Prevalence of pain in the Spanish population telephone survey in 5000 homes
Bibliographic record
Abstract
Pain has become the most common accompanying symptom in patients seeking medical advice, and it is one of the main issues in public health. In Spain, there are no reliable data about the impact of pain in general population. The aim of the study was to estimate the prevalence of acute and chronic pain in the Spanish general population. An epidemiological observational population-based cross-sectional study was carried out by means of a telephone survey. Multistep stratified quota-adjusted sampling was performed with people aged 18-95 years. A computer-assisted questionnaire was administered, covering physical pain symptoms, site, frequency, perceived cause, therapeutic measures and interference with daily life activities. There were 11,980 useful contacts, with 5000 effective interviews (42% of useful sample). Of the interviewees, 29.6% (95% confidence interval, 28.3-30.8%) reported having had pain the day before (women, 37.6%; men, 20.9%) and 43.2% the week before. Most common pain sites were lower extremities (22.7%) and back (cervical and lumbar levels) (21.5%), followed by head (20.5%). Frequency of pain increased with age, reaching 42.6% for people older than 65 years. Among people complaining of pain during the last day or week, duration of symptoms was higher than 3 months in 54% (chronic pain), representing 23.4% of the Spanish general population; most common causes of chronic pain were arthritis, rheumatism and migraine. Regarding treatment, 61.7% of people complaining of pain said they were taking drugs. Source of drug treatment advice was a physician or a nurse in 66.4% of cases and self-prescription in 29%. It is concluded that pain, particularly chronic pain, has a high prevalence in the Spanish general population and a significant impact on occupational and social relationships.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".