Evaluation of client compliance with short-term administration of antimicrobials to dogs
Bibliographic record
Abstract
OBJECTIVE: To describe the degree of and variability in the level of client compliance and identify determinants of client compliance with short-term administration of antimicrobial medications to dogs. DESIGN: Prospective study. SAMPLE POPULATION: 90 owners of dogs prescribed antimicrobials. PROCEDURE: Eligible clients were invited to participate when antimicrobial medications were dispensed. Data were collected during a follow-up appointment by use of a client questionnaire, residual pill count, and return of an electronic medication monitoring device. Attending veterinarians also completed a questionnaire that asked them to predict client compliance. Methods of assessing compliance were compared with nonparametric tests. Generalized estimating equations were used to investigate potential determinants of compliance. RESULTS: Median compliance rates of 97% of prescribed container openings, 91% of days when the correct number of doses were given, and 64% of doses given on time as assessed by the electronic medication monitoring devices were significantly lower than the median compliance rates of 100% for client self-report of missing doses and pill count. Veterinarians were unable to predict client compliance. The dosage regimen significantly determined compliance. Clients giving antimicrobials once or twice daily were 9 times more likely to be 100% compliant, compared with 3 times daily dosing. CONCLUSIONS AND CLINICAL RELEVANCE: The combination of reported missed doses and pill counts was a significant predictor of compliance as measured by electronic monitoring. Electronic monitoring caps provided useful information only when they were used appropriately. Asking clients about missed doses and performing pill counts are the most practical assessments of compliance in practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".