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Record W2031516883 · doi:10.3109/09638288.2011.563816

Individual differences in response to phantom limb movement therapy

2011· article· en· W2031516883 on OpenAlexaff
Laura P. McAvinue, Ian H. Robertson

Bibliographic record

VenueDisability and Rehabilitation · 2011
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsTrinity College
FundersIrish Research Council for the Humanities and Social Sciences
KeywordsPhysical medicine and rehabilitationMovement (music)PsychologyPhantom limbPhysical therapyRehabilitationMedicineAmputationPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: Phantom limb pain (PLP) is a distressing condition experienced by many amputees. The purpose of this study was to investigate whether motor imagery could be used to treat PLP. METHOD: Four single case studies were conducted. The participants kept a pain diary in which they recorded the intensity of their PLP during a baseline period, general motor imagery training, phantom limb movement therapy and a follow-up period. Qualitative and quantitative (i.e. interrupted time series) analyses were employed to determine whether phantom limb movement therapy had a significant effect on PLP intensity. RESULTS: Phantom limb movement therapy significantly reduced intensity of PLP in one participant. One participant gained occasional relief by doing phantom limb movement therapy exercises but did not experience an overall reduction in PLP intensity. The third participant did not experience any relief and the fourth participant reported experiencing the re-emergence of an old pain. CONCLUSION: The results display individual differences in response to phantom limb movement therapy. Individual differences are discussed in the context of motor imagery ability and the phantom limb phenomenon as a multi-dimensional disorder.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.312

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 science0.0000.000
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 head0.046
GPT teacher head0.297
Teacher spread0.251 · 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 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

Citations21
Published2011
Admission routes1
Has abstractyes

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