Mapping Network Connectivity Among Symptoms of Depression and Pain in Wuhan Residents During the Late-Stage of the COVID-19 Pandemic

Yuan Yang, Shu Fang Zhang, Bing Xiang Yang, Wen Li, Sha Sha, Fu Jun Jia, Teris Cheung, De Xing Zhang, Chee H. Ng, Yu Tao Xiang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Background: Symptoms of depression and pain often overlap, and they negatively influence the prognosis and treatment outcome of both conditions. However, the comorbidity of depression and pain has not been examined using network analysis, especially in the context of a pandemic. Thus, we mapped out the network connectivity among the symptoms of depression and pain in Wuhan residents in China during the late stage of the COVID-19 pandemic. Methods: This cross-sectional study was conducted from May 25, 2020 to June 18, 2020 in Wuhan, China. Participants' depressive and pain symptoms were assessed using the 9-item Patient Health Questionnaire (PHQ9) and a pain numeric rating scale (NRS), respectively. Network analyses were performed. Results: In total, 2,598 participants completed all assessments. PHQ4 (fatigue) in the depression community showed the highest strength value, followed by PHQ6 (worthlessness) and PHQ2 (depressed or sad mood). PHQ4 (fatigue) was also the most key bridge symptom liking depression and pain, followed by PHQ3 (sleep difficulties). There were no significant differences in network global strength (females: 4.36 vs. males: 4.29; S = 0.075, P = 0.427), network structure-distribution of edge weights (M = 0.12, P = 0.541), and individual edge weights between male and female participants. Conclusion: Depressive and pain symptoms showed strong cross-association with each other. “Fatigue” was the strongest central and bridge symptom in the network model, while “sleep difficulties” was the second strongest bridge symptom. Targeting treatment of both fatigue and sleep problems may help improve depressive and pain symptoms in those affected.

Original languageEnglish
Article number814790
JournalFrontiers in Psychiatry
Volume13
DOIs
Publication statusPublished - 17 Mar 2022

Keywords

  • Chinese
  • COVID-19
  • depression
  • network analysis
  • pain

ASJC Scopus subject areas

  • Psychiatry and Mental health

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