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Record W4226263892 · doi:10.7717/peerj.13134

Multilingual validation of the short form of the Unesp-Botucatu Feline Pain Scale (UFEPS-SF)

2022· article· en· W4226263892 on OpenAlexaff
Stélio Pacca Loureiro Luna, Pedro Henrique Esteves Trindade, Beatriz P. Monteiro, Nadia Crosignani, Giorgia Della Rocca, H Ruel, Kazuto YAMASHITA, Peter Kronen, Chia T. Tseng, L.R. Teixeira, Paulo V. Steagall

Bibliographic record

VenuePeerJ · 2022
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsUniversité de Montréal
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsConstruct validityConcurrent validityPain scaleMedicineReceiver operating characteristicPerioperativeReliability (semiconductor)Criterion validityScale (ratio)Physical therapyPsychometricsInternal consistencySurgeryClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Pain is the leading cause of animal suffering, hence the importance of validated tools to ensure its appropriate evaluation and treatment. We aimed to test the psychometric properties of the short form of the Unesp-Botucatu Feline Pain Scale (UFEPS-SF) in eight languages. Methods: The original scale was condensed from ten to four items. The content validation was performed by five specialists in veterinary anesthesia and analgesia. The English version of the scale was translated and back-translated into Chinese, French, German, Italian, Japanese, Portuguese and Spanish by fluent English and native speaker translators. Videos of the perioperative period of 30 cats submitted to ovariohysterectomy (preoperative, after surgery, after rescue analgesia and 24 h after surgery) were randomly evaluated twice (one-month interval) by one evaluator for each language unaware of the pain condition. After watching each video, the evaluators scored the unidimensional, UFEPS-SF and Glasgow composite multidimensional feline pain scales. Statistical analyses were carried out using R software for intra and interobserver reliability, principal component analysis, criteria concurrent and predictive validities, construct validity, item-total correlation, internal consistency, specificity, sensitivity, the definition of the intervention score for rescue analgesia and diagnostic uncertainty zone, according to the receiver operating characteristic (ROC) curve. Results: UFEPS-SF intra- and inter-observer reliability were ≥0.92 and 0.84, respectively, for all observers. According to the principal component analysis, UFEPS-SF is a unidimensional scale. Concurrent criterion validity was confirmed by the high correlation between UFEPS-SF and all other scales (≥0.9). The total score and all items of UFEPS-SF increased after surgery (pain), decreased to baseline after analgesia and were intermediate at 24 h after surgery (moderate pain), confirming responsiveness and construct validity. Item total correlation of each item (0.68-0.83) confirmed that the items contributed homogeneously to the total score. Internal consistency was excellent (≥0.9) for all items. Both specificity (baseline) and sensitivity (after surgery) based on the Youden index was 99% (97-100%). The suggestive cut-off score for the administration of analgesia according to the ROC curve was ≥4 out of 12. The diagnostic uncertainty zone ranged from 3 to 4. The area under the curve of 0.99 indicated excellent discriminatory capacity of UFEPS-SF. Conclusions: The UFEPS-SF and its items, assessed by experienced evaluators, demonstrated very good repeatability and reproducibility, content, criterion and construct validities, item-total correlation, internal consistency, excellent sensitivity and specificity and a cut-off point indicating the need for rescue analgesia in Chinese, French, English, German, Italian, Japanese, Portuguese and Spanish.

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 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 score0.381
Threshold uncertainty score0.547

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.061
GPT teacher head0.344
Teacher spread0.282 · 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

Citations29
Published2022
Admission routes1
Has abstractyes

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