Suicidal ideation, plans, and attempts in chronic pain patients: factors associated with increased risk
Bibliographic record
Abstract
This study describes suicidal behavior in a cross-sectional sample of chronic pain patients and evaluates factors associated with increased risk for suicidal ideation. One hundred-fifty-three adults with nonmalignant pain (42% back pain) who were consecutively referred to a tertiary care pain center completed a Structured Clinical Interview for Suicide History, the McGill Pain Questionnaire, and the Beck Depression Inventory. Nineteen-percent reported current passive suicidal ideation (PSI), 13% had active thoughts of committing suicide (ASI), 5% had a current suicide plan, and 5% reported a previous suicide attempt. Drug overdose was the most commonly reported plan and method of attempt (75%). Thirteen-percent reported a family history of suicide attempt/completion. Pain-specific and traditional suicide risk factors were evaluated as predictors of current PSI and ASI. Logistic regression analyses revealed that a family history of suicide attempts/completions was associated with a 7.5 fold increase in risk of PSI (P=0.001) and a 6.6 fold increase in ASI (P=0.003), after adjusting for significant covariates. Having abdominal pain was associated with an adjusted 5.5 fold increase in PSI (P=0.05) and a 4.2 fold increase in ASI (P=0.10). Neuropathic pain significantly reduced risk for both PSI (P=0.002) and ASI (P=0.01). Demographics, pain severity, and depression severity were not associated with suicidal ideation in multivariate analyses. These findings highlight the need for routine evaluation and monitoring of suicidal behavior in chronic pain, especially for patients with family histories of suicide, those taking potentially lethal medications, and patients with abdominal 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 | 0.004 |
| 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 | 0.000 |
| 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".