Comparative Success of Recruitment Strategies for an Exercise Intervention Trial Among Women With Polycystic Ovary Syndrome: Observational Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Effective and efficient participant recruitment is a key determinant of the success of a research program. Previously reported recruitment strategies have displayed variable success rates in studies on women with polycystic ovary syndrome (PCOS). OBJECTIVE This study aimed to evaluate the effectiveness and cost per participant of the recruitment strategies that we used in a prospective randomized controlled trial to examine the effects of exercise training among inactive women with PCOS, who are aged 18-40 years. METHODS The 4 recruitment methods we used were as follows: (1) referral by health care providers or by word of mouth, (2) media (eg, local newspaper stories and radio interviews), (3) Facebook advertisements, and (4) unpaid advertisements including posters and websites. The proportions of potential, eligible, and enrolled participants recruited with each method were determined and compared using tests of proportion. The time investment and cost per participant enrolled were calculated for each recruitment strategy. RESULTS Of 200 potential participants screened, 98 (49%) were recruited from unpaid advertisements (posters and websites), 70 (35%) from Facebook advertisements, 16 (8%) by referral, and 16 (8%) from traditional media (newspaper and radio). Every potential participant was recruited from separate means (ie, no participant was approached through more than one recruitment method). A total of 109 (54.5%) women were deemed eligible for participation in the trial, and 60 (30.0%) were enrolled. The proportion of potential participants who completed the trial was higher for those recruited from traditional media than from Facebook advertisements (n=7/16, 44% vs n=13/70, 19%, respectively; P=.03) or unpaid advertisements (n=7/16, 44% vs n=13/98, 13%, respectively; P=.002). The cost per participant was Can $18.21 for Facebook advertisements and Can $43.88 for unpaid advertisements. There were no direct trial costs for referrals or traditional media. CONCLUSIONS For this trial, each method was important for recruiting inactive women with PCOS because no participant reported learning about the trial through more than one method. Unpaid advertisements and Facebook advertisements helped recruit the largest number of participants in the trial, the former resulting in a higher cost per participant than the latter. CLINICALTRIAL ClinicalTrials.gov NCT03362918; https://clinicaltrials.gov/ct2/show/NCT03362918
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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 | 0.049 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".