Pain coping skills training for African Americans with osteoarthritis study: baseline participant characteristics and comparison to prior studies
Bibliographic record
Abstract
The Pain Coping Skills Training for African Americans with OsteoaRTthritis (STAART) trial is examining the effectiveness of a culturally enhanced pain coping skills training (CST) program for African Americans with osteoarthritis (OA). This disparities-focused trial aimed to reach a population with greater symptom severity and risk factors for poor pain-related outcomes than previous studies. This paper compares characteristics of STAART participants with prior studies of CST or cognitive behavioral therapy (CBT)-informed training in pain coping strategies for OA. A literature search identified 10 prior trials of pain CST or CBT-informed pain coping training among individuals with OA. We descriptively compared characteristics of STAART participants with other studies, in 3 domains of the National Institutes of Minority Health and Health Disparities’ Research Framework: Sociocultural Environment (e.g., age, education, marital status), Biological Vulnerability and Mechanisms (e.g, pain and function, body mass index), and Health Behaviors and Coping (e.g., pain catastrophizing). Means and standard deviations (SDs) or proportions were calculated for STAART participants and extracted from published manuscripts for comparator studies. The mean age of STAART participants, 59 years (SD = 10.3), was lower than 9 of 10 comparator studies; the proportion of individuals with some education beyond high school, 75%, was comparable to comparator studies (61–86%); and the proportion of individuals who are married or living with a partner, 42%, was lower than comparator studies (62–66%). Comparator studies had less than about 1/3 African American participants. Mean scores on the Western Ontario and McMaster Universities Osteoarthritis Index pain and function scales were higher (worse) for STAART participants than for other studies, and mean body mass index of STAART participants, 35.2 kg/m2 (SD = 8.2), was higher than all other studies (30–34 kg/m2). STAART participants’ mean score on the Pain Catastrophizing scale, 19.8 (SD = 12.3), was higher (worse) than other studies reporting this measure (7–17). Compared with prior studies with predominantly white samples, STAART participants have worse pain and function and more risk factors for negative pain-related outcomes across several domains. Given STAART participants’ high mean pain catastrophizing scores, this sample may particularly benefit from the CST intervention approach. NCT02560922
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".