Participation in Clinical Trials Among Academic Dermatologists Affiliated With Veterans Affairs Hospitals: Survey Study
Notice bibliographique
Résumé
Background: Clinical trials have led to the development of new and effective therapies for many dermatologic conditions. To our knowledge, there is no published study that has quantified and described the degree of involvement in clinical trials among academic dermatologists and their university affiliates. Objective: The purpose of this study was to characterize the involvement of academic dermatology departments in clinical trials research. Methods: An online survey was sent to 211 Veterans Affairs (VA)-employed dermatologists. It comprised 20 questions related to the number of clinical trials, support staff dedicated to clinical research, skin diseases studied, and the effect of the COVID-19 pandemic on conducting clinical research. Three rounds of survey invitations were sent over a 3-month period (March to May 2021). Data from all survey responses were reviewed for quantitative and descriptive analyses of the key outcome measures. Results: A total of 48 dermatologists completed the survey and provided their university affiliations and details of involvement in clinical trials research. Over half of participants (n=25, 58.1%) with a university affiliate reported that their affiliated dermatology department had a dedicated clinical trials unit. Basal cell carcinoma was the most frequently studied skin condition (n=9, 18.8%), followed by atopic dermatitis and psoriasis (n=4, 8.3% each); 66.7% of participants reported no current clinical trials participation. Of those conducting clinical trials, 87% (n=18) noted that COVID-19 was a barrier to conducting trials, with 52.2% (n=11) citing disrupted or decreased trials due to the pandemic. Conclusions: Although many dermatologists with university affiliations reported having a dedicated clinical trials unit at their institution, a majority of those surveyed reported not taking part in any active trials. Overall, the diseases investigated in academic clinical trials appear to follow national trends, though some of the top dermatological diseases are underrepresented in clinical trials research. A key limitation of our study was the low response rate (~23%) and that the survey responses from the sample of VA-based dermatologists may not be generalizable to all academic dermatology departments in the United States. The effect of the COVID-19 pandemic appeared to play a significant role in disrupting active trials.
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 | 0,015 | 0,056 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,002 |
| 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 ».