Rethinking the utility of the Five Domains model

Jordan O Hampton, Lauren M Hemsworth, Paul H Hemsworth, Timothy H Hyndman, Peter Sandøe

Research output: Contribution to journalJournal articleResearchpeer-review

11 Citations (Scopus)
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Abstract

The Five Domains model is influential in contemporary studies of animal welfare. It was originally presented as a conceptual model to understand the types of impact that procedures may impose on experimental animals. Its application has since broadened to cover a wide range of animal species and forms of animal use. However, it has also increasingly been applied as an animal welfare assessment tool, which is the focus of this paper. Several critical limitations associated with this approach have not been widely acknowledged, including that: (1) it relies upon expert or stakeholder opinion, with little transparency around the selection of these individuals; (2) quantitative scoring is typically attempted despite the absence of clear principles for aggregation of welfare measures and few attempts to account for uncertainty; (3) there have been few efforts to measure the repeatability of findings; and (4) it does not consider indirect and unintentional impacts such as those imposed on non-target animals. These deficiencies lead to concerns surrounding testability, repeatability and the potential for manipulation. We provide suggestions for refinement of how the Five Domains model is applied to partially address these limitations. We argue that the Five Domains model is useful for systematic consideration of all sources of possible welfare compromise and enhancement, but is not, in its current state, fit-for-purpose as an assessment tool. We argue for wider acknowledgment of the operational limits of using the model as an assessment tool, prioritisation of the studies needed for its validation, and encourage improvements to this approach.
Original languageEnglish
Article numbere62
JournalAnimal Welfare
Volume32
Number of pages10
ISSN0962-7286
DOIs
Publication statusPublished - 2023

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