The Generality and Particularity of Labor Migration in China

Labor migration among regions and between the urban-rural has been a popular research topic in labor economics,development economics, industrial economics and regional economics.The world economy development history proves that such labor migration is inevitable economic phenomenon in the process of economic development.However,there are some keys to better understand China’s labor migration,such as what are the characteristics of China’s labor migration? What differences are there in China’s labor migration compared with that of the development countries and other developing countries? What are the connotational and theoretical implications of China’s labor migration? These are the core questions of this paper.Understanding these questions will patch up the shortages in the existing researches of the field,lay solid foundation and provide valuable reference for the economic effects, the welfare effects of China’s labor migration and associated institutional arrangements and macroeconomic policies.     

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The ‘Freshman 5’: A Meta-Analysis of Weight Gain in the Freshman Year of College

Abstract

Objective: (1) To use the available research to estimate the amount of weight gained by college freshman during their first year of college. (2) To identify potential predictors of freshman weight gain. Methods: A meta-analysis was conducted in November 2008. The analysis focused on articles published in English scientific journals between 1985 and 2008 available on the MEDLINE, Web of Science, and PsycINFO databases and excluded studies of weight change over periods beyond freshman year. Results: Twenty-four studies met the inclusion criteria. Based on a pooled sample of 3,401 cases, mean weight gain was 3.86 (95% confidence intervals [CI] = 3.81–3.91) lbs. Potential contributors to gain were recent dieting, high baseline weight, and psychological stress. Conclusions: The first year of college is a period of vulnerability for weight problems. Further research is needed to better understand freshman weight gain and devise appropriate prevention strategies based on predictors of gain.     

Nonsuicidal Self-injury in a College Population: General Trends and Sex Differences

Abstract

Objective: To describe basic nonsuicidal self-injury (NSSI) characteristics and to explore sex differences. Methods: A random sample from 8 universities were invited to participate in a Web-based survey in 2006–2007; 38.9% (n = 14,372) participated. Analysis assessed sex differences in NSSI prevalence, practices, severity, perceived dependency, and help-seeking; adjusted odds ratios for NSSI characteristics were calculated by sex status. Results: Lifetime NSSI prevalence rates averaged 15.3%. Females were more likely than males to self-injure because they were upset (adjusted odds ratio [AOR] = 1.6; 95% confidence interval [CI] = 1.3–2.1) or in hopes that someone would notice them (AOR = 1.6, 95% CI = 1.1–2.7). Males were 1.6 times (95% CI = 1.2–2.2) more likely to report anger and 4.0 times (95% CI = 2.3–6.8) more likely to report intoxication as an initiating factor. Sexual orientation predicted NSSI, particularly for women (Wald F = 8.81, p ≤ .000). Only 8.9% of the NSSI sample reported disclosing NSSI to a mental health professional. Conclusions: NSSI is common in college populations but varies significantly by sex and sexual orientation. NSSI disclosure is low among both sexes.     

Positive Social Support,Negative Social Exchanges,and Suicidal Behavior in College Students

Abstract

Objective: Risk for suicide is often higher among college students, compared to same-age noncollegiate peers, and may be exacerbated by quality of social support and interactions. The authors examined the independent contributions of positive social support and negative social exchanges to suicide ideation and attempts in college students. Participants: Participants were 439 volunteer undergraduate students, who were primarily female (71%). Methods: Cross-sectional, survey design. Participants completed measures assessing positive social support, including emotional, informational, and tangible support; negative social exchanges; and suicidal behavior, including ideation and attempts. Results: Positive social support, particularly tangible support, and negative social exchanges were significantly predictive of greater suicidal behavior. Conclusions: Practical manifestations of support may buffer against suicide risk for college students, whereas conflict-based interactions may contribute to increased risk. At the institutional, parental, and peer levels, promotion of supportive relationships may be an important suicide prevention strategy.