484 Exploring fear in client-owned dogs: Insights from behavioral testing, owner surveys, and biomarker validation
Notice bibliographique
Résumé
Abstract Since the SARS-CoV-2 pandemic, pet professionals and owners have observed an increase in anxiety-related behaviors, including fearfulness, contributing to behavioral problems, reduction in pet and owner welfare, and increased rates of shelter relinquishment. The objectives of this study were to evaluate canine demographics and owner-identified fearfulness compared with fear-related behaviors during in-person behavior tests, with further verification using fear-related biomarkers. Client-owned dogs [n = 102; 25.3 ± 11.6 kg body weight (BW)] were included between 1 to 10 yr of age, of varying breeds, sex and neuter statuses, and home dynamics. Dogs had no known health issues, were not receiving medication, and were fed a standardized diet for 4 wk prior to testing. Owners provided information via a questionnaire regarding fear, anxiety, excitability, and separation behaviors, as well as information on the lifestyle and background of the dog. Behavior tests, which consisted of a novel human, novel object, and an open field test, were performed indoors in a constructed 3 x 3 m arena at the University of Guelph. Fecal samples were provided by owners and blood samples were collected immediately following the behavior assessment. Commercial ELISA kits were used to quantify fecal IgA, serum serotonin (5-HT), and 5-hydroxyindoleacetic acid (5-HIAA), then the 5-HIAA:5-HT ratio was calculated. Behavior tests were recorded on a GoPro camera, and behaviors were coded using BORIS. For preliminary analysis, owner questionnaire data relating to human-directed fear was separated into frequency of human-directed fear (HFF), intensity of human-directed fear (HFI), frequency of fear-related behaviors during grooming or veterinary visits (VHF), and intensity of fear-related behaviors during grooming or veterinary visits (VHI) section. Regression analyses were conducted using SAS, with outcomes derived from behavioral tests serving as dependent variables, and predictor variables encompassing sex, neuter status, age, BW, biomarker concentrations, and owner survey scores. Significance was determined at P ≤ 0.05 and trends at P ≤ 0.10. Preliminary data analysis using data from the novel human test of 50 dogs indicates that the duration of reduced body posture during the test was positively correlated with VHF (P = 0.0201) and VHI (P = 0.0226) scores, and negatively correlated with HIAA concentrations (P = 0.0134). The duration of the “side” ear position was also positively associated with HFF (P = 0.0219), HFI (P = 0.0471), and VHI (P = 0.0170) scores, with a trend observed in VHF (P = 0.0818) scores. Duration of time with ears pinned back was similarly associated with HFF (P = 0.0064), HFI (P = 0.0076), and VHI (0.0192) scores. These results suggest that behavior may be reliably predicted from owner-completed surveys and can be a valuable tool in gathering information for both professionals and the public. Further data analysis from the present study will be conducted to further understand the relationship between canine demographics, owner identified fear scores, physiological biomarkers and behavior testing results.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».