A network analysis of anxiety and depression symptoms in medical stuff_Chinese Journal of Evidence-Based Medicine

Authors：

ZENG Yating ^1,2,3 , HE Wenbo ³ , SU Xiaoyi ^1,2,3 , MA Jinyi ^1,2,3 , YU Zhiruo ^1,2,3 , XU Yihan ^1,2,3 , YUAN Huanhuan ² , CHEN Fan ² , LU Tianlin ² ,  DU Liang ^1,2,3 ,  LI Zhengchi ^1,2,4

1. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
2. Center for Education of Medical Humanities, West China Hospital of Sichuan University, Chengdu 610041, P. R. China;
3. Innovation Institute for Integration of Medicine and Engineering, West China Hospital of Sichuan University, Chengdu 610041, P. R. China;
4. Institute of Hospital Management, West China Hospital of Sichuan University, Chengdu 610041, P. R. China;

Corresponding author：

DU Liang, Email: duliang0606@vip.sina.com; LI Zhengchi, Email: lizhengchi@wchscu.cn

Keywords：

Medical staff; Depression; Anxiety; Network analysis

DOI：

10.7507/1672-2531.202412107

Video：

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Objective To investigate the network structure of comorbid depression and anxiety symptoms among medical staff and analyze differences across institutional types. Methods A convenience sampling method was used to select medical stuff from medical institutions at various levels in Guang'an City as participants between August 10 and 15, 2024. General demographic questionnaires, the Chinese version of the Patient Health Questionnaire (PHQ-9) for depression screening, and the Chinese version of the Generalized Anxiety Disorder Scale (GAD-7) were used to survey them. The study aimed to analyze the influencing factors of anxiety and depression and construct a network model. Predictability, bridging strength, and node strength were used to assess the network structure. The non-parametric bootstrap method was employed to evaluate the accuracy and stability of the network, and finally, a Network Comparison Test (NCT) was used to examine the impact of different levels of healthcare institutions on the network model. Results A total of 889 participants were included in the study. The analysis showed that the incidence of depressive symptoms (PHQ-9≥5) among healthcare workers was 44.88%, while the incidence of anxiety symptoms (GAD-7≥5) was 43.98%, with a comorbidity rate of 36.67%. Network analysis revealed that the top three symptoms with the highest node strength were difficulty relaxing (A4), excessive worry (A3), and fatigue (D4). The top three symptoms with the highest bridging strength were irritability/anger (A6), fatigue (D4), and worrying about terrible things happening (A7). The different levels of healthcare institutions did not have a significant impact on the network model. Conclusion The central symptoms (such as difficulty relaxing, excessive worry, and fatigue) and key bridging symptoms (such as irritability/anger, fatigue, and worrying about terrible things happening) in the anxiety and depression symptom network can serve as potential intervention targets for healthcare workers at risk of depressive and anxiety symptoms.

1.	Pereira-Lima K, Loureiro SR. Burnout, anxiety, depression, and social skills in medical residents. Psychol Health Med, 2015, 20(3): 353-362.
2.	Fang H, Zhao X, Yang H, et al. Depressive symptoms and workplace-violence-related risk factors among otorhinolaryngology nurses and physicians in Northern China: a cross-sectional study. BMJ Open, 2018, 8(1): e019514.
3.	Shanafelt TD, Balch CM, Bechamps G, et al. Burnout and medical errors among American surgeons. Ann Surg, 2010, 251(6): 995-1000.
4.	First MB. Diagnostic and statistical manual of mental disorders, 5th edition, and clinical utility. J Nerv Ment Dis, 2013, 201(9): 727-729.
5.	Zhang HH, Zhao YJ, Wang C, et al. Depression and its relationship with quality of life in frontline psychiatric clinicians during the COVID-19 pandemic in China: a national survey. Int J Biol Sci, 2021, 17(3): 683-688.
6.	Liang S, Liu C, Rotaru K, et al. The relations between emotion regulation, depression and anxiety among medical staff during the late stage of COVID-19 pandemic: a network analysis. Psychiatry Res, 2022, 317: 114863.
7.	Zhang P, Wang L, Zhou Q, et al. A network analysis of anxiety and depression symptoms in Chinese disabled elderly. J Affect Disord, 2023, 333: 535-542.
8.	Ray S, Agarwal P. Depression and anxiety in Parkinson disease. Clin Geriat Med, 2020, 36(1): 93-104.
9.	Kalin NH. Anxiety, depression, and suicide in youth. Am J Psych, 2021, 178(4): 275-279.
10.	Lai J, Ma S, Wang Y, et al. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Network Open, 2020, 3(3): e203976.
11.	Wang H, Liu Y, Hu K, et al. Healthcare workers' stress when caring for COVID-19 patients: An altruistic perspective. Nurs Ethics, 2020, 27(7): 1490-1500.
12.	Borsboom D, Cramer AOJ. Network analysis: an integrative approach to the structure of psychopathology. Ann Rev Clin Psychol, 2013, 9(1): 91-121.
13.	Beard C, Millner AJ, Forgeard MJC, et al. Network analysis of depression and anxiety symptom relationships in a psychiatric sample. Psychol Med, 2016, 46(16): 3359-3369.
14.	Borsboom D. A network theory of mental disorders. World Psychiatry, 2017, 16(1): 5-13.
15.	Wang S, Hou W, Tao Y, et al. Mapping network connection among symptoms of anxiety, depression, and sleep disturbance in Chinese high school students. Front Public Health, 2022, 10: 1015166.
16.	Li A, Wang D, Lin S, et al. Depression and life satisfaction among middle-aged and older adults: mediation effect of functional disability. Front Psychol, 2021, 12: 755220.
17.	van Borkulo C, Boschloo L, Borsboom D, et al. Association of symptom network structure with the course of [corrected] depression. JAMA Psychiatry, 2015, 72(12): 1219-1226.
18.	Wang S, Hou W, Tao Y, et al. Mapping network connection among symptoms of anxiety, depression, and sleep disturbance in Chinese high school students. Front Public Health, 2022, 10: 1015166.
19.	Li L, Niu Z, Griffiths MD, et al. A network perspective on the relationship between gaming disorder, depression, alexithymia, boredom, and loneliness among a sample of Chinese university students. Tech Society, 2021, 67: 101740.
20.	Schlechter P, Wilkinson PO, Knausenberger J, et al. Depressive and anxiety symptoms in refugees: Insights from classical test theory, item response theory and network analysis. Clin Psychol Psychother, 2021, 28(1): 169-181.
21.	Zhao N, Zhao YJ, An F, et al. Network analysis of comorbid insomnia and depressive symptoms among psychiatric practitioners during the COVID-19 pandemic. J Clin Sleep Med, 2023, 19(7): 1271-1279.
22.	傅小兰, 张侃, 陈雪峰, 等. 中国国民心理健康发展报告2021~2022. 北京: 社会科学文献出版社, 2023: 1.
23.	Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: validity of a brief depression severity measure. J Gen Int Med, 2001, 16(9): 606-613.
24.	Yang Y, Song Y, Lu Y, et al. Associations between erectile dysfunction and psychological disorders (depression and anxiety): a cross-sectional study in a Chinese population. Andrologia, 2019, 51(10): e13395.
25.	Spitzer RL, Kroenke K, Williams JBW, et al. A brief measure for assessing generalized anxiety disorder: The GAD-7. Arch Int Med, 2006, 166(10): 1092.
26.	Epskamp S, Borsboom D, Fried EI. Estimating psychological networks and their accuracy: a tutorial paper. Behav Res Methods, 2018, 50(1): 195-212.
27.	Jones PJ, Ma R, Mcnally RJ. Bridge centrality: a network approach to understanding comorbidity. Mult Behav Res, 2021, 56(2): 353-367.
28.	Tibshirani R. Regression shrinkage and selection via the lasso. J Royal Stat Soc Series B: Stat Methodol, 1996, 58(1): 267-288.
29.	Chen J, Chen Z. Extended bayesian information criteria for model selection with large model spaces. Biometrika, 2008, 95(3): 759-771.
30.	Haslbeck JMB, Fried EI. How predictable are symptoms in psychopathological networks. A reanalysis of 18 published datasets. Psychol Med, 2017, 47(16): 2767-2776.
31.	Tian G, Li R, Cui Y, et al. Association between disability, social support and depressive symptoms in Chinese older adults: a national study. Front Public Health, 2022, 10: 980465.
32.	沈钦戈, 李猛, 贾秀珍, 等. 医务人员共患抑郁和焦虑的网络分析. 济宁医学院学报, 2024, 47(5): 382-386.
33.	Peng P, Chen Q, Liang M, et al. A network analysis of anxiety and depression symptoms among Chinese nurses in the late stage of the COVID-19 pandemic. Front Public Health, 2022, 10: 996386.
34.	Yang Y, Sun H, Luo X, et al. Network connectivity between fear of cancer recurrence, anxiety, and depression in breast cancer patients. J Affect Disord, 2022, 309: 358-367.
35.	Garabiles MR, Lao CK, Xiong Y, et al. Exploring comorbidity between anxiety and depression among migrant Filipino domestic workers: a network approach. J Affect Disord, 2019, 250: 85-93.
36.	Jones PJ, Mair P, Riemann BC, et al. A network perspective on comorbid depression in adolescents with obsessive-compulsive disorder. J Anxiety Disord, 2018, 53: 1-8.
37.	Ballesio A, Aquino MRJV, Feige B, et al. The effectiveness of behavioural and cognitive behavioural therapies for insomnia on depressive and fatigue symptoms: a systematic review and network meta-analysis. Sleep Med Rev, 2018, 37: 114-129.
38.	Wang L, Duan H, Zuo H, et al. Cognitive-behavioral stress management relieves anxiety, depression, and post-traumatic stress disorder in parents of pediatric acute myeloid leukemia patients: a randomized, controlled study. Hematology, 2024, 29(1): 2293498.
39.	Takahashi M. The role of prescribed napping in sleep medicine. Sleep Med Rev, 2003, 7(3): 227-235.
40.	Ganesan S, Magee M, Stone JE, et al. The impact of shift work on sleep, alertness and performance in healthcare workers. Scient Rep, 2019, 9(1): 4635.

1. Pereira-Lima K, Loureiro SR. Burnout, anxiety, depression, and social skills in medical residents. Psychol Health Med, 2015, 20(3): 353-362.
2. Fang H, Zhao X, Yang H, et al. Depressive symptoms and workplace-violence-related risk factors among otorhinolaryngology nurses and physicians in Northern China: a cross-sectional study. BMJ Open, 2018, 8(1): e019514.
3. Shanafelt TD, Balch CM, Bechamps G, et al. Burnout and medical errors among American surgeons. Ann Surg, 2010, 251(6): 995-1000.
4. First MB. Diagnostic and statistical manual of mental disorders, 5th edition, and clinical utility. J Nerv Ment Dis, 2013, 201(9): 727-729.
5. Zhang HH, Zhao YJ, Wang C, et al. Depression and its relationship with quality of life in frontline psychiatric clinicians during the COVID-19 pandemic in China: a national survey. Int J Biol Sci, 2021, 17(3): 683-688.
6. Liang S, Liu C, Rotaru K, et al. The relations between emotion regulation, depression and anxiety among medical staff during the late stage of COVID-19 pandemic: a network analysis. Psychiatry Res, 2022, 317: 114863.
7. Zhang P, Wang L, Zhou Q, et al. A network analysis of anxiety and depression symptoms in Chinese disabled elderly. J Affect Disord, 2023, 333: 535-542.
8. Ray S, Agarwal P. Depression and anxiety in Parkinson disease. Clin Geriat Med, 2020, 36(1): 93-104.
9. Kalin NH. Anxiety, depression, and suicide in youth. Am J Psych, 2021, 178(4): 275-279.
10. Lai J, Ma S, Wang Y, et al. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Network Open, 2020, 3(3): e203976.
11. Wang H, Liu Y, Hu K, et al. Healthcare workers' stress when caring for COVID-19 patients: An altruistic perspective. Nurs Ethics, 2020, 27(7): 1490-1500.
12. Borsboom D, Cramer AOJ. Network analysis: an integrative approach to the structure of psychopathology. Ann Rev Clin Psychol, 2013, 9(1): 91-121.
13. Beard C, Millner AJ, Forgeard MJC, et al. Network analysis of depression and anxiety symptom relationships in a psychiatric sample. Psychol Med, 2016, 46(16): 3359-3369.
14. Borsboom D. A network theory of mental disorders. World Psychiatry, 2017, 16(1): 5-13.
15. Wang S, Hou W, Tao Y, et al. Mapping network connection among symptoms of anxiety, depression, and sleep disturbance in Chinese high school students. Front Public Health, 2022, 10: 1015166.
16. Li A, Wang D, Lin S, et al. Depression and life satisfaction among middle-aged and older adults: mediation effect of functional disability. Front Psychol, 2021, 12: 755220.
17. van Borkulo C, Boschloo L, Borsboom D, et al. Association of symptom network structure with the course of [corrected] depression. JAMA Psychiatry, 2015, 72(12): 1219-1226.
18. Wang S, Hou W, Tao Y, et al. Mapping network connection among symptoms of anxiety, depression, and sleep disturbance in Chinese high school students. Front Public Health, 2022, 10: 1015166.
19. Li L, Niu Z, Griffiths MD, et al. A network perspective on the relationship between gaming disorder, depression, alexithymia, boredom, and loneliness among a sample of Chinese university students. Tech Society, 2021, 67: 101740.
20. Schlechter P, Wilkinson PO, Knausenberger J, et al. Depressive and anxiety symptoms in refugees: Insights from classical test theory, item response theory and network analysis. Clin Psychol Psychother, 2021, 28(1): 169-181.
21. Zhao N, Zhao YJ, An F, et al. Network analysis of comorbid insomnia and depressive symptoms among psychiatric practitioners during the COVID-19 pandemic. J Clin Sleep Med, 2023, 19(7): 1271-1279.
22. 傅小兰, 张侃, 陈雪峰, 等. 中国国民心理健康发展报告2021~2022. 北京: 社会科学文献出版社, 2023: 1.
23. Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: validity of a brief depression severity measure. J Gen Int Med, 2001, 16(9): 606-613.
24. Yang Y, Song Y, Lu Y, et al. Associations between erectile dysfunction and psychological disorders (depression and anxiety): a cross-sectional study in a Chinese population. Andrologia, 2019, 51(10): e13395.
25. Spitzer RL, Kroenke K, Williams JBW, et al. A brief measure for assessing generalized anxiety disorder: The GAD-7. Arch Int Med, 2006, 166(10): 1092.
26. Epskamp S, Borsboom D, Fried EI. Estimating psychological networks and their accuracy: a tutorial paper. Behav Res Methods, 2018, 50(1): 195-212.
27. Jones PJ, Ma R, Mcnally RJ. Bridge centrality: a network approach to understanding comorbidity. Mult Behav Res, 2021, 56(2): 353-367.
28. Tibshirani R. Regression shrinkage and selection via the lasso. J Royal Stat Soc Series B: Stat Methodol, 1996, 58(1): 267-288.
29. Chen J, Chen Z. Extended bayesian information criteria for model selection with large model spaces. Biometrika, 2008, 95(3): 759-771.
30. Haslbeck JMB, Fried EI. How predictable are symptoms in psychopathological networks. A reanalysis of 18 published datasets. Psychol Med, 2017, 47(16): 2767-2776.
31. Tian G, Li R, Cui Y, et al. Association between disability, social support and depressive symptoms in Chinese older adults: a national study. Front Public Health, 2022, 10: 980465.
32. 沈钦戈, 李猛, 贾秀珍, 等. 医务人员共患抑郁和焦虑的网络分析. 济宁医学院学报, 2024, 47(5): 382-386.
33. Peng P, Chen Q, Liang M, et al. A network analysis of anxiety and depression symptoms among Chinese nurses in the late stage of the COVID-19 pandemic. Front Public Health, 2022, 10: 996386.
34. Yang Y, Sun H, Luo X, et al. Network connectivity between fear of cancer recurrence, anxiety, and depression in breast cancer patients. J Affect Disord, 2022, 309: 358-367.
35. Garabiles MR, Lao CK, Xiong Y, et al. Exploring comorbidity between anxiety and depression among migrant Filipino domestic workers: a network approach. J Affect Disord, 2019, 250: 85-93.
36. Jones PJ, Mair P, Riemann BC, et al. A network perspective on comorbid depression in adolescents with obsessive-compulsive disorder. J Anxiety Disord, 2018, 53: 1-8.
37. Ballesio A, Aquino MRJV, Feige B, et al. The effectiveness of behavioural and cognitive behavioural therapies for insomnia on depressive and fatigue symptoms: a systematic review and network meta-analysis. Sleep Med Rev, 2018, 37: 114-129.
38. Wang L, Duan H, Zuo H, et al. Cognitive-behavioral stress management relieves anxiety, depression, and post-traumatic stress disorder in parents of pediatric acute myeloid leukemia patients: a randomized, controlled study. Hematology, 2024, 29(1): 2293498.
39. Takahashi M. The role of prescribed napping in sleep medicine. Sleep Med Rev, 2003, 7(3): 227-235.
40. Ganesan S, Magee M, Stone JE, et al. The impact of shift work on sleep, alertness and performance in healthcare workers. Scient Rep, 2019, 9(1): 4635.

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