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Ecological momentary assessment (EMA) involves repeated real-time sampling of respondents' current behaviors and experiences. The intensive repeated assessment imposes an increased burden on respondents, rendering EMAs vulnerable to respondent noncompliance and/or careless and insufficient effort responding (C/IER). We developed a mixture modeling approach that equips researchers with a tool for (a) gauging the degree of C/IER contamination of their EMA data and (b) studying the trajectory of C/IER across the study. For separating attentive from C/IER behavior, the approach leverages collateral information from screen times, which are routinely recorded in electronically administered EMAs, and translates theoretical considerations on respondents' behavior into component models for attentive and careless screen times as well as for the functional form of C/IER trajectories. We show how a sensible choice of component models (a) allows disentangling short screen times due to C/IER from familiarity effects due to repeated exposure to the same measures, (b) aids in gaining a fine-grained understanding of C/IER trajectories by distinguishing within-day from between-day effects, and (c) allows investigating interindividual differences in attentiveness. The approach shows good parameter recovery when attentive and C/IER screen time distributions exhibit sufficient separation and yields valid conclusions even in scenarios of uncontaminated data. The approach is illustrated on EMA data from the German Socio-Economic Panel innovation sample. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Disengaged item responses pose a threat to the validity of the results provided by large-scale assessments. Several procedures for identifying disengaged responses on the basis of observed response times have been suggested, and item response theory (IRT) models for response engagement have been proposed. We outline that response time-based procedures for classifying response engagement and IRT models for response engagement are based on common ideas, and we propose the distinction between independent and dependent latent class IRT models. In all IRT models considered, response engagement is represented by an item-level latent class variable, but the models assume that response times either reflect or predict engagement. We summarize existing IRT models that belong to each group and extend them to increase their flexibility. Furthermore, we propose a flexible multilevel mixture IRT framework in which all IRT models can be estimated by means of marginal maximum likelihood. The framework is based on the widespread Mplus software, thereby making the procedure accessible to a broad audience. The procedures are illustrated on the basis of publicly available large-scale data. Our results show that the different IRT models for response engagement provided slightly different adjustments of item parameters of individuals' proficiency estimates relative to a conventional IRT model., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2021.)

Digital tests make it possible to identify student effort by means of response times, specifically, unrealistically fast responses that are defined as rapid-guessing behavior (RGB). In this study, we used latent class and growth curve models to examine (1) how student characteristics (i.e., gender, school type, general cognitive abilities, and working-memory capacity) are related to the onset point of RGB and its development over the course of a test session (i.e., item positions). Further, we examined (2) the extent to which repeated ratings of task enjoyment (i.e., intercept and slope parameters) are related to the onset and the development of RGB over the course of the test. For this purpose, we analyzed data from N = 401 students from fifth and sixth grades in Germany ( n = 247 academic track; n = 154 non-academic track). All participants solved 36 science items under low-stakes conditions and rated their current task enjoyment after each science item, constituting a micro-longitudinal design that allowed students' motivational state to be tracked over the entire test session. In addition, they worked on tests that assessed their general cognitive abilities and working-memory capacity. The results show that students' gender was not significantly related to RGB but that students' school type (which is known to be closely related to academic abilities in the German school system), general cognitive abilities, and their working-memory capacity were significant predictors of an early RGB onset and a stronger RGB increase across testing time. Students' initial rating of task enjoyment was associated with RGB, but only a decline in students' task enjoyment was predictive of earlier RGB onset. Overall, non-academic-school attendance was the most powerful predictor of RGB, together with students' working-memory capacity. The present findings add to the concern that there is an unfortunate relation between students' test-effort investment and their academic and general cognitive abilities. This challenges basic assumptions about motivation-filtering procedures and may threaten a valid interpretation of results from large-scale testing programs that rely on school-type comparisons.

Objective: Our study addressed three questions concerning the similarity of vocational interests within families: (a) How similar are vocational interests of mothers and fathers? (b) How similar are vocational interests of parents and their children? (c) Is the inference about parent-child profile similarity affected by mother-father profile similarity?, Method: Data from N=1,624 tenth graders and their parents were used to analyze interest profile similarity by means of a pseudo-coupling approach. Similarity was assessed on the level of observed profiles and model-based circumplex profiles., Results: Interest profiles of mother-father and parent-child dyads were more similar to each other than those of corresponding arbitrarily paired dyads. However, when the similarity between the parents' interest profiles was accounted for, only same-sex parent-child dyads were more similar to each other than would be expected by chance. All findings were mirrored on the level of observed profiles and model-based circumplex profiles., Conclusions: In sum, our findings support the validity of the circumplex model of vocational interests and emphasize the benefits of explicitly considering its implications when analyzing profile similarity. Moreover, we were able to show that the statistical evaluation of profile similarities must account for normative profile components., (© 2018 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.)

Circumplex structures are elements of various psychological domains. Most work focuses on assessing the circular ordering of circumplex indicators and their relationships with covariates. In this article, an extension procedure for Browne's circumplex model is presented. Our approach models the relationships among circumplex indicators and the relationships of covariates with a latent circumplex simultaneously without affecting the circumplex indicators' positions on the circumplex. The approach builds upon Browne's Fourier series parameterization of a correlation function, which is used to model the latent circumplex correlation structure. It extends the shape of the correlation function to the profile of each covariate's correlations with the circumplex. The model is specified in the framework of structural equation modeling, thereby making it possible to test various hypotheses. Procedures are presented for deriving interval estimates for the parameters that relate the covariates to the circumplex. The model is compared to other approaches for assessing the relationships of a circumplex with covariates. The results of the exemplary applications and a simulation study were in favor of the suggested model. The approach is furthermore illustrated with a real-data example, focusing on the relationships between the interpersonal circumplex and the rivalry and admiration aspects of narcissism.

Item context effects refer to the impact of features of a test on an examinee's item responses. These effects cannot be explained by the abilities measured by the test. Investigations typically focus on only a single type of item context effects, such as item position effects, or mode effects, thereby ignoring the fact that different item context effects might operate simultaneously. In this study, two different types of context effects were modeled simultaneously drawing on data from an item calibration study of a multidimensional computerized test ( N = 1,632) assessing student competencies in mathematics, science, and reading. We present a generalized linear mixed model (GLMM) parameterization of the multidimensional Rasch model including item position effects (distinguishing between within-block position effects and block position effects ), domain order effects , and the interactions between them. Results show that both types of context effects played a role, and that the moderating effect of domain orders was very strong. The findings have direct consequences for planning and applying mixed domain assessment designs.

Tests administered in studies of student achievement often have a certain amount of not-reached items (NRIs). The propensity for NRIs may depend on the proficiency measured by the test and on additional covariates. This article proposes a semiparametric model to study such relationships. Our model extends Glas and Pimentel's item response theory model for NRIs by (1) including a semiparametric representation of the distribution of the onset of NRIs, (2) modeling the relationships of NRIs with proficiency via a flexible multinomial logit regression, and (3) including additional covariates to predict NRIs. We show that Glas and Pimentel's and our model have close connections to event history analysis, thereby making it possible to apply tools developed in this context to the analysis of NRIs. Our model was applied to a timed low-stakes test of mathematics achievement. Our model fitted the data better than Glas and Pimentel's model, and allowed for a more fine-grained assessment of the onset of NRIs. The results of a simulation study showed that our model accurately recovered the relationships of proficiency and covariates with the onset of NRIs, and reduced bias in the estimates of item parameters, proficiency distributions, and covariate effects on proficiency., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Personality development in emerging adults who do not attend college after high school has been largely overlooked so far. In this study, we investigated personality development in emerging German adults (N T 1  = 1,886, M ageT1  = 18.01 years, 29% female) undergoing vocational education and training (VET). The trainees were assessed at the start of VET, 1.5 years later, and another 1.5 years after that, just before graduation. Longitudinal latent change score analyses were applied. Bivariate analyses investigated life satisfaction and job strain as social and work-related aspects that are potentially reciprocally related to personality development. Mean-level personality changes included increases in neuroticism and decreases in agreeableness and conscientiousness in the first interval. In the second interval, neuroticism decreased and conscientiousness increased. Simultaneously, trainees reported a gradual decrease in extraversion and openness across the 3-year time span. Personality, especially agreeableness and conscientiousness, emerged as a stronger predictor of changes in job strain and life satisfaction than vice versa. For example, more agreeable and more conscientious trainees subsequently showed increases in life satisfaction. Trainees reporting higher job strain subsequently showed decreases in agreeableness. Trajectories of personality development partly support the maturity principle that has been established in many college student samples., (© 2018 The British Psychological Society.)

Exerting self-control in a first task weakens self-control performance in a subsequent unrelated task (ego depletion). In self-control research new strategies are required to investigate the ego-depletion effect, which has recently been shown to be more fragile than previously assumed. Moreover, the relation between ego depletion and trait self-control is still unclear, as various studies have reported heterogeneous findings concerning the interplay of both variables. We addressed these lacunas by drawing on a sample of N = 120 students, who participated in two test sessions. In the first test session, we assessed trait self-control and several control variables. The second test session followed an experimental design and tested the effects of ego depletion on invested effort and cognitive performance trajectories in an ecologically valid computer-based assessment setting (i.e., a 30-minute mathematical problem-solving and reasoning test). Trait self-control was then used as a moderator of the ego-depletion effect. Combining an established ego-depletion paradigm (i.e., the sequential-task paradigm) with multilevel modeling of time-on-task and performance changes, our results indicate (1) that trait self-control predicted the motivation to solve cognitive tasks, (2) that ego depletion led to a progressive performance decrease, and (3) that the negative effect of ego depletion on performance was stronger for students with high trait self-control. Additional analyses revealed that our results could not be alternatively explained by fatigue effects. All effects were robust even after controlling for the students' cognitive abilities, which are known to be closely related to mathematical performance. Our results provide evidence that the self-control invested in order to keep performance at a consistently high level wanes over time. By modeling progressive ego-depletion effects while considering trait self-control, we provide an alternative approach that may help future researchers to investigate the underlying mechanisms of self-control.

Though it is frequently assumed that the college experience can influence our life goals, this claim has been relatively understudied. The current study examined the role of goals in college major selection, as well as whether major selection influences later goal change. In addition, we examined whether a person's perceptions of his or her peers' goals influence goal setting. Using a sample of German students (Mage  = 19 years; n = 3,023 at Wave 1), we assessed life goal levels and changes from high school into college across three assessment occasions. Participants reported their current aspirations, along with the perceived goals of their peers during the college assessments. Using latent growth curve models, findings suggest that life goals upon entering college significantly predict the majors students select. However, this major selection had limited influence on later changes in life goals. Stronger effects were found with respect to perceptions of peers' goals, with students tending to change their goals to better align with their peers. The current study provides evidence that life goals are relatively stable and yet can change during the emerging adult years, in ways that demonstrate the potential influence of the college experience., (© 2014 Wiley Periodicals, Inc.)

Background: Vocational interests play a central role in the vocational decision-making process and are decisive for the later job satisfaction and vocational success. Based on Ackerman's (1996) notion of trait complexes, specific interest profiles of gifted high-school graduates can be expected., Aims: Vocational interests of gifted and highly achieving adolescents were compared to those of their less intelligent/achieving peers according to Holland's (1997) RIASEC model. Further, the impact of intelligence and achievement on interests were analysed while statistically controlling for potentially influencing variables. Changes in interests over time were investigated., Sample: N= 4,694 German students (age: M= 19.5, SD= .80; 54.6% females) participated in the study (TOSCA; Köller, Watermann, Trautwein, & Lüdtke, 2004)., Method: Interests were assessed in participants' final year at school and again 2 years later (N= 2,318)., Results: Gifted participants reported stronger investigative and realistic interests, but lower social interests than less intelligent participants. Highly achieving participants reported higher investigative and (in wave 2) higher artistic interests. Considerable gender differences were found: gifted girls had a flat interest profile, while gifted boys had pronounced realistic and investigative and low social interests. Multilevel multiple regression analyses predicting interests by intelligence and school achievement revealed stable interest profiles. Beyond a strong gender effect, intelligence and school achievement each contributed substantially to the prediction of vocational interests., Conclusions: At the time around graduation from high school, gifted young adults show stable interest profiles, which strongly differ between gender and intelligence groups. These differences are relevant for programmes for the gifted and for vocational counselling., (©2012 The British Psychological Society.)

In this article, the authors develop and test a differential effects model of university entry versus major selection using a set of common predictors, including background factors (gender and socioeconomic status), academic achievement, and academic self-concept. The research used data from 2 large longitudinal databases from Germany (N = 5,048) and England (N = 15,995) to explore the generalizability of the hypothesized model in 2 cultural contexts. For both countries, the results suggested that (a) socioeconomic status was a key predictor of university entry, whereas gender was a key predictor of major selection; (b) achievement and self-concept in both math and English were positive predictors of university entry; and (c) math achievement and self-concept predicted math-intensive major choice and lower likelihood of entering verbal-intensive majors (and vice versa). Implications for theory and practice are discussed.

Many psychological constructs are conceived to be hierarchically structured and thus to operate at various levels of generality. Alternative confirmatory factor analytic (CFA) models can be used to study various aspects of this proposition: (a) The one-factor model focuses on the top of the hierarchy and contains only a general construct, (b) the first-order factor model focuses on the intermediate level of the hierarchy and contains only specific constructs, and both (c) the higher order factor model and (d) the nested-factor model consider the hierarchy in its entirety and contain both general and specific constructs (e.g., bifactor model). This tutorial considers these CFA models in depth, addressing their psychometric properties, interpretation of general and specific constructs, and implications for model-based score reliabilities. The authors illustrate their arguments with normative data obtained for the Wechsler Adult Intelligence Scale and conclude with recommendations on which CFA model is most appropriate for which research and diagnostic purposes., (© 2011 The Authors. Journal of Personality © 2011, Wiley Periodicals, Inc.)

This article examines the development of social and ethnic disparities in academic achievement in elementary schooling. It investigated whether reading and mathematics development in 136 mixed-ability classes shows path-dependent processes of cumulative advantage (Matthew effects) from Grades 4 to 6 (Grade 4 mean age = 10.62, SD = 0.57) resulting in growing inequality. Status-dependent processes of cumulative advantage, their interaction with path-dependent processes, and consequences for the degree of social and ethnic inequality are examined. Two complementary methods for analyzing multilevel data are used: growth curve and quasi-simplex models. No evidence for a Matthew effect was found in either domain. A compensation effect emerged for reading, to the benefit of ethnic minorities. A fan-spread effect was found for mathematics, partly attributable to status-dependent processes of cumulative advantage., (© 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.)

This longitudinal study examined the relation between continuity and change in the Big Five personality traits and life events. Approximately 2,000 German students were tracked from high school to university or to vocational training or work, with 3 assessments over 4 years. Life events were reported retrospectively at the 2nd and 3rd assessment. Latent curve analyses were used to assess change in personality traits, revealing 3 main findings. First, mean-level changes in the Big Five factors over the 4 years were in line with the maturity principle, indicating increasing psychological maturity from adolescence to young adulthood. Second, personality development was characterized by substantive individual differences relating to the life path followed; participants on a more vocationally oriented path showed higher increases in conscientiousness and lower increases in agreeableness than their peers at university. Third, initial level and change in the Big Five factors (especially Neuroticism and Extraversion) were linked to the occurrence of aggregated as well as single positive and negative life events. The analyses suggest that individual differences in personality development are associated with life transitions and individual life experiences., (PsycINFO Database Record (c) 2011 APA, all rights reserved.)

Most longitudinal, correlational studies on health-behaviour change examine effects of Time1 social-cognitive predictors on subsequent behaviour. In contrast, our research focuses on associations between changes in predictors with change in behaviour. The Health Action Process Approach (HAPA) distinguishes between motivational predictors for intention formation and volitional predictors for behavioural change and served as theoretical basis. Two online-studies were launched targeting different behaviours (low-fat diet, smoking), different samples (Study 1: N = 469; Study 2: N = 441) and different time spans (Study 1: 3 months, Study 2: 4 weeks). Data were analysed by means of structural equation modelling with latent difference scores. Both studies resulted in almost parallel prediction patterns. Change in risk awareness and change in outcome expectancies did not result in change in intentions, whereas change in self-efficacy was of crucial importance. Change in behaviour was associated with change in action planning and action control over and above the effects of intentions. In one study, increases in self-efficacy yielded increases in behaviour change. Results demonstrate that change in action planning and especially action control was of great importance for behaviour change across two different behaviours. Analysing change in social-cognitive predictors allows drawing precise conclusions for interventions.

Whether sequence learning entails a single or multiple memory systems is a moot issue. Recently, D. R. Shanks, L. Wilkinson, and S. Channon advanced a single-system model that predicts a perfect correlation between true (i.e., error free) response time priming and recognition. The Shanks model is contrasted with a dual-process model that incorporates both response time priming and reportable sequence knowledge as predictors of recognition. The models were tested by applying confirmatory factor analysis to data obtained from a recognition test that was administered under both speed and accuracy conditions. The Shanks model accounted for the data in the speed condition, whereas the dual-process model provided a better fit in the accuracy condition. The results are compatible with the notion that cognitive processes were engaged differentially in recognition judgments under speed and accuracy conditions., ((c) 2009 APA, all rights reserved)

Objectives: Most studies examine associations between social-cognitive variables and self-regulated behavioural change across two or three occasions only. This study adopts an innovative perspective by analysing associations across 11 occasions, which allows examining patterns of associations both on the between- and within-person levels., Method: Thirty initially untrained participants of a running training programme completed 11 monthly questionnaires. All questionnaires assessed motivational and volitional variables and self-reported running. Additionally, net running time of marathon, or half-marathon distance at the end of programme, was available., Results: Self-efficacy turned out to be associated with intentions on the between- and within-person levels. Individual differences in change patterns and within-person fluctuations in volitional variables, intentions, and self-efficacy turned out to be consistently associated with change patterns and within-person fluctuations in self-regulated running training over time and with successfully running marathon or half-marathon distance., Conclusions: In contrast to examining only one facet of change, this study is the first to differentiate two components of change in health behaviour self-regulation: a systematic trend component, and a component representing within-person unsystematic fluctuations. Thus, results of the present study provide a comprehensive picture of the dynamic relations between motivational, volitional, and behavioural characteristics which occur between and within persons.

Prevailing social cognition models consider behavioural intentions as immediate precursors of actions. This view ignores the role of more proximal self-regulatory processes, such as action control. The latter emerges after an intention has been formed and is supposed to maintain the level of intentions over time and to translate them into action. Three facets of action control were examined in terms of their predictive power for changes in intentions and for physical exercise: (a) awareness of standards, (b) self-monitoring, and (c) self-regulatory effort. A parsimonious 6-item instrument was administered to 122 cardiac patients at six weekly measurement points in time following rehabilitation. A distinction was made between the level of action control and the degree of change in action control, applying a latent growth model. While awareness of standards remained stable, the other two facets exhibited a linear change over the six-week period. Level and change were distinct predictors of physical exercise and changes in intentions. These findings emphasize the importance of self-regulatory mechanisms in the first weeks of trying to overcome a sedentary lifestyle. Action control may be a promising construct to narrow the intention-behaviour gap.