Latent State-trait Research Articles

Within-individual relations of emotional, social, and work self-efficacy beliefs to organizational citizenship behaviors

Organizational citizenship behaviors (OCBs) represent a specific class of prosocial behaviors observable in the organizational environment. This study examined the longitudinal relations among regulatory emotional, social and work self-efficacy beliefs, and their relations to Organizational Citizenship Behaviors directed at specific individuals (OCBIs) at work, using a Latent State-Trait Model with Autoregressive effects (LST-A). The LST-A decomposes variance into trait, autoregressive, and occasion-related components, and allowed for testing of all hypotheses at the within-worker level. The model was tested using longitudinal data from N = 562 italian workers. Results supported the hypotheses that both social and work self-efficacy fully mediated the longitudinal relations between regulatory emotional self-efficacy in managing negative emotions at work and OCBIs. Theoretical and practical contributions of the findings are discussed.

Development and Validation of a Short Version of the Reinforcement Sensitivity Theory of Personality Questionnaire (RST-PQ-S)

We conducted three studies (total n = 998) aimed at developing and validating a shortened version of the Reinforcement Sensitivity Theory of Personality Questionnaire (i.e., the RST-PQ-S). In Study 1 (n = 341), twenty-two items were selected from the original RST-PQ, based on both theoretical and empirical criteria. Confirmatory factor analysis (CFA) on this short-form supported the six-factor structure comprising: FFFS, BIS, and four BAS components (Reward Interest, Goal Drive-Persistence, Reward Reactivity, and Impulsivity). The six scale scores showed adequate levels of internal consistency. Construct validity was supported by correlations with established personality measures. In Study 2 (n = 340), CFA results were cross-validated in an independent sample and construct validity was supported by correlations with BIS/BAS scales. In Study 3 (n = 317) test-retest correlations showed acceptable-to-good levels of temporal stability over a four-week interval. Results revealed a substantial overlap with original, full-length RST-PQ, providing evidence for the comparability of the two versions. Latent State-Trait analyses showed that the items of the RST-PQ-S mostly capture interindividual differences that are stable across situations. Taken together, findings indicate that the RST-PQ-S provides an efficient, valid and reliable alterative to the longer RST-PQ.

Multimethod Assessement of Time-Stable and Time-Variable Interindividual Differences

Abstract. The dynamic development of interindividual differences and the temporal interplay between different personality constructs are of major interest to many researchers in the field of personality psychology. Furthermore, the collection of multiple rater-perspectives complementing classical self-report measures in psychological assessment is increasingly applied also in longitudinal research. Nevertheless, models to analyze longitudinal multitrait-multimethod (MTMM) data are scarce. A new Latent State-Trait (LST) Graded Response Model for the analysis of longitudinal MTMM data with ordered categorical response variables is introduced. The model combines advantages of LST theory and MTMM models for different types of raters (interchangeable and structurally different) with an Item Response Theory (IRT) approach. The model allows researchers to analyze the stability and variability of personality constructs, discriminant and convergent validity, as well as rater effects on the item-level. Model application and interpretation are illustrated using subjective well-being data of young adults. Results of an extensive simulation study indicate that the model can be accurately estimated with Bayesian statistics with at least 3 measurement occasions and more than 250 target persons rated by at least 5 interchangeable raters under moderate degrees of convergent validity.

The effect of sensation seeking on alcohol use among middle school students: a latent state-trait analysis

ABSTRACT Background Sensation seeking has been implicated as a major risk factor for underage alcohol use, however little research into this personality trait has been conducted among children. Objective The current study examined if sensation seeking presents as a state or trait in children, and if the state or trait predicted future alcohol use. Methods A latent state-trait (LST) analysis was conducted among 552 individuals (54.3% female; age range 8–13; mean age 9.3) to determine the state or trait-based aspects of sensation seeking, and if this state or trait predicted future alcohol use. Sensation seeking behavior and lifetime alcohol use were assessed at four time points using two previously validated measures. Results Between 49.4% and 95.3% of individual differences in sensation seeking could be attributed to a stable underlying sensation seeking trait. Further, logistic regression of the stable trait of sensation seeking predicted future alcohol use. A one unit increase in the latent trait increased the odds a student would try alcohol by 7.83 times (95% CI = 1.49–41.11, p = .015). Standardized regression coefficients revealed that an increase of one standard deviation in the latent trait of sensation seeking increased the odds of experimentation with alcohol by 1.29 times (95% CI = 1.11–1.49, p = .001). Conclusion Findings suggest sensation seeking presents as a stable trait during childhood, which can cause children to seek out a novel or exciting behaviors such as alcohol use. Future substance use interventions may need to account for the influence of the underlying trait.

Stability and change of values during the formative years: Latent state-trait analyses of adolescents in a seven-wave panel study.

Many researchers agree that a person's values are formed during the first two decades of one's life span. But little is known about the exact formation process and the typical development of values during youth. In this article, we investigate the question of intra-individual stability and changes in values during the so-called formative years. We used the dataset of a German panel study that took place in seven waves, from 2002 to 2008 (t1 -t7 ), which contained responses obtained from 2,957 boys and girls ages 13-19. The interviews were repeated yearly and were held mainly in classrooms. An analysis of stability and change over the observed time period was done using the framework of latent state-trait theory. The results showed a stable three-dimensional value structure, with strong growth in value stability that decreased slightly at the end of the adolescent period. The development of stability among youth seems to be dependent on the values themselves. These findings are consistent with the aging-stability hypothesis-that is, values become more and more stable parts of an individual's personality during the formative years. Moreover, our results would seem to substantiate hypotheses that assume value-specific courses of development and recurring periods of stability and change later in the life cycle.

Applying the Latent State-Trait Analysis to Decompose State, Trait, and Error Components of the Self-Esteem Implicit Association Test

Abstract. In the literature, self-report scales of Self-Esteem (SE) often showed a higher test-retest correlation and a lower situational variability compared to implicit measures. Moreover, several studies showed a close to zero implicit-explicit correlation. Applying a latent state-trait (LST) model on a sample of 95 participants (80 females, mean age: 22.49 ± 6.77 years) assessed at five measurement occasions, the present study aims at decomposing latent trait, latent state residual, and measurement error of the SE Implicit Association Test (SE-IAT). Moreover, in order to compare implicit and explicit variance components, a multi-construct LST was analyzed across two occasions, including both the SE-IAT and the Rosenberg Self-Esteem Scale (RSES). Results revealed that: (1) the amounts of state and trait variance in the SE-IAT were rather similar; (2) explicit SE showed a higher consistency, a lower occasion-specificity, and a lower proportion of error variance than SE-IAT; (3) latent traits of explicit and implicit SE showed a positive and significant correlation of moderate size. Theoretical implications for the implicit measurement of self-esteem were discussed.

A latent state–trait model for analyzing states, traits, situations, method effects, and their interactions

Studies on situation and Person×Situation interaction effects often use only one method of measurement, so that the extent to which the effects may be method-specific cannot be determined. We introduce a new multimethod latent state-trait model for random and fixed situations (MM-LST-RF), which allows examining person, situation, and Person×Situation interaction effects in the context of multimethod measurement designs (e.g., studies with multiple reporters), and discuss potential areas of application for the new model in personality research. The new model allows analyzing novel features of multimethod, multi-situation data, including (a) the convergent validity and method specificity of trait (person) effects, situation effects, and Person×Situation interaction effects; (b) the degree of situation specificity of method effects; and (c) potential Method×Situation interactions. An application to smoker's affect (N=235; 57% female; 93% Caucasian) before and after quitting smoking is presented with positively and negatively worded items as methods. The MM-LST-RF model fit the smoking data well. Method specificity of many effects was high. The MM-LST-RF model provides researchers with a new framework for testing method specificity of person, situation, and interaction effects.

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.

DO TEXT OR PHOTO MATTER FOR THE MARKETING PERFORMANCE OF SOCIAL MEDIA MESSAGE?

This paper utilized the dual coding theory (Yang, Hlee, Lee, & Koo, 2017) and theory of latent state–trait (LST) (Steyer, Schmitt and Eid, 1999) to the application of consumer impulse purchasing behaviors and further revealed that the number of reaching can thus be identified as a trigger for impulse buying on social media. Three inputs (number of color, text length, number of photo) and three outputs (number of likes; number of comments, and shares; and number of clicks on post) are used to develop this marketing message performance assessment model in the social medial based on the literature and expert opinions through data envelopment analysis (DEA). The disaggregate efficiencies are also assessed in order to improve the individual input resource performance in a total-factor framework. Resource-saving target ratios (RSTR) for 60 marketing message in a five-star hotel chain. The empirical findings indicate that the average total-factor text length efficiency (TFTLE) is worse than the total-factor photo efficiency (TFPE) in the Facebook platform in the five-star hotel chain. This result suggests that photo message is more attractive for viewer than the text message. Managerial discussion and the future studies are discussed.

Cross-Informant Assessment of Children's Sympathy: Disentangling Trait and State Agreement

The use of multiple informants (e.g., caregivers and teachers) is recommended to obtain a comprehensive profile of children’s social emotional development. Evidence to date indicates that only a small-to-moderate degree of convergence exists between different informants’ assessments of children’s social-emotional functioning, especially when the contexts of such informants’ observations are also different. However, whether caregivers and teachers primarily disagree about children’s dispositional emotional tendencies or situational emotional fluctuations remains unclear. In this study, we investigated the extent to which caregivers and teachers converged in their evaluation of children’s dispositional and state sympathy (i.e., a relatively internal and low visibility emotional response of concern for another’s wellbeing) in a nationally representative sample of Swiss children (N = 1,273) followed from 6 to 12 years of age. Using analyses based in latent state–trait theory, we found that caregivers and teachers showed moderate-to-large agreement (r = .510) at the dispositional, trait level of children’s sympathy, but only a small level of agreement in their assessments of children’s situational, state-like manifestations of sympathy (r = .123). These findings highlight the differential convergence of adults’ ratings of one core dimension of children’s social-emotional development, i.e., sympathy, at the dispositional and situational levels, and, relatedly the need to investigate the reasons behind discrepancies at both levels of analysis. We elaborate on practical implications for designing social-emotional screening tools across different informants and contexts.

Stability and instability in the co-development of mathematics, executive function skills, and visual-motor integration from prekindergarten to first grade

Correlational and short-term longitudinal studies both demonstrate significant associations between children’s executive function skills and visual-motor integration and their mathematics achievement in early childhood. Our current understanding of the development of these skills in early childhood is limited, however, by a lack of clarity concerning whether the associations between them are causal in nature or could be explained by other unmeasured stable characteristics shared among the constructs. Using a latent state-trait approach, we examined the development of executive function skills, visual-motor integration, and children’s mathematics achievement from the beginning of prekindergarten to the end of first grade (N = 1138). Findings of stability and instability in relative rankings in children’s skills across four time points suggest that children’s growth in mathematics skills is a product of both persistent unmeasured stable influences and time-specific effects of prior executive function skills and visual-motor integration. Specifically, visual-motor integration related to subsequent mathematics achievement and executive function skills in prekindergarten, and executive function and mathematics achievement were bidirectionally related through first grade, even when accounting for stability in each construct. These results suggest that future experimental research should consider executive function skills and visual-motor integration as well as specific mathematics skills as potential targets for early mathematics instruction.

Latent state-trait modeling

Questions concerning longitudinal stability and multi-method consistency are critical to temperament research. Latent State-Trait (LST) analyses address these directly, and were utilized in this study. Thus, our primary objective was to apply LST analyses in a temperament context, using longitudinal and multi-method data to determine the amount of trait vs. state variance, as well as convergence for measures of Distress to Limitations (DL) facets. Mothers’ ratings and independent observations of DL behaviors collected on two occasions (8 months old and 12 months old) for 148 infants (49.2% female) were utilized. Single source latent state-trait (LST) analyses indicated that parent ratings of DL behavior (PDL) contained more trait (M = 61%) than state residual (M = 39%) variance, whereas independent observations (IO) of DL behavior contained substantially more state residual (75%) than trait (25%) variance. A multiple source LST analysis indicated virtually zero convergence for either trait or state residual variance between PDL and IO ratings (M = 2%). In conclusion, PDL ratings were more trait-like across the 4-month interval, whereas IO ratings of DL were more state-like in nature. Also, no convergence was found between the two methods of measurement. Results are discussed with an emphasis on implications for the utility of LST analyses in temperament research.

Are You Ready to Have Fun? The Spanish State Form of the State–Trait–Cheerfulness Inventory

ABSTRACTAlthough cheerfulness, seriousness, and bad mood as traits have been widely studied as the basis of sense of humor, data are scarce regarding the same dimensions as states. In this study, we adapted the state form of the State–Trait–Cheerfulness Inventory (STCI–S) into Spanish. At the same time, we empirically tested new predictions. We assessed 5 independent samples accounting for 1,029 participants (647 women) with ages ranging from 18 to 78 years. We confirmed the 3-dimensional structure as well as a strong measurement invariance between men and women. The internal consistency of the scale was satisfactory, the expected intercorrelations emerged, and the convergence between states and traits was corroborated. We also confirmed that the STCI–S's items were sensitive to affective changes in the environment. A longitudinal stability study of the state–trait dimensions using latent state–trait (LST) models revealed that all three trait measures capture mostly stable interindividual differences, with occasion-specific effects mainly in the state dimensions. Finally, we found that the STCI–S dimensions were related to state well-being. The results suggest that the STCI–S is a valid option for measuring the state basis of sense of humor in the Spanish population.

A Latent State-Trait Analysis of Current Achievement Motivation Across Different Tasks of Cognitive Ability

Abstract. The current study investigates the behavior of task-specific, current achievement motivation (CAM: interest in the task, probability of success, perceived challenge, and fear of failure) across a variety of reasoning tasks featuring verbal, numerical, and figural content. CAM is conceptualized as a state-like variable, and in order to assess the relative stability of the four CAM variables across different tasks, latent state trait analyses are conducted. The major findings indicate that the degree of challenge a test taker experiences and the fear of failing a given task appear to be relatively stable regardless of the specific task utilized, whereas interest and probability of success are more directly influenced by task-specific characteristics and demands. Furthermore, task performance is related to task-specific interest and probability of success. We discuss the implications and benefits of these results with regard to the use of cognitive ability tests in general. Importantly, taking motivational differences between test takers into account appears to offer valuable information which helps to explain differences in task performance.

On the Definition of Latent-State-Trait Models With Autoregressive Effects

Abstract. In longitudinal studies with short time lags, classical models of latent state-trait (LST) theory that assume no carry-over effects between neighboring occasions of measurement are often inappropriate, and have to be extended by including autoregressive effects. The way in which autoregressive effects should be defined in LST models is still an open question. In a recently published revision of LST theory (LST-R theory), Steyer, Mayer, Geiser, and Cole (2015) stated that the trait-state-occasion (TSO) model ( Cole, Martin, & Steiger, 2005 ), one of the most widely applied LST models with autoregressive effects, is not an LST-R model, implying that proponents of LST-R theory might recommend not to apply the TSO model. In the present article, we show that a version of the TSO model can be defined on the basis of LST-R theory and that some of its restrictions can be reasonably relaxed. Our model is based on the idea that situational effects can change time-specific dispositions, and it makes full use of the basic idea of LST-R theory that dispositions to react to situational influences are dynamic and malleable. The latent variables of the model have a clear meaning that is explained in detail.

A Continuous-Time Mixture Latent-State-Trait Markov Model for Experience Sampling Data

Abstract. In psychological research, statistical models of latent state-trait (LST) theory are popular for the analysis of longitudinal data. We identify several limitations of available models when applied to intensive longitudinal data with categorical observed and latent variables and inter- and intraindividually varying time intervals. As an extension of available LST models for categorical data, we describe a general mixed continuous-time LST model that is suitable for intensive longitudinal data with unobserved heterogeneity and individually varying time intervals. This model is illustrated by an application to momentary mood data that were collected in an experience sampling study (N = 164). In addition, the results of a simulation study are reported that was conducted to find out (a) the minimal data requirements with respect to sample size and number of occasions, and (b) how strong the bias is if the continuous-time structure is ignored. The empirical application revealed two classes for which the transition pattern and effects of time-varying covariates differ. In the simulation study, only small differences between the continuous-time model and its discrete-time counterpart emerged. Sample sizes N = 100 and larger in combination with six or more occasions of measurement tended to produce reliable estimation results. Implications of the models for future research are discussed.

How Much Trait Variance Is Captured by Measures of Academic State Emotions?

Abstract. Although the popularity of research on academic emotions is on the rise, little is known about the extent to which these emotional experiences are due to stable (trait) versus situational (state) influences. In the present paper, we applied the latent state-trait approach (LST) to multiple state assessments of five frequently experienced discrete academic emotions (enjoyment, pride, anger, anxiety, boredom) to disentangle their trait versus state variance components. We had two main aims: (1) to identify the differential contributions of the person-specific (trait) and situation-specific (state) variance components of discrete academic emotions, and (2) to examine the relations between different discrete academic emotions with regard to their latent trait and latent state residual components. Eight hundred thirty-seven German students participated in this diary study that lasted 2–3 weeks. During this time, students responded to short (two items per emotion) questionnaires asking about their lesson-specific state emotions in mathematics. The results revealed that for each academic emotion the trait variance and state residual components were of about equal size. Further, while differently valenced (positive vs. negative) latent trait components of students’ emotions were mostly uncorrelated (with the exception of boredom), differently valenced latent state residual components of students’ emotions were negatively correlated. We discuss our findings in relation to the structure of current affect and highlight their implications for classroom practices.

Trait and state variance in oppositional defiant disorder symptoms: A multi-source investigation with Spanish children.

The objective was to determine and compare the trait and state components of oppositional defiant disorder (ODD) symptom reports across multiple informants. Mothers, fathers, primary teachers, and secondary teachers rated the occurrence of the ODD symptoms in 810 Spanish children (55% boys) on 2 occasions (end first and second grades). Single source latent state-trait (LST) analyses revealed that ODD symptom ratings from all 4 sources showed more trait (M = 63%) than state residual (M = 37%) variance. A multiple source LST analysis revealed substantial convergent validity of mothers' and fathers' trait variance components (M = 68%) and modest convergent validity of state residual variance components (M = 35%). In contrast, primary and secondary teachers showed low convergent validity relative to mothers for trait variance (Ms = 31%, 32%, respectively) and essentially zero convergent validity relative to mothers for state residual variance (Ms = 1%, 3%, respectively). Although ODD symptom ratings reflected slightly more trait- than state-like constructs within each of the 4 sources separately across occasions, strong convergent validity for the trait variance only occurred within settings (i.e., mothers with fathers; primary with secondary teachers) with the convergent validity of the trait and state residual variance components being low to nonexistent across settings. These results suggest that ODD symptom reports are trait-like across time for individual sources with this trait variance, however, only having convergent validity within settings. Implications for assessment of ODD are discussed. (PsycINFO Database Record

How Consistent Is Sluggish Cognitive Tempo Across Occasions, Sources, and Settings? Evidence From Latent State-Trait Modeling.

Research has yet to determine how much of the variance in sluggish cognitive tempo (SCT) symptom ratings is consistent across occasions, sources, and settings versus specific to occasion, source, and setting. Our first objective was to determine the amount of variance in SCT ratings that was consistent ( trait consistency) across three occasions of measurement over 12 months versus specific to the occasion ( occasion-specificity) with ratings by mothers, fathers, primary teachers, and secondary teachers of 811 Spanish children. Our second objective was then to determine the convergent validity for trait consistency and occasion-specificity variance components within and across settings. SCT ratings reflected mostly trait consistency for mothers, fathers, and primary teachers (less so for secondary teachers) with the convergent validity for trait consistency also being strong for mothers with fathers and for primary teachers with secondary teachers. Across home and school, however, convergent validity for trait consistency was low and even lower for occasion-specificity. SCT appears to be more trait-like rather than state-like, with similar levels of trait consistency across occasions and convergent validity within settings as attention-deficit/hyperactivity disorder (ADHD) symptoms in a prior study. However, SCT symptoms had slightly weaker convergent validity for trait consistency across settings relative to ADHD symptoms.

Exploring Occasion Specificity in the Assessment of DSM-5 Maladaptive Personality Traits

Abstract. The alternative classification system for personality disorders in DSM-5 features a hierarchical model of maladaptive personality traits. This trait model comprises five broad trait domains and 25 specific trait facets that can be reliably assessed using the Personality Inventory for DSM-5 (PID-5). Although there is a steadily growing literature on the validity of the PID-5, issues of temporal stability and situational influences on test scores are currently unexplored. We addressed these issues using a sample of 611 research participants who completed the PID-5 three times, with time intervals of 2 months. Latent state-trait (LST) analyses for each of the 25 PID-5 trait facets showed that, on average, 79.5% of the variance was due to stable traits (i.e., consistency), and 7.7% of the variance was due to situational factors (i.e., occasion specificity). Our findings suggest that the PID-5 trait facets predominantly capture individual differences that are stable across time.