Dr. Jennifer Wild from the University of Oxford explained: "Emergency workers are regularly exposed to stressful and traumatic situations and some of them will experience periods of mental illness. Some of the factors that make that more likely can be changed through resilience training, reducing the risk of PTSD and depression. We wanted to test whether we could identify such risk factors, making it possible to spot people at higher risk early in their training and to develop interventions that target these risk factors to strengthen their resilience."
The researchers followed a group of around 400 new ambulance staff through the first two years of their three-year training period. During the initial six-week classroom phase of the training, the students were given a number of assessments to establish their thinking styles, coping behaviour, psychiatric history and personality traits. Follow up sessions were carried out every four months for the next two years to see if any of the participants had had PTSD or depression. After two years, a final assessment looked at quality of life, as well as smoking, alcohol and drug use, days off work, weight change, burnout and insomnia.
The team found that even accounting for past psychiatric history, people were more likely to experience PTSD and depression if they had lower perceived resilience to trauma, or if they dwelled on stressful events from the past before they started their training. Significantly, the number of traumatic incidents they experienced could not be used to predict PTSD but was relevant to predicting MD, suggesting a cumulative risk of different exposures to trauma for depression.
Dr. Wild concludes: "This is not about screening out particular people in training. Early assessment means that those who are more at risk can be offered training to improve their resilience to stressful and traumatic experiences. That has the potential to reduce episodes of PTSD and major depression and improve the long term health of a valued and essential workforce."
(© University of Oxford, AcademiaNet)