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Title: A Bayesian investigation of farm vet's beliefs
Author: Higgins, Helen Mary
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2013
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The widespread uptake of preventive veterinary strategies to control the endemic diseases of farmed animals is important for animal health and welfare, the sustainability of farming, food security and public health. Chapters 2 and 3 report the current involvement and clinical beliefs of veterinary surgeons concerning herd-level endemic disease control strategies. Chapter 4 uses probabilistic elicitation to quantify how veterinary surgeons' beliefs changed following exposure to hypothetical clinical trial data and compares the change to predictions from Bayes theorem. The practical method developed is generally applicable to any context where quantifying a change in belief is important, and has wide potential both for research and as an educational tool. Chapter 5 uses this methodology to explore how veterinary beliefs changed after exposure to real data in the form of recent research findings concerning ovine footrot; qualitative methodology was employed in conjunction to understand why beliefs changed. In chapter 6, the dual importance of veterinary surgeons' ethical and clinical beliefs is explored using dairy cow fertility as an example. Results suggest that there is considerably more scope for proactive veterinary involvement with disease control, and cast a shadow over the extent to which a consistent approach is being delivered in practice. National control strategies are required but the lack of randomised clinical trials to base them on is problematic. It is argued that future trials should be designed in a Bayesian framework, and due to the ethical tensions and multiple stakeholders, researchers must publicise the effectiveness of interventions broadly as costs and benefits to society. However, since it appears that many veterinary surgeons do not update their beliefs logically, results should be reported using a variety of representative prior beliefs to help clinicians make best use of new data. It is hoped that this work will provide inspiration and motivation for future work and research collaborations between clinicians, psychologists and statisticians.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available