Universitat Pompeu Fabra
2026-02-20T08:05:26Z
2026-02-20T08:05:26Z
2026
2026-02-20T08:05:26Z
Data de publicació electrònica: 03-01-2026
Despite growing interest in collecting photos within online surveys, little is known about the quality of visual data and its comparison with data obtained through conventional requests. To address this gap, a self-administered online mobile survey targeting parents of children attending primary school in Spain was conducted through the Netquest opt-in panel in 2023. The survey gathered information about books in respondents' homes through photos and conventional questions. First, a review of previous research using conventional questions, photos, and other emerging data types was conducted to identify indicators suitable to evaluate the quality of the information about books at home collected through conventional and image-based formats. Second, most of these indicators to measure quality were estimated. Results reveal important measurement errors in conventional questions, while photos submitted by respondents are generally in line and can be classified. However, concrete information of interest about the books, such as the intended audience or languages, is often difficult to extract from photos. When comparing quality, conventional answers provide more information about the items asked than photos, but photos have the potential to provide additional insights, such as book titles. Overall, while collecting and analyzing photos sent through surveys presents challenges, their integration into surveys offers unique opportunities to enrich data collection methods.
This project received funding from the European Research Council (ERC) under the European Union¿s Horizon 2020 research and innovation programme (grant agreement No. 849165), the Agencia Nacional de Investigación y Desarrollo (ANID) under the "Becas Chile" Doctoral Fellowship programme (grant No. 72220301 to Patricia A. Iglesias), and GESIS-Leibniz-Institut für Sozialwissenschaften.
Article
Published version
English
(Visual) data quality; Quality indicators; Image collection; Mobile online surveys; Books at home; Measurement errors
Springer
Quality and Quantity. 2026 Jan 3
info:eu-repop/grantAgreement/EC/H2020/849165
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