Depressive symptomatology in older adults treated with behavioral activation: A network perspective.

BACKGROUND: Late-life depression is a serious mental health problem. Behavioral Activation (BA) is an effective, accessible psychotherapeutic treatment for older adults. However, little is known about which symptoms decrease and how associations between depressive symptoms change during BA treatment. METHODS: Using data from a cluster-randomized trial for older adults with late-life depression, we estimated a partial correlation network and a relative importance network of depressive symptoms before and after 8 weeks of BA treatment in primary care (n = 96). Networks were examined with measures of network structure, connectivity, centrality as well as stability. RESULTS: The most central symptoms at baseline and post-treatment were anhedonia, fatigue, and feeling depressed. In contrast, sleeping problems had the lowest centrality. The post-treatment network was significantly more interconnected than at baseline. Moreover, all symptoms were significantly more central at post-treatment. CONCLUSION: Our findings highlight the utility of the network approach to better understand symptom networks of depressed older adults before and after BA treatment. Results show that network connectivity and centrality of all symptoms increased after treatment. Future studies should investigate longitudinal idiographic networks to explore symptom dynamics within individuals over time.

Age related differences in symptom networks of overall psychological functioning in a sample of patients diagnosed with anxiety, obsessive compulsive disorder, or posttraumatic stress disorder.

Anxiety disorders, obsessive compulsive disorder (OCD), and posttraumatic stress disorder (PTSD) are among the most prevalent mental disorders across the lifespan. Yet, it has been suggested that there are phenomenological differences and differences in treatment outcomes between younger and older adults. There is, however, no consensus about the age that differentiates younger adults from older adults. As such, studies use different cut-off ages that are not well founded theoretically nor empirically. Network tree analysis was used to identify at what age adults differed in their symptom network of psychological functioning in a sample of Dutch patients diagnosed with anxiety disorders, OCD, or PTSD (N = 27,386). The networktree algorithm found a first optimal split at age 30 and a second split at age 50. Results suggest that differences in symptom networks emerge around 30 and 50 years of age, but that the core symptoms related to anxiety remain stable across age. If our results will be replicated in future studies, our study may suggest using the age split of 30 or 50 years in studies that aim to investigate differences across the lifespan. In addition, our study may suggest that age-related central symptoms are an important focus during treatment monitoring.

Anhedonia as a transdiagnostic symptom across psychological disorders: a network approach.

BACKGROUND: Anhedonia is apparent in different mental disorders and is suggested to be related to dysfunctions in the reward system and/or affect regulation. It may hence be a common underlying feature associated with symptom severity of mental disorders. METHODS: We constructed a cross-sectional graphical Least Absolute Shrinkage and Selection Operator (LASSO) network and a relative importance network to estimate the relationships between anhedonia severity and the severity of symptom clusters of major depressive disorder (MDD), anxiety sensitivity (AS), attention-deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD) in a sample of Dutch adult psychiatric patients (N = 557). RESULTS: Both these networks revealed anhedonia severity and depression symptom severity as central to the network. Results suggest that anhedonia severity may be predictive of the severity of symptom clusters of MDD, AS, ADHD, and ASD. MDD symptom severity may be predictive of AS and ADHD symptom severity. CONCLUSIONS: The results suggest that anhedonia may serve as a common underlying transdiagnostic psychopathology feature, predictive of the severity of symptom clusters of depression, AS, ADHD, and ASD. Thus, anhedonia may be associated with the high comorbidity between these symptom clusters and disorders. If our results will be replicated in future studies, it is recommended for clinicians to be more vigilant about screening for anhedonia and/or depression severity in individuals diagnosed with an anxiety disorder, ADHD and/or ASD.

A Network Analysis of DSM-5 Posttraumatic Stress Disorder Symptoms and Event Centrality.

The centrality of a traumatic event to one's autobiographical memory has been associated with posttraumatic stress disorder (PTSD) symptom severity. In the present study, we investigated the associations between specific features of event centrality (EC), as measured using the Centrality of Event Scale, and specific symptoms of PTSD. We computed a cross-sectional graphical lasso network of PTSD symptoms and specific features of EC in a sample of trauma-exposed individuals (n = 451), many of whom met the clinical threshold for a PTSD diagnosis. The graphical lasso revealed intrusive memories, negative trauma-related feelings, and the perception that the traumatic event was central to one's identity to be influential nodes. Viewing the future through the lens of one's trauma exposure was the EC feature most strongly linked to PTSD. Among all PTSD symptoms, blaming oneself or others for the traumatic event showed the strongest link to EC. The network was stable, allowing for reliable interpretations. Future longitudinal research is needed to clarify the associations among EC features and PTSD symptoms over time.