ArticleJournal of medical Internet research2018
Detection of Cases of Noncompliance to Drug Treatment in Patient Forum Posts: Topic Model Approach.
Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.
- A systematic literature review of machine learning in online personal health data.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Exploring the Lived Experience of Acne in the United States and the United Kingdom: Social Media Analysis.JMIR dermatology · 2026Article
- Using Social Media Data to Assess the Impact of Infertility on French Patients' Quality of Life: Retrospective Observational Study.Journal of medical Internet research · 2025Observational
- Pharmacovigilance in the digital age: gaining insight from social media data.Experimental biology and medicine (Maywood, N.J.) · 2025Review
- Combining Topic Modeling, Sentiment Analysis, and Corpus Linguistics to Analyze Unstructured Web-Based Patient Experience Data: Case Study of Modafinil Experiences.Journal of medical Internet research · 2024Article
- Article
- Transferability Based on Drug Structure Similarity in the Automatic Classification of Noncompliant Drug Use on Social Media: Natural Language Processing Approach.Journal of medical Internet research · 2023Article
- Examining Analytic Practices in Latent Dirichlet Allocation Within Psychological Science: Scoping Review.Journal of medical Internet research · 2022Article
- Perceived Unmet Needs in Patients Living With Advanced Bladder Cancer and Their Caregivers: Infodemiology Study Using Data From Social Media in the United States.JMIR cancer · 2022Article
- A New Method to Extract Health-Related Quality of Life Data From Social Media Testimonies: Algorithm Development and Validation.Journal of medical Internet research · 2022Article
- Active neural networks to detect mentions of changes to medication treatment in social media.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Machine learning in medicine: a practical introduction to natural language processing.BMC medical research methodology · 2021Article
- Assessing Patient Perceptions and Experiences of Paracetamol in France: Infodemiology Study Using Social Media Data Mining.Journal of medical Internet research · 2021Article
- Exploring the Health-Related Quality of Life of Patients Treated With Immune Checkpoint Inhibitors: Social Media Study.Journal of medical Internet research · 2020Article
- Use of Social Media for Pharmacovigilance Activities: Key Findings and Recommendations from the Vigi4Med Project.Drug safety · 2020Article
- What are the main patient safety concerns of healthcare stakeholders: a mixed-method study of Web-based text.International journal of medical informatics · 2020Observational
- Infodemiology and Infoveillance: Scoping Review.Journal of medical Internet research · 2020Article
- Analysis of Answers to Queries among Anonymous Users with Gastroenterological Problems on an Internet Forum.International journal of environmental research and public health · 2020Article
- Discovering themes in medical records of patients with psychogenic non-epileptic seizures.BMJ neurology open · 2020Article
- Artificial Intelligence in Health: New Opportunities, Challenges, and Practical Implications.Yearbook of medical informatics · 2019Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMedication nonadherence is a major impediment to the management of many health conditions. A better understanding of the factors underlying noncompliance to treatment may help health professionals to address it. Patients use peer-to-peer virtual communities and social media to share their experiences regarding their treatments and diseases. Using topic models makes it possible to model themes present in a collection of posts, thus to identify cases of noncompliance.
objectiveThe aim of this study was to detect messages describing patients' noncompliant behaviors associated with a drug of interest. Thus, the objective was the clustering of posts featuring a homogeneous vocabulary related to nonadherent attitudes.
methodsWe focused on escitalopram and aripiprazole used to treat depression and psychotic conditions, respectively. We implemented a probabilistic topic model to identify the topics that occurred in a corpus of messages mentioning these drugs, posted from 2004 to 2013 on three of the most popular French forums. Data were collected using a Web crawler designed by Kappa Santé as part of the Detec't project to analyze social media for drug safety. Several topics were related to noncompliance to treatment.
resultsStarting from a corpus of 3650 posts related to an antidepressant drug (escitalopram) and 2164 posts related to an antipsychotic drug (aripiprazole), the use of latent Dirichlet allocation allowed us to model several themes, including interruptions of treatment and changes in dosage. The topic model approach detected cases of noncompliance behaviors with a recall of 98.5% (272/276) and a precision of 32.6% (272/844).
conclusionsTopic models enabled us to explore patients' discussions on community websites and to identify posts related with noncompliant behaviors. After a manual review of the messages in the noncompliance topics, we found that noncompliance to treatment was present in 6.17% (276/4469) of the posts.
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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.