Evidence map›Paper›PMID 40785838›Full record

ArticlePatient preference and adherence2025

Exploring Melasma Patients' Needs Through Social Media: A Qualitative Study.

Xinjin Liu, Xu Liu, Yanbing Han, Yifei Cheng, Hongjie Luo, Yichen Liu, Dingling Li, Weihong Guo, Haoyu Jiang, Linghong Guo and 1 more

Abstract read
In one paragraph

Article in Patient preference and adherence, 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. Review
  2. Article
  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

11 authors.

Xinjin Liu *Department of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0009-0004-2901-8041
Xu Liu *Department of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0009-0003-7620-7323
Yanbing HanDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.
Yifei ChengDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.
Hongjie LuoDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.
Yichen LiuDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0009-0009-8737-3224
Dingling LiDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0009-0004-8271-1988
Weihong GuoDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0009-0003-6098-7417
Haoyu JiangDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0009-0003-3150-3225
Linghong GuoDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0000-0002-9248-5070
Xian JiangDepartment of Dermatology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0000-0001-5109-6055

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To identify the primary concerns and unmet needs of patients with melasma on social media using qualitative analysis and AI-based keyword extraction. Patients and Methods: We conducted a qualitative study of melasma patient discussions using publicly available posts on Facebook and Baidu. The data were collected between January 2014 and October 2024. ChatGPT-4o was used for keyword extraction and classification. Results: A total of 1106 related posts were analyzed, revealing 284 unique tags and 2434 keywords. Treatment and prevention were the most discussed topics, with patients seeking information on effective, long-term, and affordable treatment. Daily care and mental health accounted for 29.2% of the total, focusing on skincare routines, sun protection, and lifestyle modification. Etiology and clinical features were observed in 14.8% of the posts, whereas 2.4% addressed diagnosis and differentiation. Conclusion: This study identified key concerns of patients with melasma using AI-based keyword extraction and qualitative analysis, highlighting the need for healthcare professionals to engage in digital patient education, clarify misinformation, support patient self-management, and integrate mental health considerations into melasma care. Future research should focus on AI-based interventions to enhance patient engagement and self-management.

Indexed as

artificial intelligencedigital healthmelasmapatient educationsocial media

Identifiers

PMID40785838
PMCPMC12334853

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.