View in EDS HTML Full Text PDF Full Text

Network Analysis of Stress, Anxiety, Depression, Burnout, Insomnia, Quality of Life, and Dropout Intention Among Chinese Medical Postgraduates.

Saved in:
Bibliographic Details
Title: Network Analysis of Stress, Anxiety, Depression, Burnout, Insomnia, Quality of Life, and Dropout Intention Among Chinese Medical Postgraduates.
Authors: Wu, Min (AUTHOR), Li, Zejun (AUTHOR), Wang, Xin (AUTHOR), Xu, Huixue (AUTHOR), Liu, Yueheng (AUTHOR), Li, Manyun (AUTHOR), Yuan, Wenjing (AUTHOR), Peng, Hanrui (AUTHOR), Wu, Qiuxia (AUTHOR), Liu, Tieqiao (AUTHOR), Bosurgi, Raffaella (AUTHOR)
Source: Depression & Anxiety (1091-4269). 3/31/2026, Vol. 2026, p1-14. 14p.
Subjects: Psychological stress, Psychological burnout, Anxiety, Quality of life, School dropouts, Data analysis, Insomnia, Mental depression
Abstract: Background: Chinese medical postgraduate students are subjected to significant academic and professional pressures, leading to heightened levels of stress, anxiety, depression, burnout, and insomnia (SADBI). While network analysis offers a robust framework for examining the complex interrelationships among these symptoms, no prior studies have applied this methodology to this specific population. This study aimed to investigate the interconnections among SADBI symptoms, identify central and bridge symptoms within the network, and explore their associations with quality of life (QOL) and dropout intention (DI). Methods: A cross‐sectional survey was conducted from November 2023 to June 2024, enrolling 1228 Chinese medical postgraduates through snowball sampling via the Wenjuanxing platform. The psychological symptoms were assessed using validated instruments, including 4‐item Perceived Stress Scale (PSS‐4), 7‐item Generalized Anxiety Disorder Scale (GAD‐7), 9‐item Patient Health Questionnaire (PHQ‐9), Oldenburg Burnout Inventory (OLBI), and Insomnia Severity Index (ISI). Network analysis was employed to model the interactions among symptoms and their associations with adverse outcomes (QOL and DI). Central 0and bridge symptoms were identified using expected influence (EI) and bridge EI (BEI) indices, respectively. Results: Within the SADBI network, exhaustion (EX) demonstrated the highest EI, establishing it as the most central symptom. Perceived stress (PS) and EX were identified as the primary bridge symptoms with the highest BEI. PS, EX, and sleep dissatisfaction (ISI4) exhibited the strongest negative correlations with QOL. Additionally, disengagement (DEM), suicidal ideation (PHQ9), and worthlessness (PHQ6) were strongly correlated with DI. The constructed SADBI network exhibited excellent stability and accuracy. Conclusion: PS, EX, and DEM emerged as pivotal symptoms within the SADBI network, highlighting their critical role in the mental health challenges faced by Chinese medical postgraduate students. These findings underscore the importance of targeting these symptoms in prevention and intervention strategies to mitigate mental distress, enhance QOL, and reduce DI in this population. [ABSTRACT FROM AUTHOR]
Copyright of Depression & Anxiety (1091-4269) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 192659313
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Network Analysis of Stress, Anxiety, Depression, Burnout, Insomnia, Quality of Life, and Dropout Intention Among Chinese Medical Postgraduates.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Wu%2C+Min%22">Wu, Min</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Zejun%22">Li, Zejun</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Xin%22">Wang, Xin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Huixue%22">Xu, Huixue</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Yueheng%22">Liu, Yueheng</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Manyun%22">Li, Manyun</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yuan%2C+Wenjing%22">Yuan, Wenjing</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Peng%2C+Hanrui%22">Peng, Hanrui</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Qiuxia%22">Wu, Qiuxia</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Tieqiao%22">Liu, Tieqiao</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bosurgi%2C+Raffaella%22">Bosurgi, Raffaella</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Depression+%26+Anxiety+%281091-4269%29%22">Depression & Anxiety (1091-4269)</searchLink>. 3/31/2026, Vol. 2026, p1-14. 14p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Psychological+stress%22">Psychological stress</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+burnout%22">Psychological burnout</searchLink><br /><searchLink fieldCode="DE" term="%22Anxiety%22">Anxiety</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+of+life%22">Quality of life</searchLink><br /><searchLink fieldCode="DE" term="%22School+dropouts%22">School dropouts</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Insomnia%22">Insomnia</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+depression%22">Mental depression</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Chinese medical postgraduate students are subjected to significant academic and professional pressures, leading to heightened levels of stress, anxiety, depression, burnout, and insomnia (SADBI). While network analysis offers a robust framework for examining the complex interrelationships among these symptoms, no prior studies have applied this methodology to this specific population. This study aimed to investigate the interconnections among SADBI symptoms, identify central and bridge symptoms within the network, and explore their associations with quality of life (QOL) and dropout intention (DI). Methods: A cross‐sectional survey was conducted from November 2023 to June 2024, enrolling 1228 Chinese medical postgraduates through snowball sampling via the Wenjuanxing platform. The psychological symptoms were assessed using validated instruments, including 4‐item Perceived Stress Scale (PSS‐4), 7‐item Generalized Anxiety Disorder Scale (GAD‐7), 9‐item Patient Health Questionnaire (PHQ‐9), Oldenburg Burnout Inventory (OLBI), and Insomnia Severity Index (ISI). Network analysis was employed to model the interactions among symptoms and their associations with adverse outcomes (QOL and DI). Central 0and bridge symptoms were identified using expected influence (EI) and bridge EI (BEI) indices, respectively. Results: Within the SADBI network, exhaustion (EX) demonstrated the highest EI, establishing it as the most central symptom. Perceived stress (PS) and EX were identified as the primary bridge symptoms with the highest BEI. PS, EX, and sleep dissatisfaction (ISI4) exhibited the strongest negative correlations with QOL. Additionally, disengagement (DEM), suicidal ideation (PHQ9), and worthlessness (PHQ6) were strongly correlated with DI. The constructed SADBI network exhibited excellent stability and accuracy. Conclusion: PS, EX, and DEM emerged as pivotal symptoms within the SADBI network, highlighting their critical role in the mental health challenges faced by Chinese medical postgraduate students. These findings underscore the importance of targeting these symptoms in prevention and intervention strategies to mitigate mental distress, enhance QOL, and reduce DI in this population. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Depression & Anxiety (1091-4269) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=192659313
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1155/da/3424408
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 1
    Subjects:
      – SubjectFull: Psychological stress
        Type: general
      – SubjectFull: Psychological burnout
        Type: general
      – SubjectFull: Anxiety
        Type: general
      – SubjectFull: Quality of life
        Type: general
      – SubjectFull: School dropouts
        Type: general
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: Insomnia
        Type: general
      – SubjectFull: Mental depression
        Type: general
    Titles:
      – TitleFull: Network Analysis of Stress, Anxiety, Depression, Burnout, Insomnia, Quality of Life, and Dropout Intention Among Chinese Medical Postgraduates.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wu, Min
      – PersonEntity:
          Name:
            NameFull: Li, Zejun
      – PersonEntity:
          Name:
            NameFull: Wang, Xin
      – PersonEntity:
          Name:
            NameFull: Xu, Huixue
      – PersonEntity:
          Name:
            NameFull: Liu, Yueheng
      – PersonEntity:
          Name:
            NameFull: Li, Manyun
      – PersonEntity:
          Name:
            NameFull: Yuan, Wenjing
      – PersonEntity:
          Name:
            NameFull: Peng, Hanrui
      – PersonEntity:
          Name:
            NameFull: Wu, Qiuxia
      – PersonEntity:
          Name:
            NameFull: Liu, Tieqiao
      – PersonEntity:
          Name:
            NameFull: Bosurgi, Raffaella
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 31
              M: 03
              Text: 3/31/2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 10914269
          Numbering:
            – Type: volume
              Value: 2026
          Titles:
            – TitleFull: Depression & Anxiety (1091-4269)
              Type: main
ResultId 1