Evaluation of an Interdisciplinary Program for Chronic Pain After Spinal Cord Injury
Bibliographic record
Abstract
OBJECTIVE: To assess efficacy of an interdisciplinary pain program adapted for persons with spinal cord injury (SCI) and chronic pain. DESIGN: Prospective cohort. SETTING: University-affiliated rehabilitation hospital. PARTICIPANTS: Twenty-two persons with traumatic or nontraumatic SCI and chronic pain of at least 6 months' duration. METHODS: Subjects participated in an interdisciplinary pain program consisting of biweekly group sessions for 10 consecutive weeks. Sessions incorporated patient education on chronic pain and associated pain mechanisms, cognitive behavioral therapy, self-management strategies (eg, energy conservation, ergonomics, goal setting, stress management, anger management, and coping skills), group discussions and activities, and either exercise or guided relaxation at the end of each session. MAIN OUTCOME MEASURES: Multidimensional Pain Inventory SCI, Coping Inventory of Stressful Situations, Pain Stages of Change Questionnaire, and Life Satisfaction Questionnaire. RESULTS: After participation in an interdisciplinary pain program, persons with SCI and chronic neuropathic pain demonstrated increased involvement in learning and maintenance of coping strategies for chronic pain. Participation also led to less pain interference in daily life and a greater sense of control over one's life. CONCLUSIONS: Participation in an interdisciplinary pain program does not reduce pain severity, but it can help persons with SCI and chronic neuropathic pain cope with pain, lessen interference of pain, and improve their sense of control.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".