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Record W1989822739 · doi:10.1016/j.ejpain.2009.08.004

Reliability study in five languages of the translation of the pain behavioural scale Doloplus®

2009· article· en· W1989822739 on OpenAlexaff
Gisèle Pickering, Stephen J. Gibson, S. Serbouti, Patrizio Odetti, Ferraz Gonçalves, Giovanni Gambassi, Hirondina Guarda, Jan P.H. Hamers, David Lussier, Fiammetta Monacelli, Juan Manuel Pérez-Castejón Garrote, Sandra Zwakhalen, D. Barneto, Collectif Doloplus®, Bernard Wary

Bibliographic record

VenueEuropean Journal of Pain · 2009
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsMcGill University
Fundersnot available
KeywordsDementiaReliability (semiconductor)Scale (ratio)PsychologyTest (biology)PortuguesePain scalePain assessmentBrazilian PortugueseClinical psychologyPhysical therapyPhysical medicine and rehabilitationMedicineLinguisticsPain managementDiseaseCartography

Abstract

fetched live from OpenAlex

Non-verbal pain assessment scales are useful tools for pain evaluation in persons with communication disorders and moderate-severe dementia. The Doloplus was one of the first scales to be developed and validated as a pain assessment tool in older adults with dementia. This study aims at evaluating the translation of the Doloplus scale in five languages, as regards test-retest and inter-rater reliability. Results show that both tests are good or excellent for the English, Italian, Portuguese and Spanish versions and moderate for the Dutch version. These results bring a unique opportunity to include the translated Doloplus scale in daily assessment of elderly persons with communication disorders, and future studies should focus on enriching the validation of the scale in each language.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.043
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.273
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations46
Published2009
Admission routes1
Has abstractyes

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