Background The effects of childhood adversities on cognitive function in later life are well reported. However, few studies have examined the cumulative mechanism, especially in Chinese population. This study aims to explore this cumulative effects of childhood adversities on mid to late cognitive decline in China. Methods Data were drawn from the second and third wave of the China Health and Retirement Longitudinal Study (CHARLS). We included 9,942 respondents aged 45 and above and retrospectively collected information on childhood adversities. Cognitive function was measured in three dimensions: orientation and calculation, immediate memory, and delayed memory. A structural equation model was employed for analysis. Results Age (β = -0.155, P<0.001) and mid to late depressive symptoms (β = -0.041, P<0.001) showed direct effects on cognitive decline. Low mid to late life socioeconomic status (SES) showed a direct effect on mid-late cognitive impairment (β = 0.603, P<0.001) and an indirect effect through depression (β = 0.007, P<0.001). Low childhood SES (β = 0.310, P<0.001), lack of friends (β = 0.208, P<0.001), parental mental health problems (β = 0.008, P<0.001), and poor relationship with parents (β = 0.001, P<0.001) had an indirect effect on cognitive impairment. Conclusions Childhood adversities had negative effects on cognitive function among middle aged and elderly population in China. The findings suggest that early counter measures on childhood adversities may lead to an effective reduction of cognitive impairment.
Purpose: To examine the determinants and impacts of implementing the mitigation interventions to combat the COVID-19 disease in the United States during the first 5 weeks of the pandemic. Method: A content analysis identified nine types of mitigation interventions and the timing at which states enacted these strategies. A proportional hazard model, a multiple-event survival model, and a random-effect spatial error panel model in conjunction with a robust method analyzing zero-inflated and skewed outcomes were employed in the data analysis. Findings: Contradictory to the study hypothesis, states initially with a high COVID-19 prevalence rate enacted mitigation strategies slowly. Three mitigation strategies (nonessential business closure, large-gathering bans, and restaurant/bar limitations) showed positive impacts on reducing cumulative cases, new cases, and death rates across states. Conclusion: Some states may have missed optimal timing to implement mitigations. Swift implementation of mitigations is crucial. Reopening economy by fully lifting mitigation interventions is risky.
Social media holds the potential to engage adolescents and young adults and to facilitate interventions improving Human Papillomavirus Vaccine (HPVV). This article systematically reviewed the literature on Cochrane Library, PubMed, Web of Science, EMBASE, Scopus and CINAHL. Interventions delivered or facilitated by social media with outcomes of HPV-related knowledge, awareness, attitude, vaccination intention and behavior were included. Standardized forms were used to abstract the basic characteristics, settings, guiding theories and key findings of the interventions. Twenty-four studies met the eligibility criteria. Sixteen were educational interventions, and the other eight investigated the effect of social media message contents on improving Human Papillomavirus (HPV)-related outcomes. The studies were published between 2015 and 2021. The most frequently used social media platforms were Facebook, and the most commonly adopted theory was the health belief model (HBM). Existing interventions have shown preliminary but promising effects in improving HPV awareness and knowledge. Still, such improvements have not always been translated to improved behavioral intentions and vaccination rates. The contents and phrasing of social media messages and pre-existing individual characteristics of social media users moderated intervention effectiveness. Social media could be a valuable tool for engaging participants and delivering HPV interventions. Future interventions should apply stronger theory bases.
Distance higher education is an important component of the Chinese higher education. How to enhance the quality of distance higher education is one of the key issues to be addressed in the research areas of distance education and higher education. As a crucial step to quality improvement, the constitution of accreditation system in distance higher education balances the benefits of all parties involved. This paper explores the American accreditation system of higher education and distance education and concludes with suggestions for the constitution of the Chinese quality assurance system: 1) establishing third-party institutions to share part of the government roles; 2) constituting the accreditation system; 3) setting up appropriate standards; 4) publicizing results of quality assurance work; and 5) building internal quality assurance mechanism. This paper is aimed to provide some reference to the constitution of accreditation system of distance higher education in China, facilitate the solution of quality problems in distance education, and promote the continuous improvement and development of distance education in China.
Background To combat the Covid-19 pandemic in the United States, many states and Washington DC enacted Stay-at-Home order and nonpharmaceutical mitigation interventions. This study examined the determinants of the timing to implement an intervention. Through an impact analysis, the study explored the effects of the interventions and the potential risks of removing them under the context of reopening the economy. Method A content analysis identified nine types of mitigation interventions and the timing at which states enacted these strategies. A proportional hazard model, a multiple-event survival model, and a random-effect spatial error panel model in conjunction with a robust method analyzing zero-inflated and skewed outcomes were employed in the data analysis. Findings To our knowledge, we provided in this article the first explicit analysis of the timing, determinants, and impacts of mitigation interventions for all states and Washington DC in the United States during the first five weeks of the pandemic. Unlike other studies that evaluate the Stay-at-Home order by using simulated data, the current study employed the real data of various case counts of Covid-19. The study obtained two meritorious findings: (1) states with a higher prevalence of Covid-19 cases per 10,000 population reacted more slowly to the outbreak, suggesting that some states may have missed the optimal timing to prevent the wide spread of the Covid-19 disease; and (2) of nine mitigation measures, three (non-essential business closure, large-gathering bans, and restaurant/bar limitations) showed positive impacts on reducing cumulative cases, new cases, and death rates across states. Interpretation The opposite direction of the prevalence rate on the timing of issuing the mitigation interventions partially explains why the Covid-19 caseload in the U.S. remains high. A swift implementation of social distancing is crucial-the key is not whether such measures should be taken but when. Because there is no preventive vaccine and because there are few potentially effective treatments, recent reductions in new cases and deaths must be due, in large part, to the social interventions delivered by states. The study suggests that the policy of reopening economy needs to be implemented carefully.
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