DIFFERENT MUSCULOSKELETAL PAINS AND SOCIOCULTURAL FEATURES: THE CASE OF PRIVATE NOBEL PHYSICAL THERAPY AND REHABILITATION MEDICAL CENTER
Bibliographic record
Abstract
Aim: It was conducted to evaluate the effect of some sociodemographic and cultural characteristics on pain perception and pain intensity in different musculoskeletal pains and to determine some characteristics related to pain. Method: By recording the demographic information and sociocultural characteristics of all participants; Scandinavian Musculoskeletal Questionnaire and McGill Pain Scale Short Form were used to assess pain perception and pain intensity. Results: 544 patients, 372 women and 172 men, with subacute and chronic musculoskeletal pain were included in this study. The average age of the participants was 40.74±14.53 years. When the effect of sociocultural factors on pain intensity and pain perception (sensory and perceptual dimensions) is examined; it was determined that as the education level increased, the severity of pain (p = 0.002) and pain perception decreased (p = 0.0001), and the pain intensity of the participants living in the village was higher (p = 0.014). While the severity of pain and pain perception were higher in female individuals, it was determined that they also increased with age. When the relationship between pain intensity and pain perception of the participants is examined; positive high relationship (r = 0.630, p = 0.0001) was found between the intensity of pain and sensory pain perception, and a moderate relationship (r = 0.597, p = 0.0001) was found between perceptual dimension. A high positive correlation was found between sensory and perceptual pain dimensions (r = 0.658, p = 0.0001) Conclusion: Chronic pain experience and pain perception levels are affected by social and cultural characteristics. Sociocultural characteristics of individuals should also be taken into consideration in pain relief. Studies examining the effects of different sociocultural characteristics such as language, religious belief, family structure, pet feeding or interaction with animals on musculoskeletal pain are also needed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".