BACKGROUND & OBJECTIVE
Low back pain and burnout contribute to work-related loss through absent or poor performance. Sleep quality and quantity is linked to both pain and burnout through changes in the amygdala’s regulatory ability. The literature describes this change as related to increasing sleep debt. The authors set out to ‘disentangle’ the relationship between burnout and pain to see if there is a way to predict them based on sleep patterns.
The authors proposed that sleep problems could be an early warning sign for both risk of onset of pain and for burnout. Participants were asymptomatic, without low back pain and not suffering from “emotional exhaustion.” They expected that symptoms of burnout at the first follow-up would be predictive of the participant developing back pain by the second follow-up, and that this would be more pronounced among the older subjects and women.
Participants were drawn from an initial 2013 population-based survey in Switzerland (N=16,634). A random sampling of this data pool was selected (N=2,860) for initial inclusion. The final study sample after exclusions (those with back pain and/or emotional exhaustion at baseline) and non-return of questionnaires was N=406. Women comprised 38.8% and older subjects (45+ years) comprised 46.4%.
Sleep problems were assessed with two questions:
- “In the last four weeks, how well did you sleep?”
- “Did your sleep problems have any effects on your tiredness during the day?”
Low back pain was assessed with these questions:
“Current back problems:
- 0 = No
- 1 = Yes, but not currently undergoing treatment
- 2 = Yes, currently undergoing treatment”
“Note for low back/buttocks the average intensity of pain that you experienced in the last 4 weeks”.
Burnout had three questions to clarify the components of burnout:
- Emotional exhaustion - “In the last 4 weeks did you feel worn out?”
- Depersonalization - “How often do you feel that the things you do in daily life have little meaning?”
- Reduced performance - “How often do you feel that you can’t cope with the demands of your work?”
Data analysis was done through a confirmatory factor analysis to find paths between the variables, and the model fit was assessed by Root Mean Square Error of Approximation, Comparative Fit Index, and Standardized Root Mean Square Residual. These models predicted paths from sleep problems to LBP and burnout at the 24 and 36-month follow-ups.
Sleep problems were found to be predictors of both low back pain and burnout. Low back pain at the first follow-up was positively associated with burnout at the second follow-up, supporting the hypothesis of the study. They also found sleep