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Dynamic Monitoring and Network Analysis of Alcohol Withdrawal Symptoms: Implications for Psychiatric Nursing Practice.

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Title: Dynamic Monitoring and Network Analysis of Alcohol Withdrawal Symptoms: Implications for Psychiatric Nursing Practice.
Authors: Wu, Xuanru, Xu, Ling, Chen, Guangdong, Chen, Qiqi, Zhang, Binwei, Ding, JingJing, Jia, Suilin, Ramos-Pichardo, Juan Diego
Source: Perspectives in Psychiatric Care. 5/21/2025, Vol. 2025, p1-8. 8p.
Subjects: Research funding, Vision disorders, Cronbach's alpha, Data analysis, Nursing assessment, Nursing, Anxiety, Descriptive statistics, Severity of illness index, Alcohol withdrawal syndrome, Nursing practice, Analysis of variance, Statistics, Psychiatric nursing, Hearing disorders, Data analysis software, Symptoms
Geographic Terms: China
Abstract: Background: Alcohol withdrawal syndrome (AWS) is a complex condition characterized by a range of symptoms that can vary in severity. Effective management of AWS during the acute phase is crucial for patient safety and treatment outcomes. This study aimed to investigate the temporal changes in alcohol withdrawal symptoms and identify key symptoms relevant to nursing care using a dynamic monitoring approach and network analysis techniques. Methods: The study included 82 inpatients with alcohol use disorder (AUD) admitted to Wenzhou Seventh People's Hospital. Withdrawal symptoms were assessed using the Clinical Institute Withdrawal Assessment for Alcohol, Revised (CIWA‐Ar) scale at baseline and every 8 h up to 40 h. Repeated measures ANOVA and network analysis were employed to examine symptom changes over time and the interrelationships between symptoms. Results: Withdrawal scores significantly decreased over time, with the critical interval for symptom reduction identified between 8 and 32 h. Network analysis revealed visual disturbances as the most central symptom across both baseline and 40 h time points. Anxiety emerged as a crucial bridging symptom at 40 h, influencing the overall symptom profile. Conclusions: This study highlights the dynamic nature of alcohol withdrawal symptoms and identifies visual disturbances and anxiety as key symptoms relevant to nursing care. The findings emphasize the importance of close monitoring and targeted interventions during the acute withdrawal phase, particularly within the first 32 h. Psychiatric nurses should prioritize the assessment and management of visual disturbances and anxiety to optimize patient outcomes. [ABSTRACT FROM AUTHOR]
Copyright of Perspectives in Psychiatric Care 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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  Group: Ti
  Data: Dynamic Monitoring and Network Analysis of Alcohol Withdrawal Symptoms: Implications for Psychiatric Nursing Practice.
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  Data: <searchLink fieldCode="AR" term="%22Wu%2C+Xuanru%22">Wu, Xuanru</searchLink><br /><searchLink fieldCode="AR" term="%22Xu%2C+Ling%22">Xu, Ling</searchLink><br /><searchLink fieldCode="AR" term="%22Chen%2C+Guangdong%22">Chen, Guangdong</searchLink><br /><searchLink fieldCode="AR" term="%22Chen%2C+Qiqi%22">Chen, Qiqi</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Binwei%22">Zhang, Binwei</searchLink><br /><searchLink fieldCode="AR" term="%22Ding%2C+JingJing%22">Ding, JingJing</searchLink><br /><searchLink fieldCode="AR" term="%22Jia%2C+Suilin%22">Jia, Suilin</searchLink><br /><searchLink fieldCode="AR" term="%22Ramos-Pichardo%2C+Juan+Diego%22">Ramos-Pichardo, Juan Diego</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Perspectives+in+Psychiatric+Care%22">Perspectives in Psychiatric Care</searchLink>. 5/21/2025, Vol. 2025, p1-8. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Vision+disorders%22">Vision disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Cronbach's+alpha%22">Cronbach's alpha</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Nursing+assessment%22">Nursing assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Nursing%22">Nursing</searchLink><br /><searchLink fieldCode="DE" term="%22Anxiety%22">Anxiety</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Severity+of+illness+index%22">Severity of illness index</searchLink><br /><searchLink fieldCode="DE" term="%22Alcohol+withdrawal+syndrome%22">Alcohol withdrawal syndrome</searchLink><br /><searchLink fieldCode="DE" term="%22Nursing+practice%22">Nursing practice</searchLink><br /><searchLink fieldCode="DE" term="%22Analysis+of+variance%22">Analysis of variance</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Psychiatric+nursing%22">Psychiatric nursing</searchLink><br /><searchLink fieldCode="DE" term="%22Hearing+disorders%22">Hearing disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Symptoms%22">Symptoms</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Alcohol withdrawal syndrome (AWS) is a complex condition characterized by a range of symptoms that can vary in severity. Effective management of AWS during the acute phase is crucial for patient safety and treatment outcomes. This study aimed to investigate the temporal changes in alcohol withdrawal symptoms and identify key symptoms relevant to nursing care using a dynamic monitoring approach and network analysis techniques. Methods: The study included 82 inpatients with alcohol use disorder (AUD) admitted to Wenzhou Seventh People's Hospital. Withdrawal symptoms were assessed using the Clinical Institute Withdrawal Assessment for Alcohol, Revised (CIWA‐Ar) scale at baseline and every 8 h up to 40 h. Repeated measures ANOVA and network analysis were employed to examine symptom changes over time and the interrelationships between symptoms. Results: Withdrawal scores significantly decreased over time, with the critical interval for symptom reduction identified between 8 and 32 h. Network analysis revealed visual disturbances as the most central symptom across both baseline and 40 h time points. Anxiety emerged as a crucial bridging symptom at 40 h, influencing the overall symptom profile. Conclusions: This study highlights the dynamic nature of alcohol withdrawal symptoms and identifies visual disturbances and anxiety as key symptoms relevant to nursing care. The findings emphasize the importance of close monitoring and targeted interventions during the acute withdrawal phase, particularly within the first 32 h. Psychiatric nurses should prioritize the assessment and management of visual disturbances and anxiety to optimize patient outcomes. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Group: Ab
  Data: <i>Copyright of Perspectives in Psychiatric Care 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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    Identifiers:
      – Type: doi
        Value: 10.1155/ppc/3126913
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      – Code: eng
        Text: English
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        PageCount: 8
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    Subjects:
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Vision disorders
        Type: general
      – SubjectFull: Cronbach's alpha
        Type: general
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: Nursing assessment
        Type: general
      – SubjectFull: Nursing
        Type: general
      – SubjectFull: Anxiety
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: Severity of illness index
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      – SubjectFull: Alcohol withdrawal syndrome
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      – SubjectFull: Nursing practice
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      – SubjectFull: Analysis of variance
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      – SubjectFull: Statistics
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      – SubjectFull: Psychiatric nursing
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      – SubjectFull: Hearing disorders
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      – SubjectFull: Data analysis software
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      – SubjectFull: Symptoms
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      – SubjectFull: China
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              Text: 5/21/2025
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              Y: 2025
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