Space For Children: improving mastery and reducing negative emotions about COVID-19 in youth via mobile interactive storytelling.

BACKGROUND: The COVID-19 pandemic has been a complex event for children and adolescents, significantly impacting their daily activities. In this scenario, our study aims at verifying if "Space for Children," an ad-hoc developed game based on interactive storytelling about the pandemic, can increase mastery and reduces negative emotions about COVID-19. METHODS: The app Space for Children has been sponsored and spread online by email and social media platforms for a limited time period (from May 2021 to January 2022). Before and after the interactive storytelling, participants answered two questionnaires containing a couple of critical questions regarding their emotional state and their perceived mastery about COVID-19. RESULTS: Two hundred thirty-six participants (M=116; F=120) between 7 and 12 years old completed the Space for Children interactive experience. Our results show a significant effect of the game experience on emotional state and perceived mastery regarding COVID-19. Indeed, before the interactive storytelling unpleasant emotional states prevail (reported by 77% of participants) while after the game a clear prevalence of pleasant emotions emerges (reported by 68% of participants). Regarding perceived mastery, results show that self-reported very expert participants passed from 49% to 88%. All the results hold irrespective of age group and sex. CONCLUSIONS: This study presents preliminary findings that highlight the potential benefits of utilizing new technologies based on Interactive Storytelling for Children to effectively convey age-appropriate information about complex real-life events, such as the COVID-19 pandemic, while also mitigating associated negative emotional responses.

Verbal lie detection using Large Language Models.

Human accuracy in detecting deception with intuitive judgments has been proven to not go above the chance level. Therefore, several automatized verbal lie detection techniques employing Machine Learning and Transformer models have been developed to reach higher levels of accuracy. This study is the first to explore the performance of a Large Language Model, FLAN-T5 (small and base sizes), in a lie-detection classification task in three English-language datasets encompassing personal opinions, autobiographical memories, and future intentions. After performing stylometric analysis to describe linguistic differences in the three datasets, we tested the small- and base-sized FLAN-T5 in three Scenarios using 10-fold cross-validation: one with train and test set coming from the same single dataset, one with train set coming from two datasets and the test set coming from the third remaining dataset, one with train and test set coming from all the three datasets. We reached state-of-the-art results in Scenarios 1 and 3, outperforming previous benchmarks. The results revealed also that model performance depended on model size, with larger models exhibiting higher performance. Furthermore, stylometric analysis was performed to carry out explainability analysis, finding that linguistic features associated with the Cognitive Load framework may influence the model's predictions.

Breaking (Fake) News: No Personal Relevance Effect on Misinformation Vulnerability.

The massive spread of fake news (FN) requires a better understanding of both risks and protective psychological factors underlying vulnerability to misinformation. Prior studies have mostly dealt with news that do not bear any direct personal relevance to participants. Here, we ask whether high-stakes news topics may decrease vulnerability to FN. Data were collected during the national lockdown in Italy (COVID-19 news) and one year later (political news). We compared truth discrimination and overall belief for true news (TN) and FN concerning COVID-19 and political topics. Our findings indicate that psychological risk and protective factors have similar effects on truth discrimination, regardless of whether the news topic is highly or minimally personally relevant. However, we found different effects of psychological factors on overall belief, for high and low personal relevance. These results suggest that, given a high level of cognitive dissonance, individuals tend to rely on proximal or emotional sources of information. In summary, our study underscores the importance of understanding the psychological factors that contribute to vulnerability to misinformation, particularly in high-stakes news contexts.