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Record W4413283874 · doi:10.3389/fvets.2025.1634970

Handling techniques and risk factors reported by veterinary professionals during dog examinations: a cross-sectional survey across Canada and the United States

2025· article· en· W4413283874 on OpenAlexaboutno aff
Lindsay Nakonechny, Alissa Cisneros, Carly M. Moody, Anastasia C. Stellato

Bibliographic record

VenueFrontiers in Veterinary Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCross-sectional studyVeterinary medicineMedicineEnvironmental healthFamily medicinePathology

Abstract

fetched live from OpenAlex

Introduction: Handling techniques are known to influence dog stress in veterinary settings; however, little is known about the current handling techniques applied to dogs during routine veterinary care or risk factors associated with their use. This cross-sectional survey aimed to assess common handling techniques used on calm, fearful, and aggressive dogs by veterinary professionals in Canada and the United States and identify risk factors for minimal and full-body restraint. Methods: A convenience sample of veterinary professionals completed an online questionnaire. It collected information on participant characteristics and clinic experience (e.g., gender, Ten Item Personality Index, bite history, stress-reducing certification), participant professional quality of life (using the ProQOL scale), general examination practices (e.g., use of treats), perceptions and importance of examination factors (e.g., staff safety), and frequency of using 14 different dog handling techniques. Logistic regression models were used to identify risk factors for the use of minimal and full-body restraint on fearful and aggressive dogs. Results: = 691) were veterinarians (39.2%, 271/691) and non-veterinarians (60.8%, 420/691), who routinely handle dogs during routine examinations in Canada (21.7%, 150/691) and the United States (79.1%, 541/691). Minimal restraint was reported to be used for calm (82.7%, 566/684), fearful (73.1%, 499/683), and aggressive (51.9%, 352/678) dogs during routine examinations. Full-body restraint was commonly reported to be used for calm dogs (58.5%, 400/684) and most frequently reported for fearful (63.9%, 434/679) and aggressive dogs (68.6%, 465/678). Handling decisions were influenced by factors including age, gender, practice type, graduation year, bite history, stress-reducing certification, and owner presence. Professionals prioritizing staff safety and using stress-reducing strategies (e.g., treats) were more likely to use minimal restraint, while owner presence and focus on examination completeness were linked to full-body restraint. Personality traits and professional well-being, particularly extraversion and secondary traumatic stress, also influenced handling choices. Discussion: Handling techniques vary with dog behavior and are shaped by numerous factors, highlighting the complex relationship between personal and clinic-level influences on veterinary staff interactions with dog patients. These findings generate hypotheses for future observational research exploring factors that support stress-reducing techniques to improve dog welfare in clinical settings.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.379
Teacher spread0.352 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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