Fidelity of virtual self-management programs in pediatric autoimmune diseases: A scoping review protocol
Bibliographic record
Abstract
Pediatric autoimmune disorders represent chronic conditions in which the immune system erroneously targets healthy tissues, affecting children and adolescents. Virtual self-management programs have emerged as complementary approaches to traditional healthcare modalities, aimed at improving patient engagement and optimizing outcomes. However, the fidelity of these programs—defined as their adherence to intended design and delivery—remains underexplored, particularly in pediatric populations. This scoping review aims to provide an overview of the fidelity of virtual self-management programs tailored for children with autoimmune diseases. It will systematically document methodologies used to assess fidelity, evaluate its impact on program execution, and analyze its influence on patient outcomes. The review follows the Joanna Briggs Institute guidelines and employs the PRISMA-ScR framework. Comprehensive searches will be conducted through PubMed, CINAHL, Embase, PsycINFO, Web of Science, and Education Resources Information Center (ERIC). Eligible studies will focus on pediatric patients, with data extraction encompassing population characteristics, program features, fidelity metrics, and implementation determinants. The review will synthesize current evidence on fidelity in virtual self-management programs for pediatric autoimmune diseases, identify research gaps, and propose directions for future studies. These findings aim to inform program development, enhance implementation fidelity, and improve therapeutic outcomes in pediatric autoimmune care. Program Fidelity Assessment : This review aims to systematically document methodologies used to assess fidelity in virtual self-management programs, evaluating their impact on program execution and patient outcomes. Implementation Strategies : It will analyze existing literature on implementation strategies for virtual programs, identifying factors that influence their delivery and effectiveness. Future Directions : The review seeks to identify research gaps and propose directions for future studies, informing the development of more effective virtual self-management programs for children with autoimmune diseases.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".