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Controlling social desirability bias: An experimental investigation of the extended crosswise model

Indirect questioning techniques such as the crosswise model aim to control for socially desirable responding in surveys on sensitive personal attributes. Recently, the extended crosswise model has been proposed as an improvement over the original crosswise model. It offers all of the advantages of t...

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Detalles Bibliográficos
Autores principales: Meisters, Julia, Hoffmann, Adrian, Musch, Jochen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721152/
https://www.ncbi.nlm.nih.gov/pubmed/33284820
http://dx.doi.org/10.1371/journal.pone.0243384
Descripción
Sumario:Indirect questioning techniques such as the crosswise model aim to control for socially desirable responding in surveys on sensitive personal attributes. Recently, the extended crosswise model has been proposed as an improvement over the original crosswise model. It offers all of the advantages of the original crosswise model while also enabling the detection of systematic response biases. We applied the extended crosswise model to a new sensitive attribute, campus islamophobia, and present the first experimental investigation including an extended crosswise model, and a direct questioning control condition, respectively. In a paper-pencil questionnaire, we surveyed 1,361 German university students using either a direct question or the extended crosswise model. We found that the extended crosswise model provided a good model fit, indicating no systematic response bias and allowing for a pooling of the data of both groups of the extended crosswise model. Moreover, the extended crosswise model yielded significantly higher estimates of campus Islamophobia than a direct question. This result could either indicate that the extended crosswise model was successful in controlling for social desirability, or that response biases such as false positives or careless responding have inflated the estimate, which cannot be decided on the basis of the available data. Our findings highlight the importance of detecting response biases in surveys implementing indirect questioning techniques.