Randomized feasibility trial of the Scleroderma Patient-centered Intervention Network Self-Management (SPIN-SELF) Program
Bibliographic record
Abstract
BACKGROUND: The Scleroderma Patient-centered Intervention Network (SPIN) developed an online self-management program (SPIN-SELF) designed to improve disease-management self-efficacy in people with systemic sclerosis (SSc, or scleroderma). The aim of this study was to evaluate feasibility aspects for conducting a full-scale randomized controlled trial (RCT) of the SPIN-SELF Program. METHODS: This feasibility trial was embedded in the SPIN Cohort and utilized the cohort multiple RCT design. In this design, at the time of cohort enrollment, cohort participants consent to be assessed for trial eligibility and randomized prior to being informed about the trial. Participants in the intervention arm are informed and provide consent, but not the control group. Forty English-speaking SPIN Cohort participants from Canada, the USA, or the UK with low disease-management self-efficacy (Self-Efficacy for Managing Chronic Disease Scale [SEMCD] score ≤ 7) who were interested in using an online self-management program were randomized (3:2 ratio) to be offered the SPIN-SELF Program or usual care for 3 months. Program usage was examined via automated usage logs. User satisfaction was assessed with semi-structured interviews. Trial personnel time requirements and implementation challenges were logged. RESULTS: Of 40 SPIN Cohort participants randomized, 26 were allocated to SPIN-SELF and 14 to usual care. Automated eligibility and randomization procedures via the SPIN Cohort platform functioned properly, except that two participants with SEMCD scores > 7 (scores of 7.2 and 7.3, respectively) were included, which was caused by a system programming error that rounded SEMCD scores. Of 26 SPIN Cohort participants offered the SPIN-SELF Program, only 9 (35%) consented to use the program. Usage logs showed that use of the SPIN-SELF Program was low: 2 of 9 users (22%) logged into the program only once (median = 3), and 4 of 9 (44%) accessed none or only 1 of the 9 program's modules (median = 2). CONCLUSIONS: The results of this study will lead to substantial changes for the planned full-scale RCT of the SPIN-SELF Program that we will incorporate into a planned additional feasibility trial with progression to a full-scale trial. These changes include transitioning to a conventional RCT design with pre-randomization consent and supplementing the online self-help with peer-facilitated videoconference-based groups to enhance engagement. TRIAL REGISTRATION: clinicaltrials.gov , NCT03914781 . Registered 16 April 2019.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".