A Framework to Improve Data Quality and Manage Dropout in Web-Based Medical Surveys: Insights from an Ai Awareness Study among Italian Physicians

Background Ensuring data quality in self-reported online surveys remains a critical challenge in digital health research, particularly when targeting healthcare professionals [1,2]. Self-reported data are susceptible to multiple biases, including careless responding, social desirability bias, an...

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Detalhes bibliográficos

Principais autores:	Vincenza Cofini, Eugenio Benvenuti, Martina Mancinelli, Ginevra Di Pangrazio, Laura Piccardi, Mario Muselli, Eleonora Cimino, Loreta Tobia, Leila Fabiani, Stefano Necozione
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Milano University Press 2025-09-01
Colecção:	Epidemiology, Biostatistics and Public Health
Acesso em linha:	https://riviste.unimi.it/index.php/ebph/article/view/29202
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