Evidence map›Paper›PMID 31940384›Full record

ArticlePloS one2020

Content shared on social media for national cancer survivors day 2018.

Roy Cherian, Gem Le, James Whall, Scarlett Gomez, Urmimala Sarkar

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Social media livestreaming to disseminate geriatrics research.Journal of the American Geriatrics Society · 2022
    Article
  5. Article
  6. Review
  7. Article
  8. Article
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

5 authors.

Roy CherianDepartment of Medicine, Division of General Internal Medicine University of California, San Francisco, Zuckerberg San Francisco General Hospital, San Francisco, California, United States of America.
Gem LeDepartment of Medicine, Division of General Internal Medicine University of California, San Francisco, Zuckerberg San Francisco General Hospital, San Francisco, California, United States of America.
James WhallCalifornia Northstate University College of Medicine, Elk Grove, California, United States of America.
Scarlett GomezDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, United States of America.
Urmimala SarkarDepartment of Medicine, Division of General Internal Medicine University of California, San Francisco, Zuckerberg San Francisco General Hospital, San Francisco, California, United States of America.ORCID 0000-0003-4213-4405

Funding

Improving Survivorship Care for Diverse Cancer Patients Cared for in Safety-net SettingsK24CA212294 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SARKAR, URMIMALA · 2017 to 2021
$831k
NCI NIH HHS K24 CA212294
6 · The paper itself

Abstract

backgroundStudies estimate that the number of cancer survivors will double by 2050 due to improvements in diagnostic accuracy and treatment efficacy. Despite the growing population of cancer survivors, there is a paucity of research regarding how these individuals experience the transition from active treatment to long-term surveillance. While research has explored this transition from more organized venues, such as support groups for cancer survivors, this paper explores the discourses surrounding cancer survivorship on social media, paying particular attention to how individuals who identify as cancer survivors represent their experience.

methodsWe identified social media posts relating to cancer survivorship on Twitter and Instagram in early June 2018, in order to coincide with National Cancer Survivorship Day on June 3, 2018. We used nine pre-selected hashtags to identify content. For each hashtag, we manually collected the 150 most recent posts from Twitter and the 100 most recent plus the top 9 posts from Instagram. Our preliminary sample included 1172 posts; after eliminating posts from one hashtag due to irrelevance, we were left with 1063 posts. We randomly sampled 200 of these to create a subset for analysis; after review for irrelevant posts, 193 posts remained for analysis (118 from Instagram and 75 from Twitter). We utilized a grounded theory approach to analyze the posts, first open-coding a subset to develop a codebook, then applying the codebook to the rest of the sample and finally memo writing to develop themes.

resultsOverall, there is substantial difference in the tone and thematic content between Instagram and Twitter posts, Instagram takes on a more narrative form that represents journeys through cancer treatment and subsequent survivorship, whereas Twitter is more factual, leaning towards advocacy, awareness and fundraising. In terms of content type, 120 posts (62%) of the sample were images, of which 42 (35%) were images of the individual posting and 28 (23%) were images of patients posted by family or friends. Of the remaining images, 14 (12%) were of support groups and 7 (6%) were of family or friends. We identified four salient themes through analysis of the social media posts from Twitter and Instagram: social support, celebrating milestones and honoring survivors, expressing identity, and renewal vs. rebirth. DISCUSSION: We observed a marked relationship between physical appearance, functional status and survivorship. Additionally, our findings suggest the importance of social support for cancer patients and survivors as well as the role social media can pay in identity formation.

conclusionOur findings suggest that individuals who identify as survivors on social media define their identity fluidly, incorporating elements of physical, emotional and psychological health as well as autonomy.

Indexed as

Cancer SurvivorsHumansSocial MediaSocial Support

Identifiers

PMID31940384
PMCPMC6961846

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.