Results from the BETTER WISE trial: a pragmatic cluster two arm parallel randomized controlled trial for primary prevention and screening in primary care during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: Cancer and chronic diseases are a major cost to the healthcare system and multidisciplinary models with access to prevention and screening resources have demonstrated improvements in chronic disease management and prevention. Research demonstrated that a trained Prevention Practitioner (PP) in multidisciplinary team settings can improve achievement of patient level prevention and screening actions seven months after the intervention. METHODS: We tested the effectiveness of the PP intervention in a pragmatic two-arm cluster randomized controlled trial. Patients aged 40-65 were randomized at the physician level to an intervention group or to a wait-list control group. The intervention consisted of a patient visit with a PP. The PP received training in prevention and screening and use of the BETTER WISE tool kit. The effectiveness of the intervention was assessed using a composite outcome of the proportion of the eligible prevention and screening actions achieved between intervention and control groups at 12-months. RESULTS: Fifty-nine physicians were recruited in Alberta, Ontario, and Newfoundland and Labrador. Of the 1,005 patients enrolled, 733 (72.9%) completed the 12-month analysis. The COVID-19 pandemic occurred during the study time frame at which time nonessential prevention and screening services were not available and in-person visits with the PP were not allowed. Many patients and sites did not receive the intervention as planned. The mean composite score was not significantly higher in patients receiving the PP intervention as compared to the control group. To understand the impact of COVID on the project, we also considered a subset of patients who had received the intervention and who attended the 12-month follow-up visit before COVID-19. This assessment demonstrated the effectiveness of the BETTER visits, similar to the findings in previous BETTER studies. CONCLUSIONS: We did not observe an improvement in cancer and chronic disease prevention and screening (CCDPS) outcomes at 12 months after a BETTER WISE prevention visit: due to the COVID-19 pandemic, the study was not implemented as planned. Though benefits were described in those who received the intervention before COVID-19, the sample size was too small to make conclusions. This study may be a harbinger of a substantial decrease and delay in CCDPS activities under COVID restrictions. TRIAL REGISTRATION: ISRCTN21333761. Registered on 19/12/2016. http://www.isrctn.com/ISRCTN21333761 .
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".