Using Diary Methods to Study Marital and Family Processes.

Diary methods allow researchers to study marital and family processes within the context of daily life in a way that is not possible with more traditional methods. The authors review applications of diary designs in marital and family research and detail the types of research questions that can uniquely be asked of dyadic/family diary data. Technological developments for the use of electronic palm-top devices for implementing diary methods are also reviewed. Additionally, the authors discuss specific issues relevant to the analysis of diary data that come from dyads or families. Last, the authors raise unresolved issues and directions for future research in the use of diary methods for studying marital and family processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Using Multilevel Models to Analyze Couple and Family Treatment Data: Basic and Advanced Issues.

Couple and family treatment data present particular challenges to statistical analyses. Partners and family members tend to be more similar to one another than to other individuals, which raises interesting possibilities in the data analysis but also causes significant problems with classical, statistical methods. The present article presents multilevel models (also called hierarchical linear models, mixed-effects models, or random coefficient models) as a flexible analytic approach to couple and family longitudinal data. The article reviews basic properties of multilevel models but focuses primarily on 3 important extensions: missing data, power and sample size, and alternative representations of couple data. Information is presented as a tutorial, with a Web appendix providing datasets with SPSS and R code to reproduce the examples. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Narratives in and About Families: An Examination of Coding Schemes and a Guide for Family Researchers.

This article aims to provide the reader with a general overview of narrative methods as they apply to the study of family relationships. How narratives are collected and issues pertaining to training raters are considered. Scoring systems have been developed that code for thematic content, relative coherence, and co-constructive processes. Validity for these methods is examined through (a) concordance between narrative codes and directly observed behavior within similar domains, (b) links between narratives and self-report measures, and (c) the relation between narratives and psychological functioning. A guide for researchers in their consideration of adopting narrative methods is offered. The article concludes with a consideration of linking different coding schemes and challenges for future researchers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Observed classroom quality during teacher education and two years of professional practice.

The aims of the present study are to investigate whether and how teachers change in their observed classroom quality (emotional and instructional support, classroom organization, and students' engagement; measured with the Classroom Assessment Scoring System observation measure for secondary school [CLASS-S]; Pianta, La Paro, & Hamre, 2006) during their teacher education year and the first 2 years of professional practice, as well as the effects of personal characteristics and contextual factors on observed classroom quality. Confirmatory factor analyses (CFAs) with a reduced number of indicators per a priori construct fitted the data well. Using factor scores in 3-level multilevel models for change (376 lesson segments 20 min in duration nested within 10 time points, within 17 teachers), we found more variability over time than within lessons and the least variability between teachers. Emotional support showed an inverted U-shaped change over time, whereas classroom organization increased linearly over time. Emotional support was lower for older students, and students were more engaged in larger classes. A higher level of classroom organization during lessons was related to less variability in student engagement, but variability of instructional support was unrelated to variability of student engagement within each lesson. The findings are discussed within the context of teachers' supported transitions into professional practice. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling heterogeneity in social interaction processes using multilevel survival analysis.

More than 15 years ago, survival or hazard regression analyses were introduced to psychology (W. Gardner & W. A. Griffin, 1989; W. A. Griffin & W. Gardner, 1989) as powerful methodological tools for studying real time social interaction processes among dyads. Almost no additional published applications have appeared, although such data are commonly collected and the applicable questions are central to many important theoretical perspectives. To revisit the basic methods, the authors use an example from emotion regulation theory in which the level of child antisocial behavior is hypothesized to be positively associated with the hazard rate of angry emotions and negatively associated with sad, fearful emotions in the face of parental negative behavior (scolding). The authors discuss the limitations of traditional approaches to the analysis of social interaction and demonstrate improvements in the ability to model individual differences now available in existing software. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Current and Recollected Perceptions of Family Relationships: The Social Relations Model Approach Applied to Members of Three Generations.

Data from 81 three-generation families (comprising 567 participants) were analyzed to assess perceptions of current-family and family-of-origin relationships. The dimensions studied (Restrictiveness, Justice, Affection, and Trust) were derived from the family systems theories as developed by Boszormenyi-Nagy (I. Boszormenyi-Nagy & B. R. Krasner, 1986; I. Boszormenyi-Nagy & G. Spark, 1984; I. Boszormenyi-Nagy & D. N. Ulrich, 1981) and Stierlin (H. Stierlin, 1974, 1978; H. Stierlin, I. Rucker-Embden, N. Wetzel, & M. Wirsching, 1980). The social relations model (SRM) was used to disentangle the perception scores into characteristics of the perceiver (actor component), the target (partner component), and the family as a whole. For both current-family and family-of-origin relationships, significant variances of actor as well as family components were found. Empirical evidence for an association between current-family and (mother's) family-of-origin components was only found on the dimension of Restrictiveness. Clear differences were found between the means of current-family and family-of-origin perceptions, which could be explained by differences between current and past SRM components. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mixed-effects logistic regression for estimating transitional probabilities in sequentially coded observational data.

This article demonstrates the use of mixed-effects logistic regression (MLR) for conducting sequential analyses of binary observational data. MLR is a special case of the mixed-effects logit modeling framework, which may be applied to multicategorical observational data. The MLR approach is motivated in part by G. A. Dagne, G. W. Howe, C. H. Brown, & B. O. Muthén (2002) advances in general linear mixed models for sequential analyses of observational data in the form of contingency table frequency counts. The advantage of the MLR approach is that it circumvents obstacles in the estimation of random sampling error encountered using Dagne and colleagues' approach. This article demonstrates the MLR model in an analysis of observed sequences of communication in a sample of young adult same-sex peer dyads. The results obtained using MLR are compared with those of a parallel analysis using Dagne and colleagues' linear mixed model for binary observational data in the form of log odds ratios. Similarities and differences between the results of the 2 approaches are discussed. Implications for the use of linear mixed models versus mixed-effects logit models for sequential analyses are considered. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Adult Attachment and Marital Interaction as Predictors of Whole Family Interactions During the Transition to Parenthood.

This study examined the role of parental adult attachment and couples' prenatal and postnatal marital interactions in predicting the quality of family interactions 24 months after the birth of the couple's first child. Father's prenatal marital withdrawal and mother's postnatal marital withdrawal were associated with less adaptive family interactions at 24 months. Families with fathers who had an insecure attachment, as assessed by the Adult Attachment Interview, showed less positive and more negative interactions at 24 months, but only when there were higher levels of negative escalation in the couple's marriage prenatally. Findings are discussed in terms of the importance of exploring the transition to parenthood at the broader family level. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A social relations model of observed family negativity and positivity using a genetically informative sample.

The goal of this study was to investigate individual and relationship influences on expressions of negativity and positivity in families. Parents and adolescents were observed in a round-robin design in a sample of 687 families. Data were analyzed using a multilevel social relations model. In addition, genetic contributions were estimated for actor effects. Children showed higher mean levels of negativity and lower mean levels of positivity as actors than did parents. Mothers were found to express and elicit higher mean levels of positivity and negativity than fathers. Actor effects were much stronger than partner effects, accounting for between 18%–39% of the variance depending on the actor and the outcome. Genetic (35%) and shared environmental (19%) influences explained a substantial proportion of the actor effect variance for negativity. Dyadic reciprocities were lowest in dyads with a high power differential (i.e., parent–child dyads) and highest for dyads with equal power (sibling and marital dyads). (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

A Multiple-Goal, Multilevel Model of Feedback Effects on the Regulation of Individual and Team Performance.

When working as a member of a team, individuals must make decisions concerning the allocation of resources (e.g., effort) toward individual goals and team goals. As a result, individual and team goals, and feedback related to progress toward these goals, should be potent levers for affecting resource allocation decisions. This research develops a multilevel, multiple-goal model of individual and team regulatory processes that affect the allocation of resources across individual and team goals resulting in individual and team performance. On the basis of this model, predictions concerning the impact of individual and team performance feedback are examined empirically to evaluate the model and to understand the influence of feedback on regulatory processes and resource allocation. Two hundred thirty-seven participants were randomly formed into 79 teams of 3 that performed a simulated radar task that required teamwork. Results support the model and the predicted role of feedback in affecting the allocation of resources when individuals strive to accomplish both individual and team goals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Interpersonal Process Model of Intimacy in Marriage: A Daily-Diary and Multilevel Modeling Approach.

This study used daily reports of interactions in marriage to examine predictions from the conceptualization of intimacy as the outcome of an interpersonal process. Both partners of 96 married couples completed daily diaries assessing self-disclosure, partner disclosure, perceived partner responsiveness, and intimacy on each of 42 consecutive days. Multivariate multilevel modeling revealed that self-disclosure and partner disclosure both significantly and uniquely contributed to the contemporaneous prediction of intimacy. Perceived partner responsiveness partially mediated the effects of self-disclosure and partner disclosure on intimacy. Global marital satisfaction, relationship intimacy, and demand-withdraw communication were related to daily levels of intimacy. Implications for the importance of perceived partner responsiveness in the intimacy process for married partners are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Is It Beneficial to Involve a Family Member? A Meta-Analysis of Psychosocial Interventions for Chronic Illness.

Links between chronic illness and family relationships have led to psychosocial interventions targeted at the patient's closest family member or both patient and family member. The authors conducted a meta-analytic review of randomized studies comparing these interventions with usual medical care (k=70), focusing on patient outcomes (depression, anxiety, relationship satisfaction, disability, and mortality) and family member outcomes (depression, anxiety, relationship satisfaction, and caregiving burden). Among patients, interventions had positive effects on depression when the spouse was included and, in some cases, on mortality. Among family members, positive effects were found for caregiving burden, depression, and anxiety; these effects were strongest for nondementing illnesses and for interventions that targeted only the family member and that addressed relationship issues. Although statistically significant aggregate effects were found, they were generally small in magnitude. These findings provide guidance in developing future interventions in this area. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Beyond Significance Testing: Reforming Data Analysis Methods in Behavioral Research.

Reviews Kline's book (see record 2004-13019-000) which reviews the controversy regarding significance testing, offers methods for effect size and confidence interval estimation, and suggests some alternative methodologies. Whether or not one accepts Kline's view of the future of statistical significance testing, there is much of value in this book. As a textbook, it could serve as a reference for an upper level undergraduate course but it would be more appropriate for a graduate course. The book is a thought-provoking examination of the uneasy alliance between null hypothesis significance testing, and effect size and confidence interval estimation. There is much in this book for those on both sides of the null hypothesis testing debate and for those unsure where they stand. Whatever the future holds, Kline has done well in illustrating recent advances to statistical decision-making. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Integrative Borderline Adolescent Family Therapy: Meeting the Challenges of Treating Adolescents With Borderline Personality Disorder.

With the growing acceptance of the borderline personality disorder diagnosis for adolescents has come a need for specialized treatments for this challenging population. Further, because of the prominence of the family system during early and later adolescence, family treatments are particularly needed. The purpose of this article is to present the integrative borderline adolescent family therapy (I-BAFT) model that emerged from a National Institute on Drug Abuse-funded (Stage 1) treatment development and enhancement effort. I-BAFT integrates (a) key interventions from the family treatment of adolescent drug abuse (D. A. Santisteban et al., 2003; J. Szapocznik & W. Kurtines, 1989), (b) skills training shown effective with adults with borderline personality disorder (M. Linehan, 1993a) and adapted for adolescents, and (c) individual treatment interventions that promote motivation for treatment and enhance the integration of the 3 treatment components. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Family and individual difference predictors of trait aspects of negative interpersonal behaviors during emerging adulthood.

A latent trait-state-occasion (TSO) model (D. A. Cole, N. C. Martin, & J. H. Steiger, 2005) was used to isolate the trait and state components of negative interpersonal behaviors toward a friend or romantic partner during emerging adulthood. Results indicate that variance in negative interpersonal behaviors was due to nearly equal portions of Trait and Occasion factors. Variability in the trait aspects of negative interpersonal behaviors was then predicted by theoretically relevant constructs. In particular, mothers' negative behaviors during adolescence, adolescent core self-evaluations, negative emotionality, and feelings of security in close relationships had independent effects in predicting the enduring aspects of negative interpersonal behaviors. All told, these results indicate that TSO models can be helpful tools for understanding the developmental antecedents of the trait-like aspects of interpersonal processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An array of qualitative data analysis tools: A call for data analysis triangulation.

One of the most important steps in the qualitative research process is analysis of data. The purpose of this article is to provide elements for understanding multiple types of qualitative data analysis techniques available and the importance of utilizing more than one type of analysis, thus utilizing data analysis triangulation, in order to understand phenomenon more fully for school psychology research and beyond. The authors describe seven qualitative analysis tools: methods of constant comparison, keywords-in-context, word count, classical content analysis, domain analysis, taxonomic analysis, and componential analysis. Then, the authors outline when to use each type of analysis. In so doing, the authors use real qualitative data to help distinguish the various types of analyses. Furthermore, flowcharts and tables are provided to help delineate when to choose each type of analysis. Finally, the role of computer-assisted software in the qualitative data-analytic process is discussed. As such, use of the analyses outlined in this article should help to promote rigor in qualitative research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluating model fit for growth curve models: Integration of fit indices from SEM and MLM frameworks.

Evaluating overall model fit for growth curve models involves 3 challenging issues. (a) Three types of longitudinal data with different implications for model fit may be distinguished: balanced on time with complete data, balanced on time with data missing at random, and unbalanced on time. (b) Traditional work on fit from the structural equation modeling (SEM) perspective has focused only on the covariance structure, but growth curve models have four potential sources of misspecification: within-individual covariance matrix, between-individuals covariance matrix, marginal mean structure, and conditional mean structure. (c) Growth curve models can be estimated in both the SEM and multilevel modeling (MLM) frameworks; these have different emphases for the evaluation of model fit. In this article, the authors discuss the challenges presented by these 3 issues in the calculation and interpretation of SEM- and MLM-based fit indices for growth curve models and conclude by identifying some lines for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Meta-Analytic Methods of Pooling Correlation Matrices for Structural Equation Modeling Under Different Patterns of Missing Data.

Three methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under different degrees and mechanisms of missingness were compared for the estimation of correlation and SEM parameters and goodness-of-fit indices by using Monte Carlo simulation techniques. A revised generalized least squares (GLS) method for synthesizing correlations, weighted-covariance GLS (W-COV GLS), was compared with univariate weighting with untransformed correlations (univariate r) and univariate weighting with Fisher's z-transformed correlations (univariate z). These 3 methods were crossed with listwise and pairwise deletion. Univariate z and W-COV GLS performed similarly, with W-COV GLS providing slightly better estimation of parameters and more correct model rejection rates. Missing not at random data produced high levels of relative bias in correlation and model parameter estimates and higher incorrect SEM model rejection rates. Pairwise deletion resulted in inflated standard errors for all synthesis methods and higher incorrect rejection rates for the SEM model with univariate weighting procedures. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An Empirical Evaluation of Alternative Methods of Estimation for Confirmatory Factor Analysis With Ordinal Data.

Confirmatory factor analysis (CFA) is widely used for examining hypothesized relations among ordinal variables (e.g., Likert-type items). A theoretically appropriate method fits the CFA model to polychoric correlations using either weighted least squares (WLS) or robust WLS. Importantly, this approach assumes that a continuous, normal latent process determines each observed variable. The extent to which violations of this assumption undermine CFA estimation is not well-known. In this article, the authors empirically study this issue using a computer simulation study. The results suggest that estimation of polychoric correlations is robust to modest violations of underlying normality. Further, WLS performed adequately only at the largest sample size but led to substantial estimation difficulties with smaller samples. Finally, robust WLS performed well across all conditions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)