Abstract
Using a popular method of behaviour evaluation which rates the intensity of behaviour in different contexts, we demonstrate how pooling item scores relating to a given construct can reveal different potential risk factors for the dependent variable depending on how the total score is constructed. We highlight how similar simple total scores can be constructed through very different combinations of constituent items. We argue for the importance of examining individual item score distributions, and the results from different intensity thresholds before deciding on the preferred method for calculating a meaningful dependent variable. We consider simply pooling individual item scores which conflate context with intensity to calculate an average score and assuming this represents a biologically meaningful measure of trait intensity is a fallacy. Specifically using four items that describe intercat aggression and eleven that describe playfulness in cats in Fe-BARQ, we found sex and neuter status, social play and fearfulness were consistently significant predictors for intercat aggression scores; and age, age when obtained, social play and fearfulness were significant predictors of playfulness scores. However, the significance of other factors such as scratching varied with the threshold used to calculate to the total score. We argue that some of these inconsistent variables may be biologically and clinically important and should not be considered random error. Instead they need to be evaluated in the context of other available evidence.
Highlights
Surveys of animal carers allow us to potentially gather large datasets on the individuals with which they are familiar
A Novel Pooling Fallacy binary way, the sum score of items indicates the number of contexts in which the behaviour occurs; but if individual items relate to the frequency or intensity of the behaviour in a given context the interpretation of the sum/average of all items is more complicated
Four items make up the score for the factor “aggression towards other cats,” with each item relating to the frequency of the behaviour in four different contexts
Summary
Surveys of animal carers allow us to potentially gather large datasets on the individuals with which they are familiar. The Feline Behavioural Assessment and Research Questionnaire (Fe-BARQ) [2, 3] is a potentially useful behavioural instrument that was developed for the purposes of quantitative behavioural evaluation of pet cats in their home environment It comprises of 85 items which group into 23 factors measuring different aspects of cat behaviour (e.g., playfulness, sociability with people, purring and prey interest); this includes some potentially problematic issues such as aggressive behaviour (towards people, other cats and dogs) and repetitive behaviours. Factor scores may be strongly influenced by extreme values and while it may be argued that this reflects the intensity of a trait in some sense, it may not be very accurate This is of particular concern when we are interested in risk factors for a given factor especially when it relates to a potentially complex problem such as aggressive behaviour [9, 10]. Without access to the raw data of studies, we have no way of knowing the extent to which pooled results (and the conclusions which are drawn as a result) are affected by this potential problem
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