Digital medication adherence technologies (MATech): a qualitative study of type 2 diabetes patients’ expectations and needs

Introduction Digital Medication Adherence Technologies (MATech) have the potential to improve medication adherence and clinical outcomes, but solutions are commonly evaluated with an emphasis on product-specific designs rather than patient usefulness. Understanding patient needs, particularly regarding features supporting medication adherence, is essential for designing effective solutions. Due to the high levels of self-management required for patients with type 2 diabetes, it is relevant to explore MATech needs in this patient group. Purpose To explore Type 2 Diabetes patients’ needs and expectations of using various MATech features. Methods Qualitative semi-structured interviews were conducted during 2023–2025 with 13 patients with Type 2 Diabetes in Sweden. Participants were recruited via patient organizations, social media, and primary healthcare. Purposive sampling, informed by pre-interview questionnaires, was used to ensure diversity in age, sex, education, country of birth, self-rated medication difficulties and technology proficiency. Interviews were analyzed inductively with qualitative content analysis. Results Three main categories were identified: Control and Safety, Added Value and Motivation, and Impact on the patient-provider interaction. Most interviewed patients had high technology proficiency, while self-rated medication difficulties varied. Patients highlighted that MATech features such as medication reminders, and self-monitoring of medication intake and outcomes, could promote a sense of security and control. Perceived usefulness and motivation to use the technology depended on the technology´s ability to address multiple aspects of treatment needs, personalization capacity and functionality to support new insights. While MATech could improve the patient-provider interaction, participants emphasized the importance of in-person follow-up when necessary. Conclusion MATech features have the potential to empower patients and improve the healthcare interactions, but patients expect more advanced, responsive and personalized functionalities than those available.