Development of a fixed list of descriptors for the qualitative behavioral assessment of thoroughbred horses in the racing environment

Fernando Mosquera Jaramillo; Tiago Marcelo Oliveira; Pedro Enrique Ayres Silva; Pedro Henrique Esteves Trindade; Raquel Yvonne Arantes Baccarin

doi:10.3389/fvets.2023.1189846

Development of a fixed list of descriptors for the qualitative behavioral assessment of thoroughbred horses in the racing environment

Front Vet Sci. 2023 Aug 10:10:1189846. doi: 10.3389/fvets.2023.1189846. eCollection 2023.

Authors

Fernando Mosquera Jaramillo^{1

2}, Tiago Marcelo Oliveira¹, Pedro Enrique Ayres Silva¹, Pedro Henrique Esteves Trindade^{3

4}, Raquel Yvonne Arantes Baccarin¹

Affiliations

¹ Department of Internal Medicine, School of Veterinary Medicine and Animal Science, University of São Paulo, São Paulo, Brazil.
² Equine Centre, Melbourne Veterinary School, Faculty of Science, University of Melbourne, Werribee, VIC, Australia.
³ Graduate Program in Anesthesiology, Medical School, São Paulo State University (Unesp), Botucatu, Brazil.
⁴ Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University (NCSU), Raleigh, NC, United States.

Abstract

Introduction: Horse racing is a major sport practiced worldwide. The environment to which horses are exposed during race meetings can influence their behavior. However, to the best of our knowledge, a method for assessing a horse's response to its surroundings during the pre- and post-race periods has not yet been reported. This study aimed to create a standard list of descriptors for use in a qualitative behavioral assessment (QBA) focused on assessing the emotional expressivity of horses before and after racing events.

Materials and methods: Seventy pre- or post-race 30-second videos of horses were randomly selected from our database of 700 videos. A panel of 8 experienced equine sports medicine specialist veterinarians watched a 60 min presentation on QBA. The panel then watched all videos randomly, simultaneously, individually, continuously, and without any verbal interaction, describing the descriptors related to the emotional expressivity of the horse after each video using a method known as free-choice profiling (FCP).

Results: The initial selection of descriptors was based on those indicated by more than one evaluator in the same video, or descriptors with more than 20 occurrences. The second selection was performed based on the content validity index (CVR) to select the descriptors retained in the previous step. Another panel of six veterinarians scored each of the descriptors retained for content validity on a visual scale. Interobserver reliability was estimated using the intraclass correlation coefficient (ICC) and its respective 95% confidence intervals (CI). A natural language processing (NLP) algorithm was used to analyze the behavior (positive or negative polarity) of the descriptors based on the lexicoPT package of R software.

Discussion/conclusion: NLP analysis considered the descriptors "agitated," "troubled," "restless" and "irritated" to have a negative polarity, while "focused," "relaxed" and "peaceful" had a positive polarity. In the principal component analysis (PCA), descriptors in a negative state were associated with each other and inversely associated with descriptors in a positive state. We conclude with a fixed list of descriptors to be used in a QBA to assess emotional and welfare expressivity in racehorses' pre- and post-race environments.

Keywords: QBA; behavior; environment; racehorses; thoroughbred.