546-P: Impact of the COVID-19 Public Health Emergency on Enrollment and Outcomes in the National Diabetes Prevention Program
Bibliographic record
Abstract
The National Diabetes Prevention Program is a partnership of public and private organizations working to build a nationwide delivery system for a lifestyle change program (LCP) to prevent or delay type 2 diabetes. Using data submitted to the Diabetes Prevention Recognition Program (DPRP), this study examines the impact of the COVID-19 public health emergency (PHE) on delivery of the LCP by looking at how adapting delivery from in-person to virtual allowed the 12-month intervention to continue. Participant start dates were categorized into 3 groups: 1) enrolled/concluded pre-PHE start, 2) enrolled pre-PHE start/concluded post-PHE start, and 3) enrolled/will conclude post-PHE start. As of October 2022, enrollment was at 658,385: 348,672 in group 1, 124,077 in group 2, and 185,636 in group 3. Mean reported weekly physical activity (PA) minutes and mean weight loss (WL) were calculated for each quarter of the LCP for each group. Despite the PHE causing abrupt changes in daily life, results show that participants whose time in the LCP overlapped or was entirely within the PHE, had strong PA and WL outcomes. Regardless of phase, participants who attended sessions in the 3rd quarter and the 4th quarter, on average, met programmatic goals of 150 PA minutes and 5% weight loss. These outcomes are indicative of lifestyle change, contributing to reducing the risk of developing type 2 diabetes. Disclosure E.Ely: None.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".