SYSTEMATIC REVIEW article
Front. Public Health
Sec. Public Mental Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1708967
This article is part of the Research TopicThe Role of Psychological Constructs in Chronic Disease Prevention and Management: A Public Health PerspectiveView all 3 articles
Patterns of Discussion on Neuroticism and Self-Management Behaviors in Type 2 Diabetes: A Scoping Review Using Machine Learning–Assisted Text Mining
Provisionally accepted
- Changchun University of Chinese Medicine, Changchun, China
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Background:Self-management behaviors, including diet control, medication adherence, blood glucose monitoring, and physical activity, are crucial for type 2 diabetes management. Neuroticism, a personality trait associated with anxiety and stress sensitivity, may significantly influence these behaviors. However, a comprehensive synthesis of evidence is lacking. Objective:This scoping review aims to systematically map and synthesize how neuroticism has been examined in relation to self-management behaviors among adults with type 2 diabetes, and to identify recurring thematic patterns and knowledge gaps through machine learning–assisted text mining. Methods :A scoping review was conducted in PubMed, Scopus, Web of Science, Embase, CINAHL, PsycINFO, and the Cochrane Library, covering the period from database inception to September 2025. The search strategy included keywords such as "neuroticism," "personality traits," "type 2 diabetes," "self-management," and "adherence." We used machine learning–assisted literature mining to summarize thematic patterns across included studies.The study selection process and workflow were conducted in accordance with the PRISMA-ScR guidelines. Results: Ten studies were included. Across the literature, neuroticism was most frequently discussed alongside blood glucose monitoring, followed by diet control, medication taking, and exercise. Psychological constructs such as anxiety, stress sensitivity, and social support were commonly co-mentioned within these discussions. Machine learning–assisted analyses highlighted recurring topics, concept clusters, and co-occurrence patterns that characterize the discourse on neuroticism and T2DM self-management. Conclusion:This scoping review characterizes how neuroticism is positioned within the discourse on T2DM self-management behaviors and delineates prominent thematic linkages and gaps. Machine learning–assisted text mining proved useful for organizing and visualizing dispersed evidence. Findings describe patterns in the literature rather than estimating causal effects, and can inform future hypothesis-driven studies and tailored clinical inquiry.
Keywords: neuroticism, type 2 diabetes mellitus, Self-management behaviors, Machinelearning, text mining
Received: 19 Sep 2025; Accepted: 16 Oct 2025.
Copyright: © 2025 Sun, Xie, Zhang, Hou, Wang, Wang, Xu and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dong Xie, 1062616340@qq.com
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