CHILD-BRIGHT READYorNot Brain-Based Disabilities Trial: protocol of a randomised controlled trial (RCT) investigating the effectiveness of a patient-facing e-health intervention designed to enhance healthcare transition readiness in youth
Bibliographic record
Abstract
INTRODUCTION: BBD App, a patient-facing e-health intervention. The primary aim of this randomised controlled trial (RCT) was to determine whether the App will result in greater transition readiness compared with usual care for youth with BBD. Secondary aims included exploring the contextual experiences of youth using the App, as well as the interactive processes of youth, their parents/caregivers and healthcare providers around use of the intervention. METHODS AND ANALYSIS: We aimed to randomise 264 youth with BBD between 15 and 17 years of age, to receive existing services/usual care (control group) or to receive usual care along with the App (intervention group). Our recruitment strategy includes remote and virtual options in response to the current requirements for physical distancing due to the COVID-19 pandemic. We will use an embedded experimental model design which involves embedding a qualitative study within a RCT. The Transition Readiness Assessment Questionnaire will be administered as the primary outcome measure. Analysis of covariance will be used to compare change in the two groups on the primary outcome measure; analysis will be intention-to-treat. Interviews will be conducted with subsets of youth in the intervention group, as well as parents/caregivers and healthcare providers. ETHICS AND DISSEMINATION: The study has been approved by the research ethics board of each participating site in four different regions in Canada. We will leverage our patient and family partnerships to find novel dissemination strategies. Study findings will be shared with the academic and stakeholder community, including dissemination of teaching and training tools through patient associations, and patient and family advocacy groups. TRIAL REGISTRATION NUMBER: NCT03852550.
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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 | 0.033 | 0.036 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.053 | 0.009 |
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".