Asian Journal of Psychiatry 15 (2015) 77–78
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Letter to the Editor GHQ-12 as a predictor of burnout with emotional exhaustion in resident doctors
Keywords: Burnout Predictor Emotional distress Residency Questionnaire
I read the research paper by Ogundipe et al. (2014) with interest. The authors measured three dimensions of burnout, namely, emotional exhaustion (EE), depersonalization (D) and reduced personal accomplishment (RPA), and found no common factor in relation to the three dimensions of burnout in resident doctors. Among several independent variables, the presence of emotional distress, measured by the General Health Questionnaire-12-item version (GHQ-12), was the strongest predictor of EE, with an adjusted odds ratio of 6.97. I have some concerns on their study outcomes with special reference to the results of the GHQ-12 assessment. I have experience of using GHQ-12 in an occupational setting to check for psychological well-being. For example, I adopted a positive cutoff point of GHQ-12 of 4/3 instead of 3/2 in a 3-year follow-up study, and identified ‘feeling refreshed by sleep’ as a significant predictor of good psychological wellbeing in male workers with an odds ratio (95% confidence interval) of 0.56 (0.42–0.75) (Kawada, 2012). I conducted another survey on the association between job satisfaction and the GHQ-12 score (Kawada and Yamada, 2012). A multiple regression analysis with adjustment for gender and age revealed that a visual-analog scale score of 100 points for job satisfaction was inversely associated
with the GHQ-12 Likert-style score (p < 0.001), with an adjusted multiple correlation coefficient of 0.275. In addition, I conducted a cross-sectional study to identify the factors associated with the GHQ-12 scores (Kawada et al., 2011). Multiple logistic regression analysis identified young age, two-shift work, good sleep quality, night snacking with less than 4 times/week and habitual exercise as being significantly associated with a negative GHQ12 score using the 3/4 cutoff point. From these studies, I recommend that the authors re-explore the reason for the high odds ratio of the GHQ-12 score for EE, by a continuous survey with follow-up of the target population. Secondly, the authors observed 93 subjects with EE, 118 subjects with D, and 126 subjects with RPA among the 204 participants as events. They used a maximum of 6 independent variables for the logistic regression analysis, while the rule of the thumb that logistic and Cox regression models should be used with a minimum of 10 outcome events per predictor variable (Peduzzi et al., 1996) was maintained in their analysis. As other factors, such as the total number of events or sample size may influence the validity of the logistic model, the authors should examine a wide 95% confidence interval of the GHQ-12 score, expressed by 3.28– 14.78, for EE in a future study. Third, Ogundipe et al. (2014) showed no significant association between the perception of workload and each dimension of burnout. I previously reported the relationship between job satisfaction and the three sub-scales of a brief job stress questionnaire for workload in a cross-sectional study (Kawada and Otsuka, 2011). Logistic regression analysis revealed that job control and support contributed significantly to job satisfaction. In addition, unskilled manual workers showed significantly higher job dissatisfaction as compared to clerical workers. I suppose that the positions of resident doctors and supervisory doctors would reflect those of unskilled manual workers and clerical workers in my study. Taken together, I recommend that the authors conduct a further study on the causality of the association between workload and burnout.
Table 1 Prevalence (number) of scores on the General Health Questionnaire 12-item version (GHQ-12) of 3 or 4 in workers, stratified by the sex and age class. GHQ-12
Age in years
Cut-off in males
35–39 n = 1801
40–44 n = 1185
45–49 n = 1231
50–54 n = 738
3/2 4/3
58.4% (1052) 51.1% (921)
59.6% (706) 52.2% (619)
58.4% (719) 49.6% (611)
57.2% (422) 49.2% (363)
GHQ-12
Age in years
Cut-off in females
35–39 n = 73
40–44 n = 56
45–49 n = 38
50–54 n = 19
3/2 4/3
68.5% (50) 60.3% (44)
58.9% (33) 51.8% (29)
76.3% (29) 68.4% (26)
68.4% (13) 63.2% (12)
http://dx.doi.org/10.1016/j.ajp.2015.05.003 1876-2018/ß 2015 Elsevier B.V. All rights reserved.
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Letter to the Editor / Asian Journal of Psychiatry 15 (2015) 77–78
Finally, the authors should present the prevalence of emotional distress with a GHQ-12 score of 3. As additional information, I want to present here my recent data from workers, stratified by sex and age class (Table 1). There was no clear trend in the prevalence of a positive GHQ-12 score by age in males, and about a half of the population showed positive scores. In the case of females, I can only present the data from a limited number of subjects. Anyway, I speculate that a high prevalence of emotional distress can be observed in the study with a selected cutoff point of 3/2. References Kawada, T., 2012. Feeling refreshed by sleep can predict psychological wellbeing assessed using the General Health Questionnaire in male workers: a 3-year follow-up study. Psychiatry Invest. 9, 418–421. Kawada, T., Yamada, N., 2012. 100-point scale evaluating job satisfaction and the results of the 12-item General Health Questionnaire in occupational workers. Work 42, 415–418. Kawada, T., Otsuka, T., Inagaki, H., Wakayama, Y., Katsumata, M., Li, Q., Li, Y.J., 2011. Relationship among lifestyles, aging and psychological wellbeing using the General Health Questionnaire 12-items in Japanese working men. Aging Male 14, 115–118. Kawada, T., Otsuka, T., 2011. Relationship between job stress, occupational position and job satisfaction using a brief job stress questionnaire (BJSQ). Work 40, 393–399.
Ogundipe, O.A., Olagunju, A.T., Lasebikan, V.O., Coker, A.O., 2014. Burnout among doctors in residency training in a tertiary hospital. Asian J. Psychiatr 10, 27–32. Peduzzi, P., Concato, J., Kemper, E., Holford, T.R., Feinstein, A.R., 1996. A simulation study of the number of events per variable in logistic regression analysis. J. Clin. Epidemiol. 49, 1373–1379.
Tomoyuki Kawada* Department of Hygiene and Public Health, Nippon Medical School, Tokyo, Japan *Correspondence
to: Department of Hygiene and Public Health, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-Ku, Tokyo 113-8602, Japan. Tel.: +81 3 3822 2131; fax: +81 3 5685 3065 E-mail address:
[email protected] (T. Kawada). 29 December 2014