Neuroticism has societal, mental and physical health relevance, with an etiology involving genetic predisposition, psychological influence, and their interaction.

To understand whether the association between polygenic risk score for neuroticism (PRS-N) and neuroticism is moderated by affective well-being.

Data were derived from TwinssCan, a general population twin cohort (age range=15-35 years, 478 monozygotic twins). Self-report questionnaires were used to measure well-being and neuroticism. PRS-N was trained from the Genetics of Personality Consortium (GPC) and United Kingdom Biobank (UKB). Multilevel mixed-effects models were used to test baseline and changes in well-being and neuroticism.

Baseline wellbeing and neuroticism were associated (β=-1.35, p<0.001). PRSs-N were associated with baseline neuroticism (lowest p-value: 0.008 in GPC, 0.01 in UKB). In interaction models (PRS x wellbeing), GPC PRS-N (β=0.38, p=0.04) and UKB PRS-N (β=0.81, p<0.001) had significant interactions.

PRSs-N were associated with changes in neuroticism (lowest p-value: 0.03 in GPC, 0.3 in UKB). Furthermore, changes in wellbeing and neuroticism were associated (β =-0.66, p<0.001). In interaction models (PRS x change in wellbeing), only UKB PRS-N had a significant interaction (β=0.80, p<0.001).

Interaction between polygenic risk, wellbeing and neuroticism, were observed regarding baselines measures and change over time. Depending on the analysis step, the direction of the effect changed.

None Declared

Prior evidence suggests that men and women might be differentially susceptible to distinct types of childhood adversity (CA), but research on gender-specific associations between CA subtypes and psychiatric symptoms is limited.

To test the gender-specific associations of CA subtypes and psychiatric symptoms in the general population.

Data from 791 twins and siblings from the TwinssCan project were used. Psychopathology and CA exposure were assessed using the Symptom Checklist-90 Revised (SCL-90) and the Childhood Trauma Questionnaire (CTQ), respectively. The associations between the total CTQ scores and SCL-90 scores (i.e. total SCL-90, psychoticism, paranoid ideation, anxiety, depression, somatization, obsessive-compulsive, interpersonal sensitivity, hostility, and phobic anxiety) were tested in men and women separately. The associations between the five CA subtypes (i.e. physical abuse, emotional abuse, sexual abuse, physical neglect, and emotional neglect) and total SCL-90 were tested in a mutually adjusted model. As exploratory analyses, the associations between all CA subtypes and the nine SCL-90 subdomain scores were similarly tested. The regression coefficients between men and women were compared using Chow’s test. All models were adjusted for age and family structure.

Total CTQ was significantly associated with total SCL-90 in men (B = 0.013, SE = 0.003, P < .001) and women (B = 0.011, SE = 0.002, P < .001). The associations with the nine symptom domains were also significant in both genders (P < .001). No significant gender differences in the regression coefficients of total CTQ were detected. The analyses of CA subtypes showed a significant association between emotional abuse and total SCL-90 in women (B = 0.173, SE = 0.030, P < .001) and men (B = 0.080, SE = 0.035, P = .023), but the association was significantly stronger in women (ꭓ2(1) = 4.10, P = .043). The association of sexual abuse and total SCL-90 was only significant in women (B = 0.217, SE = 0.053, P < .001). The associations of emotional neglect (B = 0.061, SE = 0.027, P = .026) and physical neglect (B = 0.167, SE = 0.043, P < .001) with total SCL-90 were only significant in men. The explorative analyses of SCL-90 subdomains revealed significant associations of emotional abuse with all nine symptom domains and of sexual abuse with seven symptom domains in women. Significant associations of physical neglect with six symptom domains and of emotional neglect with depression were also detected in men. No other significant associations between CT subtypes and total SCL-90 or symptom domain scores were observed in men and women.

CA exposure was associated with diverse psychopathology similarly in both genders. However, women are more sensitive to abuse, but men are more sensitive to neglect. Gender-specific influences of CA subtypes on psychopathology should be considered in future studies.

None Declared

Group-level studies showed cross-sectional and prospective between-person associations between circadian rest-activity rhythms (RAR), physical activity (PA), sleep, and depressive symptoms. However, whether these associations replicate at the within-person level remains unclear. Therefore, it is clinically relevant to investigate these associations within persons and study whether changes in depressive symptoms are related to changes in circadian rhythm and sleep variables.

To identify changes in circadian rhythm elements in proximity to a transition in depressive symptoms, whether changes are less frequent in individuals without compared to those with transitions, and whether there are individual differences in the direction of change of circadian rhythm variables.

Data of remitted individuals tapering antidepressants were used: 12 with and 14 without a transition in depressive symptoms. RAR, PA, and sleep variables were calculated as predictors from four months of actigraphy data. Transitions in depressive symptoms were based on weekly SCL-90 scores and evaluation interviews. Kernel Change Point analyses were used to detect change points (CPs) and CP timing in circadian rhythm variables for each individual separately.

In 67% of individuals with depressive symptoms transitions, CPs were identified in proximity to symptom transitions. CPs were detected less frequently in the no-transition group with 7 CPs in 14 individuals, compared to transition groups with 10 CPs in 12 individuals. For several RAR and sleep variables, consistent changes were detected in expected directions.

Circadian rhythm variables provide potentially clinically relevant information although their patterns around transitions are highly person-specific. Future research is needed to disentangle which variables are predictive for which patients.

No significant relationships.

In many countries, depressed individuals often first visit primary care settings for consultation, but a considerable number of clinically depressed patients remains unidentified. Introducing additional screening tools may facilitate the diagnostic process.

This study aims to examine whether Experience Sampling Method (ESM)-based measures of depressive affect and behaviors can discriminate depressed from non-depressed individuals. In addition, the added value of actigraphy-based measures was examined.

We used data from two samples to develop and validate prediction models. The development dataset included 14 days of ESM and continuous actigraphy of currently depressed (n=43) and non-depressed individuals (n=82). The validation dataset included 30 days of ESM and continuous actigraphy of currently depressed (n=27) and non-depressed individuals (n=27). Backward stepwise logistic regression analyses were applied to build the prediction models. The performance of the models was assessed with the goodness of fit indices, calibration curves, and discriminative ability (AUC, the area under the receiver operating characteristic curve).

In the development dataset, the discriminative ability was good for the actigraphy model (AUC=0.790) and excellent for the ESM (AUC=0.991) and combined-domains model (AUC=0.993). In the validation dataset, the discriminative ability was reasonable for the actigraphy model (AUC=0.648) and excellent for the ESM (AUC=0.891) and combined-domains model (AUC=0.892).

ESM is a good diagnostic predictor and is easy to calculate, and, therefore, holds promise for implementation in clinical practice. Actigraphy shows no added value to ESM as a diagnostic predictor, but might still be useful when active monitoring with ESM is not feasible.

No significant relationships.

For patients with bipolar disorder, early recognition of impending mood episodes is crucial to enable timely intervention. Longitudinal digital mood monitoring using ecological momentary assessment (EMA) enable prospective study of early warning signals (EWS) in momentary affective estates prior to symptom transitions.

The present study examined in a unique longitudinal EMA data set whether EWS prospectively signal transitions to manic or depressive episodes.

Twenty bipolar type I/II patients completed EMA questionnaires five times a day for four months (average 491 observations per person), as well as weekly symptom questionnaires concerning depressive (Quick Inventory for Depressive Symptomatology) and manic (Altman Self-Rating Mania Scale) symptoms. Weekly data was used to determine transitions (i.e., abrupt increase in symptoms). Prior to these transitions, EWS (autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective EMA states. Kendall’s tau was calculated to detect significant rises in the EWS indicator prior to the transition.

Eleven patients reported one or two transitions to a mood episode. All transitions were preceded by at least one EWS. Average sensitivity for detecting EWS was slightly higher for manic episodes (36%) than for depressive episodes (25%). For manic episodes, EWS in thoughts racing, being full of ideas, and feeling agitated showed the highest sensitivity and specificity, whereas for depression, only feeling tired showed high sensitivity and specify.

EWS show promise in anticipating transitions to mood episodes in bipolar disorder. Further investigation is warranted.

No significant relationships.

Greater affective inertia during the day (higher carry-over effects of prior affect to the current moment) is associated with depression and its development. However, the role of overnight affective inertia (from evening to morning) in depression, and the role of sleep therein, has been scarcely studied.

We examined i) the difference in overnight inertia for positive (PA) and negative affect (NA) between individuals with past depression, current depression, and no depression; ii) how sleep duration and quality influence overnight affective inertia in these groups, and iii) whether overnight affective inertia predicts depression development.

We used data of 579 women from the East-Flanders Prospective Twin Survey. First, individuals with past (n=82), current (n=26), and no depression (n=471) at baseline were examined, and then individuals who did (n=58) and did not (n=319) develop depression at 12-months follow-up. Affect was assessed 10 times a day for 5 days. Sleep was assessed with sleep diaries. Affective inertia was operationalized as the influence of affectt-1 on affectt. Linear mixed-effect models were used to test the hypotheses.

Overnight affective inertia was not associated with depression, neither was it differently associated with sleep characteristics in the depression groups. However, sleep characteristics were more negatively associated with morning NA in both depression groups compared to the non-depressed group. Overnight affective inertia did not predict the development of depression at follow-up.

Depression and sleep characteristics might be more related to mean affect levels rather than to more complex emotion dynamics measures. Replication of these findings with longer time-series is needed.

Stress is a risk factor for developing psychopathology. Emerging evidence suggests that daily experiences of stress may also predict symptoms during the day. It is unclear to what extent the influence of stress on psychopathology during the day is the same across individuals (including across diagnostic boundaries), and which effects are individual-specific

This study aims to reveal how stress and symptoms are interrelated in a cross-diagnostic context by modeling individual level temporal networks, and examining subgroups with similar dynamics.

Hundred twenty two young adults (43.4% women) with a wide range of psychopathology in terms of severity and type of problems completed a six-month daily diary study. We used a temporal network approach (i.e., group iterative multiple model estimation) to model how stress and ten specific symptoms (e.g., feeling down, paranoia, restlessness) were related across time at the individual-specific, subgroup, and group level.

After controlling for the lagged influence of stress on itself, stress level predicted the level of restlessness, worrying, nervousness, and feeling down during the same day for >70% of individuals. We observed three larger subgroups with each over 20 individuals, whose temporal networks showed different dynamic patterns involving specific symptoms. Effects of stress on other specific symptoms differed across individuals, and these were not subgroup-specific.

This study showed important overlap between individuals in terms of impact of stress on psychopathology in daily life. Subtle differences between individuals were also observed. Possibly, such differences are relevant for examining individual-specific vulnerability for future psychopathology. This requires further investigation.

No significant relationships.

Transitions in mental health, such as the onset or sudden progression of psychopathology, are difficult to foresee. If mental health behaves like other complex systems, drops in mental health may be anticipated by early warning signals (EWS), which manifest in the dynamics of time series data.

This study aimed to establish the sensitivity and specificity of EWS as personalized risk markers for sudden drops mental health.

Individuals (N=122, mean age 23.6 ±0.7 years, 57% males) at increased risk for psychopathology completed daily questionnaires on mental states for six consecutive months. Transitions in mental health were identified by change point analyses. EWS, operationalized as rising trends in the autoregressive coefficient of 36 negative mental states, were identified using generalized additive models.

EWS were found for 59% of individuals with a drop in mental health, and for 47% without such a drop (sensitivity: 0-.12; specificity: .88-1). There were considerable individual differences in the prevalence, strength, and timing of EWS.

EWS might be informative of impeding transitions, yet they are also highly conservative. Present findings may inspire future research into the prerequisites for detecting EWS in the context of mental health, for instance with respect to the stability of pre- and post-transition phases, the magnitude of transitions, and the timescale at which EWS manifest. An improved understanding of the dynamics that govern psychopathology could ultimately allow us to determine whether a specific individual at a specific moment in time is at risk for a sudden onset or progression of mental health problems.

The reward system regulates the processes that motivate people to pursue evolutionary beneficial stimuli. Effective functioning of the reward system can protect against the development of anhedonia. In the daily life, the reward system can be expressed as the dynamic interplay of positive affect (liking), reward anticipation (wanting), and active behavior (engaging). Applying network analysis to daily life experience data allows us to identify such reward dynamics and use them to predict future depressive symptoms.

We investigated whether at baseline (i) higher network positive affect in-strength, reflecting how strongly positive affect is influenced by other components and hence the level of anhedonia, and (ii) higher network connectivity, reflecting overall functioning of the reward system, are associated with fewer depressive symptoms on follow-up.

We used data from 43 participants with mild depressive symptoms from the SMARTSCAN study. The dynamic interplay between momentary positive affect, reward anticipation, and active behavior was assessed with individual vector-autoregressive models and the network analysis. Network positive affect in-strength and connectivity indices were used to predict a six-month depressive symptoms trajectory.

Reward systems networks vary greatly between individuals. On the group level, higher positive affect in-strength (Beta=-3.66, p=0.05) and network connectivity (Beta=-4.06, p=0.03) at baseline were associated with fewer symptoms at follow-up.

Higher influences of reward anticipation and active behavior on positive affect and stronger connections between reward cycle components are associated with fewer future symptoms, suggesting the importance of daily life reward cycle dynamics in depression.

No significant relationships.

Disease trajectories of patients with anxiety disorders are highly diverse and approximately 60% remain chronically ill. The ability to predict disease course in individual patients would enable personalized management of these patients. This study aimed to predict recovery from anxiety disorders within 2 years applying a machine learning approach.

In total, 887 patients with anxiety disorders (panic disorder, generalized anxiety disorder, agoraphobia, or social phobia) were selected from a naturalistic cohort study. A wide array of baseline predictors (N = 569) from five domains (clinical, psychological, sociodemographic, biological, lifestyle) were used to predict recovery from anxiety disorders and recovery from all common mental disorders (CMDs: anxiety disorders, major depressive disorder, dysthymia, or alcohol dependency) at 2-year follow-up using random forest classifiers (RFCs).

At follow-up, 484 patients (54.6%) had recovered from anxiety disorders. RFCs achieved a cross-validated area-under-the-receiving-operator-characteristic-curve (AUC) of 0.67 when using the combination of all predictor domains (sensitivity: 62.0%, specificity 62.8%) for predicting recovery from anxiety disorders. Classification of recovery from CMDs yielded an AUC of 0.70 (sensitivity: 64.6%, specificity: 62.3%) when using all domains. In both cases, the clinical domain alone provided comparable performances. Feature analysis showed that prediction of recovery from anxiety disorders was primarily driven by anxiety features, whereas recovery from CMDs was primarily driven by depression features.

The current study showed moderate performance in predicting recovery from anxiety disorders over a 2-year follow-up for individual patients and indicates that anxiety features are most indicative for anxiety improvement and depression features for improvement in general.

The aim of this study is to assess the relationship between the use of opioid drugs and speech intelligibility and discrimination of sound frequencies.

44 opioid addicts (10 women and 34 men) during methadone maintenance treatment were examined. The mean age of participants 33 ± 9 years; the average duration of addiction: 12 years. The Polish Sentence Test (PTZ) for speech intelligibility measurements was used. The test consists of the presentation of 26 sentences, which were disrupted by the babble-noise. in the study of frequency discrimination experimental method is used. Two signals of different frequencies were presented. The task of the study is to identify the frequency-modulated stimulus (target). The study was conducted in a soundproof booth. The Psychoacoustics and Speech Workstations by Tucker Davis Technologies was used.

The difference in speech intelligibility and frequency discrimination between opioid addicts and healthy ones was found. The average value of the intensity of speech sounds in noise (Signal-to-Noise Ratio - SNR) in opioid addicts was -3.7 dB and in healthy ones was -5.6 dB. There was no correlation between the duration of addiction and the speech intelligibility in noise or frequency discrimination.

The influence of taking opioids for speech intelligibility and frequency discrimination was found.

Little is known about how daily life mood reactivity to minor stressors (stress reactivity) might change following major depressive disorder (MDD) treatment. We investigate whether (i) mood states and appraisals of daily stressors change after treatment; (ii) stress reactivity to event, activity, or social stress differs; (iii) stress reactivity depends on severity of residual depressive symptoms; and (iv) stress reactivity in individuals with remitted or non-remitted depression differ from that of never-depressed individuals.

Thirty depressed individuals participated in an experience sampling study before and after a treatment period of 18 months; 39 healthy individuals formed a comparison group. Reactivity of positive affect (PA) and negative affect (NA) to daily stressors were measured.

More residual symptoms were associated with larger NA responses to stress. Compared to healthy controls, participants with non-remitted MDD showed higher NA-reactivity to all stressors. In contrast, stress reactivity to event and activity stressors was normalized in remitted patients. However, they still showed heightened NA-reactivity to social stress.

Greater stress reactivity to event and activity stress appears to be state-dependent. The heightened social stress reactivity in remitted patients suggests that sensitivity to social stress may reflect an underlying vulnerability in MDD.

The aim of research is to assess a speech perception in alcohol addicts and healthy ones.

65 alcohol addicts (mean age 38 years, min. 22, max. 66 years) were examined. Patients admitted hearing impaired were excluded. The average duration of addiction: 8.8 years. The measure of speech understanding is the ratio of correctly received phonetic elements to the total number of presented ones. Speech understanding is often determined in the presence of masking noise. Respondents are to arrangement of sentences with words heard in the noise. The test determines the intensity of speech, for which - if it is presented in the noise - observed in 50% of correct answers. This parameter is called the Threshold Reception Speech (SRT). The logatom intelligibility test consists with over 150 presented stimuli. Both tests were conducted in a soundproof booth

In the speech understanding test were found significant difference of average SRT between alcohol addict and healthy ones. The better understanding of speech was found in healthy individuals. in a study conducted in the final phase of detoxification treatment, it was found that the level of speech understanding in addicts was improved (statistically significant). in the logatom intelligibility test wasn’t differences.

It was found that alcohol dependence is associated with worse perception of speech.

Mild psychotic experiences are common in the general population. Although transient and benign in most cases, these experiences are predictive of later mental health problems for a significant minority. The goal of the present study was to perform examinations of the dimensional and discrete variations in individuals’ reporting of subclinical positive and negative psychotic experiences in a unique Dutch internet-based sample from the general population.

Positive and negative subclinical psychotic experiences were measured with the Community Assessment of Psychic Experiences in 2870 individuals. First, the prevalence of these experiences and their associations with demographics, affect, psychopathology and quality of life were investigated. Next, latent class analysis was used to identify data-driven subgroups with different symptom patterns, which were subsequently compared on aforementioned variables.

Subclinical psychotic experiences were commonly reported. Both positive and negative psychotic experiences were associated with younger age, more negative affect, anxiety and depression as well as less positive affect and poorer quality of life. Seven latent classes (‘Low psychotic experiences’, ‘Lethargic’, ‘Blunted’, ‘Distressed’, ‘Paranormal’, ‘Distressed_grandiose’ and ‘Distressed/positive psychotic experiences’) were identified that demonstrated both dimensional differences in the number/severity of psychotic experiences and discrete differences in the patterns of reported experiences.

Subclinical psychotic experiences show both dimensional severity variations and discrete symptom-pattern variations across individuals. To understand and capture all interindividual variations in subclinical psychotic experiences, their number, nature and context (co-occurrence patterns) should be considered at the same time. Only some psychotic experiences may lay on a true psychopathological psychosis continuum.

The aim of the current study was to replicate findings in adults indicating that higher sensitivity to stressful events is predictive of both onset and persistence of psychopathological symptoms in a sample of adolescents and young adults. In addition, we tested the hypothesis that sensitivity to mild stressors in particular is predictive of the developmental course of psychopathology.

We analyzed experience sampling and questionnaire data collected at baseline and one-year follow-up of 445 adolescent and young adult twins and non-twin siblings (age range: 15–34). Linear multilevel regression was used for the replication analyses. To test if affective sensitivity to mild stressors in particular was associated with follow-up symptoms, we used a categorical approach adding variables on affective sensitivity to mild, moderate and severe daily stressors to the model.

Linear analyses showed that emotional stress reactivity was not associated with onset (ß = .02; P = .56) or persistence (ß = -.01; P = .78) of symptoms. There was a significant effect of baseline symptom score (ß = .53; P < .001) and average negative affect (NA: ß = .19; P < .001) on follow-up symptoms. Using the categorical approach, we found that affective sensitivity to mild (ß = .25; P < .001), but not moderate (ß = -.03; P = .65) or severe (ß = -.06; P = .42), stressors was associated with symptom persistence one year later.

We were unable to replicate previous findings relating stress sensitivity linearly to symptom onset or persistence in a younger sample. Whereas sensitivity to more severe stressors may reflect adaptive coping, high sensitivity to the mildest of daily stressors may indicate an increased risk for psychopathology.

Depression has been associated with abnormalities in neural underpinnings of Reward Learning (RL). However, inconsistencies have emerged, possibly owing to medication effects. Additionally, it remains unclear how neural RL signals relate to real-life behaviour. The current study, therefore, examined neural RL signals in young, mildly to moderately depressed – but non-help-seeking and unmedicated – individuals and how these signals are associated with depressive symptoms and real-life motivated behaviour.

Individuals with symptoms along the depression continuum (n = 87) were recruited from the community. They performed an RL task during functional Magnetic Resonance Imaging and were assessed with the Experience Sampling Method (ESM), completing short questionnaires on emotions and behaviours up to 10 times/day for 15 days. Q-learning model-derived Reward Prediction Errors (RPEs) were examined in striatal areas, and subsequently associated with depressive symptoms and an ESM measure capturing (non-linearly) how anticipation of reward experience corresponds to actual reward experience later on.

Significant RPE signals were found in the striatum, insula, amygdala, hippocampus, frontal and occipital cortices. Region-of-interest analyses revealed a significant association between RPE signals and (a) self-reported depressive symptoms in the right nucleus accumbens (b = −0.017, p = 0.006) and putamen (b = −0.013, p = .012); and (b) the quadratic ESM variable in the left (b = 0.010, p = .010) and right (b = 0.026, p = 0.011) nucleus accumbens and right putamen (b = 0.047, p < 0.001).

Striatal RPE signals are disrupted along the depression continuum. Moreover, they are associated with reward-related behaviour in real-life, suggesting that real-life coupling of reward anticipation and engagement in rewarding activities might be a relevant target of psychological therapies for depression.

Interventions based on the experience sampling method (ESM) are ideally suited to provide insight into personal, contextualized affective patterns in the flow of daily life. Recently, we showed that an ESM-intervention focusing on positive affect was associated with a decrease in symptoms in patients with depression. The aim of the present study was to examine whether ESM-intervention increased patient empowerment.

Depressed out-patients (n = 102) receiving psychopharmacological treatment who had participated in a randomized controlled trial with three arms: (i) an experimental group receiving six weeks of ESM self-monitoring combined with weekly feedback sessions, (ii) a pseudo-experimental group participating in six weeks of ESM self-monitoring without feedback, and (iii) a control group (treatment as usual only). Patients were recruited in the Netherlands between January 2010 and February 2012. Self-report empowerment scores were obtained pre- and post-intervention.

There was an effect of group × assessment period, indicating that the experimental (B = 7.26, P = 0.061, d = 0.44, statistically imprecise) and pseudo-experimental group (B = 11.19, P = 0.003, d = 0.76) increased more in reported empowerment compared to the control group. In the pseudo-experimental group, 29% of the participants showed a statistically reliable increase in empowerment score and 0% reliable decrease compared to 17% reliable increase and 21% reliable decrease in the control group. The experimental group showed 19% reliable increase and 4% reliable decrease.

These findings tentatively suggest that self-monitoring to complement standard antidepressant treatment may increase patients’ feelings of empowerment. Further research is necessary to investigate long-term empowering effects of self-monitoring in combination with person-tailored feedback.

It has been suggested that the structure of psychopathology is best described as a complex network of components that interact in dynamic ways. The goal of the present paper was to examine the concept of psychopathology from a network perspective, combining complementary top-down and bottom-up approaches using momentary assessment techniques.

A pooled Experience Sampling Method (ESM) dataset of three groups (individuals with a diagnosis of depression, psychotic disorder or no diagnosis) was used (pooled N = 599). The top-down approach explored the network structure of mental states across different diagnostic categories. For this purpose, networks of five momentary mental states (‘cheerful’, ‘content’, ‘down’, ‘insecure’ and ‘suspicious’) were compared between the three groups. The complementary bottom-up approach used principal component analysis to explore whether empirically derived network structures yield meaningful higher order clusters.

Individuals with a clinical diagnosis had more strongly connected moment-to-moment network structures, especially the depressed group. This group also showed more interconnections specifically between positive and negative mental states than the psychotic group. In the bottom-up approach, all possible connections between mental states were clustered into seven main components that together captured the main characteristics of the network dynamics.

Our combination of (i) comparing network structure of mental states across three diagnostically different groups and (ii) searching for trans-diagnostic network components across all pooled individuals showed that these two approaches yield different, complementary perspectives in the field of psychopathology. The network paradigm therefore may be useful to map transdiagnostic processes.