Pain, opioid use, depressive symptoms, and mortality in adults living in precarious housing or homelessness: a longitudinal prospective study
Bibliographic record
Abstract
ABSTRACT: Pain and related consequences could contribute to comorbid illness and premature mortality in homeless and precariously housed persons. We analyzed longitudinal data from an ongoing naturalistic prospective study of a community-based sample (n = 370) to characterize risk factors and consequences of bodily pain. The aims were to describe bodily pain and associations with symptoms and psychosocial function, investigate factors that may increase or ameliorate pain, and examine the consequences of pain for symptoms, functioning, and all-cause mortality. Bodily pain severity and impact were rated with the 36-item Short Form Health Survey Bodily Pain Scale monthly over 5 years. Mixed-effects linear regression models estimated the effects of time-invariant and time-varying risk factors for pain, verified by reverse causality and multiple imputation analysis. Regression models estimated the associations between overall person-mean pain severity and subsequent functioning and suicidal ideation, and Cox proportional hazard models assessed association with all-cause mortality. Bodily pain of at least moderate severity persisted (>3 months) in 64% of participants, exceeding rates expected in the general population. Greater pain severity was associated with depressive symptom severity and month-to-month opioid use, overlaid on enduring risk associated with age, arthritis, and posttraumatic stress disorder. The frequency of prescribed and nonprescribed opioid use had nonlinear relationships with pain: intermittent use was associated with severe pain, without reverse association or change with the overdose epidemic. Greater longitudinal mean pain severity was associated with premature mortality, poorer functioning, and suicidal ideation. Considering the relationships between pain, intermittent opioid use, and depressive symptoms could improve health care for precariously housed patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".