Treatment-associated network dynamics in patients with globus sensations: a proof-of-concept study.

In this proof-of-concept study, we used a systems perspective to conceptualize and investigate treatment-related dynamics (temporal and cross-sectional associations) of symptoms and elements related to the manifestation of a common functional somatic syndrome (FSS), Globus Sensations (GS). We analyzed data from 100 patients (M = 47.1 years, SD = 14.4 years; 64% female) with GS who received eight sessions of group psychotherapy in the context of a randomized controlled trial (RCT). Symptoms and elements were assessed after each treatment session. We applied a multilevel graphical vector-autoregression (ml GVAR) model approach resulting in three separate, complementary networks (temporal, contemporaneous, and between-subject) for an affective, cognitive, and behavioral dimension, respectively. GS were not temporally associated with any affective, cognitive, and behavioral elements. Temporally, catastrophizing cognitions predicted bodily weakness (r = 0.14, p < 0.01, 95% confidence interval (CI) [0.04-0.23]) and GS predicted somatic distress (r = 0.18, p < 0.05, 95% CI [0.04-0.33]). Potential causal pathways between catastrophizing cognitions and bodily weakness as well as GS and somatic distress may reflect treatment-related temporal change processes in patients with GS. Our study illustrates how dynamic NA can be used in the context of outcome research.

Transdiagnostic symptom networks in relation to mental health service use in community youth.

OBJECTIVE: The objective of this study is to scrutinize whether psychopathology symptom networks differ between those with and without lifetime: treatment seeking, treatment and treatment of longer duration. METHODS: We created non-exclusive groups of subjects with versus without lifetime treatment seeking, treatment and treatment of mid-long-term duration. We estimated Ising models and carried out network comparison tests (NCTs) to compare (a) overall connectivity and (b) network structure. Furthermore, we examined node strength. We used propensity score matching (PSM) to minimize potential confounding by indication for service use. RESULTS: Based on data from 9,172 participants, there were no statistically significant differences in overall connectivity and network structure in those with versus without lifetime: treatment seeking (p = .75 and p = .82, respectively), treatment (p = .63 and p = .49, respectively) and treatment of mid-longterm duration (p = .15 and p = .62, respectively). Notably, comparing networks with versus without service use consistently revealed higher node strength in 'obsessions' and 'aggression' and lower node strength in 'elevated mood' in all networks with service use. CONCLUSIONS: Findings suggest that after adjusting for potential confounding by indication for service use, there was no indication of an association in overall connectivity or network structure for lifetime treatment seeking, treatment and treatment of longer duration. However, selected structurally important symptoms differed consistently in all three comparisons. Our findings highlight the potential of network analysis methods to examine treatment mechanisms and outcomes. Specifically, more granular network characteristics on the node level may complement and enrich traditional outcomes in clinical research.

Multimorbidity networks of mental disorder symptom domains across psychopathology severity levels in community youth.

Our aim was to scrutinize multimorbidity in a community sample of youths (Philadelphia Neurodevelopmental Cohort) in form of co-occurrences of DSM-IV disorder symptom domains, elucidating if and when specific symptom domain interrelations emerge as mental disorder severity levels increase. We estimated four multimorbidity networks based on four severity cut-offs ('at least symptomatic', 'at least subthreshold', 'at least threshold', and 'impaired') and compared them pairwise on two measures: global network strength and network structure. We further computed community clusters for each network to detect symptom domain interrelations. Pairwise comparisons of the multimorbidity networks based on data from 9410 probands showed significant differences in global strength of the networks with the two highest severity cut-offs ('impaired' and 'at least threshold') with the at least symptomatic networks (p < .05). The networks with the three highest severity cut-offs ('impaired', 'at least threshold', and 'at least subthreshold') differed significantly (p < .001) from the at least symptomatic network regarding global network structure but did not significantly differ from each other (p > .05). We identified four common clusters in the impaired, at least threshold, and at least subthreshold networks consisting of i) domains associated with behavioral disorders; ii) domains associated with anxiety disorders (agoraphobia, social anxiety and specific phobia); iii) domains associated with anxiety/mood/eating and; iv) domains associated with mood/eating disorders. We found that major mental disorder symptom domain interrelations become consistent from a subthreshold level onwards. Findings suggest that specific multimorbidity patterns emerge as psychopathology severity levels increase.