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Record W4400084904 · doi:10.1111/evj.14115

Biosecurity perceptions among <scp>Ontario</scp> horse owners during the <scp>COVID‐19</scp> pandemic

2024· article· en· W4400084904 on OpenAlexaffabout
Juliet A. Germann, Terri L. O’Sullivan, Amy L. Greer, Kelsey L. Spence

Bibliographic record

VenueEquine Veterinary Journal · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiosecurityPandemicThematic analysisOutbreakSnowball samplingRisk perceptionEnvironmental healthMedicineQualitative researchCoronavirus disease 2019 (COVID-19)PerceptionVeterinary medicineDiseasePsychologyInfectious disease (medical specialty)Virology

Abstract

fetched live from OpenAlex

BACKGROUND: Disease outbreaks present a significant challenge to horse health and welfare and the economic stability of horse industries internationally. This is a particular concern in Ontario, Canada, where there have been frequent outbreaks of respiratory infectious diseases among horses. Despite these risks, there has been limited research on whether Ontario horse owners engage in biosecurity measures sufficient to mitigate risk of equine diseases, and whether current events such as the COVID-19 pandemic influence attitudes towards equine biosecurity practices. OBJECTIVE: To explore Ontario horse owners' perceptions, attitudes and experiences relating to on-farm biosecurity during the COVID-19 pandemic. STUDY DESIGN: Qualitative study using virtual semi-structured interviews. METHODS: Participants (horse owners, frequent horse riders and part boarders) were recruited using social media snowball sampling where advertisements were shared by equine and veterinary organisations. Interviews were conducted virtually between June and September 2022 and were analysed using reflexive thematic analysis. RESULTS: Three key themes relating to biosecurity perceptions among the 14 participants were identified. Participants relied on minimal preventative measures (such as vaccines) where perceived risk of disease was low, but implemented additional measures including quarantine and handwashing when perceived risk of disease was high. Participants' choice of biosecurity practices often mirrored those recommended by the barn manager. Moreover, participants felt that responsibility for biosecurity was not shared equally across horse owners, with more emphasis placed on those engaging in high-risk situations for disease spread. Despite experiencing biosecurity during the COVID-19 pandemic, horse owners were not consistently applying these practices to their horse care routines. MAIN LIMITATIONS: The perspectives reported here are from a small sample of horse owners and may not be generalisable to all populations. CONCLUSIONS: Our findings indicate that horse owners need improved access to and engagement with educational initiatives that emphasise the importance and purpose of all biosecurity measures.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.285
Teacher spread0.233 · 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 teacher head, not a consensus.

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
Published2024
Admission routes2
Has abstractyes

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