Assessing structure building in college classrooms at scale

Structure building refers to the way in which people construct meaning from incoming information by creating a foundation of mental nodes, mapping incoming information to the foundational structure, and shifting to a new structure when necessary. Structure building ability has been shown to moderate learning both in laboratory-based and classroom-based research (e.g., use of outlines for effective note-taking and course final grades, respectively). However, measurement of structure building can be resource intensive. The purpose of the present study was to evaluate a shortened, scalable measure of structure building (developed by a textbook publisher) in a real-world context. The results are consistent with the hypothesis that this tool, embedded in the online ancillary materials accompanying a textbook, can be used to measure a variable that is relevant to students' learning in introductory psychology courses.     

Effects of varying numbers of Likert scale points on factor structure of the Rosenberg Self‐Esteem Scale

Likert‐type rating scales are among the most widely used tools in psychological research. Different numbers of response categories would likely affect response style, data distribution, reliability, and construct validity. There is a lack of research in factor structure invariance under Likert scales with different numbers of categories. The purpose of this study is to examine the effects of varying numbers of Likert points (4–11) on scale properties such as factor structure, external validity, and latent means based on the Rosenberg Self‐Esteem Scale (M. Rosenberg, 1989 ). The sample consists of 1,807 students from secondary schools in Macau. Confirmatory factor analysis shows that the correlated two‐factor model is the most appropriate one; longitudinal invariance analysis reveals that measurement invariance across Likert scales was satisfied at the scalar level. In addition, latent mean scores on the two factors as well as observed means on the subscales are comparable across Likert scales. Moreover, the measurement model across Likert scales exhibit similar external validity. Although psychometric properties are mostly similar among a different number of points, the 4‐point Likert scale is not recommended for its higher skewness and lower loadings; the 11‐point Likert scale from 0 to 10 is slightly preferred for its higher loadings and composite reliability.     

PERMA and the building blocks of well-being

Seligman (2011) hypothesized that PERMA (Positive Emotion, Engagement, Relationships, Meaning, and Accomplishment) are the elements of well-being. Goodman, Disabato, Kashdan & Kaufmann (2017) reported strong evidence that subjective well-being is the final common path of such elements and their data are entirely consistent with Seligman’s hypothesis. They argued, incorrectly however, that he suggested that PERMA constituted a different kind of well-being rather than just its building blocks. The complicated issue, one that transcends psychometrics, of how to decide on elements of well-being is discussed.     

二阶因素模型的测量等价性检验——以大学生网络利他行为量表为例

与一阶因素模型相比,二阶因素模型具有较多优点,但二阶因素模型的测量等价性检验要更复杂,它需要依次进行七个不同水平的检验：形等价、一阶弱等价、二阶弱等价、一阶强等价、二阶强等价、二阶严等价和一阶严等价。低水平的等价性满足之后,才能进行更为严格的高一水平的等价性检验。运用均值和协方差结构（MACS）模型对大学生网络利他行为量表（IABSU）进行二阶因素模型的测量等价性检验,结果表明,IABSU具有跨地域的完全一阶、二阶严等价性。     

Evolutionary preference/utility functions: A dynamic perspective

The collection of repeated measures in psychological research is one of the most common data collection formats employed in survey and experimental research. The behavioral decision theory literature documents the existence of the dynamic evolution of preferences that occur over time and experience due to learning, exposure to additional information, fatigue, cognitive storage limitations, etc. We introduce a Bayesian dynamic linear methodology employing an empirical Bayes estimation framework that permits the detection and modeling of such potential changes to the underlying preference utility structure of the respondent. An illustration of revealed stated preference analysis (i.e., conjoint analysis) is given involving students’ preferences for apartments and their underlying attributes and features. We also present the results of several simulations demonstrating the ability of the proposed procedure to recover a variety of different sources of dynamics that may surface with preference elicitation over repeated sequential measurement. Finally, directions for future research are discussed.The authors wish to acknowledge and thank the Editor, the Associate Editor, and two anonymous reviewers for their constructive and insightful comments. Duncan K.H. Fong’s work was sponsored in part by a research grant from the Smeal College.This revised article was published online in August 2005 with the PDF paginated correctly.     

Assessment of Trichotillomania: A Psychometric Evaluation of Hair-Pulling Scales

Currently there is no gold standard treatment outcome measure for trichotillomania (TTM), a disorder characterized by repetitive hair pulling resulting in noticeable hair loss. The goal of the current study was to evaluate the psychometric properties of TTM measures of differing assessment methods: self-report, clinician-rated summary scales, and clinician-rated global severity scales. Data collected from 28 patients with TTM indicated mixed psychometric properties for current scales. Internal consistency was strong for self-report but not clinician-rated summary scales. One clinician-rated summary scale total and subjective ratings of hair loss demonstrated good interrater agreement. Although convergent validity was good within measurement type, self-report did not correlate with clinician-rated global severity scales, perhaps because of absence of hair loss severity assessment on the self-report measure. A multimethod assessment including one of each type of measure reviewed in this paper, along with self-monitoring and measures of hair loss severity, is recommended for a comprehensive best practice approach to TTM assessment.     

Measurement of Depressive Symptoms in Women With Breast Cancer and Women With Clinical Depression: A Differential Item Functioning Analysis

Differential item functioning (DIF) analyses of the Beck Depression Inventory-II (BDI-II) were conducted on samples of 267 women with breast cancer and 294 women with clinical depression. Patterns of items in which there was significant and nonsignificant DIF were identified using statistical tests and measures of DIF effect size. At the most general level, 15 of 21 BDI-II items were associated with nontrivial DIF suggesting that the item responses of these samples do not reflect the same underlying construct. Factor analyses of the BDI-II using a psychometrically defensible method for item level factor analysis supported the conclusions from the DIF analyses. These findings suggest that researchers and practitioners should apply caution when interpreting self-report depression symptoms in breast cancer patients.     

Factor Structure of the Parenting Scale in a Low-Income African American Sample

We evaluated the relative goodness-of-fit of two factor structures of the Parenting Scale (Arnold, O'Leary, Wolf, {&} Acker, 1993) among two samples of low-income African American families. Participants included 271 mother-child dyads from urban and rural areas in the southern and southeastern US, who completed the Parenting Scale along with other measures of parenting style and dyadic relationship. Confirmatory Factor Analyses (CFA) indicated that a two-factor solution, comprising Laxness and Overreactivity dimensions, was the better fit to the data. Some direct evidence for convergent validity was provided by a correlation between the Laxness factor of the Parenting Scale and the Firm/Lax Control subscale of the Children's Report of Parenting Behavior Inventory (CRPBI). Results are discussed in term of Brody and Flor's (1998) “no nonsense” parenting style.