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Objective: This manuscript evaluates and tests the group differences in migrant workers' urban integration from the perspectives of individual characteristics and migration characteristics, so as to provide theoretical support and practical guidance for the government to issue more effective assistance policies. Methods: Multilevel comprehensive evaluation method and Entropy method are used to calculate the urban integration level of migrant workers, and one-way ANOVA and optimal scaling regression are used to test the group differences in migrant workers' urban integration. Results: Based on the questionnaire data of 854 migrant workers in China, the scale of migrant workers' urban integration has good reliability and validity. The overall level of migrant workers' urban integration is 49.61% and there exist group differences in migrant workers' urban integration. The impact of education level, income level, and migration time on migrant workers' urban integration is significantly positive, whereas the impact of migration distance on migrant workers' urban integration is significantly negative. The urban integration level of migrant workers who have family members accompanying them is higher than that of migrant workers who have no family members accompanying them. Gender, age, and marriage have no significant impact on migrant workers' urban integration. Strengths and Limitations of This Study: This study aims to measure and test the group differences in migrant workers' urban integration using ANOVA and optimal scaling regression. However, the shortcomings of this study are the selection of the "migrant workers' urban integration" scale and the representativeness of the sample used in this study. Conclusion: There are group differences in migrant workers' urban integration with different education levels, income levels, migration distances, migration times, and statuses of family members accompanying. In the policy of promoting migrant workers' urban integration, we should accurately count the characteristics of migrant workers and give more attention to migrant workers with low education levels, low-income levels, long migration distances, short migration times, and no family accompany.
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Objective@#To explore the determinants of physical activity during leisure time among junior high school students in Jinshan District of Shanghai based on socio-ecological model, so as to provide basis for health promotion in adolescents. @*Methods@#Six public junior high schools were randomly selected from Jinshan District and then a class was selected from every grade. The physical activity of the students in the spare time of one week was monitored. The determinants of physical activity were investigated through a self-designed questionnaire based on socio-ecological model,and were analyzed by optimal scaling regression. @* Results@#A total of 645 questionnaires were sent out, 622（96.43%）of which were valid. The median time spent on active physical activity after school on weekdays and at weekends was 29.00 min and 45.00 min, respectively. The scores of individual, interpersonal and environmental factors were 10.53 ± 2.04, 5.10 ± 1.51 and 8.31 ± 1.85,respectively. The results of the optimal scaling regression analysis showed that residence（β=-0.117, -0.159）,individual factors（β=0.244,0.277）, interpersonal factors（β=0.113, 0.085）and environmental factors（β=-0.140, -0.120) were the influencing factors for the physical activity in extracurricular time on weekdays and at weekends. On weekdays, the influence of individual factors was the largest （62.2%）,followed by interpersonal factors（20.8%）and residence（16.8%）. At weekends, the influence of individual factors was the largest（65.4%）, followed by residence（23.6%）and interpersonal factors（10.5%）.@*Conclusions@#The physical activity level during leisure time among junior high school students in Jinshan District is most affected by individual factors, followed by interpersonal factors and residence. The time spent on physical activity at weekends is insufficient, and the influence of residence is behind individual factors.
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Objective To analyze the SCI papers output and its impact factors of a hospital during 2013-2017,to provide supports and proofs for scientific research administrators to update incentive policies for stimulate growth of SCI Paper publication.Methods Dynamic sequence and Optimal Scaling Regression methods were used to conduct statistical analysis of the output and impact factors of hospital-published SCI papers.Results The average increased number per year of hospital-published SCI papers output was 30.3 with an annual increase rate of 37.5％,which was 9.5％ higher than the national average.In 2017,the growth rate of a fixed base of hospital-published SCI papers was increased to 257.4 ％,which was 89％ higher than the national rate during the same period.The model was statistically significant (F =10.513,P＜ 0.001,adjusted R2 =0.409) according to the Optimal Scaling Regression analysis of 180 first/corresponding authors out of 516 SCI papers.We found that authors' status as tutor of post-graduate student (P＜0.001),average project fundings (P=0.001),professional titles (P=0.048) and genders (P=0.005) have significant impacts on the output of hospital-published SCI papers (P＜0.05).The sum of the importance of the four factors above was 0.961,namely account for 96.1％ of the whole model.The quantitative score conversion chart shows that doctoral tutors,high average project funding,senior professional titles,and male authors of the SCI papers have higher quantitative scores.Conclusions Tutor status,average project fundings,professional titles and genders could impact the output of SCI papers.Scientific research administrators could adjust incentive policies of SCI papers,based on the science platform construction inclining to doctor tutors,adding matching funds for science and research,bonding professional title appraisals and rising incentives for female researchers on SCI papers,to promote SCI papers output.
