An effective measure of childhood adversity that is valid with older adults

Childhood adversity (CA) has life-long effects that we are just beginning to understand. The Midlife in the United States (MIDUS) data is a rich resource that could contribute to the knowledge of the impact of CA in the later years but, while a number of CA items are included in MIDUS, a cumulative CA scale based on those items has not been created. Development of a CA scale would create numerous research opportunities within MIDUS and overcome some of the challenges of using a secondary dataset. The present study aimed to demonstrate that a cumulative measure of CA that is valid with older adults could be created using retrospective MIDUS Refresher study data (Ryff et al., 2016); analysis included data collected from 2011 to 2014 from 2542 adults ages 23–76 (1017 adults 55–76). The present study provided a rationale for which measures of CA to include in a cumulative scale. The distribution of eight types of CA and the cumulative CA scale were consistent with findings from past studies of CA. The factor structure of the cumulative CA scale was similar to the original ACE study and included two factors: household dynamics and child abuse/neglect. Consistent with past studies, the CA scale predicted a negative association with life satisfaction and a positive association with number of chronic conditions. This study demonstrated that an effective cumulative measure of CA could be created that would be of value to other studies using MIDUS data to explore outcomes with older adults.     

科学数据共享研究现状与展望

[目的/意义] 分析科学数据共享的研究现状及其发展趋势，为促进国内相关理论研究与实践进展提供参考。[方法/过程] 通过对国内外文献进行梳理和归纳，提炼出与科学数据共享研究相关的三大类主题：科学数据共享发展需求、科学数据管理共享模式与机制和科学数据服务共享度与服务效果，并构建科学数据共享管理分析框架，该框架体现上述三类主题之间的因果关联，强调科学数据共享管理与服务的合理面、重要度、关键性。[结果/结论] 国内外现有研究尚存不足，未来研究在加强实证研究、着眼管理机制完善的同时，还需注重共享服务模式的创新。     

Data Visualization as Participatory Research: A Model for Digital Collections to Inspire User-Driven Research

The emerging creative practices of digital collections are increasing in prominence thanks to the access to, and appeal of, data visualizations. Interactive data visualizations, such as a map, timeline, chart, graph, or artist’s rendering of data, enable users to pursue their own research interests within a collection and participate in new areas of research. Use of these data visualizations enhances the scope of the collection and enables a modern and diverse thematic collection to emerge. This article considers the question: Does the addition of data visualizations affect how users participate with a research collection? Impacts on collection development, application of user-centered design, and analysis of users’ exploratory strategies are discussed. Examples of data visualizations used in digital humanities projects and digital collections are presented as case studies.     

Digital Module 16: Longitudinal Data Analysis

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.     

大数据时代个人信息保护研究综述

[目的/意义]通过梳理大数据时代个人信息保护的研究文献，为未来研究个人信息保护提供借鉴。[方法/过程]利用CNKI数据库，系统收集关于大数据时代个人信息保护的国内核心期刊论文，对文献的内容进行分析，归纳研究主题，并进行论述。[结果/结论]将现有的研究成果按主题分为5类：国内外实践经验研究、基本理论问题研究、个人信息保护机制探索、个人信息安全风险与应对、相关法律法规研究，评述现有研究的不足之处并对未来的研究方向提出展望。     

男子上肢无氧功率测定方法之研究

研究采用自制的实验器材和传统的手摇自行车功量计测定男子上肢无氧功率，并对自制器材所测得无氧功率的试验结果进行可靠性、客观性和有效性检验，证明用该自制器材测定上肢无氧功率不仅制作简单、操作容易，而且具有实效性和可靠性的优点，从而表明该仪器在进一步完善后对无氧功率的测试具有一定的可行性。     

体育技术课教学中的测量与评价

体育技术的教学,是以身体素质为基础,运动能力和大脑思维为主导的复杂过程.应该遵循人体生长发育的规律,采取因势利导的原则,运用体育测量的科学性和体育评价的方法指导体育技术的教学.     

广西电大远程教育网络系统改造与应用设想

网络发展日新月异,网络上的新设备、新技术、新应用层出不穷,出现了许多新的组网方式。电大网络的数据量、用户量和访问量的迅速增大,对网络技术和网络平台提出了更高的要求。广西电大原有的组网方式太复杂,维护困难,运行成本高。因此,在体现其低资费、高效率和电大可持续发展的前提下,必须对电大网络进行重新构建。本文主要阐述全区电大网络改建和应用的初步设想。     

CUBA联赛技术统计指标研究

运用数理统计、观察和文献资料等方法，集第四届和第五届CUBA联赛全部技术统计资料，利用统计软件对近3000个数据进行了处理，用均值、均方差纵向对比的方法，对多项指标进行了分析，得出当前CUBA联赛优势所在，探讨不足之处，并提出建议。     

Assessing School Readiness: Validity and Bias in Preschool and Kindergarten Teachers' Ratings

As a part of efforts to evaluate and monitor the increasing public investment in early childhood education, teachers are being asked to assess children's school readiness. In this study, preschool teachers and kindergarten teachers rated children's skills in three areas (kindergarten readiness, academic skills, and communication skills), and these ratings were compared with direct assessments of the children's skills. Ratings by both groups of teachers tended to be more highly related to basic skills, such as counting and number naming, than to abilities such as solving applied problems and using expressive and receptive vocabulary. Preschool teachers' ratings had a lower association with children's observed skills and abilities than kindergarten teachers' ratings. Ratings of children attending Head Start were systematically inflated, but this relationship was mediated to a significant extent by the teachers' levels of education. More educated teachers rated children in a manner consistent with the children's directly assessed skills. Implications of these findings for informing future efforts to assess school readiness by using teacher ratings are discussed.