Evolution of the study coordinator role: The 28-year experience in Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC)
Bibliographic record
Abstract
BACKGROUND: The role of the study coordinator (SC) in multicenter studies of long duration has received limited attention. PURPOSE: To describe the evolution of the SC's role during the 28-year Diabetes Control and Complications Trial (DCCT) and its follow-up study, the Epidemiology of Diabetes Interventions and Complications (EDIC) study. METHODS: The evolution of the SC's position from the traditional role of protocol implementation to that of research collaborator and co-investigator, based on personal experience and observation, is described in detail. Findings from a survey regarding professional demographics and job satisfaction, completed by all 28 SCs in 2010, provided additional information. We used dimensions of the SC's role specific to DCCT/EDIC to construct a classification schema of functions and responsibilities that describe the SC's role. RESULTS: Among the 28 SCs, 24 were nurses, 12 held bachelor's degrees, 11 had a master's degree, 19 were certified diabetes educators (CDEs), 12 had worked with DCCT/EDIC for more than 20 years, and 5 had been with the study since its inception (>26 years). Responses confirmed a high degree of functional consistency across sites with data acquisition, performing study procedures, recruitment and consent for additional ancillary studies, regulatory management, scheduling, clinical consultation, and ongoing contact with study participants frequently reported. Study-wide leadership activities, a category not generally included in the usual SC role, were reported by approximately 30% of the SCs. The level of professional satisfaction was high with two-thirds being very satisfied, one-third moderately to quite satisfied, and none dissatisfied. LIMITATIONS: The limitations include a relatively small sample size, self-reported data, and a single long-term multicenter trial and observational follow-up study on which we based our findings and conclusions. CONCLUSIONS: By optimizing their organizational and scientific contributions to the overall research endeavor, SCs in DCCT/EDIC have made major contributions to the unprecedented success of the study and report high job satisfaction. The efforts of the SCs have been integral to the remarkably high participant retention and data completion rates. The DCCT/EDIC experience may serve as a model for the role of the SC in future diabetes and other multicenter clinical trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.059 | 0.121 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".