Evidence map›Paper›PMID 40053739›Full record

ArticleJournal of medical Internet research2025

Exploring Psychological Trends in Populations With Chronic Obstructive Pulmonary Disease During COVID-19 and Beyond: Large-Scale Longitudinal Twitter Mining Study.

Chunyan Zhang, Ting Wang, Caixia Dong, Duwei Dai, Linyun Zhou, Zongfang Li, Songhua Xu

Abstract read
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Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Chunyan Zhang *The High School Affiliated to Xi'an Jiaotong University, Xi'an, China.ORCID 0000-0002-4485-0248
Ting Wang *School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, China.ORCID 0000-0002-5386-1918
Caixia DongInstitute of Medical Artificial Intelligence, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.ORCID 0000-0002-6353-7273
Duwei DaiInstitute of Medical Artificial Intelligence, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.ORCID 0000-0001-6351-4840
Linyun ZhouInstitute of Medical Artificial Intelligence, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.ORCID 0000-0001-6500-537X
Zongfang LiInstitute of Medical Artificial Intelligence, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.ORCID 0000-0003-4813-1176
Songhua XuInstitute of Medical Artificial Intelligence, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.ORCID 0000-0002-2276-2538

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic obstructive pulmonary disease (COPD) ranks among the leading causes of global mortality, and COVID-19 has intensified its challenges. Beyond the evident physical effects, the long-term psychological effects of COVID-19 are not fully understood.

objectiveThis study aims to unveil the long-term psychological trends and patterns in populations with COPD throughout the COVID-19 pandemic and beyond via large-scale Twitter mining.

methodsA 2-stage deep learning framework was designed in this study. The first stage involved a data retrieval procedure to identify COPD and non-COPD users and to collect their daily tweets. In the second stage, a data mining procedure leveraged various deep learning algorithms to extract demographic characteristics, hashtags, topics, and sentiments from the collected tweets. Based on these data, multiple analytical methods, namely, odds ratio (OR), difference-in-difference, and emotion pattern methods, were used to examine the psychological effects.

resultsA cohort of 15,347 COPD users was identified from the data that we collected in the Twitter database, comprising over 2.5 billion tweets, spanning from January 2020 to June 2023. The attentiveness toward COPD was significantly affected by gender, age, and occupation; it was lower in females (OR 0.91, 95% CI 0.87-0.94; P<.001) than in males, higher in adults aged 40 years and older (OR 7.23, 95% CI 6.95-7.52; P<.001) than in those younger than 40 years, and higher in individuals with lower socioeconomic status (OR 1.66, 95% CI 1.60-1.72; P<.001) than in those with higher socioeconomic status. Across the study duration, COPD users showed decreasing concerns for COVID-19 and increasing health-related concerns. After the middle phase of COVID-19 (July 2021), a distinct decrease in sentiments among COPD users contrasted sharply with the upward trend among non-COPD users. Notably, in the post-COVID era (June 2023), COPD users showed reduced levels of joy and trust and increased levels of fear compared to their levels of joy and trust in the middle phase of COVID-19. Moreover, males, older adults, and individuals with lower socioeconomic status showed heightened fear compared to their counterparts.

conclusionsOur data analysis results suggest that populations with COPD experienced heightened mental stress in the post-COVID era. This underscores the importance of developing tailored interventions and support systems that account for diverse population characteristics.

Indexed as

COVID-19Data MiningPulmonary Disease, Chronic ObstructiveSocial MediaAdultAgedDeep LearningFemaleHumansLongitudinal StudiesMaleMiddle AgedSARS-CoV-2chronic obstructive pulmonary disease (COPD)COVID-19data miningdeep learningpsychological trendsTwitter

Identifiers

PMID40053739
PMCPMC11923484

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.