The Scleroderma Patient-Centered Intervention Network Self-Management Program: Protocol for a Randomized Feasibility Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND Systemic sclerosis (SSc), or scleroderma, is a rare disease that often results in significant disruptions to activities of daily living and can negatively affect physical and psychological well-being. Because there is no known cure, SSc treatment focuses on reducing symptoms and disability and improving health-related quality of life (HRQoL). Self-management programs are known to increase self-efficacy for disease management in many chronic diseases. The Scleroderma Patient-centered Intervention Network (SPIN) developed a Web-based self-management program (SPIN self-management; SPIN-SELF) to increase self-efficacy for disease management and to improve HRQoL for patients with SSc. OBJECTIVE The proposed study aims to assess the feasibility of conducting a full-scale randomized controlled trial (RCT) of the SPIN-SELF program by evaluating the trial implementation processes, required resources and management, scientific aspects, and participant acceptability and usage of the SPIN-SELF program. METHODS The SPIN-SELF feasibility trial will be conducted via the SPIN Cohort. The SPIN Cohort was developed as a framework for embedded pragmatic trials using the cohort multiple RCT design. In total, 40 English-speaking SPIN Cohort participants with low disease management self-efficacy (Self-Efficacy for Managing Chronic Disease Scale score ≤7), who have indicated interest in using a Web-based self-management program, will be randomized with a 3:2 ratio into the SPIN-SELF program or usual care for 3 months. Feasibility outcomes include trial implementation processes, required resources and management, scientific aspects, and patient acceptability and usage of the SPIN-SELF program. RESULTS Enrollment of the 40 participants occurred between July 5, 2019, and July 27, 2019. By November 25, 2019, data collection of trial outcomes was completed. Data analysis is underway, and results are expected to be published in 2020. CONCLUSIONS The SPIN-SELF program is a self-help tool that may improve disease-management self-efficacy and improve HRQoL in patients with SSc. The SPIN-SELF feasibility trial will ensure that trial methodology is robust, feasible, and consistent with trial participant expectations. The results will guide adjustments that need to be implemented before undertaking a full-scale RCT of the SPIN-SELF program. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/16799
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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 | 0.049 | 0.040 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.136 | 0.023 |
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".