Katherine J. W. Baucom

Depressive symptoms, daily stress, and adherence in late adolescents with type 1 diabetes

OBJECTIVE To examine whether depressive symptoms are associated with greater perceived daily stress and moderate the link between stress severity and poorer daily adherence in late adolescents with Type 1 diabetes (T1D). METHOD 175 late adolescents with T1D completed measures of depressive symptoms and glycemic control during a baseline laboratory assessment. This assessment was followed by a 14-day daily diary during which adolescents rated the severity of general (GS) and diabetes-specific (DSS) stressful events, as well as adherence to their diabetes regimen. RESULTS Multilevel modeling revealed that adolescents with more depressive symptoms reported more severe daily stress and poorer daily adherence on average, and had poorer glycemic control. On days with more severe DSS, but not GS, adolescents reported poorer adherence. This association was moderated by an interaction between depressive symptoms and the mean level of DSS severity experienced across the 2-week diary. In adolescents with low levels of depressive symptoms, poorer adherence was reported on days with more severe DSS across all levels of mean DSS severity. In adolescents with average or high levels of depressive symptoms, poorer adherence was reported on days with more severe DSS only when mean DSS severity was average or high. CONCLUSIONS Depressive symptoms are associated with poorer daily adherence and greater stress severity, and interact with mean DSS severity to moderate the link between daily stress and adherence. The results point to the importance of depressive symptoms for understanding associations between stress and adherence during late adolescence.

Treating Comorbid Social Anxiety and Major Depression: The Challenge of Diagnostic Overshadowing

Depression and social anxiety disorder (SAD) are two of the most common mental health conditions, and often occur together. Depression is usually identified as the presenting problem, which may result in SAD being overshadowed and undertreated among those with this particular comorbidity. In this case study, diagnostic overshadowing results in successful treatment of depression but delayed identification of SAD, causing an attenuated anxiety treatment response. We present recommendations on how clinicians may more thoroughly assess for comorbid Axis I diagnoses, avoid diagnostic overshadowing, and better integrate treatment approaches for SAD–major depressive disorder (MDD) comorbidity. Mechanisms underlying cognitive-behavioral treatments such as behavioral activation and exposure hold particular promise for promoting improvement in SAD and major depression simultaneously.

Do the naïve know best? The predictive power of naïve ratings of couple interactions.

We examined the utility of naïve ratings of communication patterns and relationship quality in a large sample of distressed couples. Untrained raters assessed 10-min videotaped interactions from 134 distressed couples who participated in both problem-solving and social support discussions at each of 3 time points (pre-therapy, post-therapy, and 2-year follow-up) during a randomized clinical trial of behavioral couple therapy. Teams of naïve raters observed a particular type of discussion from the 3 time points at a single sitting in a random order and rated dyadic interaction patterns (negative reciprocity, positive reciprocity, wife demand/husband withdraw, husband demand/wife withdraw, and mutual avoidance) and the overall relationship quality of couples. These naïve ratings were strongly and consistently associated with both levels of, and changes in, trained observational codes and self-reported relationship satisfaction. Naïve ratings of couples accounted for similar--and at times superior--amounts of variance in both concurrent relationship satisfaction and divorce at 5-year follow-up when compared with trained ratings. These findings offer compelling support for the use of naïve raters in research with couples and also suggest important future directions that are applicable to both research and practice with distressed couples.

Graphic methods for interpreting longitudinal dyadic patterns from repeated-measures actor–partner interdependence models.

Researchers commonly use repeated-measures actor–partner interdependence models (RM-APIM) to understand how romantic partners change in relation to one another over time. However, traditional interpretations of the results of these models do not fully or correctly capture the dyadic temporal patterns estimated in RM-APIM. Interpretation of results from these models largely focuses on the meaning of single-parameter estimates in isolation from all the others. However, considering individual coefficients separately impedes the understanding of how these associations combine to produce an interdependent pattern that emerges over time. Additionally, positive within-person, or actor, effects are commonly misinterpreted as indicating growth from one time point to the next when they actually represent decline. We suggest that change-as-outcome RM-APIMs and vector field diagrams (VFDs) can be used to improve the understanding and presentation of dyadic patterns of association described by standard RM-APIMs. The current article briefly reviews the conceptual foundations of RM-APIMs, demonstrates how change-as-outcome RM-APIMs and VFDs can aid interpretation of standard RM-APIMs, and provides a tutorial in making VFDs using multilevel modeling.

A multivariate dynamic systems model for psychotherapy with more than one client.

The dynamics of the give and take between therapist and client(s) is frequently of interest to therapy process researchers. Characterizing the ways that therapists respond to clients and clients respond to therapists can be challenging in therapeutic encounters involving a single therapist and a single client. The complexity of this challenge increases as the number of people involved in a therapeutic encounter increases not only because there are more people responding to one another but also because the patterns of responding can become more complex. This manuscript demonstrates how dyadic cross-lagged panel models can be extended to psychotherapeutic encounters involving 3 people and used to test processes that exist between dyadic subsets of the larger group as well as the group as one cohesive unit. Three hundred seventy-nine talk turns of fundamental frequency from a couple therapy session were modeled using 3 dyadic cross-lagged panel models, and each individual’s respiratory sinus arrhythmia (RSA) was treated as a moderator. Although the regression coefficients for each dyadic subset (e.g., therapist–husband) were nonsignificant, an eigenvalue/eigenvector decomposition of the regression coefficients from the 3 dyadic cross-lagged panel models suggests that interdependence exists at the level of the whole group (i.e., therapist–husband–wife) rather than between pairs of individuals within the group (e.g., husband–wife). Further, an interaction involving husband’s RSA suggested that interdependence involving the husband ceased when the husband displayed greater regulatory effort. This combination of statistical methods allows for clearly distinguishing between dyadic therapeutic processes and group-level therapeutic processes.

Depressive symptoms and diabetes management from late adolescence to emerging adulthood.

Objective: To examine changes in depressive symptoms as well as between- and within-person associations between depressive symptoms and Type 1 diabetes (T1D) management across the transition from late adolescence to emerging adulthood. Method: Beginning in the senior year of high school, 197 late adolescents with T1D (Mage = 17.77) reported on their student status and living situation, and completed self-report measures of depressive symptoms and adherence to the diabetes regimen, annually at 3 time points. Glycemic control was gathered from hemoglobin A1c (HbA1c) assay kits at the same time points. Results: Results of multilevel models demonstrated high depressive symptoms at baseline, with significant increases in depressive symptoms across time when participants were not living in their parental home, but no change when living with parents. Participants with higher mean levels of depressive symptoms relative to peers (between-person association) had poorer adherence and glycemic control (i.e., higher HbA1c) on average. Within-person fluctuations in depressive symptoms were significantly associated with adherence: greater increases in depressive symptoms (relative to adolescents’ own average) were associated with greater deteriorations in adherence. There was not a significant within-person effect of depressive symptoms on glycemic control. Conclusions: The transition from late adolescence to emerging adulthood is particularly challenging for those with T1D. The findings that individuals with greater depressive symptoms have poorer adherence and glycemic control relative to those with lower depressive symptoms, and that increases in depressive symptoms are associated with declines in adherence, highlight the importance of screening and monitoring depressive symptoms during this life transition.

Conceptual and statistical issues in couples observational research: Rationale and methods for design decisions.

Observational behavioral coding methods are widely used for the study of relational phenomena. There are numerous guidelines for the development and implementation of these methods that include principles for creating new and adapting existing coding systems as well as principles for creating coding teams. While these principles have been successfully implemented in research on relational phenomena, the ever expanding array of phenomena being investigated with observational methods calls for a similar expansion of these principles. Specifically, guidelines are needed for decisions that arise in current areas of emphasis in couple research including observational investigation of related outcomes (e.g., relationship distress and psychological symptoms), the study of change in behavior over time, and the study of group similarities and differences in the enactment and perception of behavior. This article describes conceptual and statistical considerations involved in these 3 areas of research and presents principle- and empirically based rationale for design decisions related to these issues. A unifying principle underlying these guidelines is the need for careful consideration of fit between theory, research questions, selection of coding systems, and creation of coding teams. Implications of (mis)fit for the advancement of theory are discussed.