The associations of hair cortisol and DHEA with posttraumatic stress disorder symptoms in refugees.

BACKGROUND: Exposure to traumatic events, ongoing adversity, and posttraumatic stress disorder (PTSD) are associated with altered activity of the hypothalamic-pituitary-adrenal (HPA) axis, but findings are mixed. This may be explained in part by heterogeneity in PTSD symptom profiles. AIM: The aim of this study was to investigate the complex relationships between the number of traumatic events and post-displacement stressors, individual symptoms of PTSD, and HPA-axis hormones cortisol and dehydroepiandrosterone (DHEA) in refugees. METHODS: Adult (18+ years) Syrian refugees with increased levels of distress participating in a randomized controlled trial completed baseline measures to assess traumatic events (trauma checklist), post-displacement stressors (Post-Migration Living Difficulties checklist), symptoms of PTSD (PTSD Checklist for DSM-5; PCL-5), and provided a hair sample for additional stress hormone analyses. We used R-packages qgraph and bootnet to perform network analysis on the number of traumatic events and post-displacement stressors, individual symptoms of PTSD, and HPA-axis hormones cortisol and DHEA. The final network model was corrected for depression severity. RESULTS: 115 (53% male, M age = 36.9, SD = 12.7) of 206 participants provided a hair sample. A higher number of traumatic events was directly associated with three symptoms of the PTSD cluster arousal and reactivity, i.e., sleep disturbance, hypervigilance and physiological reactivity, and with three other PTSD symptoms, namely flashbacks, avoidance of reminders, and self-destructive behavior. A higher number of post-displacement stressors was associated with four symptoms of the PTSD cluster cognition and mood, i.e., trauma-related amnesia, negative beliefs, blaming of self/others, and detachment, as well as with intrusive thoughts, sleep disturbance, hypervigilance, and exaggerated startle response. The number of traumatic events and post-displacement stressors were not associated with cortisol or DHEA. Cortisol was positively associated with two symptoms of the PTSD cluster cognition and mood, i.e., negative beliefs and negative trauma-related emotions, and negatively associated with avoidance of reminders. DHEA was positively associated with restricted affect and with three symptoms of the PTSD symptom cluster arousal and reactivity, i.e., irritability/anger, sleep disturbance, and self-destructive behavior, and negatively associated with avoidance of thoughts. CONCLUSIONS: This study demonstrated that exposure to traumatic events and post-displacement stressors is not related to cortisol and DHEA, but that cortisol and DHEA are differentially related to individual symptoms of PTSD. While lower levels of both cortisol and DHEA were associated with increased avoidance, higher levels of cortisol were mostly associated with symptoms of the PTSD cluster cognition and mood and higher levels of DHEA were mostly associated with symptoms of the PTSD cluster arousal and reactivity. These findings contribute to explaining the variability of findings in the literature on HPA-axis activity in PTSD. ETHICS: The study was approved by the Research Ethics Review Committee at VU Medical Center, the Netherlands (Protocol ID: NL61361.029.17, 7 September 2017) and prospectively registered online (https://www.trialregister.nl/trial/6665).

The complex clinical response to selective serotonin reuptake inhibitors in depression: a network perspective.

The clinical response to selective serotonin reuptake inhibitors (SSRIs) in depression takes weeks to be fully developed and is still not entirely understood. This study aimed to determine the direct and indirect effects of SSRIs relative to a placebo control condition on clinical symptoms of depression. We included data of 8262 adult patients with major depression participating in 28 industry-sponsored US Food and Drug Administration (FDA) registered trials on the efficacy of SSRIs. Clinical symptoms of depression were assessed by the 17 separate items of the Hamilton Depression Rating Scale (HDRS) after 1, 2, 3, 4 and 6 weeks of treatment. Network estimation techniques showed that SSRIs had quick and strong direct effects on the two affective symptoms, i.e., depressed mood and psychic anxiety; direct effects on other symptoms were weak or absent. Substantial indirect effects were found for all four cognitive symptoms, which showed larger reductions in the SSRI condition but mainly in patients reporting larger reductions in depressed mood. Smaller indirect effects were found for two arousal/somatic symptoms via the direct effect on psychic anxiety. Both direct and indirect effects on sleep problems and most arousal/somatic symptoms were weak or absent. In conclusion, our study revealed that SSRIs primarily caused reductions in affective symptoms, which were related to reductions in mainly cognitive symptoms and some specific arousal/somatic symptoms. The results can contribute to disclosing the mechanisms of action of SSRIs, and has the potential to facilitate early detection of responders and non-responders in clinical practice.

NET-RMDs study: networks of fatigue and pain in rheumatic and musculoskeletal diseases - protocol for an international cross-sectional study.

INTRODUCTION: Fatigue and pain are the main symptoms of rheumatic and musculoskeletal diseases (RMDs). Healthcare professionals have a primary role in helping patients to manage both these symptoms, which are part of a complex network of co-occurring factors including sleep problems, psychological distress, social support, body weight, diet, inactive lifestyle and disease activity. The patterns of relationships (networks) between these factors and these symptoms, fatigue and pain, are largely unknown. The current proposal aims to reveal them using network estimation techniques. We will also consider differences in networks for subgroups of people with (1) different RMDs and (2) different clusters (profiles) of biopsychosocial factors. METHODS AND ANALYSIS: Adults with at least one RMD will be recruited to this online cross-sectional observational project. To provide a complete overview, a large sample size from different countries will be included. A brief online survey, using 0-10 numeric rating scales will measure, for the past month, levels of fatigue and pain as well as scores on seven biopsychosocial factors. These factors were derived from literature and identified by interviews with patients, health professionals and rheumatologists. Using this input, the steering committee of the project decided the factors to be measured giving priority to those that can be modified in self-management support in community health centres worldwide. Network estimation techniques are used to detect the complex patterns of relationships between these biopsychosocial factors, fatigue and pain; and how these differ for subgroups of people with different RMDs and profiles. ETHICS AND DISSEMINATION: Ethical approval of national Institutional Review Boards was obtained. The online survey includes an information letter and informed consent form. The findings will be disseminated via conferences and publications in peer-reviewed scientific journals, while public media channels will be used to inform people with RMDs and other interested parties.

Exploring the Association of Age with Depressive Symptomatology in Childhood and Adolescence: A Network Study.

OBJECTIVE: This study aimed to explore the association of age with individual depression and anxiety symptoms and their connectivity (i.e., number/strength of connections with other symptoms) in girls and boys. METHOD: Our study comprised cross-sectional data from 31,960 Dutch girls and 32,162 Dutch boys aged 8 to 18 and considered 11 depression symptoms and 14 anxiety symptoms measured by the Revised Child Anxiety and Depression Scale. Network estimations were used to examine whether age was associated with individual symptoms and, in a separate step, with the connectivity of depression symptoms with other depression symptoms and with the connectivity of depression symptoms with anxiety symptoms. RESULTS: Age was, in general, positively associated with depression symptoms in girls, but not in boys, and with the connectivity of depression symptoms with other depression symptoms in both sexes. These findings were the most profound for energy-related symptoms in girls. Age was, in general, negatively associated with anxiety symptoms and not or negatively associated with the connectivity of depression symptoms with anxiety symptoms in girls and boys, respectively. Substantial differences across symptoms were found. CONCLUSIONS: This study shows that it is important to focus on individual symptoms, for age is mainly associated with energy-related depression symptoms and their connectivity in girls. Future etiologic studies may examine the role of energy-related depression symptoms in the development of depressive symptomatology in girls as these symptoms seem potential targets for the prevention of depression in the female population.

Comparing network structures on three aspects: A permutation test.

Network approaches to psychometric constructs, in which constructs are modeled in terms of interactions between their constituent factors, have rapidly gained popularity in psychology. Applications of such network approaches to various psychological constructs have recently moved from a descriptive stance, in which the goal is to estimate the network structure that pertains to a construct, to a more comparative stance, in which the goal is to compare network structures across populations. However, the statistical tools to do so are lacking. In this article, we present the network comparison test (NCT), which uses resampling-based permutation testing to compare network structures from two independent, cross-sectional data sets on invariance of (a) network structure, (b) edge (connection) strength, and (c) global strength. Performance of NCT is evaluated in simulations that show NCT to perform well in various circumstances for all three tests: The Type I error rate is close to the nominal significance level, and power proves sufficiently high if sample size and difference between networks are substantial. We illustrate NCT by comparing depression symptom networks of males and females. Possible extensions of NCT are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Maintaining Outcomes of Internet-Delivered Cognitive-Behavioral Therapy for Depression: A Network Analysis of Follow-Up Effects.

Background: Depression is a highly prevalent mental disorder, but only a fraction of those affected receive evidence-based treatments. Recently, Internet-based interventions were introduced as an efficacious and cost-effective approach. However, even though depression is a heterogenous construct, effects of treatments have mostly been determined using aggregated symptom scores. This carries the risk of concealing important effects and working mechanisms of those treatments. Methods: In this study, we analyze outcome and long-term follow-up data from the EVIDENT study, a large (N = 1,013) randomized-controlled trial comparing an Internet intervention for depression (Deprexis) with care as usual. We use Network Intervention Analysis to examine the symptom-specific effects of the intervention. Using data from intermediary and long-term assessments that have been conducted over 36 months, we intend to reveal how the treatment effects unfold sequentially and are maintained. Results: Item-level analysis showed that scale-level effects can be explained by small item-level effects on most depressive symptoms at all points of assessment. Higher scores on these items at baseline predicted overall symptom reduction throughout the whole assessment period. Network intervention analysis offered insights into potential working mechanisms: while deprexis directly affected certain symptoms of depression (e.g., worthlessness and fatigue) and certain aspects of the quality of life (e.g., overall impairment through emotional problems), other domains were affected indirectly (e.g., depressed mood and concentration as well as activity level). The configuration of direct and indirect effects replicates previous findings from another study examining the same intervention. Conclusions: Internet interventions for depression are not only effective in the short term, but also exert long-term effects. Their effects are likely to affect only a small subset of problems. Patients reporting these problems are likely to benefit more from the intervention. Future studies on online interventions should examine symptom-specific effects as they potentially reveal the potential of treatment tailoring. Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT02178631.

Symptom-specific effectiveness of an internet-based intervention in the treatment of mild to moderate depressive symptomatology: The potential of network estimation techniques.

The internet-based intervention Deprexis® has proven to be effective in improving overall depression severity. The current pragmatic randomized controlled trial included 1013 participants with mild to moderate symptomatology and aimed to identify the symptom-specific effects of the internet-based intervention Deprexis (intervention group) in comparison to care as usual (control group). All participants -in both conditions- were permitted to use any type of treatment. Of the nine considered symptoms (assessed with the Patient Health Questionnaire), seven showed larger improvements in the intervention condition relative to care as usual (effect sizes ranging from 0.15 to 0.31). No significant differences were found for the two other symptoms. In a next step, a network was estimated including treatment condition as well as changes in all nine symptoms. The resulting network suggests that four of the seven identified symptom-specific effects were direct, whereas the three other symptom-specific effects were indirect and could be explained by effects on other symptoms. Lastly, exploratory analyses showed that the intervention was more effective in improving overall depression severity for participants with higher scores on those four symptoms that were directly affected by the intervention; consequently, the network estimation techniques showed potential in precision psychiatry.

The symptom-specific efficacy of antidepressant medication vs. cognitive behavioral therapy in the treatment of depression: results from an individual patient data meta-analysis.

A recent individual patient data meta-analysis showed that antidepressant medication is slightly more efficacious than cognitive behavioral therapy (CBT) in reducing overall depression severity in patients with a DSM-defined depressive disorder. We used an update of that dataset, based on seventeen randomized clinical trials, to examine the comparative efficacy of antidepressant medication vs. CBT in more detail by focusing on individual depressive symptoms as assessed with the 17-item Hamilton Rating Scale for Depression. Five symptoms (i.e., "depressed mood" , "feelings of guilt" , "suicidal thoughts" , "psychic anxiety" and "general somatic symptoms") showed larger improvements in the medication compared to the CBT condition (effect sizes ranging from .13 to .16), whereas no differences were found for the twelve other symptoms. In addition, network estimation techniques revealed that all effects, except that on "depressed mood" , were direct and could not be explained by any of the other direct or indirect treatment effects. Exploratory analyses showed that information about the symptom-specific efficacy could help in identifying those patients who, based on their pre-treatment symptomatology, are likely to benefit more from antidepressant medication than from CBT (effect size of .30) versus those for whom both treatments are likely to be equally efficacious. Overall, our symptom-oriented approach results in a more thorough evaluation of the efficacy of antidepressant medication over CBT and shows potential in "precision psychiatry" .

Zooming In and Zooming Out: A Network Perspective on the Comorbidity of Depression and Anxiety.

Several statistical techniques are available to shed light on the structure of psychopathology, and each is valuable in its own way. It is, however, important to realize that the results of these techniques are substantially influenced by the structure of the studied instrument. Network analyses are no exception and do not perform miracles. However, they are unique in embracing the diversity of psychopathology, as the approach is both specific, by zooming in on individual symptoms, and transdiagnostic, by zooming out on the broad spectrum of psychopathology. Therefore, I genuinely believe that it will move our field forward.

Offspring of depressed and anxious patients: Help-seeking after first onset of a mood and/or anxiety disorder.

BACKGROUND: Offspring of patients with depressive and/or anxiety disorders are at high risk of developing a similar disorder themselves. Early recognition and treatment may have substantial effects on prognosis. The main aim of this study was to examine the time to initial help-seeking and its determinants in offspring after the first onset of a mood and/or anxiety disorder. METHODS: Data are presented of 215 offspring with a mood and/or anxiety disorder participating in a cohort study with 10 year follow-up. We determined age of disorder onset and age of initial help-seeking. Offspring characteristics (gender, IQ, age of onset, disorder type, suicidal ideation) and family characteristics (socioeconomic status, family functioning) were investigated as potential predictors of the time to initial help-seeking. RESULTS: The estimated overall proportion of offspring of depressed/anxious patients who eventually seek help after onset of a mood and/or anxiety disorder was 91.9%. The time to initial help-seeking was more than two years in 39.6% of the offspring. Being female, having a mood disorder or comorbid mood and anxiety disorder (relative to anxiety) and a disorder onset in adolescence or adulthood (relative to childhood) predicted a shorter time to initial help-seeking. LIMITATIONS: Baseline information relied on retrospective reports. Age of onsets and age of initial help-seeking may therefore be subject to recall bias. CONCLUSION: Although most offspring eventually seek help after onset of a mood/anxiety disorder, delays in help-seeking were common, especially in specific subgroups of patients. This information may help to develop targeted strategies to reduce help-seeking delays.

Mental disorders as networks of problems: a review of recent insights.

PURPOSE: The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years. METHODS: This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three main themes: comorbidity, prediction, and clinical intervention. RESULTS: Pertaining to comorbidity, the network approach provides a powerful new framework to explain why certain disorders may co-occur more often than others. For prediction, studies have consistently found that symptom networks of people with mental disorders show different characteristics than that of healthy individuals, and preliminary evidence suggests that networks of healthy people show early warning signals before shifting into disordered states. For intervention, centrality-a metric that measures how connected and clinically relevant a symptom is in a network-is the most commonly studied topic, and numerous studies have suggested that targeting the most central symptoms may offer novel therapeutic strategies. CONCLUSIONS: We sketch future directions for the network approach pertaining to both clinical and methodological research, and conclude that network analysis has yielded important insights and may provide an important inroad towards personalized medicine by investigating the network structures of individual patients.

Doomed for Disorder? High Incidence of Mood and Anxiety Disorders in Offspring of Depressed and Anxious Patients: A Prospective Cohort Study.

OBJECTIVE: Early recognition of individuals at risk for depressive and anxiety disorders is key in influencing onset and course of these disorders. Parental history is a potent risk factor for the development of these disorders in offspring. However, knowledge about the magnitude of this risk is limited as large-scale longitudinal studies with a follow-up into adulthood are scarce. Those offspring at highest risk may possibly be identified by easy-to-determine parental psychiatric characteristics, family context, and offspring characteristics. METHODS: From 2000-2002, we recruited 523 offspring (age 13-25 years) of 366 patients who had received specialized treatment for depressive and/or anxiety disorder. Offspring DSM-IV mood (major depressive disorder, dysthymia, and bipolar disorder) and anxiety disorders (generalized anxiety disorder, social phobia, panic disorder, and agoraphobia) were assessed at baseline and at 4-, 6-, 8-, and 10-year follow-up. RESULTS: Kaplan-Meier analysis showed that the cumulative incidence of mood and/or anxiety disorder was 38.0% at age 20 years and 64.7% at age 35 years. Parental early disorder onset (hazard ratio [HR] = 1.33; 95% CI, 1.00-1.77), having 2 affected parents (HR = 1.58; 95% CI, 1.10-2.27), and offspring female gender (HR = 2.34; 95% CI, 1.74-3.15) were independent predictors of offspring mood and/or anxiety disorder. Balanced family functioning (HR = 0.73; 95% CI, 0.56-0.96) was found to be protective against offspring risk. CONCLUSIONS: Offspring of depressed and anxious patients are at very high risk of a mood and/or anxiety disorder themselves. Parental early onset, having 2 affected parents, female gender, and family functioning are important additional markers that can be used in clinical practice to identify those offspring at greatest risk.

The impact of somatic symptoms on the course of major depressive disorder.

OBJECTIVE: Somatic symptoms have been suggested to negatively affect the course of major depressive disorder (MDD). Mechanisms behind this association, however, remain elusive. This study examines the impact of somatic symptoms on MDD prognosis and aims to determine whether this effect can be explained by psychiatric characteristics, somatic diseases, lifestyle factors, and disability. METHODS: In 463 MDD patients (mean age=44.9 years, 69.8% female) from the Netherlands Study of Depression and Anxiety (NESDA), we examined whether the type and number of somatic symptom clusters predicted the two-year persistence of MDD. Diagnoses of MDD were established with the Composite International Diagnostic Interview (CIDI) and somatic symptom clusters were assessed with the Four-Dimensional Symptom Questionnaire (4DSQ) somatization scale. Psychiatric characteristics, somatic diseases, lifestyle factors, and disability were taken into account as factors potentially underlying the association. RESULTS: The cardiopulmonary, gastrointestinal, and general cluster significantly predicted the two-year persistence of MDD, but only when two or more of these clusters were present (OR=2.32, 95% CI=1.51-3.57, p=<0.001). Although the association was partly explained by MDD severity, the presence of multiple somatic symptom clusters remained a significant predictor after considering all potentially underlying factors (OR=1.69, 95%CI=1.07-2.68, p=0.03). CONCLUSIONS: Somatic symptoms are predictors of a worse prognosis of MDD independent of psychiatric characteristics, somatic diseases, lifestyle factors, and disability. These results stress the importance of considering somatic symptoms in the diagnostic and treatment trajectory of patients with MDD. Future research should focus on identifying treatment modalities targeting depressive as well as somatic symptoms.

The network structure of psychopathology in a community sample of preadolescents.

Psychopathology is often classified according to diagnostic categories or scale scores. These ignore potentially important information about associations between specific symptoms and, consequently, lead to heterogeneous constructs that may mask relevant individual differences. Network analyses focus on these specific symptom associations, providing the opportunity to explore the complex structure of psychopathology in more detail. We examined the empirical network structure of 95 emotional and behavioral problems of the Youth Self-Report (YSR) to explore how well this structure reflected the predefined YSR domains. The study was conducted in a large community sample (N = 2,175) of preadolescents (mean age = 11.1, SD = 0.6 years), and the network structure was determined by means of the recently developed network analysis technique, eLasso. Although problems within the same domain, in general, showed more and stronger connections than problems belonging to different domains, some problems showed substantially more or stronger associations than others; consequently, problems cannot be considered interchangeable indicators of their domain. Furthermore, no sharp boundaries were found between the domains as specific symptom pairs of different domains showed strong connections. Taken together, our findings indicate that network models provide a promising addition to the more traditional way of distinguishing diagnoses or scale scores. (PsycINFO Database Record

Association of Symptom Network Structure With the Course of [corrected] Depression.

IMPORTANCE: Major depressive disorder (MDD) is a heterogeneous condition in terms of symptoms, course, and underlying disease mechanisms. Current classifications do not adequately address this complexity. In novel network approaches to psychopathology, psychiatric disorders are conceptualized as complex dynamic systems of mutually interacting symptoms. This perspective implies that a more densely connected network of symptoms is indicative of a poorer prognosis, but, to date, no previous study has examined whether network structure is indeed associated with the longitudinal course of MDD. OBJECTIVE: To examine whether the baseline network structure of MDD symptoms is associated with the longitudinal course of MDD. DESIGN, SETTING, AND PARTICIPANTS: In this prospective study, in which remittent and persistent MDD was defined on the basis of a follow-up assessment after 2 years, 515 patients from the Netherlands Study of Depression and Anxiety with past-year MDD (established with the Composite International Diagnostic Interview) and at least moderate depressive symptoms (assessed with the Inventory of Depressive Symptomatology [IDS]) at baseline were studied. Baseline starting and ending dates were September 1, 2004, through February 28, 2007. Follow-up starting and ending dates were September 1, 2006, through February 28, 2009. Analysis was conducted August 2015. The MDD was considered persistent if patients had at least moderate depressive symptoms (IDS) at 2-year follow-up; otherwise, the MDD was considered remitted. MAIN OUTCOMES AND MEASURES: Sparse network structures of baseline MDD symptoms assessed via IDS were computed. Global and local connectivity of network structures were compared across persisters and remitters using a permutation test. RESULTS: Among the 515 patients, 335 (65.1%) were female, mead (SD) age was 40.9 (12.1) years, and 253 (49.1%) had persistent MDD at 2-year follow-up. Persisters (n = 253) had a higher baseline IDS sum score than remitters (n = 262) (mean [SD] score, 40.2 [8.9] vs 35.1 [7.1]; the test statistic for the difference in IDS sum score was 22 027; P < .001). The test statistic for the difference in network connectivity was 1.79 (P = .01) for the original data, 1.55 for data matched on IDS sum score (P = .04), and 1.65 for partialed out data (P = .02). At the symptom level, fatigue or loss of energy and feeling guilty had the largest difference in importance in persisters' network compared with that of remitters (Cohen d = 1.13 and 1.18, respectively). CONCLUSIONS AND RELEVANCE: This study reports that symptom networks of patients with MDD are related to longitudinal course: persisters exhibited a more densely connected network at baseline than remitters. More pronounced associations between symptoms may be an important determinant of persistence in MDD.