Skip Content
You are currently on the new version of our website. Access the old version .
MDPIMDPI
HealthcareHealthcare
Download PDF
  • Article
  • Open Access

25 September 2020

Analysis of Altmetrics in Social Recognition of Neurology and Neurological Disorders

,
,
,
and
1
Department of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul 05355, Korea
2
Department of Neurology, Ewha Womans University Seoul Hospital, Seoul 07804, Korea
3
Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon 24253, Korea
4
Department of Radiology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul 05355, Korea
Healthcare2020, 8(4), 367;https://doi.org/10.3390/healthcare8040367
This article belongs to the Special Issue Statistical Process Monitoring in Healthcare
Version Notes
Order Reprints

Abstract

This study used Altmetric analysis to rank neurological articles and assessed the implications in relation to the social recognition of neurology and neurological disorders. An Altmetric Explorer search was conducted on 25 May 2018 for articles published in the 91 journals included in the 2015 InCites™ Journal Citation Report®. We identified and analyzed the 100 articles with the highest Altmetric Attention Scores (AASs). A major proportion of the social impact (high AASs) was focused on neurodegenerative disorders such as dementia and neurodegenerative disorders. About half of the high-ranking articles provided academic information such as disease information (29 articles, 29%), new or advanced treatments (17%), and side effects of treatment (8%). The journal with largest number of top 100 articles was the New England Journal of Medicine (29 articles). Some of the data gathered via altmetrics can change a field of study, the public’s health, or a larger society. This is the first report on the impact of academic articles in neurological disorder on the general public living in our altered information society.

1. Introduction

The impact of research articles has traditionally been measured and graded mainly based on the frequency and the numbers of citations during a certain period. Bibliometric analysis utilizing this approach can quantitatively measure the academic influence and the impact of researchers. However, this technique involves a considerable amount of time to have lapsed after articles are published [1]. In addition, certain types of bibliometric analysis have disclosed that specific academic trends or popular issues may contribute to articles being ranked highly [2]. Another crucial issue to consider is that bibliometrics does not reflect the impact of articles on the general public.
The acquisition of medical information is changing markedly with the increasing popularity of the internet. This means that many people are nowadays exposed to medical news from mass communication and social network systems as well as from academic articles written by specialists [3,4]. For example, online platforms such as Twitter, blogs, and online sites of community addressing medical information can rapidly disseminate new information and academic outcomes related to medical science. It is therefore reasonable to assume that this changing environment will alter attitudes toward learning about new medical information.
Several tools have been developed to address the impact of this new communication environment [5,6,7]. Altmetric analysis is one such commonly available tool and is now being used by some influential medical journals for measuring the social impact of their publications. Altmetrics is a term that has been used in the literature to refer to both article-level and alternative metrics. It can measure and visualize the impact of research articles on various new online platforms [8]. Therefore, Altmetric analysis can be used to estimate the dissemination of medical information related to certain research articles.
Neurology is a specialty of clinical medicine that covers numerous subspecialties such as dementia, stroke, epilepsy, demyelinating disorders, parkinsonism, and neuromuscular disorders. These disorders have been among the most popular subjects of investigation in neuroscience research, and many basic research studies related to these diseases are ongoing, which is rapidly improving the understanding of the basic mechanisms underlying the diseases. Neurologists across all subspecialties also perform clinical research based on advances in basic research, and some of their outcomes have been drawn to the attention of the general public thanks to them being highlighted in the mass media. The aim of this study was to determine which recent papers in the field of neurology have received the highest Altmetric Attention Scores (AASs). This study analyzed the highly ranked articles in the fields of neurology and neurological disorders as identified using Altmetric analysis and evaluated the implications of this technique in terms of the recognition of neurology and neurological disorders among the general public.

2. Materials and Methods

2.1. Study Design and Setting

The web-based application Altmetric Explorer (Altmetric, London, UK) was utilized as a search engine in this study. The results were visualized using the Altmetric donut, which is a multicolored circle that displays the relative contributions of all sources. This donut symbolizes the dissemination of research output via different sources (Facebook, Twitter, Google+, Linked In, Sina Weibo, and Pinterest), and the display format demonstrates a weighted score. The Altmetric Attention Score (AAS) is presented in the center of the graphic. Detailed information about the algorithm and examples of its application are available elsewhere [6,9].
An Altmetric Explorer search was conducted on 25 May 2018 for articles published in the 91 journals included in the 2015 InCites™ Journal Citation Report® grouped under the subject categories of clinical neurology, neuroscience, and general and internal medicine. The site was accessed on only a single specific day (25 May 2018) to avoid changes in the online presentation of articles interfering with the analyses. No restrictions were applied regarding language, date of publication, AAS, keywords, title of output, type of output, or scholarly identifiers.
Data cannot be shared because there are embargoes on datasets. Anonymized data will be shared by request from any qualified investigator.

2.2. Data Sources

We analyzed the full text of the 100 articles with the top AASs and extracted detailed information about title, year of publication, AAS, corresponding author, journal name, and journal impact factor (based on the 2017 science edition). Because of considerable subject overlap between articles in the clinical neurology and the neuroscience fields, the authors first analyzed clinical neurology journals and thereafter included additional articles in neuroscience journals that provided clear information regarding neurological disorders. We also analyzed the articles in general and internal medicine journals that focused on neurological disorders as the main subject. After selecting 100 articles, we categorized them into 15 subspecialties of disease groups and 5 categories of main subjects.
Two neurologists (Yerim Kim. and Jong Seok Bae) independently identified and analyzed the articles. In cases of disagreement between these two reviewers, consensus was achieved through open discussions. The present study adopted a descriptive research approach by means of bibliometric analysis.

2.3. Standard Protocol Approvals, Registrations, and Patient Consents

The present study did not involve human subjects and thus did not require approval from an institutional review board. We used STROBE guidelines for a descriptive study [10].

3. Results

We finally selected the 100 articles with the highest AASs (range = 868–3873), as listed in Table 1. The journal with largest number of top 100 article was the New England Journal of Medicine (29 articles), while the Neurology journal had the largest number of articles in the field of clinical neurology (13 articles). We investigated the type of access because they can also affect the accessibility of social media (Table 2). The most common author nationality was American (Table 3). In cases of a co-corresponding author, the nationality of the first author was listed.
Table 1. Top 100 articles with the highest Altmetric Attention Scores (AASs).
Table 2. Journals with top 100 articles, ranked according to the AAS.
Table 3. Journals with top 100 articles, ranked according to the country of the corresponding author.
Regarding the disease category or subspecialty, social recognition was relatively concentrated on degenerative disorders and cerebrovascular disorders. Research articles in the neuroscience field providing advanced information about disease mechanisms had the second highest ranks (Table 4). A particularly interesting finding was that most of the articles classified in the neuroscience field also contained subjects related to cognitive and behavioral science (e.g., memory, addiction, and intelligence). These findings suggest that dementia and cognitive/neurobehavioral problems receive more attention from the general public.
Table 4. Numbers of articles with top 100 AASs according to neurology subspecialties.
We arbitrarily categorized the articles in the following five subjects based on interest in health and medical services among the general public: disease information, lifestyle and disease, science information, new or advanced treatments, and side effects of treatment. As indicated in Table 5, the ranking order of subject categories was identical to the order in the above list. About half of the high-rank articles provided medical information such as disease information (29 articles, 29%), new or advanced treatments (17%), and side effects of treatment (8%). However, half of the 100 articles were about less academic subjects, with 27 articles (27%) addressing the relationship between lifestyle and diseases.
Table 5. Numbers of articles with top 100 AASs according to subject categories.

4. Discussion

This Altmetric analysis revealed the current status of social recognition and public attention regarding neurology and neurological disorders. This is the first trial to evaluate this subject based on the premise that the acquisition of information and learning behaviors will eventually change from before the era of easy internet accessibility. Of the various subspecialties in neurology, research into degenerative and cerebrovascular disorders receives the strongest interest from the general public. People are frequently exposed to journals in general and internal medicine and clinical neurology with high impact factors via the present environment of information flow. In addition to the topic of disease information, members of the general public pay considerable attention to the relationship between lifestyle and disease. The present results may be utilized when establishing policies or planning promotions for public health in neurology and neurological disorders.
With the global accessibility and the popularity of the internet and social media, the utility of Altmetric analysis has grown rapidly since the concept was first introduced in 2011 [11]. This trend is expected to continue, because, by 2020, the number of worldwide social media users is expected to reach 2.95 billion, or around one-third of the worldwide population [12].
The article with the highest AAS (=3873) was an invited editorial (in the form of a letter) written by the wife of a famous patient [13]. Despite not being a medical specialist, she provided a precise description of the disease course and the treatment of her husband, Robin Williams. According to both his disease course and pathological examination, he tragically ended his life due to severe neuropsychiatric symptoms from diffuse Lewy body disease. The subjects of most of the other top 10 ranked articles were related to environment and lifestyle and diseases, such as chronic trauma, alcohol, living environment, and nutrients [14,15,16,17].
About half of the top 100 ranked articles were related to clinical aspects of medical information, such as disease information (29 articles, 29%), new or advanced treatments (17%), and side effects of treatment (8%). However, the other half of the articles focused on less academic subjects, with 27 articles (27%) addressing the relationship between lifestyle and diseases, as exemplified above. Science information rather than specific disease diagnoses/treatments was the subject in 19 articles (e.g., newly demonstrated mechanisms of memory persistence, the mechanism of dreaming, and the genetics of intelligence) [18,19].
Our list naturally included some diseases that give rise to social problems. One of these is the Zika virus and its neurological complications, such as microcephaly and Guillain-Barré syndrome [20,21]. Another issue is chronic traumatic encephalopathy, which is a major problem among Americans [14]. Many American parents are informed about this issue by studies of cognitive performance and chronic physical head trauma, especially for American football athletes. It can therefore be presumed that the results of Altmetric analysis that are of interest to the general public may change as new social issues develop.
Another distinct characteristic of our analysis is that the articles ranked highly in the Altmetric analysis appeared to use general terminology for disorders in their titles rather than specific disease entities; for example, “Alzheimer’s disease” was less common than “dementia” and “cognitive or intellectual dysfunction/disorders.” This finding implies that common and easy-to-understand terminology might be more acceptable to the general public.

5. Conclusions

It is reasonable to use traditional citation-based metrics to measure the impact of a scholarly article in the sense that citations indicate that new evidence has been built upon by the findings of a given paper. Altmetrics, on the other hand, appears to reflect public interest rather than the scientific merits of an article. It should be remembered that there can be considerable discordance between the expectations of academic and medical value among scholars and the attitudes of the general public.

Author Contributions

Y.K., J.S.B., and D.Y.Y. conceived and designed the study; Y.K., J.S.B., and D.Y.Y. collected the data; Y.K., J.S.B., J.-E.K., and S.-H.L. analyzed the data; Y.K. and J.S.B. drafted the manuscript; J.S.B. supervised the study; and Y.K., J.-E.K., D.Y.Y., S.-H.L., and J.S.B. critically revised the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under grant number NRF-2017R1D1A1B03029672 and by the Ministry of Science and ICT (grant number NRF-2018R1C1B5086320) and was supported by a grand no. 2019-08 from the Kangdong Sacred Heart Hospital Fund.

Conflicts of Interest

The authors declared no potential conflict of interest with respect to the research, authorship, and/or publication of this article.

Ethics Approval

The present study did not involve human subjects and thus did not require approval from an institutional review board.

Availability of Data and Material

Data cannot be shared because there are embargoes on datasets. Anonymized data will be shared by request from any qualified investigators.

References

  1. MacRoberts, M.H.; MacRoberts, B.R. Problems of citation analysis: A critical review. J. Am. Soc. Inf. Sci. 1989, 40, 342–349. [Google Scholar] [CrossRef]
  2. Kim, J.E.; Kim, J.K.; Park, K.M.; Kim, Y.; Yoon, D.Y.; Bae, J.S. Top-100 cited articles on Guillain-Barre syndrome: A bibliometric analysis. J. Peripher. Nerv. Syst. 2016, 21, 329–338. [Google Scholar] [CrossRef] [PubMed]
  3. Cline, R.J.; Haynes, K.M. Consumer health information seeking on the Internet: The state of the art. Health Educ. Res. 2001, 16, 671–692. [Google Scholar] [CrossRef] [PubMed]
  4. Trueger, N.S.; Thoma, B.; Hsu, C.H.; Sullivan, D.; Peters, L.; Lin, M. The altmetric score: A new measure for article-level dissemination and impact. Ann. Emerg. Med. 2015, 66, 549–553. [Google Scholar] [CrossRef] [PubMed]
  5. Ruan, Q.Z.; Chen, A.D.; Cohen, J.B.; Singhal, D.; Lin, S.J.; Lee, B.T. Alternative metrics of scholarly output: The relationship among altmetric score, Mendeley reader score, citations, and downloads in plastic and reconstructive surgery. Plast. Reconstr. Surg. 2018, 141, 801–809. [Google Scholar] [CrossRef] [PubMed]
  6. Delli, K.; Livas, C.; Spijkervet, F.K.L.; Vissink, A. Measuring the social impact of dental research: An insight into the most influential articles on the Web. Oral Dis. 2017, 23, 1155–1161. [Google Scholar] [CrossRef] [PubMed]
  7. Peoples, B.K.; Midway, S.R.; Sackett, D.; Lynch, A.; Cooney, P.B. Twitter predicts citation rates of ecological research. PLoS ONE 2016, 11, e0166570. [Google Scholar] [CrossRef] [PubMed]
  8. Amath, A.; Ambacher, K.; Leddy, J.J.; Wood, T.J.; Ramnanan, C.J. Comparing alternative and traditional dissemination metrics in medical education. Med. Educ. 2017, 51, 935–941. [Google Scholar] [CrossRef] [PubMed]
  9. Ortega, J.L. Disciplinary differences of the impact of altmetric. FEMS Microbiol. Lett. 2018, 365. [Google Scholar] [CrossRef] [PubMed]
  10. Von Elm, E.; Altman, D.G.; Egger, M.; Pocock, S.J.; Gøtzsche, P.C.; Vandenbroucke, J.P. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Ann. Intern. Med. 2007, 147, 573–577. [Google Scholar] [CrossRef] [PubMed]
  11. Brigham, T.J. An introduction to altmetrics. Med. Ref. Serv. Q. 2014, 33, 438–447. [Google Scholar] [CrossRef] [PubMed]
  12. Statista, the Statistics Portal. Available online: https://www.statista.com/topics/1164/social-networks/ (accessed on 30 January 2017).
  13. Williams, S.S. The terrorist inside my husband’s brain. Neurology 2016, 87, 1308–1311. [Google Scholar] [CrossRef] [PubMed]
  14. Mez, J.; Daneshvar, D.H.; Kiernan, P.T.; Abdolmohammadi, B.; Alvarez, V.E.; Huber, B.R.; Alosco, M.L.; Solomon, T.M.; Nowinski, C.J.; McHale, L.; et al. Clinicopathological evaluation of chronic traumatic encephalopathy in players of American football. JAMA 2017, 318, 360–370. [Google Scholar] [CrossRef] [PubMed]
  15. Morris, M.C.; Wang, Y.; Barnes, L.L.; Bennett, D.A.; Dawson-Hughes, B.; Booth, S.L. Nutrients and bioactives in green leafy vegetables and cognitive decline: Prospective study. Neurology 2018, 90, e214–e222. [Google Scholar] [CrossRef] [PubMed]
  16. Chen, H.; Kwong, J.C.; Copes, R.; Tu, K.; Villeneuve, P.J.; van Donkelaar, A.; Hystad, P.; Martin, R.V.; Murray, B.J.; Jessiman, B.; et al. Living near major roads and the incidence of dementia, Parkinson’s disease, and multiple sclerosis: A population-based cohort study. Lancet 2017, 389, 718–726. [Google Scholar] [CrossRef]
  17. Topiwala, A.; Allan, C.L.; Valkanova, V.; Zsoldos, E.; Filippini, N.; Sexton, C.; Mahmood, A.; Fooks, P.; Singh-Manoux, A.; Mackay, C.E.; et al. Moderate alcohol consumption as risk factor for adverse brain outcomes and cognitive decline: Longitudinal cohort study. BMJ 2017, 357. [Google Scholar] [CrossRef] [PubMed]
  18. Richards, B.A.; Frankland, P.W. The persistence and transience of memory. Neuron 2017, 94, 1071–1084. [Google Scholar] [CrossRef] [PubMed]
  19. Siclari, F.; Baird, B.; Perogamvros, L.; Bernardi, G.; LaRocque, J.J.; Riedner, B.; Boly, M.; Postle, B.R.; Tononi, G. The neural correlates of dreaming. Nat. Neurosci. 2017, 20, 872–878. [Google Scholar] [CrossRef]
  20. Mlakar, J.; Korva, M.; Tul, N.; Popovic, M.; Poljsak-Prijatelj, M.; Mraz, J.; Kolenc, M.; Resman Rus, K.; Vesnaver Vipotnik, T.; Fabjan Vodusek, V.; et al. Zika virus associated with microcephaly. N. Engl. J. Med. 2016, 374, 951–958. [Google Scholar] [CrossRef] [PubMed]
  21. Cao-Lormeau, V.M.; Blake, A.; Mons, S.; Lastere, S.; Roche, C.; Vanhomwegen, J.; Dub, T.; Baudouin, L.; Teissier, A.; Larre, P.; et al. Guillain-Barre Syndrome outbreak associated with Zika virus infection in French Polynesia: A case-control study. Lancet 2016, 387, 1531–1539. [Google Scholar] [CrossRef]

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Download PDF
Translation and Cultural Adaptation of the Patient Self-Administered Financial Effects (P-SAFE) Questionnaire to Assess the Financial Burden of Cancer in French-Speaking Patients
Previous
Benefits of Multiple-Intervention Pulmonary Rehabilitation to Older Adults with High-Risk Multimorbidity after Coronary Artery Bypass Grafting
Next