Efficiency and Cost: E-Recruitment Is a Promising Method in Gynecological Trials
Bibliographic record
Abstract
BACKGROUND: Recruitment of participants is crucial to the success of any trial as it can have a major impact on study costs, the duration of the study itself, and, more critically, trial failure. Given that vulvodynia particularly affects young women, the use of social media and e-recruitment could prove efficient for enrollment. AIM: To compare the efficiency, effectiveness, and cost-effectiveness of three different recruitment methods. METHODS: The comparison data were collected as part of a bicentric randomized controlled trial evaluating the efficacy of physiotherapy in comparison with topical lidocaine in 212 women suffering from provoked vestibulodynia. The recruitment methods included: (i) conventional methods (eg, posters, leaflets, business cards, newspaper ads); (ii) health professional referrals, and (iii) e-recruitment (eg, Facebook ads and web initiatives). Women interested in participating were screened by telephone for eligibility criteria and were assessed by a gynecologist to confirm their diagnosis. Once included, structured interviews were undertaken to describe their baseline characteristics. MAIN OUTCOME MEASURES: The outcomes of this study were the recruitment efficiency (the number of patients screened/enrolled), recruitment effectiveness (the number of participants enrolled), cost-effectiveness (cost per enrolled participant), and retention rate, and baseline characteristics of participants were monitored for each method. RESULTS: The conventional methods (n = 101, 48%) were more effective as they allowed for greater enrollment of participants, followed by e-recruitment (n = 60, 28%) and health professional referrals (n = 33, 16%) (P < 0.007). Recruitment efficiency was found to be similar for e-recruitment and referrals (60/122 and 33/67, 49%, P = 0.055) but lower for conventional methods (101/314, 32%, P < 0.011). Nonsignificant differences were found between the three groups for baseline characteristics (P ≥ 0.189) and retention rate (91%, P ≥ 0.588). The average cost per enrolled participant was fairly similar for e-recruitment ($117) and conventional methods ($110) and lower for referrals ($60). CLINICAL IMPLICATIONS: Our results suggest that having a variety of recruitment methods is beneficial in promoting clinical trial recruitment without affecting participant characteristics and retention rates. STRENGTH & LIMITATIONS: Although recruitment methods were used concomitantly, this study gives an excellent insight into the advantages and limitations of recruitment methods owing to a large sample size. CONCLUSION: The study findings revealed that e-recruitment is a valuable recruitment method because of its comparable efficiency and cost-effectiveness to health professional referrals and conventional methods, respectively. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, number NCT01455350. Benoit-Piau J, Dumoulin C, Carroll MS, et al. Efficiency and Cost: E-Recruitment Is a Promising Method in Gynecological Trials. J Sex Med 2020;17:1304-1311.
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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 | 0.357 | 0.524 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier 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".