RESUMEN
Food purchase choices, one of the main determinants of food consumption, is highly influenced by food environments. Given the surge in online grocery shopping because of the COVID-19 pandemic, interventions in digital environments present more than ever an opportunity to improve the nutritional quality of food purchase choices. One such opportunity can be found in gamification. Participants (n = 1228) shopped for 12 items from a shopping list on a simulated online grocery platform. We randomized them into four groups in a 2 × 2 factorial design: presence vs. absence of gamification, and high vs. low budget. Participants in the gamification groups saw foods with 1 (least nutritious) to 5 (most nutritious) crown icons and a scoreboard with a tally of the number of crowns the participant collected. We estimated ordinary least squares and Poisson regression models to test the impact of the gamification and budget on the nutritional quality of the shopping basket. In the absence of gamification and low budget, participants collected 30.78 (95% CI [30.27; 31.29]) crowns. In the gamification and low budget condition, participants increased the nutritional quality of their shopping basket by collecting more crowns (B = 4.15, 95% CI [3.55; 4.75], p < 0.001). The budget amount ($50 vs. $30) did not alter the final shopping basket (B = 0.45, 95% CI [-0.02; 1.18], p = 0.057), nor moderated the gamification effect. Gamification increased the nutritional quality of the final shopping baskets and nine of 12 shopping list items in this hypothetical experiment. Gamifying nutrition labels may be an effective strategy to improve the nutritional quality of food choices in online grocery stores, but further research is needed.
Asunto(s)
COVID-19 , Preferencias Alimentarias , Humanos , Comportamiento del Consumidor , Gamificación , Estado Nutricional , PandemiasRESUMEN
Progressive visualization is fast becoming a technique in the visualization community to help users interact with large amounts of data. With progressive visualization, users can examine intermediate results of complex or long running computations, without waiting for the computation to complete. While this has shown to be beneficial to users, recent research has identified potential risks. For example, users may misjudge the uncertainty in the intermediate results and draw incorrect conclusions or see patterns that are not present in the final results. In this article, we conduct a comprehensive set of studies to quantify the advantages and limitations of progressive visualization. Based on a recent report by Micallef et al., we examine four types of cognitive biases that can occur with progressive visualization: uncertainty bias, illusion bias, control bias, and anchoring bias. The results of the studies suggest a cautious but promising use of progressive visualization - while there can be significant savings in task completion time, accuracy can be negatively affected in certain conditions. These findings confirm earlier reports of the benefits and drawbacks of progressive visualization and that continued research into mitigating the effects of cognitive biases is necessary.