ArticleFrontiers in public health2021
Leveraging Text Mining Approach to Identify What People Want to Know About Mental Disorders From Online Inquiry Platforms.
Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Medical short text classification via Soft Prompt-tuning.Frontiers in medicine · 2025Article
- Advancing psychosocial disability and psychosocial rehabilitation research through large language models and computational text mining.Global mental health (Cambridge, England) · 2024Article
- Depression, anxiety, and burnout in academia: topic modeling of PubMed abstracts.Frontiers in research metrics and analytics · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Online inquiry platforms, which is where a person can anonymously ask questions, have become an important information source for those who are concerned about social stigma and discrimination that follow mental disorders. Therefore, examining what people inquire about regarding mental disorders would be useful when designing educational programs for communities. The present study aimed to examine the contents of the queries regarding mental disorders that were posted on online inquiry platforms. A total of 4,714 relevant queries from the two major online inquiry platforms were collected. We computed word frequencies, centralities, and latent Dirichlet allocation (LDA) topic modeling. The words like symptom, hospital and treatment ranked as the most frequently used words, and the word my appeared to have the highest centrality. LDA identified four latent topics: (1) the understanding of general symptoms, (2) a disability grading system and welfare entitlement, (3) stressful life events, and (4) social adaptation with mental disorders. People are interested in practical information concerning mental disorders, such as social benefits, social adaptation, more general information about the symptoms and the treatments. Our findings suggest that instructions encompassing different scopes of information are needed when developing educational programs.
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Registered trials
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