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. 2024 Jan 16;28(1):75–77. doi: 10.1177/12034754231221988

Atopic Dermatitis Patient Needs Assessed through the Largest Online Patient Community: A Cross-Sectional Reddit Analysis

Maxine Joly-Chevrier 1, Safin Aly 1, Kaoutar Bahous 2, Philippe Lefrançois 3,4,5,
PMCID: PMC10908197  PMID: 38229271

To the Editor,

Atopic dermatitis (AD) is known as a high burden disease. 1 Patients are increasingly using social media to seek medical advice. 2 It is estimated that Reddit attracts more than 430 million users monthly. 3 Within Reddit, community groups are separated by topics named “subreddits.” The largest AD community is composed of approximately 72,000 users. Analyzing users’ posts with sentiment analysis may help physicians and AD organizations better assess and respond to patient needs.2,4,5

A total of 1128 random posts were retrieved from the subreddit “r/eczema.” Since its inception date in 2010, a minimum of 100 random posts per year were retrieved until 2021. For the year 2021, authors of the posts and associated 6730 comments were screened and categorized. A sentiment analysis was conducted on all posts using Natural Language Processing, an artificial intelligence field analyzing human language. The dataset was processed using Pandas, Natural Language Toolkit, and NRCLex, which are validated Python libraries (Supplementary Material). Following preprocessing steps (eg, removing special characters and tokenization), every post was assessed by emotion and sentiment polarity (positive, neutral, or negative).

Among the 1128 random posts analyzed, 533 (47.3%) were related to advice seeking [encompassing personal disease question (251, 22.2%), advice seeking for potential treatment (144, 12.8%), non-personal general disease question (81, 7.2%), and skin inquiry with picture (57, 5.1%)], 280 (24.8%) to emotional support, 107 (9.5%) to treatment update by patient, 101 (9.0%) to other topics [educational material (57, 5.1%), treatment promotion (18, 1.6%), survey (11, 1.0%), and prevention questions (15, 1.3%)], 69 (6.1%) to treatment recommendation by patient and 38 (3.4%) to humour (Figure 1). Posts had a median of 93 [interquartile range (IQR): 72, 100] upvotes, which translates to “likes.” Posts had a median of 24 [IQR: 7, 45] comments. Based on 6730 comments in 2021, most users who commented (6579, 99.8%) did not specifically self-describe as non-physicians and no self-reported dermatologists replied to these posts.

Figure 1.

Figure 1.

Post category distribution since year of online forum inception.

Fear, anger, surprise, sadness, disgust, and joy exhibited comparable baseline averages between 3% and 4% across posts. Trust was accentuated at 7%, whereas anticipation was consistently absent. Analyzing non-zero emotional presence, intensities heightened with fear (26%), anger (24%), disgust (24%), trust (32%), surprise (22%), sadness (23%), and joy (21%). In the realm of sentiment distribution, trust manifested itself in 1 out of every 5 posts, followed by fear (1/6 posts) and sadness (1/7 posts) (Table 1). Of all posts, 81% had a neutral sentiment, 8% were negative, and 10% were positive.

Table 1.

Emotional and Sentimental Analysis Results.

Metric Fear Anger Anticipation Trust Surprise Sadness Disgust Joy Negative Neutral Positive
Average of all posts (%) 4.15 2.79 0 6.51 2.75 3.37 2.56 3.75 8.23 81.26 10.43
Average of posts showing results (%) 26.01 24.28 0 32.36 21.62 23.19 23.56 21.19
Ratio of posts with results to total number of posts 16 19 0 15 18 17 19 16

The table shows the average of each emotion calculated by the NRClex emotional analysis tool present in all posts, the average of each emotion calculated from posts presenting results only, the ratio of posts presenting results calculated by the algorithm to the total number of posts and the sentiment score calculated by the algorithm implementation Valence Aware Dictionary for Sentiment Reasoning (VADER) named SentimentIntensityAnalyzer.

Users of the subreddit “r/eczema” represent an active international AD patient community regularly seeking medical and emotional support. Our sentiment analysis provides insights into the emotional dynamics of patient discussions with trust being the most present sentiment. The presence of dermatologists and AD organizations is limited, near non-existent, on this platform. Given the anonymous identity of users and commenters, the lack of verified medical advice may promote the propagation of false and/or inaccurate information. Dermatologists and medical organizations can benefit from such a large audience to rapidly engage with patients.

Supplemental Material

sj-docx-1-cms-10.1177_12034754231221988 – Supplemental material for Atopic Dermatitis Patient Needs Assessed through the Largest Online Patient Community: A Cross-Sectional Reddit Analysis

Supplemental material, sj-docx-1-cms-10.1177_12034754231221988 for Atopic Dermatitis Patient Needs Assessed through the Largest Online Patient Community: A Cross-Sectional Reddit Analysis by Maxine Joly-Chevrier, Safin Aly, Kaoutar Bahous and Philippe Lefrançois in Journal of Cutaneous Medicine and Surgery

Footnotes

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

IRB Approval Status: Exempt.

ORCID iD: Maxine Joly-Chevrier Inline graphic https://orcid.org/0000-0001-6706-8139

Supplemental Material: Supplemental material for this article is available online.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

sj-docx-1-cms-10.1177_12034754231221988 – Supplemental material for Atopic Dermatitis Patient Needs Assessed through the Largest Online Patient Community: A Cross-Sectional Reddit Analysis

Supplemental material, sj-docx-1-cms-10.1177_12034754231221988 for Atopic Dermatitis Patient Needs Assessed through the Largest Online Patient Community: A Cross-Sectional Reddit Analysis by Maxine Joly-Chevrier, Safin Aly, Kaoutar Bahous and Philippe Lefrançois in Journal of Cutaneous Medicine and Surgery


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