Efficiency and Cost: E-Recruitment Is a Promising Method in Gynecological Trials
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,357 | 0,524 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,006 | 0,008 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,007 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,005 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».