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Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors
The coronavirus disease 2019 (COVID-19) pandemic has created a global health crisis, with disproportionate effects on vulnerable sociodemographic groups. Although the pandemic is showing potential to increase suicide ideation (SI), we know little about which sociodemographic characteristics or COVID...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Pergamon Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553642/ https://www.ncbi.nlm.nih.gov/pubmed/36252348 http://dx.doi.org/10.1016/j.jpsychires.2022.10.009 |
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author | Dolsen, Emily A. Nishimi, Kristen LeWinn, Kaja Z. Byers, Amy L. Tripp, Paige Woodward, Eleanor Khan, Amanda J. Marx, Brian P. Borsari, Brian Jiha, Ahmad Neylan, Thomas C. O'Donovan, Aoife |
author_facet | Dolsen, Emily A. Nishimi, Kristen LeWinn, Kaja Z. Byers, Amy L. Tripp, Paige Woodward, Eleanor Khan, Amanda J. Marx, Brian P. Borsari, Brian Jiha, Ahmad Neylan, Thomas C. O'Donovan, Aoife |
author_sort | Dolsen, Emily A. |
collection | PubMed |
description | The coronavirus disease 2019 (COVID-19) pandemic has created a global health crisis, with disproportionate effects on vulnerable sociodemographic groups. Although the pandemic is showing potential to increase suicide ideation (SI), we know little about which sociodemographic characteristics or COVID-19 experiences are associated with SI. Our United States-based sample (n = 837 adults [mean age = 37.1 years]) completed an online survey during August–September 2020. The study utilized an online convenience sample from a prior study, which was enriched for exposure to trauma and experiences of posttraumatic stress symptoms. We assessed SI using the Beck Depression Inventory-II. Traditional (i.e., logistic regression) and machine learning (i.e., LASSO, random forest) methods evaluated associations of 148 self-reported COVID-19 factors and sociodemographic characteristics with current SI. 234 participants (28.0%) reported SI. Twenty items were significantly associated with SI from logistic regression. Of these 20 items, LASSO identified seven sociodemographic characteristics (younger age, lower income, single relationship status, sexual orientation other than heterosexual as well as specifically identifying as bisexual, non-full-time employment, and living in a town) and six COVID-19 factors (not engaging in protective COVID-19 behaviors, receiving mental health treatment (medication and/or psychotherapy) due to the COVID-19 pandemic, socializing during the pandemic, losing one's job due to COVID-19, having a friend with COVID-19, and having an acquaintance with COVID-19) associated with SI. Random forest findings were largely consistent with LASSO. These findings may inform multidisciplinary research and intervention work focused on understanding and preventing adverse mental health outcomes such as SI during and in the aftermath of the pandemic. |
format | Online Article Text |
id | pubmed-9553642 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Pergamon Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-95536422022-10-12 Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors Dolsen, Emily A. Nishimi, Kristen LeWinn, Kaja Z. Byers, Amy L. Tripp, Paige Woodward, Eleanor Khan, Amanda J. Marx, Brian P. Borsari, Brian Jiha, Ahmad Neylan, Thomas C. O'Donovan, Aoife J Psychiatr Res Article The coronavirus disease 2019 (COVID-19) pandemic has created a global health crisis, with disproportionate effects on vulnerable sociodemographic groups. Although the pandemic is showing potential to increase suicide ideation (SI), we know little about which sociodemographic characteristics or COVID-19 experiences are associated with SI. Our United States-based sample (n = 837 adults [mean age = 37.1 years]) completed an online survey during August–September 2020. The study utilized an online convenience sample from a prior study, which was enriched for exposure to trauma and experiences of posttraumatic stress symptoms. We assessed SI using the Beck Depression Inventory-II. Traditional (i.e., logistic regression) and machine learning (i.e., LASSO, random forest) methods evaluated associations of 148 self-reported COVID-19 factors and sociodemographic characteristics with current SI. 234 participants (28.0%) reported SI. Twenty items were significantly associated with SI from logistic regression. Of these 20 items, LASSO identified seven sociodemographic characteristics (younger age, lower income, single relationship status, sexual orientation other than heterosexual as well as specifically identifying as bisexual, non-full-time employment, and living in a town) and six COVID-19 factors (not engaging in protective COVID-19 behaviors, receiving mental health treatment (medication and/or psychotherapy) due to the COVID-19 pandemic, socializing during the pandemic, losing one's job due to COVID-19, having a friend with COVID-19, and having an acquaintance with COVID-19) associated with SI. Random forest findings were largely consistent with LASSO. These findings may inform multidisciplinary research and intervention work focused on understanding and preventing adverse mental health outcomes such as SI during and in the aftermath of the pandemic. Pergamon Press 2022-12 2022-10-12 /pmc/articles/PMC9553642/ /pubmed/36252348 http://dx.doi.org/10.1016/j.jpsychires.2022.10.009 Text en Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Dolsen, Emily A. Nishimi, Kristen LeWinn, Kaja Z. Byers, Amy L. Tripp, Paige Woodward, Eleanor Khan, Amanda J. Marx, Brian P. Borsari, Brian Jiha, Ahmad Neylan, Thomas C. O'Donovan, Aoife Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors |
title | Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors |
title_full | Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors |
title_fullStr | Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors |
title_full_unstemmed | Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors |
title_short | Identifying correlates of suicide ideation during the COVID-19 pandemic: A cross-sectional analysis of 148 sociodemographic and pandemic-specific factors |
title_sort | identifying correlates of suicide ideation during the covid-19 pandemic: a cross-sectional analysis of 148 sociodemographic and pandemic-specific factors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553642/ https://www.ncbi.nlm.nih.gov/pubmed/36252348 http://dx.doi.org/10.1016/j.jpsychires.2022.10.009 |
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