Participant characteristics and study features associated with high retention rates in a longitudinal investigation of type 1 diabetes mellitus
Bibliographic record
Abstract
BACKGROUND: The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study has sustained an extraordinarily high level of participant involvement for over two decades. PURPOSE: In order to identify specific characteristics of EDIC that contributed most strongly to retention, study-designed questionnaires were distributed to 1334 participants. METHODS: Confidential questionnaires were completed during EDIC Years 15-17. Participants were classified as Completely Adherent (completed all visits), Partly Adherent (missed >1 visit or major portion of a visit), or Inactive (did not participate for >5 years). Questionnaire items addressed specific aspects of clinic visits, evaluation procedures, staff-participant relationships, and medical/health-care support provided by EDIC. RESULTS: The most commonly cited reasons for continuing participation were Cutting Edge Tests to assess diabetes complications (79.3%), Annual Evaluations (67.7%), a desire to Help Others (65.2%), and Better Care for Diabetes (61.6%). Women chose Cutting Edge Tests as their first or second most important reason significantly more often than men, whereas men chose Better Care for Diabetes more frequently. Individuals with at least three diabetes-related complications were more likely than those with fewer complications to choose Annual Evaluations as their first or second reason for continued involvement. LIMITATIONS: The small proportion of individuals who discontinued participation restricted our ability to identify factors associated with suspended involvement. In addition, our analysis is limited to a cohort with type 1 diabetes followed in an observational study after an average participation time of 6.5 years in a randomized trial. CONCLUSIONS: The primary reasons identified by respondents for their long-term commitment are consistent with shorter-term studies and underscore the importance of expert medical care, supportive staff-participant relationships, and involvement with clinically and scientifically meaningful research.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".