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Could a new Mental Health Act distort clinical judgement? A Bayesian justification of naturalistic reasoning about risk

Background: The proposed new Mental Health Act for England and Wales places a premium on identifying substantial clinical risk. This raises the question of how justifiable judgements about risk can be made when the evidence in this area is based upon frequentist statistical analysis which is of limited value in clinical practice. Aims: To develop a model of judgement about risk that articulates the relationship between the results of classical statistical research and the real-time reasoning of professionals in clinical practice. Methods: We use a Bayesian framework to explore the respective roles of frequentist quantities relating to classes and qualitative data idiosyncratic to individuals in real-time reasoning about risk. Results: We develop a model of naturalistic reasoning about risk within which clinical judgement is central. Conclusions: Data that stands as evidence in research literature recedes to become background knowledge in clinical practice, while difficult-to-quantify information idiosyncratic to individuals actually determines clinical judgement. This process is relatively neglected in the literature. We therefore advocate greater research into the reasoning process underlying judgements about clinical risk and advance some suggestions about how that reasoning might be better supported. It should be a matter of concern that legislation such as the proposed Mental Health Act could impair such reasoning. Declaration of Interest: None.