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Record W3128284945 · doi:10.3389/fvets.2021.629121

The Initial Months of COVID-19: Dog Owners' Veterinary-Related Concerns

2021· article· en· W3128284945 on OpenAlexaboutno aff
Lori R. Kogan, Phyllis Erdman, Cori Bussolari, Jennifer Currin‐McCulloch, Wendy Packman

Bibliographic record

VenueFrontiers in Veterinary Science · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)MedicineVeterinary medicineMedical emergencyBusinessNursingDisease

Abstract

fetched live from OpenAlex

Veterinarians, like many other professions, were significantly impacted by the onset of COVID-19 in the spring of 2020. Standard practices were disrupted, and veterinary hospitals had to quickly modify standard protocols to safely serve their clients and patients. The purpose of this study was to better understand dog owners' fears and concerns pertaining to veterinary care and obtainment of pet care products and food during the lock down phase of a pandemic to be better prepared to address these concerns now and in the future. To this end, an online, anonymous, cross-sectional survey was designed and distributed to adult dog owners via social media. The results, from a total of 4,105 participants (the majority from the United States and Canada), indicated substantial areas of concern. The number one concern of dog owners during this time was the availability of emergency veterinary care. Owners under 30 years of age, compared to older owners, were significantly more concerned about both availability and cost of veterinary care (emergency and non-emergency). The ability to care for one's dog if they were to become ill was a concern for many owners, yet only 60% had identified a caretaker for their dog if one was needed. These results suggest that the majority of dog owners remained true steadfast guardians of their dogs, continuing to make them a priority, even during pandemic times. Suggestions to help mitigate dog owners' concerns and improve communication between owners and veterinarian teams are offered.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.391
Teacher spread0.347 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations41
Published2021
Admission routes1
Has abstractyes

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