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      Factors associated with online media attention to research: a cohort study of articles evaluating cancer treatments

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          Abstract

          Background

          New metrics have been developed to assess the impact of research and provide an indication of online media attention and data dissemination. We aimed to describe online media attention of articles evaluating cancer treatments and identify the factors associated with high online media attention.

          Methods

          We systematically searched MEDLINE via PubMed on March 1, 2015 for articles published during the first 6 months of 2014 in oncology and medical journals with a diverse range of impact factors, from 3.9 to 54.4, and selected a sample of articles evaluating a cancer treatment regardless of study design. Altmetric Explorer was used to identify online media attention of selected articles. The primary outcome was media attention an article received online as measured by Altmetric score (i.e., number of mentions in online news outlets, science blogs and social media). Regression analysis was performed to investigate the factors associated with high media attention, and regression coefficients represent the logarithm of ratio of mean (RoM) values of Altmetric score per unit change in the covariate.

          Results

          Among 792 articles, 218 (27.5%) received no online media attention (Altmetric score = 0). The median [Q1–Q3] Altmetric score was 2.0 [0.0–8.0], range 0.0–428.0. On multivariate analysis, factors associated with high Altmetric score were presence of a press release (RoM = 10.14, 95%CI [4.91–20.96]), open access to the article (RoM = 1.48, 95%CI [1.02–2.16]), and journal impact factor (RoM = 1.10, 95%CI [1.07–1.12]. As compared with observational studies, systematic reviews were not associated with high Altmetric score (RoM = 1.46, 95%CI [0.74–2.86]; P = 0.27), nor were RCTs (RoM = 0.65, 95%CI [0.41–1.02]; P = 0.059) and phase I/II non-RCTs (RoM = 0.58, 95%CI [0.33–1.05]; P = 0.07). The articles with abstract conclusions favouring study treatments were not associated with high Altmetric score (RoM = 0.97, 95%CI [0.60–1.58]; P = 0.91).

          Conclusions

          Most important factors associated with high online media attention were the presence of a press release and the journal impact factor. There was no evidence that study design with high level of evidence and type of abstract conclusion were associated with high online media attention.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s41073-017-0033-z) contains supplementary material, which is available to authorized users.

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          Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact

          Gunther Eysenbach (2011)
          Background Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Web 2.0 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence. However, the relationship of the these new metrics to traditional metrics such as citations is not known. Objective (1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles. Methods Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated. Results A total of 4208 tweets cited 286 distinct JMIR articles. The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 43.94% of all tweets in a 60-day period) or on the following day (528/3318, 15.9%), followed by a rapid decay. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from .42 to .72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. A linear multivariate model with time and tweets as significant predictors (P < .001) could explain 27% of the variation of citations. Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles (9/12 or 75% of highly tweeted article were highly cited, while only 3/43 or 7% of less-tweeted articles were highly cited; rate ratio 0.75/0.07 = 10.75, 95% confidence interval, 3.4–33.6). Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity. Conclusions Tweets can predict highly cited articles within the first 3 days of article publication. Social media activity either increases citations or reflects the underlying qualities of the article that also predict citations, but the true use of these metrics is to measure the distinct concept of social impact. Social impact measures based on tweets are proposed to complement traditional citation metrics. The proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time.
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            Self-Selected or Mandated, Open Access Increases Citation Impact for Higher Quality Research

            Yassine Gargouri, Chawki Hajjem, Vincent Larivière … (2010)
            Background Articles whose authors have supplemented subscription-based access to the publisher's version by self-archiving their own final draft to make it accessible free for all on the web (“Open Access”, OA) are cited significantly more than articles in the same journal and year that have not been made OA. Some have suggested that this “OA Advantage” may not be causal but just a self-selection bias, because authors preferentially make higher-quality articles OA. To test this we compared self-selective self-archiving with mandatory self-archiving for a sample of 27,197 articles published 2002–2006 in 1,984 journals. Methdology/Principal Findings The OA Advantage proved just as high for both. Logistic regression analysis showed that the advantage is independent of other correlates of citations (article age; journal impact factor; number of co-authors, references or pages; field; article type; or country) and highest for the most highly cited articles. The OA Advantage is real, independent and causal, but skewed. Its size is indeed correlated with quality, just as citations themselves are (the top 20% of articles receive about 80% of all citations). Conclusions/Significance The OA advantage is greater for the more citable articles, not because of a quality bias from authors self-selecting what to make OA, but because of a quality advantage, from users self-selecting what to use and cite, freed by OA from the constraints of selective accessibility to subscribers only. It is hoped that these findings will help motivate the adoption of OA self-archiving mandates by universities, research institutions and research funders.
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              Mass media interventions: effects on health services utilisation.

              R Grilli, C. Ramsay, S Minozzi … (2002)
              The mass media frequently cover health related topics, are the leading source of information about important health issues, and are targeted by those who aim to influence the behaviour of health professionals and patients. To assess the effects of mass media on the utilisation of health services. We searched the Cochrane Effective Practice and Organisation of Care Group specialised register (1996 to 1999), MEDLINE, EMBASE, Eric, PsycLit (to 1999), and reference lists of articles. We hand searched the journals Communication Research (February 1987 to August 1996), European Journal of Communication (1986 to 1994), Journal of Communication (winter 1986 to summer 1996), Communication Theory (February 1991 to August 1996), Critical Studies in Mass Communication (March 1984 to March 1995) and Journalism Quarterly (1986 to summer 1996). Randomised trials, controlled clinical trials, controlled before-and-after studies and interrupted time series analyses of mass media interventions. The participants were health care professionals, patients and the general public. Two reviewers independently extracted data and assessed study quality. Twenty studies were included. All used interrupted time series designs. Fifteen evaluated the impact of formal mass media campaigns, and five of media coverage of health-related issues. The overall methodological quality was variable. Six studies did not perform any statistical analysis, and nine used inappropriate statistical tests (ie not taking into account the effect of time trend). All of the studies apart from one concluded that mass media was effective. These positive findings were confirmed by our re-analysis in seven studies. The direction of effect was consistent across studies towards the expected change. Despite the limited information about key aspects of mass media interventions and the poor quality of the available primary research there is evidence that these channels of communication may have an important role in influencing the use of health care interventions. Although the findings of this review may be affected by publication bias, those engaged in promoting better uptake of research information in clinical practice should consider mass media as one of the tools that may encourage the use of effective services and discourage those of unproven effectiveness.
              Article 0 comments Cited 108 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Romana Haneef: romana.haneef@gmail.com
                Philippe Ravaud: philipperavaud@gmail.com
                Gabriel Baron: gabriel.baron.ap@gmail.com
                Lina Ghosn: linaghosn83@hotmail.com
                Isabelle Boutron: isabelle.boutron@aphp.fr
                Journal
                Journal ID (nlm-ta): Res Integr Peer Rev
                Journal ID (iso-abbrev): Res Integr Peer Rev
                Title: Research Integrity and Peer Review
                Publisher: BioMed Central (London )
                ISSN (Electronic): 2058-8615
                Publication date (Electronic): 1 July 2017
                Publication date PMC-release: 1 July 2017
                Publication date Collection: 2017
                Volume: 2
                Electronic Location Identifier: 9
                Affiliations
                [1 ]INSERM, UMR 1153 Epidemiology and Biostatistics Sorbonne Paris Cité Center (CRESS), METHODS team, University of Paris Descartes, Centre d’Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
                [2 ]ISNI 0000 0001 2188 0914, GRID grid.10992.33, Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine, ; Paris, France
                [3 ]Centre d’Épidémiologie Clinique, AP-HP (Assistance Publique des Hôpitaux de Paris), Hôpital Hôtel Dieu, Paris, France
                [4 ]French Cochrane Center, Paris, France
                [5 ]ISNI 0000000419368729, GRID grid.21729.3f, Department of Epidemiology, , Columbia University Mailman School of Public Health, ; New York, NY USA
                Article
                Publisher ID: 33
                DOI: 10.1186/s41073-017-0033-z
                PMC ID: 5803628
                PubMed ID: 29451556
                SO-VID: 6f857b52-8217-4430-84e7-a44780ce9fb2
                Copyright © © The Author(s) 2017
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 7 March 2017
                Date accepted : 5 May 2017
                Funding
                Funded by: Ecole des hautes études en santé publique (EHESP), Rennes, France
                Award ID: PhD Fellowship
                Award Recipient :
                Categories
                Subject: Methodology
                Custom metadata
                issue-copyright-statement © The Author(s) 2017

                Keywords: cancer treatment,media attention,altmetric score,journal impact factor,press release,open access
                Data availability:
                Keywords: cancer treatment, media attention, altmetric score, journal impact factor, press release, open access

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