Study protocol for the Sino-Canadian Healthy Life Trajectories Initiative (SCHeLTI): a multicentre, cluster-randomised, parallel-group, superiority trial of a multifaceted community-family-mother-child intervention to prevent childhood overweight and obesity
Bibliographic record
Abstract
INTRODUCTION: Childhood overweight and obesity (OWO) is a primary global health challenge. Childhood OWO prevention is now a public health priority in China. The Sino-Canadian Healthy Life Trajectories Initiative (SCHeLTI), one of four trials being undertaken by the international HeLTI consortium, aims to evaluate the effectiveness of a multifaceted, community-family-mother-child intervention on childhood OWO and non-communicable diseases risk. METHODS AND ANALYSIS: This is a multicentre, cluster-randomised, controlled trial conducted in Shanghai, China. The unit of randomisation is the service area of Maternal Child Health Units (N=36). We will recruit 4500 women/partners/families in maternity and district level hospitals. Participants in the intervention group will receive a multifaceted, integrated package of health promotion interventions beginning in preconception or in the first trimester of pregnancy, continuing into infancy and early childhood. The intervention, which is centred on a modified motivational interviewing approach, will target early-life maternal and child risk factors for adiposity. Through the development of a biological specimen bank, we will study potential mechanisms underlying the effects of the intervention. The primary outcome for the trial is childhood OWO (body mass index for age ≥85th percentile) at 5 years of age, based on WHO sex-specific standards. The study has a power of 0.8 (α=0.05) to detect a 30% risk reduction in the proportion of children with OWO at 5 years of age, from 24.4% in the control group to 17% in the intervention group. Recruitment was launched on 30 August 2018 for the pilot study and 10 January 2019 for the formal study. ETHICS AND DISSEMINATION: The study has been approved by the Medical Research Ethics Committee of the International Peace Maternity and Child Health Hospital in Shanghai, China, and the Research Ethics Board of the Centre Intégré Universitaire de Santé et Services Sociaux de l'Estrie-CHUS in Sherbrooke, Canada. Data sharing policies are consistent with the governance policy of the HeLTI consortium and government legislation. TRIAL REGISTRATION NUMBER: ChiCTR1800017773. PROTOCOL VERSION: November 11, 2020 (Version #5).
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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 | 0.040 | 0.040 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.136 | 0.026 |
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".