The nature and prevalence of chronic pain in homeless persons: an observational study
Bibliographic record
Abstract
BACKGROUND: Homeless people are known to suffer disproportionately with health problems that reduce physical functioning and quality of life, and shorten life expectancy. They suffer from a wide range of diseases that are known to be painful, but little information is available about the nature and prevalence of chronic pain in this vulnerable group. This study aimed to estimate the prevalence of chronic pain among homeless people, and to examine its location, effect on activities of daily living, and relationship with alcohol and drugs. METHODS: We conducted face-to-face interviews with users of homeless shelters in four major cities in the United Kingdom, in the winters of 2009-11. Participants completed the Brief Pain Inventory, Short Form McGill Pain questionnaire, Leeds Assessment of Neuropathic Symptoms and Signs, and detailed their intake of prescribed and unprescribed medications and alcohol. We also recorded each participant's reasons for homelessness, and whether they slept rough or in shelters. FINDINGS: Of 168 shelter users approached, 150 (89.3%) participated: 93 participants (63%) reported experiencing pain lasting longer than three months; the mean duration of pain experienced was 82.2 months. The lower limbs were most frequently affected. Opioids appeared to afford a degree of analgesia for some, but whilst many reported symptoms suggestive of neuropathic pain, very few were taking anti-neuropathic drugs. INTERPRETATION: The prevalence of chronic pain in the homeless appears to be substantially higher than the general population, is poorly controlled, and adversely affects general activity, walking and sleeping. It is hard to discern whether chronic pain is a cause or effect of homelessness, or both. Pain is a symptom, but in this challenging group it might not always be possible to treat the underlying cause. Exploring the diagnosis and treatment of neuropathic pain may offer a means of improving the quality of these vulnerable people's lives.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 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".