Rethinking Psychosocial Research in the Era of Diabetes Technology
Dominic Ehrmann, Eloise Litterbach, Sonya Deschenes, Rita Forde, Norbert Hermanns, Maaike Horsselenberg, Mandy Jansen, Amy McInerney, Eimear Morrissey, Andreas Schmitt, Uffe Søholm, Giesje Nefs
From narratives to numbers and back: Assessing the psychosocial aspects of diabetes in the era of high technology with emerging qualitative and quantitative methodologies. Diabet Med. 2026 Jan 2:e70206.
Rapid advances in diabetes technology—such as continuous glucose monitoring, automated insulin delivery, and digital health tools—have transformed how biomedical outcomes are measured and managed. However, methods used to assess the psychosocial aspects of living with diabetes have evolved more slowly. Traditional approaches, often based on retrospective questionnaires and group averages, may not fully capture the dynamic and individual nature of daily diabetes experiences. This invited review explores how emerging research methods can better reflect real-life psychosocial experiences and support the development of more personalised diabetes care.
The authors present a narrative review of innovative qualitative and quantitative methodologies drawn from diabetes research and related disciplines. The paper discusses limitations of conventional psychosocial assessment and highlights new approaches that allow researchers to measure experiences in real time, understand within-person variation, and integrate psychological data with modern diabetes technologies.
Key findings:
- Retrospective questionnaires often fail to capture day-to-day fluctuations in wellbeing and diabetes-related experiences.
- Qualitative approaches such as storytelling, photovoice, and culturally sensitive research methods help uncover diverse lived experiences.
- Ecological momentary assessment enables real-time monitoring of mood, distress, and behaviour in everyday contexts.
- Combining psychosocial data with CGM and wearable sensor data allows analysis of interactions between glucose levels and psychological experiences.
- Intensive longitudinal and N-of-1 analyses support more personalised insights and intervention development.
- Emerging approaches such as digital phenotyping and artificial intelligence may enable future precision mental health care.
The review argues that psychosocial diabetes research should evolve alongside technological innovation. Integrating qualitative narratives with high-frequency quantitative data may help explain why psychosocial outcomes do not always improve despite advances in diabetes technology. These approaches could enable more personalised psychosocial support by identifying when and for whom interventions are most needed, moving toward a precision mental health framework within diabetes care.
Concluding, the authors state
"Ultimately, these emerging qualitative and quantitative methodologies can progress the field of psychosocial diabetes research, moving beyond a group-based ‘one-size-fits-all’ approach towards a precision mental health approach." -
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