Sex differences in symptom network structure of depression, anxiety, and self-efficacy among people with diabetes: a network analysis

Front Public Health. 2024 Mar 1:12:1368752. doi: 10.3389/fpubh.2024.1368752. eCollection 2024.

Abstract

Aims: The present study aims to explore the relations between symptoms of depression and anxiety and self-efficacy among people with diabetes. At the same time, we also examined the sex difference between network structures.

Methods: This study recruited 413 participants with diabetes, and they completed Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire (PHQ-9), and the Self-efficacy for Diabetes (SED). Symptom network analysis and network comparison test were used to construct and compare the depression-anxiety symptom network models of the female and male groups. Finally, we conducted flow diagrams to explore the symptoms directly or indirectly related to self-efficacy.

Results: The strongest edges in the depression-anxiety symptom networks are the edge between "GAD3" (Excessive worry) and "GAD4" (Trouble relaxing) and the edge between "PHQ1" (Anhedonia) and "PHQ4" (Energy) in the female and male groups, respectively. Most of the symptoms with the highest EI and bridge EI are related to worry and nervousness. Additionally, in the flow diagram of the female group, "PHQ6" (Guilt) has a high negative association with self-efficacy.

Conclusion: Females with diabetes are more vulnerable to depression and anxiety. Interventions targeting key symptoms in the network may be helpful in relieving the psychological problems among people with diabetes.

Keywords: anxiety; depression; diabetes; network analysis; self-efficacy; sex difference.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Anxiety / psychology
  • Depression* / psychology
  • Diabetes Mellitus* / epidemiology
  • Female
  • Humans
  • Male
  • Self Efficacy
  • Sex Characteristics

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Clinical Research Key Project of Bengbu Medical College, titled “A Cohort Study of Type 2 Diabetes with Panvascular Diseases Based on Electronic Medical Records and MMC Platform” (Grant No. 2022byflc007), and the Key Research and Development Program of Anhui Province, titled “Evaluation of Intervention Effects on Individualized Cardiovascular Diseases Associated with Glycometabolic Disorders” (Grant No. 202204295107020049).