Wanting Zu , Fei Li , Xiaoxuan Ma , Shiyun Zhang , Wenbo Nie , Lisheng Wang
{"title":"探索 2 型糖尿病成人患者抑郁、焦虑、糖尿病困扰及相关社会心理因素之间的相互联系:网络分析","authors":"Wanting Zu , Fei Li , Xiaoxuan Ma , Shiyun Zhang , Wenbo Nie , Lisheng Wang","doi":"10.1016/j.jcbs.2024.100843","DOIUrl":null,"url":null,"abstract":"<div><h3>Background and objective</h3><div>Anxiety, depression, and diabetes distress are three common psychological distresses among people with type 2 diabetes. Although previous research has explored factors associated with them, most studies have viewed these factors as independent constructs, overlooking the complex interactions between these factors, which can limit our understanding of psychological symptoms and associated factors from an integrated perspective. The purpose of this study was to explore the relationships between psychological distress outcomes and related psychological factors in people with diabetes from a network analysis perspective and further provide evidence for the selection of specific psychological intervention targets.</div></div><div><h3>Design and setting</h3><div>A cross-sectional study was conducted in person at diabetes centers of three tertiary hospitals in China.</div></div><div><h3>Participants</h3><div>481 adults with type 2 diabetes (62% male; mean age 51.91 ± 13.64 years; mean HbA1c 9.34 ± 2.23%) were recruited between December 2022 and April 2023.</div></div><div><h3>Methods</h3><div>Psychological distress outcomes and related factors analyzed included depression (PHQ-9), anxiety (GAD-7), diabetes distress (DDS), acceptance level (AADQ), cognitive fusion (CFQ), social support (PSSS), and self-efficacy (DMSES). Correlation analyses and network analyses were used to explore complex associations among these variables.</div></div><div><h3>Results</h3><div>The network included ten nodes, diabetes-related interpersonal distress, anxiety, and regimen-related distress were the most influential in the network. Significant relationships emerged in networks with five nodes, with both acceptance level and cognitive fusion associated with the general psychological distress and diabetes distress; social support demonstrated stable associations with all three psychological outcomes in each network.</div></div><div><h3>Conclusion</h3><div>After controlling for other factors, psychological flexibility and social support could still be significantly associated with psychological distress outcomes, indicating the potential to integrate them as transdiagnostic processes into psychological interventions for this population. However, the results of this study are based on the group level, and the dynamic networks of individuals need to be further explored in order to meet the needs of individuals in different contexts.</div></div>","PeriodicalId":47544,"journal":{"name":"Journal of Contextual Behavioral Science","volume":"34 ","pages":"Article 100843"},"PeriodicalIF":3.4000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring the interconnectedness of depression, anxiety, diabetes distress, and related psychosocial factors in adults with type 2 diabetes: A network analysis\",\"authors\":\"Wanting Zu , Fei Li , Xiaoxuan Ma , Shiyun Zhang , Wenbo Nie , Lisheng Wang\",\"doi\":\"10.1016/j.jcbs.2024.100843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background and objective</h3><div>Anxiety, depression, and diabetes distress are three common psychological distresses among people with type 2 diabetes. Although previous research has explored factors associated with them, most studies have viewed these factors as independent constructs, overlooking the complex interactions between these factors, which can limit our understanding of psychological symptoms and associated factors from an integrated perspective. The purpose of this study was to explore the relationships between psychological distress outcomes and related psychological factors in people with diabetes from a network analysis perspective and further provide evidence for the selection of specific psychological intervention targets.</div></div><div><h3>Design and setting</h3><div>A cross-sectional study was conducted in person at diabetes centers of three tertiary hospitals in China.</div></div><div><h3>Participants</h3><div>481 adults with type 2 diabetes (62% male; mean age 51.91 ± 13.64 years; mean HbA1c 9.34 ± 2.23%) were recruited between December 2022 and April 2023.</div></div><div><h3>Methods</h3><div>Psychological distress outcomes and related factors analyzed included depression (PHQ-9), anxiety (GAD-7), diabetes distress (DDS), acceptance level (AADQ), cognitive fusion (CFQ), social support (PSSS), and self-efficacy (DMSES). Correlation analyses and network analyses were used to explore complex associations among these variables.</div></div><div><h3>Results</h3><div>The network included ten nodes, diabetes-related interpersonal distress, anxiety, and regimen-related distress were the most influential in the network. Significant relationships emerged in networks with five nodes, with both acceptance level and cognitive fusion associated with the general psychological distress and diabetes distress; social support demonstrated stable associations with all three psychological outcomes in each network.</div></div><div><h3>Conclusion</h3><div>After controlling for other factors, psychological flexibility and social support could still be significantly associated with psychological distress outcomes, indicating the potential to integrate them as transdiagnostic processes into psychological interventions for this population. However, the results of this study are based on the group level, and the dynamic networks of individuals need to be further explored in order to meet the needs of individuals in different contexts.</div></div>\",\"PeriodicalId\":47544,\"journal\":{\"name\":\"Journal of Contextual Behavioral Science\",\"volume\":\"34 \",\"pages\":\"Article 100843\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Contextual Behavioral Science\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2212144724001236\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, CLINICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Contextual Behavioral Science","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212144724001236","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}
Exploring the interconnectedness of depression, anxiety, diabetes distress, and related psychosocial factors in adults with type 2 diabetes: A network analysis
Background and objective
Anxiety, depression, and diabetes distress are three common psychological distresses among people with type 2 diabetes. Although previous research has explored factors associated with them, most studies have viewed these factors as independent constructs, overlooking the complex interactions between these factors, which can limit our understanding of psychological symptoms and associated factors from an integrated perspective. The purpose of this study was to explore the relationships between psychological distress outcomes and related psychological factors in people with diabetes from a network analysis perspective and further provide evidence for the selection of specific psychological intervention targets.
Design and setting
A cross-sectional study was conducted in person at diabetes centers of three tertiary hospitals in China.
Participants
481 adults with type 2 diabetes (62% male; mean age 51.91 ± 13.64 years; mean HbA1c 9.34 ± 2.23%) were recruited between December 2022 and April 2023.
Methods
Psychological distress outcomes and related factors analyzed included depression (PHQ-9), anxiety (GAD-7), diabetes distress (DDS), acceptance level (AADQ), cognitive fusion (CFQ), social support (PSSS), and self-efficacy (DMSES). Correlation analyses and network analyses were used to explore complex associations among these variables.
Results
The network included ten nodes, diabetes-related interpersonal distress, anxiety, and regimen-related distress were the most influential in the network. Significant relationships emerged in networks with five nodes, with both acceptance level and cognitive fusion associated with the general psychological distress and diabetes distress; social support demonstrated stable associations with all three psychological outcomes in each network.
Conclusion
After controlling for other factors, psychological flexibility and social support could still be significantly associated with psychological distress outcomes, indicating the potential to integrate them as transdiagnostic processes into psychological interventions for this population. However, the results of this study are based on the group level, and the dynamic networks of individuals need to be further explored in order to meet the needs of individuals in different contexts.
期刊介绍:
The Journal of Contextual Behavioral Science is the official journal of the Association for Contextual Behavioral Science (ACBS).
Contextual Behavioral Science is a systematic and pragmatic approach to the understanding of behavior, the solution of human problems, and the promotion of human growth and development. Contextual Behavioral Science uses functional principles and theories to analyze and modify action embedded in its historical and situational context. The goal is to predict and influence behavior, with precision, scope, and depth, across all behavioral domains and all levels of analysis, so as to help create a behavioral science that is more adequate to the challenge of the human condition.