Evidence map›Paper›PMID 42335467›Full record

ArticleJMIR dermatology2026

Exploring the Lived Experience of Acne in the United States and the United Kingdom: Social Media Analysis.

John S Barbieri, Valentine Delore, Isabelle Vieillard, Sandrine Samson, Esteban Puentes, Joelle Malaab, Melanie Sambrès, Manissa Talmatkadi, Stéphane Schück

Abstract read
In one paragraph

Article in JMIR dermatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

John S BarbieriDepartment of Dermatology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.ORCID 0000-0002-5467-4102
Valentine DeloreGlobal Medical, Vaccines, Sanofi, Lyon, France.ORCID 0009-0008-1004-0360
Isabelle VieillardGlobal Medical, Vaccines, Sanofi, Lyon, France.ORCID 0009-0003-4626-8205
Sandrine SamsonGlobal Medical, Vaccines, Sanofi, Lyon, France.ORCID 0000-0001-8365-5093
Esteban PuentesGlobal Medical, Vaccines, Sanofi, Lyon, France.ORCID 0000-0001-9026-818X
Joelle MalaabKap Code, 4 rue de Cléry, Paris, 75002, France, 33 0764853053.ORCID 0000-0002-4489-0071
Melanie SambrèsKap Code, 4 rue de Cléry, Paris, 75002, France, 33 0764853053.ORCID 0009-0003-4026-481X
Manissa TalmatkadiKap Code, 4 rue de Cléry, Paris, 75002, France, 33 0764853053.ORCID 0000-0002-8019-6159
Stéphane SchückKap Code, 4 rue de Cléry, Paris, 75002, France, 33 0764853053.ORCID 0000-0003-2642-7726

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acne is a chronic skin condition that primarily affects adolescents and young adults but can persist into adulthood. It can have repercussions on physical and mental health, self-esteem, and body image. The increasing use of social media for health information and peer support offers an opportunity to explore real-life experiences with acne. Objective: This study aims to analyze social media messages from users in the United States and the United Kingdom using artificial intelligence to assess the impact of acne on quality of life (QoL), identify discussion topics, and explore unmet needs. Methods: The data were extracted from public platforms using a query containing the word "acne" between January 1 and December 31, 2024. Data cleaning and filtering were performed using natural language processing, machine learning methods, and algorithms. Biterm topic modeling was used to identify the main discussion topics, and QoL impact was assessed using a deep learning algorithm adapted from the EuroQol 5-Dimension Questionnaire or the 36-Item Short Form Health Survey. Unmet needs were identified through manual annotation using the saturation method. Results: A total of 646,809 messages posted by 432,234 users were identified. The main topics included skincare routines and product recommendations (n=154,907, 23.9%), acne scars (n=135,643, 21%), and general treatment information (n=97,177, 15%). Engagement varied across topics and platforms. On Instagram, dietary and nutritional strategies (0.16%, SD 6.36%) showed the highest mean engagement, followed by skincare routines and product recommendations (0.11%, SD 4.81%). In general, engagement scores were higher in the United Kingdom compared to the United States across all topics. On TikTok, content about makeup and acne had the highest mean engagement score (3.03%, SD 92.65%). Overall, 52.9% (228,613/432,234) of the users expressed at least 1 QoL impact, most frequently related to signs and symptoms (175,604/228,613, 76.8%), social functioning (n=149,234, 65.3%), mental health (n=107,155, 46.9%), and cost (n=62,008, 27.1%). Of 3200 annotated messages, 582 contained unmet needs, including effective solutions for hormonal acne (111/582, 19.1%), clarity in identifying acne triggers (n=84, 14.4%), treatment guidance (n=68, 11.7%), and psychological support (n=68, 11.7%). Conclusions: This study revealed the significant physical, psychological, social, and financial impact of acne on QoL and identified several unmet needs. Given the growing role of social media, these findings highlight opportunities for dermatologists and health professionals to educate and engage with the acne community through digital platforms.

Indexed as

Acne VulgarisQuality of LifeSocial MediaAdolescentAdultFemaleHumansMaleMedia ExposureSurveys and QuestionnairesUnited KingdomUnited StatesYoung Adultacnedermatologyinfodemiologymachine learningnatural language processingsocial media listening

Identifiers

PMID42335467
PMCPMC13290109

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.