Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic management is limited by great uncertainty, for both health systems and citizens. Facing this information gap requires a paradigm shift from traditional approaches to healthcare to the participatory model of improving health. This work describes the design and function of the Doing Risk sElf-assessment and Social health Support for COVID (Dress-COV) system. It aims to establish a lasting link between the user and the tool; thus, enabling modeling of the data to assess individual risk of infection, or developing complications, to improve the individual’s self-empowerment. The system uses bot technology of the Telegram application. The risk assessment includes the collection of user responses and the modeling of data by machine learning models, with increasing appropriateness based on the number of users who join the system. The main results reflect: (a) the individual’s compliance with the tool; (b) the security and versatility of the architecture; (c) support and promotion of self-management of behavior to accommodate surveillance system delays; (d) the potential to support territorial health providers, e.g., the daily efforts of general practitioners (during this pandemic, as well as in their routine practices). These results are unique to Dress-COV and distinguish our system from classical surveillance applications.

Low back pain (LBP) carries a high risk of chronicization and disability, greatly impacting the overall demand for care and costs, and its treatment is at risk of scarce adherence. This work introduces a new scenario based on the use of a mobile health tool, the Dress-KINESIS, to support the traditional rehabilitation approach. The tool proposes targeted self-manageable exercise plans for improving pain and disability, but it also monitors their efficacy. Since LBP prevention is the key strategy, the tool also collects real-patient syndromic information, shares valid educational messages and fosters self-determined motivation to exercise. Our analysis is based on a comparison of the performance of the traditional rehabilitation process for non-specific LBP patients and some different scenarios, designed by including the Dress-KINESIS’s support in the original process. The results of the simulations show that the integrated approach leads to a better capacity for taking on patients while maintaining the same physiotherapists’ effort and costs, and it decreases healthcare costs during the two years following LBP onset. These findings suggest that the healthcare system should shift the paradigm towards citizens’ participation and the digital support, with the aim of improving its efficiency and citizens’ quality of life.

Breast cancer (BC) has overtaken lung cancer as the most common cancer in the world and the projected incidence rates show a further increase. Early detection through population screening remains the cornerstone of BC control, but a progressive change from early diagnosis only-based to a personalized preventive and risk-reducing approach is widely debated. Risk-stratification models, which also include personal lifestyle risk factors, are under evaluation, although the documentation burden to gather population-based data is relevant and traditional data collection methods show some limitations. This paper provides the preliminary results from the analysis of clinical data provided by radiologists and lifestyle data collected using self-administered questionnaires from 5601 post-menopausal women. The weight of the combinations of women’s personal features and lifestyle habits on the BC risk were estimated by combining a model-driven and a data-driven approach to analysis. The weight of each factor on cancer occurrence was assessed using a logistic model. Additionally, communities of women sharing common features were identified and combined in risk profiles using social network analysis techniques. Our results suggest that preventive programs focused on increasing physical activity should be widely promoted, in particular among the oldest women. Additionally, current findings suggest that pregnancy, breast-feeding, salt limitation, and oral contraception use could have different effects on cancer risk, based on the overall woman’s risk profile. To overcome the limitations of our data, this work also introduces a mobile health tool, the Dress-PINK, designed to collect real patients’ data in an innovative way for improving women’s response rate, data accuracy, and completeness as well as the timeliness of data availability. Finally, the tool provides tailored prevention messages to promote critical consciousness, critical thinking, and increased health literacy among the general population.

The literature about the relationship between extreme BMI and at-risk behaviors is quite inconsistent, and few articles focus on the underweight male population. This study aimed to analyze BMI level and its association with risky behavior, such as psychoactive substances use, gaming, and gambling, in a representative sample of the male adolescent population. Psychosocial variables were considered to better describe the possible at-risk profiles. This study used data from the 2018 ESPAD^®Italia cross-sectional study, a survey using a self-administered anonymous questionnaire. For the purpose of the paper, males only were included in the analysis, with a total sample of 6938 students aged 15–19 years. Multinomial logistic regression showed that being overweight is positively associated with the gambler profile, the perception of a low financial family situation, and dissatisfaction with health conditions. Furthermore, being underweight was positively associated with gaming. Both extremes of BMI were associated with a frequent alcohol consumption and a sedentary lifestyle. This study provides important information regarding both extremes of BMI conditions, underling the presence of at-risk behavior and self-related perceptions with shared factors between underweight and overweight.

Background: Well-being encompasses physical, mental, social, and cultural aspects. Sleep quality and pathologies are among the objective conditions jeopardising it. Chronic insomnia, inflammatory-based diseases, and mood disorders often occur in a single cluster, and inflammation can negatively impact sleep, potentially harming well-being. Some evidence from specific clinical populations suggests that also some resolved past diseases could still have an impact on present sleep quality and well-being. The aim of the present study is to investigate, in the general population, whether and to what degree well-being and insomnia are associated with resolved pathologies. Methods: A cross-sectional survey (IPSAD^®) was carried out using anonymous postal questionnaires that investigated past and present general health, well-being, and insomnia. A total of 10,467 subjects answered the questionnaire. Results: Several classes of both current and resolved pathologies resulted in increased odds ratios for current insomnia (odds ratios = 1.90; 1.43, respectively) and impaired well-being (odds ratios = 1.75; 1.33, respectively), proportional to the number of the displayed pathologies. Notably, both current and resolved past psychiatric disorders were strongly associated with both current impaired well-being (odds ratios = 5.38; 1.70, respectively) and insomnia (odds ratios = 4.99; 2.15, respectively). Conclusions: To explain these associations, we suggest that systemic inflammation conveyed by several medical conditions disrupts homeostatic processes, with final effects on sleep quality and behaviour.

Background/Objectives: Early detection of breast cancer (BC) substantially improves outcomes, with a 5-year survival rate of 99% for early-stage disease. Risk-based screening, which tailors recommendations according to individual clinical, personal, and lifestyle factors, is a promising strategy to enhance early detection. However, previous studies have reported inconsistent evidence of association with BC risk for several modifiable lifestyle factors including premenopausal adiposity, sedentary behaviour, oral contraceptive use. To address these uncertainties, we investigated the association between clinical, personal, and modifiable lifestyle factors and BC risk in the Prevention, Imaging, Network, Knowledge (P.I.N.K.) project. P.I.N.K. generated real-world evidence by integrating clinical data with information collected through a structured questionnaire evaluating the associations between BC and clinical, personal, and lifestyle factors in 27,123 Italian women aged ≥ 40 years, who underwent integrated breast imaging diagnostics. Methods: Characteristics of women with and without BC were compared. Adjusted logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest models were applied to identify relevant predictors. Variables selected by at least two methods were included in a multivariate logistic regression model, with BC diagnosis as the outcome. Results: Accordingly with previous studies a consistent association was found for high breast density, late menopause, overweight, abdominal adiposity, cardiovascular-cerebrovascular and oncological comorbidities and smoking. Greater consumption of plant-based foods, lower intake of red and processed meat, and regular physical activity were associated with lower odds of BC as well. Conversely, an unexpected inverse association was assessed for menstrual irregularities, hyperlipidaemia, and oral contraceptive use. Conclusions: The integration of multiple sources of information both clinical and self-reported data collected directly from women adds to the growing evidence on the role of modifiable lifestyle factors in BC risk in supporting more targeted prevention strategies. Future prospective studies should further investigate the long-term effects of lifetime physical activity trajectories, different oral contraceptive formulations, and detailed reproductive history, including menstrual cycle characteristics and menopausal timing, to refine individualized BC risk prediction.