The Effects of Social Support on Sleep Quality of Medical Staff Treating Patients with Coronavirus Disease 2019 (COVID-19) in January and February 2020 in China.
Identifieur interne : 000139 ( PubMed/Checkpoint ); précédent : 000138; suivant : 000140The Effects of Social Support on Sleep Quality of Medical Staff Treating Patients with Coronavirus Disease 2019 (COVID-19) in January and February 2020 in China.
Auteurs : Han Xiao ; Yan Zhang ; Desheng Kong ; Shiyue Li [République populaire de Chine] ; Ningxi YangSource :
- Medical science monitor : international medical journal of experimental and clinical research [ 1643-3750 ] ; 2020.
Descripteurs français
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- MESH :
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- geographic : République populaire de Chine.
English descriptors
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- MESH :
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19), formerly known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 2019 novel coronavirus (2019-nCoV), was first identified in December 2019 in Wuhan City, China. Structural equation modeling (SEM) is a multivariate analysis method to determine the structural relationship between measured variables. This observational study aimed to use SEM to determine the effects of social support on sleep quality and function of medical staff who treated patients with COVID-19 in January and February 2020 in Wuhan, China. MATERIAL AND METHODS A one-month cross-sectional observational study included 180 medical staff who treated patients with COVID-19 infection. Levels of anxiety, self-efficacy, stress, sleep quality, and social support were measured using the and the Self-Rating Anxiety Scale (SAS), the General Self-Efficacy Scale (GSES), the Stanford Acute Stress Reaction (SASR) questionnaire, the Pittsburgh Sleep Quality Index (PSQI), and the Social Support Rate Scale (SSRS), respectively. Pearson's correlation analysis and SEM identified the interactions between these factors. RESULTS Levels of social support for medical staff were significantly associated with self-efficacy and sleep quality and negatively associated with the degree of anxiety and stress. Levels of anxiety were significantly associated with the levels of stress, which negatively impacted self-efficacy and sleep quality. Anxiety, stress, and self-efficacy were mediating variables associated with social support and sleep quality. CONCLUSIONS SEM showed that medical staff in China who were treating patients with COVID-19 infection during January and February 2020 had levels of anxiety, stress, and self-efficacy that were dependent on sleep quality and social support.
DOI: 10.12659/MSM.923549
PubMed: 32132521
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uniqKey="Kong D" first="Desheng" last="Kong">Desheng Kong</name><affiliation><nlm:affiliation>College of Humanities and Social Sciences, Harbin Engineering University, Harbin, Heilongjiang, China (mainland).</nlm:affiliation><wicri:noCountry code="subField">China (mainland)</wicri:noCountry></affiliation></author><author><name sortKey="Li, Shiyue" sort="Li, Shiyue" uniqKey="Li S" first="Shiyue" last="Li">Shiyue Li</name><affiliation wicri:level="4"><nlm:affiliation>School of Health Sciences, Wuhan University, Wuhan, Hubei, China (mainland).</nlm:affiliation><orgName type="university">Université de Wuhan</orgName><country>République populaire de Chine</country><placeName><settlement type="city">Wuhan</settlement><region type="province">Hubei</region></placeName></affiliation></author><author><name sortKey="Yang, Ningxi" sort="Yang, Ningxi" uniqKey="Yang N" first="Ningxi" last="Yang">Ningxi Yang</name><affiliation><nlm:affiliation>College of Humanities and Social Sciences, Harbin 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Disease 2019 (COVID-19) in January and February 2020 in China.</title><author><name sortKey="Xiao, Han" sort="Xiao, Han" uniqKey="Xiao H" first="Han" last="Xiao">Han Xiao</name><affiliation><nlm:affiliation>Department of Respiration, Xuanwu Hospital Capital Medical University, Beijing, China (mainland).</nlm:affiliation><wicri:noCountry code="subField">China (mainland)</wicri:noCountry></affiliation></author><author><name sortKey="Zhang, Yan" sort="Zhang, Yan" uniqKey="Zhang Y" first="Yan" last="Zhang">Yan Zhang</name><affiliation><nlm:affiliation>College of Humanities and Social Sciences, Harbin Engineering University, Harbin, Heilongjiang, China (mainland).</nlm:affiliation><wicri:noCountry code="subField">China (mainland)</wicri:noCountry></affiliation></author><author><name sortKey="Kong, Desheng" sort="Kong, Desheng" uniqKey="Kong D" first="Desheng" last="Kong">Desheng Kong</name><affiliation><nlm:affiliation>College of Humanities and Social Sciences, Harbin Engineering University, Harbin, Heilongjiang, China (mainland).</nlm:affiliation><wicri:noCountry code="subField">China (mainland)</wicri:noCountry></affiliation></author><author><name sortKey="Li, Shiyue" sort="Li, Shiyue" uniqKey="Li S" first="Shiyue" last="Li">Shiyue Li</name><affiliation wicri:level="4"><nlm:affiliation>School of Health Sciences, Wuhan University, Wuhan, Hubei, China (mainland).</nlm:affiliation><orgName type="university">Université de Wuhan</orgName><country>République populaire de Chine</country><placeName><settlement type="city">Wuhan</settlement><region type="province">Hubei</region></placeName></affiliation></author><author><name sortKey="Yang, Ningxi" sort="Yang, Ningxi" uniqKey="Yang N" first="Ningxi" last="Yang">Ningxi Yang</name><affiliation><nlm:affiliation>College of Humanities and Social Sciences, Harbin Engineering University, Harbin, Heilongjiang, China (mainland).</nlm:affiliation><wicri:noCountry code="subField">China (mainland)</wicri:noCountry></affiliation></author></analytic><series><title level="j">Medical science monitor : international medical journal of experimental and clinical research</title><idno type="eISSN">1643-3750</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult</term><term>Anxiety</term><term>Betacoronavirus</term><term>China</term><term>Coronavirus Infections</term><term>Cross-Sectional Studies</term><term>Female</term><term>Humans</term><term>Male</term><term>Medical Staff</term><term>Pneumonia, Viral</term><term>Self Efficacy</term><term>Sleep</term><term>Social Support</term><term>Stress, Psychological</term><term>Surveys and Questionnaires</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adulte</term><term>Anxiété</term><term>Auto-efficacité</term><term>Chine</term><term>Corps médical</term><term>Enquêtes et questionnaires</term><term>Femelle</term><term>Humains</term><term>Infections à coronavirus</term><term>Mâle</term><term>Pneumopathie virale</term><term>Sommeil</term><term>Soutien social</term><term>Stress psychologique</term><term>Études transversales</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>China</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Anxiety</term><term>Betacoronavirus</term><term>Coronavirus Infections</term><term>Cross-Sectional Studies</term><term>Female</term><term>Humans</term><term>Male</term><term>Medical Staff</term><term>Pneumonia, Viral</term><term>Self Efficacy</term><term>Sleep</term><term>Social Support</term><term>Stress, Psychological</term><term>Surveys and Questionnaires</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adulte</term><term>Anxiété</term><term>Auto-efficacité</term><term>Chine</term><term>Corps médical</term><term>Enquêtes et questionnaires</term><term>Femelle</term><term>Humains</term><term>Infections à coronavirus</term><term>Mâle</term><term>Pneumopathie virale</term><term>Sommeil</term><term>Soutien social</term><term>Stress psychologique</term><term>Études transversales</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">BACKGROUND Coronavirus disease 2019 (COVID-19), formerly known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 2019 novel coronavirus (2019-nCoV), was first identified in December 2019 in Wuhan City, China. Structural equation modeling (SEM) is a multivariate analysis method to determine the structural relationship between measured variables. This observational study aimed to use SEM to determine the effects of social support on sleep quality and function of medical staff who treated patients with COVID-19 in January and February 2020 in Wuhan, China. MATERIAL AND METHODS A one-month cross-sectional observational study included 180 medical staff who treated patients with COVID-19 infection. Levels of anxiety, self-efficacy, stress, sleep quality, and social support were measured using the and the Self-Rating Anxiety Scale (SAS), the General Self-Efficacy Scale (GSES), the Stanford Acute Stress Reaction (SASR) questionnaire, the Pittsburgh Sleep Quality Index (PSQI), and the Social Support Rate Scale (SSRS), respectively. Pearson's correlation analysis and SEM identified the interactions between these factors. RESULTS Levels of social support for medical staff were significantly associated with self-efficacy and sleep quality and negatively associated with the degree of anxiety and stress. Levels of anxiety were significantly associated with the levels of stress, which negatively impacted self-efficacy and sleep quality. Anxiety, stress, and self-efficacy were mediating variables associated with social support and sleep quality. CONCLUSIONS SEM showed that medical staff in China who were treating patients with COVID-19 infection during January and February 2020 had levels of anxiety, stress, and self-efficacy that were dependent on sleep quality and social support.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32132521</PMID><DateCompleted><Year>2020</Year><Month>03</Month><Day>16</Day></DateCompleted><DateRevised><Year>2020</Year><Month>04</Month><Day>20</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1643-3750</ISSN><JournalIssue CitedMedium="Internet"><Volume>26</Volume><PubDate><Year>2020</Year><Month>Mar</Month><Day>05</Day></PubDate></JournalIssue><Title>Medical science monitor : international medical journal of experimental and clinical research</Title><ISOAbbreviation>Med. Sci. Monit.</ISOAbbreviation></Journal><ArticleTitle>The Effects of Social Support on Sleep Quality of Medical Staff Treating Patients with Coronavirus Disease 2019 (COVID-19) in January and February 2020 in China.</ArticleTitle><Pagination><MedlinePgn>e923549</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.12659/MSM.923549</ELocationID><Abstract><AbstractText>BACKGROUND Coronavirus disease 2019 (COVID-19), formerly known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 2019 novel coronavirus (2019-nCoV), was first identified in December 2019 in Wuhan City, China. Structural equation modeling (SEM) is a multivariate analysis method to determine the structural relationship between measured variables. This observational study aimed to use SEM to determine the effects of social support on sleep quality and function of medical staff who treated patients with COVID-19 in January and February 2020 in Wuhan, China. MATERIAL AND METHODS A one-month cross-sectional observational study included 180 medical staff who treated patients with COVID-19 infection. Levels of anxiety, self-efficacy, stress, sleep quality, and social support were measured using the and the Self-Rating Anxiety Scale (SAS), the General Self-Efficacy Scale (GSES), the Stanford Acute Stress Reaction (SASR) questionnaire, the Pittsburgh Sleep Quality Index (PSQI), and the Social Support Rate Scale (SSRS), respectively. Pearson's correlation analysis and SEM identified the interactions between these factors. RESULTS Levels of social support for medical staff were significantly associated with self-efficacy and sleep quality and negatively associated with the degree of anxiety and stress. Levels of anxiety were significantly associated with the levels of stress, which negatively impacted self-efficacy and sleep quality. Anxiety, stress, and self-efficacy were mediating variables associated with social support and sleep quality. CONCLUSIONS SEM showed that medical staff in China who were treating patients with COVID-19 infection during January and February 2020 had levels of anxiety, stress, and self-efficacy that were dependent on sleep quality and social support.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Xiao</LastName><ForeName>Han</ForeName><Initials>H</Initials><AffiliationInfo><Affiliation>Department of Respiration, Xuanwu Hospital Capital Medical University, Beijing, China (mainland).</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Yan</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>College of Humanities and Social Sciences, Harbin Engineering University, Harbin, Heilongjiang, China (mainland).</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kong</LastName><ForeName>Desheng</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>College of Humanities and Social Sciences, Harbin Engineering University, Harbin, Heilongjiang, China (mainland).</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Shiyue</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>School of Health Sciences, Wuhan University, Wuhan, Hubei, China (mainland).</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yang</LastName><ForeName>Ningxi</ForeName><Initials>N</Initials><AffiliationInfo><Affiliation>College of Humanities and Social Sciences, Harbin Engineering University, Harbin, Heilongjiang, China (mainland).</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D064888">Observational Study</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>03</Month><Day>05</Day></ArticleDate></Article><MedlineJournalInfo><Country>United 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Kong</name><name sortKey="Xiao, Han" sort="Xiao, Han" uniqKey="Xiao H" first="Han" last="Xiao">Han Xiao</name><name sortKey="Yang, Ningxi" sort="Yang, Ningxi" uniqKey="Yang N" first="Ningxi" last="Yang">Ningxi Yang</name><name sortKey="Zhang, Yan" sort="Zhang, Yan" uniqKey="Zhang Y" first="Yan" last="Zhang">Yan Zhang</name></noCountry><country name="République populaire de Chine"><region name="Hubei"><name sortKey="Li, Shiyue" sort="Li, Shiyue" uniqKey="Li S" first="Shiyue" last="Li">Shiyue Li</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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