Mental health, pain and likelihood of opioid misuse among adults with sickle cell disease
Bibliographic record
Abstract
Depressive symptoms are prevalent in individuals living with sickle cell disease (SCD) and may exacerbate pain. This study examines whether higher depressive symptoms are associated with pain outcomes, pain catastrophizing, interference and potential opioid misuse in a large cohort of adults with SCD. The study utilized baseline data from the 'CaRISMA' trial, which involved 357 SCD adults with chronic pain. Baseline assessments included pain intensity, daily mood, the Patient Health Questionnaire (PHQ), the Generalized Anxiety Disorders scale, PROMIS Pain Interference, Pain Catastrophizing Scale, the Adult Sickle Cell Quality of Life Measurement Information System and the Current Opioid Misuse Measure. Participants were categorized into 'high' or 'low' depression groups based on PHQ scores. Higher depressive symptoms were significantly associated with increased daily pain intensity, negative daily mood, higher pain interference and catastrophizing, poorer quality of life and a higher likelihood of opioid misuse (all p < 0.01). SCD patients with more severe depressive symptoms experienced poorer pain outcomes, lower quality of life and increased risk of opioid misuse. Longitudinal data from this trial will determine whether addressing depressive symptoms may potentially reduce pain frequency and severity in SCD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".