In their day-to-day tasks, police officers are repeatedly subjected to stressful and traumatic events and as such are at significant risk of developing post - traumatic stress disorder (PTSD). There is a wealth of literature exploring risk and protective factors, however there is still a need to develop our understanding of specific factors which may be unique to the police. In light of this need, two potential factors have been identified for this current research, burnout and social connectedness. Burnout relates to a culmination of stress which is unmanaged and untreated. Social connectedness relates to the internal experience of feeling connected to others and the world around. This thesis is primarily concerned with exploring the relationship between these factors and PTSD and general distress within the context of the police force. This research took place within one UK police force. In total, 93 participants from specialist departments at high risk of exposure to trauma took part in an online survey. The survey included self-report measures of burnout, social connectedness, Post-Traumatic Stress Disorder (PTSD) and general distress. Non-standardised measures also sought to capture demographic information and an additional outcome variable of sickness absence. A series of multiple forced-entry regressions were carried out. Increased symptoms of exhaustion (one aspect of burnout), significantly predicted increased PTSD symptom severity. Further exploratory analyses found that exhaustion significantly predicted two of the four PTSD symptom clusters: intrusion and alterations in arousal and reactivity. The same multiple regression analysis indicated that social connectedness made a significant contribution to the model predicting PTSD symptom severity, greater than that of exhaustion. It was also found that increased symptoms of exhaustion significantly predicted increased general distress, whereas disengagement (a further aspect of burnout) and social connectedness did not. Lastly, it was found that none of the predictor variables made a significant contribution to the model predicting sickness absence. These findings are discussed in terms of their theoretical and clinical implications.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:693703 |
| Date | January 2016 |
| Creators | Melunsky, Nina |
| Publisher | University of Essex |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://repository.essex.ac.uk/17511/ |
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