ArticleFrontiers in veterinary science2022
V-QBA vs. QBA-How Do Video and Live Analysis Compare for Qualitative Behaviour Assessment?
Article in Frontiers in veterinary science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Pasture Heterogeneity Improves Donkey Welfare: Effects of Structural Variation, Species Diversity, and Sward Height on Herd Emotional States.Animals : an open access journal from MDPI · 2025Article
- Use of animal-mounted accelerometers to identify positive welfare in dairy cattle.Dairy science and management · 2025Article
- Literature review of the use of Qualitative Behaviour Assessment with a fixed list of terms.Frontiers in veterinary science · 2025Review
- A systematic approach to defining and verifying descriptors used in the Qualitative Behavioural Assessment of sows.Animal welfare (South Mimms, England) · 2024Article
- The Power Is in the Word-Do Laypeople Interpret Descriptors of Dog Emotional States Correctly?Animals : an open access journal from MDPI · 2023Article
- Comparison of the welfare of beef cattle in housed and grazing systems: hormones, health, and behaviour.The Journal of agricultural science · 2023Article
- Long-Lasting Chews Elicit Positive Emotional States in Dogs during Short Periods of Social Isolation.Animals : an open access journal from MDPI · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Animal welfare is an inextricable part of livestock production and sustainability. Assessing welfare, beyond physical indicators of health, is challenging and often relies on qualitative techniques. Behaviour is a key component of welfare to consider and Qualitative Behaviour Assessment (QBA) aims to achieve this by systematically scoring behaviour across specific terms. In recent years, numerous studies have conducted QBA by using video footage, however, the method was not originally developed using video and video QBA (V-QBA) requires validation. Forty live QBAs were conducted, by two assessors, on housed beef cattle to help fill this validation gap. Video was recorded over the assessment period and a second video assessment was conducted. Live and video scores for each term were compared for both correlation and significant difference. Principle component analysis (PCA) was then conducted and correlations and differences between QBA and V-QBA for the first two components were calculated. Of the 20 terms, three were removed due to an overwhelming majority of scores of zero. Of the remaining 17 terms, 12 correlated significantly, and a significant pairwise difference was found for one ("Bored"). QBA and V-QBA results correlated across both PC1 (defined as "arousal") and PC2 (defined as "mood"). Whilst there was no significant difference between the techniques for PC1, there was for PC2, with V-QBA generally yielding lower scores than QBA. Furthermore, based on PC1 and PC2, corresponding QBA and V-QBA scores were significantly closer than would be expected at random. Results found broad agreement between QBA and V-QBA at both univariate and multivariate levels. However, the lack of absolute agreement and muted V-QBA results for PC2 mean that caution should be taken when implementing V-QBA and that it should ideally be treated independently from live QBA until further evidence is published. Future research should focus on a greater variety of animals, environments, and assessors to address further validation of the method.
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Registered trials
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