How Animals Communicate Quality of Life: The Qualitative Assessment of Behaviour

The notion ‘quality of life’ (QoL) suggests that welfare in animals encompasses more than just an absence of suffering; it concerns the quality of an animal’s entire relationship with its environment, of how it lives its life. Judgements of such quality are based on the integration of perceived details of how animals behave over time in different contexts. The scientific status of such judgements has long been ambiguous, but in recent decades has begun to be addressed by animal scientists. This paper starts with a brief review of qualitative approaches to the study of animal behaviour, which tend to address characteristics such as individuality, personality, and emotionality. The question then arises whether such characteristics involve a subjective, experiential aspect, and identify animals as sentient beings. The second half of this paper argues that taking the integrative nature of qualitative judgements seriously enables a ‘whole animal’ perspective, through which it becomes possible to view behaviour as a dynamic, expressive body language that provides a basis for assessing the quality of an animal’s experience (eg contented, anxious). Judging this quality is a skill that requires knowledge of species-specific behaviour, experience in observing and interacting with animals in different contexts, and a willingness to communicate with animals as sentient beings. A substantial body of research indicates that this skill can function reliably in a scientific context, and can be applied usefully as a practical welfare assessment tool. Thus qualitative approaches to the study of animal behaviour should make an important contribution to the growing interest in animal QoL

Animal Boredom: Is a Scientific Study of the Subjective Experiences of Animals Possible?

The aim of this paper is to explore the relationship between different meta-scientific frameworks and the science of animal welfare. Animal Boredom 117 During the past few years, I have become more and more convinced that the great difficulty science has in studying subjective experience in its objects, might be related to the denial of any role to subjective experience in the observer as an interpretational guide. Can a quality in the world around us be observed, when this same quality is deliberately excluded from the process of observing? As a practical example for the discussion described above, the phenomenon of animal boredom has been chosen. Boredom implies some sort of awareness, some form of a direct inner experience of selfhood. Because without a sense of selfhood related to the developmental potential of the animal, it would be impossible to miss certain things, to be bored. With the phenomenon of boredom one can illustrate the qualitative difference between behavioural and physiological deviations, but is still bored, since it misses the opportunity to perform its specific behaviour. How important behaviour is for an animal is a crucial question in theories on adaptation and stress, and as we shall see, on the existence of animal boredom as well

Applying ethological and health indicators to practical animal welfare assessment

There is a growing effort worldwide to develop objective indicators for animal welfare assessment, which provide information on an animal’s quality of life, are scientifically trustworthy, and can readily be used in practice by professionals. Animals are sentient beings capable of positive and negative emotion, and so these indicators should be sensitive not only to their physical health, but also to their experience of the conditions in which they live. This paper provides an outline of ethological research aimed at developing practical welfare assessment protocols. The first section focuses on the development and validation of welfare indicators generally, in terms of their relevance to animal well-being, their interobserver reliability, and the confidence with which the prevalence of described features can be estimated. Challenges in this work include accounting for the ways in which welfare measures may fluctuate over time, and identifying measures suited to monitoring positive welfare states. The second section focuses more specifically on qualitative welfare indicators, which assess the ‘whole animal’ and describe the expressive qualities of its demeanour (e.g. anxious, content). Such indicators must be validated in the same way as other health and behaviour indicators, with the added challenge of finding appropriate methods of measurement. The potential contribution of qualitative indicators, however, is to disclose an emotional richness in animals that helps to interpret information provided by other indicators, thus enhancing the validity of welfare assessment protocols. In conclusion, the paper emphasises the importance of integrating such different perspectives, showing that new knowledge of animals and new ways of relating to animals are bot

The qualitative assessment of responsiveness to environmental challenge in horses and ponies.

The responsiveness of 10 horses and 10 ponies to environmental challenge (represented by an open field test) was assessed using a qualitative approach based on free choice profiling methodology (FCP), which gives observers complete freedom to choose their own descriptive terms. Data were analysed with generalised Procrustes analysis (GPA), a multivariate statistical technique associated with FCP. A cross-validation of the outcomes of this approach to data recorded through quantitative behaviour analysis, and through a questionnaire given to the animals’ owner/riding instructor, was also performed using principal component analysis (PCA). Twelve undergraduate students generated their own descriptive vocabularies, by watching 20 horse/pony video clips lasting 2.5 min each. GPA showed that the consensus profile explained a high percentage of variation among the 12 observers, and differed significantly from the mean randomised profile ( p < 0.001). Two main dimensions of the consensus profile were identified, explaining 60% and 5.2% of the variation between animals, respectively. The 12 observer word charts interpreting these dimensions were semantically consistent, as they all converged towards the same meaning, albeit using different terms. The most used term to describe the positive end of axis 1 was ‘‘quiet’’, whereas ‘‘attentive’’ was the best positive descriptor of axis 2. The most frequently used descriptors for the negative ends of axes 1 and 2 were ‘‘nervous’’ and ‘‘bored’’, respectively. Thus, axis 1 was labelled as ‘‘quiet/nervous’’ and axis 2 was named as ‘‘attentive/bored’’. A marked effect of animal category was observed on the scores of the animals on the first dimension ( p < 0.001). Horses received significantly higher scores, and were thus assessed as more quiet and calm, than ponies. Conversely, ponies tended to receive lower scores on the second dimension ( p < 0.12), therefore they appeared less curious and attentive. The results of the PCA showed that the variables from different types of measurement clearly had meaningful relationships. For instance, the variables with the highest loading on the positive end of axis 1 were all indicative of tractable and docile animals, whereas axis 2 showed high loadings on the positive end for variables indicating attentive animals. Qualitative behaviour assessment proved to be an appropriate methodology for the study of horse behavioural responsiveness, in that it provided a multifaceted characterisation of horse behavioural expression that was in agreement with other quantitative and subjective assessments of the animals’ behaviour

Welfare assessment: correlations and integration between a Qualitative Behavioural Assessment and a clinical/health protocol applied in veal calves farms

This study is aimed at finding correlations and possible integration among Qualitative Behavioural Assessment (QBA) and a specific protocol of clinical/health evaluation. Both welfare assessment methods were based on direct animal observation and were applied in 24 Italian veal calves farms at 3 weeks (wks) of rearing. Principal component analysis (PCA) summarized 20 QBA descriptors on two main components (PC1 and PC2) with eigenvalues above 4 and explaining 29.6 and 20.3% of the variation respectively. PCA on residuals obtained after correcting for housing condition yielded highly similar results, indicating that the rearing environment of the calves was not an important determinant of the observer reliability of QBA. A relationship was found between QBA PC2 and the presence of signs of cross-sucking recorded during the clinical visit (presence PC2=1.11 vs. absence PC2=-1.55,