484 Exploring fear in client-owned dogs: Insights from behavioral testing, owner surveys, and biomarker validation
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".