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Record W7036010705

The Adolescent Pediatric Pain Tool: psychometric properties of the Portuguese version

2013· other· en· W7036010705 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2013
Typeother
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsRecallMeasure (data warehouse)PortuguesePain assessmentPediatric cancerMcGill Pain QuestionnaireQuality (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

Introduction and aims\nLong lasting illnesses such as cancer require a multidimensional pain assessment that can provide a more complete understanding of the pain experienced by subjects.\nThe Adolescent Pediatric Pain Tool (APPT) is a measure of the location, intensity and quality of pain, validated in English and Spanish for children and adolescents 8 to 17 years. The measure of location consists of a body outline diagram; the measure of intensity is a 10 centimeter word graphic rating scale; the measure of pain quality is a list of 67 descriptors categorized in sensory, affective, evaluative and temporal dimensions.\nThis study examined the properties of the Portuguese version of the APPT, which was previously submitted to semantic and cultural validation.\n\nMethods\nEighty-eight children and adolescents (8-17 years old) with cancer, either hospitalized or in the out-patient clinic, were asked to report their pain using the APPT. If they were not in pain, they were asked to recall their last pain episode. A principal component analysis (PCA) was conducted. We analysed if type of tumour and time elapsed since the diagnosis were related to the total number of pain descriptors used and to the number of descriptors in each dimension. We also examined the correlation between pain intensity and the number of descriptors and number of locations marked. \n\nResults\nAll descriptors were used by at least one child. Only one child suggested a new word. PCA with 4 factors explained 29,48% of the variance. Two factors contain mainly sensory descriptors; one factor includes a mix of sensory and affective descriptors and one factor a mix of sensory and temporal descriptors.\nType of tumour and time elapsed since diagnosis were not related to the total number of descriptors used, to the number of descriptors used in each dimension. The correlation between pain intensity and the numbers of descriptors used was significant (p< 0,001, r=0,38).\n\nDiscussion\nIn the Portuguese version, the list of words seems to represent a sensory, an affective and a temporal dimension. The results are not very different from those of the original scale, although the restricted range of variance and small sample size should be considered. Concurrent validity may be supported by the correlation between pain intensity and the numbers of descriptors used.\n\nConclusion \nThe Portuguese version of the APPT is a promising tool to assess pain in a multidimensional way, requiring further research.

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)0.005
metaresearch head score (Gemma)0.011
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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.350
Teacher spread0.291 · 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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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