ArticleBMC medical research methodology2022
Spontaneously generated online patient experience data - how and why is it being used in health research: an umbrella scoping review.
Article in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
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.
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Who cites it
9 citing papers in PubMed.
- Outcomes reported in interventional studies for mild cognitive impairment: a scoping umbrella review to inform core outcome set development.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Contested illness and communication: Positioning long Covid in online discussion forums.Journal of health psychology · 2026Article
- Opinion Mining of Erowid's Experience Reports on LSD and Psilocybin-Containing Mushrooms.Drug safety · 2025Article
- The experience and impact of living with idiopathic hypersomnia: A qualitative study of patient perspectives shared in online media.PloS one · 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
- Acupuncture Topics on Twitter (Currently X) in English and Japanese: Co-occurrence Network Analysis.Cureus · 2024Article
- The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review.JMIR research protocols · 2023Article
- Sentiment analysis of epidemiological surveillance reports on COVID-19 in Greece using machine learning models.Frontiers in public health · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeSocial media has led to fundamental changes in the way that people look for and share health related information. There is increasing interest in using this spontaneously generated patient experience data as a data source for health research. The aim was to summarise the state of the art regarding how and why SGOPE data has been used in health research. We determined the sites and platforms used as data sources, the purposes of the studies, the tools and methods being used, and any identified research gaps.
methodsA scoping umbrella review was conducted looking at review papers from 2015 to Jan 2021 that studied the use of SGOPE data for health research. Using keyword searches we identified 1759 papers from which we included 58 relevant studies in our review.
resultsData was used from many individual general or health specific platforms, although Twitter was the most widely used data source. The most frequent purposes were surveillance based, tracking infectious disease, adverse event identification and mental health triaging. Despite the developments in machine learning the reviews included lots of small qualitative studies. Most NLP used supervised methods for sentiment analysis and classification. Very early days, methods need development. Methods not being explained. Disciplinary differences - accuracy tweaks vs application. There is little evidence of any work that either compares the results in both methods on the same data set or brings the ideas together.
conclusionTools, methods, and techniques are still at an early stage of development, but strong consensus exists that this data source will become very important to patient centred health research.
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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.