It has been suggested that the way in which owners interact with their dogs can largely vary and influence the dog-owner bond, but very few objective studies, so far, have addressed how the owner interacts with the dog. The goal of the present study was to record dog owners' interaction styles by means of objective observation and coding. The experiment included eight standardized situations in which owners of pet dogs were asked to perform specific tasks including both positive (i.e. playing, teaching a new task, showing a preference towards an object in a food searching task, greeting after separation) and potentially distressing tasks (i.e. physical restriction during DNA sampling, putting a T-shirt onto the dog, giving basic obedience commands while the dog was distracted). The video recordings were coded off-line using a specifically designed coding scheme including scores for communication, social support, warmth, enthusiasm, and play style, as well as frequency of behaviors like petting, praising, commands, and attention sounds. Exploratory Factor Analysis of the 20 variables measured revealed 3 factors, labeled as Owner Warmth, Owner Social Support, and Owner Control, which can be viewed as analogues to parenting style dimensions. The experimental procedure introduced here represents the first standardized measure of interaction styles of dog owners. The methodology presented here is a useful tool to investigate individual variation in the interaction style of pet dog owners that can be used to explain differences in the dog-human relationship, dogs' behavioral outcomes, and dogs stress coping strategies, all crucial elements both from a theoretical and applied point of view.
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http://dx.doi.org/10.3791/56233 | DOI Listing |
Animals (Basel)
January 2025
Department of Basic Psychological Processes and Their Development, Euskal Herriko Unibertsitatea (UPV/EHU), Tolosa Hiribidea, 20018 Donostia, Spain.
The relationship between humans and their pets has long fascinated researchers, particularly in exploring how attachment varies according to the type of pet. Cats and dogs exhibit unique behavioral and social traits that influence the dynamics of human-pet relationships. Moreover, specific human characteristics have been found to affect this attachment.
View Article and Find Full Text PDFAnimals (Basel)
December 2024
Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Groblje 3, 1230 Domžale, Slovenia.
Our understanding of social cognition in brachycephalic dog breeds is limited. This study focused specifically on French Bulldogs and hypothesized that a closer relationship between dog and owner would improve the dogs' understanding of nonverbal cues, particularly pointing gestures. To investigate this, we tested twenty-six dogs and their owners in a two-way object choice test in which the familiar person pointed to the bowl.
View Article and Find Full Text PDFNat Immunol
January 2025
Department of Immunology and Neag Comprehensive Cancer Center, University of Connecticut School of Medicine, Farmington, CT, USA.
T cells recognize neoepitope peptide-major histocompatibility complex class I on cancer cells. The strength (or avidity) of the T cell receptor-peptide-major histocompatibility complex class I interaction is a critical variable in immune control of cancers. Here, we analyze neoepitope-specific CD8 cells of distinct avidities and show that low-avidity T cells are the sole mediators of cancer control in mice and are solely responsive to checkpoint blockade in mice and humans.
View Article and Find Full Text PDFAnim Welf
December 2024
Department of Animal Science, University of California, Davis, CA, USA.
US and Canadian caregivers (n = 6,529) of two domestic cats () were recruited to participate in an online cross-sectional questionnaire to assess: (1) knowledge of inter-cat behaviour; (2) the frequency of positive and negative cat-cat interactions in the home; and (3) factors associated with positive and negative cat-cat interactions in the home. The questionnaire included ten videos (five negatively valenced, five positively valenced), in which participants scored: the overall cat-cat interaction; cat 1's experience; and cat 2's experience, using a Likert scale. Participants were also asked to report how often they see each interaction in their own two cats.
View Article and Find Full Text PDFAnimals (Basel)
December 2024
Division of Artificial Intelligence Engineering, National Korea Maritime & Ocean University, Busan 49112, Republic of Korea.
While the pet market is continuously rapidly increasing in Korea, pet dog owners feel uncomfortable in coping with pet dog's health problems in time. In this paper, we propose a pre-diagnosis system based on neuro-fuzzy learning, enabling non-expert users to monitor their pets' health by inputting observed symptoms. To develop such a system, we form a disease-symptom database based on several textbooks with veterinarians' guidance and filtering.
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