Evidence map›Paper›PMID 36472899›Full record

ArticleJMIR cancer2022

How TikTok Is Being Used to Help Individuals Cope With Breast Cancer: Cross-sectional Content Analysis.

Corey H Basch, Grace C Hillyer, Bhavya Yalamanchili, Aldean Morris

Open access · goldAbstract read
In one paragraph

Article in JMIR cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.1field-weighted citation impact, top 5% of its field
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

14 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. The use of social media interventions for breast cancer survivors: a narrative review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Review
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  9. TikTok as a platform for hysteroscopy information: An analytical video-based cross-sectional study to assess quality, reliability, and accuracy.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
    Article
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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

4 authors at 2 institutions in 1 country.

Corey H BaschDepartment of Public Health, William Paterson University, Wayne, NJ, United States.ORCID https://orcid.org/0000-0003-4862-4229
Grace C HillyerDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States.ORCID https://orcid.org/0000-0003-0467-075X
Bhavya YalamanchiliDepartment of Public Health, William Paterson University, Wayne, NJ, United States.ORCID https://orcid.org/0000-0002-8660-3907
Aldean MorrisDepartment of Public Health, William Paterson University, Wayne, NJ, United States.ORCID https://orcid.org/0000-0003-1887-2870
William Paterson University · USColumbia University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcknowledging the popularity of TikTok, how quickly medical information can spread, and how users seek support on social media, there is a clear lack of research on breast cancer conversations on TikTok. There is a paucity of information on how these videos can advocate for those impacted by breast cancer as a means to provide support and information as well as raise awareness.

objectiveThe purpose of this cross-sectional content analysis was to describe the content of videos from the hashtag #breastcancer on TikTok. Content related to breast cancer support and coping, cancer education, and heightening the awareness of breast cancer early detection, prevention, and treatment was evaluated.

methodsThis study included 100 of the most viewed TikTok videos related to breast cancer through June 30, 2022. Videos were excluded if they were not in the English language or relevant to the topic being studied. Content was deductively coded into categories related to video characteristics and content topics using a screener based on expert breast cancer information sheets. Univariable analyses were conducted to evaluate differences in video characteristics and content when stratified as advocating or not advocating for breast cancer (yes or no) support, education, and awareness.

resultsThe cumulative number of views of the videos included in this study was 369,504,590. The majority (n=81, 81%) of videos were created by patients and loved ones of individuals with breast cancer, and the most commonly discussed topic was breast cancer support (n=88, 88%), followed by coping with the myriad issues surrounding breast cancer (n=79, 79%). Overall, <50% of the videos addressed important issues such as body image (n=48, 48%), surgery (n=46, 46%), medication and therapy (n=41, 41%), or the stigma associated with a breast cancer diagnosis (n=44, 44%); however, in videos that were advocacy oriented, body image (40/62, 64% vs 8/38, 21%; P<.001), stigma associated with breast cancer (33/62, 53% vs 11/38, 29%; P=.02), and breast cancer surgery (36/62, 58% vs 10/38, 26%; P=.002) were discussed significantly more often than in videos that did not specifically advocate for breast cancer.

conclusionsThe use of videos to display health journeys can facilitate engagement by patients, family members, and loved ones interested in information about challenging conditions. Collectively, these findings highlight the level of peer-to-peer involvement on TikTok and may provide insights for designing breast cancer educational campaigns.

Indexed as

breast cancercontent analysishealth informationmedical informationonline conversationonline health informationpatient supportpeer supportshort video appssocial mediasocial supportTikTokvideo

Identifiers

PMID36472899
PMCPMC9768649
OpenAlexW4310947449

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.