Academic journal article Australian Journal of Social Issues

Vocational Education, Self-Employment and Burnout among Australian Workers

Academic journal article Australian Journal of Social Issues

Vocational Education, Self-Employment and Burnout among Australian Workers

Article excerpt


It is generally accepted that formal education improves productivity at work. Human capital theorists argue that education bestows expectations and attitudes which bring about greater efficiency and satisfaction (Wan, 2007). Furthermore, formal education provides the human capital which reduces the likelihood of becoming alienated or disaffected with one's work, or what social scientists call burnout. Burnout can manifest itself in a number of negative workplace behaviours, including absenteeism, high accident rates, poor work output and poor interpersonal relationships in the workplace (Australian Government, NOHSC, 2004). The existing literature on burnout is mostly informed by the psychology of particular occupations, and occasionally only task-related training or events in specific work locations are considered as mediating factors (Goddard, Creed, and Patton 2001). In contrast, the sociological approach to burnout focuses on broader structural contexts, i.e. differences across groups of occupations, employment situations and a range of educational credentials considered simultaneously. Our goal is to complement the existing, primarily psychological, studies with a sociological analysis of burnout among the Australian self-employed and employees, who work across the private and the public sector on either a full-time or part-time basis. To the best of our knowledge, our study is unique in comparing the propensity to burnout of workers with more academic versus vocational credentials. In particular we are interested to know whether vocational education may serve as a buffer against disaffection with one's work, and how this may vary between the self-employed and employees.

What is burnout?

Burnout or 'role alienation', with its psychological manifestations such as job frustration and the feeling of powerlessness, has been at the centre of sociological analyses of work since Marx's exposition of alienation first became influential. As a structurally reinforced predisposition to apathy and feelings of ineffectiveness and failure, occupational burnout was researched in bureaucratic settings and the service sector, including healthcare and education (Dworkin 1987). In the Marxist tradition, alienation is inherently linked to job content and, in particular, workers' autonomy. However, research on teachers suggests that burnout is best understood as the outcome of a 'basic contradiction' between the training and the work experience of employees (Dworkin 1987: 68-69). This approach underscores as correlates of the propensity to feel exhaustion at work not only the importance of job conditions, but also to the process of preparatory education itself.

Psychologists, such as Maslach, Cherniss and Pines, regard burnout as the result of the failure of an individual to cope with stress. They see its symptoms in feelings of fatigue, hopelessness, depression and low morale. However, sociologists such as Dworkin, LeCompte and Townsend focus on alienation which is embedded in social organisations and social structures. They see burnout reflected in negative attitudes such as meaninglessness and isolation, and in the negative relationships towards one's work or colleagues. (See Dworkin, 1997, for a review of these approaches.)

In this study we follow the more sociological definition of burnout developed in research on American teachers (Dworkin 1987). Dworkin combined the psychological and sociological traditions, and described burnout as:

'... an extreme form of role-specific alienation characterized by a sense that one's work is meaningless and that one is powerless to effect changes which could make the work more meaningful. Further, this sense of meaninglessness and powerlessness is heightened by a belief that the norms associated with the role and the setting are absent, conflicting, or inoperative, and that one is alone and isolated among one's colleagues and clients.' (Dworkin 1987: 28).

This definition conceptualises burnout as a form of alienation which is not explained solely by individual traits, but also includes structural factors within the work environment. This partly reflects the original Marxist tradition of regarding alienation as an inextricable characteristic of capitalist employment. While Marx saw alienation in purely structural terms, Marxists, such as Blauner and Seeman, adopted a more socio-psychological perspective (Blauner 1973; Seeman 1959). Central to their approach was the belief that alienation from one's work could be reduced or eliminated with appropriate adjustments in work organisation and management. Seeman, on whose work Dworkin based his own definition, described five ways of understanding alienation (1959): 1) powerlessness, which is the worker's inability to control the work process, including the tools and products of labour; 2) meaninglessness, which refers to the uncertainty about what ought to be believed and the inability to predict behaviour based on shared beliefs; 3) normlessness, which refers to obsolete rules or the absence of rules which leads to distrust; 4) social isolation, which Seeman saw as 'assigning low reward value to goals or beliefs that are typically highly valued in the given society' (1959: 789); and 5) alienation which is defined as self-estrangement, that is, the state in which an individual does not reach her or his full human potential, and instead becomes 'insecure, given to appearances [and] conformist' (Seeman 1959: 790).

These components of alienation informed the construction of a ten-item scale, which measures occupational burnout (Dworkin 1987). Respondents recorded their feelings using five Likert-type response categories ranging from 'Strongly agree' to 'Strongly disagree'. The ten items, the concept measured, and the relevant direction of a "burnout" response are given in Table 1.

This ten-item scale has good measurement properties and has been used in recent studies of burnout (Saha & Dworkin 2004, 2006).

Self-employment and burnout

Much research on burnout, conceived as role alienation, has focused on service workers because of the spill-over effects which may profoundly affect service recipients such as students, patients and other clients. As the service sector continues to expand, the responsibility for the provision of services has been steadily shifting to the private sector and in some industries has boosted the numbers of the self-employed who were once thought to be doomed in the wake of standardised Fordist mass production of affordable consumer goods. Recent studies confirm that the self-employment niche is intact and, in many countries, has even been growing (Arum & Mueller 2004). Self-employment accounts for between 10% and 20% of workers in Western countries, with the Australian figure nearing the higher end of this spectrum (Australian Bureau of Statistics 2006). While the self-employed are in a minority in developed nations, they are usually more satisfied with their jobs and healthier than employees, despite working longer hours, sometimes for less pay (Blanchflower 2000, 2004).

Although there are numerous studies of the relationship between self-employment and job satisfaction (Evans & Sikora 2004: 220; Long 2005: 309; Louie et al. 2006; VandenHeuvel & Wooden 1997: 19), research on the small scale entrepreneurs and burnout is virtually non-existent (but see: Jamal 2007). Hence our first hypothesis concerns the impact of running one's own business on the likelihood of experiencing burnout. Because of a higher level of autonomy, and control over scheduling and the content of tasks on the job, we expect the self-employed to be less susceptible to feeling exhausted and apathetic (H1). This hypothesis is counter to the argument that small scale entrepreneurs suffer more from burnout than employees, because they work longer hours, experience virtually no separation between work and non-work time, and live in 'chronic uncertainty' due to high rates of small business failure (Jamal 2007). But this argument has not been backed up by nationally representative studies, which, if anything, indicate that the self-employed are the winners rather than losers in the quest for autonomy and self-determination (Blanchflower 2000, 2004). We argue that these disadvantages do not outweigh the empowerment felt by self-employed persons, and hence we expect lower levels of burnout among them.

Vocational education and employment contexts

Although pathways into and out of self-employment vary from country to country, in Australia, particularly for men, the completion of vocational education significantly enhances the chances of running a business (Evans & Sikora 2004: 223). This is also the case in a number of other countries (Arum and Mueller 2004). This is why our second hypothesis (H2) proposes that vocational education may reduce the chances of burnout, even after various job characteristics have been taken into account. In addition to this hypothesis, we also test a number of propositions concerning the relationship between job characteristics and burnout. We argue that education reduces burnout indirectly, as particular forms of education facilitate specific career trajectories and thus influence the propensity to burnout (H3). We also control for precarious work arrangements, measured indirectly by distinguishing between part-time and full-time positions in the private and government sectors of employment. Our expectation is that employment conditions, thus defined, also affect the feelings of burnout, but their effects are net of other influences (H4).

Data, method and measurement

We use the 2001 data from the International Survey of Social Attitudes (IsssA), collected from a random sample of Australian citizens, drawn by the Australian Electoral Commission from the electoral roll (Kelley & Evans 1999, 2002). The IsssA are academic mail surveys conducted mainly in the 1990s, for which response rates oscillated between 60% and 65%. This compares favourably with other mail-out surveys in Australia and overseas. The 2001 survey collected information about burnout using a modified version of the Dworkin scale (1987). As far as we know, this is the best data source for Australia, because other more recent data sets with appropriate educational and occupational information include no sociological measures of occupational burnout.

As burnout in our data was operationalised by ten indicators, we first factor analysed (1) them to confirm measurement properties of the scale and then constructed a weighted average scale score for each respondent. Our burnout measure ranges from 0 to 100, where the highest score denotes the most intense feelings of burnout. Given that this is a continuous measure, we employ, as our main modeling technique, robust regression as available in STATA 9 in the RREG procedure. Because occupational burnout is by definition work-related, only people in the labour force at the time of the survey are included in the analysis, which reduces the sample size to approximately 800 individuals (2).

To demonstrate that burnout cannot be conceptually reduced to work-related stress, we also model another dependent variable denoting stress. It is measured by a three-item scale comprising reports of fears 'that the amount of stress in my job will make me physically ill'; perceptions that 'My work is more stressful that I had ever imagined' and lack of identification with the proposition that 'I feel that I am usually able to handle the stress levels on my job'. Likert type five-response categories were used to record respondents' perceptions and we also factor analysed them to confirm that they constituted a scale. The resulting stress scale has good measurement characteristics and has been used in prior research by Saha and Dworkin (2004; 2006).

Age is measured in years, gender is a dummy variable on which men are scored 1 and women 0, education is conceptualised as a continuous variable depicting years of schooling, complemented by two dummy variables to distinguish people with basic vocational and skilled vocational qualifications, in this case defined as the ABSCQ levels 6 and 7. We began our preliminary analyses from coding all ABSCQ levels into dummy variables, but this did not result in more explanatory power so we adopted a more parsimonious model employing education in years supplemented with only two dummy predictors without any loss of information. Occupation is measured in the Worldwide Status Scores (Kelley 1990), which are conceptually very similar to ISEI scores (Ganzeboom & Treiman 1996) used by the PISA surveys (OECD 2002). We also distinguish between holders of supervisory positions and those who work exclusively as supervisees, as this is likely to be crucial for feeling empowered or powerless on the job. The self-employed are all people who reported running their own business, coded into three occupational groups: the unskilled, the skilled and professionals, based on the Erikson, Goldthorpe and Portocarero (EGP) class schema (Arum & Mueller 2004: 9). This recognises that self-employment is not a homogeneous category but is strongly differentiated by occupation (VandenHeuvel & Wooden 1997). We also distinguish between self-identified full-time and part-time workers within the private and government sectors of employment. The proportion of part-time private sector workers is closely related to casual employment i.e. "employment without leave entitlements". In Australia 70% of employees without leave entitlements work part-time and 89% of employees without leave entitlements self-identify as casuals (Australian Bureau of Statistics 2004: 14).

How representative are our data on vocational educational qualifications?

One important technical issue is the representativeness of the survey data with respect to vocational qualifications. The 2001 IsssA respondents were asked about the highest educational qualification they held at the time of the survey. About 41% reported no qualification, which is much lower than the 53.8 % reported in the 2001 Census in the population of over 15-year-olds. A small part of this difference is attributable to the fact that the survey was conducted with respondents aged 18 and over, but it also indicates that our survey sample is biased by including more respondents with educational qualifications. Nevertheless, the distribution of reported qualifications appears to match well with the 2001 Census, despite problems of comparability caused by the use of two different classifications: the ABSCQ in the survey and the ASCED in the Census (Table 2).

According to the Census, 45.4% of the Australian adult population held a Certificate II, III or IV, as defined by ASCED. In the IsssA survey, 42% of the respondents held either an Associate Diploma, a skilled vocational qualification or a basic vocational qualification (Australian Bureau of Statistics 2003: 207). These figures are not strictly comparable because an ABSCQ Associate Diploma may be equivalent to either an ASCED Diploma or a Certificate IV, and the breakdown between Advanced Diplomas and Diplomas is not available in the Census data. In the IsssA data, however, only 6 % of the respondents hold Associate Diplomas, the qualifications which we treat as equivalent to having a Certificate IV and not a Diploma, so our risk of misclassification is very low.

Overall, despite noting some overrepresentation of the more educated respondents typical for mail-out surveys, our data appear of good quality and are certainly the best available.


Because our burnout scale is a weighted average and ranges from 0 to 100, it is reasonable to assume that any scale score above 50 indicates a certain level of burnout. Applying the same logic, we treat a score of 75 or over as an indication of serious burnout. Making this assumption, 19 % of our respondents report moderate burnout, while 1% report serious burnout. Overall, about one-fifth of our respondents feel disillusioned about their jobs.

Table 3, which summarises average burnout and stress scores by education, occupation and particular self-employment sectors, reveals that burnout is more related to labour market characteristics than the educational profiles of respondents.

Burnout and education

Although previous research led us to expect people with higher degrees to experience less burnout than workers with lower educational credentials, all confidence intervals around these estimates overlap in Table 3, and thus we cannot ascertain any differences in burnout by education when measured in this way. Similarly, particular levels of education do not differentiate between the likelihood of experiencing stress (Panel B in Table 3).

Burnout and self-employment

Although the self-employed are as likely to feel stressed at work as employees, they are significantly less prone to burnout. In Table 3 the average score for employees is 40.5 points, which is distinctly higher than 32.3 points for the self-employed.

In line with prior research emphasizing the need to recognize the heterogeneity of self-employment, we next compare burnout indicators for the unskilled, skilled and professional entrepreneurs. We find that the unskilled self-employed are more likely than the professionals to suffer from burnout, which is not unexpected. But the scores for the skilled entrepreneurs, for instance builders, electricians or plumbers, show no difference between them and the other two groups. Overall, although all three occupational groups of the self-employed experience similar levels of stress, not all of them are equally likely to experience burnout. With these preliminary observations in mind, we next turn to the more powerful multivariate models.

Multivariate Analyses: Education, occupation and burnout

Our robust regression models reveal more complexities in the relationships between education, labour market characteristics and burnout. Overall, demographic, educational and occupational characteristics explain about 10% of the variation in the dependent variable (Model 2, Table 4), and when stress is controlled for, the model explains about 20%. While this leaves 80% of the variation unexplained, the variables in our models certainly deserve attention as broad structural determinants of occupational burnout. Older workers, seasoned by experience, are less likely to feel burned out as shown by the standardised coefficients of -.24 in Model 1. This is the largest effect in this model. Moreover, education, measured in years of schooling, appears to act as a buffer against burnout (-0.65), but this is only because we do not account for occupational differences in Model 1. Once these are controlled for in Models 2 and 3, years spent at school cease to exert any independent influence.

In contrast, dummy variables identifying respondents with unskilled and skilled vocational qualifications show that completing skilled vocational training reduces, by about 3.6 out of 100 points, the chances of experiencing burnout, regardless of age, gender, occupation, and other labour market characteristics. Even after stress on the job is taken into account in Model 3, skilled vocational credentials help to protect against apathy and disillusion with work. This supports our second hypothesis (H2) and calls for future research to identify the processes either in the training process itself or in the match between the training and job placement which account for this association.

Are vocational qualifications simply indicators of pathways to particular niches of the labour market in which people are less likely to experience role alienation and thus burnout? In this case, burnout should be determined by the characteristics of particular jobs, which we might have measured imperfectly. But it is also possible that this effect reflects something about the process of a skilled vocational education itself that affects the lasting predispositions of these workers. If this is the case, burnout cannot be attributed solely to job content.

In contrast to skilled vocational qualifications, basic training has no discernible impact on burnout, which in terms of policy implications, suggests that programs of vocational training should aim to equip their graduates with advanced rather than only basic skills. In the public debate over the increasing need for a skilled labour force, one of the key concerns should be the quality and level of skills acquired in various vocational training programs. Our analysis indicates that basic and skilled vocational qualifications can lead to diverse outcomes. These outcomes might go beyond the experiences of burnout alone.

Education affects burnout by increasing the chances of obtaining a job with higher occupational status, which is revealed by the comparison between models in Table 4. Once occupation is accounted for, university degrees or diplomas make little difference. Professionals, managers and administrators, who have high scores on our measure of occupational status, are less likely to report feeling powerless and alienated (Model 2). But a professional occupation becomes an effective buffer against burnout, particularly when combined with self-employment. To highlight this we have differentiated business owners into the unskilled, the skilled and professionals using the EGP schema previously utilised for this purpose by Arum and Mueller (2004).

The professional self-employed are least affected by burnout. Their relative advantage over the unskilled entrepreneurs is significant and amounts to 6.14 points out of 100 (Model 3 in Table 4). The skilled entrepreneurs are 4.67 points less likely to feel burned out than their unskilled counterparts. The standardised coefficients leave no doubt that a professional occupation, combined with running a business, for instance as a medical doctor in general practice, a financial consultant, designer or even a private music teacher, constitutes the best possible position to avoid burnout.

Different forms of employment and predicted burnout levels

To better understand the findings in Model 3 in Table 4 let us consider predicted burnout levels for selected ideal-typical workers. All of these workers are about 43 years of age, which is the average in our working sample, and their stress scores are set at 50. Twenty-five percent of our sample reported stress levels equal or above 50 points on the stress scale, and Appendix 1 shows that this is an above-average level of stress. For people with an average level of stress, the predicted scores will be lower, although the relative differences between them will remain the same.

Firstly, a highly educated architect, lawyer or a general practitioner who runs their own business and employs other people will have a predicted burnout score of only 32 points. In contrast, an employee with otherwise identical characteristics will have a much higher score of 38 points. However, a plumber or an electrician who completed a skilled vocational qualification, runs his own business and employs a couple of people will have a predicted burnout score of 37, which is substantially more than the professional self-employed but almost the same as the score for the very educated, professional employee in a supervisory position.

In contrast, a self-employed truck driver whose occupational status is identical to that of a plumber or an electrician, but who has neither a vocational qualification nor employees, will have a predicted burnout score of 45. Finally, an unskilled labourer who works part-time for an employer has a predicted score of 54 points--the highest of all examples considered. Although most of these predicted averages are lower than 50 points, as only the minority in our analysis report very high stress and burnout levels, they illustrate well the differences in educational and job characteristics which make particular groups of workers more vulnerable.

Burnout and casualisation

The literature on the increasing casualisation of Australian work arrangements and the insecurities embedded in irregular employment suggests that burnout may be experienced more frequently by casual workers (Watson et al. 2003). Our data do not contain explicit information on casual employment, which is defined by the Australian Bureau of Statistics as employment with no leave benefits (Australian Bureau of Statistics 2003: 3). Nevertheless, by creating a set of proxy variables, we can compare the likelihood of burnout among full-time and part-time government employees, as well as their counterparts in the private sector. We assume that part-time workers are most likely to work on a casual basis, as most Australian casuals work part-time (Australian Bureau of Statistics 2006). In line with our assumption, even this imperfect indicator of casual employment has a positive effect on burnout. Particularly after we take into consideration various levels of stress that workers experience, part-time private sector employees are significantly more prone to apathy and exhaustion (coefficient 3.06 in Model 3).

Is burnout the same as stress?

In the sociological tradition, occupational burnout has always been conceptually distinct from work-related stress, and our analysis confirms this distinction. Unlike with burnout, we find that the chances of experiencing stress are no different between the well educated and the less-well educated (Table 5). Moreover there are fewer significant relationships between labour market characteristics and stress (Table 5) than there are between these characteristics and burnout (Table 4). This clearly demonstrates that although stress enhances occupational burnout, there are many individuals who function in highly stressful work environments without serious risk of permanent loss of enthusiasm or interest in their daily job tasks.

The only four relevant predictors of stress in Table 5 appear to be age, supervisory status, working as a professional self-employed, and part-time work in the private sector. Older workers seem to be affected more by stress than their younger counterparts (0.11) while, as expected, supervisors report higher levels of stress than supervisees (5.53). The latter is consistent with the research on stress-related compensation claims, which indicates that high levels of responsibility for other people's welfare trigger stress-related illnesses (Australian Safety and Compensation Council 2007).

The professional self-employed are likely to be less prone to stress compared to the unskilled entrepreneurs (-5.05) because, as we noted earlier, they have more control over their work environment, despite bearing the responsibility for their own success or failure. Finally, part-timers outside of the public sector report less stress than full time government employees (-6.94). While this may seem surprising, as these are part-time workers many of whom are casuals working in highly unpredictable environments, one possible explanation is the research on identity, which stipulates that part-timers often define their lives more in terms of their out-of-work activities than jobs which may help them manage stress. Yet, as we have no measures to further explore this proposition, the apparently lower levels of stress among private sector part-timers must be treated as an hypothesis to be evaluated by future research.

How does vocational education reduce burnout?

Skilled vocational education appears to moderate the likelihood of experiencing burnout at work. While this result needs confirmation in future studies to establish its robustness in varying contexts, we have found that this effect holds in our models even after a wide range of labour market characteristics have been taken into account. Workers with a skilled vocational qualification are less likely to experience burnout even when they do not run their own business, although having a business further reduces this likelihood. If they are employees, it does not matter in which sector and what hours per week they work.

We therefore suggest that higher level vocational courses equip graduates with special skills to resist burnout. However, this proposition is less plausible than an alternative which suggests that skilled vocational education facilitates a person's placement in the labour market where there is higher autonomy in terms of management of task contents and organisation, as well as the availability of appropriate human and material resources. These characteristics are common for highly specialised professional jobs, and hence the professional self-employed are best poised to be less prone to burnout. But professional qualifications are not the only type of educational credentials which facilitate entry to autonomous work environments. Skilled vocational qualifications offer the promise of extensive on-the-job autonomy, even if their holders end up working for someone else. Therefore skilled vocational training may be a ticket to burnout-flee jobs. However, the same is not the case for basic vocational qualifications.

Discussion and Conclusion

Burnout is detrimental not only for individuals, but also for an economy. A workforce with many burned out workers is likely to be inefficient and costly because of potential negative work behaviours. Our study complements the psychological research on specific occupations and work settings by demonstrating that broadly defined work characteristics and the type of education may affect propensity to feel exhausted and disillusioned with work. Firstly we have found that small scale entrepreneurs who enjoy greater work autonomy, do not have to be concerned about obeying orders or pleasing a supervisor or similar person in authority, are less likely to burn out. This finding supports our first hypothesis (H1).

We have also investigated in more depth the variations in propensity to burnout among holders of academic and vocational credentials and among particular occupational groups within the self-employment sector. Workers who have skilled vocational qualifications are less prone to burnout when compared to those with basic vocational qualifications. In fact their risk is comparable to that of highly educated professional employees in supervisory positions. This supports our second hypothesis (H2). We have also found that part of the effects of educational credentials rests in their provision of entry to particular occupations, and that persons in occupations with higher status are less prone to burnout, as predicted by our third hypothesis (H3).

Professionals, particularly when working for their own business, are at the lowest risk of burnout, and the skilled have an advantage over the unskilled. This is the case not only among the self-employed but also among the employees. Finally, we have found that precarious work arrangements, that is part-time as opposed to full-time work, the former of which is often linked to casualisation, is positively related to burnout. This is consistent with our fourth hypothesis (H4).

The work conditions among the professional self-employed and the skilled self-employed, which make them less prone to burnout, are similar. Both the academically educated professional entrepreneurs and the vocationally skilled self-employed have higher levels of autonomy, consider their work identity important, and, as already demonstrated, feel significantly more job satisfaction than any other employees (Evans & Sikora 2004).

Overall our research reveals that particular educational credentials, both their type, namely academic versus vocational, and level may equip graduates with characteristics that help combat burnout in specific work situations. This corresponds to the psychological research mentioned at the outset of this paper. In contrast, we have identified influences broader than specific task-related training. Broadly conceived work characteristics also create environments which systematically affect the risk of burnout. This does not supersede but complements the research on burnout within particular professions. We have demonstrated that forms of employment, that is, business ownership, sector, and hours of work all affect our dependent variable above and beyond the psychological predispositions of workers and their immediate work environment.

However this link between vocational education and burnout merits further investigation if we are going to learn more about both the educational preparation of individuals for work, and the nature of work conditions which are necessary to ensure a healthy workforce. So far it seems that in terms of policy implications, we must suggest that programs of vocational training should aim to equip their graduates with higher level rather than only basic skills.

In conclusion, we have demonstrated that, in addition to a range of work characteristics, educational credentials, including skilled vocational education, may minimise burnout. Raising the educational profile of the workforce and providing opportunities for the development of skilled and professional self-employment are two strategies likely to decrease burnout rates. But while academic credentials benefit individuals only indirectly, through facilitating placement in professional jobs, vocational qualifications benefit workers both directly and indirectly. This, in addition to considering a broad range of work characteristics, should be taken into account in future endeavors to understand and curb exhaustion, apathy and negative work behaviour, not only among workers in the service sector, but also among workers in general.

Appendix Table 1. Descriptive Statistics

                           Mean     Dev    Minimum   Maximum    N

Burnout scale              38.95   14.67      0        85      849
Work-related stress
  scale                    33.67   18.54      0       100      847

Age                        43.19   11.46     20        70      862
Gender                      0.47    0.50      0         1      870
Education in years         12.77    2.80      2        18      868
Skilled Vocational
  Qual (ABSCQ)              0.16    0.37      0         1      865
Basic Vocational
  Qual (ABSCQ)              0.07    0.25      0         1      865

Occupational status
  (0 =farm labourer;
  100=Professional)        54.78   26.13     14       100      855
Supervises at work          0.41    0.49      0         1      837

Unskilled Self-employed     0.03    0.16      0         1      876
Skilled Self-employed       0.05    0.22      0         1      876
  Self-employed             0.12    0.33      0         1      876

Full-time government
  employee                  0.15    0.36      0         1      817
Part-time government
  employee                  0.04    0.20      0         1      817
Full-time in private
  sector                    0.37    0.48      0         1      817
Part-time in private
  sector                    0.21    0.41      0         1      817

Source: IsssA 2001


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Watson, I. Buchanan, J. Campbell, I. & Briggs, C. (2003) Fragmented Futures: New Challenges in Working Life. Annandale, NSW, Federation Press.

(1) We do not report the results of factor and reliability analyses to conserve space, but they are available upon request.

(2) The proportion of the working population in our sample is approximately 53% which is lower than the ABS' 63.7 % for 2002. This discrepancy is attributable to the differences in the definitions of the working population (Australian Bureau of Statistics 2004).

Table 1: The Items of Dworkin's Occupational Burnout Scale

Item                                   Dimension            burnout

1.   Those who make the ultimate       Powerlessness        Disagree
     decisions at my work really
     pay attention to my ideas and
2.   The longer I work at my job,      Powerlessness        Agree
     the more I realize how little
     control I have over things
     that happen there.
3.   Employees at my work can get      Normlessness         Disagree
     their work done without
     breaking the rules.
4.   Many of the rules at my work      Normlessness         Agree
     are so rigid and/or absurd
     that a good employee must
     defy regulations.
5.   My experiences at work prove      Meaninglessness      Disagree
     that I have a satisfying
6.   I see my job as contributing      Meaninglessness      Agree
     very little to the betterment
     of the world.
7.   The people I work with make       Isolation            Disagree
     me feel that I'm of vital
     importance to my workplace.
8.   Sometimes I think the average     Isolation            Agree
     employee at my workplace could
     drop dead or quit and nobody
     would notice or care.
9.   I cannot imagine my choosing      Alienation           Disagree
     any other career than the         (Self-estrangement)
     one I have now.
10.  I am seriously planning to        Alienation           Agree
     leave the career I have now.      (Self-estrangement)

Source: Dworkin (1987:39)

Table 2. Distribution of educational qualifications
in 2001 Census and IsssA

IsssA 2001 ABSCQ

Higher Degree (1) and Postgraduate         12.4
Diploma (2)

Bachelor Degree (3)                        29.3

Undergraduate Diploma (4)                  16.3

Associate diploma (5),Skilled Vocational   42.0
Qualifications (6) and Basic Vocational
Qualifications (7)

2001 Census ASCED

Postgraduate Degree (1), Graduate           9.2
Diploma or Certificate (2)

Bachelor Degree (3)                        28.1

Advanced Diploma (411) and                 17.3
  Diploma (421)

Certificates II, III and IV (5)            45.4


Source: IsssA and the 2001 Census

Table 3. Descriptive Statistics: burnout and stress by education and
labor market characteristics

                          A) Burnout score (out of 100)

                          Mean       95%       Min   Max   N

  Higher degree           34.8   (31.7-38.0)   3     78    87

  Bachelor's degree       39.3   (37.1-41.6)   0     78    190

  Undergraduate           39.0   (36.0-42.1)   8     70    80

  Associate diploma       41.5   (37.5-45.5)   23    60    28

  Skilled vocational      38.3   (36.0-40.7)   0     78    132

  Unskilled vocational    40.8   (37.3-44.3)   13    85    57
  No educational          39.7   (37.9-41.5)   0     85    264

Labour market characteristics
  Supervisees             40.9   (39.5-42.2)   0     85    482

  Supervisors             36.2   (34.7-37.7)   0     78    339

  Employees               40.5   (39.4-41.5)   0     85    688

  All self-employed       32.3   (30.2-34.5)   0     75    165

  Professional            30.0   (27.4-32.5)   0     70    105

  Skilled                 35.3   (30.8-39.8)   0     75    39

  Unskilled               40.2   (33.9-46.5)   10    68    19

  Government sector       39.8   (37.4-42.2)   0     78    125

  Government sector       39.3   (34.7-43.5)   15    63    34

  Private sector          40.6   (39.0-42.2)   0     83    303

  Private sector          41.6   (39.4-43.3)   0     85    166

                          B) Work related stress (out of 100)

                          Mean       95%       Min   Max   N
  Higher degree           35.4   (31.3-39.6)   0     92    87

  Bachelor's degree       34.4   (31.5-37.2)   0     100   189

  Undergraduate           36.0   (31.8-40.3)   0     83    80

  Associate diploma       37.2   (29.3-45.1)   0     83    28

  Skilled vocational      33.9   (30.8-37.0)   0     83    132

  Unskilled vocational    32.3   (28.3-36.3)   0     67    57
  No educational          31.8   (29.7-33.9)   0     92    263

Labour market characteristics
  Supervisees             31.2   (29.7-32.7)   0     92    481

  Supervisors             36.9   (34.8-39.1)   0     100   338

  Employees               34.2   (32.8-35.6)   0     100   687

  All self-employed       31.6   (28.8-34.4)   0     75    164

  Professional            32.4   (28.9-35.9)   0     75    104

  Skilled                 31.8   (26.5-37.2)   0     67    39

  Unskilled               28.9   (20.1-37.8)   0     58    19

  Government sector       36.5   (33.2-39.8)   0     83    124

  Government sector       39.5   (32.8-46.1)   0     92    35

  Private sector          34.9   (33.0-36.8)   0     100   387

  Private sector          28.2   (26.1-30.4)   0     83    215

Source. IsssA 2001

Table 4. Robust regression predicting burnout from educational and job
characteristics. Australia 2001

                                              Model 1

                                Coefficient   Standard   Standardised
                                               error     coefficient

Demographic characteristics
  Age                              -.24 **      0.05        -0.24
  Gender (Male =1)                 3.02 **      1.11         0.10
  Education in years               -.65 **      0.20        -0.13

  Skilled Vocational Qual         -4.09 **      1.56        -0.09

  Basic Vocational Qual            0.21         2.02         0.00
Labor market characteristics
  Occupational status
  (0 =farm labourer;





  Full-time government

  Part-time government

  Full-time in private sector

  Part-time in private sector
  Constant                        56.63 **      3.69
  Adjusted R2                      0.03
  N                                822

                                              Model 2

                                Coefficient   Standard   Standardised
                                               error     coefficient

Demographic characteristics
  Age                             -0.10 *       0.05        -0.09
  Gender (Male =1)                 4.05 **      1.17         0.13
  Education in years               0.02         0.24         0.01

  Skilled Vocational Qual         -4.01 **      1.59        -0.08

  Basic Vocational Qual            1.55         2.06         0.04
Labor market characteristics
  Occupational status             -0.09 **      0.02        -0.14
  (0 =farm labourer;

  Supervisor                      -3.22 **      1.09         0.11

  Unskilled                          --

  Skilled                          5.91 *       2.73        -0.08

  Professional                    -7.70 **      1.87        -0.19

  Full-time government               --

  Part-time government             1.01         2.82         0.02

  Full-time in private sector      1.39         1.46         0.05

  Part-time in private sector      1.14         1.74         0.06
  Constant                        47.85 **      4.19
  Adjusted R2                      0.09
  N                                736

                                              Model 3

                                Coefficient   Standard   Standardised
                                               error     coefficient

Demographic characteristics
  Age                             -0.11 *       0.05         0.11
  Gender (Male =1)                 4.18 **      1.10         0.14
  Education in years               0.07         0.22         0.01

  Skilled Vocational Qual         -3.62 **      1.47        -0.08

  Basic Vocational Qual            2.21         1.90         0.04
Labor market characteristics
  Occupational status              0.10 **      0.02        -0.18
  (0 =farm labourer;

  Supervisor                      -4.41 **      1.01        -0.14

  Unskilled                          --

  Skilled                         -4.67 **      2.52        -0.13

  Professional                    -6.14 **      1.73        -0.07

  Full-time government               --

  Part-time government             1.36         2.61         0.02

  Full-time in private sector      1.68         1.35         0.05

  Part-time in private sector      3.06         1.62         0.08
  Stress                           0.27 **      0.03         0.35
  Constant                        38.67 **      3.93
  Adjusted R2                      0.19
  N                                735

** significantly different from zero at p = 0.01

* significantly different from zero at p = 0.05

Table 5. Robust regression predicting work-related stress from
educational and job characteristics. Australia 2001

                                              Standard    Standardised
                                Coefficient     error     coefficient

Demographic characteristics
  Age                            0.11 **        0.07          0.09
  Gender (Male =1)              -1.74           1.64         -0.04
  Education in years             0.05           0.33          0.01
  Skilled Vocational
    Qual (ABSCQ)                 0.02           2.17          0.00
  Basic Vocational
    Qual (ABSCQ)                -0.23           2.82          0.00
Labor market characteristics
  Occupational status            0.04           0.03          0.05
    (0 =farm labourer;
  Supervisor                     5.53 **        1.49          0.14
  Unskilled Self-employed         --
  Skilled Self-employed         -1.73           3.74          0.02
  Professional Self-employed    -5.05 **        2.56         -0.08
  Full-time government
    employee                      --
  Part-time government
    employee                    -0.15           3.87          0.00
  Full-time in private sector   -0.74           2.01         -0.02
  Part-time in private sector   -6.94 **        2.38         -0.14
  Constant                      25.88           5.75
  Adjusted R2                    0.03
  N                              735

** significantly different from zero at p = 0.01

* significantly different from zero at p = 0.05
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