Background: Public organizations in healthcare are progressively adopting digital tools to disseminate information regarding the benefits of screening. Nevertheless, no research has hitherto been conducted to investigate the link between the website-based health communications and cancer screening uptake. This study addresses this gap by assessing whether health communications conveyed via the websites of local health organizations improve adherence to breast and cervical cancer screening. Methods: We performed thematic content analysis of 97 websites belonging to Italian health organizations based on the OSEC-p model. This latter was developed to measure the compliance of prevention-oriented health communication with the effectiveness requirements indicated in the model. Next, correlation and regression analyses were performed to examine the relationship between the average regional OSEC-p scores and the regional breast and cervical cancer screening adherence rates reported by the National Centre for Screening Monitoring in 2022. Results: The findings show that the prevention-oriented health communication via health organizations’ websites can explain the 45% of the variance in female cancer (breast and cervical) screening uptake. Patient engagement tools and information on preventive cancer initiatives are key web-based communication elements that enhance cancer screening adherence. Conclusion: This exploratory study is one of the first to highlight the importance of digital health communications for improving cancer screening and public health. It offers insights both for national health policy-makers to optimize health economics through screening campaigns and health organizations managers to enhance the compliance of health communication on websites with the effectiveness requirements defined in the OSEC-p model.

Background: While region-based models have informed pain neuroscience, chronic pain is now increasingly conceptualized as a network disorder. This narrative review aimed to critically examine the conceptual evolution of chronic pain models from region-based representations toward large-scale functional network frameworks across adult and pediatric populations while exploring how emerging artificial intelligence (AI)-driven approaches may support future precision pain medicine. Methods: A structured literature search was performed in PubMed, Scopus, and Web of Science, focusing on the scientific output addressing adult and pediatric chronic pain, pain-related neuroplasticity, functional network alterations, neuromodulation, and AI-based applications in pain medicine. Results: The reviewed literature supports a progressive conceptual shift from region-based representations of pain toward network-oriented models involving dysfunctional interactions among the salience, default mode, central executive, and sensorimotor networks. Although emerging evidence suggests developmental network alterations in pediatric chronic pain, current conclusions remain limited by the relative scarcity of longitudinal neuroimaging studies. Emerging AI applications demonstrate promising potential for objective pain assessment, trajectory prediction, and personalized therapeutic decision-making. Conclusions: The transition from the pain matrix to functional network models represents one of the most important conceptual advances in contemporary pain neuroscience. A network-based perspective may accelerate AI-enabled pain biomarkers and individualized interventions.