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Teacher burnout and turnover intent

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Abstract

Correlates of turnover intent among primary (N = 580) and secondary (N = 675), male (N = 254) and female (N = 999) teachers, were examined through the lens of the job demands-resources (JD-R) model. Multigroup structural equation modelling indicated that job demands (workload, student misbehaviour), and the personal demand of work–family conflict, were positively associated with emotional exhaustion—the core dimension of burnout. All demands indirectly related to turnover intent via emotional exhaustion. Among all teacher groups, no significant differences were found in level of emotional exhaustion or turnover intent, and only mild stress was reported as a result of student misbehaviour. Work–family conflict was the strongest predictor of emotional exhaustion for male and female teachers. Results suggest the JD-R as a promising theory for use in explaining job-related outcomes among Australian teachers, and that personal demands should be examined in addition to job demands within it.

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Notes

  1. Copyright ©1996 Christina Maslach, Susan E. Jackson & Richard L. Schwab. All rights reserved in all media. Published by Mind Garden, Inc., www.mindgarden.com.

  2. Increasing a scale’s response format from 5 to 7 does not make any appreciable difference to the distributional properties (skewness/kurtosis), nor does it destroy the comparability of historical data (Dawes 2008).

  3. Little’s MCAR test was not significant, χ2(616) = 686.69, p > 0.05.

  4. Due to low numbers of male primary teachers (n = 83), it was not possible to cross gender by school level.

  5. Cohen’s d provides a metric for comparing effects between groups that is not biased by sample size.

  6. In Australia, household tasks have become less gendered over time, and as men become more egalitarian in their attitudes, they become more willing to do what was traditionally (e.g. cooking, cleaning, laundry) known as women’s work (Chesters 2012).

  7. The average travel time across Australian cities ranges from approximately 3 (Northern Territory) to 6 h (Sydney).

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  1. Faculty of Education, Monash University, Wellington Road, Melbourne, VIC, 3800, Australia

    Natalia Rajendran & Paul W. Richardson

  2. School of Education and Social Work, The University of Sydney, Manning Road, Sydney, NSW, 2006, Australia

    Helen M. G. Watt

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Appendix

Appendix

Measurement model for primary versus secondary and male versus female teachers

Results of the initial CFAs revealed the data did not fit the model sufficiently well for any teacher group: primary—χ2(314, N = 580) = 1244.831, p < 0.001, CFI = 0.912, TLI = 0.902, RMSEA = 0.073 (CI 0.069–0.077) and SRMR = 0.062; secondary—χ2(314, N = 675) = 1472.285, p < 0.001, CFI = 0.907, TLI = 0.896, RMSEA = 0.076 (CI 0.072–0.080) and SRMR = 0.067; male—χ2(314, N = 254) = 741.414, p < 0.001, CFI = 0.900, TLI = 0.888, RMSEA = 0.073 (CI 0.066–0.080) and SRMR = 0.067; female—χ2(314, N = 999) = 1823.928, p < 0.001, CFI = 0.906, TLI = 0.894, RMSEA = 0.069 (CI 0.066–0.072) and SRMR = 0.064. Examination of the modification indices (MIs) revealed the measurement error covariance between EE8 and EE4 indicated large MIs in all samples: primary MI = 243.863, secondary MI = 297.232; male MI = 92.226, female MI = 419.159. Inspection of the items EE8 (“Working with people directly puts too much stress on me”) and EE4 (“Working with people all day is really a strain for me”) revealed item content overlap/parallel wording of the items relating to the negative impact that working with people can have on a person which would explain their additional relationship. Therefore, the error covariance for these two items was freed for estimation and the models were reanalysed. This resulted in acceptable fit of the data to the model, in all samples: primary, χ2(313, N = 580) = 941.271, p < 0.001, CFI = 0.941, TLI = 0.933, RMSEA = 0.060 (CI 0.056–0.064) and SRMR = 0.057; secondary, χ2(313, N = 675) = 1097.944, p < 0.001, CFI = 0.937, TLI = 0.929, RMSEA = 0.062 (CI 0.058–0.066) and SRMR = 0.063; male, χ2(313, N = 254) = 634.508, p < 0.001, CFI = 0.925, TLI = 0.916, RMSEA = 0.064 (CI 0.056–0.071) and SRMR = 0.064; female, χ2(313, N = 999) = 1298.573, p < 0.001, CFI = 0.938, TLI = 0.931, RMSEA = 0.056 (CI 0.053–0.059) and SRMR = 0.060. The measurement models of the measures used in the current study for primary and secondary teachers are shown in Fig. 3, and those for male and female teachers are shown in Fig. 4. Except for item sm5 on the student misbehaviour factor, all items showed moderate to high factor loadings (standardised), across all subsamples.

Fig. 3
figure 3

Measurement model of the measures used in the study across primary and secondary teachers. wfc work–family conflict, wrk workload, sm student misbehaviour, emot emotional exhaustion, toi turnover intent

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Fig. 4
figure 4

Measurement model of the measures used in the study across gender groups. wfc work–family conflict, wrk workload, sm student misbehaviour, emot emotional exhaustion, toi turnover intent

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Rajendran, N., Watt, H.M.G. & Richardson, P.W. Teacher burnout and turnover intent. Aust. Educ. Res. 47, 477–500 (2020). https://doi.org/10.1007/s13384-019-00371-x

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