Effect of a Standardized Four-Week Desensitization and Counter-Conditioning Training Program on Pre-Existing Veterinary Fear in Companion Dogs
Bibliographic record
Abstract
Many dogs show signs of fear during veterinary appointments. It is widely recommended to use desensitization and counter-conditioning training to reduce this fear. However, the efficacy of this method for reducing veterinary fear has not been examined. We assessed the effect of a standardized four-week training program on behavioural and physiological signs of fear in dogs with pre-existing veterinary fear. Owned dogs were randomly allocated to receive training (n = 15) or no training (n = 22; Control). Owners of dogs in the training group were instructed to perform exam-style handling on their dog and to visit the veterinary clinic weekly. Owners of control dogs were given no instructions. Fear responses were assessed before and after the training period by a blinded observer during clinic arrival and examination. Despite motivated owners volunteering to participate in the current study, 44% of owners were non-compliant to this training program. During examination, control dogs had higher odds (95% confidence Interval (CI)) of reduced posture compared to trained dogs (Odds ratio (OR): 3.79, CI: 1.03–16.3). Fear scores for trained dogs lowered during the second examination (p = 0.046), and 86.7% of dog owners reported a reduction in their dog’s fear levels across the training period (p = 0.007). When entering the clinic (p = 0.002) and during examination (p = 0.002), trained female dogs had a higher rate of lip licking than control females. The training program did not influence temperature, heart rate, respiratory rate, avoidance, trembling, vocalizations, or willingness and encouragement to step on the scale. Results suggest that this four-week training program was mildly effective at reducing veterinary fear in dogs. Further research is necessary to explore the efficacy of longer, more intensive, and individualized training programs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".