Clinically Important Change in Insomnia Severity After Chronic Pain Rehabilitation
Bibliographic record
Abstract
OBJECTIVES: Insomnia is a common problem for people with chronic pain. It is unclear, however, whether interdisciplinary treatment centered on pain management, rather than sleep, confers a benefit in reducing insomnia symptoms. In this study, we examined clinically important change in insomnia severity following participation in an interdisciplinary chronic pain rehabilitation program. METHODS: A total of 140 patients (43 men and 97 women) completed a 4-week outpatient day program for interdisciplinary rehabilitation that incorporated psychoeducation about pain, physical fitness, and group psychotherapy. The Insomnia Severity Index (ISI) was included as an outcome, along with measures of pain, mood, and function. RESULTS: On the ISI before treatment, 20 patients (14.3%) reported no insomnia, 36 (25.7%) had a mild or subthreshold problem, and 84 (60%) had moderate (31.4%) or severe (28.6%) clinical insomnia. After treatment, ISI scores showed a statistically significant improvement overall (P<0.001). Six indices of individual change were examined among those with moderate-severe insomnia at baseline. Depending on the index used, rates of clinically important improvement ranged from 2.4% to 47.6%; however, only 2 patients with insomnia met criteria for full remission. Among patients with no or subthreshold symptoms at baseline, from 0% to 14.3% were worse after treatment, depending on the criterion. DISCUSSION: Insomnia improves overall following interdisciplinary rehabilitation for chronic pain, but most patients with clinical insomnia continue to have a significant sleep problem after treatment, and some patients may get worse. Interventions to alleviate persistent insomnia comorbid with chronic pain are likely to require a more intensive focus on sleep itself.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".