Background:The Victorian Institute of Sport Assessment–Patella(VISA-P) scale is the most condition-specific patient-reported outcome measure used to assess symptom severity in athletes with patellar tendinopathy.Prev...Background:The Victorian Institute of Sport Assessment–Patella(VISA-P) scale is the most condition-specific patient-reported outcome measure used to assess symptom severity in athletes with patellar tendinopathy.Previous exploratory factor analyses have been conducted to evaluate the scale's dimensionality,with inconsistent results,and the factor structure of the scale remains unclear.The aims of the present study were to determine the factorial structure of the VISA-P scale using confirmatory factor analysis(CFA) and test measurement invariance across sexes.Methods:The study included a convenience sample of 249 Spanish athletes with patellar tendinopathy.CFA was performed to assess factorial validity.Hypothesized 1-and 2-factor models were tested.Measurement invariance across sexes was evaluated via multi-group CFA with several fit indices using EQS 6.1 software.Results:The internal consistency coefficient was 0.74.Several CFA models were examined and the 1-factor model in which errors for Items 7 and8 were correlated showed acceptable fit in terms of comparative fit index(CFI) and goodness-of-fit index(GFI) statistics(CFI = 0.93;GFI = 0.94;standardized root mean square residual = 0.06;root mean square error of approximation = 0.10;90% confidence interval:0.08–0.13).This model was invariant across sexes.Conclusion:The 1-factor model of the Spanish version of the VISA-P scale(VISA-P-Sp) in which errors for Items 7 and 8 were correlated demonstrated relative fit in CFA.Scores obtained via VISA-P-Sp can be compared between men and women without sexes bias.Further studies should examine the VISA-P scale and other single-score patient-reported outcome measures concurrently.展开更多
This article proposes a novel methodology that uses mathematical and numerical models of a structure to build a data set and determine crucial nodes that possess the highest sensitivity.Regression surfaces between the...This article proposes a novel methodology that uses mathematical and numerical models of a structure to build a data set and determine crucial nodes that possess the highest sensitivity.Regression surfaces between the structural parameters and structural output features,represented by the natural frequencies of the structure and local transmissibility,are built using the numerical data set.A description of a possible experimental application is provided,where sensors are mounted at crucial nodes,and the natural frequencies and local transmissibility at each natural frequency are determined from the power spectral density and the power spectral density ratios of the sensor responses,respectively.An inverse iterative process is then applied to identify the structural parameters by matching the experimental features with the available parameters in the myriad numerical data set.Three examples are presented to demonstrate the feasibility and efficacy of the proposed methodology.The results reveal that the method was able to accurately identify the boundary coefficients and physical parameters of the Euler-Bemoulli beam as well as a highway bridge model with elastic foundations using only two measurement points.It is expected that the proposed method will have practical applications in the identification and analysis of restored structural systems with unknown parameters and boundary coefficients.展开更多
文摘Background:The Victorian Institute of Sport Assessment–Patella(VISA-P) scale is the most condition-specific patient-reported outcome measure used to assess symptom severity in athletes with patellar tendinopathy.Previous exploratory factor analyses have been conducted to evaluate the scale's dimensionality,with inconsistent results,and the factor structure of the scale remains unclear.The aims of the present study were to determine the factorial structure of the VISA-P scale using confirmatory factor analysis(CFA) and test measurement invariance across sexes.Methods:The study included a convenience sample of 249 Spanish athletes with patellar tendinopathy.CFA was performed to assess factorial validity.Hypothesized 1-and 2-factor models were tested.Measurement invariance across sexes was evaluated via multi-group CFA with several fit indices using EQS 6.1 software.Results:The internal consistency coefficient was 0.74.Several CFA models were examined and the 1-factor model in which errors for Items 7 and8 were correlated showed acceptable fit in terms of comparative fit index(CFI) and goodness-of-fit index(GFI) statistics(CFI = 0.93;GFI = 0.94;standardized root mean square residual = 0.06;root mean square error of approximation = 0.10;90% confidence interval:0.08–0.13).This model was invariant across sexes.Conclusion:The 1-factor model of the Spanish version of the VISA-P scale(VISA-P-Sp) in which errors for Items 7 and 8 were correlated demonstrated relative fit in CFA.Scores obtained via VISA-P-Sp can be compared between men and women without sexes bias.Further studies should examine the VISA-P scale and other single-score patient-reported outcome measures concurrently.
基金The research described in this paper was funded by the Mid-America Transportation Center through a grant from the US Department of Transportation's University Transportation Centers Program(Grant No.DOT 69A3551747107)The contents reflect the views of the authors,who are responsible for the veracity and accuracy of the information presented herein and are not necessarily representative of the views of the sponsoring agencies.
文摘This article proposes a novel methodology that uses mathematical and numerical models of a structure to build a data set and determine crucial nodes that possess the highest sensitivity.Regression surfaces between the structural parameters and structural output features,represented by the natural frequencies of the structure and local transmissibility,are built using the numerical data set.A description of a possible experimental application is provided,where sensors are mounted at crucial nodes,and the natural frequencies and local transmissibility at each natural frequency are determined from the power spectral density and the power spectral density ratios of the sensor responses,respectively.An inverse iterative process is then applied to identify the structural parameters by matching the experimental features with the available parameters in the myriad numerical data set.Three examples are presented to demonstrate the feasibility and efficacy of the proposed methodology.The results reveal that the method was able to accurately identify the boundary coefficients and physical parameters of the Euler-Bemoulli beam as well as a highway bridge model with elastic foundations using only two measurement points.It is expected that the proposed method will have practical applications in the identification and analysis of restored structural systems with unknown parameters and boundary coefficients.
