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Measuring emotional contagion in Horse-Human interactions: A systematic scoping review of methods and outcomes
Mirela Alexandra Tripon1, Dan Manolăchescu2, Ionel Papuc2
1Department of Reproduction, Faculty of Veterinary Medicine, University of Agricultural Sciences and Veterinary Medicine, Mănăștur St. 3-5, 400372 Cluj-Napoca, Romania.
Background:
Emotional contagion between horses and humans is a key aspect of their interaction, influencing welfare, training, and therapy, yet current methods for measuring this phenomenon lack standardization and consistency.
Aims/Objectives:
The aim of this study was to verify what methods are used to assess emotional contagion in horse-human interactions, and what outcomes have been reported.
Methods:
A systematic search of Google Scholar, Web of Science, Scopus, PubMed, and Science Direct was conducted up to March 2024. Peer-reviewed studies assessing emotional transfer through behavioral and/or physiological measures were included; studies outside this scope were excluded. From n=486 records screened, n=104 met inclusion criteria. Behavioral indicators included body language, facial expressions, and vocalizations. Physiological indicators included heart rate, heart rate variability (HRV), and cortisol concentrations.
Results:
Behavioral measures, particularly body language (73.1 %), were most frequently applied. Heart rate (49 %) and HRV (30.8 %) dominated physiological assessments, while cortisol was less often used. Studies combining behavioral and physiological methods, especially body language with heart rate or variability, provided more robust insights into emotional contagion. However, methodological inconsistencies and lack of standardized frameworks limited comparability across studies.
Conclusion:
Combining behavioral and physiological measures offers a more comprehensive assessment of emotional contagion in horse-human interactions. To advance this field, standardized frameworks, interdisciplinary collaboration, and integration of emerging technologies such as artificial intelligence and wearable devices are needed. These improvements could enhance reliability, enable real-time monitoring, and support evidence-based practices that benefit both horse welfare and human-horse interactions.
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