Evidence map›Paper›PMID 35077706›Full record

ArticleChest2022

Perceptions of Life Support and Advance Care Planning During the COVID-19 Pandemic: A Global Study of Twitter Users.

Vishal R Patel, Sofia Gereta, Christopher J Blanton, Alexander L Chu, Akash P Patel, Michael Mackert, David Zientek, Nico Nortjé, Anjum Khurshid, Christopher Moriates and 1 more

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In one paragraph

Article in Chest, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Vishal R PatelDepartment of Internal Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX. Electronic address: vishpatel97@utexas.edu.
Sofia GeretaDepartment of Internal Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX.
Christopher J BlantonDepartment of Internal Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX.
Alexander L ChuDepartment of Internal Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX.
Akash P PatelDepartment of Internal Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX.
Michael MackertCenter for Health Communication, Moody College of Communication, The University of Texas at Austin, Austin, TX.
David ZientekDepartment of Internal Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX.
Nico NortjéDepartment of Critical Care Medicine, Division of Anesthesiology and Critical Care, The University of Texas MD Anderson Cancer Center, Houston, TX.
Anjum KhurshidDepartment of Population Health, Dell Medical School, The University of Texas at Austin, Austin, TX.
Christopher MoriatesDepartment of Internal Medicine, Dell Medical School, The University of Texas at Austin, Austin, TX.
Gregory WallingfordDepartment of Internal Medicine, Section of Palliative Care, Dell Medical School, The University of Texas at Austin, Austin, TX.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has presented new challenges surrounding end-of-life planning and has been associated with increased online discussion about life support. RESEARCH QUESTION: How has online communication about advance care planning (ACP) and specific life-sustaining interventions (LSIs) changed during the pandemic? STUDY DESIGN AND

methodsConversations on Twitter containing references to LSIs (eg, "ECMO") or ACP (eg, "DNR/DNI") were collected between January 2019 and May 2021. User account metadata were used to predict user demographic information and to classify users as organizations, individuals, clinicians, or influencers. The number of impressions was compared across these user categories and the content of tweets analyzed by using natural language processing models to identify topics of discussion and associated emotional sentiment.

resultsThere were 202,585 unique tweets about LSIs and 67,162 unique tweets about ACP. Users who were younger, male, or influencers were more likely to discuss LSIs online. Tweets about LSIs were associated with more positive emotional sentiment scores than tweets about ACP (LSIs, 0.3; ACP, -0.2; P < .001). Among tweets about ACP, most contained personal experiences related to the death of loved ones (27%) or discussed discrimination through do-not-resuscitate orders directed at the elderly and disabled (19%). Personal experiences had the greatest retweet-to-tweet-ratio (4.7), indicating high levels of user engagement. Tweets about discrimination contained the most negative net sentiment score (-0.5).

interpretationThe observed increase in tweets regarding LSIs and ACP suggests that Twitter was consistently used to discuss treatment modalities and preferences related to intensive care during the pandemic. Future interventions to increase online engagement with ACP may consider leveraging influencers and personal stories. Finally, we identified do-not-resuscitate-related discrimination as a commonly held public fear, which should be further explored as a barrier to ACP completion and can be proactively addressed by clinicians during bedside goals-of-care discussions.

Indexed as

Advance Care PlanningCOVID-19Social MediaAgedCommunicationHumansMalePandemicsCOVID-19decision-makingend of lifemechanical ventilationmedical informatics

Identifiers

PMID35077706
PMCPMC8783527

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.