ArticlePloS one2021
Characterising experiences with acute myeloid leukaemia using an Instagram content analysis.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Mapping Characteristics, Applications, and Implementation Challenges of Virtual Communities in Cancer Care: NASSS Framework-Informed Scoping Review.Journal of medical Internet research · 2025Article
- Instagram Posts Promoting Colorectal Cancer Awareness: Content Analysis of Themes and Engagement During Colorectal Cancer Awareness Month.JMIR formative research · 2025Article
- Reporting of Ethical Considerations in Qualitative Research Utilizing Social Media Data on Public Health Care: Scoping Review.Journal of medical Internet research · 2024Article
- Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review.Journal of medical Internet research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Instagram has more than one billion monthly users, which presents a unique research opportunity particularly in rare diseases or hard to reach populations. This study focuses on acute myeloid leukaemia, a rare haematological malignancy and aims to characterise who posts acute myeloid leukaemia-related content and the type of content created. The findings can provide information and a method for future studies, particularly those focused on online or social media based interventions. Acute myeloid leukaemia-related Instagram posts were identified by searching specific and relevant hashtags (#). A content analysis systematically classified themes in the data. A convenience sample of 100 posts (138 photos) were manually extracted and coded. Data are described using descriptive statistics and demonstrated by qualitative examples. The most frequent users in our sample were patients (66%), patient support networks (24%) and professional organisations (10%). Patients who were communicating their health update (31%) were the most frequently posted content and 25% of these posts described a symptom experience. Our findings demonstrate that patients and their support networks are frequenting Instagram and therefore may be able to receive and benefit from tailored intervention, however there is an identified gap in health-organisations participating in this virtual online community.
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Registered trials
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 Socratic graph.