Associations of burnout with awakening and diurnal cortisol among police officers.

The aim of this cross-sectional study was to assess the associations of burnout with cortisol parameters in 197 police officers from the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) study (2010-2014). The Maslach Burnout Inventory-General Survey assessed depersonalization, exhaustion, and professional efficacy. Officers provided salivary cortisol samples collected upon awakening, and 15, 30, and 45 min thereafter as well as three additional samples at lunchtime, dinnertime, and bedtime. Total area under the curve with respect to increase (AUCWI for waking and AUCDI for diurnal), total area under the curve with respect to ground (AUCWG for waking and AUCDG for diurnal), and diurnal slope were determined and used in this study. Unadjusted and adjusted (age, sex, and race/ethnicity) associations were examined using linear regression. The mean age of the officers was 48 years and 72% were males. The depersonalization component of burnout was negatively associated with AUCDG (ß = -108.4; p = 0.036). Similarly, as exhaustion increased, AUCWI (ß = -9.58, p = 0.038), AUCDG (ß = -114.7, p = 0.029) and the diurnal slope (ß = -0.000038; p = 0.017) decreased. The Professional efficacy was not associated with any of the cortisol parameters. These results suggest that certain characteristics of burnout may be associated with diminished cortisol secretion in this group of urban police officers. Our findings add to previous studies examining associations of burnout with the cortisol awakening response. Future longitudinal studies are needed to evaluate the temporal relationship between burnout and these cortisol parameters.

Dimensional analysis of actigraphic derived sleep data.

Nonlinear dimensional analyses can be a useful tool in understanding the underlying behavior of dynamical systems, including biological systems. Many biological functions can be modeled as chaotic processes, including sleep. Sleep data can be obtained from several methods, such as electroencephalograms, polysomnography, and actigraph. Actigraphy, because of its low level of invasiveness, is an increasingly popular method of obtaining sleep data. This study analyzed actigraphy data with nonlinear dimensional analyses to determine if such analytic methods would be useful in sleep studies. Participants wore actigraphs on their wrists, which recorded movement for several days. Several sleep quality variables, such as movement during sleep and total sleep time, were derived from these sleep data. These variables were used to determine whether the quality of sleep was good or poor. Lagged phase space plots were graphed and nonlinear parameters for the fractal dimension and the correlation dimension were computed for each participant. Descriptive and inferential statistics were performed to determine if the nonlinear parameters showed significant differences with respect to sleep quality.