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Telefisioterapia para o tratamento da dor no membro fantasma: um estudo quasi-experimental

2025· article· pt· W4411945565 on OpenAlexaboutno aff
Amanda de Aguiar Piazza, Soraia Cristina Tonon da Luz, Juliana Barcellos de Souza, Amábile Catarina Vieira, Amanda Borges Medeiros

Bibliographic record

VenueBrazilian Journal Of Pain · 2025
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsnot available
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Phantom limb pain (PLP) is a common complication of limb amputation, with a prevalence ranging from 41% to 46% of cases.Despite its uncertain pathophysiology, evidence suggests multifactorial mechanisms to explain the painful phenomenon, which directly affects the individual's quality of life.This study aimed to analyze the possible influence of a telephysiotherapy protocol for PLP on quality of life, pain intensity, and pain perception in individuals with limb amputation, in a quasi-experimental context.METHODS: A quasi-experimental study with a qualitative-quantitative approach, involving a sample of nine individuals.The instruments used were the McGill Pain Questionnaire, a verbal pain scale, the Short-Form Health Survey (SF-36), and an assessment form designed as an interview, all applied before and after the treatment protocol.The intervention consisted of an adaptation of the Graded Motor Imagery (GMI) protocol, conducted online via the Google Meet platform.Quantitative analysis was performed using the paired Wilcoxon test for nonparametric variables.The qualitative approach was analyzed using content analysis methodology.RESULTS: No significant differences were observed in quality-of-life parameters, pain intensity, or pain perception.However, qualitative reports demonstrated a perceived improvement among participants.CONCLUSION: The divergence between qualitative and quantitative results highlights the need for the development of specific questionnaires for PLP and its impact on the quality of life of individuals with limb amputation.

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)0.007
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.000
Research integrity0.0000.002
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 head0.027
GPT teacher head0.341
Teacher spread0.315 · 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 designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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