Evidence map›Paper›PMID 27854532›Full record

SynthesisAmerican journal of public health2017

Twitter as a Tool for Health Research: A Systematic Review.

Lauren Sinnenberg, Alison M Buttenheim, Kevin Padrez, Christina Mancheno, Lyle Ungar, Raina M Merchant

Registry-linked trialAbstract readSystematic Review
In one paragraph

Synthesis in American journal of public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05442762 (A Social Media-based Machine Learning Study to Monitor Vaccine Confidence and Hesitancy and Early Warn Emerging Vaccine-related Risks in Real Time), which is not on this map. Cited by 310 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
310citing papers in PubMed, 7 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

NCT05442762 withdrawnnot on this mapstarted 2022, after this paper: background citation

A Social Media-based Machine Learning Study to Monitor Vaccine Confidence and Hesitancy and Early Warn Emerging Vaccine-related Risks in Real Time

TypeobservationalSponsorFudan UniversityRan2022 to 2022Enrolled0ConditionsSocial Medium, Data Collection, Patient Acceptance of Health Care, Immunization Programs
3 · Its place in the literature

Who cites it

310 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Social Media Use for Health Purposes: Systematic Review.Journal of medical Internet research · 2021
    Pooled it
  7. Pooled it
  8. Trial
  9. Article
  10. Article
  11. Observational
  12. Article
  13. Article
  14. Article
  15. Observational
  16. Review
  17. Article
  18. Article
  19. Digital phenotyping and ASCVD risk: An exploratory cross-sectional analysis using online behavioral data.American heart journal plus : cardiology research and practice · 2026
    Article
  20. Article

250 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lauren SinnenbergLauren Sinnenberg, Kevin Padrez, Christina Mancheno, and Raina M. Merchant are with Penn Medicine Social Media and Health Innovation Lab, University of Pennsylvania, Philadelphia. Lyle Ungar is with the Department of Computer and Information Science, University of Pennsylvania. Alison M. Buttenheim is with Department of Family and Community Health, School of Nursing, University of Pennsylvania, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania.
Alison M ButtenheimLauren Sinnenberg, Kevin Padrez, Christina Mancheno, and Raina M. Merchant are with Penn Medicine Social Media and Health Innovation Lab, University of Pennsylvania, Philadelphia. Lyle Ungar is with the Department of Computer and Information Science, University of Pennsylvania. Alison M. Buttenheim is with Department of Family and Community Health, School of Nursing, University of Pennsylvania, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania.
Kevin PadrezLauren Sinnenberg, Kevin Padrez, Christina Mancheno, and Raina M. Merchant are with Penn Medicine Social Media and Health Innovation Lab, University of Pennsylvania, Philadelphia. Lyle Ungar is with the Department of Computer and Information Science, University of Pennsylvania. Alison M. Buttenheim is with Department of Family and Community Health, School of Nursing, University of Pennsylvania, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania.
Christina ManchenoLauren Sinnenberg, Kevin Padrez, Christina Mancheno, and Raina M. Merchant are with Penn Medicine Social Media and Health Innovation Lab, University of Pennsylvania, Philadelphia. Lyle Ungar is with the Department of Computer and Information Science, University of Pennsylvania. Alison M. Buttenheim is with Department of Family and Community Health, School of Nursing, University of Pennsylvania, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania.
Lyle UngarLauren Sinnenberg, Kevin Padrez, Christina Mancheno, and Raina M. Merchant are with Penn Medicine Social Media and Health Innovation Lab, University of Pennsylvania, Philadelphia. Lyle Ungar is with the Department of Computer and Information Science, University of Pennsylvania. Alison M. Buttenheim is with Department of Family and Community Health, School of Nursing, University of Pennsylvania, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania.
Raina M MerchantLauren Sinnenberg, Kevin Padrez, Christina Mancheno, and Raina M. Merchant are with Penn Medicine Social Media and Health Innovation Lab, University of Pennsylvania, Philadelphia. Lyle Ungar is with the Department of Computer and Information Science, University of Pennsylvania. Alison M. Buttenheim is with Department of Family and Community Health, School of Nursing, University of Pennsylvania, and Center for Health Incentives and Behavioral Economics, University of Pennsylvania.

Funding

Twitter and Cardiovascular HealthR01HL122457 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI MERCHANT, RAINA · 2015 to 2017
$2.1M
NHLBI NIH HHS R01 HL122457
6 · The paper itself

Abstract

backgroundResearchers have used traditional databases to study public health for decades. Less is known about the use of social media data sources, such as Twitter, for this purpose.

objectivesTo systematically review the use of Twitter in health research, define a taxonomy to describe Twitter use, and characterize the current state of Twitter in health research. SEARCH

methodsWe performed a literature search in PubMed, Embase, Web of Science, Google Scholar, and CINAHL through September 2015. SELECTION CRITERIA: We searched for peer-reviewed original research studies that primarily used Twitter for health research. DATA COLLECTION AND ANALYSIS: Two authors independently screened studies and abstracted data related to the approach to analysis of Twitter data, methodology used to study Twitter, and current state of Twitter research by evaluating time of publication, research topic, discussion of ethical concerns, and study funding source. MAIN

resultsOf 1110 unique health-related articles mentioning Twitter, 137 met eligibility criteria. The primary approaches for using Twitter in health research that constitute a new taxonomy were content analysis (56%; n = 77), surveillance (26%; n = 36), engagement (14%; n = 19), recruitment (7%; n = 9), intervention (7%; n = 9), and network analysis (4%; n = 5). These studies collectively analyzed more than 5 billion tweets primarily by using the Twitter application program interface. Of 38 potential data features describing tweets and Twitter users, 23 were reported in fewer than 4% of the articles. The Twitter-based studies in this review focused on a small subset of data elements including content analysis, geotags, and language. Most studies were published recently (33% in 2015). Public health (23%; n = 31) and infectious disease (20%; n = 28) were the research fields most commonly represented in the included studies. Approximately one third of the studies mentioned ethical board approval in their articles. Primary funding sources included federal (63%), university (13%), and foundation (6%).

conclusionsWe identified a new taxonomy to describe Twitter use in health research with 6 categories. Many data elements discernible from a user's Twitter profile, especially demographics, have been underreported in the literature and can provide new opportunities to characterize the users whose data are analyzed in these studies. Twitter-based health research is a growing field funded by a diversity of organizations. Public health implications. Future work should develop standardized reporting guidelines for health researchers who use Twitter and policies that address privacy and ethical concerns in social media research.

Indexed as

Biomedical ResearchSocial MediaHumansInformation DisseminationPublic Health SurveillancePublic Opinion

Identifiers

PMID27854532
PMCPMC5308155

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.