Le malattie croniche invisibili pongono una questione che va oltre la diagnosi e il trattamento: come viene riconosciuta una sofferenza che non sempre può essere osservata, misurata o verificata attraverso un esame? A partire da 12 interviste a pazienti, caregiver e studentesse e specializzande in medicina, e da una successiva survey che ha coinvolto 129 persone con malattia cronica, questo contributo osserva il rapporto tra invisibilità della malattia, ascolto e relazione di cura. Le narrazioni raccolte mostrano come il mancato riconoscimento del dolore possa diventare esso stesso una forma di sofferenza, incidendo sulla quotidianità, sull’identità, sulle relazioni e sulla fiducia nei professionisti sanitari. Al tempo stesso emergono esperienze in cui una parola, un gesto o la disponibilità ad ascoltare modificano profondamente la percezione della malattia. Il lavoro propone infine una riflessione nata dalla medicina narrativa e tradotta in un’esperienza installativa, Ti sento, pensata come spazio di ascolto, riconoscimento e condivisione.
Summary. The digital revolution, spearheaded by generative artificial intelligence (AI), is transforming healthcare working practice, patient behaviors and doctor-patient relationship. At this crossroads, public health frameworks must remain equitable and sustainable. This paper explores how AI, health literacy (HL) deficits, and Sex and Gender-Specific Medicine (SGSM) impact clinical relationship. Although AI promises enhanced efficiency, current models are trained on datasets heavily affected by bias, compromising diagnostic appropriateness for female patients and minorities. To safeguard equity, a focus on training is needed: citizens must develop appropriate HL and progressively digital HL while physicians must develop “algorithmic literacy” and resist delegating clinical listening to AI agents. In this context, SGSM emerges as an essential precision framework. By recognizing that communication is an active component of treatment and that neither doctor nor patient is a neutral operator, medicine can reclaim its humanistic core through targeted, lifelong education.
Background. Healthcare service use among people with Multiple Sclerosis (MS) and a migration background (pwMSMB) in Italy remains poorly characterized. Objective. In the framework of IMPACT-MS project to compare sociodemographic, clinical, and healthcare-utilization profiles of pwMSMB by country-of-origin income level, using real-world data of MS register. Methods. Retrospective analysis (2000-2025) of the Italian MS Registrer (RISM), including 3,404 adults with confirmed MS and available residence data. Countries of origin were classified as high-income or lower-middle-income (World Bank Atlas 2025). Mixed-effects logistic regression (random intercept for center) compared groups on sociodemographic, clinical, and healthcare-utilization variables. Results. 56% of pwMSMB originated from high-income countries, 44% from lower-middle-income countries. Lower-middle-income origin was associated with younger age (OR=0.93, p=0.004), lower likelihood of Southern Italy/Islands residence (OR=0.33, p<0.001), higher disability at first access (OR=1.16, p<0.001), and modestly greater diagnostic delay (OR=1.00, p=0.038). No significant differences emerged in treatment exposure or service-use frequency. Conclusions. Country-of-origin income was not associated with markedly different quantitative service access, but was linked to demographic, geographic, and clinical differences – particularly higher disability at intake – warranting further population-based research on unmet needs among pwMSMB. Key limitations include the lack of migration-status data, reliance on indirect proxies of service use that cannot capture socio-cultural barriers or care quality, register coverage limited to people already accessing MS centers, and the observational design, which precludes causal inference.
