Diabetes self-management in the digital health era: a concept analysis using natural language processing

Diabetes self-management is increasingly shaped by digital health technologies, yet existing conceptual definitions do not fully reflect this evolving landscape. This study aimed to refine the concept of diabetes self-management in the digital health era by applying Rodgers’ evolutionary method integrated with Natural Language Processing (NLP). Ninety-seven studies were analyzed through a dual-phase design combining manual review and computational clustering of sentence-level embeddings.

The analysis identified core attributes, including daily behavioral routines, cognitive and psychological processes, multilevel social support, personalization, digital health integration, and dynamic patient–provider relationships. Antecedents encompassed physical and psychological demands, emotional readiness, access to education and support, resource and technology availability, and health and digital literacy. Consequences included improved clinical outcomes, enhanced quality of life, empowerment, and reduced healthcare burden.

Integrating manual and NLP-based approaches strengthened conceptual clarity and provided a contemporary framework for understanding diabetes self-management within digitally enabled patient-centered care. These authors contributed equally: Ryan J. Duke University School of Nursing, Durham, NC, USA Donghwan Lee, Aderonke Kareem, Ryan J.

Shaw & Kais Gadhoumi Gyeongnam Center for Infectious Disease Control and Prevention, Changwon-si, South Korea University Libraries, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA Duke University Medical Center Library & Archives, Durham, NC, USA Duke University Health System, Durham, NC, USA Division of Clinical Health Systems and Analytics, Duke University School of Nursing, Durham, NC, USA The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Lee, D., Kareem, A., Shin, S. et al. Diabetes self-management in the digital health era: a concept analysis using natural language processing. npj Digit. Med. (2026). https://doi.org/10.1038/s41746-026-03300-2 DOI: https://doi.org/10.1038/s41746-026-03300-2