What Builds Resilience? Sociodemographic and Social Correlates in the Population-Based LIFE-Adult-Study
Resilience is closely related to mental health and well-being. Identifying risk groups with lower resilience and the variables associated with resilience informs preventive approaches. Previous research on resilience patterns in the general population is heterogeneous, and comprehensive large-scale...
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| Published in: | International journal of environmental research and public health Vol. 19; no. 15; p. 9601 |
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| Main Authors: | , , , , , , , , , , , , |
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| Language: | English |
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04.08.2022
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| ISSN: | 1660-4601, 1661-7827, 1660-4601 |
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| Abstract | Resilience is closely related to mental health and well-being. Identifying risk groups with lower resilience and the variables associated with resilience informs preventive approaches. Previous research on resilience patterns in the general population is heterogeneous, and comprehensive large-scale studies are needed. The aim of our study is to examine sociodemographic and social correlates of resilience in a large population-based sample. We examined 4795 participants from the LIFE-Adult-Study. Assessments included resilience (RS-11), social support (ESSI), and social network (LSNS), as well as the sociodemographic variables age, gender, marital status, education, and occupation. The association of resilience with sociodemographic and social correlates was examined using linear regression analyses. Higher resilience was associated with female gender, married marital status, high education, and full-time occupation. Social support and social network were positively associated with resilience. Our results implicate that resilience is related to various sociodemographic variables. Social variables seem to be particularly important for resilience. We identified risk groups with lower resilience, which should be given special attention by public health policies, especially in times of crisis. Reducing loneliness and promoting social connectedness may be promising ways to build resilience in the general population. |
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| AbstractList | Resilience is closely related to mental health and well-being. Identifying risk groups with lower resilience and the variables associated with resilience informs preventive approaches. Previous research on resilience patterns in the general population is heterogeneous, and comprehensive large-scale studies are needed. The aim of our study is to examine sociodemographic and social correlates of resilience in a large population-based sample. We examined 4795 participants from the LIFE-Adult-Study. Assessments included resilience (RS-11), social support (ESSI), and social network (LSNS), as well as the sociodemographic variables age, gender, marital status, education, and occupation. The association of resilience with sociodemographic and social correlates was examined using linear regression analyses. Higher resilience was associated with female gender, married marital status, high education, and full-time occupation. Social support and social network were positively associated with resilience. Our results implicate that resilience is related to various sociodemographic variables. Social variables seem to be particularly important for resilience. We identified risk groups with lower resilience, which should be given special attention by public health policies, especially in times of crisis. Reducing loneliness and promoting social connectedness may be promising ways to build resilience in the general population. Resilience is closely related to mental health and well-being. Identifying risk groups with lower resilience and the variables associated with resilience informs preventive approaches. Previous research on resilience patterns in the general population is heterogeneous, and comprehensive large-scale studies are needed. The aim of our study is to examine sociodemographic and social correlates of resilience in a large population-based sample. We examined 4795 participants from the LIFE-Adult-Study. Assessments included resilience (RS-11), social support (ESSI), and social network (LSNS), as well as the sociodemographic variables age, gender, marital status, education, and occupation. The association of resilience with sociodemographic and social correlates was examined using linear regression analyses. Higher resilience was associated with female gender, married marital status, high education, and full-time occupation. Social support and social network were positively associated with resilience. Our results implicate that resilience is related to various sociodemographic variables. Social variables seem to be particularly important for resilience. We identified risk groups with lower resilience, which should be given special attention by public health policies, especially in times of crisis. Reducing loneliness and promoting social connectedness may be promising ways to build resilience in the general population.Resilience is closely related to mental health and well-being. Identifying risk groups with lower resilience and the variables associated with resilience informs preventive approaches. Previous research on resilience patterns in the general population is heterogeneous, and comprehensive large-scale studies are needed. The aim of our study is to examine sociodemographic and social correlates of resilience in a large population-based sample. We examined 4795 participants from the LIFE-Adult-Study. Assessments included resilience (RS-11), social support (ESSI), and social network (LSNS), as well as the sociodemographic variables age, gender, marital status, education, and occupation. The association of resilience with sociodemographic and social correlates was examined using linear regression analyses. Higher resilience was associated with female gender, married marital status, high education, and full-time occupation. Social support and social network were positively associated with resilience. Our results implicate that resilience is related to various sociodemographic variables. Social variables seem to be particularly important for resilience. We identified risk groups with lower resilience, which should be given special attention by public health policies, especially in times of crisis. Reducing loneliness and promoting social connectedness may be promising ways to build resilience in the general population. |
| Author | Engel, Christoph Glaesmer, Heide Henger, Sylvia Löbner, Margrit Zeynalova, Samira Witte, A. Veronica Löffler, Markus Wirkner, Kerstin Riedel-Heller, Steffi G. Weitzel, Elena Caroline Reyes, Nigar Villringer, Arno Hinz, Andreas |
| AuthorAffiliation | 5 Department Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Max Planck Society, Stephanstr. 1a, 04103 Leipzig, Germany 4 LIFE—Leipzig Research Centre for Civilization Diseases, University of Leipzig, Philipp-Rosenthal-Str. 27, 04103 Leipzig, Germany 2 Department of Medical Psychology and Medical Sociology, Medical Faculty, University of Leipzig, Philipp-Rosenthal-Str. 55, 04103 Leipzig, Germany 1 Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Philipp-Rosenthal-Str. 55, 04103 Leipzig, Germany 3 Institute of Medical Informatics, Statistics and Epidemiology, University of Leipzig, Härtelstr. 16-18, 04107 Leipzig, Germany |
| AuthorAffiliation_xml | – name: 3 Institute of Medical Informatics, Statistics and Epidemiology, University of Leipzig, Härtelstr. 16-18, 04107 Leipzig, Germany – name: 1 Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Philipp-Rosenthal-Str. 55, 04103 Leipzig, Germany – name: 4 LIFE—Leipzig Research Centre for Civilization Diseases, University of Leipzig, Philipp-Rosenthal-Str. 27, 04103 Leipzig, Germany – name: 5 Department Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Max Planck Society, Stephanstr. 1a, 04103 Leipzig, Germany – name: 2 Department of Medical Psychology and Medical Sociology, Medical Faculty, University of Leipzig, Philipp-Rosenthal-Str. 55, 04103 Leipzig, Germany |
| Author_xml | – sequence: 1 givenname: Elena Caroline orcidid: 0000-0002-1469-1514 surname: Weitzel fullname: Weitzel, Elena Caroline – sequence: 2 givenname: Heide surname: Glaesmer fullname: Glaesmer, Heide – sequence: 3 givenname: Andreas surname: Hinz fullname: Hinz, Andreas – sequence: 4 givenname: Samira surname: Zeynalova fullname: Zeynalova, Samira – sequence: 5 givenname: Sylvia surname: Henger fullname: Henger, Sylvia – sequence: 6 givenname: Christoph orcidid: 0000-0002-7247-282X surname: Engel fullname: Engel, Christoph – sequence: 7 givenname: Markus surname: Löffler fullname: Löffler, Markus – sequence: 8 givenname: Nigar surname: Reyes fullname: Reyes, Nigar – sequence: 9 givenname: Kerstin surname: Wirkner fullname: Wirkner, Kerstin – sequence: 10 givenname: A. Veronica surname: Witte fullname: Witte, A. Veronica – sequence: 11 givenname: Arno surname: Villringer fullname: Villringer, Arno – sequence: 12 givenname: Steffi G. surname: Riedel-Heller fullname: Riedel-Heller, Steffi G. – sequence: 13 givenname: Margrit orcidid: 0000-0001-5984-8127 surname: Löbner fullname: Löbner, Margrit |
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| SubjectTerms | Age groups Coronaviruses COVID-19 Education Gender Likert scale Mental disorders Mental health Pandemics Population Population-based studies Regression analysis Resilience (Psychology) Social networks Social support Sociodemographics Variables Well being Womens health |
| Title | What Builds Resilience? Sociodemographic and Social Correlates in the Population-Based LIFE-Adult-Study |
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