一般自我效能感量表的信度和效度研究

由Schwarzer等人编制的一般自我效能感量表(GSES)目前在国际上广泛使用,本研究拟对中文版GSES的信度和效度进行研究.412名大学生接受了GSES的测试.结果表明①和其他文字版本的GSES一样,中文版GSES也具有较高的信度;②中文版GSES的单维度性得到了证实,印证了Schwarzer等人的有关发现;③中文版GSES具有很好的预测效度.     

Measuring Qualitative Aspects of Preschool Boys' Noncompliance: The Response Style Questionnaire (RSQ)

Child noncompliance is a core maladjustment factor in current clinical models of aggression and antisocial development. However, little is known about the relations among qualitative aspects of child noncompliance and aggressive maladjustment. The authors developed the Response Style Questionnaire, an instrument designed to measure the multidimensional qualities of child noncompliance, and tested its validity and reliability. Tests of internal validity provided a five-factor solution, featuring distinctions in noncompliance quality between and among skilled noncompliance (verbally skilled and emotionally regulated) and unskilled noncompliance (overt/confrontational, covert/sneaky, and emotionally labile). Theory-driven tests of external validity using peer-adjustment variables as criteria provided discriminant prediction (a) among qualitatively distinct aspects of noncompliance and (b) between noncompliance qualities and rate. Discussion focuses on a modified view of the nature and role of noncompliance in aggressive and antisocial development.     

Psychometrics in Support of a Valid Assessment of Linguistic Minorities: Implications for the Test and Sampling Designs

In this study, we propose that the unique needs and characteristics of linguistic minorities should be considered throughout the test development process. Unlike most measurement invariance investigations in the assessment of linguistic minorities, which typically are conducted after test administration, we propose strategies that focus on the early stages of test development. Our approaches involve considering linguistic minorities in the selection of the test and sampling designs. We posit that joint consideration of these issues preemptively can strengthen the claims derived from tests used to assess linguistically diverse populations. This also will contribute to more psychometrically robust assessments, which can yield accurate and valid score-based inferences for linguistic minorities. To this end, we provide various examples and methodological approaches that can be used in the selection of the test and sampling designs that take these issues into consideration.     

Predicting Self‐Confident Behaviour with Implicit and Explicit Self‐Esteem Measures

The present research compared the validity of popular direct and indirect measures of self‐esteem in predicting self‐confident behaviour in different social situations. In line with behavioural dual‐process models, both implicit and explicit self‐esteem were hypothesized to be related to appearing self‐confident to unacquainted others. A total of 127 participants responded to the Rosenberg Self‐Esteem Scale, the Multidimensional Self‐Esteem Scale, and an adjective scale for measuring explicit self‐esteem (ESE). Participants' implicit self‐esteem (ISE) was assessed with four indirect measures: the Implicit Association Test (IAT), the name‐letter task (NLT), and two variants of an affective priming task, the reaction‐time affective priming task (RT‐APT) and the error‐based affective priming task (EB‐APT). Self‐confident behaviour was observed in four different social situations: (i) self‐introduction to a group; (ii) an ostracism experience; (iii) an interview about the ostracism experience; and (iv) an interview about one's personal life. In general, appearing self‐confident to unknown others was independently predicted by ESE and ISE. The indirect measures of self‐esteem were, as expected, not correlated, and only the self‐esteem APTs—but not the self‐esteem IAT or the NLT—predicted self‐confident behaviours. It is important to note that in particular the predictive power of the self‐esteem EB‐APT pertained to all four criteria and was incremental to the ESE measures. Copyright © 2016 European Association of Personality Psychology     

中文版一般自我效能量表的信度和效度检验

该研究以山东省610名高中生为被试,检验了中文版一般自我效能量表（GSES）的信度和效度.结果表明：（1）中文版GSES的有些项目,区分度不高;（2）中文版GSES具有较高的内部一致性信度与分半信度,但重测信度不高;（3）中文版GSES的单维度性没有得到证实;（4）中文版GSES不具有很好的预测效度.     

《中国大学生人格量表》的编制*

在建立中国人人格大七结构模型以及成熟的人格量表基础上,本研究通过实证研究建立了适用于大学生群体的人格量表。统计结果表明,由68个项目、7个维度构成的中国大学生人格量表(CCSPS)与中国人人格的7因素模型有着良好的拟合,而且信度和效度检验均符合心理测量学要求;此外,在55098名被试上建立了CC-SPS的常模。研究结果表明CCSPS针对中国大学生群体可靠的人格测量工具。     

Driving construals: Personal Construct Theory in a reckless driving context

With research revealing low road safety campaign efficacy and links between reckless driving behaviors and crash frequency, further investigation into the foundations and composition of driver education and training is required. Through two studies, the current research aimed to develop a measure that utilized the principles of Kelly’s (1955) Personal Construct Theory to (a) elicit constructs, or construals, specific to selected elements of reckless driving behaviors, (b) pilot a method in which the elicited constructs could be measured by asking participants to choose those they deemed most important, (c) group participants based on their constructs, and (d) assess between-group differences in self-reported reckless driving behavior. Results suggest that drivers can be categorized based on the constructs they use, and that rates of self-reported past engagement in reckless driving behavior, and willingness to do so in the future, vary systematically between these construal-based driver categories. Continuing research is required to develop and test applications of these findings.     

Analysing multisource feedback with multilevel structural equation models: Pitfalls and recommendations from a simulation study

When multisource feedback instruments, for example, 360-degree feedback tools, are validated, multilevel structural equation models are the method of choice to quantify the amount of reliability as well as convergent and discriminant validity. A non-standard multilevel structural equation model that incorporates self-ratings (level-2 variables) and others’ ratings from different additional perspectives (level-1 variables), for example, peers and subordinates, has recently been presented. In a Monte Carlo simulation study, we determine the minimal required sample sizes for this model. Model parameters are accurately estimated even with the smallest simulated sample size of 100 self-ratings and two ratings of peers and of subordinates. The precise estimation of standard errors necessitates sample sizes of 400 self-ratings or at least four ratings of peers and subordinates. However, if sample sizes are smaller, mainly standard errors concerning common method factors are biased. Interestingly, there are trade-off effects between the sample sizes of self-ratings and others’ ratings in their effect on estimation bias. The degree of convergent and discriminant validity has no effect on the accuracy of model estimates. The χ² test statistic does not follow the expected distribution. Therefore, we suggest using a corrected level-specific standardized root mean square residual to analyse model fit and conclude with further recommendations for applied organizational research.     

Simple Structure Detection Through Bayesian Exploratory Multidimensional IRT Models

In modern validity theory, a major concern is the construct validity of a test, which is commonly assessed through confirmatory or exploratory factor analysis. In the framework of Bayesian exploratory Multidimensional Item Response Theory (MIRT) models, we discuss two methods aimed at investigating the underlying structure of a test, in order to verify if the latent model adheres to a chosen simple factorial structure. This purpose is achieved without imposing hard constraints on the discrimination parameter matrix to address the rotational indeterminacy. The first approach prescribes a 2-step procedure. The parameter estimates are obtained through an unconstrained MCMC sampler. The simple structure is, then, inspected with a post-processing step based on the Consensus Simple Target Rotation technique. In the second approach, both rotational invariance and simple structure retrieval are addressed within the MCMC sampling scheme, by introducing a sparsity-inducing prior on the discrimination parameters. Through simulation as well as real-world studies, we demonstrate that the proposed methods are able to correctly infer the underlying sparse structure and to retrieve interpretable solutions.     

Construct validity for the verbal associated pairs screen

The present study introduces the Verbal Associated Pairs Screen (VAPS) as a new measure for assessing performance validity in pediatric populations. This study presents initial data on psychometric properties and establishes construct validity for the VAPS in a sample of 30 adolescent healthy controls and 206 youths with traumatic brain injury (TBI: moderate/severe, N = 30; mild, N = 176). The control group’s age (M = 14.93, SD = 1.8) was significantly higher than the moderate/severe TBI (M = 13.9, SD = 2.8), t(68.508) = ?3.038, p = .003, and mild TBI (mTBI) groups (M = 14, SD = 2.8), t(54.147) = 2.038, p = .046. The TBI groups were administered the VAPS in accord with other established performance validity tests (PVTs) and well-established memory tests as part of routine clinical evaluations. The healthy control group was administered the VAPS only. VAPS score distributions for the control group were negatively skewed and highly kurtotic. VAPS scores from the moderate/severe TBI and control groups were indistinguishable for Trial 2 (U = 274, p < .01) and the Delay (U = 396, p = .218). In the mTBI group, convergent and divergent validity was established with other well-validated PVTs and memory tests, respectively. ROC curve analyses identified optimal cutoff scores for the VAPS Total Score, with acceptable sensitivity (55%) and excellent specificity (100%), as well as strong detectability (AUC = .829, 95% CI: 0.731 – 0.928, p < .001). Clinical applications, limitations, and directions for future research with the VAPS are discussed.