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Aplicación del cuestionario mcgill en mujeres con fibromialgia y con lombalgia: un estudio comparativo

2009· article· en· W1538133193 on OpenAlexaboutno aff
Ana Cláudia de Souza Leite, Weidinara De Oliveira Rodrigues, Lorita Marlena Freitag Pagliuca

Bibliographic record

VenueRevista de Enfermagem UFPE on line · 2009
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsFibromyalgiaMcGill Pain QuestionnaireMedicinePhysical therapyOutpatient clinicQuantitative sensory testingPopulationHumanitiesPsychologySensory systemInternal medicineArt

Abstract

fetched live from OpenAlex

Objective: to apply the McGill Questionnaire, translated and adapted to Brazil, and to identify the degree of internal association between this clinical group of women with fibromyalgia and another group of women with low back pain. Methods: this experimental research includes a case-control study. The population consisted of 83 patients diagnosed with fibromyalgia and low back pain who attended the Orthopedics and Trauma Outpatient Clinic at a Teaching Hospital in Fortaleza-CE, Brazil, from December 2005 to June 2006. The following exclusion criteria were adopted: patients with sensory and cognitive deficits, illiterate, younger than 21 and older than 60 years. A sample of 50 patients was obtained. The control and experimental groups were paired and the MPQ was applied to both. This study has been approved by the Research Ethics Committee of the Federal University of Ceará (04545014-5). Results: were analyzed comparatively through non-parametrical statistics (Kruskal-Wallis). This test found significant means and standard deviations for the sensory and affective categories, with significant p-values for the descriptor “tiring”. Conclusion: the MPQ showed its appropriateness for pain assessment and analysis in fibromyalgia patients. Descriptors: pain; pain measurement; fibromyalgia.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.027
GPT teacher head0.331
Teacher spread0.303 · 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.

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

Citations2
Published2009
Admission routes1
Has abstractyes

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