Table 5.
Characteristics of correlational studies of poor quality (n=12).
| Study ID and reference | Health research area/unit and period of analysis | Metrics reported | Results | Methodological quality indicatorsa | |||
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1 | 2 | 3 | 4 |
| Amath, 2017 [32,33] | Medical education: 482 articles appearing on Medical Education journal (2012-2013) | Social media: Twitter, Mendeley; Altmetrics-Bibliometrics: Citations (Scopus) | Very strong correlation between Tweet counts and Altmetrics score; Citations were strongly correlated with access counts and Mendeley downloads, and weakly and moderately correlated respectively with Twitter mentions and Altmetric scores | - | - | + | - |
| Azer, 2019 [55] | Medical professionalism; 50 most-cited articles in medical professionalism identified by searching WoSb (1994-2011) | Social media: Altmetrics-Bibliometrics: Citations (WoSb) | No significant correlation between Altmetrics and citations | − | + | − | − |
| Baan, 2017 [56] | Transplantation; All articles published on transplantation in 2015 (volume 99) | Social media: Twitter-Bibliometrics: number of views and downloads | Significant correlation between downloads and Twitter activity | − | − | − | + |
| Batooli, 2016 [57] | Medical sciences; 533 articles published by faculty at Kashan University of Medical Sciences (1997-2014) | Social media: ResearchGate, Mendeley-Bibliometrics: Citations (Scopus) | Positive correlation between the number of views of articles in ResearchGate and citations; positive correlation between reading frequency in Mendeley and citations; number of views of articles in ResearchGate correlated with higher reading frequency in Mendeley and citations | − | − | − | + |
| Chen, 2019 [41] | Rheumatology; 1460 articles appearing in Rheumatology journal (2010-2015) | Social media: Altmetrics-Bibliometrics: Citations and downloads | Strong correlations between Altmetric and downloads, but not citations | − | + | − | − |
| Chiang, 2016 [42] | Gastroenterology; 1671 articles appearing on 5 core gastroenterology journals, 482 being tweeted (2012) | Social media: Twitter-Bibliometrics: Citations (Google Scholar) | No significant correlation between Twitter and citations | − | + | − | − |
| Cho, 2017 [60] | Medical sciences; 98 articles from medical sciences from Korean researchers in Scopus (2010-2014) | Social media: ImpactStory; Altmetrics-Bibliometrics: Citations (Scopus) | The more the papers are cited in the journal, the more papers saved on Mendeley | − | + | − | − |
| Hayon, 2019 [34] | Urology; 213 articles from 7 prominent urology journals (2014-2015) | Social media: Altmetrics-Bibliometrics: Citations (Google Scholar and Scopus) | Positive relationship between Twitter activity and Scopus citations | + | − | − | − |
| Jedhav, 2019 [68] | Neurointerventional surgery; 451 articles first published on the web on the Journal of Neurointerventional Surgery (2015-2016) | Social media: Twitter-Bibliometrics: Citations (WoSb) | The level of evidence of the publication and the topic of research strongly predicts future citations. The number of clicks also appears to be a strong predictor of future citations, and the number of clicks increases as the number of Twitter users also grows | − | − | + | − |
| Jeong, 2019 [69] | Coloproctology; 404 articles published on 3 journals with Twitter profiles (2015-2016) | Social media: Twitter-Bibliometrics: Citations (WoSb) | Significant correlations between citations and Twitter activity | − | + | − | − |
| Konstantiniuk, 2015 [44] | Sepsis research; 12 articles on sepsis compared with 8 articles on ICUc (period not indicated) | Social media: Twittter; Altmetrics; ResearchGate-Bibliometrics: Citations (Google Scholar and WoSb) | The Altmetric score neither correlated with Google Citations nor publishing date | − | + | − | − |
| Shirazi, 2018 [79] | Health literacy; 615 articles with a digital object identifier and indexed in WoSb (2015) | Social media: Altmetrics-Bibliometrics: Citations (WoSb) | Significant correlations between Altmetrics and citations | − | − | − | + |
a1: appropriately adjusting for time of the social media metric (+); 2: appropriately adjusting for confounders such as article type (+) and seasonality/time factors (++); 3: appropriately exploring correlations by including scatterplots (+); 4: appropriately reporting nonlinear correlations tests and statistics (+) as well as log-linear relationship tests (++).
bWoS: Web of Science.
cICU: Intensive Care Unit.