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Optimising the utility of injury surveillance systems to inform injury prevention in active populations
Version 2 2017-05-15, 02:20
Version 1 2017-03-22, 01:47
thesisposted on 2017-05-15, 02:20 authored by McKinnon, Adam David
Background: Injury is the most common disbenefit of participation in physical activity and has substantial related personal, social and economic costs. An understanding of where, when, how and to whom injuries occur is critical for the development of interventions designed to prevent injuries. Injury surveillance contributes to this understanding, and despite the importance of such systems, limited research exists examining their optimisation from a user perspective. Aim: To investigate strengths and weaknesses, and identify shortcomings of injury surveillance systems with regard to factors that influence system operation, and thereby identify enhancements that optimise system utility from a user perspective. Methods: Six studies utilising a series of complementary research designs were undertaken, some using more than one analysis method. Two qualitative studies, directed by the tenets of Grounded Theory, were conducted with key informants interacting with injury surveillance systems in the Australian Defence Force, and in the Australian state of Victoria, to determine system experiences and future operational expectations. The results of these qualitative studies informed the objectives and designs of the later research. A Discrete Choice Modeling study was then performed with 225 users of the Victorian Injury Surveillance System data output to determine user preferences toward predetermined current and hypothetical information dissemination mediums. Finally, three studies trialed and evaluated five novel analytical methods, previously untried in the analysis of injury surveillance data. The methods were: (1) the 11 and EWMA statistical process control charts, (2) Kohonen Self Organising Maps, and (3) the A priori Association Rule and SPSS Clementine Sequence Analysis algorithms. These analytical techniques were applied to an historical ADF injury data set. The process of applying each technique and interpreting the results obtained were evaluated using preliminary criteria designed to assess utility through the evaluation of usefulness and user responsiveness. Results: A range of factors relating to injury data collection, analysis and interpretation, and information dissemination that act as barriers to optimal injury surveillance in terms of quality, efficiency and usefulness were identified in the qualitative studies. Sociocontextual factors were also identified which were unique to each research setting. These have received limited attention in previous research. The Discrete Choice Modeling study indicated user preference, in order of preference strength, toward online dissemination of injury data and information, a willingness to pay for system information products (inverse relationship); an online information repository; and dissemination of a regular publication. The five data analysis methods each identified previously unidentified injury problems within the ADF data, and each met several of the criteria associated with utility. The strength and weaknesses of these methods are discussed. Conclusions: There is a scarcity of critical research directed at optimising the performance and utility of injury surveillance systems, particularly from a user perspective. This research identifies some potential means of achieving enhancements. Future research is required in two major categories: (l) the human interaction with all phases of injury surveillance systems; and (2) improving the empirical evidence and knowledge regarding optimal methods of analysis, interpretation and dissemination of injury surveillance data and information.