A Cross Sectional Survey of Recruitment Practices, Supports, and Perceived Roles for Unaffiliated and Non-scientist Members of IRBs
Notice bibliographique
Résumé
BACKGROUND: Institutional Review Boards (IRBs) are federally mandated to include both nonscientific and unaffiliated representatives in their membership. Despite this, there is no guidance or policy on the selection of unaffiliated or non-scientist members and reports indicate a lack of clarity regarding members' roles. In the present study we sought to explore processes of recruitment, training, and the perceived roles for unaffiliated and non-scientist members of IRBs. METHODS: We distributed a self-administered REDCap survey of members of the Association for the Accreditation of Human Research Protection Programs familiar with IRB member recruitment. The survey included closed and open-ended questions regarding: the operation of the HRPP/IRB(s), how unaffiliated and non-scientist members are recruited, whether they had faced challenges recruiting for these roles, and training and mentorship offered. The survey also collected information regarding the perceived value and roles of unaffiliated and non-scientist members. RESULTS: 76 responses were included in the analysis (38% completion rate). The most common approach for recruitment was referral from current IRB members, with almost half of respondents indicating challenges recruiting unaffiliated members. Over 75% indicated no additional training was provided to unaffiliated or non-scientist members compared to affiliated or scientist members. Most common supports provided were travel/parking expenses and honoraria. Commonly perceived roles were to provide an independent voice from the participant perspective, notably regarding consent processes and materials. CONCLUSIONS: Respondents indicated challenges in defining unaffiliated and non-scientist members and limited practices toward recruitment and support. Future work should more closely examine the challenges in defining these roles and applying the definitions in practice, as well as strategies that may improve recruitment and retention of unaffiliated and non-scientist members.
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 | 0,014 | 0,060 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,003 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».