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Resilience and depressive symptoms in inpatients with depression: A cross‐lagged panel model.

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Title: Resilience and depressive symptoms in inpatients with depression: A cross‐lagged panel model.
Authors: Meule, Adrian (AUTHOR), Lieb, Klaus (AUTHOR), Chmitorz, Andrea (AUTHOR), Voderholzer, Ulrich (AUTHOR)
Source: Clinical Psychology & Psychotherapy. Jan2024, Vol. 31 Issue 1, p1-6. 6p.
Subjects: Length of stay in hospitals, Hospital patients, Confidence intervals, Cross-sectional method, T-test (Statistics), Mental depression, Questionnaires, Medical records, Descriptive statistics, Research funding, Sociodemographic factors, Data analysis software, Psychological resilience
Abstract: Background: Resilience—the ability to bounce back or quickly recover from stress—has been found to predict treatment outcome in patients with mental disorders such as depression. The current study aimed to test whether resilience itself changes during treatment and whether resilience exclusively predicts changes in depressive symptoms or whether depressive symptoms also predict changes in resilience. Methods: Inpatients with depression (N = 2165; average length of stay M = 60 days, SD = 32) completed the Brief Resilience Scale and the Patient Health Questionnaire Depression Scale at admission and discharge, scores of which were used to run a cross‐lagged panel model. Results: Resilience increased and depressive symptoms decreased from admission to discharge. Cross‐sectionally, higher resilience was related to lower depressive symptoms at admission and at discharge. Prospectively, higher resilience at admission predicted stronger decreases in depressive symptoms, and higher depressive symptoms at admission predicted smaller increases in resilience. Limitations: Self‐report questionnaires may potentially be biased (e.g., through recall bias, social desirability, or demand effects). Conclusions: The current study further supports that resilience is related not only to fewer mental health problems cross‐sectionally but also is sensitive to change and a predictor of treatment outcome in patients with mental disorders. Given this pivotal role in mental health, the current findings highlight the importance of prevention and intervention approaches for promoting resilience in the general population and in persons with mental disorders in particular. [ABSTRACT FROM AUTHOR]
Copyright of Clinical Psychology & Psychotherapy 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
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  Data: Resilience and depressive symptoms in inpatients with depression: A cross‐lagged panel model.
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  Data: <searchLink fieldCode="AR" term="%22Meule%2C+Adrian%22">Meule, Adrian</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lieb%2C+Klaus%22">Lieb, Klaus</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chmitorz%2C+Andrea%22">Chmitorz, Andrea</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Voderholzer%2C+Ulrich%22">Voderholzer, Ulrich</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Clinical+Psychology+%26+Psychotherapy%22">Clinical Psychology & Psychotherapy</searchLink>. Jan2024, Vol. 31 Issue 1, p1-6. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Length+of+stay+in+hospitals%22">Length of stay in hospitals</searchLink><br /><searchLink fieldCode="DE" term="%22Hospital+patients%22">Hospital patients</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Cross-sectional+method%22">Cross-sectional method</searchLink><br /><searchLink fieldCode="DE" term="%22T-test+%28Statistics%29%22">T-test (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+depression%22">Mental depression</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+records%22">Medical records</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Sociodemographic+factors%22">Sociodemographic factors</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+resilience%22">Psychological resilience</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Background: Resilience—the ability to bounce back or quickly recover from stress—has been found to predict treatment outcome in patients with mental disorders such as depression. The current study aimed to test whether resilience itself changes during treatment and whether resilience exclusively predicts changes in depressive symptoms or whether depressive symptoms also predict changes in resilience. Methods: Inpatients with depression (N = 2165; average length of stay M = 60 days, SD = 32) completed the Brief Resilience Scale and the Patient Health Questionnaire Depression Scale at admission and discharge, scores of which were used to run a cross‐lagged panel model. Results: Resilience increased and depressive symptoms decreased from admission to discharge. Cross‐sectionally, higher resilience was related to lower depressive symptoms at admission and at discharge. Prospectively, higher resilience at admission predicted stronger decreases in depressive symptoms, and higher depressive symptoms at admission predicted smaller increases in resilience. Limitations: Self‐report questionnaires may potentially be biased (e.g., through recall bias, social desirability, or demand effects). Conclusions: The current study further supports that resilience is related not only to fewer mental health problems cross‐sectionally but also is sensitive to change and a predictor of treatment outcome in patients with mental disorders. Given this pivotal role in mental health, the current findings highlight the importance of prevention and intervention approaches for promoting resilience in the general population and in persons with mental disorders in particular. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Clinical Psychology & Psychotherapy 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.)
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      – Type: doi
        Value: 10.1002/cpp.2926
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      – Code: eng
        Text: English
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        PageCount: 6
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    Subjects:
      – SubjectFull: Length of stay in hospitals
        Type: general
      – SubjectFull: Hospital patients
        Type: general
      – SubjectFull: Confidence intervals
        Type: general
      – SubjectFull: Cross-sectional method
        Type: general
      – SubjectFull: T-test (Statistics)
        Type: general
      – SubjectFull: Mental depression
        Type: general
      – SubjectFull: Questionnaires
        Type: general
      – SubjectFull: Medical records
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Research funding
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      – SubjectFull: Sociodemographic factors
        Type: general
      – SubjectFull: Data analysis software
        Type: general
      – SubjectFull: Psychological resilience
        Type: general
    Titles:
      – TitleFull: Resilience and depressive symptoms in inpatients with depression: A cross‐lagged panel model.
        Type: main
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            NameFull: Meule, Adrian
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            NameFull: Lieb, Klaus
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            NameFull: Chmitorz, Andrea
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            – D: 01
              M: 01
              Text: Jan2024
              Type: published
              Y: 2024
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              Value: 31
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