婴儿指示性手势与其语言学习的关系

指示性手势是指明空间中某个物体、处所或事件的手部动作,在婴儿1岁时出现,与婴儿的语言学习存在着较强的相关,然而目前尚不清楚为什么会存在此相关。可能存在两种内在机制:(1)指示性手势影响婴儿的学习环境——引发了适时的语言输入;(2)影响学习者本身——帮助婴儿创造有效的学习状态并示意给他人。未来的研究需要探讨这两种机制如何交互作用,以及如何将指示性手势作为诊断或干预工具,用于识别和帮助有语言障碍风险的个体。     

Developmental stability and change in self-regulation from childhood to adolescence

The authors examined the developmental course of self-regulation in a cohort of children from the National Longitudinal Survey of Youth. The longitudinal sample included 646 children (48% girls; 52% boys; 36.2% Black, 23.4% Hispanic, 40.4% White) who were 4 to 5 years old in 1986 and who were followed up at ages 8 to 9 and ages 12 to 13. Levels of self-regulation (assessed with 12 maternal-report items that measured regulation of affect, behavior, attention) increased from early childhood (when sample children were 4 or 5 years old) to middle childhood (ages 8 or 9), but not from middle childhood to early adolescence (ages 12 or 13). Girls exhibited significantly higher levels of self-regulation than did boys at all 3 time points. Individual differences in self-regulation were fairly stable across the 8-year span (rs = .47 to .50). Comparisons of 1-, 2-, and 3-factor models suggested that the different aspects of self-regulation are highly interrelated, and support adoption of a single-factor model for both genders. The authors discuss implications of these findings for theory and intervention.     

Psychometric properties of the Hong psychological reactance scale

The Hong Psychological Reactance Scale (HPRS; Hong & Felda, 1996) was developed to measure the individual difference in reactance proneness, that is, a person's trait propensity to experience psychological reactance. We performed confirmatory factor analyses to test the dimensionality of the 11-item version of the HPRS. Three message outcome variables (i.e., perceived threat to freedom, attitude, and intention) served as reference variables to test the construct validity of the HPRS. Data from 3 studies (Ns = 188, 200, and 233) of reactions to persuasive health messages confirmed the existence of 4 first-order factors but also provided evidence that the HPRS can be treated as unidimensional at the second order. The relationships between the second-order factor and the message outcome variables provided evidence of the validity of the scale.     

How does exposure to masked individuals affect White Americans' attitudes toward Asian American and Pacific Islanders?

Across three studies, conducted between Spring 2020 and Spring 2021, we tested whether exposure to an Asian American/Pacific Islander (AAPI) target person wearing a face mask would increase or decrease White Americans' perceived threat from and positivity toward AAPI individuals. Although results varied by study, a single-paper meta-analysis revealed that the masked (compared to unmasked) AAPI target resulted in greater positivity toward AAPIs, due to reduced perceptions of both symbolic threat to group values and realistic threat to group health. Positivity toward AAPIs did not reliably differ after exposure to a masked versus unmasked White target. Implications for interventions that encourage COVID-safe behaviors and combat anti-AAPI attitudes are discussed.     

异性拒绝对大学生择偶行为的长期影响:基于社会计量器理论的探讨

运用问卷调查法以339名大学生为研究对象,基于社会计量器理论探讨异性拒绝经历和择偶价值感对大学生择偶行为的长期影响。研究发现:(1)女大学生的择偶标准显著高于男大学生,男大学生的择偶行为倾向略高于女大学生;(2)异性拒绝经历与择偶价值感、择偶标准、择偶行为倾向呈负相关,择偶价值感与择偶标准、择偶行为倾向呈显著正相关;(3)异性拒绝经历可以显著负向预测大学生的择偶行为,择偶价值感在异性拒绝经历对大学生择偶行为影响中起部分中介作用,但其发挥作用的方式存在性别差异。这一结果表明,择偶价值感是一种重要的缓冲因素,可以在一定程度上缓解异性拒绝给大学生择偶行为带来的负面影响。     

Specifying Ability Growth Models Using a Multidimensional Item Response Model for Repeated Measures Categorical Ordinal Item Response Data

When categorical ordinal item response data are collected over multiple timepoints from a repeated measures design, an item response theory (IRT) modeling approach whose unit of analysis is an item response is suitable. This study proposes a few longitudinal IRT models and illustrates how a popular compensatory multidimensional IRT model can be utilized to formulate such longitudinal IRT models, which permits an investigation of ability growth at both individual and population levels. The equivalence of an existing multidimensional IRT model and those longitudinal IRT models is also elaborated so that one can make use of an existing multidimensional IRT model to implement the longitudinal IRT models.     

Development of a Multidimensional Instrument of Person–Environment Fit: The Perceived Person–Environment Fit Scale (PPEFS)

This research identifies four challenges in the field of person–environment fit (PE fit): the multidimensionality of PE fit, the integration of fit theories, the simultaneous effects of the multiple dimensions, and the function of the dimensions. To address those challenges, we develop a theory‐driven and systematically validated multidimensional instrument, the Perceived Person–Environment Fit Scale (PPEFS), consisting of four measures: the Person–Job Fit Scale (PJFS), the Person–Organisation Fit Scale (POFS), the Person–Group Fit Scale (PGFS), and the Person–Supervisor Fit Scale (PSFS). Data are collected from 532 employees and 122 managers for two independent studies with multiple rater sources and multiple time points. A series of validation analyses and hypothesis tests reveals that the PPEFS measures have good psychometric properties (i.e. reliability, convergent validity, discriminant validity, and criterion‐related validity) and exhibit incremental validity above and beyond Cable and DeRue's (2002) fit measures. Furthermore, the measures are reflected by a superordinate (vs. aggregate) construct of PE fit. Overall, the four different types of fit significantly predict in‐role behavior, job satisfaction, intent to quit, and organisational citizenship behavior (OCB), each explaining the greatest amount of variance in different outcomes. The PPEFS should prove useful in future research regarding PE fit.     

Limited‐information goodness‐of‐fit testing of diagnostic classification item response models

Despite the growing popularity of diagnostic classification models (e.g., Rupp et al., 2010, Diagnostic measurement: theory, methods, and applications, Guilford Press, New York, NY) in educational and psychological measurement, methods for testing their absolute goodness of fit to real data remain relatively underdeveloped. For tests of reasonable length and for realistic sample size, full‐information test statistics such as Pearson's X² and the likelihood ratio statistic G² suffer from sparseness in the underlying contingency table from which they are computed. Recently, limited‐information fit statistics such as Maydeu‐Olivares and Joe's (2006, Psychometrika, 71, 713) M₂ have been found to be quite useful in testing the overall goodness of fit of item response theory models. In this study, we applied Maydeu‐Olivares and Joe's (2006, Psychometrika, 71, 713) M₂ statistic to diagnostic classification models. Through a series of simulation studies, we found that M₂ is well calibrated across a wide range of diagnostic model structures and was sensitive to certain misspecifications of the item model (e.g., fitting disjunctive models to data generated according to a conjunctive model), errors in the Q‐matrix (adding or omitting paths, omitting a latent variable), and violations of local item independence due to unmodelled testlet effects. On the other hand, M₂ was largely insensitive to misspecifications in the distribution of higher‐order latent dimensions and to the specification of an extraneous attribute. To complement the analyses of the overall model goodness of fit using M₂, we investigated the utility of the Chen and Thissen (1997, J. Educ. Behav. Stat., 22, 265) local dependence statistic $X_{\mathrm{LD}}^2$ for characterizing sources of misfit, an important aspect of model appraisal often overlooked in favour of overall statements. The $X_{\mathrm{LD}}^2$ statistic was found to be slightly conservative (with Type I error rates consistently below the nominal level) but still useful in pinpointing the sources of misfit. Patterns of local dependence arising due to specific model misspecifications are illustrated. Finally, we used the M₂ and $X_{\mathrm{LD}}^2$ statistics to evaluate a diagnostic model fit to data from the Trends in Mathematics and Science Study, drawing upon analyses previously conducted by Lee et al., (2011, IJT, 11, 144).