Nonparticipation reasons in a randomized international trial of a new latent tuberculosis infection regimen
Notice bibliographique
Résumé
BACKGROUND/AIMS: Efficient recruitment of eligible participants, optimizing time and sample size, is a crucial component in conducting a successful clinical trial. Inefficient participant recruitment can impede study progress, consume staff time and resources, and limit quality and generalizability or the power to assess outcomes. Recruitment for disease prevention trials poses additional challenges because patients are asymptomatic. We evaluated candidates for a disease prevention trial to determine reasons for nonparticipation and to identify factors that can be addressed to improve recruitment efficiency. METHODS: During 2001-2009, the Tuberculosis Trials Consortium conducted Study 26 (PREVENT TB), a randomized clinical trial at 26 sites in four countries, among persons with latent tuberculosis infection at high risk for tuberculosis disease progression, comparing 3 months of directly observed once-weekly rifapentine plus isoniazid with 9 months of self-administered daily isoniazid. During March 2005-February 2008, non-identifying demographic information, risk factors for experiencing active tuberculosis disease, and reasons for not enrolling were collected from screened patients to facilitate interpretation of trial data, to meet Consolidated Standards of Reporting Trials standards, and to evaluate reasons for nonparticipation. RESULTS: Of the 7452 candidates screened in Brazil, Canada, Spain, and the United States, 3584 (48%) were not enrolled, because of ineligibility (41%), site decision (10%), or patient choice (49%). Among those who did not enroll by own choice, and for whom responses were recorded on whether they would accept treatment outside of the study (n = 1430), 68% reported that they planned to accept non-study latent tuberculosis infection treatment. Among 1305 patients with one or more reported reasons for nonparticipation, study staff recorded a total of 1886 individual reasons (reason count: median = 1/patient; range = 1-9) for why patients chose not to enroll, including grouped concerns about research (24% of 1886), work or school conflicts (20%), medication or health beliefs (16%), latent tuberculosis infection beliefs (11%), and patient lifestyle and family concerns (10%). CONCLUSION: Educational efforts addressing clinical research concerns and beliefs about medication and health, as well as study protocols that accommodate patient-related concerns (e.g. work, school, and lifestyle) might increase willingness to enter clinical trials. Findings from this evaluation can support development of communication and education materials for clinical trial sites at the beginning of a trial to allow study staff to address potential participant concerns during study screening.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,038 | 0,154 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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; les deux têtes enseignantes 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 ».