Background: Interpreting health information and acquiring health knowledge have become more important with the accumulation of scientific medical knowledge and ideals of patient autonomy. Health literacy and its tremendous success as a concept can be considered an admission that not all is well in the distribution of health knowledge. The internet makes health information much more easily accessible than ever, but it introduces its own problems, of which health disinformation is a major one. Objective: The objective of this study was to determine whether objective and subjective health literacy are independent concepts and to test which of the two was associated more strongly with accurate judgments of the quality of a medical website and with behavioral intentions beneficial to health. Methods: A survey on depression and its treatments was conducted online (n=362). The Newest Vital Sign was employed to measure objective, performance-based health literacy, and the eHealth Literacy Scale was used to measure subjective, perception-based health literacy. Correlations, comparisons of means, linear and binary logistic regression, and mediation models were used to determine the associations. Results: Objective and subjective health literacy were weakly associated with one another (r=0.06, P=.24). High objective health literacy levels were associated with an inclination to behave in ways that are beneficial to one’s own or others’ health (Exp[B]=2.068, P=.004) and an ability to recognize low-quality online sources of health information (β=–.4698, P=.005). The recognition also improved participants’ choice of treatment (β=–.3345, P<.001). Objective health literacy helped people to recognize misinformation on health websites and improved their judgment on their treatment for depression. Conclusions: Self-reported, perception-based health literacy should be treated as a separate concept from objective, performance-based health literacy. Only objective health literacy appears to have the potential to prevent people from becoming victims of health disinformation.

Background: The pervasiveness of smartphones has raised concerns about an increase in the prevalence of problematic smartphone use (PSU), which depends on a set of psychological and behavioral risk factors. Previous research has yielded mixed results on factors predicting PSU, including social anxiety and trust. In particular, the role of trust remained largely unexplored. In the present study, we aimed to investigate the relationship between social anxiety and PSU, via the mediating role of time spent on the phone, and to explore the moderating role of dispositional trust toward others, by using a moderated mediation model with PSU as the outcome. Methods: A total of 240 young adults (M_age = 23.33, SD = 3.90, 50% male) answered an online questionnaire, which included the 12-item Social Anxiety Scale, a question on the daily duration of smartphone use, a single-item measure of dispositional trust, and the 10-item Smartphone Addiction Scale Short Version. Gender and occupational status were included as covariates. Results: Social anxiety was significantly and positively related to PSU; however, smartphone use did not mediate this relationship. Although the relationship between smartphone use and PSU was significant and positive, the link between social anxiety and smartphone use was not. Dispositional trust moderated and strengthened the direct relationships between social anxiety and PSU as well as smartphone use and PSU. Conclusions. Heavy smartphone users as well as socially anxious individuals, with the tendency of trusting others, are more at risk of PSU, which can be explained by their preference and search for online connections.

In this paper, a computational approach is proposed and put into practice to assess the capability of children having had diagnosed Autism Spectrum Disorders (ASD) to produce facial expressions. The proposed approach is based on computer vision components working on sequence of images acquired by an off-the-shelf camera in unconstrained conditions. Action unit intensities are estimated by analyzing local appearance and then both temporal and geometrical relationships, learned by Convolutional Neural Networks, are exploited to regularize gathered estimates. To cope with stereotyped movements and to highlight even subtle voluntary movements of facial muscles, a personalized and contextual statistical modeling of non-emotional face is formulated and used as a reference. Experimental results demonstrate how the proposed pipeline can improve the analysis of facial expressions produced by ASD children. A comparison of system’s outputs with the evaluations performed by psychologists, on the same group of ASD children, makes evident how the performed quantitative analysis of children’s abilities helps to go beyond the traditional qualitative ASD assessment/diagnosis protocols, whose outcomes are affected by human limitations in observing and understanding multi-cues behaviors such as facial expressions.

The present study provides a systematic review of level 1 and level 2 screening tools for the early detection of autism under 24 months of age and an evaluation of the psychometric and measurement properties of their studies. Methods: Seven databases (e.g., Scopus, EBSCOhost Research Database) were screened and experts in the autism spectrum disorders (ASD) field were questioned; Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) guidelines and Consensus-based Standard for the selection of health Measurement INstruments (COSMIN) checklist were applied. Results: the study included 52 papers and 16 measures; most of them were questionnaires, and the Modified-CHecklist for Autism in Toddler (M-CHAT) was the most extensively tested. The measures’ strengths (analytical evaluation of methodological quality according to COSMIN) and limitations (in term of Negative Predictive Value, Positive Predictive Value, sensitivity, and specificity) were described; the quality of the studies, assessed with the application of the COSMIN checklist, highlighted the necessity of further validation studies for all the measures. According to COSMIN results, the M-CHAT, First Years Inventory (FYI), and Quantitative-CHecklist for Autism in Toddler (Q-CHAT) seem to be promising measures that may be applied systematically by health professionals in the future.

E-cadherin (CDH1 gene) germline mutations are associated with the development of diffuse gastric cancer in the context of the so-called hereditary diffuse gastric syndrome, and with an inherited predisposition of lobular breast carcinoma. In 2019, the international gastric cancer linkage consortium revised the clinical criteria and established guidelines for the genetic screening of CDH1 germline syndromes. Nevertheless, the introduction of multigene panel testing in clinical practice has led to an increased identification of E-cadherin mutations in individuals without a positive family history of gastric or breast cancers. This observation motivated us to review and present a novel multidisciplinary clinical approach (nutritional, surgical, and image screening) for single subjects who present germline CDH1 mutations but do not fulfil the classic clinical criteria, namely those identified as—(1) incidental finding and (2) individuals with lobular breast cancer without family history of gastric cancer (GC).