Evidence map›Paper›PMID 29458394›Full record

ArticleImplementation science : IS2018

Twitter use at the 2016 Conference on the Science of Dissemination and Implementation in Health: analyzing #DIScience16.

Caitlin G Allen, Brittany Andersen, David A Chambers, Jacob Groshek, Megan C Roberts

Abstract read
In one paragraph

Article in Implementation science : IS, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Article
  5. Article
  6. [The Early Mobilization Network].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2020
    Review
  7. Article
  8. Article
  9. Communication About Hereditary Cancers on Social Media: A Content Analysis of Tweets About Hereditary Breast and Ovarian Cancer and Lynch Syndrome.Journal of cancer education : the official journal of the American Association for Cancer Education · 2020
    Article
  10. Article
  11. Article
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

5 authors.

Caitlin G AllenRollins School of Public Health, Emory University, 1518 Clifton Rd, Atlanta, GA, 30322, USA. caitlin.gloeckner.allen@emory.edu.ORCID 0000-0001-6985-0423
Brittany AndersenDivision of Emerging Media Studies, Boston University, 704 Commonwealth Avenue, Boston, MA, 02215, USA.
David A ChambersDivision of Cancer Control and Population Sciences, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, 20850, USA.
Jacob GroshekDivision of Emerging Media Studies, Boston University, 704 Commonwealth Avenue, Boston, MA, 02215, USA.
Megan C RobertsDivision of Cancer Control and Population Sciences, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, 20850, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPoor dissemination of research findings may hamper the reach and impact of scientific discoveries. One key emerging platform for research dissemination is social media, including Twitter. While Twitter and other social media are increasingly being used to disseminate research content presented during scientific conferences, few studies have investigated the extent to which these tools are used throughout conferences and how they are being used. The aim for this study was to better understand the use of Twitter during the 2016 Annual Conference on the Science of Dissemination and Implementation in Health (D&I conference).

methodsWe performed an analysis of Twitter use before, during, and after the 2016 D&I conference, which took place from December 14 to 15. All tweets (posted between December 1 and 31) that included the conference-specific hashtag (#DIScience16) were assessed. We identified 2639 tweets using the data analytics platform NUVI. We used NUVI software to generate statistics about reach, influence, mentions, and origin of the tweets. Individual tweet content was also assessed using DiscoverText and coded for disease category, implementation outcomes discussed, category of tweet, and conference track.

resultsA total of 2639 tweets were analyzed; 89.1% of the tweets were posted during the conference. A total of 389 unique users participated on Twitter, representing 31 states and 22 locations outside of the USA. Most (56.8%) tweets were re-tweets and were used for scientific promotion (50.6%). Key conference speakers and implementation outcomes (de-implementation, adaptation, and fidelity) were commonly discussed.

conclusionsOur findings reveal that Twitter was used as a platform during the D&I conference, both to facilitate conference discussion and to promote scientific ideas. This work contributes to the existing data analytics and implementation science literature in two major ways: (1) by advancing knowledge of how social media is used during annual academic conferences and (2) by providing a deeper understanding of themes and emerging areas of interest in the dissemination and implementation sciences. Knowing specific topics of interest can help planners and scientists better understand the landscape of current and future implementation research and encourage new research dissemination strategies.

Indexed as

Congresses as TopicInternetSocial MediaConsensusData MiningHumansInformation DisseminationRetrospective StudiesWashingtonData analyticsDisseminationHealthImplementation scienceSocial media

Identifiers

PMID29458394
PMCPMC5819210

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.