Citation metrics of excellence in sports biomechanics research

Knudson, Duane

doi:10.1080/14763141.2017.1391328

Cited by 8 publications

(7 citation statements)

References 29 publications

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“…The median GS C in the present study (1,794) was similar to the median GS C for professor rank biomechanics faculty worldwide [15]. The median 2,784 GS C in the current study also corresponds to about the 70-80% percentile of international biomechanics scholars with GS Profiles [15] and the median estimated GS C (3,000 to 5,000) at the time of receipt of national or international career awards in sports biomechanics [18].…”

Section: Discussionsupporting

confidence: 76%

“…Median prestige (h) of the top cited sports biomechanics scholars (15 to 21) were consistent with previous studies of senior biomechanics scholars. The median GS h for a sample of national and international sports biomechanics winners was 30 to 36 [18] and this would be at or above the 75 th percentile in the current study (Table 1). The median WoS h for a similar size sample of associate professor and professor rank biomechanists from top biomedical engineering departments in the US and Europe were also higher (20 to 32) than the 75 th percentile in the current study using GS h. Prestige estimated by GS h and RG h will likely higher than h estimates from Scopus or WoS.…”

Section: Discussionmentioning

confidence: 65%

“…It was hypothesized that there would be very strong associations of RG RIS with usage metrics, but moderate associations with prestige metrics. This study expands our understanding of RG RIS, usage and prestige metrics for individual researchers; as well as the initial work on citation patterns of biomechanics scholars across academic rank [15] and related to prestigious awards [16,17,18].…”

Section: Introductionmentioning

confidence: 67%

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Association of ResearchGate research influence score with other metrics of top cited sports biomechanics scholars

Knudson

2023

Biomedical Human Kinetics

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Study aim: Scientific networking sites are increasingly popular in connecting researchers and providing influence metrics, however the research on measures like the ResearchGate Research Influence Score (RG RIS) are limited. This study documented the associations between RG RIS, usage, and prestige metrics from Google Scholar (GS), RG, and Scopus for top cited scientists in sports biomechanics. Material and methods: Research usage (total citations: C), prestige (Hirsch index: h), and RG RIS metrics were extracted from GS, RG, and Scopus for the top sixty cited scholars that used either the label “’73ports biomechanics” or “sport biomechanics” in their GS Profile. Results: RG RIS was strongly correlated (r = 0.796–0.895) with all usage and prestige metrics. There were very strong correlations among the three citation metrics (r = 0.929–0.967) and among the three h indexes (r = 0.960–0.974). Conclusions: The recent RG RIS does not provide unique scientific influence information about sport(s) biomechanics researchers beyond common citation metrics. The RG RIS was strongly associated with total citation and h-index values from GS, RG, and Scopus for top 60 cited sport(s) biomechanics researchers based on GS Profiles. The scientific usage and prestige factors previously reported in bibliometric research was supported by very strong associations among the three C and among the three h index values from these two scientific networking and one database service.

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Section: Discussionsupporting

confidence: 76%

Section: Discussionmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 67%

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Association of ResearchGate research influence score with other metrics of top cited sports biomechanics scholars

Knudson

2023

Biomedical Human Kinetics

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“…Statistical education was a key recurring theme throughout the thematic analysis and is supported by the quantitative results as respondents selected poor experimental design, inadequate mentoring, low statistical power, and mistakes as contributing factors towards a failure to replicate. Statistical and methodological errors are prevalent in sports and exercise science (Knudson, 2005;Nielsen et al, 2018;Borg, Lohse and Sainani, 2020). The use of controversial statistical methods even resulted in mainstream media criticism (Aschwanden and Nguyen, 2018;Sainani et al, 2019).…”

Section: )mentioning

confidence: 99%

Survey on the Attitudes Towards and Perception of Reproducibility and Replicability in Sports and Exercise Science

Murphy

Mesquida

Warne

2023

Commun in Kinesiology

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There are formal calls for increased reproducibility and replicability in sports and exercise science, yet there is minimal information on the overall knowledge of these concepts at a field-wide level. Therefore, we conducted a survey on the attitudes and perceptions of sports and exercise science researchers towards reproducibility and replicability. Descriptive statistics (e.g., proportion of responses), and thematic analysis, were utilized to characterize the responses. Of the 511 respondents, 42% (n = 217) believe there is a significant crisis of reproducibility or replicability in sports and exercise science while 36% (n = 182) believe there is a slight crisis. 3% (n = 15) of respondents believe there is no crisis while 19% (n = 95) did not know. Four themes were generated in the thematic analysis: the research and publishing culture, educational barriers to research integrity, research responsibility to ensure reproducibility and replicability, and current practices facilitating reproducibility and replicability. Researchers believe that engaging in open science can be detrimental to career opportunities due to lack of incentives. They also feel journals are a barrier to reproducible and replicable research due to high publication charges and a focus on novelty. Statistical expertise was identified as a key factor for improving reproducibility and replicability in the future, particularly, a better understanding of study design and different statistical techniques. Statistical education should be prioritised for early career researchers which could positively affect publication and peer review. Researchers must accept responsibility for reproducibility and replicability with thorough project design, appropriate planning of analyses, and transparent reporting practices.

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“…Sports biomechanics is an important required course, which deems biomechanics as the key point to analyze the influence of human movements on human body from the perspective of biology and combines theory and practice for movement essentials in sports [4]. At present, sports biomechanics is characterized by the combination of biomechanics knowledge and movements, and teachers can teach it with a flexible teaching method.…”

Section: State Of the Artmentioning

confidence: 99%

Individualized New Teaching Mode for Sports Biomechanics based on Big Data

Liu

Zhu

2020

Int. J. Emerg. Technol. Learn.

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Sports biomechanics is an applied discipline with relatively strong theoretical knowledge. At present, it is used as an analysis means in exercise training in various countries and plays a huge promotion role for the development of competitive sports and sports science. However, phenomena, such as single-teaching methods, fixed-teaching thinking, backward-teaching environment, and hardware, still exist in the current education for sports biomechanics. For such phenomena, we perform individualized IRDC (Internet + retrieval literature + big data + cloud) teaching by using the Internet big data analysis and considering different characteristics of every student and apply it in online teaching of sports biomechanics course. We base our proposed individualized IRDC teaching mode on postmodern curriculum theory. According to four features, namely, rich, recursive, relational, and rigorous, we propose an individualized IRDC online teaching mode in this study. Moreover, we apply a new wireless telemetry surface EMG tester as a learning tool of practical teaching in the teaching mode, which we use to acquire Internet information data of online course and induce a real time communication between teachers and students. Finally, we adopt the principal component analysis to develop evaluation indices, including expert evaluation in and out of school and peer teacher evaluation, for the teaching mode. We find through teaching practice that the proposed individualized IRDC teaching mode can make the best of advantages of big data teaching, help teachers implement targeted individualized teaching, and contribute to the improvement of students' academic performance and comprehensive qualities.

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Citation metrics of excellence in sports biomechanics research

Cited by 8 publications

References 29 publications

Association of ResearchGate research influence score with other metrics of top cited sports biomechanics scholars

Association of ResearchGate research influence score with other metrics of top cited sports biomechanics scholars

Survey on the Attitudes Towards and Perception of Reproducibility and Replicability in Sports and Exercise Science

Individualized New Teaching Mode for Sports Biomechanics based on Big Data

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