The global rise in cancer incidence and mortality represents a major challenge for modern healthcare. Although current screening programs rely mainly on histological or immunological biomarkers, cancer is a multifactorial disease in which biological, psychological, and behavioural determinants interact. Psychological dimensions such as stress, anxiety, and depression may influence vulnerability and disease evolution through neuro-endocrine, immune, and behavioural pathways, especially by affecting adherence to therapeutic recommendations. However, these dimensions remain underexplored in current screening workflows. This review synthesizes current evidence on the integration of biological markers (tumor and inflammatory biomarkers), psychometric profiling (stress, depression, anxiety, personality traits), and behavioural digital phenotyping (facial micro-expressions, vocal tone, gait/posture metrics) for potential early cancer risk evaluation. We examine recent advances in computational sciences and artificial intelligence that could enable multimodal signal harmonization, structured representation, and hybrid data fusion models. We discuss how structured computational information management may improve interpretability and may support future AI-assisted screening paradigms. Finally, we highlight the relevance of digital health infrastructure and telemedical platforms in strengthening accessibility, continuity of monitoring, and population-level screening coverage. Further empirical research is required to determine the true predictive contribution of psychological and behavioural modalities beyond established biological markers.

Background: Psychological distress has been frequently reported in individual autoimmune diseases, but evidence regarding shared psychological characteristics across heterogeneous autoimmune conditions remains limited. Objective: This study compared stress vulnerability, exposure to major life events, state and trait anxiety, and Type A behavioral characteristics between adults with autoimmune diseases and controls. Methods: This cross-sectional case–control study included 389 adults: 204 patients with autoimmune diseases and 185 controls. Participants completed the Stress Vulnerability Scale, Holmes–Rahe Life Stress Inventory, State–Trait Anxiety Inventory, and Jenkins Activity Survey. Between-group differences, effect sizes, and correlations among psychometric variables were examined. Results: Patients with autoimmune diseases had significantly higher stress vulnerability scores (Cohen’s d = 0.39) and Holmes–Rahe life-event burden (d = 0.54) than controls. State anxiety (d = 0.52) and trait anxiety (d = 0.68) were also higher (all p < 0.001). Type A behavioral characteristics did not differ significantly between groups. State and trait anxiety showed the strongest correlation (r = 0.755, p < 0.001). Disease duration was positively associated with Holmes–Rahe scores but not with stress vulnerability or anxiety. Conclusions: Adults with autoimmune diseases showed a higher psychological burden across several complementary psychometric dimensions. These findings support consideration of psychological screening within multidisciplinary autoimmune disease care. Longitudinal and disease-specific studies integrating biological, psychological, and social factors are required to clarify temporal and potentially bidirectional relationships.