cris.boxmetadata.label.title
Identifying Silver Linings During the Pandemic Through Natural Language Processing
cris.boxmetadata.label.dateissued
03 browse.startsWith.months.september 2021
cris.boxmetadata.label.accesslevel
open access
cris.boxmetadata.label.resourcetype
journal article
cris.boxmetadata.label.authors
Stanford University
cris.boxmetadata.label.publisher
Frontiers Media S.A.
cris.boxmetadata.label.abstract
COVID-19 has presented an unprecedented challenge to human welfare. Indeed, we have witnessed people experiencing a rise of depression, acute stress disorder, and worsening levels of subclinical psychological distress. Finding ways to support individuals' mental health has been particularly difficult during this pandemic. An opportunity for intervention to protect individuals' health & well-being is to identify the existing sources of consolation and hope that have helped people persevere through the early days of the pandemic. In this paper, we identified positive aspects, or “silver linings,” that people experienced during the COVID-19 crisis using computational natural language processing methods and qualitative thematic content analysis. These silver linings revealed sources of strength that included finding a sense of community, closeness, gratitude, and a belief that the pandemic may spur positive social change. People's abilities to engage in benefit-finding and leverage protective factors can be bolstered and reinforced by public health policy to improve society's resilience to the distress of this pandemic and potential future health crises.
cris.boxmetadata.label.volume
12
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Salud pública, Salud ambiental
Psiquiatría
cris.boxmetadata.label.subjects
cris.boxmetadata.label.doi
cris.boxmetadata.label.scopusidentifier
2-s2.0-85115122942
cris.boxmetadata.label.source
Frontiers in Psychology
cris.boxmetadata.label.containerissn
16641078
cris.boxmetadata.label.sponsor
We would like to thank Mark York, who worked as research assistant in the Social Media Lab at Stanford University, for helping annotate the data. Funding. Research reported in this publication was supported by the (1) National Cancer Institute of the National Institutes of Health under Award Number DP2CA225433 and (2) National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under Award Number K24AR075060. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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