The validity of the Physical Literacy in Children Questionnaire in children aged 4 to 12

BACKGROUND

Given the growing evidence on the health benefits associated with physical literacy (PL), it is necessary to develop sound measures to assess the levels of PL in children. The Physical Literacy in Children Questionnaire (PL-C Quest) is the first self-report pictorial-based scale to assess children's perceived PL. It has good validity and reliability in Australian children aged 7 to 12 years, but little is known in younger children and in other cultural contexts. The aim of this study was to examine the validity and reliability in an expanded age range.

METHODS

A total of 1,870 Chinese children (girls, n = 871; 46.6%), aged 4 to 12 years (M = 8.07 ± 2.42) participated in validity testing. Structural equation modeling with the Weighted Least Squares with Mean and Variance approach was used to assess construct validity. The hypothesized theoretical model used the 30 items and four hypothesized factors: physical, psychological, social and cognitive capabilities. Multigroup confirmatory factor analysis was used to assess sex and age group (4-6 years, 7-9 years and 10-12 years) measurement invariance. Internal consistency analyses were conducted using polychoric alpha. A random subsample (n = 262) was selected to determine test-retest reliability using Intra-Class Correlations (ICC).

RESULTS

All items except one (moving with equipment-skateboarding) loaded on sub-domains with λ > 0.45. The hypothesized model had a good fit (CFI = 0.954, TLI = 0.950, RMSEA = 0.042), with measurement equivalence across sex and age groups separately. Internal consistency values were good to excellent (overall: α = 0.94; physical: α = 0.86; psychological: α = 0.83; social: α = 0.81; cognitive: α = 0.86). Test-retest reliability was adequate to excellent (overall: ICC = 0.90, physical: ICC = 0.86, psychological: ICC = 0.75, social: ICC = 0.71, cognitive: ICC = 0.72).

CONCLUSION

The Chinese version of the PL-C Quest is valid and reliable for testing the self-reported PL of Chinese children aged 4 to 12. This study provides the first evidence of validity for this tool in children aged 4-6 years and also evidence that the PL-C Quest would be a meaningful instrument to assess PL in Chinese children.

Time flies, but you're in control: the mediating effect of self-control between time attitude and academic procrastination

BACKGROUND

Academic procrastination has become an increasing concern in the educational sector. Prior studies identified various correlations among academic procrastination, time attitude and self-control. Nevertheless, few studies have examined the past time attitude and the mechanism underlying those relationships, and the existing studies have been implemented during regular school time. To fill those gaps, the present study includes all three dimensions of time attitude (past-oriented, present-oriented and future-oriented in both positive and negative perspectives), and proposes self-control as a mediator between academic procrastination and time attitude. The study was carried out during an extraordinary winter holiday in China, with final exams waiting at the end of the holiday.

METHODS

A total of 323 middle school students in China (178 girls and 145 boys, 12-19 years old) completed an online survey with questions on their academic procrastination, time attitude and self-control. The collected data were analyzed using IBM SPSS Statistics 25 and Hayes SPSS macro PROCESS (Model 4).

RESULTS

The results showed that academic procrastination was negatively associated with all three positive time attitudes and positively correlated with the present negative time attitude. Moreover, self-control significantly mediates the relationship between academic procrastination and all three positive time attitudes.

CONCLUSION

Based on these findings, self-control could be the underlying mechanism in the relationship between academic procrastination and time attitude. This study broadens the scope of relevant empirical research to the past time attitude, and determines the mechanism that underlies the association between academic procrastination and time attitude under a novel context. Further implications for teaching regulation and intervention are discussed.

The dynamic impact of digital finance on green innovation: evidence enterprise-level empirical data in China

The digital finance generated by technology empowerment profoundly affects the innovative behavior of micro-enterprises. To estimate how digital finance influences the quantity and quality of green technological innovation, this paper introduces digital finance into endogenous economic growth model and further conducts correlation analysis with the combination of fixed effects model (FE) and panel threshold model (PTM). Moreover, this paper investigates the action mechanism from the perspective of financial constraint and financial cost. The empirical results indicate that digital finance improves the quantity and quality of green technological innovation significantly. Compared with the coverage of digital finance and digital services, the impact of usage depth on green innovation accumulates dynamically superimposed in the long term. The digital finance contributes to correct the mismatch of financial resources and further induces inclusive green innovation in the dimension of ownership, growth cycle, and enterprise scale. Mechanism analysis shows that the relief of financial constraint, environmental information disclosure, and increase of R&D investment are the main paths for digital finance to drive green innovation. With the different thresholds, the dynamic evolution process of green innovation driven by digital finance is characterized by "first quantitative change and then qualitative change." This paper suggests that the integration of technological innovation and digital financial services needs to build an inclusive digital financial service system, cultivate diversified financial formats, and improve the market environment of digital financial services.

Robust optimization model of anti-epidemic supply chain under technological innovation: learning from COVID-19

The anti-epidemic supply chain plays an important role in the prevention and control of the COVID-19 pandemic. Prior research has focused on studying the facility location, inventory management, and route optimization of the supply chain by using certain parameters and models. Nevertheless, uncertainty, as a vital influence factor, greatly affects the supply chain. As such, the uncertainty that comes with technological innovation has a heightened influence on the supply chain. Few studies have explicitly investigated the influence of technological innovation on the anti-epidemic supply chain under the COVID-19 pandemic. Hence, the current research aims to investigate the influences of the uncertainty caused by technological innovation on the supply chain from demand and supply, shortage penalty, and budget. This paper presents a three-level model of the anti-epidemic supply chain under technological innovation and employs an interval data robust optimization to tackle the uncertainties of the model. The findings are obtained as follows. Firstly, the shortage penalty will increase the costs of the objective function but effectively improve demand satisfaction. Secondly, if the shortage penalty is sufficiently large, the minimum demand satisfaction rate can ensure a fair distribution of materials among the affected areas. Thirdly, technological innovation can reduce costs. The technological innovation related to the transportation costs of the anti-epidemic material distribution center has a greater influence on the optimal value. Meanwhile, the technological innovation related to the transportation costs of the supplier has the least influence. Fourthly, both supply and demand uncertainty can influence costs, but demand uncertainty has a greater influence. Fifthly, the multi-scenario budgeting approach can decrease the calculation complexity. These findings provide theoretical support for anti-epidemic dispatchers to adjust the conservativeness of uncertain parameters under the influence of technological innovation.

Coupling relationship between cold chain logistics and economic development: A investigation from China

This paper builds an evaluation index system, uses the entropy weight method (EWM) to decide the weights and, based on the coupling coordination degree model (CCDM), it systematically studies the coupling relationship between Chinese cold chain logistics and the Chinese economy from 2010 to 2019. It performs a grey relational analysis (GRE) to explore the main factors influencing the coordinated development of the two. The results show that the coupling coordination degree between the two presents a steady upward trend, and their coupling relationship has been upgraded from ‘coordination’ to ‘good coordination’. They also indicate that the added value in the tertiary industry, the per capita gross domestic product (GDP), and household consumption levels are the main factors affecting the development of cold chain logistics, while the per capita cold storage capacity, the turnover of road cold chain freight, and the volume of human-power employed in cold chain logistics are the main factors affecting economic development. This study makes suggestions to support the coordinated development of cold chain logistics and economy, and provides a scientific basis for further research.