Yu-Tsen Yeh1, Tsair-Wei Chien2, Wei-Chih Kan3,4, Shu-Chun Kuo5,6. 1. Medical , School, St. George's, University of London, London, United Kingdom. 2. Department of Medical Research, Chi-Mei Medical Center. 3. Ncphrology Department, Chi-Mei Medical Center. 4. Department of Biological Science and Technology, Chung-Hwa University of Medical Technology, Tainan. 5. Department of Optometry, Chung Hwa University of Medical Technology, Jen-The. 6. Department of Ophthalmology, Chi-Mei Medical Center, Yong Kang, Tainan, Taiwan.
We emphasized the importance of the h-index in comparing individual achievements.A summary of research achievements in Mainland China, Hong Kong, and Taiwan for ophthalmology authors is rarely seen in literature because of difficulties in extracting data for authors who were only in the department of ophthalmology.Choropleth maps were plotted in this study. The need for complementing choropleth maps with the Kano diagrams and pyramid plot were introduced and demonstrated in this study.
Introduction
A few bibliometric studies have been published in the field of ophthalmology.[ Despite the h-index[ being one of the most popular indicators of individual research achievement (IRA),[ there are 2 main disadvantages:coauthors are weighted equally in contribution to the article bylines[ andthe integer nature of the h-index making it very hard to differentiate the IRA among groups.[We were motivated to use these novel approaches (i.e., AWS and modified h-index) to evaluate IRAs for ophthalmology authors in mainland China, Hong Kong, or Taiwan.Visualizations of results are commonly included in bibliographic analyses.[ However, none of the bibliometric studies have displayed IRAs on a dashboard for better understanding and detailed examination of the IRAs with a user-friendly interface. Visualization is a potential area of improvement in bibliometric studies.Three questions were of interest:which regions and institutes have significantly higher IRA,which individual author has higher IRA, andhow the AWS and the modified h-index compared in assessing IRA.
Methods
Data sources
We included original research articles and excluded letters, editorials, and comments. A total of 19,364 results published since 2010 were obtained from PubMed Central (PMC) by searching keywords (“Ophthalmology [Affiliation] and (China [Affiliation] or “Hong Kong” [Affiliation], or Taiwan [Affiliation] China [Affiliation])) on January 2, 2019. A total number of 76,895 citing articles were successfully linked to 9327 cited papers on the PMC. The rest of the articles (n = 10,037) have not been cited as of January 2, 2019. Study data were included in Supplemental Digital Content file 1.The study is exempt from review and approval by the research ethics committees because it did not involve any patient records.
Two novel approaches used in this study
1. An authorship-weighted scheme (AWS) was used in the previous articles[ to quantify contributions of individual authors with the definition of total weights equal to 1.0 for each publication. More importance is given to the first (primary) and the last (corresponding or supervisory) authors while assuming that others (the middle authors) made smaller contributions.[2. The hx-index shown in formula (1) is derived from the h-index and allow better discrimination in the form of decimal places;[ it is defined by rh denoting the ratio (=citations/publications on the x-core of the x-index = , where all of the cited papers are denoted by ci at the i-th publications sorted in descending order) based on the x-core publications and the citations.[For instance, an author whose h-index=2 and has an x-index with publications and citations of 3 and 1 has an hx-index of 2.25 (=2 + (1/3)/(1 + 1/3)). This hx-index is the first 1 proposed in the literature so far, and the idea was inspired by previous studies.[ From formula (1), it can be seen that the hx-index is used to distinguish authors with the same h indexes. In other words, the formula rank the authors with the same h indexes by looking at the impact factors (=citations/publications on the x-core of the x-index) in order to overcome the integer nature of the h-index, which would have made it hard to differentiate the IRAs among entities.[
Representations of the research results
Choropleth maps
The term “choropleth map” was raised by John Kirtland Wright in 1938.[ The most famous example of CM used was on the results of the 2000 US presidential election.[ Other examples included showing the disparities in health outcomes across areas involved with dengue outbreaks,[ disease hotspots,[ and the Global Health Observatory (GHO) maps on major health topics.[
Kano diagrams
The Kano model is developed based on a theory of product development and customer satisfaction in 1984 by Professor Noriaki Kano,[ who classified products or items into 3 main categories of quality: basic requirement, one-dimensional quality, and excitement (aka. wow) feature. Graphs are made with the satisfaction perceived by customers on Axis Y and the accomplishment achieved by providers on Axis X. In this study, we attempt to demonstrate the use of the Kano diagram to characterize the feature of authors using the hx-index in bubble and x-core publications and citations on axes X and Y, respectively.
Pyramid plot for comparing IRAs with AWS or non-AWS in comparison
A productive author will be illustrated using the pyramid plot comparing the feature of IRAs with AWS and non-AWS.
Visual representations for a personal hx-index
Visual representation on a dashboard was developed to present individual IRAs in this study.
Creating dashboards on Google Maps
All figures but the pyramid are shown by author-made modules in Excel (Microsoft Corp). We created pages of HTML with Google Maps used. All relevant h-index information on the entities can be linked to dashboards on Google Maps.
Results
The overall impact factor is 3.97 (=76895/19364), as shown in Table 1. There was a significant rise over time in the number of publications, referring to statistics of each region in Table 1. The top 3 regions in publication number were Shanghai, Beijing, and Guangdong, with the proportion being of 12.87%, 12.71%, and 12.41%, respectively.
Table 1
Publications with first authors in China, Hong Kong, and Taiwan.
Regions
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
Total
%
Citations
IF
Shanghai
84
130
152
166
206
273
302
342
363
474
2492
12.87
10766
4.32
Beijing
106
134
178
194
239
284
279
303
352
392
2461
12.71
9610
3.90
Guangdong
99
130
164
158
194
236
269
324
361
468
2403
12.41
9940
4.14
Taiwan
113
102
94
105
182
256
259
273
288
383
2055
10.61
7298
3.55
Zhejiang
39
55
66
79
128
153
178
188
217
297
1400
7.23
5295
3.78
Hong Kong
52
47
55
63
110
142
133
139
110
158
1009
5.21
5713
5.66
Shandong
44
39
47
46
67
110
118
123
137
171
902
4.66
3146
3.49
Jiangsu
14
11
24
36
47
61
82
97
94
143
609
3.15
2275
3.74
Hunan
17
28
30
26
39
34
75
75
68
132
524
2.71
2245
4.28
Hubei
28
23
33
14
37
56
48
90
81
108
518
2.68
2418
4.67
Tianjin
10
16
22
23
45
65
67
73
84
98
503
2.60
1282
2.55
Sichuan
18
31
21
25
30
45
52
57
76
105
460
2.38
2322
5.05
Shaanxi
19
22
22
22
30
40
60
55
75
97
442
2.28
1155
2.61
Others
42
58
72
87
164
181
239
264
331
405
1844
9.52
2144
1.16
Total
723
882
1050
1108
1642
2134
2366
2657
2976
3825
19364
100.00
76895
3.97
Publications with first authors in China, Hong Kong, and Taiwan.The top 3 regions in hx-index were Shanghai (26.82), Guangdong (25.82), and Beijing (25.81), as shown in Figure 1.
Figure 1
The top 3 regions whose authors were in ophthalmology department using choropleth map to present.
The top 3 regions whose authors were in ophthalmology department using choropleth map to present.The top 30 authors are shown in Figure 2 using the Kano diagram. It is worth noting that the article[ cited 34 times was authored by Dr Wu and his/her colleagues from the Department of Ophthalmology Chang Gung Memorial Hospital, Linkou(Taiwan). The article will instantly appear on PMC when the bubble is clicked, and the publication is selected in Figure 2.
Figure 2
Comparison of research achievements in regions where their authors were in ophthalmology department using 95% CI to present.
Comparison of research achievements in regions where their authors were in ophthalmology department using 95% CI to present.Moreover, we noticed an individual author Dr Wu (Taiwan), on PMC, who published 46 articles since 2004. The importance of AWS when IRAs were assessed is present in Figure 3, where we can see the author's impact factor increased from 6.5 to 8.9. The hx-indexes identified by either AWS or non-AWS are substantially different because the weighted hx-index will be smaller due to both weighted publications and citations being less than the non-AWS ones.
Figure 3
Author Dr Wu who was in ophthalmology department using the pyramid plot tp present his research achievements since 2004.
Author Dr Wu who was in ophthalmology department using the pyramid plot tp present his research achievements since 2004.The hx-index for Dr Wu is 7.64, as shown in Figure 4. It is worth mentioning that the citations and publications have been weighted by the AWS[ we proposed in this study. Readers are invited to click on the link[ to see the details about the hx-index for Dr Wu on Google Maps.
Figure 4
An online module used for displaying the author hx-index on Google Maps.
An online module used for displaying the author hx-index on Google Maps.
Discussion
In this study, there was a significant rise over time in the number of original research published by ophthalmology authors in mainland China, Hong Kong, and Taiwan. Citations were not considered in the case.Similar to choropleth maps that provide a better interpretation of the disparities in health outcomes across countries/areas,[ the hx-index in Figure 4 helps us understand the IRA for an individual author.[There are other features in this study. First, the hx-index with decimal places can complement the original h-index to increase the discrimination power[ for identifying the IRA characteristics and rankings of a given group.The second feature is the application of the Kano model[ to interpret the attributes for one's IRA using visual representations. Particularly, the dashboard-type display allows us to see details of the bibliometric indices by scanning the QR-code and clicking on the entity of interest on Google Maps. Readers are invited to see the number of citations for each author in Figure 2 by clicking the bubbles.The reasons for using x-index on 2 axes in Figure 4 areto closely correlate to h-index;[ andbecause it was newly developed in 2018, and despite being a simple and easy-to-use metric in comparison to others, the disadvantage of using h-index has been raised.[For example, an h-index of 5 means that a scientist has published 5 papers with at least 5 citations each.[ The h-index is little affected in those with a high volume of low-impact papers or authors with only a few high-impact articles.[ A high number of citations or publications were often neglected.[ The x-index was thus used to complement the h-index to clearly interpret one's feature toward either citation-oriented or productivity-oriented. The hx-index shown on the Kano diagram (Fig. 4) is novel and innovative in showing the author's IRAs on a dashboard.The third feature is the dashboard of the Kano diagram combined with the hx-index on Google Maps, which is more difficult to create using the traditional BibExce software.[ The pyramid plot (Fig. 3) for displaying author publications and citations is unique and innovative in comparing the non-weighted and weighted AWS colored bars.[
Limitations and suggestions
Although our analysis provides significant findings, several potential limitations were noticed, and may encourage further research. First, this study only focused on authors in China, Hong Kong, or Taiwan. The results cannot be generalized to other areas and countries. Second, certain biases might have occurred during citation extraction because of the number of citations increasing over the years. Namely, the IRA might differ if the time periods and the citation sources of the data are disparate. Third, many authors work for multiple departments, such as in university, medical school, and affiliated hospital. Only the units listed first were included in this study. The results of hx-index in comparison in Figures 3 might be biased if we were to apply the author-weighted scheme.[ Fourth, although our proposed hx-index can be easily applied to many other disciplines for comparison of IRAs, many statistical software do not provide such an approach to their users. A simple and useful hyperlink was provided to readers to display the hx-index on a dashboard[ and arrange their citations in descending order on their own in the future.Finally, although the hx-index is considered useful and applicable in nature, the comparison of the difference in hx-index between groups should be used in cautions due to the hx-indexes not always following a normal distribution. The bootstrapping method[ was recommended to readers for comparison among groups.
Conclusions
The hx-index and the Kano models can complement the original h-index in identifying the various IRA characteristics among groups. The bootstrapping method that allows estimation of the sampling distribution for almost all statistic data using random sampling methods with accuracy (as defined by 95% CI) is recommended in future studies when hx-indexes were compared among departments or institutes. We highly recommend the 3 features used in this study, AWS, hx-index, and the Kano diagram, to be applied in the future, not just limited to ophthalmology publications.