More than 422 million people worldwide are affected by diabetes, with a significant proportion living in low- and middle-income countries, particularly in rural areas with limited resources. Diabetic persons often face complications such as limited joint mobility syndrome or diabetic foot, which are more prevalent among older people. Despite the recognized role of technology in managing diabetes-related factors, evidence on its potential to enhance mobility remains limited. This study explores the lived experiences of older diabetic people (N = 1822, aged 65 years and older) with mobility challenges in urban and rural Spain, using data from the “Encuesta de Discapacidad, Autonomía personal y Situaciones de Dependencia, EDAD” (2020). Results revealed correlations between mobility challenges and health deterioration, influenced by socio-spatial factors such as urban or rural living. Urban residents reported challenges with “changing posture,” “walking/moving at home,” and “traveling by transport,” while rural residents noted adverse technology perceptions related to difficulties in the case of “driving vehicles” and “manipulating objects.” To address these complexities, a quantum circuit framework, including the quantum approximate optimization algorithm, variational quantum algorithm, and quantum support vector machine, is proposed to model multidimensional relationships among mobility, health perception, technology perception, and socio-spatial factors. This approach leverages quantum computing to uncover nonlinear patterns, offering insights for personalized technology design. These findings guide the customization of technology to address chronic condition challenges within socio-spatial constraints, with further research needed to incorporate additional sociodemographic variables and a gender perspective.