The global SARS-CoV-2 outbreak and subsequent lockdown had a significant impact on people’s daily lives, with strong implications for stress levels due to the threat of contagion and restrictions to freedom. Given the link between high stress levels and adverse physical and mental consequences, the COVID-19 pandemic is certainly a global public health issue. In the present study, we assessed the effect of the pandemic on stress levels in N = 2053 Italian adults, and characterized more vulnerable individuals on the basis of sociodemographic features and stable psychological traits. A set of 18 psycho-social variables, generalized regressions, and predictive machine learning approaches were leveraged. We identified higher levels of perceived stress in the study sample relative to Italian normative values. Higher levels of distress were found in women, participants with lower income, and participants living with others. Higher rates of emotional stability and self-control, as well as a positive coping style and internal locus of control, emerged as protective factors. Predictive learning models identified participants with high perceived stress, with a sensitivity greater than 76%. The results suggest a characterization of people who are more vulnerable to experiencing high levels of stress during the COVID-19 pandemic. This characterization may contribute to early and targeted intervention strategies.

The latest developments in the field of artificial intelligence (AI) have given rise to many ethical and socio-economic concerns. Nonetheless, the impact of AI technologies is evident and tangible in our everyday life. This dichotomy leads to mixed feelings toward AI: people recognize the positive impact of AI, but they also show concerns, especially about their privacy and security. In this article, we try to understand whether the implicit and explicit attitudes toward AI are coherent. We investigated explicit and implicit attitudes toward AI by combining a self-report measure and an implicit measure, i.e., the implicit association test. We analyzed the explicit and implicit responses of 829 participants. Results revealed that while most of the participants explicitly express a positive attitude toward AI, their implicit responses seem to point in the opposite direction. Results also show that, in both the explicit and implicit measures, females show a more negative attitude than males, and people who work in the field of AI are inclined to be positive toward AI.

Background: Advancements in technology offer new opportunities to support vulnerable populations, such as pregnant women and women diagnosed with breast cancer, during physiologically and psychologically stressful periods. Objective: This study aims to adapt and co-design the World Health Organization’s Self-Help Plus intervention into a mobile health intervention for these target groups. Methods: On the basis of the Obesity-Related Behavioral Intervention Trials and Center for eHealth Research and Disease Management models, low-fidelity and high-fidelity prototypes were developed. Prototypes were evaluated by 13 domain experts from diverse sectors and 15 participants from the target groups to assess usability, attractiveness, and functionality through semantic differential scales, the User Version of the Mobile Application Rating Scale questionnaire, and semistructured interviews. Results: Feedback from participants indicated positive perceptions of the mobile health intervention, highlighting its ease of use, appropriate language, and attractive multimedia content. Areas identified for improvement included enhancing user engagement through reminders, monitoring features, and increased personalization. The quality of the content and adherence to initial protocols were positively evaluated. Conclusions: This research provides valuable insights for future studies aiming to enhance the usability, efficacy, and effectiveness of the app, suggesting the potential role of a chatbot-delivered Self-Help Plus intervention as a supportive tool for pregnant women and women with a breast cancer diagnosis.

Existing studies in the literature indicate an association between the use of dating apps and substance-related behaviours (i.e., alcohol consumption, drug consumption). However, to date, no studies investigated the relation between dating app use and smoking. This study aims to explore this association. A total of 1278 respondents completed an online ad hoc questionnaire assessing demographics, smoking habits, dating app use, motivations for using dating apps. Multiple logistic regression analyses were run to investigate the relation between demographics and dating apps use on tobacco consumption. Being active user was significantly associated with being smoker, light daily and moderate-to-heavy smoker. Among users, using apps with the motive of searching for friends accounted for lower odds of smoking, light daily smoking and moderate-to-heavy smoking. However, heavy dating app users were less likely to smoke, to be light daily smokers and to be moderate-to-heavy smokers. The study indicates an association between using the apps and smoking, suggesting that motives for using the apps and intensity of use may moderate this association.

To date, the relationship between alcohol use and dating app use has been investigated mostly in conjunction with sexual activities and in homosexual men. For this reason, the aim of this study was to explore the association between dating app use and alcohol consumption among the general population. A cross-sectional study was conducted including app users, non-users, and former users: 1278 respondents completed an online ad hoc questionnaire assessing dating app use, motivations for installing dating apps, alcohol use, and demographics. Multiple logistic regression analysis was run to investigate the association between dating app use, demographic features, and alcohol consumption. Whereas educational level, age, and gender significantly contributed to the regular consumption of alcohol, dating app use did not account for a significant amount of variance between regular and not regular drinkers. However, people who installed and used dating apps with the motivation of searching for sexual partners were more likely to be regular drinkers. Among the active users, heavy app users were less likely to drink regularly. The study indicates that underlying factors (sexual aspects, motives for using the apps) and the intensity of using the apps may mediate the relationship between dating app use and alcohol use.