Recruitment and retention of participants for an international type 1 diabetes prevention trial: a coordinators' perspective
Bibliographic record
Abstract
BACKGROUND: The Trial to Reduce Insulin Dependent Diabetes Mellitus in the Genetically at Risk (TRIGR) is the first multicenter international type 1 diabetes (T1D) prevention trial to be undertaken. A unique feature of TRIGR has been recruitment of eligible pregnant women and enrollment of newborns for long-term follow-up assessments. PURPOSE: Our purpose is to summarize the recruitment and retention strategies used to conduct TRIGR from the perspective of the study coordinators. METHODS: TRIGR was designed to test whether weaning to formula containing hydrolyzed versus intact cow's milk protein would be efficacious in decreasing risk for development of T1D-associated autoantibodies and T1D among infants identified to be at increased risk for T1D based on their human leukocyte antigen (HLA) profile and family history. Multiple strategies tailored to local issues were required to enroll and follow the target number of infants. RESULTS: This study was conducted in the United States, Canada, Australia, and 12 countries in Europe. Of the 5606 mothers registered worldwide, 5000 of their infants were randomized. Of these, 2159 were HLA eligible and enrolled in the 8-month intervention and 10-year follow-up phases of this study. The TRIGR study met the accrual goal after 4.7 years of recruitment, 2.7 years longer than projected initially. Challenges included difficulty in finding fathers with T1D, a higher than expected rate of premature delivery among T1D mothers, and implementation of new privacy regulations mid-trial. The majority of participants were recruited from primary care antenatal clinics located near the study centers and from a general hospital or pediatric center that was affiliated with a TRIGR Study center. Internet and magazine advertisements were found to be useful for recruitment of families. Alternative follow-up strategies are offered to families who wish to reduce or discontinue participation. LIMITATIONS: Our experience is limited to a single international multicenter trial. CONCLUSIONS: TRIGR coordinators played key roles in the recruitment and intervention periods and continue to be instrumental in retaining families and children during the 10-year follow-up period for each child.
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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 | 0.277 | 0.277 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".