Softly empowering a prosocial expert in the family: lasting effects of a counter-misinformation intervention in an informational autocracy.

The present work is the first to comprehensively analyze the gravity of the misinformation problem in Hungary, where misinformation appears regularly in the pro-governmental, populist, and socially conservative mainstream media. In line with international data, using a Hungarian representative sample (Study 1, N = 991), we found that voters of the reigning populist, conservative party could hardly distinguish fake from real news. In Study 2, we demonstrated that a prosocial intervention of ~ 10 min (N = 801) helped young adult participants discern misinformation four weeks later compared to the control group without implementing any boosters. This effect was the most salient regarding pro-governmental conservative fake news content, leaving real news evaluations intact. Although the hypotheses of the present work were not preregistered, it appears that prosocial misinformation interventions might be promising attempts to counter misinformation in an informational autocracy in which the media is highly centralized. Despite using social motivations, it does not mean that long-term cognitive changes cannot occur. Future studies might explore exactly how these interventions can have an impact on the long-term cognitive processing of news content as well as their underlying neural structures.

Willingness of Participation in an Application-Based Digital Data Collection among Different Social Groups and Smartphone User Clusters.

The main question of this paper is what factors influence willingness to participate in a smartphone-application-based data collection where participants both fill out a questionnaire and let the app collect data on their smartphone usage. Passive digital data collection is becoming more common, but it is still a new form of data collection. Due to the novelty factor, it is important to investigate how willingness to participate in such studies is influenced by both socio-economic variables and smartphone usage behaviour. We estimate multilevel models based on a survey experiment with vignettes for different characteristics of data collection (e.g., different incentives, duration of the study). Our results show that of the socio-demographic variables, age has the largest influence, with younger age groups having a higher willingness to participate than older ones. Smartphone use also has an impact on participation. Advanced users are more likely to participate, while users who only use the basic functions of their device are less likely to participate than those who use it mainly for social media. Finally, the explorative analysis with interaction terms between levels has shown that the circumstances of data collection matter differently for different social groups. These findings provide important clues on how to fine-tune circumstances to improve participation rates in this novel passive digital data collection.