Scopus's Source Normalized Impact per Paper (SNIP) versus a Journal Impact Factor based on Fractional Counting of Citations

Impact factors (and similar measures such as the Scimago Journal Rankings) suffer from two problems: (i) citation behavior varies among fields of science and therefore leads to systematic differences, and (ii) there are no statistics to inform us whether differences are significant. The recently introduced SNIP indicator of Scopus tries to remedy the first of these two problems, but a number of normalization decisions are involved which makes it impossible to test for significance. Using fractional counting of citations-based on the assumption that impact is proportionate to the number of references in the citing documents-citations can be contextualized at the paper level and aggregated impacts of sets can be tested for their significance. It can be shown that the weighted impact of Annals of Mathematics (0.247) is not so much lower than that of Molecular Cell (0.386) despite a five-fold difference between their impact factors (2.793 and 13.156, respectively)

Mathematical properties of weighted impact factors based on measures of prestige of the citing journals

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-015-1741-0An abstract construction for general weighted impact factors is introduced. We show that the classical weighted impact factors are particular cases of our model, but it can also be used for defining new impact measuring tools for other sources of information as repositories of datasets providing the mathematical support for a new family of altmet- rics. Our aim is to show the main mathematical properties of this class of impact measuring tools, that hold as consequences of their mathematical structure and does not depend on the definition of any given index nowadays in use. In order to show the power of our approach in a well-known setting, we apply our construction to analyze the stability of the ordering induced in a list of journals by the 2-year impact factor (IF2). We study the change of this ordering when the criterium to define it is given by the numerical value of a new weighted impact factor, in which IF2 is used for defining the weights. We prove that, if we assume that the weight associated to a citing journal increases with its IF2, then the ordering given in the list by the new weighted impact factor coincides with the order defined by the IF2. We give a quantitative bound for the errors committed. We also show two examples of weighted impact factors defined by weights associated to the prestige of the citing journal for the fields of MATHEMATICS and MEDICINE, GENERAL AND INTERNAL, checking if they satisfy the increasing behavior mentioned above.Ferrer Sapena, A.; Sánchez Pérez, EA.; González, LM.; Peset Mancebo, MF.; Aleixandre Benavent, R. (2015). Mathematical properties of weighted impact factors based on measures of prestige of the citing journals. Scientometrics. 105(3):2089-2108. https://doi.org/10.1007/s11192-015-1741-0S208921081053Ahlgren, P., & Waltman, L. (2014). The correlation between citation-based and expert-based assessments of publication channels: SNIP and SJR vs. Norwegian quality assessments. Journal of Informetrics, 8, 985–996.Aleixandre Benavent, R., Valderrama Zurián, J. C., & González Alcaide, G. (2007). Scientific journals impact factor: Limitations and alternative indicators. El Profesional de la Información, 16(1), 4–11.Altmann, K. G., & Gorman, G. E. (1998). The usefulness of impact factor in serial selection: A rank and mean analysis using ecology journals. Library Acquisitions-Practise and Theory, 22, 147–159.Arnold, D. N., & Fowler, K. K. (2011). Nefarious numbers. Notices of the American Mathematical Society, 58(3), 434–437.Beliakov, G., & James, S. (2012). Using linear programming for weights identification of generalized bonferroni means in R. In: Proceedings of MDAI 2012 modeling decisions for artificial intelligence. Lecture Notes in Computer Science, Vol. 7647, pp. 35–44.Beliakov, G., & James, S. (2011). Citation-based journal ranks: The use of fuzzy measures. Fuzzy Sets and Systems, 167, 101–119.Buela-Casal, G. (2003). Evaluating quality of articles and scientific journals. Proposal of weighted impact factor and a quality index. Psicothema, 15(1), 23–25.Dorta-Gonzalez, P., & Dorta-Gonzalez, M. I. (2013). Comparing journals from different fields of science and social science through a JCR subject categories normalized impact factor. Scientometrics, 95(2), 645–672.Dorta-Gonzalez, P., Dorta-Gonzalez, M. I., Santos-Penate, D. R., & Suarez-Vega, R. (2014). Journal topic citation potential and between-field comparisons: The topic normalized impact factor. Journal of Informetrics, 8(2), 406–418.Egghe, L., & Rousseau, R. (2002). A general frame-work for relative impact indicators. Canadian Journal of Information and Library Science, 27(1), 29–48.Gagolewski, M., & Mesiar, R. (2014). Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. Information Sciences, 263, 166–174.Garfield, E. (2006). The history and meaning of the journal impact factor. JAMA, 295(1), 90–93.Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172.Klement, E., Mesiar, R., & Pap, E. (2010). A universal integral as common frame for Choquet and Sugeno integral. IEEE Transaction on Fuzzy System, 18, 178–187.Leydesdorff, L., & Opthof, T. (2010). Scopus’s source normalized impact per paper (SNIP) versus a journal impact factor based on fractional counting of citations. Journal of the American Society for Information Science and Technology, 61, 2365–2369.Li, Y. R., Radicchi, F., Castellano, C., & Ruiz-Castillo, J. (2013). Quantitative evaluation of alternative field normalization procedures. Journal of Informetrics, 7(3), 746–755.Moed, H. F. (2010). Measuring contextual citation impact of scientific journals. Journal of Informetrics, 4, 265–277.NISO. (2014). Alternative metrics initiative phase 1. White paper. http://www.niso.org/apps/group-public/download.php/13809/Altmetrics-project-phase1-white-paperOwlia, P., Vasei, M., Goliaei, B., & Nassiri, I. (2011). Normalized impact factor (NIF): An adjusted method for calculating the citation rate of biomedical journals. Journal of Biomedical Informatics, 44(2), 216–220.Pinski, G., & Narin, F. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing and Management, 12, 297–312.Pinto, A. C., & Andrade, J. B. (1999). Impact factor of scientific journals: What is the meaning of this parameter? Quimica Nova, 22, 448–453.Raghunathan, M. S., & Srinivas, V. (2001). Significance of impact factor with regard to mathematics journals. Current Science, 80(5), 605.Ruiz Castillo, J., & Waltman, L. (2015). Field-normalized citation impact indicators using algorithmically constructed classification systems of science. Journal of Informetrics, 9, 102–117.Saha, S., Saint, S., & Christakis, D. A. (2003). Impact factor: A valid measure of journal quality? Journal of the Medical Library Association, 91, 42–46.Torra, V., & Narukawa, Y. (2008). The h-index and the number of citations: Two fuzzy integrals. IEEE Transaction on Fuzzy System, 16, 795–797.Torres-Salinas, D., & Jimenez-Contreras, E. (2010). Introduction and comparative study of the new scientific journals citation indicators in journal citation reports and scopus. El Profesional de la Información, 19, 201–207.Waltman, L., & van Eck, N. J. (2008). Some comments on the journal weighted impact factor proposed by Habibzadeh and Yadollahie. Journal of Informetrics, 2(4), 369–372.Waltman, L., van Eck, N. J., van Leeuwen, T. N., & Visser, M. S. (2013). Some modifications to the SNIP journal impact indicator. Journal of Informetrics, 7, 272–285.Zitt, M. (2011). Behind citing-side normalization of citations: some properties of the journal impact factor. Scientometrics, 89, 329–344.Zitt, M., & Small, H. (2008). Modifying the journal impact factor by fractional citation weighting: The audience factor. Journal of the American Society for Information Science and Technology, 59, 1856–1860.Zyczkowski, K. (2010). Citation graph, weighted impact factors and performance indices. Scientometrics, 85(1), 301–315

Popular and/or Prestigious? Measures of Scholarly Esteem

Citation analysis does not generally take the quality of citations into account: all citations are weighted equally irrespective of source. However, a scholar may be highly cited but not highly regarded: popularity and prestige are not identical measures of esteem. In this study we define popularity as the number of times an author is cited and prestige as the number of times an author is cited by highly cited papers. Information Retrieval (IR) is the test field. We compare the 40 leading researchers in terms of their popularity and prestige over time. Some authors are ranked high on prestige but not on popularity, while others are ranked high on popularity but not on prestige. We also relate measures of popularity and prestige to date of Ph.D. award, number of key publications, organizational affiliation, receipt of prizes/honors, and gender.Comment: 26 pages, 5 figure

Vector-valued impact measures and generation of specific indexes for research assessment

A mathematical structure for defining multi-valued bibliometric indices is provided with the aim of measuring the impact of general sources of information others than articles and journals-for example, repositories of datasets. The aim of the model is to use several scalar indices at the same time for giving a measure of the impact of a given source of information, that is, we construct vector valued indices. We use the properties of these vector valued indices in order to give a global answer to the problem of finding the optimal scalar index for measuring a particular aspect of the impact of an information source, depending on the criterion we want to fix for the evaluation of this impact. The main restrictions of our model are (1) it uses finite sets of scalar impact indices (altmetrics), and (2) these indices are assumed to be additive. The optimization procedure for finding the best tool for a fixed criterion is also presented. In particular, we show how to create an impact measure completely adapted to the policy of a specific research institution.Calabuig, JM.; Ferrer Sapena, A.; Sánchez Pérez, EA. (2016). Vector-valued impact measures and generation of specific indexes for research assessment. Scientometrics. 108(3):1425-1443. doi:10.1007/s11192-016-2039-6S142514431083Aleixandre Benavent, R., Valderrama Zurián, J. C., & González Alcaide, G. (2007). Scientific journals impact factor: Limitations and alternative indicators. El Profesional de la Información, 16(1), 4–11.Alguliyev, R., Aliguliyev, R. & Ismayilova, N. (2015). Weighted impact factor (WIF) for assessing the quality of scientific journals. arXiv:1506.02783Beauzamy, B. (1982). Introduction to Banach spaces and their geometry. Amsterdam: North-Holland.Beliakov, G., & James, S. (2011). Citation-based journal ranks: the use of fuzzy measures. Fuzzy Sets and Systems, 167, 101–119.Buela-Casal, G. (2003). Evaluating quality of articles and scientific journals. Proposal of weighted impact factor and a quality index. Psicothema, 15(1), 23–25.Diestel, J., & Uhl, J. J. (1977). Vector measures. Providence: Am. Math. Soc.Dorta-González, P., & Dorta-González, M. I. (2013). Comparing journals from different fields of science and social science through a JCR subject categories normalized impact factor. Scientometrics, 95(2), 645–672.Dorta-González, P., Dorta-González, M. I., Santos-Penate, D. R., & Suarez-Vega, R. (2014). Journal topic citation potential and between-field comparisons: The topic normalized impact factor. Journal of Informetrics, 8(2), 406–418.Egghe, L., & Rousseau, R. (2002). A general frame-work for relative impact indicators. Canadian Journal of Information and Library Science, 27(1), 29–48.Ferrer-Sapena, A., Sánchez-Pérez, E. A., González, L. M., Peset, F. & Aleixandre-Benavent, R. (2016). The impact factor as a measuring tool of the prestige of the journals in research assessment in mathematics. Research Evaluation, 1–9. doi: 10.1093/reseval/rvv041 .Ferrer-Sapena, A., Sánchez-Pérez, E. A., González, L. M., Peset, F., & Aleixandre-Benavent, R. (2015). Mathematical properties of weighted impact factors based on measures of prestige of the citing journals. Scientometrics, 105(3), 2089–2108.Gagolewski, M., & Mesiar, R. (2014). Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. Information Sciences, 263, 166–174.Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172.Klement, E., Mesiar, R., & Pap, E. (2010). A universal integral as common frame for Choquet and Sugeno integral. IEEE Transactions on Fuzzy Systems, 18, 178–187.Leydesdorff, L., & Opthof, T. (2010). Scopus’s source normalized impact per paper (SNIP) versus a journal impact factor based on fractional counting of citations. Journal of the American Society for Information Science and Technology, 61, 2365–2369.Li, Y. R., Radicchi, F., Castellano, C., & Ruiz-Castillo, J. (2013). Quantitative evaluation of alternative field normalization procedures. Journal of Informetrics, 7(3), 746–755.Moed, H. F. (2010). Measuring contextual citation impact of scientific journals. Journal of Informetrics, 4, 265–277.Owlia, P., Vasei, M., Goliaei, B., & Nassiri, I. (2011). Normalized impact factor (NIF): An adjusted method for calculating the citation rate of biomedical journals. Journal of Biomedical Informatics, 44(2), 216–220.Pinski, G., & Narin, F. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing and Management, 12, 297–312.Piwowar, H. (2013). Altmetrics: Value all research products. Nature, 493(7431), 159–159.Pudovkin,A.I., & Garfield, E. (2004). Rank-normalized impact factor: A way to compare journal performance across subject categories. In Proceedings of the 67th annual meeting of the American Society for Information science and Technology, 41, 507-515.Rousseau, R. (2002). Journal evaluation: Technical and practical issues. Library Trends, 50(3), 418–439.Ruiz Castillo, J., & Waltman, L. (2015). Field-normalized citation impact indicators using algorithmically constructed classification systems of science. Journal of Informetrics, 9, 102–117.Torra, V., & Narukawa, Y. (2008). The h-index and the number of citations: Two fuzzy integrals. IEEE Transactions on Fuzzy Systems, 16, 795–797.Waltman, L., & van Eck, N. J. (2008). Some comments on the journal weighted impact factor proposed by Habibzadeh and Yadollahie. Journal of Informetrics, 2(4), 369–372.Waltman, L., & van Eck, N. J. (2010). The relation between Eigenfactor, audience factor, and influence weight. Journal of the American Society for Information Science and Technology, 61, 1476–1486.Zahedi, Z., Costas, R., & Wouters, P. (2014). How well developed are altmetrics? A cross-disciplinary analysis of the presence of ’alternative metrics’ in scientific publications. Scientometrics, 101(2), 1491–1513.Zitt, M. (2010). Citing-side normalization of journal impact: A robust variant of the Audience Factor. Journal of Informetrics, 4(3), 392–406.Zitt, M. (2011). Behind citing-side normalization of citations: Some properties of the journal impact factor. Scientometrics, 89, 329–344.Zitt, M., & Small, H. (2008). Modifying the journal impact factor by fractional citation weighting: The audience factor. Journal of the American Society for Information Science and Technology, 59, 1856–1860.Zyczkowski, K. (2010). Citation graph, weighted impact factors and performance indices. Scientometrics, 85(1), 301–315

Assessing the Scientific Research Productivity of a Brazilian Healthcare Institution: A Case Study at the Heart Institute of São Paulo, Brazil

INTRODUCTION: The present study was motivated by the need to systematically assess the research productivity of the Heart Institute (InCor), Medical School of the University of São Paulo, Brazil. OBJECTIVE: To explore methodology for the assessment of institutional scientific research productivity. MATERIALS AND METHODS: Bibliometric indicators based on searches for author affiliation of original scientific articles or reviews published in journals indexed in the databases Web of Science, MEDLINE, EMBASE, LILACS and SciELO from January 2000 to December 2003 were used in this study. The retrieved records were analyzed according to the index parameters of the journals and modes of access. The number of citations was used to calculate the institutional impact factor. RESULTS: Out of 1253 records retrieved from the five databases, 604 original articles and reviews were analyzed; of these, 246 (41%) articles were published in national journals and 221 (90%) of those were in journals with free online access through SciELO or their own websites. Of the 358 articles published in international journals, 333 (93%) had controlled online access and 223 (67%) were available through the Capes Portal of Journals. The average impact of each article for InCor was 2.224 in the period studied. CONCLUSION: A simple and practical methodology to evaluate the scientific production of health research institutions includes searches in the LILACS database for national journals and in MEDLINE and the Web of Science for international journals. The institutional impact factor of articles indexed in the Web of Science may serve as a measure by which to assess and review the scientific productivity of a research institution

The Autism Spectrum Quotient-Revised: A measure to better identify the Autism Spectrum Disorder presentation in females?

Literature reflects a growing concern that females may be "slipping through the net" because current understanding of the autistic phenotype and diagnostic approaches are derived primarily from research on males. The present study sought to develop a psychometrically sound revision of the Autism Spectrum Quotient (AQ), to improve its sensitivity in identifying adult females with high levels of Autism Spectrum Disorder (ASD) traits. In phase one of the study, 30 experienced ASD practitioners rated how relevant they thought 20 newly developed screening items were to ASD in females. Fifteen of these items were then added into the existing AQ, comprising the AQ-Revised. Alongside measures assessing convergent and divergent validity and levels of distress and impairment, 1007 non-ASD (55% female) and 45 ASD (51% female) participants completed the AQ-Revised. The AQ-Revised and the AQ were found to be psychometrically sound and both fit a 2-factor structure, based on factor analyses. No significant gender differences were apparent in non-ASD participants on the total AQ-Revised, however in the ASD group females scored significantly higher on the total AQ-Revised and AQ scores compared to males. The AQ-Revised was found to discriminate well between ASD and non-ASD cases and, with a cut off score of 29, captured 130 more females high on ASD traits than the existing AQ. These women scoring above 29 on the measure were found to have significantly higher levels of distress and functional impairment than those scoring below 29, but reported levels of distress and impairment were equivalent to women scoring above the recommended AQ cut off (32). The utility of the revised instrument for females and the concept of gender-specific ASD screening are discussed

Isaac Asimov’s sci-fi novella “Profession” versus professionalism: Reflections on the (missing) scientific revolutions in the 21th century

This is a partly provocative essay edited as a humanitarian study in philosophy of science and social philosophy. The starting point is Isaac Asimov’s famous sci-fi novella “Profession” (1957) to be “back” extrapolated to today’s relation between Thomas Kuhn’s “normal science” and “scientific revolutions” (1962). The latter should be accomplished by Asimov’s main personage George Platen’s ilk (called “feeble minded” in the novella) versus the “burned minded” professionals able only to “normal science”. Francis Fukuyama’s “end of history” in post-Hegelian manner is now interpreted to an analogically supposed “end of scientific history” without “scientific revolutions” any more. The relevant dystopia of the prolonged or even “eternal” period of normal science is justified to the contemporary institution of science due to mechanisms such as “peer-review”, “impact-factor rating”, the projects’ competition for funding, etc. Positive feedbacks forcing all scientists needing careers to be more and more orthodox are demonstrated therefore establishing for that dystopia to be the real state of contemporary science. Two counterfactual case studies based correspondingly on Feyerabend’s “Against method” (1975) if Galilei should make his discoveries today and Sokal’s hoax (1996) if he suggested a scientific masterpiece to be really rejected by journals are discussed. Still one case study considering the abundance of Kelvin’s “clouds” on the horizon of today’s physics (dark matter, dark energy, entanglement, quantum gravitation, phenomena refuting the Big Bang, etc.) serves to verify the aforementioned conjecture that science has already entered that dystopia of eternal normal science. The conception of “ontomathematics” implying “creation ex nihilo” being scandalous for the dominating paradigm is sketched as an eventual revolutionary way out. An imaginary and utopic “happy end” reinterpreting the analogical “happy end” of Asimov’s “Profession” finishes the essay “instead of conclusion” relying on the Internet and AI in an increasingly “fluid” and anti-hierarchical society

Public health law in Timor-Leste

Post-conflict, ‘fragile’ nations face significant health, social, economic and political challenges. The international community is, on the whole, organised and effective in assisting these nations to address urgent priorities. Often, however, prioritisation of immediate concerns has resulted in less focus being given to capacity building, including the fostering of lasting, effective and autonomous systems within these nations.This study examined the post-conflict, transitional nation of Timor-Leste. In particular, it focused on the potential for a health systems-strengthening approach, public health law, to improve the exceptionally poor level of population health found in Timor-Leste. Public health law has a long history within the developed world of success in facilitating the prevention and control of disease. The extent to which law can assist in addressing key health concerns within the developing world has, however, attracted little attention to date.This thesis documents a social and political history of Timor-Leste and provides a review of selected population health indicators. An overview of the Timorese health and legal systems is provided with a focus on system capacity, existing public health law and reported strategic directions. The review is complemented by a survey of 245 residents of Dili, the capital of Timor-Leste, in order to ascertain levels of community awareness of, and support for, selected existing public health laws. Further context was provided through in-depth interviews with 19 health and legal professionals living and working in Timor-Leste. Importantly the study was designed and conducted according to guidance provided by four Timorese cultural advisors.Awareness of law is clearly essential if it is to be effective as a preventive intervention. Community support for law is arguably also fundamental if there is to be widespread adherence to law and political willingness to pursue law reform. Key dependent variables within the community survey and interviews with professionals included awareness of, and support for, public health law amongst a suite of specific regulatory areas including road safety, the sale of alcohol and tobacco to children, food safety and water safety. These areas were selected due to their existing or steadily increasing importance in the developing world. Quantitative analytical methods included Chi-square for examining differences between survey sub-groups, and Kendall’s tau-b for examining correlations between ordinal variables. Qualitative data from interviews was subject to thematic analysis.Analysis of survey and interview data highlighted a poor level of awareness of selected existing public health laws in Timor-Leste amongst participating community members and health and legal professionals. A number of demographic factors were identified as being statistically associated with levels of awareness within the community and these provide direction for future educative efforts. Encouragingly, this study has also identified a strong level of support for public health law amongst both community and professional groups. Support was high for the legal approach to health law overall and for each of the regulatory areas examined. Attitudinal factors associated with community support were identified and these provide guidance for future efforts to raise understanding and acceptance of public health law in Timor- Leste.The review of the health and legal systems, however, highlights that there currently exists an incomplete set of laws that lacks cohesion and accessibility in Timor-Leste: an analysis of applicable law requires a detailed investigation of Timorese and Indonesian law, and United Nations regulations. There appears also to be little systemic capacity to enforce existing, or develop additional, law and regulation. Public health law reform, furthermore, does not appear to be among the Timor-Leste government’s strategic directions.This study is one of few undertaken globally on public health law in a developing, post-conflict transitional society. The observation of widespread support for the legal approach to health provides impetus and direction to the proposition of a coordinated and resourced public health law strategy in Timor-Leste. Recommendations have been provided to address some of the current barriers to such a strategy, including capacity constraints, low awareness and low political and public service profile. Finally a theoretical framework is provided to specifically guide further research and implementation of public health law in Timor-Leste and similar settings

A Longitudinal Examination of Biomechanical Balance and Quantitative Multidomain Assessments During Recovery Following Sport-Related Concussion

Sport-related concussion is an inherent risk to athlete health in contact and collision sports. Both short- and long-term risks are associated with the injury. Short-term, athletes may develop post-concussion syndrome (PCS), the persistence of cognitive, physical, and emotional symptoms for weeks or months after injury. Athletes who return to play (RTP) prematurely are at increased risk for lower extremity injury and repeated concussion injuries. Long-term, history of multiple concussions have been linked to neurodegenerative diseases. Due to these risks, concussion assessments must be sensitive to the injury and useful in the diagnosis, recovery, and RTP phases of the injury. Sideline clinical assessments for symptoms, balance, and neurocognition among other domains are utilized to meet the recommendation for a multidomain approach to concussion assessment. Particularly in balance testing, there is concern that standard observational sideline tests do not measure lasting balance deficits for more than three days post-injury. Biomechanical balance measures appear to longitudinally assess sensory integration capabilities of concussed athletes better than clinical observational scoring. This dissertation measured the sensitivity of biomechanical balance measures to concussion longitudinally in athletes up to 6 months post-injury, and in athletes reporting a history of concussion. Sensitive biomechanical balance measures were then assessed in multidomain logistic regression models to determine the most longitudinally sensitive combination of multidomain assessments to concussion. A combined cohort of 186 National Collegiate Athletic Association (NCAA) Division I (DI) athletes at the University of Denver participated in this research. Each athlete participated in an extensive data collection, including instrumented standing and functional balance tasks, neurocognitive assessment, oculomotor assessment, vestibular-ocular assessment, a blood draw, and symptom scoring. Specific Aim 1 assessed the discriminative ability and sensitivity to concussion of linear measures of biomechanical balance in a comparison of non-concussed athletes to concussed athletes tracked longitudinally up to 6 months post-injury. Specific Aim 2 evaluated group differences between non-concussed athletes and those with a documented history of concussion more than 6 months post-injury of linear and nonlinear measures of biomechanical balance. Specific Aim 3 evaluated the longitudinally sensitive and discriminatory measures of biomechanical balance from Aim 1 in multidomain logistic regression models to determine the most longitudinally sensitive combination of multidomain assessments. Together, these Specific Aims indicate that linear measures of COP velocity in standing balance discriminate well between non-concussed and acutely concussed athletes and are longitudinally sensitive to concussion up to 6 months post-injury. These measures also show deficits in athletes with a history of concussion, indicating a potential lack of vestibular and sensorimotor integration recovery leading to reduced neuromuscular functioning. Lastly, these measures on their own generate a model that is longitudinally sensitive to concussion and may aid in concussion recovery, rehabilitation, and RTP decision making