Intimate partner cohesion and military unit cohesion: Different types of interpersonal relationships each uniquely predict soldier well-being

Although research on military populations has found that measures of personal well-being are correlated with both intimate partner cohesion and military unit cohesion, it is not clear how these correlations should be interpreted. Based on Relationship Regulation Theory, it was expected that each type of interpersonal relationship would have independent effects, that each would uniquely predict outcomes, and that effects would remain significant after controlling for person-level traits and experiences, such as trait resilience and exposure to combat. A sample of 273 active-duty military personnel completed self-report measures of cohesion in two types of interpersonal relationships (intimate relationships and military unit relationships), two control variables (trait resilience and combat exposure), and three outcome variables (well-being, negative emotionality, and trauma-related stress). Results indicated that cohesion in the two types of relationships were minimally related to each other, but both correlated with outcome variables. Effects for each type of interpersonal relationship remained significant after controlling for the other type and controlling for trait resilience and combat exposure. The results suggest that the effects of interpersonal cohesion are best understood as reflecting experiences in specific types of relationships rather than general characteristics of people in those relationships.     

The relationship between positive and negative affect in the Positive and Negative Affect Schedule

The Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) is one of the most widely used affect scales. Nevertheless, the relation between its two scales, positive affect (PA) and negative affect (NA), is still controversial. Previous results that suggest independence between NA and PA were limited to manifest variables. In this study, the relation between PA and NA for both state and trait instructions was analyzed by means of structural equation modeling. Two hundred ninety-two participants responded to the PANAS at three occasions of measurement. No association was found between trait PA and NA, but significant negative correlations between state PA and NA emerged. In the second step, the observed variance of state PA and NA was decomposed into a dispositional component, an occasion-specific component, a method-specific component, and a component due to measurement error by employing a multi-construct latent state–trait model. This analysis confirmed and extended the results of our first analysis: the dispositional components of state PA and NA were unrelated. In contrast, the situation-specific components were negatively associated. Thus, the negative correlation between state PA and NA could be traced back to situation-specific effects.     

If you feel bad, it's unfair: a quantitative synthesis of affect and organizational justice perceptions

Whereas research interest in both individual affect/temperament and organizational justice has grown substantially in recent years, affect's role in the perception of organizational justice has received scant attention. Here, the authors integrate these literatures and test bivariate relationships between state affect (e.g., moods), trait affect (e.g., affectivity), and organizational justice variables using meta-analytically aggregated effect sizes. Results indicated that state and trait positive and negative affect exhibit statistically significant relationships with perceptions of distributive, procedural, and interactional justice in the predicted directions, with mean population-level correlations ranging in absolute magnitude from M(rho) = .09 to M(rho) = .43. Correlations involving state affect generally were larger but not significantly different from those involving trait affect. Finally, the authors propose ideas for investigations at the primary-study level.     

When Thoughts Turn Toward Nuclear War: Stress Responses,Coping Strategies,and the Importance of Trait Anxiety in Moderating Effects on “Mental Health”1

The present investigation attempted to link the concept of Nuclear Anxiety (NA) to theory and research on stress and coping, which would predict that person variables would be extremely important in determining the amount of anxiety precipitated by the hypothetical and ambiguous nature of nuclear war. In Part I of this study, 356 undergraduates were divided into high and low NA groups on the basis of state anxiety experienced while thinking about the threat of nuclear war. Groups were compared on five personality traits (trait anxiety, death anxiety, and three locus of control variables), two “mental health” indices (psychological well-being and expectancy for future goal attainment), five nuclear war-related attitudinal measures, nine nuclear threat orientations, nine strategies for coping with the threat, and a single behavioral measure of approach toward information about nuclear war. In Part II, the relationships between key explanatory variables were explored, and a preliminary model of Nuclear Anxiety was developed. Results revealed that the two NA groups differed on 22 of the 32 dependent measures, and that four variables (i.e., sustained [nuclear] concern, death anxiety, trait anxiety, and psychological well-being) were the best group discriminators. More importantly, path analysis revealed that trait anxiety rather than nuclear anxiety was the variable primarily controlling “mental health” status. Results are discussed with regard to the resiliency and adaptability of young people in dealing with the threat of nuclear war, intergroup differences in coping styles, and questions in need of further empirical attention.     

Multidimensionality of state and trait anxiety: factor structure of the Endler Multidimensional Anxiety Scales

The Endler Multidimensional Anxiety Scales (EMAS) are derived from an interactional model of personality that proposes that anxiety is a function of the interaction of person and situation variables. The EMAS distinguish between state and trait anxiety and assume that both are multidimensional constructs. The EMAS were administered to 2,009 students in a neutral situation. Three factor analyses were performed to clarify the empirical relation between state and trait anxiety and the variables within the 2 domains. Results support the distinction between state and trait anxiety. Factor analysis of the state items provided support for the separate dimensions of cognitive and autonomic state anxiety. Factor analysis of the trait items provided support for trait anxiety multidimensionality. Four congruent factors were associated with increases in state anxiety in 4 general situations: Social Evaluation, Physical Danger, Ambiguous, and Daily Routines.     

The role of faith in intuition, need for cognition and method of attitude formation in implicit–explicit brand attitude relationship strength

We tested the hypothesis that Faith in Intuition (FI) would moderate implicit–explicit attitude relationship strength for attitudes formed via associative processes, but not propositional processes. Experiments 1 and 2 demonstrated that FI moderated I–E relationship strength for attitudes formed via evaluative conditioning. High FI people had stronger I–E correlations. Experiment 2 showed that FI did not moderate I–E relationship strength for attitudes formed via propositional reasoning. Those low in Need for Cognition (NC), however, showed stronger I–E correlations than those high in NC. The importance of considering trait variables in combination with the method of attitude formation is discussed.     

The multidimensionality of state and trait anxiety

Abstract.— The two major problems investigated were ( a ) the multidimensionality of trait (A-Trait) and state (A-State) anxiety, and ( b ) the relationship between A-Trait and A-State under neutral conditions, using two measures of A-Trait (SR-GTA and STAI-T) and two measures of A-State (BRQ and STAI-S). These scales were administered to a sample of Swedish university students (54 males and 105 females). Factor analyses of the GTA situational scales yielded an interpersonal ego threat A-Trait factor and a physical danger A-Trait factor. Factor analyses of the GTA reaction scales and STAI-T reaction scales yielded, respectively, two and three factors providing evidence for the multidimensionality of A-Trait. Results of variance components analyses of the GTA scales provided further evidence for the multidimensionality of A-Trait. Factor analyses of the BRQand STAI-S measures yielded four and three factors, respectively, indicating the multidimensionality of A-State. The correlations between trait and state measures were higher than the correlations between the two state measures, and a factor analysis of the trait and state scales did not yield separate state and trait factors, questioning the proposition that A-Trait and A-State are distinct concepts. Via latent profile analysis, it was possible to compare A-State differences for different A-Trait profiles. Problems for further research were discussed.     

Modeling Common Traits and Method Effects in Multitrait-Multimethod Analysis

Method effects often occur when constructs are measured by different methods. In traditional multitrait-multimethod (MTMM) models method effects are regarded as residuals, which implies a mean method effect of zero and no correlation between trait and method effects. Furthermore, in some recent MTMM models, traits are modeled to be specific to a certain method. However, often we are not interested in a method-specific trait but in a trait that is common to all methods. Here we present the Method Effect model with common trait factors, which allows modeling “common” trait factors and method factors that represent method “effects” rather than residuals. The common trait factors are defined as the mean of the true-score variables of all variables measuring the same trait and the method factors are defined as differences between true-score variables and means of true-score variables. Because the model allows estimating mean method effects, correlations between method factors, and correlations between trait and method factors, new research questions may be investigated. The application of the model is demonstrated by 2 examples studying the effect of negative, as compared with positive, item wording for the measurement of mood states.     

Self-control strength and physical exercise: An ecological momentary assessment study

ObjectiveWe tested predictions made by the self-control strength model on a day level using ecological momentary assessment methodology. The study examined the relationship between self-control strength and physical exercise in participants who intended to exercise on a regular basis. We hypothesized that individuals would exercise more on days when their self-control strength was high than on days when their self-control strength was low and that trait self-control would moderate this relationship.MethodsN = 63 students aged between 19 and 32 years participated in the study. Self-control strength and physical exercise were assessed daily over a period of 20 days with an electronic diary.ResultsMultilevel analyses revealed that the level of self-control strength was positively associated with physical exercise (p = 0.01), and this relationship was stronger in individuals with low trait self-control than in those with high trait self-control (interaction effect: p = 0.03).ConclusionThese findings highlight the interplay between momentarily fluctuating variables such as self-control strength and dispositional variables such as trait self-control in the prediction of physical exercise.     

Predictors of suicide attempts: state and trait components

The authors examined the state and trait components of 3 predictors of suicide attempts (depression, hopelessness, and anxiety), and their relationship to suicidal behavior. Self-report questionnaire and interview data from 180 adolescents enrolled in a prospective naturalistic study were analyzed. Between 23% and 30% of the variance in the predictors was attributable to subjects' trait levels of these variables; the trait, as well as the state, components of the predictor variables were interrelated; and trait levels of these variables were consistently related to suicide attempts. To reduce long-term risk of suicide attempts, clinicians should focus not only on reducing short-term distress but also on reducing individuals' more enduring patterns (trait levels) of negative affectivity.     

Passionate love and anxiety in young adolescents

Two studies tested the hypothesis that young adolescents who experience a great deal of anxiety will be more likely to experience passionate love as well. In the first study, 24 boys and 17 girls, ranging in age from 12 to 14, were given the Child Anxiety Scale (which measures trait anxiety) and the Juvenile Love Scale (JLS). In the second study, 32 adolescent girls and 32 adolescent boys, ranging in age from 13 to 16, were given the State-Trait Anxiety Inventory for Children (which measures both trait and state anxiety) and the JLS. The studies found significant correlations between anxiety (both state and trait) and JLS scores in these young adolescents.As you might guess, it is extremely difficult to secure permission to interview children and adolescents about their feelings of passionate love. Thus, we would like to thank Dr. Mark Silzer, Principal of Our Redeemer Lutheran Elementary School, for his help on this project.     

Multilevel factor analysis and structural equation modeling of daily diary coping data: Modeling trait and state variation

The current study used multilevel modeling of daily diary data to model within-person (state) and between-person (trait) components of coping variables. This application included the introduction of multilevel factor analysis (MFA) and a comparison of the predictive ability of these trait/state factors. Daily diary data was collected on a large (n = 366) multiethnic sample over the course of five days. Intraclass correlation coefficient for the derived factors suggested approximately equal amounts of variability in coping usage at the state and trait levels. MFAs showed that Problem-Focused Coping and Social Support emerged as stable factors at both the within-person and between-person levels. Other factors (Minimization, Emotional Rumination, Avoidance, Distraction) were specific to the within-person or between-person levels, but not both. Multilevel structural equation modeling (MSEM) showed that the prediction of daily positive and negative affect differed as a function of outcome and level of coping factor. The Discussion section focuses primarily on a conceptual and methodological understanding of modeling state and trait coping using daily diary data with MFA and MSEM to examine covariation among coping variables and predicting outcomes of interest.     

Multilevel Factor Analysis and Structural Equation Modeling of Daily Diary Coping Data: Modeling Trait and State Variation

This study used multilevel modeling of daily diary data to model within-person (state) and between-person (trait) components of coping variables. This application included the introduction of multilevel factor analysis (MFA) and a comparison of the predictive ability of these trait/state factors. Daily diary data were collected on a large (n = 366) multiethnic sample over the course of 5 days. Intraclass correlation coefficient for the derived factors suggested approximately equal amounts of variability in coping usage at the state and trait levels. MFAs showed that Problem-Focused Coping and Social Support emerged as stable factors at both the within-person and between-person levels. Other factors (Minimization, Emotional Rumination, Avoidance, Distraction) were specific to the within-person or between-person levels but not both. Multilevel structural equation modeling (MSEM) showed that the prediction of daily positive and negative affect differed as a function of outcome and level of coping factor. The Discussion section focuses primarily on a conceptual and methodological understanding of modeling state and trait coping using daily diary data with MFA and MSEM to examine covariation among coping variables and predicting outcomes of interest.     

Examining the Role of Trait Reactance and Sensation Seeking on Perceived Threat,State Reactance,and Reactance Restoration

The present investigation sought to advance Psychological Reactance Theory (PRT) by examining whether trait reactance and sensation seeking influence the magnitude of a perceived threat, state reactance, and reactance restoration. Results revealed that high trait reactant (HTR) and low trait reactant (LTR) individuals and high sensation seekers (HSS) and low sensation seekers (LSS) processed persuasive messages similarly, adding credibility to recent PRT advances. Dogmatic and vivid language were perceived as a threat for most individuals. An interaction between dogmatic and vivid language on perceived threat was found for HTR and HSS for the sunscreen message. An indirect effect connecting language features and state reactance through perceived threat was supported. Regression analysis revealed that trait reactance and sensation seeking predict variables associated with state reactance.     

Ordinary Least Squares Estimation of Parameters in Exploratory Factor Analysis With Ordinal Data

Exploratory factor analysis (EFA) is often conducted with ordinal data (e.g., items with 5-point responses) in the social and behavioral sciences. These ordinal variables are often treated as if they were continuous in practice. An alternative strategy is to assume that a normally distributed continuous variable underlies each ordinal variable. The EFA model is specified for these underlying continuous variables rather than the observed ordinal variables. Although these underlying continuous variables are not observed directly, their correlations can be estimated from the ordinal variables. These correlations are referred to as polychoric correlations. This article is concerned with ordinary least squares (OLS) estimation of parameters in EFA with polychoric correlations. Standard errors and confidence intervals for rotated factor loadings and factor correlations are presented. OLS estimates and the associated standard error estimates and confidence intervals are illustrated using personality trait ratings from 228 college students. Statistical properties of the proposed procedure are explored using a Monte Carlo study. The empirical illustration and the Monte Carlo study showed that (a) OLS estimation of EFA is feasible with large models, (b) point estimates of rotated factor loadings are unbiased, (c) point estimates of factor correlations are slightly negatively biased with small samples, and (d) standard error estimates and confidence intervals perform satisfactorily at moderately large samples.     

Competitive worries, sport confidence, and performance ratings for young swimmers

The purpose of this study was to examine the relationships among competitive worries, sport confidence, and performance of young athletes. Participants were 143 young swimmers aged 11 to 12 years. The athletes completed trait and state questionnaires (competitive worries and sport confidence) in noncompetitive and competitive conditions, respectively. The results indicated: (a) significant relationships among trait and state characteristics and between trait General Self-confidence and performance ratings in both races as well as between performance ratings in Races 1 and 2; (b) significant differences in state variables among athletes with moderate or high and low scores on the trait variables; (c) significant differences in performance among athletes with moderate or high and low scores on the trait General Self-confidence and trait Positive Thinking in Race 1 and on variables trait General Self-confidence, state General Self confidence, and state Positive Thinking Race 2; and (d) trait General Self-confidence and trait Confidence in Unfavorable Situations were the most important predictors of young swimmers' performances. These results may be useful in application to competitive sports for young athletes. They may help in psychodiagnostic procedures and may be used for both the content and the direction of individual programs for psychological preparation of young athletes.     

Relations between CBM (oral reading and maze) and reading comprehension on state achievement tests: A meta-analysis

The purpose of this study was to examine the validity of two widely used Curriculum-Based Measures (CBM) in reading—oral reading and maze—in relation to reading comprehension on state tests using a meta-analysis. A total of 61 studies (132 correlations) were identified across Grades 1 to 10. A random-effects meta-analysis was conducted to estimate the average correlations between the two CBM tasks and reading comprehension on state tests, and to analyze the effects of potential moderating variables (characteristics of study, students, CBM, and state tests). Results revealed that the average correlation for oral reading was significantly larger than that for maze when all grade levels were included together in the analysis. When grade levels were separated, the difference between average correlations was only at the higher grades (Grades 4–10), favoring oral reading. In terms of correlations by grade level, oral reading and maze showed a similar pattern; that is, correlations were comparable across elementary grades, but decreased for secondary grades. In addition to the type of CBM and grade level differences, type of publication, type of state tests (commercial versus state-developed), and time interval between CBM and state tests were significant sources of variance in correlations. Implications for research and educational practice are discussed highlighting the somewhat different conclusions from previous literature, especially regarding the use of CBM for older students.     

Evidence of differential stability of state and trait anxiety in adults

This study used Structural Equation Modeling (SEM) to assess the differential longitudinal stabilities of state and trait anxiety. In 1985 and 1987, 227 adult volunteers (ages 22-78) rated themselves on established state and trait questionnaires. In addition, aggregated-state anxiety was measured by self-rated frequency of state anxiety experienced over the previous month. Analysis of split-half subscales from single Trait and State Anxiety scales showed the State Anxiety true score factor to have a significantly lower unstandardized autoregression coefficient (.57 vs. .91), indicating less longitudinal stability. Additional models found longitudinal factor correlations .90, .72, and .66 for Trait, Aggregate-State, and State Anxiety, respectively, further establishing the differential stability of each. There were no significant age differences in longitudinal stability or in within-occasion state-trait factor correlations.     

Predicting post-event processing in social anxiety disorder following two prototypical social situations: State variables and dispositional determinants

This study investigated self-reported state (anxiety, physical symptoms, cognitions, internally focused attention, safety behaviors, social performance) and trait (social anxiety, depressive symptoms, dysfunctional self-consciousness) predictors of post-event processing (PEP) subsequent to two social situations (interaction, speech) in participants with a primary diagnosis of social anxiety disorder (SAD) and healthy controls (HC). The speech triggered significantly more intense PEP, especially in SAD. Regardless of the type of social situation, PEP was best predicted by situational anxiety and dysfunctional cognitions among the state variables. If only trait variables were considered, PEP following both situations was accounted for by trait social anxiety. In addition, dysfunctional self-consciousness contributed to PEP-speech. If state and trait variables were jointly considered, for both situations, situational anxiety and dysfunctional cognitions were confirmed as the most powerful PEP predictors above and beyond trait social anxiety (interaction) and dysfunctional self-consciousness (speech). Hence, PEP as assessed on the day after a social situation seems to be mainly determined by state variables. Trait social anxiety and dysfunctional self-consciousness also significantly contribute to PEP depending on the type of social situation. The present findings support dysfunctional cognitions as a core cognitive mechanism for the maintenance of SAD. Implications for treatment are discussed.     

A latent state-trait anxiety model and its application to determine consistency and specificity coefficients

Abstract

In the present study the consistency model (Steyer, 1987) was applied to data gathered with the German version of the State-Trait Anxiety Inventory (Laux, Glanzmann, Schaffner, and Spielberger, 1981). The questionnaire was presented twice to 64 university students with an interval of two months between first and second testing. The consistency and specificity coefficients, estimated by LISREL (Jöreskog and Sörbom, 1984), support the state-trait distinction. The state variables have high specificity and consistency coefficients; the trait variables, in contrast, have high consistency coefficients but low or even negligible specificity coefficients. The discussion points out the advantages of the consistency model over the stability model; the most important advantage is that the theoretical structure of the consistency model is more appropriate for the type of application considered. It contains a state factor for each occasion of measurement and a trait factor common to all occasions of measurement. In the stability model, only latent states, but no latent traits occur. Consistency, specificity, and reliability can be identified as proportions of variance determined by latent variables specified in the model. Therefore, data analysis provides statistics concerning the practical significance of the trait and of the effects of situations and/or interactions.