Pain Management: Effects on Pain Perception in Older Adults and College Students
Bibliographic record
Abstract
This study examined the relationship between pain perception and meditation among older adults and college students diagnosed with a chronic pain condition. Chronic pain was defined as having pain most days of the week for at least three months. 13 participants were older adults recruited from a local senior center and 18 participants were college students recruited from a local university. Participants attended one intervention that measured the immediate effects of a meditation or education training on perceptual aspects of pain. Pain intensity, sensation and emotional response were measured with the McGill pain questionnaire short-form. Catastrophic thoughts about pain were measured by the pain catastrophizing scale. The depression, anxiety and stress scale was also utilized in this study to measure overall distress. Results showed a marginally significant trend towards meditation decreasing the intensity of pain in older adults. Results also revealed greater reductions in all measures of pain in both older adults and college students who underwent meditation training versus an education group, yet these results did not reach statistical significance. College students showed somewhat greater improvement in comparison to older adults in both control and experimental groups, though not significantly so. This study was limited in its effectiveness because of a small sample size and an unclear sample of individuals with chronic pain conditions. Although the study only yielded significant decreases distress levels in college students, it highlights the overall potential benefits of a meditation intervention as a plausible and effective treatment for chronic pain as well as co-morbid conditions associated with pain.
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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 | 0.000 | 0.001 |
| 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".