BackgroundChildhood adversity (CA) is strongly associated with mental health problems. Resilience factors (RFs) reduce mental health problems following CA. Yet, knowledge on the nature of RFs is... Show moreBackgroundChildhood adversity (CA) is strongly associated with mental health problems. Resilience factors (RFs) reduce mental health problems following CA. Yet, knowledge on the nature of RFs is scarce. Therefore, we examined RF mean levels, RF interrelations, RF-distress pathways, and their changes between early (age 14) and later adolescence (age 17).MethodsWe studied 10 empirically supported RFs in adolescents with (CA+; n = 631) and without CA (CA−; n = 499), using network psychometrics.ResultsAll inter-personal RFs (e.g. friendships) showed stable mean levels between age 14 and 17, and three of seven intra-personal RFs (e.g. distress tolerance) changed in a similar manner in the two groups. The CA+ group had lower RFs and higher distress at both ages. Thus, CA does not seem to inhibit RF changes, but to increase the risk of persistently lower RFs. At age 14, but not 17, the RF network of the CA+ group was less positively connected, suggesting that RFs are less likely to enhance each other than in the CA− group. Those findings underpin the notion that CA has a predominantly strong proximal effect. RF-distress pathways did not differ in strength between the CA+ and the CA− group, which suggests that RFs have a similarly protective strength in the two groups. Yet, as RFs are lower and distress is higher, RF-distress pathways may overall be less advantageous in the CA+ group. Most RF interrelations and RF-distress pathways were stable between age 14 and 17, which may help explain why exposure to CA is frequently found to have a lasting impact on mental health.ConclusionsOur findings not only shed light on the nature and changes of RFs between early and later adolescence, but also offer some accounts for why exposure to CA has stronger proximal effects and is often found to have a lasting impact on mental health. Show less
BackgroundStudies investigating the link between depressive symptoms and inflammation have yielded inconsistent results, which may be due to two factors. First, studies differed regarding the... Show moreBackgroundStudies investigating the link between depressive symptoms and inflammation have yielded inconsistent results, which may be due to two factors. First, studies differed regarding the specific inflammatory markers studied and covariates accounted for. Second, specific depressive symptoms may be differentially related to inflammation. We address both challenges using network psychometrics.MethodsWe estimated seven regularized Mixed Graphical Models in the Netherlands Study of Depression and Anxiety (NESDA) data (N = 2321) to explore shared variances among (1) depression severity, modeled via depression sum-score, nine DSM-5 symptoms, or 28 individual depressive symptoms; (2) inflammatory markers C-reactive protein (CRP), interleukin 6 (IL-6), and tumor necrosis factor α (TNF-α); (3) before and after adjusting for sex, age, body mass index (BMI), exercise, smoking, alcohol, and chronic diseases.ResultsThe depression sum-score was related to both IL-6 and CRP before, and only to IL-6 after covariate adjustment. When modeling the DSM-5 symptoms and CRP in a conceptual replication of Jokela et al., CRP was associated with ‘sleep problems’, ‘energy level’, and ‘weight/appetite changes’; only the first two links survived covariate adjustment. In a conservative model with all 38 variables, symptoms and markers were unrelated. Following recent psychometric work, we re-estimated the full model without regularization: the depressive symptoms ‘insomnia’, ‘hypersomnia’, and ‘aches and pain’ showed unique positive relations to all inflammatory markers.ConclusionsWe found evidence for differential relations between markers, depressive symptoms, and covariates. Associations between symptoms and markers were attenuated after covariate adjustment; BMI and sex consistently showed strong relations with inflammatory markers. Show less
De Beurs, D.; Fried, E.I.; Wetherall, K.; Cleare, S.; O' Connor, D.B.; Ferguson, E.; ... ; O' Connor, R.C. 2019
Two leading theories within the field of suicide prevention are the interpersonal psychological theory of suicidal behaviour (IPT) and the integrated motivational-volitional (IMV) model. The IPT... Show moreTwo leading theories within the field of suicide prevention are the interpersonal psychological theory of suicidal behaviour (IPT) and the integrated motivational-volitional (IMV) model. The IPT posits that suicidal thoughts emerge from high levels of perceived burdensomeness and thwarted belongingness. The IMV model is a multivariate framework that conceptualizes defeat and entrapment as key drivers of suicide ideation. We applied network analysis to cross-sectional data collected as part of the Scottish Wellbeing Study, in which a nationally representative sample of 3508 young adults (18–34 years) completed a battery of psychological measures. Network analysis can help us to understand how the different theoretical components interact and how they relate to suicide ideation. Within a network that included only the core factors from both models, internal entrapment and perceived burdensomeness were most strongly related to suicide ideation. The core constructs defeat, external entrapment and thwarted belonginess were mainly related to other factors than suicide ideation. Within the network of all available psychological factors, 12 of the 20 factors were uniquely related to suicide ideation, with perceived burdensomeness, internal entrapment, depressive symptoms and history of suicide ideation explaining the most variance. None of the factors was isolated, and we identified four larger clusters: mental wellbeing, interpersonal needs, personality, and suicide-related factors. Overall, the results suggest that relationships between suicide ideation and psychological risk factors are complex, with some factors contributing direct risk, and others having indirect impact. Show less
This article explores attachment relationships from a network theory perspective: Correlations among behaviors, beliefs, and feelings related to attachment are hypothesized to stem from causal... Show moreThis article explores attachment relationships from a network theory perspective: Correlations among behaviors, beliefs, and feelings related to attachment are hypothesized to stem from causal relations. The authors used two data sets that assessed relationships with four attachment figures (mother, father, romantic partner, and best friend) using the Relationship Structures Questionnaire. Separate networks (Gaussian Graphical Models) were estimated based on 10 items for each attachment figure. Across networks in Study 1 (N = 310), items related to anxiety, seeking support, and discomfort disclosing feelings clustered with other items from their respective domains; a trust‐related item bridged the clusters. Study 2 replicated these findings in a larger and more diverse sample (N = 3,710). The potential of network analysis for advancing the study of attachment is discussed. Show less
A growing body of evidence highlights the role of life stress as a risk factor for the development and relapse of substance use disorders (SUDs), but the relationship of life stress with the... Show moreA growing body of evidence highlights the role of life stress as a risk factor for the development and relapse of substance use disorders (SUDs), but the relationship of life stress with the interactions among SUD symptoms is overlooked. The current study investigated the role of life stress in symptom networks of 3 different SUDs—alcohol, tobacco, and drug use—using the U.S. representative data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) I and II (N = 34,653). The symptom networks were estimated using the Ising model and l1-regularziation with model selection based on the Extended Bayesian Information Criterion. We examined the association of stress with 2 network characteristics: the network connectivity and the network structure. In addition, we applied bootstrap routines to examine the stability of our results and tested whether our findings of Wave 1 replicated in Wave II of the NESARC. For alcohol and drug use symptoms, but not for tobacco use symptoms, greater network connectivity (which is related to psychiatric severity and prognosis) was associated with the number of stressors. In contrast, the structure of SUD symptom networks remained stable regardless of the level of stress, which indicated that the order of central nodes in the symptom networks was not significantly associated with stress. Altogether, our findings suggest that there is a quantitative (i.e., greater connectivity), but not qualitative (i.e., structure), difference in alcohol and drug use symptom relationships associated with life stress. Show less
