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Abstract

There has been limited research on humans’ ability to perceive and predict social interactions among cats using facial signals. This area is crucial to explore since conflicts between cats often cause significant stress for their guardians. By evaluating individuals’ skills in understanding cat interactions, researchers can develop tools to help guardians predict affiliative and nonaffiliative behaviors, leading to effective intervention strategies for multicat households. We distributed a survey to individuals subscribed to the Companion Animals New Zealand newsletter to assess cat guardians’ effectiveness in perceiving and predicting various social interactions among cats. We hypothesized that guardians with one or more cats (P1), those who grew up with cats (P2), or those who frequently interacted with cats (P3) would perform similarly to those without such experiences. Additionally, we predicted that guardians with professional experience (P4) would outperform those without. The survey consisted of four parts: (1) assessing participants’ experiences and knowledge of cats; (2) an experimental video paradigm; (3) a follow-up assessment; and (4) a demographic questionnaire. Participants viewed 10 video clips (five affiliative and five nonaffiliative) showcasing the beginning of cat interactions and were asked to predict the outcomes based on facial signals. Specifically, participants had to determine whether the outcome would be friendly or not and describe their predictions. Afterward, they watched complete interactions to revise their responses. We found that participants struggled most with predicting nonaffiliative interactions based on facial signals. Predictions P1 to P3 received full support, while P4 received partial support; participants with professional experience performed significantly better at identifying nonaffiliative facial signals. Although our sample of videos and facial signals is limited, our results suggest that creating training tools to help participants recognize and respond to nonaffiliative facial signals is a promising direction. Additionally, early intervention strategies may prove to be the most effective approach.

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