2023
DOI: 10.2196/44774
|View full text |Cite
|
Sign up to set email alerts
|

Public Opinions About Palliative and End-of-Life Care During the COVID-19 Pandemic: Twitter-Based Content Analysis

Abstract: Background Palliative and end-of-life care (PEoLC) played a critical role in relieving distress and providing grief support in response to the heavy toll caused by the COVID-19 pandemic. However, little is known about public opinions concerning PEoLC during the pandemic. Given that social media have the potential to collect real-time public opinions, an analysis of this evidence is vital to guide future policy-making. Objective This study aimed to use s… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
1
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 97 publications
0
1
0
Order By: Relevance
“…They have enabled palliative and end-of-life care researchers to identify different palliative and end-of-life care stakeholders, 45 understand public sentiment, 15 extract demographic features 13 and conduct large-scale content analysis. 14 Additionally, more research tasks can be addressed by using natural language processing techniques. For example, several studies have made use of natural language processing technologies as applied to social media data to examine healthcare performance, 64 predict mental health states 65 and identify patient-reported symptoms.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…They have enabled palliative and end-of-life care researchers to identify different palliative and end-of-life care stakeholders, 45 understand public sentiment, 15 extract demographic features 13 and conduct large-scale content analysis. 14 Additionally, more research tasks can be addressed by using natural language processing techniques. For example, several studies have made use of natural language processing technologies as applied to social media data to examine healthcare performance, 64 predict mental health states 65 and identify patient-reported symptoms.…”
Section: Discussionmentioning
confidence: 99%
“…13 Advances in natural language processing technologies have enabled researchers to extract useful information from unstructured social media data such as demographic features, views and emotional sentiment of participants which provide valuable insights. [13][14][15] Despite promising benefits, when used as a tool for research, social media is open to criticism. While there is an increasing number of studies that have focused on how to conduct social media research, few studies have examined what constitutes high-quality and ethically responsible social media research.…”
Section: Systematic Reviewmentioning
confidence: 99%