Faculty Opinions recommendation of Pain Support for Adults with a Diabetes-Related Lower Limb Amputation: an Empirical Phenomenology Study.
Bibliographic record
Abstract
BACKGROUND: Chronic pain after lower extremity amputation surgery has been reported in up to 80% of patients. Amputations are among the most debilitating chronic complication of diabetes with a variety of consequences including depression, inability to perform daily activities, and change in quality of life.AIMS: This study sought to understand the lived experience of chronic pain support among those who have undergone a diabetes-related lower limb amputation.METHOD: Researchers used a qualitative empirical phenomenology design. Private, semistructured interviews were conducted on a purposive sample (N = 11). Codes were identified for each participant separately and then across participants for common themes.RESULTS: Three major themes emerged from the research: (1) Phantom pain is nontreatable pain; (2) support systems were nonempathetic; and (3) participants experienced identification of a new normal. Participants did not understand that neuropathic (phantom) pain was part of the total pain experience. Further, they felt that there was no help from family or providers for alleviation of this pain.CONCLUSIONS: Phantom pain was identified as something the participants had to tolerate when it occurred. They did not feel that family or providers understood their pain. Further, they wanted a means of controlling their pain using nonpharmacologic therapies.Copyright © 2018 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved. PMID: 30528363
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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.
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".