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Using Ecological and Twitter-Based Assessments to Examine Impacts in Temporal and Community Context

In March 2020, Bronx County (NY) saw one of the first U.S. COVID-19 outbreaks. This outbreak coincided with the ongoing Einstein Aging Study (EAS), which involved older adults living in Bronx County completing annual two-week intensive data collection “bursts.” Thus, it serves as a natural experimen...

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Autores principales: Bouklas, Isabella, Ferguson, Giselle, Pasquini, Giancarlo, Vu, Huy, Zamani, Mohammadzaman, Zhaoyang, Ruixue, Scott, Stacey, Schwartz, H Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8679347/
http://dx.doi.org/10.1093/geroni/igab046.053
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author Bouklas, Isabella
Ferguson, Giselle
Pasquini, Giancarlo
Vu, Huy
Zamani, Mohammadzaman
Zhaoyang, Ruixue
Scott, Stacey
Schwartz, H Andrew
author_facet Bouklas, Isabella
Ferguson, Giselle
Pasquini, Giancarlo
Vu, Huy
Zamani, Mohammadzaman
Zhaoyang, Ruixue
Scott, Stacey
Schwartz, H Andrew
author_sort Bouklas, Isabella
collection PubMed
description In March 2020, Bronx County (NY) saw one of the first U.S. COVID-19 outbreaks. This outbreak coincided with the ongoing Einstein Aging Study (EAS), which involved older adults living in Bronx County completing annual two-week intensive data collection “bursts.” Thus, it serves as a natural experiment to study pre-COVID to early pandemic-related changes in the daily well-being of participants who were at risk both due to their age and their location. We examined within-person change in self-reported negative thoughts, affect, stress, and loneliness from a subsample of 78 EAS participants. Participants’ data from a two-week “burst” of momentary surveys during 2019 were compared with their data from the corresponding timeframe during the early COVID-19 period (February-June 2020). Personality and mild cognitive impairment were examined as predictors of change. Average momentary loneliness significantly increased from 2019 to 2020. Participants with greater neuroticism increased more in thought unpleasantness and depressed feelings. To understand the community context, community distress markers were analyzed using Artificial Intelligence (AI)-based assessments of public Twitter posts from Bronx County during the same periods. These Twitter posts also showed a surge of COVID-related topics at the onset of the Bronx outbreak. Language analysis showed a 2019-2020 increase in Bronx community markers of anxiety, depressivity, and negatively-valenced affect extracted from Twitter. We observed 2019-2020 change in both individuals’ well-being (via intensive reports) and in their communities (via Twitter). Contextualizing these with the increased COVID-19 discussion online suggests that these may reflect common pandemic effects.
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spelling pubmed-86793472021-12-17 Using Ecological and Twitter-Based Assessments to Examine Impacts in Temporal and Community Context Bouklas, Isabella Ferguson, Giselle Pasquini, Giancarlo Vu, Huy Zamani, Mohammadzaman Zhaoyang, Ruixue Scott, Stacey Schwartz, H Andrew Innov Aging Abstracts In March 2020, Bronx County (NY) saw one of the first U.S. COVID-19 outbreaks. This outbreak coincided with the ongoing Einstein Aging Study (EAS), which involved older adults living in Bronx County completing annual two-week intensive data collection “bursts.” Thus, it serves as a natural experiment to study pre-COVID to early pandemic-related changes in the daily well-being of participants who were at risk both due to their age and their location. We examined within-person change in self-reported negative thoughts, affect, stress, and loneliness from a subsample of 78 EAS participants. Participants’ data from a two-week “burst” of momentary surveys during 2019 were compared with their data from the corresponding timeframe during the early COVID-19 period (February-June 2020). Personality and mild cognitive impairment were examined as predictors of change. Average momentary loneliness significantly increased from 2019 to 2020. Participants with greater neuroticism increased more in thought unpleasantness and depressed feelings. To understand the community context, community distress markers were analyzed using Artificial Intelligence (AI)-based assessments of public Twitter posts from Bronx County during the same periods. These Twitter posts also showed a surge of COVID-related topics at the onset of the Bronx outbreak. Language analysis showed a 2019-2020 increase in Bronx community markers of anxiety, depressivity, and negatively-valenced affect extracted from Twitter. We observed 2019-2020 change in both individuals’ well-being (via intensive reports) and in their communities (via Twitter). Contextualizing these with the increased COVID-19 discussion online suggests that these may reflect common pandemic effects. Oxford University Press 2021-12-17 /pmc/articles/PMC8679347/ http://dx.doi.org/10.1093/geroni/igab046.053 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Bouklas, Isabella
Ferguson, Giselle
Pasquini, Giancarlo
Vu, Huy
Zamani, Mohammadzaman
Zhaoyang, Ruixue
Scott, Stacey
Schwartz, H Andrew
Using Ecological and Twitter-Based Assessments to Examine Impacts in Temporal and Community Context
title Using Ecological and Twitter-Based Assessments to Examine Impacts in Temporal and Community Context
title_full Using Ecological and Twitter-Based Assessments to Examine Impacts in Temporal and Community Context
title_fullStr Using Ecological and Twitter-Based Assessments to Examine Impacts in Temporal and Community Context
title_full_unstemmed Using Ecological and Twitter-Based Assessments to Examine Impacts in Temporal and Community Context
title_short Using Ecological and Twitter-Based Assessments to Examine Impacts in Temporal and Community Context
title_sort using ecological and twitter-based assessments to examine impacts in temporal and community context
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8679347/
http://dx.doi.org/10.1093/geroni/igab046.053
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