Implications of the Bifactor S - 1 Model for Individual Clinical Assessment

Burns et al. (this issue) have shown that the application of the symmetrical bifactor model to attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms leads to anomalous and inconsistent results across different rater groups. In contrast to the symmetrical bifactor model, applications of the bifactor S-1 model showed consistent and theoretically well-founded results. The implications of the bifactor S-1 model for individual clinical assessment are discussed. It is shown that individual factor scores of the bifactor S-1 model reveal important information about the profile of individual symptoms that is not captured by factor scores of the multidimensional model with correlated first-order factors. It is argued that for individual clinical assessment factor scores from both types of model (multidimensional model with correlated first-order factors, bifactor S -1 model) should be estimated and compared. Finally, a general strategy for choosing an appropriate model for analyzing multi-faceted constructs is presented that compares areas of applications for (1) the multidimensional model with correlated first-order factors, (2) the bifactor S-1 model with a general reference factor, and (3) the bifactor S – 1 model with a directly assessed general factor

What makes a thriver? Unifying the concepts of posttraumatic and postecstatic growth

The thriver model is a novel framework that unifies the concepts of posttraumatic and postecstatic growth. According to the model, it is not the quality of an event, but the way it is processed, that is critical for the occurrence of post-event growth. The model proposes that meaning making, supportive relationships, and positive emotions facilitate growth processes after positive as well as traumatic experiences. The tenability of these propositions was investigated in two dissimilar cultures. In Study 1, participants from the USA (n = 555) and India (n = 599) answered an extended version of the Social Readjustment Rating Scale to rank the socioemotional impact of events. Results indicate that negative events are perceived as more impactful than positive ones in the USA, whereas the reverse is true in India. In Study 2, participants from the USA (n = 342) and India (n = 341) answered questions about the thriver model's main components. Results showed that posttraumatic and postecstatic growth are highly interrelated. All elements of the thriver model were key variables for the prediction of growth. Supportive relationships and positive emotions had a direct effect on growth, while meaning making mediated the direct effect of major life events

The Effect of Rating Scale Length on the Occurrence of Inappropriate Category Use for the Assessment of Job Satisfaction: an Experimental Online Study

When job satisfaction is measured in national panel surveys using a rating scale that consists of many response categories the psychometric quality of the data obtained is often reduced. One reason lies in an inappropriate category use (e.g., in terms of response styles or ignoring superfluous categories), which occurs when respondents are faced with an overwhelmingly large number of response options. The use of response styles can also be triggered by stable respondent characteristics. The objective of the present between-subject experimental study is to explore the impact of rating scale length on the occurrence of inappropriate category use and scale reliability. In addition, this study investigates which stable respondent characteristics and job-related factors consistently predict the use of a particular response style across all experimental conditions. A sample of MTurk workers (N = 7042) filled out a 12-item online questionnaire on aspects of job satisfaction, with a 4-, 6-, or 11-point rating scale randomly assigned. Considering the three-dimensional structure of the job satisfaction measure, we applied a multidimensional extension of the restricted mixed generalized partial credit model to explore category use patterns within each condition. The results show a similar configuration of three response-style classes in all conditions. Nevertheless, the proportion of respondents who used the rating scale inappropriately was lower in the conditions with fewer response categories. An exception was the extreme response style, which showed a similar prevalence rate in all conditions. Furthermore, we found that the use of extreme response style can be explained by a high level of general self-efficacy and perceived job autonomy, regardless of rating scale length. The findings of the study demonstrate that the prevalence of inappropriate category use can be reduced by administering rating scales with six or four response categories instead of eleven. These findings may be extended to other domains of life satisfaction

Psychometric benefits of self-chosen rating scales over given rating scales

Rating scales are susceptible to response styles that undermine the scale quality. Optimizing a rating scale can tailor it to individuals’ cognitive abilities, thereby preventing the occurrence of response styles related to a suboptimal response format. However, the discrimination ability of individuals in a sample may vary, suggesting that different rating scales may be appropriate for different individuals. This study aims to examine (1) whether response styles can be avoided when individuals are allowed to choose a rating scale and (2) whether the psychometric properties of self-chosen rating scales improve compared to given rating scales. To address these objectives, data from the flourishing scale were used as an illustrative example. MTurk workers from Amazon’s Mechanical Turk platform (N = 7042) completed an eight-item flourishing scale twice: (1) using a randomly assigned four-, six-, or 11-point rating scale, and (2) using a self-chosen rating scale. Applying the restrictive mixed generalized partial credit model (rmGPCM) allowed examination of category use across the conditions. Correlations with external variables were calculated to assess the effects of the rating scales on criterion validity. The results revealed consistent use of self-chosen rating scales, with approximately equal proportions of the three response styles. Ordinary response behavior was observed in 55–58% of individuals, which was an increase of 12–15% compared to assigned rating scales. The self-chosen rating scales also exhibited superior psychometric properties. The implications of these findings are discussed

Multimethod latent class analysis

Correct and, hence, valid classifications of individuals are of high importance in the social sciences as these classifications are the basis for diagnoses and/or the assignment to a treatment. The via regia to inspect the validity of psychological ratings is the multitrait-multimethod (MTMM) approach. First, a latent variable model for the analysis of rater agreement (latent rater agreement model) will be presented that allows for the analysis of convergent validity between different measurement approaches (e.g., raters). Models of rater agreement are transferred to the level of latent variables. Second, the latent rater agreement model will be extended to a more informative MTMM latent class model. This model allows for estimating (i) the convergence of ratings, (ii) method biases in terms of differential latent distributions of raters and differential associations of categorizations within raters (specific rater bias), and (iii) the distinguishability of categories indicating if categories are satisfyingly distinct from each other. Finally, an empirical application is presented to exemplify the interpretation of the MTMM latent class model

A comparison of German and Canadian adolescent students on their socio- motivational relationships in school

This cross-national study investigates the perception of the impact of students’ relationships towards teachers and peers on scholastic motivation in a total sample of 1477 seventh and eighth grade German (N = 1088) and Canadian (N = 389) secondary school students. By applying Multigroup Confirmatory Latent Class Analysis in Mplus we confirmed four different motivation types: (1) teacher-dependent; (2) peer-dependent; (3) teacher-and-peer-dependent; (4) teacher-and-peer-independent motivation types in Québec, Canada, as they were found in a preliminary study among German students in the state of Brandenburg (Raufelder, Jagenow, Drury, & Hoferichter, 2013). However, across the two samples, the class sizes varied considerable. The largest group among Canadian students was composed of teacher-and-peer-dependent students, followed by teacher-and-peer-independent students, while the largest group among German students was composed of peer-dependent students, followed by teacher-and- peer-independent students. In both settings the teacher-dependent motivation type constituted the smallest group. These results manifest the different impacts of social environmental variables on the motivation of German and Canadian students, having practical implications for school psychologists and educators in general

The development of socio-motivational dependency from early to middle adolescence

Research on students’ motivation has shown that motivation can be enhanced or undermined by social factors. However, when interpreting such findings, interindividual differences, and intraindividual changes underlying students’ perception of peers and teachers as a source of motivation are often neglected. The aim of the present study was to complement our understanding of socio-motivational dependency by investigating differences in the development of students’ socio-motivational dependency from early to middle adolescence. Data from 1088 students on their perceptions of peers and teachers as positive motivators when students were in seventh and eighth grade were compared with data of the same sample 2 years later. Latent class analysis supported four different motivation types (MT): (1) teacher-dependent MT, (2) peer-dependent MT, (3) teacher-and-peer-dependent MT, and (4) teacher-and-peer-independent MT. Latent transition analysis revealed substantial changes between the groups. The perceived teacher influence on students’ academic motivation increased from early to middle adolescence. Divergent roles of peers and teachers on students’ academic motivation are discussed

Uncovering mnestic problems in help-seeking individuals reporting subjective cognitive complaints

In individuals with subjective cognitive impairments (SCI) the risk for the development of a neurodegenerative disease is assumed to be increased. However, it is not clear which factors contribute to the expression of SCI: Is it related to the cognitive resources already challenged, or is the psycho-affective state of more relevance? Using a novel online assessment combining self-report questionnaires and neuropsychological psychometric tests, significant predictors for the level of complaints were identified in two samples of elderly individuals: Help-seekers (HS, n = 48) consulting a memory clinic and a matched sample of non-help-seekers (nHS, n = 48). Based on the results of the online assessment, the SCI level was found to be significantly determined by the psycho-affective state (depressive mood) in the nHS group, whereas cognitive performance (cued recall) was the main predictor in the HS group. The predictive value of recall performance, however, is more-strongly expressed in memory tests which reduce the impact of compensatory strategies (face–name-association vs. word lists). Our results indicate that the problem-focused behavior of help-seeking individuals is also associated with a higher sensitivity for cognitive deficits—which can be uncovered with an appropriate psychometric test. Considering these factors, the conversion risk in individuals with SCI can probably be determined more reliably

Skew t Mixture Latent State-Trait Analysis: A Monte Carlo Simulation Study on Statistical Performance

This simulation study assessed the statistical performance of a skew t mixture latent state-trait (LST) model for the analysis of longitudinal data. The model aims to identify interpretable latent classes with class-specific LST model parameters. A skew t-distribution within classes is allowed to account for non-normal outcomes. This flexible function covers heavy tails and may reduce the risk of identifying spurious classes, e.g., in case of outliers. Sample size, number of occasions and skewness of the trait variable were varied. Generally, parameter estimation accuracy increases with increasing numbers of observations and occasions. Larger bias compared to other parameters occurs for parameters referring to the skew t-distribution and variances of the latent trait variables. Standard error estimation accuracy shows diffuse patterns across conditions and parameters. Overall model performance is acceptable for large conditions, even though none of the models is free from bias. The application of the skew t mixture model in case of large numbers of occasions and observations may be possible, but results should be treated with caution. Moreover, the skew t approach may be useful for other mixture models