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Previous empirical studies show that stress occurring outside of the relationship (referred to as external stress) can spill over into couples' relationships, influencing dyads' behaviors and their relationship satisfaction. There is substantial evidence that the association between external stress and relationship satisfaction is explained by 2 mediators: internal stress and dyadic coping. However, the mediation processes of internal stress and dyadic coping have solely been examined in Western couples. Accordingly, the current study aimed to test these processes in a sample of 474 Chinese couples (N = 948) using the actor-partner interdependence mediation model. Results reveal that internal stress and dyadic coping can fully mediate the association between external stress and relationship satisfaction in Chinese couples for men and women in a similar way. These findings underscore the importance of moving beyond examining stress and dyadic coping processes among couples in Eastern cultures. [ABSTRACT FROM AUTHOR]

How parents cope with stress as a couple (i.e., dyadic coping [DC]) is related to mental health problems in children. But little is known about DC within first-time parents and child mental health problems in early childhood. This study investigated subgroups in DC trajectories across the transition to parenthood (TTP) and examined subgroup differences in child mental health problems. Mothers' and fathers' self-report of positive and negative DC (n = 288 couples) at seven points of measurement (27th, 32nd week of pregnancy, 2nd, 14th, 40th week postpartum, 3- and 4-year postpartum) and children's emotional and behavioral problems from parent report (4-year postpartum) were used. Latent class growth analyses revealed that over half of the couples experienced a moderate decline in positive DC across the TTP (58%), whereas only fathers reported a decline among the remaining couples (42%). Fathers with a partner who maintained their level of positive DC reported more child emotional and behavioral problems than fathers whose partners' DC also decreased. Results for negative DC indicated two subgroups in which one partner maintained their initial level of negative DC (stable fathers: 10%, stable mothers: 23%), while the other increased. In most couples, both parents increased their negative DC (67%). Fathers reported more child emotional and behavioral problems if their negative DC increased across the TTP than if their negative DC remained stable regardless of the negative DC of their partner. The existence of different DC trajectory patterns needs to be considered in further research as well as prevention. [ABSTRACT FROM AUTHOR]

Rationale: Couples share distress as well as potential personal growth (PG) after a cancer diagnosis. It is essential for professionals to learn more about the ways couples cope together with adversity. Dyadic results may help to understand controversial results in the PG literature and inform clinicians in optimizing psychological support for couples., Objective: We examine the temporal and dyadic development of PG among patients and their intimate partners. In addition, life threat is examined as a potential factor influencing PG after cancer diagnosis., Methods: We assessed PG using the Personal Growth Inventory in a clinically representative, mixed-type and mixed-stage cancer cohort (N = 154 couples) 6 and 12 months after cancer diagnosis. Medical data on cancer diagnoses and treatments were collected from physicians. Actor-partner interdependence models were applied., Results: PG was reported by patients and their partners. Women (either as patients or partners) reported more PG than male patients or partners. PG remained relatively stable over 6 months and was related to whether the patient was receiving curative or palliative treatment. Female patients experienced less PG 6 months after the cancer diagnosis and if treatment was curative. Male patients experienced less PG if their partners experienced PG, and the treatment was curative., Conclusions: Dyadic growth is a phenomenon not limited to breast cancer or female patient couples and may represent a form of dyadic coping. Patients and partners seem to develop individual and dyadic growth, depending on a combination of gender and life threat. Psycho-oncology services may want to promote both couple level coping and support in order to optimize cancer care.

Background: We investigated the psychometric properties of a short questionnaire for combined assessment of different perceived stress management skills in the general population and tested whether scores relate to physiological stress reactivity., Methods: For psychometric evaluation, we determined the factor structure of the questionnaire and investigated its measurement invariance in the participant groups and over time in three different independent samples representing the general population (total N=332). Reliability was tested by estimating test-retest reliability, internal consistency, and item reliabilities. We examined convergent and criterion validity using selected criterion variables. For endocrine validation, 35 healthy non-smoking and medication-free men in a laboratory study and 35 male and female employees in a workplace study underwent an acute standardized psychosocial stress task. We assessed stress management skills and measured salivary cortisol before and several times up to 60 min (workplace study) and 120 min (laboratory study) after stress. Potential confounders were controlled., Results: The factor structure of the questionnaire consists of five scales reflecting acceptably distinct stress management skills such as cognitive strategies, use of social support, relaxation strategies, anger regulation, and perception of bodily tension. This factor structure was stable across participant groups and over time. Internal consistencies, item reliabilities, and test-retest reliabilities met established statistical requirements. Convergent and criterion validity were also established. In both endocrine validation studies, higher stress management skills were independently associated with lower cortisol stress reactivity (p's<.029)., Conclusions: Our findings suggest that the questionnaire has good psychometric properties and that it relates to subjective psychological and objective physiological stress indicators. Therefore, the instrument seems a suitable measure for differential assessment of stress management skills in the general population., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

The authors show how structural equation modeling can be applied to analyze change in longitudinal multitrait-multimethod (MTMM) studies. For this purpose, an extension of latent difference models (McArdle, 1988; Steyer, Eid, & Schwenkmezger, 1997) to multiple constructs and multiple methods is presented. The model allows investigators to separate true change from measurement error and to analyze change simultaneously for different methods. The authors also show how Campbell and Fiske's (1959) guidelines for analyzing convergent and discriminant validity can be applied to the measurement of latent change. The practical application of the multimethod change model is illustrated in a reanalysis of child depression and anxiety scores (N = 906 American children) that were assessed by self- and parent reports on three measurement occasions. The analyses revealed that (a) the convergent validity of change was low for both constructs and (b) sex was a significant predictor of self-reported, but not of parent reported, anxiety states. Finally, the authors discuss advantages and limitations and compare the model with other approaches for analyzing longitudinal MTMM data., (Copyright 2009 APA, all rights reserved.)

The question as to which structural equation model should be selected when multitrait-multimethod (MTMM) data are analyzed is of interest to many researchers. In the past, attempts to find a well-fitting model have often been data-driven and highly arbitrary. In the present article, the authors argue that the measurement design (type of methods used) should guide the choice of the statistical model to analyze the data. In this respect, the authors distinguish between (a) interchangeable methods, (b) structurally different methods, and (c) the combination of both kinds of methods. The authors present an appropriate model for each type of method. All models allow separating measurement error from trait influences and trait-specific method effects. With respect to interchangeable methods, a multilevel confirmatory factor model is presented. For structurally different methods, the correlated trait-correlated (method-1) model is recommended. Finally, the authors demonstrate how to appropriately analyze data from MTMM designs that simultaneously use interchangeable and structurally different methods. All models are applied to empirical data to illustrate their proper use. Some implications and guidelines for modeling MTMM data are discussed., (Copyright (c) 2008 APA, all rights reserved.)

The analysis of convergent and discriminant validity is an integral part of the construct validation process. Models for analyzing the convergent and discriminant validity have typically been developed for cross-sectional data. There exist, however, only a few approaches for longitudinal data that can be applied for analyzing the construct validity of fluctuating states. In this article, the authors show how models of latent state-trait theory can be combined with models of multitrait-multimethod analysis to develop a model that allows for analyzing convergent and discriminant validity in time: the multimethod latent state-trait model. The model allows for identifying different sources of variance (trait consistency, trait-method specificity, occasion-specific consistency, occasion-specific method specificity, and unreliability). It is applied to the repeated measurement of depression and anxiety in children, which was assessed by self and teacher reports (N = 375). The application shows that the proposed models fit the data well and allow a deeper understanding of method effects in clinical assessment., ((c) 2008 APA, all rights reserved.)

In a recent article, A. Maydeu-Olivares and D. L. Coffman (2006) presented a random intercept factor approach for modeling idiosyncratic response styles in questionnaire data and compared this approach with competing confirmatory factor analysis models. Among the competing models was the CT-C(M-1) model (M. Eid, 2000). In an application to the Life Orientation Test (M. F. Scheier & C. S. Carver, 1985), Maydeu-Olivares and Coffman found that results obtained from the CT-C(M-1) model were difficult to interpret. In particular, Maydeu-Olivares and Coffman challenged the asymmetry of the CT-C(M-1) model. In the present article, the authors show that the difficulties faced by Maydeu-Olivares and Coffman rest upon an improper interpretation of the meaning of the latent factors. The authors' aim is to clarify the meaning of the latent variables in the CT-C(M-1) model. The authors explain how to properly interpret the results from this model and introduce an alternative restricted model that is conceptually similar to the CT-C(M-1) model and nested within it. The fit of this model is invariant across different reference methods. Finally, the authors provide guidelines as to which model should be used in which research context.

Extensions of latent state-trait models for continuous observed variables to mixture latent state-trait models with and without covariates of change are presented that can separate individuals differing in their occasion-specific variability. An empirical application to the repeated measurement of mood states (N=501) revealed that a model with 2 latent classes fits the data well. The larger class (76%) consists of individuals whose mood is highly variable, whose general well-being is comparatively lower, and whose mood variability is influenced by daily hassles and uplifts. The smaller class (24%) represents individuals who are rather stable and happier and whose mood is influenced only by daily uplifts but not by daily hassles. A simulation study on the model without covariates with 5 sets of sample sizes and 5 sets of number of occasions revealed that the appropriateness of the parameter estimates of this model depends on number of observations (the higher the better) and number of occasions (the higher the better). Another simulation study estimated Type I and II errors of the Lo-Mendell-Rubin test., ((c) 2007 APA, all rights reserved.)