Remote Participant Recruitment for Pediatric Research During the COVID-19 Pandemic
Notice bibliographique
Résumé
Background The COVID-19 pandemic exposed significant vulnerabilities of traditional in-person recruitment methodology in the context of limited access to clinical facilities. Remote recruitment is a potential solution, but its yield and efficiency are unknown. Objective This study aimed to determine remote recruitment and enrollment rates for a pilot feasibility trial of an electronic monitoring device (EMD) for asthma in the pediatric population. Methods Children aged 4-18 years with persistent asthma receiving inhaler medications compatible with an EMD were screened for enrollment in a feasibility and acceptability trial. The emergency department (ED) and inpatient wards were identified as initial in-person recruitment locations prior to the pandemic. Owing to the COVID-19 pandemic, recruitment sites transitioned from exclusive ED or inpatient enrollment to outpatient primary care or pulmonary clinics in an attempt to increase enrollment rates. Study staff called families to determine their interest in the study. Patient age, race and ethnicity, insurance, contact attempts, and reasons for enrollment or refusal were recorded. e-Consent was obtained through the REDCap database, and baseline surveys were administered by telephone. Results Since November 2019, the study staff reached 147 out of 278 (52.3%) eligible families by telephone. In total, 37 (13%) families contacted were enrolled in the study. It took the study staff a mean of 2 attempts to reach individuals for initial enrollment but a mean of 4 additional attempts to complete consent forms. Of the families approached, 47% were Hispanic or Latino, 26.5% were Black or African American, 24.5% were White, and 2% were Asian. Among patients approached, 20% Asian, 16% White, 14.5% Hispanic or Latino, and 12% Black patients were enrolled in the study. Conclusions Telephone recruitment had a low yield across all racial and ethnic groups, averaging approximately 1 successful enrollment per 8 candidates approached. A substantial number of contacts was required to obtain e-consent forms and complete survey questionnaires after participants agreement to enroll. The study findings suggest that when there are barriers to in-person recruitment, remote recruitment is a feasible alternative, but the yield is relatively low, and enrollment requires persistent, repeated follow-up contact. Conflicts of Interest None declared.
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 | 0,115 | 0,067 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 0,004 |
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 source (Gemma direct ou Codex distillé), 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 ».