Development, Preliminary Validation, and Refinement of the Composite Oral and Maxillofacial Pain Scale-Canine/Feline (COPS-C/F)
Bibliographic record
Abstract
Objectives: Oral pain is underrecognized and undertreated in small animal practice. This study aimed to develop and perform a preliminary validation of an instrument to evaluate oral and maxil-lofacial pain in dogs and cats. Methods: Indicators potentially associated with oral pain in dogs and cats were identified and selected. The Composite Oral Pain Scale – Canine/Feline (COPS-C/F) in the Italian language was developed using a two-part questionnaire (owner and veterinary specific questionnaires). The instrument was used to score the intensity of oral and maxillofacial pain in patients with oral disease. Content validity was performed and the COPS-C/F was applied to 20 dogs and 16 cats with oral disease at baseline and 15 days after dental treatment for construct validity. Criterion validity was assessed by comparing the COPS-C/F with a visual analog scale (VAS), a numeric rating scale (NRS) and a simple descriptive scale (SDS). Construct validity/responsiveness and criterion validity were assessed with Wilcoxon and Spearman Pearson tests, respectively (p ≤ 0.05). The Cronbach's alpha coefficient was used to calculate internal consistency. Thereafter, the instrument was refined and translated to English and back-translated for semantic equivalence. Results: Construct validity was confirmed with a significant reduction of pain scores after treatment (p < 0.05) for most items. Criterion validity was confirmed by a significant correlation among the COPS-C/F total pain scores and those from VAS, NRS and SDS (p < 0.05). Cronbach’s alpha coefficient was 0.876 and 0.860 for the owner and the veterinary specific questionnaires, respectively indicating good internal consistency. The items that did not present significant differences between time-points and the VAS, NRS and SDS were removed prior to translation to English (COPS-C/F ENG). Conclusions and Clinical Relevance: The study described the development and preliminary validation of the COPS-C/F as an instrument for pain assessment in dogs and cats. Refinement and back-translation of COPS-C/F with semantic equivalency resulted in the COPS-C/F ENG consisting of 6 and 4 items for the owner and veterinary specific questionnaires, respectively. The English version requires further validation and testing using a larger number of patients in the clinical setting.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".