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A systematic review on the relationship between socioeconomic conditions and emotional disorder symptoms during Covid-19: unearthing the potential role of economic concerns and financial strain
Covid-19 has disrupted the lives of many and resulted in high prevalence rates of mental disorders. Despite a vast amount of research into the social determinants of mental health during Covid-19, little is known about whether the results are consistent with the social gradient in mental health. Her...
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Published in: | BMC Psychology 2024-04, Vol.12 (1), p.237-237, Article 237 |
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description | Covid-19 has disrupted the lives of many and resulted in high prevalence rates of mental disorders. Despite a vast amount of research into the social determinants of mental health during Covid-19, little is known about whether the results are consistent with the social gradient in mental health. Here we report a systematic review of studies that investigated how socioeconomic condition (SEC)-a multifaceted construct that measures a person's socioeconomic standing in society, using indicators such as education and income, predicts emotional health (depression and anxiety) risk during the pandemic. Furthermore, we examined which classes of SEC indicators would best predict symptoms of emotional disorders.
Following PRISMA guidelines, we conducted search over six databases, including Scopus, PubMed, etc., between November 4, 2021 and November 11, 2021 for studies that investigated how SEC indicators predict emotional health risks during Covid-19, after obtaining approval from PROSPERO (ID: CRD42021288508). Using Covidence as the platform, 362 articles (324 cross-sectional/repeated cross-sectional and 38 longitudinal) were included in this review according to the eligibility criteria. We categorized SEC indicators into 'actual versus perceived' and 'static versus fluid' classes to explore their differential effects on emotional health.
Out of the 1479 SEC indicators used in these 362 studies, our results showed that 43.68% of the SEC indicators showed 'expected' results (i.e., higher SEC predicting better emotional health outcomes); 51.86% reported non-significant results and 4.46% reported the reverse. Economic concerns (67.16% expected results) and financial strains (64.16%) emerged as the best predictors while education (26.85%) and living conditions (30.14%) were the worst.
This review summarizes how different SEC indicators influenced emotional health risks across 98 countries, with a total of 5,677,007 participants, ranging from high to low-income countries. Our findings showed that not all SEC indicators were strongly predictive of emotional health risks. In fact, over half of the SEC indicators studied showed a null effect. We found that perceived and fluid SEC indicators, particularly economic concerns and financial strain could best predict depressive and anxiety symptoms. These findings have implications for policymakers to further understand how different SEC classes affect mental health during a pandemic in order to tackle associated social issues |
doi_str_mv | 10.1186/s40359-024-01715-8 |
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Following PRISMA guidelines, we conducted search over six databases, including Scopus, PubMed, etc., between November 4, 2021 and November 11, 2021 for studies that investigated how SEC indicators predict emotional health risks during Covid-19, after obtaining approval from PROSPERO (ID: CRD42021288508). Using Covidence as the platform, 362 articles (324 cross-sectional/repeated cross-sectional and 38 longitudinal) were included in this review according to the eligibility criteria. We categorized SEC indicators into 'actual versus perceived' and 'static versus fluid' classes to explore their differential effects on emotional health.
Out of the 1479 SEC indicators used in these 362 studies, our results showed that 43.68% of the SEC indicators showed 'expected' results (i.e., higher SEC predicting better emotional health outcomes); 51.86% reported non-significant results and 4.46% reported the reverse. Economic concerns (67.16% expected results) and financial strains (64.16%) emerged as the best predictors while education (26.85%) and living conditions (30.14%) were the worst.
This review summarizes how different SEC indicators influenced emotional health risks across 98 countries, with a total of 5,677,007 participants, ranging from high to low-income countries. Our findings showed that not all SEC indicators were strongly predictive of emotional health risks. In fact, over half of the SEC indicators studied showed a null effect. We found that perceived and fluid SEC indicators, particularly economic concerns and financial strain could best predict depressive and anxiety symptoms. These findings have implications for policymakers to further understand how different SEC classes affect mental health during a pandemic in order to tackle associated social issues effectively.</description><identifier>ISSN: 2050-7283</identifier><identifier>EISSN: 2050-7283</identifier><identifier>DOI: 10.1186/s40359-024-01715-8</identifier><identifier>PMID: 38671542</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Analysis ; Anxiety ; Anxiety - epidemiology ; Anxiety - psychology ; Coronaviruses ; COVID-19 ; COVID-19 - economics ; COVID-19 - epidemiology ; COVID-19 - psychology ; Depression ; Depression - epidemiology ; Depression - psychology ; Depression, Mental ; Education ; Emotional health ; Epidemics ; Family income ; Financial Stress - epidemiology ; Financial Stress - psychology ; Health aspects ; Households ; Humans ; Investigations ; Longitudinal studies ; Low income groups ; Medical research ; Medicine, Experimental ; Mental disorders ; Mental health ; Mental Health - statistics & numerical data ; Pandemics ; Psychological aspects ; SARS-CoV-2 ; Social aspects ; Social classes ; Social determinants ; Socioeconomic conditions ; Socioeconomic Factors ; Stress ; Systematic review</subject><ispartof>BMC Psychology, 2024-04, Vol.12 (1), p.237-237, Article 237</ispartof><rights>2024. The Author(s).</rights><rights>COPYRIGHT 2024 BioMed Central Ltd.</rights><rights>2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c558t-5ef1f677ee4cec2b217d238b84c1fd44cf4ed421e75550846c69609f94623fa43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/3054194887?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,37013,38516,43895,44590</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38671542$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chan, Jee Kei</creatorcontrib><creatorcontrib>Marzuki, Aleya A</creatorcontrib><creatorcontrib>Vafa, Samira</creatorcontrib><creatorcontrib>Thanaraju, Arjun</creatorcontrib><creatorcontrib>Yap, Jie</creatorcontrib><creatorcontrib>Chan, Xiou Wen</creatorcontrib><creatorcontrib>Harris, Hanis Atasha</creatorcontrib><creatorcontrib>Todi, Khushi</creatorcontrib><creatorcontrib>Schaefer, Alexandre</creatorcontrib><title>A systematic review on the relationship between socioeconomic conditions and emotional disorder symptoms during Covid-19: unearthing the potential role of economic concerns and financial strain</title><title>BMC Psychology</title><addtitle>BMC Psychol</addtitle><description>Covid-19 has disrupted the lives of many and resulted in high prevalence rates of mental disorders. Despite a vast amount of research into the social determinants of mental health during Covid-19, little is known about whether the results are consistent with the social gradient in mental health. Here we report a systematic review of studies that investigated how socioeconomic condition (SEC)-a multifaceted construct that measures a person's socioeconomic standing in society, using indicators such as education and income, predicts emotional health (depression and anxiety) risk during the pandemic. Furthermore, we examined which classes of SEC indicators would best predict symptoms of emotional disorders.
Following PRISMA guidelines, we conducted search over six databases, including Scopus, PubMed, etc., between November 4, 2021 and November 11, 2021 for studies that investigated how SEC indicators predict emotional health risks during Covid-19, after obtaining approval from PROSPERO (ID: CRD42021288508). Using Covidence as the platform, 362 articles (324 cross-sectional/repeated cross-sectional and 38 longitudinal) were included in this review according to the eligibility criteria. We categorized SEC indicators into 'actual versus perceived' and 'static versus fluid' classes to explore their differential effects on emotional health.
Out of the 1479 SEC indicators used in these 362 studies, our results showed that 43.68% of the SEC indicators showed 'expected' results (i.e., higher SEC predicting better emotional health outcomes); 51.86% reported non-significant results and 4.46% reported the reverse. Economic concerns (67.16% expected results) and financial strains (64.16%) emerged as the best predictors while education (26.85%) and living conditions (30.14%) were the worst.
This review summarizes how different SEC indicators influenced emotional health risks across 98 countries, with a total of 5,677,007 participants, ranging from high to low-income countries. Our findings showed that not all SEC indicators were strongly predictive of emotional health risks. In fact, over half of the SEC indicators studied showed a null effect. We found that perceived and fluid SEC indicators, particularly economic concerns and financial strain could best predict depressive and anxiety symptoms. These findings have implications for policymakers to further understand how different SEC classes affect mental health during a pandemic in order to tackle associated social issues effectively.</description><subject>Analysis</subject><subject>Anxiety</subject><subject>Anxiety - epidemiology</subject><subject>Anxiety - psychology</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 - economics</subject><subject>COVID-19 - epidemiology</subject><subject>COVID-19 - psychology</subject><subject>Depression</subject><subject>Depression - epidemiology</subject><subject>Depression - psychology</subject><subject>Depression, Mental</subject><subject>Education</subject><subject>Emotional health</subject><subject>Epidemics</subject><subject>Family income</subject><subject>Financial Stress - epidemiology</subject><subject>Financial Stress - psychology</subject><subject>Health aspects</subject><subject>Households</subject><subject>Humans</subject><subject>Investigations</subject><subject>Longitudinal studies</subject><subject>Low income groups</subject><subject>Medical research</subject><subject>Medicine, Experimental</subject><subject>Mental disorders</subject><subject>Mental health</subject><subject>Mental Health - statistics & numerical data</subject><subject>Pandemics</subject><subject>Psychological aspects</subject><subject>SARS-CoV-2</subject><subject>Social aspects</subject><subject>Social classes</subject><subject>Social determinants</subject><subject>Socioeconomic conditions</subject><subject>Socioeconomic Factors</subject><subject>Stress</subject><subject>Systematic review</subject><issn>2050-7283</issn><issn>2050-7283</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNk81q3DAUhU1paUKaF-iiCAolXTiVLMmyuxuG_gwEAv3bCo18NaNgS1NJTprH65tVnpmmM6WL4oWsy3fORUe6RfGc4EtCmvpNZJjytsQVKzERhJfNo-K0whyXomro44P_k-I8xhuMMSEU07Z6WpzQps4SVp0WP2co3scEg0pWowC3Fu6QdyitIe_6XPUuru0GLSHdATgUvbYetHd-yIK8dnbLIOU6BIOfNqpHnY0-dBCy-7BJfoioG4N1KzT3t7YrSfsWjQ5USOupOHXb-AQu2awNvgfkDTrsoiHsexjrlNMTF1NQ1j0rnhjVRzjfr2fF1_fvvsw_llfXHxbz2VWpOW9SycEQUwsBwDToalkR0VW0WTZME9Mxpg2DjlUEBOccN6zWdVvj1rSsrqhRjJ4Vi51v59WN3AQ7qHAvvbJyW_BhJfNxrO5B4iXBoq4VbzhnNadKASf5pgypl2CoyF4XO69N8N9HiEkONmroe-XAj1FSzERL2xbXGX35F3rjx5AjnijOSMuaRvyhVir3t874nI2eTOUsO-FWUDEd4fIfVP46yDF7B8bm-pHg9ZEgMwl-pJUaY5SLz5_-n73-dsy-OmDXoPq0jr4fty_pGKx2oA4-xgDmIXiC5TQHcjcHMqcrt3Mgmyx6sY9sXA7QPUh-v3r6C7MKAic</recordid><startdate>20240426</startdate><enddate>20240426</enddate><creator>Chan, Jee Kei</creator><creator>Marzuki, Aleya A</creator><creator>Vafa, Samira</creator><creator>Thanaraju, Arjun</creator><creator>Yap, Jie</creator><creator>Chan, Xiou Wen</creator><creator>Harris, Hanis Atasha</creator><creator>Todi, Khushi</creator><creator>Schaefer, Alexandre</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>DOA</scope></search><sort><creationdate>20240426</creationdate><title>A systematic review on the relationship between socioeconomic conditions and emotional disorder symptoms during Covid-19: unearthing the potential role of economic concerns and financial strain</title><author>Chan, Jee Kei ; Marzuki, Aleya A ; Vafa, Samira ; Thanaraju, Arjun ; Yap, Jie ; Chan, Xiou Wen ; Harris, Hanis Atasha ; Todi, Khushi ; Schaefer, Alexandre</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c558t-5ef1f677ee4cec2b217d238b84c1fd44cf4ed421e75550846c69609f94623fa43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Analysis</topic><topic>Anxiety</topic><topic>Anxiety - epidemiology</topic><topic>Anxiety - psychology</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>COVID-19 - economics</topic><topic>COVID-19 - epidemiology</topic><topic>COVID-19 - psychology</topic><topic>Depression</topic><topic>Depression - epidemiology</topic><topic>Depression - psychology</topic><topic>Depression, Mental</topic><topic>Education</topic><topic>Emotional health</topic><topic>Epidemics</topic><topic>Family income</topic><topic>Financial Stress - epidemiology</topic><topic>Financial Stress - psychology</topic><topic>Health aspects</topic><topic>Households</topic><topic>Humans</topic><topic>Investigations</topic><topic>Longitudinal studies</topic><topic>Low income groups</topic><topic>Medical research</topic><topic>Medicine, Experimental</topic><topic>Mental disorders</topic><topic>Mental health</topic><topic>Mental Health - statistics & numerical data</topic><topic>Pandemics</topic><topic>Psychological aspects</topic><topic>SARS-CoV-2</topic><topic>Social aspects</topic><topic>Social classes</topic><topic>Social determinants</topic><topic>Socioeconomic conditions</topic><topic>Socioeconomic Factors</topic><topic>Stress</topic><topic>Systematic review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chan, Jee Kei</creatorcontrib><creatorcontrib>Marzuki, Aleya A</creatorcontrib><creatorcontrib>Vafa, Samira</creatorcontrib><creatorcontrib>Thanaraju, Arjun</creatorcontrib><creatorcontrib>Yap, Jie</creatorcontrib><creatorcontrib>Chan, Xiou Wen</creatorcontrib><creatorcontrib>Harris, Hanis Atasha</creatorcontrib><creatorcontrib>Todi, Khushi</creatorcontrib><creatorcontrib>Schaefer, Alexandre</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC Psychology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chan, Jee Kei</au><au>Marzuki, Aleya A</au><au>Vafa, Samira</au><au>Thanaraju, Arjun</au><au>Yap, Jie</au><au>Chan, Xiou Wen</au><au>Harris, Hanis Atasha</au><au>Todi, Khushi</au><au>Schaefer, Alexandre</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A systematic review on the relationship between socioeconomic conditions and emotional disorder symptoms during Covid-19: unearthing the potential role of economic concerns and financial strain</atitle><jtitle>BMC Psychology</jtitle><addtitle>BMC Psychol</addtitle><date>2024-04-26</date><risdate>2024</risdate><volume>12</volume><issue>1</issue><spage>237</spage><epage>237</epage><pages>237-237</pages><artnum>237</artnum><issn>2050-7283</issn><eissn>2050-7283</eissn><abstract>Covid-19 has disrupted the lives of many and resulted in high prevalence rates of mental disorders. Despite a vast amount of research into the social determinants of mental health during Covid-19, little is known about whether the results are consistent with the social gradient in mental health. Here we report a systematic review of studies that investigated how socioeconomic condition (SEC)-a multifaceted construct that measures a person's socioeconomic standing in society, using indicators such as education and income, predicts emotional health (depression and anxiety) risk during the pandemic. Furthermore, we examined which classes of SEC indicators would best predict symptoms of emotional disorders.
Following PRISMA guidelines, we conducted search over six databases, including Scopus, PubMed, etc., between November 4, 2021 and November 11, 2021 for studies that investigated how SEC indicators predict emotional health risks during Covid-19, after obtaining approval from PROSPERO (ID: CRD42021288508). Using Covidence as the platform, 362 articles (324 cross-sectional/repeated cross-sectional and 38 longitudinal) were included in this review according to the eligibility criteria. We categorized SEC indicators into 'actual versus perceived' and 'static versus fluid' classes to explore their differential effects on emotional health.
Out of the 1479 SEC indicators used in these 362 studies, our results showed that 43.68% of the SEC indicators showed 'expected' results (i.e., higher SEC predicting better emotional health outcomes); 51.86% reported non-significant results and 4.46% reported the reverse. Economic concerns (67.16% expected results) and financial strains (64.16%) emerged as the best predictors while education (26.85%) and living conditions (30.14%) were the worst.
This review summarizes how different SEC indicators influenced emotional health risks across 98 countries, with a total of 5,677,007 participants, ranging from high to low-income countries. Our findings showed that not all SEC indicators were strongly predictive of emotional health risks. In fact, over half of the SEC indicators studied showed a null effect. We found that perceived and fluid SEC indicators, particularly economic concerns and financial strain could best predict depressive and anxiety symptoms. These findings have implications for policymakers to further understand how different SEC classes affect mental health during a pandemic in order to tackle associated social issues effectively.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>38671542</pmid><doi>10.1186/s40359-024-01715-8</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Anxiety Anxiety - epidemiology Anxiety - psychology Coronaviruses COVID-19 COVID-19 - economics COVID-19 - epidemiology COVID-19 - psychology Depression Depression - epidemiology Depression - psychology Depression, Mental Education Emotional health Epidemics Family income Financial Stress - epidemiology Financial Stress - psychology Health aspects Households Humans Investigations Longitudinal studies Low income groups Medical research Medicine, Experimental Mental disorders Mental health Mental Health - statistics & numerical data Pandemics Psychological aspects SARS-CoV-2 Social aspects Social classes Social determinants Socioeconomic conditions Socioeconomic Factors Stress Systematic review |
title | A systematic review on the relationship between socioeconomic conditions and emotional disorder symptoms during Covid-19: unearthing the potential role of economic concerns and financial strain |
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