Assessing knowledge, attitudes, and practices of Canadian veterinarians with regard to Lyme disease in dogs
Bibliographic record
Abstract
BACKGROUND: The blacklegged tick (BLT) is a vector for the bacterium Borrelia burgdorferi (Bb), which causes Lyme disease. Range expansion of the BLT in Canada is related to an increased risk of Lyme disease in many regions. Current literature, such as the 2018 American College of Veterinary Internal Medicine consensus statement, suggests that there may be differences in the approaches of veterinarians who encounter dogs exposed to Bb and dogs with Lyme disease. OBJECTIVES: To determine current knowledge, attitudes, and practices of Canadian veterinarians regarding Lyme disease in dogs. ANIMALS: None. METHODS: An online survey was distributed to Canadian veterinarians through veterinary associations and industries. Survey responses were analyzed using descriptive statistics, spatial analysis, Fisher's exact tests, and univariable logistic regression. RESULTS: At the completion of the survey, 192 responses were received from veterinarians practicing in all 10 Canadian provinces. Answers to short scenario and treatment questions reflected a wide variety of clinical approaches taken by veterinarians. Regional differences were seen in reported tick distribution and clinical approaches. CONCLUSIONS AND CLINICAL IMPORTANCE: Regional differences and generalized differences were found in approaches used by responding Canadian veterinarians with regard to managing Bb exposure and Lyme disease in dogs. We identified areas for future research and knowledge mobilization for veterinarians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".