBI) General Survey (Schaufeli, Leiter, Maslach, & Jackson, 1996). Five items measured emotional exhaustion (e.g., “I feel tired when I get up in the morning and have to face another day on the job”), four items measured cynicism (e.g., “I have lost interest in my work since I took this position”), and six items measured professional efficacy (e.g., “I can solve problems that arise in my work effectively”). Depersonalization was measured with five items (e.g., “In fact, it is of no concern to me what will happen to some people whom I must deal with in my work”) from the corresponding scale of the MBI Human Services Survey (Maslach, Jackson, & Leiter, 1996). All the items were scored on a seven-point frequency scale (0 = never, 6 = always). In order to obtain all the dimensions of burnout with the same sign, we reversed the scores of the professional efficacy items to obtain professional inefficacy. The Cronbach reliabilities for the scales were.85 for emotional exhaustion,.78 for cynicism,.47 for depersonalization, and.73 for lack of professional efficacy.

Work engagement was measured with the Utrecht Work Engagement Scale (Schaufeli et al., 2002). Six items measured vigor (e.g., “At work, I feel bursting with energy”), five items measured dedication (e.g., “My job inspires me”) and five items María Vera et al.

measured absorption (e.g., “When I’m working, I forget everything around me”). All the items were scored on a seven-point frequency scale (0 = never, 6 = always). The Cronbach reliabilities for the scales were.80,.92, and.75 respectively.

Job satisfaction was measured with the S20/23 Job Satisfaction Questionnaire (Meliá & Peiró, 1989). More specifically, we focused on the fourth factor of this scale, i.e. intrinsic satisfaction, which was measured by four items (e.g., “The opportunities that your job offers you to do the things you like”). All the items were scored on a seven-point frequency scale, (1 = highly dissatisfied, 7 = highly satisfied). The Cronbach reliability for the total scale was.92 and the Cronbach reliabilities for the dimensions range from.76 to.89. We focused on this factor and not on the others because we are interested in studying the satisfaction that work itself gives, that is, the opportunities that your job offers you to do what you really like.


All university faculty members received an envelope through the university’s internal mail service. This envelope contained a presentation letter, a document which they had to complete with their personal data, and a questionnaire. Both the personal data document and the questionnaire ensured confidentiality because we did not ask them for any self-identifying information. All the documents were written in Spanish.

Data Analyses

Firstly, we performed descriptive analyses, correlations and internal consistencies for each scale. Secondly, in order to establish the different work profiles, that is, to test Hypothesis 1, confirmatory K-means cluster analyses were performed and twocluster, three-cluster and four-cluster solutions were analyzed. Thirdly, once the groups had been established, we carried out ANOVA analyses in order to test Hypothesis 2 and Hypothesis 3. Finally, confirmatory factor analyses (CFA), as implemented by AMOS (Arbuckle, 1997) were used to confirm Hypothesis 4. The goodness-of-fit of the models was evaluated using absolute and relative indexes. The four absolute goodness-of-fit indexes that were calculated were: (1) the χ2 goodness-of-fit statistic; (2) the Goodnessof-Fit Index (GFI); (3) the Adjusted Goodness-of-Fit Index (AGFI); and (4) the Root Mean Square Error of Approximation (RMSEA). Additionally, we computed three relaProfesorado universitario y su bienestar laboral: la importancia del triple perfil laboral tive indexes: (1) the Tucker-Lewis Index (TLI); (2) the Comparative Fit Index (CFI);

and (3) the Incremental Fit Index (IFI). Since the distributions of the GFI and the AGFI were unknown, no statistical test or critical value was available (Jöreskog & Sörbom, 1986). Values below.06 for the RMSEA are indicative of an acceptable fit (Hu & Bentler, 1999), whereas for the IFI a cut-off value close to.90 suggests a good fit (Hoyle, 1995). As a rule of thumb for the remaining fit indexes (TLI, CFI), values greater than.95 are considered to indicate an adequate model fit (Hu & Bentler, 1999).

Results Descriptive Analyses Descriptive analyses, correlations and internal consistencies were performed for each scale. Table 1 shows the means, standard deviations and intercorrelations of the eight dimensions. As Table 1 illustrates, although all the correlations were not significant, all their items correlated significantly in the predicted direction. The same table presents the scores of the internal consistencies (Cronbach’s alpha) for all the dimensions and all scores met the.70 criterion (Nunnally & Bernstein, 1994). In all cases, except for absorption, the alpha values in our sample are higher than those obtained on the respective scale.

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Testing the hypotheses A K-means cluster analysis was performed to test Hypothesis 1 and two-cluster, three-cluster and four-cluster solutions were analyzed. The four-cluster solution provided a better interpretation because the solution fitted the university faculty members’ jobs. Moreover, all three tasks in the four-cluster solution were predominant in one cluster, i.e., each task uses up more than 50% of the time available. Table 2 shows the Kmeans cluster analysis, and we can see the number of university faculty members per cluster and the percentage of time dedicated to each task in each cluster. Three clusters corresponded to the triple work profile. Furthermore, one cluster shared teaching and research tasks equally. Regarding the characteristics of each cluster, we have tested whether there are differences between the university faculty members that make up each cluster with respect to sociodemographic variables. And there are only significant differences in the level of education (F(3, 166) = 9.16, p 0.001), type of job contract (F(3, 166) = 9.31, p 0.001), and work tenure (F(3, 166) = 3.29, p 0.05). In this way, PhD university faculty members belong mainly to the research cluster, the cluster that has a greater number of contract employees is the teaching cluster, and finally those university faculty members with more years at the university belong mainly to the management cluster.

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Moreover, in order to test Hypotheses 2 and 3, ANOVA analyses were carried out to determine whether differences in burnout, engagement and intrinsic satisfaction in university faculty members are dependent on the work patterns. Membership to a particular cluster only produced significant differences in absorption (F(3, 166) = 2.81, p.05, η2 =.048) and intrinsic satisfaction (F(3, 166) = 3.29, p.05, η2 =.056). However, in Table 3 we can see the means of the eight dimensions in each cluster.

Profesorado universitario y su bienestar laboral: la importancia del triple perfil laboral

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Figure 1 also presents the differences in burnout, engagement and satisfaction in the four clusters. This figure clearly shows how the research cluster offers the lowest value in burnout and the highest value in engagement and intrinsic satisfaction. In contrast, the management cluster presents the highest value in burnout, and the lowest in engagement and intrinsic satisfaction. Therefore, and although there are only significant differences in absorption and intrinsic satisfaction, the trend of the averages in the other variables are in line with Hypotheses 2 and 3.

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Finally, in order to test Hypothesis 4, CFA were used to confirm the four dimensions of burnout. We compared two alternative models: a three-factor model (M1), which assumed the traditional three dimensions of burnout, and a four-factor model (M2), which assumed four dimensions of burnout.

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As seen in Table 4, M2 (four dimensions) fits better than M1 (three dimensions).

On the basis of the modification indexes, the fit of the four-factor model can be improved by allowing one pair of errors to correlate from the emotional exhaustion dimension, one pair of errors to correlate from the cynicism dimension, and three pairs of errors to correlate from the professional efficacy dimension, as seen in model M2r (see Figure 2). Finally, we can confirm Hypothesis 4 because the four-dimension model consisting of emotional exhaustion, cynicism, depersonalization, and lack of professional efficacy (M2) fits better than a model made up of the three traditional dimensions, in which there are no differences between depersonalization and cynicism (M1).

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Discussion This study had three objectives. Firstly, although most university faculty members perform teaching, research and management tasks, not all of them dedicate the same amount of time to all these tasks. Our first objective was therefore to test whether different work profiles exist among university faculty members, taking into account the percentage of time that they dedicate to each of their three tasks (i.e., teaching, research and management). Secondly, and once we know how many work profiles there are, our aim is to test whether different work profiles of university faculty members relate with the experience of well-being at work (i.e., burnout, work engagement and intrinsic job satisfaction). And thirdly, we sought to confirm the four-factor structure of burnout (i.e., emotional exhaustion, depersonalization, cynicism, and lack of professional efficacy).

María Vera et al.

Thus, first, we have demonstrated that, in fact, although the triple work profile applies to most of our sample of university faculty members, the distribution of the three tasks within this profile is not equal in all them. Consequently, different work patterns were found to exist and were tested by a K-means cluster analysis. As already mentioned, we tested the two-cluster, three-cluster and four-cluster solutions. We also tested these solutions, and no others, because our initial aim was to confirm that there were three clusters that correspond to the triple work profile (i.e., teaching, research and management). Thus, in order to cover more possibilities, we tested two more solutions with one more cluster and one less cluster. For us, clusters make sense if there is a task in each of them that takes up more than 50% of the time spent. The four-cluster solution offers a better interpretation because this solution fits the university faculty members’ job better.

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