Pain in Brazilian people experiencing homelessness
Bibliographic record
Abstract
BACKGROUND: Previous studies conducted in developed countries have shown that homeless people experience a high rate of pain. In this population, pain is not only underdiagnosed but is also undertreated. In Brazil, the pain of people experiencing homelessness is unknown and this is the first study on this subject in the country. OBJECTIVE: To assess and characterize the prevalence of pain in homeless people living on the streets in the center of São Paulo, Brazil, and to understand its implications to general activities according to the Brief Pain Inventory (BPI) questionnaire. METHOD: This is a descriptive-exploratory cross-sectional study with a quantitative approach conducted with 69 homeless people from the central region of São Paulo, Brazil. The data were captured as protected health information and analyzed with a sociodemographic form, the BPI questionnaire, the McGill Pain Questionnaire (MPQ), and the Wong-Baker Face Scale. RESULTS: The sample consisted mainly of men who spend the night on the streets, of black and miscegenated Brazilian people, with a mean age of 51 years. This population lived an average of 12 years on the streets, presented low levels of education, and used psychoactive substances. We observed a prevalence of severe musculoskeletal pain in the spine, with intermittent activity and duration of several days. The most common self-reported worsening factor was body movement and the most common factor of improvement was use of medication, but only 15% reported pain relief. Pain greatly interfered with all BPI's Activities of Daily Living, in particular with sleep (87.2%). The MPQ was difficult for the subjects to understand. There was no evidence of an association between pain and sex. Our results suggest that the longer the time living on the street, the less pain symptoms are acknowledged by the subjects, due to the accommodation phenomenon.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".