Use of the nominal group technique and a cohort-based survey to identify important barriers and fascilitators to physical activity for people with scleroderma
Bibliographic record
Abstract
Background: Physical activity is often recommended to enhance health in people living with the rare chronic, autoimmune rheumatic disease of systemic sclerosis (SSc; scleroderma).However, approximately 50% of patients in a large international SSc cohort were inactive, and patients who were active rarely engaged in activities other than walking.The diverse medical presentation of SSc creates many possible physical and psychological barriers to physical activity.However, there are no physical activity promotion interventions designed to support individuals with SSc in overcoming their specific barriers, and no studies have researched barriers or facilitators to physical activity in SSc.Therefore, the objective of Phase 1 (manuscript 1) was to identify barriers and facilitators to physical activity for people with scleroderma.The objectives of Phase 2 (manuscript 2) were to determine the (1) prevalence and importance of different barriers experienced in SSc, and (2) likelihood that people with SSc would use different barrier-specific and general facilitators to be physically active. Methods: Phase 1: We conducted nominal group technique sessions with 3-8 SSc patients per session.Participants identified, shared, and discussed physical activity barriers and facilitators (barrier-specific and general).They rated importance of barriers and likelihood of using facilitators, and indicated whether they had tried facilitators.Similar barriers and facilitators across sessions were merged; edited by investigators, patient advisors, and clinicians; and categorized (qualitative content analysis) based on relevant literature.Phase 2: We invited 1,707 SSc patients enrolled in the Scleroderma Patient-centered Intervention Network Cohort to complete a survey of barriers and facilitators (from Phase 1) to (1) rate their experienced barriers for importance; (2) rate corresponding barrier-specific facilitators, and general facilitators for likelihood of use; and (3) indicate whether they tried facilitators.
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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 | 0.041 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".