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Abstract

Clinical ethics support services (CESS) are valuable tools in psychiatric practice. They have often been advocated as being useful by professionals in this field. More than 90% of German psychiatric hospitals have already implemented ethical support structures. However, despite this high implementation rate, the number of cases dealt with in these services is considerably low. Recent data suggests a mismatch between what is supplied and what is demanded. To develop their supportive capacities, structures and concepts of CESS must be reconsidered to fit psychiatry’s needs more accurately.

In this talk, the theoretical foundations of CESS are explored in regard to this challenge. One of their core elements is the claim of ethical expertise, that is, to be able to identify, analyze or solve ethical issues more accurate or better than others. Unfortunately, concepts of expertise within the context of CESS are manifold and often vague. In theoretic literature consistency -and even existence- of ethical expertise is often disputed. Claiming authority, it is said, is opposed by the idea of ethics itself. Others try to define expertise as kind of a practical skill rather than authority over a certain branch of knowledge.

Empirical evidence, however, suggests that this discussion might be misleading. At least in psychiatry, the idea of authority is rejected by clinicians in practice. On the contrary, experts are appreciated for their non-directive behaviour or their ability to provide normative insights and mutual understanding. It is recommended that experts should possess attributes like tolerance, prudence and integrity. Accordingly, the signifying property of expertise may not be its authority but rather its trustworthiness. Following this argument, trust-based concepts of expertise, their extent and their applicability in psychiatry are explored.

Forthcoming events

Infectious Disease Seminar Series: Hepatitis B diagnosis, prevention and treatment: laboratory approaches to the elimination agenda

Monday, 06 February 2023, 1pm to 2pm @ BDI Seminar Room LG 0-1, Old Road Campus, Headington, OX3 7LF

Richard Doll Seminar: Edgar Sydenstricker: Household Equivalence Scales and the Causes of Pellagra

Tuesday, 07 February 2023, 1pm to 2pm @ Richard Doll Lecture Theatre, Richard Doll Building, Old Road Campus, OX3 7LF

Ethox seminar- Feminist-Ethical Perspectives on Digital (Health) Technologies

Tuesday, 14 February 2023, 11am to 12.30pm @ Big Data Institute, Lower Ground Seminar Room 1, Oxford Population Heath, University of Oxford

Richard Doll Seminar - E-Freeze trial results

Tuesday, 14 February 2023, 1pm to 2pm @ Richard Doll Lecture Theatre, Richard Doll Building, Old Road Campus, OX3 7LF

Infectious Disease Seminar Series: Informing on Neisseria gonorrhoeae treatment and management through pathogen genomics

Monday, 20 February 2023, 1pm to 2pm @ BDI Seminar Room LG 0-1, Old Road Campus, Headington, OX3 7LF

Richard Doll Seminar- Triangulation of evidence in aetiological epidemiology: principles, prospects and limitations.

Tuesday, 21 February 2023, 1pm to 2pm @ Richard Doll Lecture Theatre, Richard Doll Building, Old Road Campus, OX3 7LF

Aetiological epidemiology is concerned with the identification of causal influences on disease risk. Randomized controlled trials are, when possible, the cornerstone of knowledge as to whether interventions based on aetiological studies are merited. It is not feasible to subject all of the many candidate causes to large-scale RCTs, however, even in situations where they are in principle possible. Triangulation of evidence is an approach that attempts to formally combine findings from different domains to strengthen causal inference. Triangulation embraces the variety of evidence thesis, that inferential strength depends not only on the quantity of available evidence, but also on its variety: the greater the variety, the stronger the resulting support. An essential condition is that the systematic errors and biases are unrelated across different study types. For example, the effect of raising circulating HDL cholesterol on the risk of coronary heart disease can be estimated from RCTs or through Mendelian randomization using genetic variants related to HDL level. Both the results of RCTs and Mendelian randomization studies could be biased. However, the potential biases in one study design would not influence estimates from the other approach: the biases are unrelated to each other. In observational epidemiology approaches that can be applied include the use of negative control exposures or outcomes; the deliberate use of data from contexts in which confounding structures differ; the use of instrumental variables and related approaches, such as regression discontinuity; quasi-experimental studies; the estimation of the expected magnitude of associations generated by confounding and the incorporation of mechanistic data, amongst others. Pre-registration of protocols for the triangulation of evidence increases confidence in the findings produced.