Cigarette Smoking and Dating App Use: Findings from a Survey in a Sample of Adults in Italy.

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.

"What Are You Looking For?" Investigating the Association Between Dating App Use and Sexual Risk Behaviors.

INTRODUCTION: Literature on the association between dating app use and sexual risk behaviors is still scant and inconclusive. AIM: To investigate the association between dating app use and sexual risk behaviors, considering the role of motives for using them. METHODS: 1,278 Italian respondents completed an online questionnaire assessing demographics, motives and patterns of dating app use, sexual behaviors and sexually transmitted infections (STIs) diagnoses. One-way ANOVA and Chi-squared analyses were used to investigate differences among the three subsamples (active vs former vs non-users). Multiple linear and logistic regression analyses were run to investigate the role of demographics, motives and patterns of dating app use on sexual risk taking and sexual health. MAIN OUTCOME MEASURES: Number of protected and unprotected full sexual partners in the last year; frequency of hook-ups in the last year; STIs lifetime. RESULTS: Active users, even more than former app users, were more likely to report risky behaviors and STI diagnoses than non-users (χ2 = 26.37, P < .001). Installing the apps to find friends or romantic partners was associated with less protected (find friends B = -0.364, P = .015; find romantic partners B = -0.300, P = .006) and unprotected (find friends B = -0.346, P = .016; find romantic partners B = -0.360, P < .001) sexual intercourses. Installing the apps to find sexual partners predicted higher odds of unprotected sexual activity (B = 0.193, P = .048), hook-ups (B = 0.496, P < .001) and STIs diagnoses (OR = 2.835, P = .025). Accessing apps more frequently and more years of usage was associated with reporting risky sexual behaviors and STI diagnoses among active users (app access frequency OR = 1.461, P = .003; usage years OR = 1.089, P = .013). CONCLUSION: Installing the apps to search for sexual partners, using them at length since first installation and accessing them frequently are significant factors in influencing the association between dating app use and sexual risk behaviors. Flesia L, Fietta V, Foresta C, Monaro M. "What Are You Looking For?" Investigating the Association Between Dating App Use and Sexual Risk Behaviors. Sex Med 2021;9:100405.

The detection of malingering in whiplash-related injuries: a targeted literature review of the available strategies.

OBJECTIVE: The present review is intended to provide an up-to-date overview of the strategies available to detect malingered symptoms following whiplash. Whiplash-associated disorders (WADs) represent the most common traffic injuries, having a major impact on economic and healthcare systems worldwide. Heterogeneous symptoms that may arise following whiplash injuries are difficult to objectify and are normally determined based on self-reported complaints. These elements, together with the litigation context, make fraudulent claims particularly likely. Crucially, at present, there is no clear evidence of the instruments available to detect malingered WADs. METHODS: We conducted a targeted literature review of the methodologies adopted to detect malingered WADs. Relevant studies were identified via Medline (PubMed) and Scopus databases published up to September 2020. RESULTS: Twenty-two methodologies are included in the review, grouped into biomechanical techniques, clinical tools applied to forensic settings, and cognitive-based lie detection techniques. Strengths and weaknesses of each methodology are presented, and future directions are discussed. CONCLUSIONS: Despite the variety of techniques that have been developed to identify malingering in forensic contexts, the present work highlights the current lack of rigorous methodologies for the assessment of WADs that take into account both the heterogeneous nature of the syndrome and the possibility of malingering. We conclude that it is pivotal to promote awareness about the presence of malingering in whiplash cases and highlight the need for novel, high-quality research in this field, with the potential to contribute to the development of standardised procedures for the evaluation of WADs and the detection of malingering.

Predicting Perceived Stress Related to the Covid-19 Outbreak through Stable Psychological Traits and Machine Learning Models.

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.