COVER-ME: Developing and Evaluating community-based interventions to promote vaccine uptake in East London minority ethnicity (ME) populations; underserved migrants and persons with low income: protocol for a pilot randomised controlled trial
Bibliographic record
Abstract
Abstract Introduction Under vaccination amongst underserved groups remains low due to existing disparities. This is particularly the case with post-pandemic COVID-19 vaccinations, and other vaccine-preventable diseases including measles, Mumps and Rubella (MMR) or influenza. Therefore, we aim to 1) to determine the feasibility and practicality of implementing a patient engagement tool (PET) and gain vital insights to plan a subsequent definitive randomised controlled trial (RCT) to evaluate the effectiveness of this tool for increasing uptake of COVID-19 and Flu vaccination; 2) and to define the appropriate level of support needed for health care providers at site-level to ensure successful implementation of the PET and to identify supporting activities needed to implement interventions for COVID-19 and Flu vaccinations. Methods and Analysis This is a randomised controlled feasibility study evaluating a co-designed PET, involving randomisation at individual and cluster level. For individual randomisation, patients will be individually randomised 1:1 to receive the intervention (PET) or routine care; whereas for cluster randomisation six GP practices will be randomised 1:1, and divided into two tranches at two separate time points. Both groups will receive training and activation of the software. Data will be analysed using statistical software R (4.0 or greater) or STATA (17 or greater). Baseline characteristics will be summarised and presented in groups based on an intention to treat (ITT) basis with categorical data; including demographics, socioeconomic variables, co-morbidities, and vaccination status. Ethics and Dissemination Ethical approval was granted Westminster Ethics Committee (ref: 316860). Our dissemination strategy targets three audiences: (1) Policy makers, public and health service managers and clinicians responsible for delivering vaccines and infection prevention services; (2) patients and public from underserved population groups (3) academics.
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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 | 0.050 | 0.044 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.069 | 0.012 |
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".