Evidence map›Paper›PMID 42416814›Full record

ArticleFrontiers in digital health2026

Life, death, and 280 characters: a hashtag analysis of #AssistedSuicide on X (2015-2025).

Elisa Opriessnig, Olena Litvinova, Zilin Ma, Yining Hua, ArunSundar MohanaSundaram, Maria Kletecka-Pulker, Atanas G Atanasov, Thomas Wochele-Thoma

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Elisa OpriessnigMedical University of Graz, Graz, Austria.
Olena LitvinovaDepartment of Management, Marketing and Quality Assurance in Pharmacy, National University of Pharmacy of the Ministry of Health of Ukraine, Kharkiv, Ukraine.
Zilin MaIntelligent Interactive Systems Group, Harvard School of Engineering and Applied Sciences, Allston, MA, United States.
Yining HuaDepartment of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, MA, United States.
ArunSundar MohanaSundaramSchool of Pharmacy, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India.
Maria Kletecka-PulkerLudwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.
Atanas G AtanasovLudwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.
Thomas Wochele-ThomaLudwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Population aging and the growing prevalence of chronic diseases pose significant challenges to the global healthcare system and highlight the relevance of issues related to the end-of-life stages. Social media is an important platform for discussing and exchanging views on these issues. This study aims to analyse public discourse on the X platform (formerly Twitter) between 2015 and 2025, based on the text content of posts (tweets) containing the hashtag #AssistedSuicide. Methods: A retrospective analysis was conducted on 105,130 posts containing #AssistedSuicide, published by 28,314 users on X between 2015 and 2025. Data were retrieved via Fedica (20 February 2025) and processed using Python 3. The study included quantitative content analysis, sentiment analysis, geographic distribution mapping, keyword and hashtag analysis, and assessment of legislative discourse and potential amplification patterns. Results: Most posts (99.1%) were in English. The highest activity was observed in the United Kingdom (39.48%), the United States (29.75%), Canada (13.94%), New Zealand (6.22%), and Australia (3.80%), accounting for 93.19% of all posts. Legislative-related content represented a substantial thematic category (38.7%) and also included issues concerning vulnerable populations. Analysis of frequently occurring words and hashtags shows that the discussion on #AssistedSuicide is multifaceted, polarized, and closely linked to legislative, medical, and social issues. The discourse is characterized by high sensitivity to political events and shifts in tone during periods of legislative activity. Conclusion: This study highlights the value of large-scale social media analysis for understanding public attitudes toward assisted suicide and identifying its ethical, social, and regulatory dimensions. Palliative care remains central to reducing suffering and preserving human dignity. The findings underscore the need for evidence-based policies that ensure protection of vulnerable groups, support healthcare professionals, and promote balanced end-of-life care frameworks.

Indexed as

assisted suicidedeathlifemental healthpalliative carepatient rightssocial media

Identifiers

PMID42416814
PMCPMC13337767

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.