Abstract
Scientific assessment of affective states in animals is challenging but vital for animal welfare studies. One possible approach is Qualitative Behavioural Assessment (QBA), a ‘whole animal’ methodology which integrates information from multiple behavioural signals and styles of behavioural expression (body language) directly in terms of an animal's emotional expression. If QBA provides a valid measure of animals’ emotional state it should distinguish between groups where emotional states have been manipulated. To test this hypothesis, QBA was applied to video-recordings of pigs, following treatment with either saline or the neuroleptic drug Azaperone, in either an open field or elevated plus-maze test. QBA analysis of these recordings was provided by 12 observers, blind to treatment, using a Free Choice Profiling (FCP) methodology. Generalised Procrustes Analysis was used to calculate a consensus profile, consisting of the main dimensions of expression. Dimension one was positively associated with terms such as ‘Confident’ and ‘Curious’ and negatively with ‘Unsure’ and ‘Nervous’. Dimension two ranged from ‘Agitated’/‘Angry’ to ‘Calm’/‘Relaxed’. In both tests, Azaperone pre-treatment was associated with a more positive emotionality (higher scores on dimension one reflecting a more confident/curious behavioural demeanour) than control pigs. No effect of drug treatment on dimension two was found. Relationships between qualitative descriptions of behaviour and quantitative behavioural measures, taken from the same recordings, were found. Overall, this work supports the use of QBA for the assessment of emotionality in animals.
Highlights
The assessment of affective states in animals is a critical component of animal welfare research
A report from the UK Farm Animal Welfare Council (FAWC, 2009) on the future of animal welfare research emphasised the importance of including consideration of positive welfare states and the role that Qualitative Behavioural Assessment (QBA) could play in assessing these
Assessment of the words positively or negatively associated with each dimension (Table 2) demonstrates the semantic coherence generated across observers
Summary
The assessment of affective states in animals is a critical component of animal welfare research. Qualitative Behavioural Assessment (QBA) is one such method. QBA is a whole-animal approach, and the underlying premise is that human observers can integrate perceived behavioural details and signals to judge an animal’s behavioural expression, using qualitative. A recent review of methodologies that might be used to assess positive welfare states in cattle concluded that QBA was ‘the most promising’ assessment methodology (Napolitano et al, 2009). Boissy et al, 2007b noted that QBA represented one of the most immediately applicable methodologies for assessing positive emotions in animals. A report from the UK Farm Animal Welfare Council (FAWC, 2009) on the future of animal welfare research emphasised the importance of including consideration of positive welfare states and the role that QBA could play in assessing these
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