ArticleTrends in molecular medicine2015
Mining the social mediome.
Article in Trends in molecular medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed.
- Digital phenotyping and ASCVD risk: An exploratory cross-sectional analysis using online behavioral data.American heart journal plus : cardiology research and practice · 2026Article
- Integrating Patient-Generated Digital Data Into Mental Health Therapy: Mixed Methods Analysis of User Experience.JMIR mental health · 2024Article
- Perspectives of Patients and Therapists on Social Media and Digital Data Use in Mental Health Therapy: Thematic Analysis.JMIR formative research · 2022Article
- Expressed Symptoms and Attitudes Toward Using Twitter for Health Care Engagement Among Patients With Lupus on Social Media: Protocol for a Mixed Methods Study.JMIR research protocols · 2021Article
- Predicting Cardiovascular Risk Using Social Media Data: Performance Evaluation of Machine-Learning Models.JMIR cardio · 2021Article
- Perspectives Toward Seeking Treatment Among Patients With Psoriasis: Protocol for a Twitter Content Analysis.JMIR research protocols · 2021Article
- Insights From Twitter Conversations on Lupus and Reproductive Health: Protocol for a Content Analysis.JMIR research protocols · 2020Article
- Variability in Language used on Social Media prior to Hospital Visits.Scientific reports · 2020Article
- Google search histories of patients presenting to an emergency department: an observational study.BMJ open · 2019Observational
- Article
- Novel Approach to Cluster Patient-Generated Data Into Actionable Topics: Case Study of a Web-Based Breast Cancer Forum.JMIR medical informatics · 2018Article
- An Application of Data Mining Techniques to Explore Congressional Lobbying Records for Patterns in Pediatric Special Interest Expenditures Prior to the Affordable Care Act.Frontiers in big data · 2018Article
- Digital Cohorts Within the Social Mediome: An Approach to Circumvent Conventional Research Challenges?Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2017Article
- The Future of Genetics and Genomics: Closing the Phenotype Gap in Precision Medicine.Circulation · 2016Review
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
The experiences and behaviors revealed in our everyday lives provide as much insight into health and disease as any analysis of our genome could ever produce. These characteristics are not found in the genome, but may be revealed in our online activities, which make up our social mediome.
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.