Cost analysis and efficacy of recruitment strategies used in a large pragmatic community-based clinical trial targeting low-income seniors: a comparative descriptive analysis
Bibliographic record
Abstract
OBJECTIVE: One of the most challenging parts of running clinical trials is recruiting enough participants. Our objective was to determine which recruitment strategies were effective in reaching specific subgroups. STUDY DESIGN AND SETTING: We assessed the efficacy and costs of the recruitment strategies used in the Assessing Outcomes of Enhanced Chronic Disease Care Through Patient Education and a Value-based Formulary Study (ACCESS) in Alberta, Canada. RESULTS: Twenty percent of the study budget ($354,330 CAD) was spent on recruiting 4013 participants, giving an average cost per enrolled of $88 CAD. Pharmacies recruited the most participants (n = 1217), at a cost of $128/enrolled. "Paid media" had the highest cost ($806/enrolled), whereas "word of mouth" and "unpaid media" had the lowest (~$3/enrolled). Participants enrolled from "seniors outreach" had the lowest baseline quality of life and income, while participants from "word of mouth" had the lowest educational attainment. CONCLUSION: The "health care providers" strategies were especially successful - at a moderate cost per enrolled. The "media" strategies were less effective, short lasting, and more costly. No strategy was singularly effective in recruiting our targeted groups, emphasizing the importance of utilizing a variety of strategies to reach recruitment goals. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02579655 . Registered on 19 October 2015.
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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 | 0.097 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".