scholarly journals Analyzing the Relationship Between Altmetric Score and Literature Citations in the Dermatology Literature

2020 ◽  
Vol 4 (6) ◽  
pp. 497-505
Author(s):  
Meredith E Thomley ◽  
Ana Preda-Naumescu ◽  
Carter J Boyd ◽  
Tiffany Mayo
Keyword(s):  
Impact Factor ◽  
Pearson Correlation ◽  
Citation Count ◽  
Correlation Coefficients ◽  
Impact Factors ◽  
Microsoft Excel ◽  
Number Of Citations ◽  
The Relationship ◽  
Journal Impact ◽  
Article Impact

Background: Standard bibliometric methods used in dermatologic research include impact factor and citations. The Altmetric score is an adjunctive measure of article impact. Objectives: The purpose of this study is to examine the breadth of societal impact made by scientific articles in dermatology and investigate a correlation between an article’s impact factor and citations, with its Altmetric score. Methods: We reviewed 15 dermatology journals with the highest impact factors and analyzed the 10 most cited articles from 2013 and 2016 within those journals. We studied the articles’ Altmetric scores, number of citations, and social media mentions. Using Microsoft Excel, we performed statistical analysis with Pearson correlation coefficients and descriptive statistics. Results: Analysis revealed a significant positive relationship between citation count and Altmetric scores for articles published in 2013 (p=0.0009) and 2016 (p=0.003). Impact factor was also significantly associated with Altmetric scores across both years (p=0.002, p=0.0005). Conclusions: Altmetric score weakly corresponded with citation count and journal impact factor across cohorts. We conclude that Altmetric scores serve as an additional measurement of article impact in dermatology, though they are insufficient as a replacement for traditional measures at this time.

Bibliometric study of ‘overviews of systematic reviews’: evaluation of prevalence, citation and impact factor

2021 ◽  
Author(s):  
Carole Lunny ◽  
Trish Neelakant ◽  
Alyssa Chen ◽  
Gavindeep Shinger ◽  
Adrienne Stevens ◽  
...  
Keyword(s):  
Impact Factor ◽  
Systematic Reviews ◽  
Citation Count ◽  
Impact Factors ◽  
Cochrane Library ◽  
Funding Source ◽  
Sample Sizes ◽  
Number Of Citations ◽  
Journal Impact ◽  
Overviews Of Systematic Reviews

Abstract Background: Overviews synthesizing the results of multiple systematic reviews help inform evidence-based clinical practice. In this first of two companion papers, we evaluate the bibliometrics of ‘overviews of systematic reviews’, including their prevalence, number of citations, and factors affecting citation rates and journal impact factor.Methods: We searched MEDLINE, Epistemonikos and the Cochrane library databases. We applied eligibility criteria to identify overviews that: (a) aimed to focus on synthesizing reviews, (b) conducted a systematic search, (c) had a full methods section, and (d) examined a health intervention or clinical treatment effect. A multivariate regression was conducted to determine the association between citation density and impact factor and 6 predictor variables of interest. Results: We found 1218 overviews published from 2000 to 2020; the majority (73%) of which were published in the most recent 5-year period (2016-2020). We extracted a selection of these overviews (n=541; 44%) dated from 2000 to 2018. The 541 overviews were published in 307 journals; the Cochrane Database of Systematic Reviews (8%), PLOS ONE (3%) and the Sao Paulo Medical Journal (2%) being the most prevalent. The majority of overviews (70%) were published in journals with impact factors between 0.05 and 3.97. The average citation rate was 90 (SD ±219.7) over 9 years, or 10 citations per overview per year. In multivariate analysis, overviews with a high number of citations and high journal impact factors tended to have more authors, larger sample sizes, be open access and report funding source. Conclusions: We found an 8 fold increase in the number of overviews from 2009 to 2020; and a representation of one published a day in 2020. Factors driving the increase in overviews include the exponential increase in the number of systematic reviews, the publication of Cochrane guidance on overview of reviews in 2009 and the subsequent publication of the first Cochrane overview in the same year. Our study found a significantly higher mean citation count of 10 overviews per year, published in journals with a mean impact factor of 4.4. These data indicate that, overall, overviews perform above average for the journals in which they publish. We also found that highly cited overviews in high impact factor journals had group authorship, large sample sizes, were openly accessible, and reported funding source.

scholarly journals Examining the Relationship between Altmetric Score and Traditional Bibliometrics in the Ophthalmology Literature for 2013 and 2016 Cohorts

2021 ◽  
Vol 13 (01) ◽  
pp. e95-e101
Author(s):  
Zachary C. Wiley ◽  
Carter J. Boyd ◽  
Shivani Ananthasekar ◽  
Nita Bhat ◽  
Shruthi Harish Bindiganavile ◽  
...  
Keyword(s):  
Impact Factor ◽  
Citation Count ◽  
Correlation Coefficients ◽  
Coefficient Of Determination ◽  
Quality Metric ◽  
Journal Citation Reports ◽  
Twitter Account ◽  
Positive Correlations ◽  
Number Of Citations ◽  
The Relationship

Abstract Background In this study, we reviewed a select sample of ophthalmology literature to determine if there was a correlation between Altimetric and traditional citation-based and impact factor metrics. We hypothesized that Altmetric score would more closely correlate with impact factor and citations in 2016. Methods Journal Citation Reports for the year 2013 was used to find the 15 highest impact factor ophthalmology journals in 2013. Then Elsevier's Scopus was used to identify the 10 most cited articles from each journal for the years 2013 and 2016. Metrics for all identified articles were collected using the Altmetric Bookmarklet, and date of Twitter account creation was noted for journals with such an account. Altmetric scores, impact factor, and citation counts were tabulated for each article. Pearson's correlation coefficient (r) determined correlation of independent variables (number of citations or impact factor) with dependent variable (Altmetric score). For our Twitter analysis, account age was the independent variable and calculated correlation coefficients (r) were the dependent variable. Proportion of variance was determined with a coefficient of determination (R 2). Results This study included 300 articles, evenly split between 2013 and 2016. Within the 2013 cohort, three journals had significant positive correlations between citation count and Altmetric score. For the 2016 cohort, both Altmetric score and citation count (r = 0.583, p < 0.001) and Altmetric score and impact factor (r = 0.183, p = 0.025) revealed significant positive correlations. In 2016, two journals were found to have significant correlations between Altmetric score and citation number. Neither year revealed a significant correlation between the age of a journal's Twitter profile and the relationship between Altmetric score and citation count. In each year, Twitter accounted for the highest number of mentions. Conclusion The findings suggest that correlation between Altmetric score and traditional quality metric scores may be increasing. Altmetric score was correlated with impact factor and number of citations in 2016 but not 2013. At this time, Altmetrics are best used as an adjunct that is complementary but not an alternative to traditional bibliometrics for assessing academic productivity and impact.

scholarly journals Bibliometric study of ‘overviews of systematic reviews’ of health interventions: evaluation of prevalence, citation and impact factor

2021 ◽  
Author(s):  
Carole Lunny ◽  
Trish Neelakant ◽  
Alyssa Chen ◽  
Gavindeep Shinger ◽  
Adrienne Stevens ◽  
...  
Keyword(s):  
Impact Factor ◽  
Systematic Reviews ◽  
Citation Count ◽  
Fold Increase ◽  
Impact Factors ◽  
Healthcare Intervention ◽  
Factors Affecting ◽  
Cochrane Database ◽  
Number Of Citations ◽  
Selection Of

Abstract Background: Overviews synthesising the results of multiple systematic reviews help inform evidence-based clinical practice. In this first of two companion papers, we evaluate the bibliometrics of overviews, including their prevalence and factors affecting citation rates and journal impact factor.Methods: We searched MEDLINE, Epistemonikos and Cochrane databases. We included overviews that: (a) synthesised reviews, (b) conducted a systematic search, (c) had a methods section, and (d) examined a healthcare intervention. Multivariate regression was conducted to determine the association between citation density, impact factor and 6 predictor variables. Results: We found 1218 overviews published from 2000 to 2020; the majority (73%) were published in the most recent 5-year period. We extracted a selection of these overviews (n=541; 44%) dated from 2000 to 2018. The 541 overviews were published in 307 journals; Cochrane Database (8%), PLOS ONE (3%) and Sao Paulo Medical Journal (2%) were the most prevalent. The majority (70%) were published in journals with impact factors between 0.05 and 3.97. We found a mean citation count of 10 overviews per year, published in journals with a mean impact factor of 4.4. In multivariate analysis, overviews with a high number of citations and impact factors had more authors, larger sample sizes, were open access and reported the funding source. Conclusions: An 8-fold increase in the number of overviews was found between 2009 and 2020. We identified 332 overviews published in 2020, which is equivalent to 1 overview published per day. Overviews perform above average for the journals in which they publish.

Impact factors, citations, and GEOPHYSICS

Geophysics ◽  
2005 ◽  
Vol 70 (2) ◽  
pp. 3MA-17MA ◽  
Author(s):  
Markku Peltoniemi
Keyword(s):  
Impact Factor ◽  
Citation Count ◽  
Threshold Value ◽  
Impact Factors ◽  
Geophysical Prospecting ◽  
Geophysical Research ◽  
Journal Citation Reports ◽  
History Of Geophysics ◽  
Number Of Citations ◽  
The Impact

This review assesses the contributions and impact that GEOPHYSICS journal has made to both the theory and the applications of exploration geophysics during its publication life span. The contributions are evaluated first on the basis of Journal Citation Reports data, which summarize information available since 1975 about the impact factor of our journal. The impact factor for GEOPHYSICS in 1975–2002 has ranged between 1.461 and 0.591, with an average of 0.924 and with a relative ranking between 16 and 45 for all journals in its category. The journal receiving the highest impact factor for the period 2000–2003 in the “Geochemistry and Geophysics” category is Reviews of Geophysics, with an average impact factor of 7.787 and which ranged between 9.226 and 6.083. A second and important criterion is the frequency with which individual papers published in GEOPHYSICS have been cited elsewhere. This information is available for the entire publication history of GEOPHYSICS and supports the choices made for the early classic papers. These were listed in both the Silver and the Golden Anniversary issues of GEOPHYSICS. In August 2004, the five most-cited papers in GEOPHYSICS published in the time period 1936 to February 2003 are Thomsen (1986) with 423 citations, Constable et al. (1987) with 380 citations, Cagniard (1953) with 354 citations, Sen et al. (1981) with 313 citations, and Stolt (1978) with 307 citations. Fifteen more papers exceed a threshold value of 200 citations. During 2000–2002, GEOPHYSICS, Geophysical Prospecting, Geophysical Journal International, and Journal of Applied Geophysics were the four journals with the highest number of citations of papers published in GEOPHYSICS. In the same 2000–2002 period, those journals in which papers published in GEOPHYSICS are cited most are GEOPHYSICS, Geophysical Prospecting, Geophysical Journal International, and Journal of Geophysical Research. During 1985, the total number of citations in all journals in the Science Citation Index database to papers published in GEOPHYSICS was 2657. By 2002, this same citation count for GEOPHYSICS had increased to 4784.

scholarly journals Auto-correlation of journal impact factor for consensus research reporting statements: a cohort study

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1887 ◽  
Author(s):  
Daniel R. Shanahan
Keyword(s):  
Impact Factor ◽  
Citation Count ◽  
Reporting Guidelines ◽  
Strong Positive Correlation ◽  
Research Reporting ◽  
Median Increase ◽  
Citation Counts ◽  
Number Of Citations ◽  
The Impact ◽  
Journal Impact

Background.The Journal Citation Reports journal impact factors (JIFs) are widely used to rank and evaluate journals, standing as a proxy for the relative importance of a journal within its field. However, numerous criticisms have been made of use of a JIF to evaluate importance. This problem is exacerbated when the use of JIFs is extended to evaluate not only the journals, but the papers therein. The purpose of this study was therefore to investigate the relationship between the number of citations and journal IF for identical articles published simultaneously in multiple journals.Methods.Eligible articles were consensus research reporting statements listed on the EQUATOR Network website that were published simultaneously in three or more journals. The correlation between the citation count for each article and the median journal JIF over the published period, and between the citation count and number of article accesses was calculated for each reporting statement.Results.Nine research reporting statements were included in this analysis, representing 85 articles published across 58 journals in biomedicine. The number of citations was strongly correlated to the JIF for six of the nine reporting guidelines, with moderate correlation shown for the remaining three guidelines (medianr= 0.66, 95% CI [0.45–0.90]). There was also a strong positive correlation between the number of citations and the number of article accesses (medianr= 0.71, 95% CI [0.5–0.8]), although the number of data points for this analysis were limited. When adjusted for the individual reporting guidelines, each logarithm unit of JIF predicted a median increase of 0.8 logarithm units of citation counts (95% CI [−0.4–5.2]), and each logarithm unit of article accesses predicted a median increase of 0.1 logarithm units of citation counts (95% CI [−0.9–1.4]). This model explained 26% of the variance in citations (median adjustedr2= 0.26, range 0.18–1.0).Conclusion.The impact factor of the journal in which a reporting statement was published was shown to influence the number of citations that statement will gather over time. Similarly, the number of article accesses also influenced the number of citations, although to a lesser extent than the impact factor. This demonstrates that citation counts are not purely a reflection of scientific merit and the impact factor is, in fact, auto-correlated.

Reliability of the Minimum Masking Level as Outcome Variable in Tinnitus Clinical Research

2020 ◽  
Vol 29 (3) ◽  
pp. 429-435
Author(s):  
Patricia C. Mancini ◽  
Richard S. Tyler ◽  
Hyung Jin Jun ◽  
Tang-Chuan Wang ◽  
Helena Ji ◽  
...  
Keyword(s):  
Standard Deviation ◽  
High Frequency ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Outcome Variable ◽  
Reliable Estimate ◽  
Moderate Correlation ◽  
Trained Subjects ◽  
The Relationship ◽  
Minimum Intensity

Purpose The minimum masking level (MML) is the minimum intensity of a stimulus required to just totally mask the tinnitus. Treatments aimed at reducing the tinnitus itself should attempt to measure the magnitude of the tinnitus. The objective of this study was to evaluate the reliability of the MML. Method Sample consisted of 59 tinnitus patients who reported stable tinnitus. We obtained MML measures on two visits, separated by about 2–3 weeks. We used two noise types: speech-shaped noise and high-frequency emphasis noise. We also investigated the relationship between the MML and tinnitus loudness estimates and the Tinnitus Handicap Questionnaire (THQ). Results There were differences across the different noise types. The within-session standard deviation averaged across subjects varied between 1.3 and 1.8 dB. Across the two sessions, the Pearson correlation coefficients, range was r = .84. There was a weak relationship between the dB SL MML and loudness, and between the MML and the THQ. A moderate correlation ( r = .44) was found between the THQ and loudness estimates. Conclusions We conclude that the dB SL MML can be a reliable estimate of tinnitus magnitude, with expected standard deviations in trained subjects of about 1.5 dB. It appears that the dB SL MML and loudness estimates are not closely related.

Analysis of the journal impact factor and related bibliometric indicators in education and educational research category

2021 ◽  
pp. 1-22
Author(s):  
Metin Orbay ◽  
Orhan Karamustafaoğlu ◽  
Ruben Miranda
Keyword(s):  
Impact Factor ◽  
Educational Research ◽  
Journal Impact Factor ◽  
Impact Factors ◽  
Bibliometric Indicators ◽  
Strongly Correlated ◽  
Starting Point ◽  
Consistent Assessment ◽  
The Impact ◽  
Journal Impact

This study analyzes the journal impact factor and related bibliometric indicators in Education and Educational Research (E&ER) category, highlighting the main differences among journal quartiles, using Web of Science (Social Sciences Citation Index, SSCI) as the data source. High impact journals (Q1) publish only slightly more papers than expected, which is different to other areas. The papers published in Q1 journal have greater average citations and lower uncitedness rates compared to other quartiles, although the differences among quartiles are lower than in other areas. The impact factor is only weakly negative correlated (r=-0.184) with the journal self-citation but strongly correlated with the citedness of the median journal paper (r= 0.864). Although this strong correlation exists, the impact factor is still far to be the perfect indicator for expected citations of a paper due to the high skewness of the citations distribution. This skewness was moderately correlated with the citations received by the most cited paper of the journal (r= 0.649) and the number of papers published by the journal (r= 0.484), but no important differences by journal quartiles were observed. In the period 2013–2018, the average journal impact factor in the E&ER has increased largely from 0.908 to 1.638, which is justified by the field growth but also by the increase in international collaboration and the share of papers published in open access. Despite their inherent limitations, the use of impact factors and related indicators is a starting point for introducing the use of bibliometric tools for objective and consistent assessment of researcher.

scholarly journals The Relationship Between Soldier Height, Weight and Army Combat Fitness Scores

2021 ◽  
Author(s):  
Ryan Palmer ◽  
Mark DeBeliso
Keyword(s):  
United States Army ◽  
Body Mass ◽  
National Guard ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
The United States ◽  
Military Leaders ◽  
Physical Fitness Test ◽  
Fitness Test ◽  
The Relationship

The United States Army recently implemented the Army Combat Fitness Test (ACFT) which was designed to more accurately measure functional-combat fitness constructs. The ACFT replaced the former Army Physical Fitness Test (APFT). The three advent APFT consisted of: two-minute push-ups (PU), two-minute sit-ups (SU), and a timed two-mile run (RUN). The ACFT consists of six events; 3 Rep Max Deadlift (MDL), Standing Power Throw (SPT), Hand Release Push-up (HRP), Sprint-Drag-Carry (SDC), Hanging Leg Tuck (LTK), and a timed two-mile run (2MR). This study investigated the relationship between Soldier height and body mass kg on ACFT scores of 655 male U.S. Army National Guard Soldiers in a Field Artillery Brigade. For the purpose of the investigation body mass index (BMI) was calculated as the metric representing the Soldier(s) height and weight. The mean and standard deviation (sd) were calculated for the ACFT event and total scores. Pearson correlation coefficients (PCCs or r) were calculated between BMI and ACFT event and total scores. Likewise, PCCs were calculated between the ACFT event and total scores. The ACFT mean(sd) scores were as follows: MDL=92.2(31.8) (3 maximum repetitions), SPT=9.5(2.2) (meters), HRP=24.6(13.1) (repetitions), SDC=119.8(21.7) (seconds), LTK=6.2(5.4) (repetitions), 2MR=1095.0(233.7) (seconds), ACFT total score=442.3(54.4) (points). Significant positive correlations were found between the ACFT total score: MDL (r=0.70), SPT (r=0.50), HRP (r=0.74), and LTK (r=0.76) events. Conversely, significant negative correlations were identified between ACFT total score: SDC (r=-0.68) and 2MR (r=-0.53) events. Within the parameters of this study, Soldier BMI demonstrated no to weak association with individual ACFT event or ACFT total scores. Further, the range of PCCs between the ACFT event scores were no to moderately high. Military leaders may consider the results provided as combat and fitness tests continue to evolve.

scholarly journals Impact Factors Workgroup Report

2017 ◽  
Vol 1 ◽  
Author(s):  
Susie Allard ◽  
Ali Andalibi ◽  
Patty Baskin ◽  
Marilyn Billings ◽  
Eric Brown ◽  
...  
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Impact Factors ◽  
Journal Impact

Following up on recommendations from OSI 2016, this team will dig deeper into the question of developing and recommending new tools to repair or replace the journal impact factor (and/or how it is used), and propose actions the OSI community can take between now and the next meeting. What’s needed? What change is realistic and how will we get there from here?

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