Scoping review of the methodology of large health surveys conducted in Spain early on in the COVID-19 pandemic

• Main Authors: Carmen Sánchez-Cantalejo Garrido (Author), Daniela Yucumá Conde (Author), María del Mar Rueda (Author), Antonio Olry- (Author), Eva Martín-Ruiz (Author), Camila Higueras-Callejón (Author), Andrés Cabrera-León (Author)
• Format: Book
• Published: Frontiers Media S.A., 2023-08-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2296-2565; 10.3389/fpubh.2023.1217519
• Keywords: COVID-19; surveys and questionnaires; mental health; non-probability surveys; reweighting; Public aspects of medicine; RA1-1270
• Source: Frontiers in Public Health, Vol 11 (2023)

BackgroundThe use of health surveys has been key in the scientific community to promptly communicate results about the health impact of COVID-19. But what information was collected, where, when and how, and who was the study population?ObjectiveTo describe the methodological characteristics used in large health surveys conducted in Spain early on in the COVID-19 pandemic.MethodsScoping review. Inclusion criteria: observational studies published between January 2020 and December 2021, with sample sizes of over 2,000 persons resident in Spain. Databases consulted: PubMed, CINAHL, Literatura Latinoamericana y del Caribe en CC de la Salud, Scopus, PsycINFO, Embase, Sociological Abstracts, Dialnet and Web of Science Core Collection. We analyzed the characteristics of the literature references, methodologies and information gathered in the surveys selected. Fifty five studies were included.ResultsSixty percentage of the studies included had mental health as their main topic and 75% were conducted on the general adult population. Thirteen percentage had a longitudinal design, 93% used the internet to gather information and the same percentage used non-probability sampling. Thirty percentage made some type of sampling correction to reduce coverage or non-response biases, but not selection biases. Sixty seven percentage did not state the availability of their data.ConclusionsConsistent with the extensive use of non-probability sampling without any bias correction in the extraordinary setting created by COVID-19, quality population frameworks are required so that probability and representative samples can be extracted quickly to promptly address other health crises, as well as to reduce potential coverage, non-response and particularly selection biases by utilizing reweighting techniques. The low data accessibility despite the huge opportunity that COVID-19 provided for Open Science-based research is striking.