The bridge symptoms of childhood trauma, sleep disorder and depressive symptoms: a network analysis

BACKGROUND

This study aimed to elucidate the characteristics of symptom network of childhood trauma (CT) and sleep disorder (SD) in Chinese adolescents, with the influence of depressive symptoms taken into account.

METHOD

A total of 1301 adolescent students were included, and their CT, SD and depressive symptoms were measured using the Pittsburgh sleep quality index (PSQI), the Childhood Trauma Questionnaire-Short Form (CTQ-SF), and The Patient Health Questionnaire-9 (PHQ-9), respectively. Central symptoms and bridge symptoms were identified based on centrality indices and bridge centrality indices, respectively. Network stability was examined using the case-dropping procedure.

RESULTS

In CT and SD symptom network, emotional abuse and sleep quality symptoms had the highest centrality values, and two bridge symptoms, i.e., emotional abuse and sleep disturbance symptoms, were also identified. In symptom network for CT, SD, and depressive symptoms, sleeping difficulty symptoms, daily dysfunction symptoms, and emotional abuse appeared to be potential bridge symptoms. In symptom network of CT, SD, and depressive symptoms (excluding the symptom of sleeping difficulty), daily dysfunction symptoms, emotional abuse, and sleep disturbance symptoms appeared to be bridge symptoms.

CONCLUSIONS

In this study, emotional abuse and poor sleep quality were found to be central symptoms in the CT-SD network structure among Chinese adolescent students, with daytime dysfunction as the bridge symptom in the CT-SD-depression network structure. Systemic multi-level interventions targeting the central symptoms and bridge symptoms may be effective in alleviating the co-occurrence of CT, SD and depression in this population.

Oppositional Defiant Disorder Symptoms and Multi-level Family Factors in Chinese Migrant Children: A Network Perspective

Based on the network theory of mental disorders, this study used network analysis to examine the network of ODD symptoms and multilevel family factors and identify the most crucial family factors influencing ODD symptoms in children. A total of 718 Chinese migrant children aged 7-14 years participated in this study. This study measured ODD symptoms, family system-level variables (3 factors), family dyadic-level variables (6 factors), and family individual-level variables (6 factors) with factors selected based on the multilevel family factors theory of ODD symptoms. The results indicated that (1) "annoy" was the center symptom of ODD, (2) "annoy" and "vindictive" was the main bridge connecting the multilevel family factors, and (3) family cohesion at the family system level, parent-child conflict at the family dyadic level, and parental depression at the family individual level were critical central and bridging influencing factors. The findings of this study highlight the critical role of "annoy" and "vindictive" symptoms in the activation of ODD symptom networks in children and provide a basis for future improvements in diagnostic criteria. These potential core and bridge factors might become key intervention targets for childhood ODD.

Network analysis of internet addiction and sleep disturbance symptoms

BACKGROUND

Internet addiction (IA) is a behavioral addiction to problematic internet use. IA is associated with poorer sleep quality. Few studies to date, however, have explored the interactions between symptoms of IA and symptoms of sleep disturbance. This study uses network analysis to identify bridge symptoms by analyzing these interactions in a large sample of students.

METHOD

We recruited 1977 university students to participate in our study. Each student completed the Internet Addiction Test (IAT) and the Pittsburgh Sleep Quality Index (PSQI). We used these collected data for network analysis to identify the bridge symptoms in the IAT-PSQI network by calculating the bridge centrality. Furthermore, the closest symptom connected with the bridge symptom was found to identify the comorbidity mechanisms.

RESULTS

The core symptom of IA and the sleep disturbance network was "I08" (Study efficiency suffers due to internet use). The bridge symptoms between IA and sleep disturbance were "I14" (Surfing the internet late instead of sleeping), "P_DD" (Daytime dysfunction), and "I02" (Spending much time online instead of socializing in real life). Among the symptoms, "I14" had the highest bridge centrality. The edge connecting nodes "I14" and "P_SDu" (Sleep duration) had the strongest weight (0.102) around all the symptoms of sleep disturbance. Nodes "I14" and "I15" (Thinking about online shopping, games, social networking, and other network activities when unable to access the internet) had the strongest weight (0.181), connecting all the symptoms of IA.

CONCLUSIONS

IA leads to poorer sleep quality, most likely by shortening sleep duration. Preoccupation with and craving the internet while being offline may lead to this situation. Healthy sleep habits should be learned, and craving may be a good point at which to treat the symptoms of IA and sleep disturbance.

Network analysis of internet addiction and depression among Chinese college students during the COVID-19 pandemic: A longitudinal study

Background

There has been growing evidence of comorbidity between internet addiction and depression in youth during the COVID-19 period. According to the network theory, this may arise from the interplay of symptoms shared by these two mental disorders. Therefore, we examined this underlying process by measuring the changes in the central and bridge symptoms of the co-occurrence networks across time.

Methods

A total of 852 Chinese college students were recruited during two waves (T1: August 2020; T2: November 2020), and reported their internet addiction symptoms and depressive symptoms. Network analysis was utilized for the statistical analysis.

Results

The internet addiction symptoms "escape" and "irritable," and depression symptoms "energy" and "guilty" were the central symptoms for both waves. At the same time, "guilty" and "escape" were identified as bridge symptoms. Notably, the correlation between "anhedonia" and "withdrawal" significantly increased, and that between "guilty" and "escape" significantly decreased over time.

Conclusions

This study provides novel insights into the central features of internet addiction and depression during the two stages. Interestingly, "guilty" and "escape," two functions of the defense mechanism, are identified as bridge symptoms. These two symptoms are suggested to activate the negative feedback loop and further contribute to the comorbidity between internet addiction and depression. Thus, targeting interventions on these internalized symptoms may contribute to alleviating the level of comorbidity among college students.

Network of depression and anxiety symptoms in patients with epilepsy

PURPOSE

Depression and anxiety are often comorbid in people with epilepsy. Network models consider this comorbidity as an interacting system of depressive and anxiety symptoms. The present study investigates the network structure of depressive and anxiety symptoms in people with epilepsy and aims to identify the central and bridge symptoms to provide suggestions for the prevention of and intervention for depression-anxiety comorbidity in patients with epilepsy.

METHODS

A total of 313 patients with epilepsy were enrolled in our study. Anxiety symptoms were evaluated with the Generalized Anxiety Disorder 7-Item questionnaire. Depressive symptoms were evaluated with the Patient Health Questionnaire-9. Network analyses were used for the statistical analysis.

RESULTS

The findings indicated that ten edges with the strongest regularized partial correlations existed in the network. Six were among depressive symptoms, such as "sleep difficulties" with "fatigue" and " feeling of worthlessness" with "thoughts of death". Four were among anxiety symptoms, such as "nervousness or anxiety" with "uncontrollable worry" and "uncontrollable worry" with "worry too much". Those strongest edges had no connection linking anxiety and depressive symptoms. The symptoms "depressed or sad mood", "trouble relaxing" and "uncontrollable worry" had the highest strength centrality in the network. The results revealed three bridge symptoms: "psychomotor agitation/retardation", "irritable", and "depressed or sad mood".

CONCLUSION

"Feeling of worthlessness" was identified as a key priority due to associations with suicidal ideation. The current study highlighted the critical central symptoms "depressed or sad mood", "trouble relaxing" and "uncontrollable worry" and the critical bridge symptoms "psychomotor agitation/retardation", "irritable", and "depressed or sad mood". Implications for clinical prevention and intervention based on these symptoms are discussed.

Comorbidity between depression and anxiety: assessing the role of bridge mental states in dynamic psychological networks

BACKGROUND

Comorbidity between depressive and anxiety disorders is common. A hypothesis of the network perspective on psychopathology is that comorbidity arises due to the interplay of symptoms shared by both disorders, with overlapping symptoms acting as so-called bridges, funneling symptom activation between symptom clusters of each disorder. This study investigated this hypothesis by testing whether (i) two overlapping mental states "worrying" and "feeling irritated" functioned as bridges in dynamic mental state networks of individuals with both depression and anxiety as compared to individuals with either disorder alone, and (ii) overlapping or non-overlapping mental states functioned as stronger bridges.

METHODS

Data come from the Netherlands Study of Depression and Anxiety (NESDA). A total of 143 participants met criteria for comorbid depression and anxiety (65%), 40 participants for depression-only (18.2%), and 37 for anxiety-only (16.8%) during any NESDA wave. Participants completed momentary assessments of symptoms (i.e., mental states) of depression and anxiety, five times a day, for 2 weeks (14,185 assessments). First, dynamics between mental states were modeled with a multilevel vector autoregressive model, using Bayesian estimation. Summed average lagged indirect effects through the hypothesized bridge mental states were compared between groups. Second, we evaluated the role of all mental states as potential bridge mental states.

RESULTS

While the summed indirect effect for the bridge mental state "worrying" was larger in the comorbid group compared to the single disorder groups, differences between groups were not statistically significant. The difference between groups became more pronounced when only examining individuals with recent diagnoses (< 6 months). However, the credible intervals of the difference scores remained wide. In the second analysis, a non-overlapping item ("feeling down") acted as the strongest bridge mental state in both the comorbid and anxiety-only groups.

CONCLUSIONS

This study empirically examined a prominent network-approach hypothesis for the first time using longitudinal data. No support was found for overlapping mental states "worrying" and "feeling irritable" functioning as bridge mental states in individuals vulnerable for comorbid depression and anxiety. Potentially, bridge mental state activity can only be observed during acute symptomatology. If so, these may present as interesting targets in treatment, but not prevention. This requires further investigation.

The interrelations among aspects of dyspnea and symptoms of depression in COPD patients - a network analysis

BACKGROUND

Depression is a frequent comorbidity in COPD. COPD symptoms such as dyspnea may play an important role in the causal relationship between COPD and depression. We investigated the interrelations among different aspects of dyspnea and other COPD parameters and symptoms of depression in COPD patients.

METHODS

This is a secondary analysis of N = 590 COPD patients. At the beginning (T0) and the end (T1) of a 3-week inpatient pulmonary rehabilitation, dyspnea aspects intensity (BORG scale), frequency (2 CCQ items), functioning (CCQ-function) and cognitive/emotional response (2 SGRQ items) as well as cough (2 CCQ items), functional capacity (6MWD), lung function (FEV1) and symptoms of depression (PHQ-9) were assessed. Regression analyses with PHQ-9 sum score as dependent variable as well as network analysis using PHQ-9 single items were performed. Structural invariance over time was examined.

RESULTS

Dyspnea frequency, function, and cognitive/emotional response showed conditional independent relationships with PHQ-9 sum score. Network analysis showed that dyspnea frequency and dyspnea functioning were primarily associated with somatic depression symptoms (for example, sleep problems, loss of energy), while cognitive/emotional response was primarily related to cognitive-affective depression symptoms (for example, feeling down/depressed/hopeless). Regression parameters, network structure and network global strength did not differ between T0 and T1.

LIMITATIONS

Models are based on between-person relationships. Results should be confirmed using time-series data.

CONCLUSIONS

Dyspnea and depression seem to be interrelated through a variety of different and complex pathways in COPD patients. Results may be used to explain intervention effects and develop new intervention strategies to reduce depression in COPD.