The relative contribution of pain and psychological factors to opioid misuse: A 6-month observational study.
Bibliographic record
Abstract
There is a pressing need to better understand the factors contributing to prescription opioid misuse among patients with chronic pain. Cross-sectional studies have been conducted in this area, but longitudinal studies examining the determinants of prescription opioid misuse repeatedly over the course of opioid therapy have yet to be conducted. The main objective of this study was to examine the relative contribution of pain and psychological factors to the occurrence of opioid misuse among patients with chronic pain prescribed opioids. Of particular interest was to examine whether pain intensity and psychological factors were more strongly associated with certain types of opioid misuse behaviors. Patients with chronic pain (n = 194) prescribed long-term opioid therapy enrolled in this longitudinal observational cohort study. Patients completed baseline measures and were then followed for 6 months. Opioid misuse was assessed once a month using self-report measures, and urine toxicology screens complemented patients' reports of opioid misuse. Heightened pain intensity levels were associated with a greater likelihood of opioid misuse (p = .014). However, pain intensity was no longer significantly associated with opioid misuse when controlling for psychological factors (i.e., negative affect, catastrophizing). Subsequent analyses revealed that higher levels of catastrophizing were associated with a greater likelihood of running out of opioid medication early, even after controlling for patients' levels of pain intensity and negative affect (p = .016). Our findings provide new insights into the determinants of prescription opioid misuse and have implications for the nature of interventions that may be used to reduce specific types of opioid misuse behaviors. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".