Over the past decade, the use of artificial intelligence (AI) has radically transformed the understanding and clinical approach to diabetes. Advances such as closed-loop monitoring, continuous glucose monitoring, and digital platforms have enabled a shift from reactive medicine to ultra-personalized care. The integration of psychological and AI techniques opens up promising avenues for predicting adherence, modulating emotions, and reducing acute and chronic complications.
This Research Topic seeks to bring together cutting-edge research exploring the synergies between AI and psychology in diabetes: from predictive models of glycemic imbalance to the impact of apps, chatbots, and e-health on motivation, distress reduction, and quality of life optimization. The presentation and discussion of theoretical frameworks, empirical studies, clinical applications, and technological developments in both types of diabetes is encouraged, fostering interdisciplinarity.
This Research Topic welcomes original research studies, reviews, technological developments, and clinical cases that address specific questions such as:
• AI algorithms for predicting acute and chronic complications in type 1 and 2 diabetes. • Hybrid models: personalizing therapeutic adjustment by combining AI and behavioral/emotional variables. • AI-based digital interventions (apps, chatbots, e-health platforms) for adherence and self-care. • Impact of distress and psychosocial variables on the effectiveness of automated systems (artificial pancreas, smart pens, etc.). • AI-powered digital phenotyping and emotional monitoring studies. • AI-powered psychological risk assessment and prediction (e.g., mood disorders, eating disorders). • AI applications in patient education and shared decision-making. • Early detection of type 2 diabetes using AI combined with psychosocial factors. • New ethical challenges in the integration of AI and clinical psychology in diabetes. • Multicultural and global perspectives on the application of AI and psychological approaches. • Integrating AI into clinical decision-making: exploring how psychological and behavioral data can complement biomedical data for a more holistic approach to diabetes management. • Evaluation frameworks for AI-psychology integration: developing metrics to assess the usability, engagement, trust, and emotional impact of AI-based psychological tools.
The collection is open to all types of articles accepted by the journal and encourages collaboration among researchers, technologists, clinicians, and psychologists. Priority is given to papers that combine psychometric variables with artificial intelligence and present results transferable to clinical practice.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Classification
Clinical Trial
Community Case Study
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Classification
Clinical Trial
Community Case Study
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Policy and Practice Reviews
Policy Brief
Review
Study Protocol
Systematic Review
Technology and Code
Keywords: Artificial intelligence, Machine learning, Psychology, Personalization, Glycemic Control, Behavioral intervention, Digital Health, eHealth, Type 1 diabetes, Type 2 diabetes
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.