Pain coping skills training for African Americans with osteoarthritis (STAART): study protocol of a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: African Americans bear a disproportionate burden of osteoarthritis (OA), with higher prevalence rates, more severe pain, and more functional limitations. One key barrier to addressing these disparities has been limited engagement of African Americans in the development and evaluation of behavioral interventions for management of OA. Pain Coping Skills Training (CST) is a cognitive-behavioral intervention with shown efficacy to improve OA-related pain and other outcomes. Emerging data indicate pain CST may be a promising intervention for reducing racial disparities in OA symptom severity. However, there are important gaps in this research, including incorporation of stakeholder perspectives (e.g. cultural appropriateness, strategies for implementation into clinical practice) and testing pain CST specifically among African Americans with OA. This study will evaluate the effectiveness of a culturally enhanced pain CST program among African Americans with OA. METHODS/DESIGN: This is a randomized controlled trial among 248 participants with symptomatic hip or knee OA, with equal allocation to a pain CST group and a wait list (WL) control group. The pain CST program incorporated feedback from patients and other stakeholders and involves 11 weekly telephone-based sessions. Outcomes are assessed at baseline, 12 weeks (primary time point), and 36 weeks (to assess maintenance of treatment effects). The primary outcome is the Western Ontario and McMaster Universities Osteoarthritis Index, and secondary outcomes include self-efficacy, pain coping, pain interference, quality of life, depressive symptoms, and global assessment of change. Linear mixed models will be used to compare the pain CST group to the WL control group and explore whether participant characteristics are associated with differential improvement in the pain CST program. This research is in compliance with the Helsinki Declaration and was approved by the Institutional Review Boards of the University of North Carolina at Chapel Hill, Durham Veterans Affairs Medical Center, East Carolina University, and Duke University Health System. DISCUSSION: This culturally enhanced pain CST program could have a substantial impact on outcomes for African Americans with OA and may be a key strategy in the reduction of racial health disparities. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02560922 , registered 9/22/2015.
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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 | 0.040 | 0.037 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.075 | 0.011 |
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".