Effectiveness of massage therapy in reducing back pain in older adults
Bibliographic record
Abstract
Background: Lower back pain is one of the most common complaints in the elderly. Pain symptoms can be chronic and aggravated by comorbidities. Back pain leads to reduced function, difficulty performing activities of daily living, and prevents physical activity. Massage is one of the more commonly used forms of physiotherapy for these complaints. Aim of the study: The purpose of this study was to assess the effectiveness of therapeutic massage for spinal pain in older adults. Material and methods: Twenty-three participants, including 18 females and 5 males aged 61–85 years old, participated in the study. All patients had degenerative lesions of the spine that were diagnosed by their primary care physician. Patients received classical therapeutic back massages for a period of 3 weeks at a frequency of 2 times a week. Each treatment session was 40-minute-long. Analysis of pain was performed before and immediately after therapy to assess changes in pain. The McGill (short form) and the WHOQL-BREF questionnaires were used to assess the level and quality of life of the study participants. Pain intensity was assessed using the visual analog scale (VAS). Results: There was a reduction in pain intensity (VAS) and pain perception after massage therapy, with changes in the sensory and emotional components of the pain score. The changes were statistically significant. Quality of life measured by the WHOQOL-BREF questionnaire was at a good level. Elderly participants rated social relationships the highest and physical components the lowest. Conclusions: Massage therapy resulted in a reduction of spinal pain in older adults. Massage is an effective form of therapy for reducing back pain in older adults.
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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".