Provider Perspectives on Outcome Goals for Children's Day Treatment

I describe service provider perspectives regarding outcome goals of children's day treatment and their ideas for how to make day treatment programs successful in achieving stated outcomes. Respondents were direct service staff from ten day treatment programs in one county in Washington state. Data were obtained through nominal group process methods. The primary outcome goals of day treatment reported were: community re-integration, improved adaptive functioning skills, psychological growth, and improved family functioning. Aspects of day treatment that may help achieve outcome targets included: team quality; comprehensive programming; a consistent, safe, accepting program environment; an individualized, developmental approach; linkages with other services; family involvement, and a low staff-to-client ratio. Outcome goals are discussed relative to those described within the research literature on children's mental health services. Implications for the use of outcome goals for quality improvement are described.     

Dissociations in performance on novel versus irregular items: single-route demonstrations with input gain in localist and distributed models

Four pairs of connectionist simulations are presented in which quasi-regular mappings are computed using localist and distributed representations. In each simulation, a control parameter termed input gain was modulated over the only level of representation that mapped inputs to outputs. Input gain caused both localist and distributed models to shift between regularity-based and item-based modes of processing. Performance on irregular items was selectively impaired in the regularity-based modes, whereas performance on novel items was selectively impaired in the item-based modes. Thus, the models exhibited double dissociations without separable processing components. These results are discussed in the context of analogous dissociations found in language domains such as word reading and inflectional morphology.     

Two efficient selection methods for high-dimensional CD-CAT utilizing max-marginals factor from MAP query and ensemble learning approach

Computerized adaptive testing for cognitive diagnosis (CD-CAT) needs to be efficient and responsive in real time to meet practical applications' requirements. For high-dimensional data, the number of categories to be recognized in a test grows exponentially as the number of attributes increases, which can easily cause system reaction time to be too long such that it adversely affects the examinees and thus seriously impacts the measurement efficiency. More importantly, the long-time CPU operations and memory usage of item selection in CD-CAT due to intensive computation are impractical and cannot wholly meet practice needs. This paper proposed two new efficient selection strategies (HIA and CEL) for high-dimensional CD-CAT to address this issue by incorporating the max-marginals from the maximum a posteriori query and integrating the ensemble learning approach into the previous efficient selection methods, respectively. The performance of the proposed selection method was compared with the conventional selection method using simulated and real item pools. The results showed that the proposed methods could significantly improve the measurement efficiency with about 1/2–1/200 of the conventional methods' computation time while retaining similar measurement accuracy. With increasing number of attributes and size of the item pool, the computation time advantage of the proposed methods becomes more significant.     

A Leader Who Sees the World as I Do: Voters Prefer Candidates Whose Statements Reveal Matching Social-Psychological Attitudes

Politicians are increasingly able to communicate their values, attitudes, and concerns directly to voters. Yet little is known about which of these signals resonate with voters and why. We employ a discrete choice experiment to investigate whether and which social-psychological attitudes predict how adult British voters respond to corresponding attitudinal signals communicated by candidates in hypothetical social media posts. For all attitudes studied, covering social feelings (trust, collective nostalgia), social perceptions (nationalism, populist sentiment), and social commitments (national identification, authoritarianism, egalitarianism), we find that participants are much more likely to vote for candidates who signal proximity to their own attitudinal position and less likely for candidates who signal opposing views. The strongest effects were observed for national identification, authoritarianism, and egalitarianism, indicating the importance of commitment to a shared group and to particular principles for distributing power and resources within and between groups. We further demonstrate that social-psychological attitudes are not acting as mere proxies for participants' past votes or left–right ideology. Our results extend adaptive followership theory to incorporate preferences concerning intragroup coordination and intergroup hierarchy, while highlighting the social-psychological dynamics of political communication that may transcend the concerns of particular election cycles.     

Multidimensional adaptive testing

Maximum likelihood and Bayesian procedures for item selection and scoring of multidimensional adaptive tests are presented. A demonstration using simulated response data illustrates that multidimensional adaptive testing (MAT) can provide equal or higher reliabilities with about one-third fewer items than are required by one-dimensional adaptive testing (OAT). Furthermore, holding test-length constant across the MAT and OAT approaches, substantial improvements in reliability can be obtained from multidimensional assessment. A number of issues relating to the operational use of multidimensional adaptive testing are discussed.     

Cultural Variations in the Sexual Marketplace: Gender Equality Correlates With More Sexual Activity

ABSTRACT

Sexual economics theory assumes that heterosexual communities can be analyzed as marketplaces in which men offer women resources such as love, respect, money, and commitment in exchange for sex. In response to economic, political, and other disadvantages, women collectively restrict their sexuality to maintain a low supply relative to male demand, thereby ensuring a high price. Hence, we tested the hypothesis that sexual norms and practices would be more restrictive in countries marked by gender inequality than in countries where the genders were more equal. An international online sex survey (N>317,000) yielded four measures of sexual activity, and 37 nations' means on all four measures were correlated with independent (World Economic Forum) ratings of gender equality. Consistent with predictions, relatively high gender equality was associated with more casual sex, more sex partners per capita, younger ages for first sex, and greater tolerance/approval of premarital sex.     

计算机自适应测验在特质焦虑量表中的运用

将基于项目反应理论的计算机自适应测验运用于特质焦虑量表,考察这一测验形式在人格测量中所具有的特性.收集特质焦虑量表真实纸笔作答数据,选用合适的心理测量模型,模拟计算机自适应测验.结果表明：相对纸笔测验而言,计算机自适应测验的测试效率更高、对被试的分辨力更强、结果更直观.计算机自适应测验在人格测量中的实践值得进一步探索.     

Using a Response Time–Based Expected A Posteriori Estimator to Control for Differential Speededness in Computerized Adaptive Test

This study investigates using response times (RTs) with item responses in a computerized adaptive test (CAT) setting to enhance item selection and ability estimation and control for differential speededness. Using van der Linden’s hierarchical framework, an extended procedure for joint estimation of ability and speed parameters for use in CAT is developed following van der Linden; this is called the joint expected a posteriori estimator (J-EAP). It is shown that the J-EAP estimate of ability and speededness outperforms the standard maximum likelihood estimator (MLE) of ability and speededness in terms of correlation, root mean square error, and bias. It is further shown that under the maximum information per time unit item selection method (MICT)—a method which uses estimates for ability and speededness directly—using the J-EAP further reduces average examinee time spent and variability in test times between examinees above the resulting gains of this selection algorithm with the MLE while maintaining estimation efficiency. Simulated test results are further corroborated with test parameters derived from a real data example.     

Interactions between Learning Sets in Monkeys

Relationships between stage of moral judgment and antecedent social experiences are presented for a non-Western sample of young adults. Cross sectional data are presented for two groups of Kenyan students: 52 University of Nairobi students; and 40 fourth form secondary school Ss. Critical variables are (a) family modernization, (b) attending ethnically pluralistic secondary schools, and (c) living independently away from home. The correlations between moral judgment stage and these three variables are controlled for, and compared to, correlations between stage of moral judgment and age, sex, race, and academic ability (as measured by standardized achievement tests or by grades). The evidence demonstrates associations between moral stage and all three critical variables, though in different ways for the two age levels of Ss.