Huan Chen, Xiaohui Dong, Shi Chen, Xinyu Chen, Xianying Lu, Jiali He, Wenting Ji, Chaoming Hou, Dingxi Bai, Jing Gao
{"title":"2型糖尿病患者抑郁症状、社会支持和糖尿病困扰的网络分析:一项横断面研究","authors":"Huan Chen, Xiaohui Dong, Shi Chen, Xinyu Chen, Xianying Lu, Jiali He, Wenting Ji, Chaoming Hou, Dingxi Bai, Jing Gao","doi":"10.2147/PPA.S521735","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Diabetes distress (DD) is common in patients with type 2 diabetes (T2D). Little is known about the complex intercorrelations between different components of depressive symptoms (DS), social support (SS), and DD. This study aimed to identify the central components of DD and to examine the interconnectedness between DS, SS, and DD components.</p><p><strong>Methods: </strong>A cross-sectional survey design was employed in this study. We investigated 886 patients with T2D from two diabetes centers. The Chinese versions of the Diabetes Distress Scale (DDS), Patient Health Questionnaire (PHQ-9), and Social Support Rating Scale (SSRS) were used. GGM was employed to estimate the network model. We identified central and bridge symptoms based on betweenness, closeness, and node strength centrality. The stability and accuracy of the network were examined using the case-dropping and bootstrapped procedures.</p><p><strong>Results: </strong>Three items (\"Do not have doctor I can see regularly\", \"Doctor does not give clear directions\", and \"Doctor does not know about diabetes\") in the network of DD exhibited the highest strength centrality. The DD-DS-SS network exhibited four strong positive bridges and two strong negative bridges. The stability and accuracy tests demonstrated that the two networks were robust.</p><p><strong>Conclusion: </strong>Physician-related distress may contribute to the development and maintenance of DD. Fatigue, diet, and social interaction summarize the complex link between DD and DS. Furthermore, subjective support and support utilization of patients with T2D were closely related to the DD. These provided more targeted theoretical guidance and a scientific basis for psychological counseling and intervention in patients with T2D.</p>","PeriodicalId":19972,"journal":{"name":"Patient preference and adherence","volume":"19 ","pages":"1951-1964"},"PeriodicalIF":2.0000,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12257158/pdf/","citationCount":"0","resultStr":"{\"title\":\"Network Analysis of Depressive Symptoms, Social Support, and Diabetes Distress Among Patients with Type 2 Diabetes: A Cross-Sectional Study.\",\"authors\":\"Huan Chen, Xiaohui Dong, Shi Chen, Xinyu Chen, Xianying Lu, Jiali He, Wenting Ji, Chaoming Hou, Dingxi Bai, Jing Gao\",\"doi\":\"10.2147/PPA.S521735\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Diabetes distress (DD) is common in patients with type 2 diabetes (T2D). Little is known about the complex intercorrelations between different components of depressive symptoms (DS), social support (SS), and DD. This study aimed to identify the central components of DD and to examine the interconnectedness between DS, SS, and DD components.</p><p><strong>Methods: </strong>A cross-sectional survey design was employed in this study. We investigated 886 patients with T2D from two diabetes centers. The Chinese versions of the Diabetes Distress Scale (DDS), Patient Health Questionnaire (PHQ-9), and Social Support Rating Scale (SSRS) were used. GGM was employed to estimate the network model. We identified central and bridge symptoms based on betweenness, closeness, and node strength centrality. The stability and accuracy of the network were examined using the case-dropping and bootstrapped procedures.</p><p><strong>Results: </strong>Three items (\\\"Do not have doctor I can see regularly\\\", \\\"Doctor does not give clear directions\\\", and \\\"Doctor does not know about diabetes\\\") in the network of DD exhibited the highest strength centrality. The DD-DS-SS network exhibited four strong positive bridges and two strong negative bridges. The stability and accuracy tests demonstrated that the two networks were robust.</p><p><strong>Conclusion: </strong>Physician-related distress may contribute to the development and maintenance of DD. Fatigue, diet, and social interaction summarize the complex link between DD and DS. Furthermore, subjective support and support utilization of patients with T2D were closely related to the DD. These provided more targeted theoretical guidance and a scientific basis for psychological counseling and intervention in patients with T2D.</p>\",\"PeriodicalId\":19972,\"journal\":{\"name\":\"Patient preference and adherence\",\"volume\":\"19 \",\"pages\":\"1951-1964\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12257158/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Patient preference and adherence\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/PPA.S521735\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Patient preference and adherence","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/PPA.S521735","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Network Analysis of Depressive Symptoms, Social Support, and Diabetes Distress Among Patients with Type 2 Diabetes: A Cross-Sectional Study.
Background: Diabetes distress (DD) is common in patients with type 2 diabetes (T2D). Little is known about the complex intercorrelations between different components of depressive symptoms (DS), social support (SS), and DD. This study aimed to identify the central components of DD and to examine the interconnectedness between DS, SS, and DD components.
Methods: A cross-sectional survey design was employed in this study. We investigated 886 patients with T2D from two diabetes centers. The Chinese versions of the Diabetes Distress Scale (DDS), Patient Health Questionnaire (PHQ-9), and Social Support Rating Scale (SSRS) were used. GGM was employed to estimate the network model. We identified central and bridge symptoms based on betweenness, closeness, and node strength centrality. The stability and accuracy of the network were examined using the case-dropping and bootstrapped procedures.
Results: Three items ("Do not have doctor I can see regularly", "Doctor does not give clear directions", and "Doctor does not know about diabetes") in the network of DD exhibited the highest strength centrality. The DD-DS-SS network exhibited four strong positive bridges and two strong negative bridges. The stability and accuracy tests demonstrated that the two networks were robust.
Conclusion: Physician-related distress may contribute to the development and maintenance of DD. Fatigue, diet, and social interaction summarize the complex link between DD and DS. Furthermore, subjective support and support utilization of patients with T2D were closely related to the DD. These provided more targeted theoretical guidance and a scientific basis for psychological counseling and intervention in patients with T2D.
期刊介绍:
Patient Preference and Adherence is an international, peer reviewed, open access journal that focuses on the growing importance of patient preference and adherence throughout the therapeutic continuum. The journal is characterized by the rapid reporting of reviews, original research, modeling and clinical studies across all therapeutic areas. Patient satisfaction, acceptability, quality of life, compliance, persistence and their role in developing new therapeutic modalities and compounds to optimize clinical outcomes for existing disease states are major areas of interest for the journal.
As of 1st April 2019, Patient Preference and Adherence will no longer consider meta-analyses for publication.