SynthesisBritish journal of clinical pharmacology2015
Systematic review on the prevalence, frequency and comparative value of adverse events data in social media.
Synthesis in British journal of clinical pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
58 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Evaluating Messaging on Prenatal Health Behaviors Using Social Media Data: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Attitudes Toward the Ethics of Research Using Social Media: A Systematic Review.Journal of medical Internet research · 2017Pooled it
- Self-Reported Health Outcomes in Metabolic Health YouTube Comments: Cross-Sectional Study and Rule-Based Natural Language Processing Framework Development and Validation.Journal of medical Internet research · 2026Observational
- What do cancer patients discuss online regarding CINV management? A social media-based topic modeling study.Frontiers in oncology · 2026Article
- Signals of Adverse Reactions to Herbal Medicines: Evidence and Document Analysis Based on a Scoping Review.Drug safety · 2025Article
- On the Influence of Apologies on the Likelihood of Lawsuits in Cases of Perceived Medical Negligence: Analysis of Archival and Experimental Data.Journal of medical Internet research · 2025Article
- Understanding social media discourse on antidepressants: unsupervised and sentiment analysis using X.European psychiatry : the journal of the Association of European Psychiatrists · 2025Article
- Pharmacovigilance in the Age of Legalized Cannabis: Using Social Media to Monitor Drug-Drug Interactions Between Immunosuppressants and Cannabis-Derived Products.Drug safety · 2025Article
- Analysis of User-Generated Posts on Social Media of Adjuvant Analgesics: A Machine Learning Study.International journal of medical sciences · 2025Article
- 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
- The Value of Social Media Analysis for Adverse Events Detection and Pharmacovigilance: Scoping Review.JMIR public health and surveillance · 2024Article
- Patient-Reported Reasons for Antihypertensive Medication Change: A Quantitative Study Using Social Media.Drug safety · 2024Article
- Understanding Public Perceptions and Discussions on Opioids Through Twitter: Cross-Sectional Infodemiology Study.Journal of medical Internet research · 2023Article
- The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review.JMIR research protocols · 2023Article
- Reasons for Discontinuation or Change of Selective Serotonin Reuptake Inhibitors in Online Drug Reviews.JAMA network open · 2023Article
- Social media and internet search data to inform drug utilization: A systematic scoping review.Frontiers in digital health · 2023Article
- Sample Bias in Web-Based Patient-Generated Health Data of Dutch Patients With Gastrointestinal Stromal Tumor: Survey Study.JMIR formative research · 2022Article
- Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers.Database : the journal of biological databases and curation · 2022Article
- Patient-Reported Reasons for Switching or Discontinuing Statin Therapy: A Mixed Methods Study Using Social Media.Drug safety · 2022Article
- Automated gathering of real-world data from online patient forums can complement pharmacovigilance for rare cancers.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
aimThe aim of this review was to summarize the prevalence, frequency and comparative value of information on the adverse events of healthcare interventions from user comments and videos in social media.
methodsA systematic review of assessments of the prevalence or type of information on adverse events in social media was undertaken. Sixteen databases and two internet search engines were searched in addition to handsearching, reference checking and contacting experts. The results were sifted independently by two researchers. Data extraction and quality assessment were carried out by one researcher and checked by a second. The quality assessment tool was devised in-house and a narrative synthesis of the results followed.
resultsFrom 3064 records, 51 studies met the inclusion criteria. The studies assessed over 174 social media sites with discussion forums (71%) being the most popular. The overall prevalence of adverse events reports in social media varied from 0.2% to 8% of posts. Twenty-nine studies compared the results from searching social media with using other data sources to identify adverse events. There was general agreement that a higher frequency of adverse events was found in social media and that this was particularly true for 'symptom' related and 'mild' adverse events. Those adverse events that were under-represented in social media were laboratory-based and serious adverse events.
conclusionsReports of adverse events are identifiable within social media. However, there is considerable heterogeneity in the frequency and type of events reported, and the reliability or validity of the data has not been thoroughly evaluated.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.