Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 Pandemic
Background: This research analyses the relations between anxiety symptoms from the network perspective to deepen the understanding of anxiety in front-line medical staff during the COVID-19 pandemic and can also provide a reference for determining potential goals of clinical interventions. Methods:...
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| Format: | Article |
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MDPI AG
2023-08-01
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| Series: | Brain Sciences |
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| Online Access: | https://www.mdpi.com/2076-3425/13/8/1155 |
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| author | Lin Wu Lei Ren Fengzhan Li Kang Shi Peng Fang Xiuchao Wang Tingwei Feng Shengjun Wu Xufeng Liu |
| author_facet | Lin Wu Lei Ren Fengzhan Li Kang Shi Peng Fang Xiuchao Wang Tingwei Feng Shengjun Wu Xufeng Liu |
| author_sort | Lin Wu |
| collection | DOAJ |
| description | Background: This research analyses the relations between anxiety symptoms from the network perspective to deepen the understanding of anxiety in front-line medical staff during the COVID-19 pandemic and can also provide a reference for determining potential goals of clinical interventions. Methods: A convenience sampling was adopted, and the Generalized Anxiety Disorder 7-item scale (GAD-7) was administered to front-line medical staff through online platforms. A regularized partial correlation network of anxiety was constructed and then we evaluated its accuracy and stability. The expected influence and predictability were used to describe the relative importance and the controllability, using community detection to explore community structure. The gender-based differences and the directed acyclic graph were implemented. Results: The connections between A1 “Feeling nervous, anxious or on edge” and A2 “Not being able to stop or control worrying”, A6 “Becoming easily annoyed or irritable” and A7 “Feeling afraid as if something awful might happen”, etc., were relatively strong; A2 “Not being able to stop or control worrying” and A3 “Worrying too much about different things” had the highest expected influence, and A2 “Not being able to stop or control worrying” had the highest predictability. The community detection identified two communities. The results of the gender network comparison showed the overall intensity of the anxiety network in women was higher than that in men; DAG indicated that A2 “Not being able to stop or control worrying” had the highest probabilistic priority; the lines from A2 “Not being able to stop or control worrying” to A1 “Feeling nervous, anxious or on edge” and A2 “Not being able to stop or control worrying” to A7 “Feeling afraid as if something awful might happen” represented the most important arrows. Conclusion: There exist broad interconnections among anxiety symptoms of front-line medical staff on the GAD-7. A2 “Not being able to stop or control worrying” might be the core symptom and a potential effective intervention target. It was possible to bring an optimal result for the entire GAD symptom network by interfering with A2 “Not being able to stop or control worrying”. GAD may have two “subsystems”. The modes of interconnection among anxiety may be consistent between genders. |
| first_indexed | 2024-03-11T00:05:47Z |
| format | Article |
| id | doaj.art-ccbc20b972564117b7111e85daaaa30a |
| institution | Directory Open Access Journal |
| issn | 2076-3425 |
| language | English |
| last_indexed | 2024-03-11T00:05:47Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
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| series | Brain Sciences |
| spelling | doaj.art-ccbc20b972564117b7111e85daaaa30a2023-11-19T00:26:29ZengMDPI AGBrain Sciences2076-34252023-08-01138115510.3390/brainsci13081155Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 PandemicLin Wu0Lei Ren1Fengzhan Li2Kang Shi3Peng Fang4Xiuchao Wang5Tingwei Feng6Shengjun Wu7Xufeng Liu8Department of Military Medical Psychology, Air Force Medical University, Xi’an 710032, ChinaMilitary Psychology Section, Logistics University of PAP, Tianjin 300309, ChinaDepartment of Military Medical Psychology, Air Force Medical University, Xi’an 710032, ChinaDepartment of Military Medical Psychology, Air Force Medical University, Xi’an 710032, ChinaDepartment of Military Medical Psychology, Air Force Medical University, Xi’an 710032, ChinaDepartment of Military Medical Psychology, Air Force Medical University, Xi’an 710032, ChinaDepartment of Military Medical Psychology, Air Force Medical University, Xi’an 710032, ChinaDepartment of Military Medical Psychology, Air Force Medical University, Xi’an 710032, ChinaDepartment of Military Medical Psychology, Air Force Medical University, Xi’an 710032, ChinaBackground: This research analyses the relations between anxiety symptoms from the network perspective to deepen the understanding of anxiety in front-line medical staff during the COVID-19 pandemic and can also provide a reference for determining potential goals of clinical interventions. Methods: A convenience sampling was adopted, and the Generalized Anxiety Disorder 7-item scale (GAD-7) was administered to front-line medical staff through online platforms. A regularized partial correlation network of anxiety was constructed and then we evaluated its accuracy and stability. The expected influence and predictability were used to describe the relative importance and the controllability, using community detection to explore community structure. The gender-based differences and the directed acyclic graph were implemented. Results: The connections between A1 “Feeling nervous, anxious or on edge” and A2 “Not being able to stop or control worrying”, A6 “Becoming easily annoyed or irritable” and A7 “Feeling afraid as if something awful might happen”, etc., were relatively strong; A2 “Not being able to stop or control worrying” and A3 “Worrying too much about different things” had the highest expected influence, and A2 “Not being able to stop or control worrying” had the highest predictability. The community detection identified two communities. The results of the gender network comparison showed the overall intensity of the anxiety network in women was higher than that in men; DAG indicated that A2 “Not being able to stop or control worrying” had the highest probabilistic priority; the lines from A2 “Not being able to stop or control worrying” to A1 “Feeling nervous, anxious or on edge” and A2 “Not being able to stop or control worrying” to A7 “Feeling afraid as if something awful might happen” represented the most important arrows. Conclusion: There exist broad interconnections among anxiety symptoms of front-line medical staff on the GAD-7. A2 “Not being able to stop or control worrying” might be the core symptom and a potential effective intervention target. It was possible to bring an optimal result for the entire GAD symptom network by interfering with A2 “Not being able to stop or control worrying”. GAD may have two “subsystems”. The modes of interconnection among anxiety may be consistent between genders.https://www.mdpi.com/2076-3425/13/8/1155COVID-19front-line medical staffGAD-7anxietynetwork analysis |
| spellingShingle | Lin Wu Lei Ren Fengzhan Li Kang Shi Peng Fang Xiuchao Wang Tingwei Feng Shengjun Wu Xufeng Liu Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 Pandemic Brain Sciences COVID-19 front-line medical staff GAD-7 anxiety network analysis |
| title | Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 Pandemic |
| title_full | Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 Pandemic |
| title_fullStr | Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 Pandemic |
| title_full_unstemmed | Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 Pandemic |
| title_short | Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 Pandemic |
| title_sort | network analysis of anxiety symptoms in front line medical staff during the covid 19 pandemic |
| topic | COVID-19 front-line medical staff GAD-7 anxiety network analysis |
| url | https://www.mdpi.com/2076-3425/13/8/1155 |
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