Open Access Peer-reviewed Research Article

The most highly-cited authors who published papers on the topic of health behavior: A Bibliometric Analysis

Article Sidebar

Dispersion of coauthor clusters based on weighted contributions
Download PDF Download HTML
Submitted   Sep 23, 2018
Published   Nov 1, 2018
Issue    Vol 1 (2018)
DOI   10.25082/AHB.2018.01.005

Views

6153

Downloads

2401

Citations

PlumX Metrics

Main Article Content

Chen Fang Hsu
Department of Paediatrics, Chi-Mei Medical Center, Tainan 710, Taiwan
Tsair Wei Chien
Research Department, Chi-Mei Medical Center, Tainan, Taiwan
Julie Chi Chow
Department of Paediatrics, Chi Mei medical center, Tainan, Taiwan
Willy Chou corresponding author
Chi-Mei Medical Center, 901 Chung Hwa Road, Yung Kung Dist., Tainan 710, Taiwan

Abstract

Background: Health behavior(HB) is an action taken by a person who pursues good health and prevents illness. Health behavior, thus, reflects a person's health beliefs and attracts, particularly, on published papers in academics. However, who is the most influential author(MIA) with highly-cited papers on HB remains unknown.
Objective: The purpose of this study is to apply the authorship-weighted scheme (AWS) developed by authors to select the MIA on HB using the visual displays on Google Maps.
Methods: We obtained 1,116 abstracts published between 2012 and 2016 from Medline based on the keywords of (health[Title]) and (behavior[Title] or behavior [Title]) on September 22, 2018. The author names, countries/areas, and Pubmed paper IDs were recorded. The AWS was applied to (1)select the most productive authors(MPA) using social network analysis(SNA); (2) discover the MIA using h-indexes and author impact factors(AIF) dispersed on Google Maps, and (3)display the countries/areas distributed for the x-index in geography. Pajek software was performed to determine the partition categories of clusters.
Results: We found that the MPA and MIA are Matthew K Nock(US) and Erika A Waters(US) for the MPA and MIA, respectively. All visual representations that are the form of a dashboard can be easily displayed on Google Maps. The most influential countries are the US(=19.03) and Australia(=6.46) with the highest x-indexes. Readers are suggested to manipulate them on their own on Google Maps.  
Conclusion: Many individual researchers’ achievements (IRA) were determined using h-index, AIF, x-index, or other bibliometric indices without quantifying author contributions. We demonstrated visualized representations on Google Maps using the AWS developed by authors to measure authors’ influences in a specific discipline. The research approach using the AWS to quantify the authors’ contributions can be applied to measure IRA in the future.

Keywords
authorship-weighted scheme, most productive author, most influential author, Google Maps, social network analysis, health behavior

Article Details

How to Cite
Hsu, C. F., Chien, T. W., Chow, J. C., & Chou, W. (2018). The most highly-cited authors who published papers on the topic of health behavior: A Bibliometric Analysis. Advances in Health and Behavior, 1(1), 24-29. https://doi.org/10.25082/AHB.2018.01.005
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

References

  1. Haileamlak A. What Factors Affect Health Seeking Behavior? Ethiop J Health Sci, 2018, 28(2): 110. https://doi.org/10.4314/ejhs.v28i2.1
  2. Chen SH, Chien TW, Su SB, et al. A dashboard on Google Maps to show the most influential author on the topic of health behavior: A Bibliometric Analysis. Adv Health And Behavior, 2018, 1(1): 1-7. https://doi.org/10.25082/AHB.2018.01.004
  3. Hirsch JE. An index to quantify an individuals scientific research output. Proc. Natl. Acad. Sci., 2005, 15(102): 16569-16572. https://doi.org/10.1073/pnas.0507655102
  4. Etersen AM, Fortunato S, Pan RK, et al. Reputation and impact in academic careers. Proc Natl Acad Sci USA, 2014, 111(43): 15316-15321. https://doi.org/10.1073/pnas.1323111111
  5. Sekercioglu CH. Quantifying coauthor contributions. Science, 2008, 322(5900): 371. https://doi.org/10.1126/science.322.5900.371a
  6. Yuen J. Comparison of Impact Factor, Eigenfactor Metrics, and SCImago Journal Rank Indicator and h-index for Neurosurgical and Spinal Surgical Journals. World Neurosurg, 2018, (119): e328-e337. https://doi.org/10.1016/j.wneu.2018.07.144
  7. Post A, Li AY, Dai JB, et al. c-index and Subindices of the h-index: New Variants of the h-index to Account for Variations in Author Contribution. Send to Cureus, 2018, 10(5): e2629. https://doi.org/10.7759/cureus.2629
  8. Ashfaq A, Kalagara R and Wasif N. H-index and academic rank in general surgery and surgical specialties in the United States. J Surg Res., 2018, (229): 108-113. https://doi.org/10.1016/j.jss.2018.03.059
  9. Jayant SV and V-index. A fairer index to quantify an individual’s research output capacity”. BMJ, 2005, 311(728): 1339c-1340c.
  10. Vavryuk V. Fair ranking of researchers and research teams. PLoS One, 2018, 13(4): e0195509. https://doi.org/10.1371/journal.pone.0195509
  11. Batista PD, Campiteli MG, Kinouchi O, et al. Is it possible to compare researchers with different scientific interests? Scientometrics. 2006, 68(1): 179-189. https://arxiv.org/ftp/physics/papers/0509/0509048.pdf
  12. Lindsey D. Production and citation measures in the sociology of science: The problem of multiple authorship. Soc Stud Sci, 1980, 10(2): 145-162. https://doi.org/10.1177/030631278001000202
  13. Lindsey D. Further evidence for adjusting for multiple authorship. Scientometrics, 1982, 4(5): 389-395. https://doi.org/10.1007/BF02135124
  14. Egghe L, Rousseau R and Van Hooydonk G. Methods for accrediting publications to authors or countries: Consequences for evaluation studies. J Am Soc Inform Sci, 2000, 51(2): 145-157. https://doi.org/10.1002/(SICI)1097-4571(2000)51:2h145:: AID-ASI6i3.0.CO;2-9
  15. Tscharntke T, Hochberg ME, Rand TA, et al. Author sequence and credit for contributions in multiauthored publications. PLOS Biology, 2007, 5(1): e18. https://doi.org/10.1371/journal.pbio.0050018
  16. Waltman L. A review of the literature on citation impact indicators. Journal of Informetrics, 2015, 10(2): 365-391. https://doi.org/10.1016/j.joi.2016.02.007
  17. Pan RK and Fortunato S. Author Impact Factor: tracking the dynamics of individual scientific impact. Sci Rep, 2014, (4): 4880. https://doi.org/10.1038/srep04880
  18. Lippi G and Mattiuzzi C. Scientist impact factor (SIF): a new metric for improving scientists’ evaluation? Ann Transl Med, 2017, 5(15): 303. https://doi.org/10.21037/atm.2017.06.24
  19. Fenner T, Harris M, Levene M, et al. A novel bibliometric index with a simple geometric interpretation. PLoS One, 2018, 13(7): 19.e0200098. https://doi.org/10.1371/journal.pone.0200098
  20. Bright CF, Haynes EE, Patterson D, et al. The Value of Social Network Analysis for Evaluating Academic- Community Partnerships and Collaborations for Social Determinants of Health Research. Ethn Dis, 2017, (Suppl 1): 337-346. https://doi.org/10.18865/ed.27.S1.337
  21. De Nooy W, Mrvar A and Batagelj V. Exploratory Social Network Analysis With Pajek: Revised and Expanded, 2nd edn. New York, NY: Cambridge University Press, 2011. https://doi.org/10.1017/9781108565691
  22. Otte E and Rousseau R. Social network analysis: a powerful strategy, also for the information sciences. J Inform Sci., 2002, 28(6): 441-453. https://doi.org/10.1177/016555150202800601
  23. Bright CF, Haynes EE, Patterson D, et al. The Value of Social Network Analysis for Evaluating Academic- Community Partnerships and Collaborations for Social Determinants of Health Research. Ethn Dis., 2017, 27(Suppl 1): 337-346. https://doi.org/10.18865/ed.27.S1.337
  24. Phan TG, Beare R, Chen J, et al. Googling Service Boundaries for Endovascular Clot Retrieval Hub Hospitals in a Metropolitan Setting: Proof-of-Concept Study. Stroke, 2017, 48(5): 1353-1361. https://doi.org/10.1161/STROKEAHA.116.015323
  25. Andrich D. Relationships between the Thurstone and Rasch approaches to item scaling. Applied Psychological Measurement, 1978, 2(3): 451-462. https://doi.org/10.1177/014662167800200319
  26. Lindsey D. Further evidence for adjusting for multiple authorship. Scientometrics, 1982, 4(5): 389-395. https://doi.org/10.1007/BF02135124
  27. Hagen NT. Harmonic allocation of authorship credit: source-level correction of bibliometric bias assures accurate publication and citation analysis. PLoS One, 2008, 3(12): e402. https://doi.org/10.1371/journal.pone.0004021
  28. Hu SK, Huang J, Hong WD, et al. The 50 Most-cited Articles in Gastroenterology and Hepatology from Mainland China. Pak J Med Sci., 2017, 33(1): 215-220. https://doi.org/10.12669/pjms.331.12286
  29. Coelho DH, Edelmayer LW and Fenton JE. A century of citation classics in otolaryngology-head and neck surgery journals revisited. Laryngoscope, 2014. 124(6): 1358-1362. https://doi.org/10.1002/lary.24573
  30. Chang HT, Lin MH, Hwang IH, et al. Scientific publications in gastroenterology and hepatology in Taiwan: An analysis of Web of Science from 1993 to 2013. J Chin Med Assoc, 2017, 80(2): 80-85. https://doi.org/10.1016/j.jcma.2016.06.006
  31. Sadoughi F, Valinejadi A and Shirazi MS, et al. Social Network Analysis of Iranian Researchers on Medical Parasitology: A 41 Year Co-Authorship Survey. Iran J Parasitol, 2016, 11(2): 204-212. http://ijpa.tums.ac.ir/index.php/ijpa/article/view/1060
  32. Borgatti SP, Everett MG and Freeman LC. Ucinet for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies, 2002,
  33. Bastian M, Heymann S and Jacomy M. Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media, 2009. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.172.7704&rep=rep1&type=pdf