Evidence map›Paper›PMID 42625233›Full record

ArticleBMC psychology2026

Latent profiles of diabetes distress and determinants in type 2 diabetes patients.

Siyu Li, Pengyue Zheng, Jie Gao, Lianheng Xia, Min Liu, Yuhuan Zhang, Zhixin Di

Abstract read
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Article in BMC psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Siyu Li *Department of Orthopedics (Wards 9 and 10), The Second Affiliated Hospital of Harbin Medical University, Harbin, 150000, Heilsongjiang, China.
Pengyue Zheng *Department of Peripheral Vascular Diseases, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, 150040, China.
Jie GaoDepartment of Peripheral Vascular Surgery, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, 150040, Heilongjiang, China.
Lianheng XiaDepartment of Peripheral Vascular Diseases, The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, 150040, Heilongjiang, China.
Min LiuDepartment of Respiratory Medicine I, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150000, Heilongjiang, China.
Yuhuan ZhangStudent Affairs Office, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150000, Heilongjiang, China. 2802262584@qq.com.
Zhixin DiDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150000, Heilongjiang, China. 44725660@qq.com.

Funding

2023 China Youth Science Fund Project 8230153519the 2025 Harbin Medical University Key Project for Comprehensive Reform and Quality Enhancement in Ideological and Political Work HYDSZZDXM011the Heilongjiang Higher Education Association Special Project on the Third Plenary Session of the 20th CPC Central Committee and the 2024 National Education Conference 24GJZXE003
6 · The paper itself

Abstract

backgroundType 2 diabetes is a prevalent chronic condition that may pose substantial psychological challenges for patients, particularly in managing long-term glycemic control and its associated complications. Although previous research has examined diabetes distress among individuals with diabetes, studies investigating its latent profiles and associated factors remain scarce. Therefore, this study aimed to identify distinct latent profiles of diabetes distress among patients with type 2 diabetes and explore the factors associated with profile membership.

methodsA convenience sampling method was employed to recruit 155 patients with T2D from a tertiary hospital in Heilongjiang Province. Participants completed a general information questionnaire, the Diabetes Distress Scale, and the Self-Regulation Fatigue Scale (SRFS). Latent profile analysis (LPA) was used to categorize diabetes distress, and unordered multinomial logistic regression was applied to identify factors associated with each profile.

resultsDiabetes distress was categorized into three latent profiles: low (38.1%), moderate (17.4%), and high (44.5%). The three-class model was identified as the optimal solution based on model fit indices and classification quality, with high entropy (0.905) indicating good separation between profiles. Factors significantly associated with higher distress included being female, older age, more comorbidities, longer duration of diabetes, higher HbA1c levels, and greater self-regulation fatigue (all P < 0.05).

conclusionLPA identified three distinct profiles of diabetes distress among patients with type 2 diabetes. Targeted interventions for patients with moderate and high levels of distress, focusing on alleviating psychological burden and self-regulation fatigue, may help improve disease management and overall quality of life.

Indexed as

Diabetes Mellitus, Type 2Psychological DistressStress, PsychologicalAdultAgedChinaFatigueFemaleHumansLatent Class AnalysisMaleMiddle AgedDeterminantsDiabetes distressLatent profile analysisSelf-Regulation fatigueType 2 diabetes

Identifiers

PMID42625233
PMCPMC13495488

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.