What Does "Palliative" Mean? Sentiment, Knowledge, and Public Perception Concerning Palliative Care on the Internet since the COVID-19 Pandemic.

Abstract

Background: Little is known about the public perception of palliative care during and after the pandemic. Assuming that analyzing online language data has the potential to collect real-time public opinions, an analysis of large online datasets can be beneficial to guide future policymaking.

Objectives: To identify long-term effects of the COVID-19 pandemic on the public perception of palliative care and palliative care-related misconceptions on the Internet (worldwide) through natural language processing (NLP).

Design: Using large language model NLP analysis, we identified public attitudes, opinions, sentiment, and misconceptions about palliative care on the Internet, comparing a corpus of English-language web texts and X-posts ("tweets") (02/2020-02/2022) with similar samples before (02/2018-02/2020) and after the pandemic (03/2022-02/2024).

Setting: The study is a statistical analysis of website and social media data, conducted on six large language corpora.

Results: Since the COVID-19 pandemic, palliative care situations are more often portrayed as frightening, uncertain, and stressful, misconceptions about the activities and aims of palliative care occur on average 44% more frequently, especially on the social media platform X.

Conclusions: The impact of the COVID-19 pandemic on public discussion on social media continues to persist even in 2024. Insights from online NLP analysis helped to determine the image of palliative care in the Internet discourse and can help find ways to react to certain trends such as the spread of negative attitudes and misconceptions.