The impact of COVID-19 restrictions on participant enrollment in the PREPARE trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: At the initiation of the COVID-19 pandemic, restrictions forced researchers to decide whether to continue their ongoing clinical trials. The PREPARE (Pragmatic Randomized Trial Evaluating Pre-Operative Alcohol Skin Solutions in Fractured Extremities) trial is a pragmatic cluster-randomized crossover trial in patients with open and closed fractures. PREPARE was enrolling over 200 participants per month at the initiation of the pandemic. We aim to describe how the COVID-19 research restrictions affected participant enrollment. Methods: The PREPARE protocol permitted telephone consent, however, sites were obtaining consent in-person. To continue enrollment after the initiation of the restrictions participating sites obtained ethics approval for telephone consent scripts and the waiver of a signature on the consent form. We recorded the number of sites that switched to telephone consent, paused enrollment, and the length of the pause. We used t-tests to compare the differences in monthly enrollment between July 2019 and November 2020. Results: All 19 sites quickly implement telephone consent. Fourteen out of nineteen (73.6%) sites paused enrollment due to COVID-19 restrictions. The median length of enrollment pause was 46.5 days (range, 7-121 days; interquartile range, 61 days). The months immediately following the implementation of restrictions had significantly lower enrollment. Conclusion: A pragmatic design allowed sites to quickly adapt their procedures for obtaining informed consent via telephone and allowed for minimal interruptions to enrollment during the pandemic.
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.
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 | 0.040 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it