"Did I buy that just now?" – Investigating factors influencing the accuracy of food choice self-reports in a simulated online grocery store

Food choices profoundly impact population health and the environment. Related research often relies on self-reported data, which is prone to biases, compromising the accuracy and validity of conclusions about consumer behavior. There are few systematic validations of self-reported data with behavioral data, or examinations of predictors for their accuracy. Consequently, this study compares self-reported with observed food choices, by having participants (N = 290) complete a shopping task in a simulated online grocery store, followed immediately by shopping self-reports and a survey, therefore minimizing recall-related distortions to self-reports due to time delays. Nevertheless, on average, participants had reporting errors in 3.81 out of 29 categories, with accuracy as low as a mean of 44 % for categories with no cues provided. Reporting accuracy significantly increased to 78 % with image-based memory aids for specific product categories (e.g., apples), and to 89 % with text-based memory aids for general categories (e.g., vegetables). Contrary to expectations related to social desirability bias, processed foods, often perceived as unhealthy, were overreported. Regression analysis revealed mental load during shopping, deliberation time per item, and health-related identity as significant predictors of self-report accuracy, with mental load also predicting the accuracy of participants' estimates of the proportion of organic products in their shopping basket. Our findings show that even in conditions that minimize social desirability and recall limitations, substantial self-reporting errors persist. Accounting for mental load and product-specific biases is therefore necessary to enhance the validity of self-reports in food choice research.