Individual differences in response to phantom limb movement therapy
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".