PeerJ (Jun 2024)

Choice-based severity scale (CSS): assessing the relative severity of procedures from a laboratory animal’s perspective

  • Lauren Cassidy,
  • Stefan Treue,
  • Alexander Gail,
  • Dana Pfefferle

DOI
https://doi.org/10.7717/peerj.17300
Journal volume & issue
Vol. 12
p. e17300

Abstract

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One primary goal of laboratory animal welfare science is to provide a comprehensive severity assessment of the experimental and husbandry procedures or conditions these animals experience. The severity, or degree of suffering, of these conditions experienced by animals are typically scored based on anthropocentric assumptions. We propose to (a) assess an animal’s subjective experience of condition severity, and (b) not only rank but scale different conditions in relation to one another using choice-based preference testing. The Choice-based Severity Scale (CSS) utilizes animals’ relative preferences for different conditions, which are compared by how much reward is needed to outweigh the perceived severity of a given condition. Thus, this animal-centric approach provides a common scale for condition severity based on the animal’s perspective. To assess and test the CSS concept, we offered three opportunistically selected male rhesus macaques (Macaca mulatta) choices between two conditions: performing a cognitive task in a typical neuroscience laboratory setup (laboratory condition) versus the monkey’s home environment (cage condition). Our data show a shift in one individual’s preference for the cage condition to the laboratory condition when we changed the type of reward provided in the task. Two additional monkeys strongly preferred the cage condition over the laboratory condition, irrespective of reward amount and type. We tested the CSS concept further by showing that monkeys’ choices between tasks varying in trial duration can be influenced by the amount of reward provided. Altogether, the CSS concept is built upon laboratory animals’ subjective experiences and has the potential to de-anthropomorphize severity assessments, refine experimental protocols, and provide a common framework to assess animal welfare across different domains.

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