Natural language processing of online support group postings reveals patients' perspectives on strategies for managing psoriasis

对在线互助小组帖子进行自然语言处理,揭示了患者对银屑病治疗策略的看法

阅读:1

Abstract

Psoriasis is a chronic skin disorder, and patients encounter high physical and psychosocial burdens. Social media forums feature extensive patient-generated comments. We hypothesized that analyzing patient-posted comments using natural language processing would provide insights into patient engagements, sentiments, concerns, and support, which are vital for the holistic management of psoriasis. We collected 32,000 active user comments posted on Reddit. We applied Latent Dirichlet Allocation to categorize posts into popular topics and employed spectral clustering to establish cohesive themes and word representation frequency within these topics. We sorted posts into 29 significant topics of discussion and categorized them into four categories: management (37.48%), emotion (21.57%), presentation (19.79%), and others (3.57%). The frequent posts on management were diet (7.23%), biologics (6.95%), and adverse effects (3.88%). The emotion category comprised negative sentiments (11.02%), encouragement (5.49%), and gratitude (5.06%). The presentation topic included a discussion of scalp (5.69%), flare-timing (3.63%), and arthritis (2.64%). Others comprised differential diagnosis (5.01%), leaky gut (4.12%), and referrals (3.70%). This study identified patients' experiences and perspectives associated with psoriasis, which should be considered to tailor support systems to improve their quality of life.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。