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Many promising Phase II trials have been carried out in head injury however to date there has been no successful translation of the positive results from these explanatory trials into improved patient outcomes in Phase III trials. Many reasons have been hypothesised for this failure. Outcomes in head injury trials are usually measured using the five point Glasgow Outcome Scale. Traditionally the ordinality of this scale is disregarded and it is dichotomised into two groups, favourable and unfavourable outcome. This thesis explores whether suboptimal statistical analysis techniques, including the dichotomisation of outcomes could have contributed to the reasons why Phase III trials have been unsuccessful. Based on eleven completed head injury studies, simulation modelling is used to compare outcome as assessed by the conventional dichotomy with both modelling that takes into account the ordered nature of the outcome (proportional odds modelling) and modelling which individualises a patient’s risk of a good or poor outcome ( the ‘sliding dichotomy’). The results of this modelling show that both analyses which use the full outcome scale and those which individualise risk show great efficiency gains (as measured by reduction in required sample sizes) over the conventional analysis of the binary outcome. These results are consistent both when the simulated treatment effects followed a proportional odds model and when they did not. Consistent results were also observed when targeting or restricting improvement to groups of subjects based on clinical characteristics or prognosis. Although proportional odds modelling shows consistently greater sample size reductions the choice of whether to use proportional odds modelling or the sliding dichotomy depends on the question of interest.

The mild head inured population accounts for 80 per cent of all head injuries and whilst research has identified no neurological abnormalities, this population still report to experience functional impairment. The current study set out to explore the biopsychosocial factors that could exacerbate the symptoms of mild head injury. In this respect, the study looks at the relationship between post concussion symptoms, social ability, psychological morbidity and coping style using the Rivermead Post-concussion symptoms Questionnaire, the Multidimensional Scale of Perceived Social Support, the Hospital Anxiety and Depression Scale and the COPE questionnaire. Questionnaires were sent out to 138 individuals at 6 months post injury to identify relationships between coping style, post concussion symptoms, social support and psychological morbidity. 32 respondents completed and returned the questionnaires. Post concussion symptoms were positively related to social support, depression and anxiety. Active coping was found to be negatively related to post concussion symptoms whereas emotion focused and avoidant coping were positively associated with post concussion symptoms. The results of the study suggest that in order to improve symptoms of mild head injury practitioners must address symptoms of depression and anxiety, in addition to promoting a more productive coping style.

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Background: Examining factors unique to major head injury (HI) etiogenesis can help reduce the burden of injury by identifying factors amenable to prevention. Objectives: To describe the epidemiology of HI in Nova Scotia. Risk and protective factors unique to HI were also examined specific to falls and Motor Vehicle Collision (MVC) injuries. Methods: Descriptive analyses and regression models were used to examine the socio-demographic profile of HI and associated risk factors using data from the Nova Scotia Trauma Registry. Results: Regression analyses for MVC-related injury found age, injury place, vehicle type and lack of safety restraint to be independently associated with an increased risk of HI. For falls-related injuries, age, time of trauma, injury mechanism and place were significant factors for a HI event. Conclusion: While HI share many similar characteristics to other major injuries, prevention programs must be aware of both common and unique risk factors for head injuries.

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No description available.