Factors Associated with Medication Noncompliance in Dogs in New Zealand
Bibliographic record
Abstract
Client compliance with prescribed medication instructions to treat their pets is a concern. This study describes factors associated with the noncompliance of dog owners with veterinary recommendations for medication, as well as client-reported barriers and aids to administering medications. A cross-sectional survey of dog owners’ compliance with veterinary medication recommendations was performed from 9 January 2019 to 18 July 2020. A convenience sample of owners who prescribed medication for their dogs during or following elective veterinary examination was surveyed regarding medication administration experience and compliance. Owners were followed up to determine if the course of medication had been completed. Compliance data were analyzed descriptively. Logistic regression was performed with compliance as the outcome. Medication noncompliance was recorded for 47% (71/151) of owners. Increasing dog age was associated with better owner compliance (p < 0.05). Pet owners who used “nothing” as an aid to medicating were less likely to be noncompliant (p < 0.05). Forty-seven percent (71/151) of owners reported that “nobody” showed them how to administer the medication. One-third of dog owners (47/151) reported challenges in medicating their pets. The most common reason cited by clients reporting challenges was a resistant pet. Demonstration of medication administration techniques and discussion about available aids to medicating a pet may improve client compliance.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".