Evidence map›Paper›PMID 40112288›Full record

ArticleJMIR infodemiology2025

Exploring the Use of Social Media for Medical Problem Solving by Analyzing the Subreddit r/medical_advice: Quantitative Analysis.

Xiyu Zhao, Victor Yang, Arjun Menta, Jacob Blum, Padmini Ranasinghe

Abstract read
In one paragraph

Article in JMIR infodemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Observational
  3. 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.

Xiyu ZhaoSchool of Medicine, The Johns Hopkins University, Baltimore, MD, United States.ORCID 0000-0002-7468-8456
Victor YangSchool of Medicine, The Johns Hopkins University, Baltimore, MD, United States.ORCID 0000-0002-4869-609X
Arjun MentaSchool of Medicine, The Johns Hopkins University, Baltimore, MD, United States.ORCID 0000-0002-6371-6052
Jacob BlumSchool of Medicine, The Johns Hopkins University, Baltimore, MD, United States.ORCID 0000-0003-0140-5555
Padmini RanasingheSchool of Medicine, The Johns Hopkins University, Baltimore, MD, United States.ORCID 0000-0003-0224-3850

Funding

CTSA Predoctoral T32 at Johns HopkinsT32TR004928 · NCATS · JOHNS HOPKINS UNIVERSITY · PI Meredith Ann Atkinson · 2024 to 2026
$1.6M
NCATS NIH HHS T32 TR004928
6 · The paper itself

Abstract

backgroundThe advent of the internet has transformed the landscape of health information acquisition and sharing. Reddit has become a hub for such activities, such as the subreddit r/medical_advice, affecting patients' knowledge and decision-making. While the popularity of these platforms is recognized, research into the interactions and content within these communities remains sparse. Understanding the dynamics of these platforms is crucial for improving online health information quality.

objectiveThis study aims to quantitatively analyze the subreddit r/medical_advice to characterize the medical questions posed and the demographics of individuals providing answers. Insights into the subreddit's user engagement, information-seeking behavior, and the quality of shared information will contribute to the existing body of literature on health information seeking in the digital era.

methodsA cross-sectional study was conducted, examining all posts and top comments from r/medical_advice since its creation on October 1, 2011. Data were collected on March 2, 2023, from pushhift.io, and the analysis included post and author flairs, scores, and engagement metrics. Statistical analyses were performed using RStudio and GraphPad Prism 9.0.

resultsFrom October 2011 to March 2023, a total of 201,680 posts and 721,882 comments were analyzed. After excluding autogenerated posts and comments, 194,678 posts and 528,383 comments remained for analysis. A total of 41% (77,529/194,678) of posts had no user flairs, while only 0.1% (108/194,678) of posts were made by verified medical professionals. The average engagement per post was a score of 2 (SD 7.03) and 3.32 (SD 4.89) comments. In period 2, urgent questions and those with level-10 pain reported higher engagement, with significant differences in scores and comments based on flair type (P<.001). Period 3 saw the highest engagement in posts related to pregnancy and the lowest in posts about bones, joints, or ligaments. Media inclusion significantly increased engagement, with video posts receiving the highest interaction (P<.001).

conclusionsThe study reveals a significant engagement with r/medical_advice, with user interactions influenced by the type of query and the inclusion of visual media. High engagement with posts about pregnancy and urgent medical queries reflects a focused public interest and the subreddit's role as a preliminary health information resource. The predominance of nonverified medical professionals providing information highlights a shift toward community-based knowledge exchange, though it raises questions about the reliability of the information. Future research should explore cross-platform behaviors and the impact of misinformation on public health. Effective moderation and the involvement of verified medical professionals are recommended to enhance the subreddit's role as a reliable health information resource.

Indexed as

Consumer Health InformationInformation Seeking BehaviorProblem SolvingSocial MediaAdultCross-Sectional StudiesFemaleHumansInformation DisseminationMaleMiddle Agedcross-sectional studydecision-makinghealth informationhealth information–seeking behaviorinformation qualitymedical advicemedical problemonline healthonline health informationpatient educationquantitative analysesRedditr/medical_advicesocial mediasocial newssubredditsuser-generated contentuser interactionsvirtual environments

Identifiers

PMID40112288
PMCPMC11969121

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.