A cross-sectional study of factors associated with the number of anatomical pain sites in an actual elderly general population: results from the PainS65+ cohort
Bibliographic record
Abstract
BACKGROUND: Several studies have illustrated that multisite pain is more frequent than single pain site, and it is associated with an array of negative consequences. However, there is limited knowledge available about the potential factors associated with multisite pain in the elderly general population. OBJECTIVE: This cross-sectional study examines whether the number of anatomical pain sites (APSs) is related to sociodemographic and health-related factors in older adults including oldest-old ages using a new method (APSs) to assess the location of pain on the body. MATERIALS AND METHODS: The sample came from the PainS65+ cohort, which included 6,611 older individuals (mean age = 76.0 years; standard deviation [SD] = 7.4) residing in southeastern Sweden. All the participants completed and returned a postal survey that measured sociodemographic data, total annual income, pain intensity and frequency, general well-being, and quality of life. The number of pain sites (NPS) was marked on a body manikin of 45 sections, and a total of 23 APSs were then calculated. Univariable and multivariable models of regression analysis were performed. RESULTS: Approximately 39% of the respondents had at least two painful sites. The results of the regression analysis showed an independent association between the APSs and the age group of 75-79 years, women, married, high pain intensity and frequency, and low well-being and quality of life, after adjustments for consumption of analgesics and comorbidities. The strongest association was observed for the higher frequency of pain. CONCLUSION: Our results suggest that APSs are highly prevalent with strong relationships with various sociodemographic and health-related factors and concur well with the notion that multisite pain is a potential indicator of increased pain severity and impaired quality of life in the elderly. Our comprehensive method of calculating the number of sites could be an essential part of the clinical presentation, assessment, and treatment of multisite 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".