Effectiveness of Medical Massage in Reducing Neck Pain Among Multiple Occupational Groups: A Longitudinal Study
Bibliographic record
Abstract
Background: Neck pain is a common complaint affecting people across various professions, especially those involving prolonged sedentary activities. Purpose: This study aimed to evaluate the efficacy of medical massage in reducing neck pain among diverse occupational groups in North Macedonia over a 3-year period (2019-2022). Methods: A total of 127 participants from various professions such as information technology professionals, bank accountants, textile workers, business sector employees, and secretaries were subjected to one or two massages per month. Pain intensity was measured using a numerical rating scale at the start and throughout the study. The statistical methods in this research study included descriptive statistics for summarizing demographic data, comparative analyses to assess the effectiveness of massage therapy on pain reduction, and inferential statistics to determine significance levels and correlations within the data. Results: At the beginning of the study, participants reported an average pain intensity level of 7 on a numerical rating scale from 1 to 10. Over the study period, consistent massage therapy led to a significant reduction in neck pain, with participants reporting an average pain level of 2 in the final months. Crucially, the research revealed that discontinuation of massage sessions, as observed in a subset of respondents who abstained for approximately 4 months, resulted in an escalation of pain intensity. This finding draws attention to the importance of regular massage therapy in sustaining pain relief benefits. Conclusion: The study's outcomes focus on the effectiveness of medical massage in managing neck pain across various occupational backgrounds. This research provides valuable perception in the potential long-term benefits of massage therapy, accenting the need for continued treatment to maintain pain relief among people exposed to neck and back pain. These findings offer essential guidance to healthcare professionals and individuals seeking non-pharmacological interventions for chronic neck pain management.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".