Social support and mental health among health care workers during Coronavirus Disease 2019 outbreak: A moderated mediation model.
Identifieur interne : 000313 ( Main/Exploration ); précédent : 000312; suivant : 000314Social support and mental health among health care workers during Coronavirus Disease 2019 outbreak: A moderated mediation model.
Auteurs : Tianya Hou [République populaire de Chine] ; Taiquan Zhang [République populaire de Chine] ; Wenpeng Cai [République populaire de Chine] ; Xiangrui Song [République populaire de Chine] ; Aibin Chen [République populaire de Chine] ; Guanghui Deng [République populaire de Chine] ; Chunyan Ni [République populaire de Chine]Source :
- PloS one [ 1932-6203 ] ; 2020.
Descripteurs français
- KwdFr :
- MESH :
- psychologie : Personnel de santé.
- épidémiologie : Chine, Infections à coronavirus, Pneumopathie virale.
- Humains, Médecine de catastrophe, Pandémies, Résilience psychologique, Services de santé mentale, Soutien social, Échelles d'évaluation en psychiatrie.
- Wicri :
- geographic : République populaire de Chine.
English descriptors
- KwdEn :
- MESH :
- geographic , epidemiology : China.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- psychology : Health Personnel.
- Disaster Medicine, Humans, Mental Health Services, Pandemics, Psychiatric Status Rating Scales, Resilience, Psychological, Social Support.
Abstract
PURPOSES
During the outbreak of Coronavirus Disease 2019 (COVID-19) all over the world, the mental health conditions of health care workers are of great importance to ensure the efficiency of rescue operations. The current study examined the effect of social support on mental health of health care workers and its underlying mechanisms regarding the mediating role of resilience and moderating role of age during the epidemic.
METHODS
Social Support Rating Scale (SSRS), Connor-Davidson Resilience scale (CD-RISC) and Symptom Checklist 90 (SCL-90) were administrated among 1472 health care workers from Jiangsu Province, China during the peak period of COVID-19 outbreak. Structural equation modeling (SEM) was used to examine the mediation effect of resilience on the relation between social support and mental health, whereas moderated mediation analysis was performed by Hayes PROCESS macro.
RESULTS
The findings showed that resilience could partially mediate the effect of social support on mental health among health care workers. Age group moderated the indirect relationship between social support and mental health via resilience. Specifically, compared with younger health care workers, the association between resilience and mental health would be attenuated in the middle-aged workers.
CONCLUSIONS
The results add knowledge to previous literature by uncovering the underlying mechanisms between social support and mental health. The present study has profound implications for mental health services for health care workers during the peak period of COVID-19.
DOI: 10.1371/journal.pone.0233831
PubMed: 32470007
PubMed Central: PMC7259684
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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first="Tianya" last="Hou">Tianya Hou</name><affiliation wicri:level="1"><nlm:affiliation>Department of Psychology, Naval Medical University (Second Military Medical University), Shanghai, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Psychology, Naval Medical University (Second Military Medical University), Shanghai</wicri:regionArea><wicri:noRegion>Shanghai</wicri:noRegion></affiliation></author><author><name sortKey="Zhang, Taiquan" sort="Zhang, Taiquan" uniqKey="Zhang T" first="Taiquan" last="Zhang">Taiquan Zhang</name><affiliation wicri:level="1"><nlm:affiliation>Nursing Department, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Nursing Department, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, 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Medical University), Shanghai, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Psychology, Naval Medical University (Second Military Medical University), Shanghai</wicri:regionArea><wicri:noRegion>Shanghai</wicri:noRegion></affiliation></author><author><name sortKey="Ni, Chunyan" sort="Ni, Chunyan" uniqKey="Ni C" first="Chunyan" last="Ni">Chunyan Ni</name><affiliation wicri:level="1"><nlm:affiliation>Nursing Department, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Nursing Department, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou</wicri:regionArea><wicri:noRegion>Suzhou</wicri:noRegion></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>China (epidemiology)</term><term>Coronavirus Infections (epidemiology)</term><term>Disaster Medicine</term><term>Health Personnel (psychology)</term><term>Humans</term><term>Mental Health Services</term><term>Pandemics</term><term>Pneumonia, Viral (epidemiology)</term><term>Psychiatric Status Rating Scales</term><term>Resilience, Psychological</term><term>Social Support</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Chine (épidémiologie)</term><term>Humains</term><term>Infections à coronavirus (épidémiologie)</term><term>Médecine de catastrophe</term><term>Pandémies</term><term>Personnel de santé (psychologie)</term><term>Pneumopathie virale (épidémiologie)</term><term>Résilience psychologique</term><term>Services de santé mentale</term><term>Soutien social</term><term>Échelles d'évaluation en psychiatrie</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>China</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="psychologie" xml:lang="fr"><term>Personnel de santé</term></keywords><keywords scheme="MESH" qualifier="psychology" xml:lang="en"><term>Health Personnel</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Chine</term><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Disaster Medicine</term><term>Humans</term><term>Mental Health Services</term><term>Pandemics</term><term>Psychiatric Status Rating Scales</term><term>Resilience, Psychological</term><term>Social Support</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Humains</term><term>Médecine de catastrophe</term><term>Pandémies</term><term>Résilience psychologique</term><term>Services de santé mentale</term><term>Soutien social</term><term>Échelles d'évaluation en psychiatrie</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>République populaire de Chine</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>PURPOSES</b></p><p>During the outbreak of Coronavirus Disease 2019 (COVID-19) all over the world, the mental health conditions of health care workers are of great importance to ensure the efficiency of rescue operations. The current study examined the effect of social support on mental health of health care workers and its underlying mechanisms regarding the mediating role of resilience and moderating role of age during the epidemic.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>Social Support Rating Scale (SSRS), Connor-Davidson Resilience scale (CD-RISC) and Symptom Checklist 90 (SCL-90) were administrated among 1472 health care workers from Jiangsu Province, China during the peak period of COVID-19 outbreak. Structural equation modeling (SEM) was used to examine the mediation effect of resilience on the relation between social support and mental health, whereas moderated mediation analysis was performed by Hayes PROCESS macro.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>The findings showed that resilience could partially mediate the effect of social support on mental health among health care workers. Age group moderated the indirect relationship between social support and mental health via resilience. Specifically, compared with younger health care workers, the association between resilience and mental health would be attenuated in the middle-aged workers.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>The results add knowledge to previous literature by uncovering the underlying mechanisms between social support and mental health. The present study has profound implications for mental health services for health care workers during the peak period of COVID-19.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32470007</PMID><DateCompleted><Year>2020</Year><Month>06</Month><Day>04</Day></DateCompleted><DateRevised><Year>2020</Year><Month>06</Month><Day>09</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>15</Volume><Issue>5</Issue><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS ONE</ISOAbbreviation></Journal><ArticleTitle>Social support and mental health among health care workers during Coronavirus Disease 2019 outbreak: A moderated mediation model.</ArticleTitle><Pagination><MedlinePgn>e0233831</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0233831</ELocationID><Abstract><AbstractText Label="PURPOSES">During the outbreak of Coronavirus Disease 2019 (COVID-19) all over the world, the mental health conditions of health care workers are of great importance to ensure the efficiency of rescue operations. The current study examined the effect of social support on mental health of health care workers and its underlying mechanisms regarding the mediating role of resilience and moderating role of age during the epidemic.</AbstractText><AbstractText Label="METHODS">Social Support Rating Scale (SSRS), Connor-Davidson Resilience scale (CD-RISC) and Symptom Checklist 90 (SCL-90) were administrated among 1472 health care workers from Jiangsu Province, China during the peak period of COVID-19 outbreak. Structural equation modeling (SEM) was used to examine the mediation effect of resilience on the relation between social support and mental health, whereas moderated mediation analysis was performed by Hayes PROCESS macro.</AbstractText><AbstractText Label="RESULTS">The findings showed that resilience could partially mediate the effect of social support on mental health among health care workers. Age group moderated the indirect relationship between social support and mental health via resilience. Specifically, compared with younger health care workers, the association between resilience and mental health would be attenuated in the middle-aged workers.</AbstractText><AbstractText Label="CONCLUSIONS">The results add knowledge to previous literature by uncovering the underlying mechanisms between social support and mental health. The present study has profound implications for mental health services for health care workers during the peak period of COVID-19.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Hou</LastName><ForeName>Tianya</ForeName><Initials>T</Initials><Identifier Source="ORCID">0000-0001-7361-1935</Identifier><AffiliationInfo><Affiliation>Department of Psychology, Naval Medical University (Second Military Medical University), Shanghai, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Taiquan</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>Nursing Department, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cai</LastName><ForeName>Wenpeng</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>Department of Psychology, Naval Medical University (Second Military Medical University), Shanghai, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Song</LastName><ForeName>Xiangrui</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Department of Psychology, Naval Medical University (Second Military Medical University), Shanghai, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Aibin</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Psychology, Naval Medical University (Second Military Medical University), Shanghai, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Deng</LastName><ForeName>Guanghui</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Department of Psychology, Naval Medical University (Second Military Medical University), Shanghai, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ni</LastName><ForeName>Chunyan</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Nursing Department, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>05</Month><Day>29</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002681" MajorTopicYN="N" Type="Geographic">China</DescriptorName><QualifierName UI="Q000453" 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