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  • Title: An exploration of the prevalence and predictors of work-related well-being among psychosocial oncology professionals: An application of the job demands-resources model.
    Author: Turnell A, Rasmussen V, Butow P, Juraskova I, Kirsten L, Wiener L, Patenaude A, Hoekstra-Weebers J, Grassi L, IPOS RESEARCH COMMITTEE.
    Journal: Palliat Support Care; 2016 Feb; 14(1):33-41. PubMed ID: 26653250.
    Abstract:
    OBJECTIVE: Burnout is reportedly high among oncology healthcare workers. Psychosocial oncologists may be particularly vulnerable to burnout. However, their work engagement may also be high, counteracting stress in the workplace. This study aimed to document the prevalence of both burnout and work engagement, and the predictors of both, utilizing the job demands-resources (JD-R) model, within a sample of psychosocial oncologists. METHOD: Psychosocial-oncologist (N = 417) clinicians, recruited through 10 international and national psychosocial-oncology societies, completed an online questionnaire. Measures included demographic and work characteristics, burnout (the MBI-HSS Emotional Exhaustion (EE) and Depersonalization (DP) subscales), the Utrecht Work Engagement Scale, and measures of job demands and resources. RESULTS: High EE and DP was reported by 20.2 and 6.6% of participants, respectively, while 95.3% reported average to high work engagement. Lower levels of job resources and higher levels of job demands predicted greater burnout, as predicted by the JD-R model, but the predicted interaction between these characteristics and burnout was not significant. Higher levels of job resources predicted higher levels of work engagement. SIGNIFICANCE OF RESULTS: Burnout was surprisingly low and work engagement high in this sample. Nonetheless, one in five psychosocial oncologists have high EE. Our results suggest that both the positive (resources) and negative (demands) aspects of this work environment have an on impact burnout and engagement, offering opportunities for intervention. Theories such as the JD-R model can be useful in guiding research in this area.
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