The Gaussian Graphical Model in Cross-Sectional and Time-Series Data

The association of impulsivity with depression and anxiety symptoms: A transdiagnostic network analysis and replication

BACKGROUND

Impulsivity increases the risk for depression and anxiety. However, the granular pathways among them remain unknown. A network approach that moves from disorder-level analysis to symptom-level analysis can provide further understanding of psychopathological mechanisms. In this study, we examined the network structure of impulsivity and separate and comorbid symptoms of depression and anxiety.

METHODS

Regularized partial-correlation networks were estimated using cross-sectional data from 1047 Chinese participants aged 18-26 years (main dataset, mean age = 21.45 ± 2.01 years) and 325 Chinese participants aged 18-36 years (an independent replication dataset, mean age = 21.49 ± 3.73 years), including impulsivity-depression, impulsivity-anxiety, and impulsivity-depression-anxiety networks. The datasets were collected from 1 June 2023 to 4 August 2023 and from 27 April 2022 to 16 May 2022, respectively. Impulsivity, depression, and anxiety were assessed using Barratt Impulsiveness Scale Version 11, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7, respectively. Bridge centrality was analyzed, and a network comparison test (NCT) was conducted to investigate the differences between the main dataset and replication dataset.

RESULTS

The motor impulsivity dimension was revealed to be closely connected with individual symptoms of depression and anxiety regardless of whether they were in separate disorder forms or comorbid forms. In all the networks, motor impulsivity was the most important bridge node. The NCT showed comparable network connectivity and network structure between the main and replication datasets.

LIMITATIONS

The use of cross-sectional data limited the inferences about the direction of causality between variables.

CONCLUSIONS

These findings elucidate the psychopathological mechanisms underlying how impulsivity functions within depression, anxiety, and comorbidity and support that motor impulsivity is an important risk factor across different mental disorders and is responsible for comorbidity. The implications of these findings are discussed.

Impact of psychopathology on day-to-day living in patients with schizophrenia: A network analysis

Although the relationship between schizophrenia and disability is well established, the association between the symptoms of the disorder and functional domains remains unclear. The current study explored the nuances of the relationship between symptoms and domains of functioning in a sample of 1127 patients with schizophrenia. We assessed the symptoms of schizophrenia with the Positive and Negative Syndrome Scale (PANSS) and psychosocial functioning with the mini-ICF-APP (mini-International Classification of Functioning Rating for Limitations of Activities and Participation in Psychological Disorders). The mean PANSS score was 94.28 (27.20), and the mean mini-ICF-APP score was 25.25 (8.96), both of which are indicative of severe symptom load and impairment. We were able to show a strong relationship and overlap between symptoms and disability in patients with schizophrenia. We identified several symptoms related to functional impairment. Deficits in judgment and abstract thinking contribute to impairment through poor adherence (to routines and compliance with rules) and difficulties in planning and organizing. We believe that in schizophrenia, symptoms and their interactions constitute a disorder beyond any single manifestation. Furthermore, we suggest that cognitive testing and cognitive treatment should become part of the standard of care for patients with schizophrenia.

Effects of childhood trauma on the symptom-level relation between depression, anxiety, stress, and problematic smartphone use: A network analysis

BACKGROUND

Childhood trauma experience is closely associated with depression, anxiety, stress, and problematic smartphone use (PSU). However, few studies have explored the complex symptom-level relations between these variables among people with and without trauma experiences, leaving a gap in treating and alleviating these mental disorders among individuals with childhood trauma.

METHODS

The current study used a convenience sampling method and recruited 2708 participants who completed Childhood Trauma Questionnaire-Short Form (CTQ-SF), Depression Anxiety and Stress Scales (DASS-21), and Mobile Phone Addiction Tendency Scale (MPATS), dividing them into trauma (n = 1454, Mean age = 19.67) and no-trauma (n = 1254, Mean age = 19.57) groups according to the cut-off scores of CTQ-SF. Symptom network analysis and network comparison test were conducted to construct and compare the network models between trauma and no-trauma groups.

RESULTS

The findings indicate that the trauma group and females exhibit greater average levels of DASS-21 and PSU symptoms compared to the no-trauma group and males, respectively. Additionally, the edge between "Stress" and "Anxiety" is the strongest across trauma and no-trauma groups. "Social comfort" is a bridge symptom of the trauma group network and the results of bridge symptoms in the no-trauma group are not stable.

LIMITATIONS

This study did not categorize all individuals according to specific types of trauma experiences and it is a cross-sectional design. The prevalences calculated in this study may not be generalizable.

CONCLUSIONS

Interventions targeting different bridge symptoms in the trauma and no-trauma network models may help reduce the severity of symptoms.

The effect of an online acceptance and commitment intervention on the meaning-making process in cancer patients following hematopoietic cell transplantation: study protocol for a randomized controlled trial enhanced with single-case experimental design

BACKGROUND

Hematopoietic cell transplantation (HCT) is a highly invasive and life-threatening treatment for hematological neoplasms and some types of cancer that can challenge the patient's meaning structures. Restoring meaning (i.e., building more flexible and significant explanations of the disease and treatment burden) can be aided by strengthening psychological flexibility by means of an Acceptance and Commitment Therapy (ACT) intervention. Thus, this trial aims to examine the effect of the ACT intervention on the meaning-making process and the underlying mechanisms of change in patients following HCT compared to a minimally enhanced usual care (mEUC) control group. The trial will be enhanced with a single-case experimental design (SCED), where ACT interventions will be compared between individuals with various pre-intervention intervals.

METHODS

In total, 192 patients who qualify for the first autologous or allogeneic HCT will be recruited for a two-armed parallel randomized controlled trial comparing an online self-help 14-day ACT training to education sessions (recommendations following HCT). In both conditions, participants will receive once a day a short survey and intervention proposal (about 5-10 min a day) in the outpatient period. Double-blinded assessment will be conducted at baseline, during the intervention, immediately, 1 month, and 3 months after the intervention. In addition, 6-9 participants will be invited to SCED and randomly assigned to pre-intervention measurement length (1-3 weeks) before completing ACT intervention, followed by 7-day observations at the 2nd and 3rd post-intervention measure. The primary outcome is meaning-related distress. Secondary outcomes include psychological flexibility, meaning-making coping, meanings made, and well-being as well as global and situational meaning.

DISCUSSION

This trial represents the first study that integrates the ACT and meaning-making frameworks to reduce meaning-related distress, stimulate the meaning-making process, and enhance the well-being of HCT recipients. Testing of an intervention to address existential concerns unique to patients undergoing HCT will be reinforced by a statistically rigorous idiographic approach to see what works for whom and when. Since access to interventions in the HCT population is limited, the web-based ACT self-help program could potentially fill this gap.

TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT06266182. Registered on February 20, 2024.

Exploring the complex interrelation between depressive symptoms, risk, and protective factors: A comprehensive network approach

BACKGROUND

Depressive symptoms seem to be interrelated in a complex and self-reinforcing way. To gain a better understanding of this complexity, the inclusion of theoretically relevant constructs (such as risk and protective factors) offers a comprehensive view into the complex mechanisms underlying depression.

METHODS

Cross-sectional data from individuals diagnosed with a major depressive disorder (N = 986) and healthy controls (N = 1049) were analyzed. Participants self-reported their depressive symptoms, as well as several risk factors and protective factors. Regularized partial correlation networks were estimated for each group and compared using a network comparison test.

RESULTS

Symptoms of depression were more strongly connected in the network of depressed patients than in healthy controls. Among the risk factors, perceived stress, the experience of negative life events, emotional neglect, and emotional abuse were the most centrally embedded in both networks. However, the centrality of risk factors did not significantly differ between the two groups. Among the protective factors, social support, personal competence, and acceptance were the most central in both networks, where the latter was significantly more strongly associated with the symptom of self-hate in depressed patients.

CONCLUSION

The network analysis revealed that key symptoms of depression were more strongly connected for depressed patients than for healthy controls, and that risk and protective factors play an important role, particularly perceived stress in both groups and an accepting attitude for depressed patients. However, the purpose of this study is hypothesis generating and assisting in the potential selection of non-symptom nodes for future research.

Assessing and accounting for measurement in intensive longitudinal studies: current practices, considerations, and avenues for improvement

PURPOSE

Intensive longitudinal studies, in which participants complete questionnaires multiple times a day over an extended period, are increasingly popular in the social sciences in general and quality-of-life research in particular. The intensive longitudinal methods allow for studying the dynamics of constructs (e.g., how much patient-reported outcomes vary across time). These methods promise higher ecological validity and lower recall bias than traditional methods that question participants only once, since the high frequency means that participants complete questionnaires in their everyday lives and do not have to retrospectively report about a large time interval. However, to ensure the validity of the results obtained from analyzing the intensive longitudinal data (ILD), greater awareness and understanding of appropriate measurement practices are needed.

METHOD

We surveyed 42 researchers experienced with ILD regarding their measurement practices and reasons for suboptimal practices.

RESULTS

Results showed that researchers typically do not use measures validated specifically for ILD. Participants assessing the psychometric properties and invariance of measures in their current studies was even less common, as was accounting for these properties when analyzing dynamics. This was mainly because participants did not have the necessary knowledge to conduct these assessments or were unaware of their importance for drawing valid inferences. Open science practices, in contrast, appear reasonably well ingrained in ILD studies.

CONCLUSION

Measurement practices in ILD still need improvement in some key areas; we provide recommendations in order to create a solid foundation for measuring and analyzing psychological constructs.

Academic procrastination of nursing students in higher vocational college: Application of latent profile analysis and network analysis

BACKGROUND

Academic procrastination is especially prevalent among nursing students in higher vocational colleges and it is considered an important factor of poor academic performance. However, existing research mainly focused on the overall level of academic procrastination, and little is known about the individual heterogeneity of academic procrastination among nursing students in higher vocational colleges. Thus, the aim of this study was to clarify the subgroups and factors of academic procrastination among nursing students in higher vocational college and explore academic procrastination networks of the latent subgroups.

METHODS

A cross-sectional study with online survey. 1369 nursing students in one higher vocational college were recruited using convenience sampling. Participants completed electronic questionnaires that collected demographic and academic characteristics, perceived stress, and academic procrastination. Latent profile analysis, multinomial logistic regression analysis, and network analysis were performed to analyze the data.

RESULTS

Three latent profiles of academic procrastination were identified: low (32.4 %), medium (53.3 %), and high (14.3 %). Higher vocational college nursing students who have reset an exam, low professional identity, and perceived more stress are more likely to have higher academic procrastination than other profiles. Network analysis showed that academic procrastination networks structure of the three latent profiles had distinct central components. For the low academic procrastination group, AP11 ("I make study plans, but I often fail to stick to them") and AP12 ("If there is no external pressure, I tend to postpone assignments or reports with deadlines") were the core components. For the medium academic procrastination group, AP17 ("I always wait until I can't postpone my academic tasks any longer before starting them") and AP16 ("I always tend to postpone on assignments or other academic tasks") were the central components. For the high academic procrastination group, AP16 and AP7 ("When studying in my dorm room, I often stop to do other things") were the essential components.

CONCLUSIONS

There is heterogeneity in higher vocational college nursing students' academic procrastination that can be classified into three latent profiles. The examined factors of academic procrastination and identified the central components of academic procrastination networks of the three latent profiles help nurse educators tailor targeted interventions.

Peer functioning difficulties may exacerbate symptoms of attention-deficit/hyperactivity disorder and irritability over time: a temporal network analysis

BACKGROUND

Children with attention-deficit/hyperactivity disorder (ADHD) have been consistently found to experience impairments in peer functioning. Irritability is highly prevalent in children with ADHD and may worsen social impairments given the frequent temper outbursts and low frustration tolerance characterizing irritability. However, it is still unclear how ADHD and irritability symptoms interact with peer functioning difficulties over time. Assessing these temporal dynamics using a novel longitudinal approach (i.e., temporal network analysis) may reveal precise targets for intervention.

METHODS

This study investigates the dynamic associations between ADHD symptoms, irritability, and peer functioning in a community sample of 739 children (ages 8-11 years, Mage = 10.06 [SD = 0.59], 47.77% females) assessed at three timepoints, 6 months apart, in a school-based study. Parents reported their child's ADHD symptoms using the Swanson, Nolan, and Pelham Rating Scale (SNAP-IV), and irritability symptoms using the Child Behavior Checklist (CBCL) irritability items. Children's peer functioning (i.e., peer acceptance, peer rejection, number of friendships, and victimization) was measured via peer nomination. To estimate the longitudinal associations between the variables, we built a graphical vector autoregression model for panel data.

RESULTS

The longitudinal network highlighted that poor peer functioning contributed to increases in symptoms over time. Specifically, (1) physical victimization predicted increases in inattention, hyperactivity, and irritability; (2) peer rejection predicted increases in inattention, which in turn predicted increases in irritability; (3) peer acceptance predicted decreases in inattention and irritability; and (4) higher numbers of mutual friendships increased inattention.

CONCLUSIONS

These results suggest that a negative social environment involving physical bullying and rejection may aggravate ADHD and irritability symptoms. Conversely, positive social interactions, such as being liked by peers, may improve inattention and irritability symptoms. Fostering social-emotional skills and positive social interactions and environments in children with ADHD and irritability may be a promising target for future interventions to reduce symptoms.

The impact of antidepressant treatment on the network structure of neurocognition and core emotional depressive symptoms among depressed individuals with a history of suicide attempt: An 8-week clinical study

BACKGROUND

A more in-depth understanding of the relationship between depressive symptoms, neurocognition and suicidal behavior could provide insights into the prognosis and treatment of major depressive disorder (MDD) and suicide. We conducted a network analysis among depressed patients examining associations between history of suicide attempt (HSA), core emotional major depression disorder, and key neurocognitive domains.

METHOD

Depressed patients (n = 120) aged 18-65 years were recruited from a larger randomized clinical trial conducted at the Douglas Institute in Montreal, Canada. They were randomly assigned to receive one of two antidepressant treatments (i.e., escitalopram or desvenlafaxine) for 8 weeks. Core emotional MDD and key neurocognitive domains were assessed pre-post treatment.

RESULTS

At baseline, an association between history of suicide attempt (HSA) and phonemic verbal fluency (PVF) suggested that HSA patients reported lower levels of the latter. After 8 weeks of antidepressant treatment, HSA became conditionally independent from PVF. Similar results were found for both the HAM-D and the QIDS-SR core emotional MDD/neurocognitive networks.

CONCLUSION

Network analysis revealed a pre-treatment relationship between a HSA and decreased phonemic VF among depressed patients, which was no longer present after 8 weeks of antidepressant treatment.

Sex differences in entrapment in a multinational sample: a network analysis perspective

Background

The concept of entrapment has been highlighted as a transdiagnostic element that manifests itself in disorders such as depression, anxiety, and suicidal ideation. Although research has been conducted in different contexts independently, a comprehensive multi-country study to assess gender differences in entrapment through network analysis has not yet been carried out. The objective of this study was to evaluate the entrapment network in men and women at the multinational level.

Methods

A sample of 2,949 participants, ranging in age from 18 to 73 years from six countries (Germany, Iran, Spain, Slovakia, El Salvador, and Peru), was considered. They completed the entrapment scale. A network analysis was performed for both men and women to identify the connectivity between indicators and the formation of clusters and domains, in addition to the centrality assessment in both sex groups.

Results

The study findings revealed the presence of a third domain focused on external interpersonal entrapment in the network of men and women. However, in relation to the interconnectivity between domains, variations were evidenced in both networks, as well as in centrality, it was reported that men present a greater generalized entrapment in various aspects of life, while women tend to experience a more focused entrapment in expressions of intense emotional charge.

Conclusion

The multinational study identified variations in the structure of entrapment between genders, with three domains (internal, external, and external-interpersonal) and differences in the interaction of indicators and groupings, as well as discrepancies in centrality.

The dynamic relationships between well-being, behavioral restrictions, and health behaviors during the COVID-19 pandemic: A large-scale intensive longitudinal network study

The behavioral restrictions disrupting daily life during the COVID-19 pandemic have profoundly impacted well-being, and health behaviors have been advocated to prevent decline. To understand how processes related to fluctuation in well-being unfold within individuals, analyses on the within-person level are required. In this preregistered intensive longitudinal study, 1,709 individuals from the Norwegian adult population provided data daily over 40 consecutive days during the pandemic. The responses were modeled in a multilevel vector autoregressive model to estimate within-person networks, across and within-day, and a between-person network. All three networks revealed productivity, relatedness, and optimism as positively associated. Social distancing was contemporaneously negatively associated with productivity and relatedness. Among behavioral factors, being physically active predicted lower relatedness across days but displayed positive associations with relatedness, productivity, and optimism contemporaneously. Alcohol consumption predicted lower productivity across and within-day, although revealing a positive association with optimism within-day. Being social online and feeling related to others displayed a temporal negative bidirectional relationship. In contrast, being social online was positively associated with optimism, productivity, and relatedness contemporaneously. Our study emphasizes the dynamic nature of well-being and its complex associations with behavioral factors during the pandemic. The study shed light on opposing associations of behavioral factors at the within- and between-person level.

Heterogeneity in suicide risk: Evidence from personalized dynamic models

Most theories of suicide propose within-person changes in psychological states cause suicidal thoughts/behaviors; however, most studies use between-person analyses. Thus, there are little empirical data exploring current theories in the way they are hypothesized to occur. We used a form of statistical modeling called group iterative multiple model estimation (GIMME) to explore one theory of suicide: The Interpersonal Theory of Suicide (IPTS). GIMME estimates personalized statistical models for each individual and associations shared across individuals. Data were from a real-time monitoring study of individuals with a history of suicidal thoughts/behavior (adult sample: participants = 111, observations = 25,242; adolescent sample: participants = 145, observations = 26,182). Across both samples, none of theorized IPTS effects (i.e., contemporaneous effect from hopeless to suicidal thinking) were shared at the group level. There was significant heterogeneity in the personalized models, suggesting there are different pathways through which different people come to experience suicidal thoughts/behaviors. These findings highlight the complexity of suicide risk and the need for more personalized approaches to assessment and prediction.

Identifying symptom clusters and temporal interconnections in patients with lung tumors after CT-guided microwave ablation: A network analysis

PURPOSE

To explore symptom clusters and interrelationships using a network analysis approach among symptoms in patients with lung tumors who underwent computed tomography (CT)-guided microwave ablation (MWA).

METHODS

A longitudinal study was conducted, and 196 lung tumor patients undergoing MWA were recruited and were measured at 24 h, 48 h, and 72 h after MWA. The Chinese version of the MD Anderson Symptom Inventory and the Revised Lung Cancer Module were used to evaluate symptoms. Network analyses were performed to explore the symptom clusters and interrelationships among symptoms.

RESULTS

Four stable symptom communities were identified within the networks. Distress, weight loss, and chest tightness were the central symptoms. Distress, and weight loss were also the most key bridge symptoms, followed by cough. Three symptom networks were temporally stable in terms of symptom centrality, global connectivity, and network structure.

CONCLUSION

Our findings identified the central symptoms, bridge symptoms, and the stability of symptom networks of patients with lung tumors after MWA. These network results will have important implications for future targeted symptom management intervention development. Future research should focus on developing precise interventions for targeting central symptoms and bridge symptoms to promote patients' health.

Methodological and Statistical Practices of Using Symptom Networks to Evaluate Mental Health Interventions: A Review and Reflections

The network approach to psychopathology, which assesses associations between individual symptoms, has recently been applied to evaluate treatments for mental disorders. While various options for conducting network analyses in intervention research exist, an overview and an evaluation of the various approaches are currently missing. Therefore, we conducted a review on network analyses in intervention research. Studies were included if they constructed a symptom network, analyzed data that were collected before, during or after treatment of a mental disorder, and yielded information about the treatment effect. The 56 included studies were reviewed regarding their methodological and analytic strategies. About half of the studies based on data from randomized trials conducted a network intervention analysis, while the other half compared networks between treatment groups. The majority of studies estimated cross-sectional networks, even when repeated measures were available. All but five studies investigated networks on the group level. This review highlights that current methodological practices limit the information that can be gained through network analyses in intervention research. We discuss the strength and limitations of certain methodological and analytic strategies and propose that further work is needed to use the full potential of the network approach in intervention research.

Relationships among anxiety, depression, and health-related quality of life in adult epilepsy: A network analysis

OBJECTIVE

Comorbid depression and anxiety in patients with epilepsy (PWE) are common and frequently under-treated, thus, causing poor health-related quality of life (HRQoL). However, little is known regarding the interconnections between anxious/depressive symptoms and the dimensions of HRQoL. Therefore, we conducted a network analysis to explore these relationships in detail among Chinese adult PWE.

METHODS

A cohort of adult PWE was consecutively recruited from the First Affiliated Hospital of Chongqing Medical University. HRQoL, depression, and anxiety were measured with Quality of Life in Epilepsy Inventory-31, Neurological Disorders Depression Inventory for Epilepsy, and Generalized Anxiety Disorder 7-Item Scale, respectively. A regularized partial correlation network was constructed to investigate the interconnections between symptoms of anxiety/depression and the dimensions of HRQoL. We calculated expected influence (EI) and bridge expected influence (BEI) values to identify the most influential nodes.

RESULTS

A total of 396 PWE were enrolled in this study, 78.1% of whom had focal onset epilepsy. The prevalence of anxiety and depression was 30.3% and 28.8%, respectively. The symptoms "frustrated" and "uncontrollable worry" had the highest EI values, whereas "emotional well-being", "seizure worry", "difficulty finding pleasure", and "nervousness or anxiety" had the highest BEI values.

CONCLUSION

This study provides new insights into the relationships among anxiety, depression, and HRQoL. Critical central symptoms and bridge symptoms identified in the network might help to quickly identify PWE comorbid anxiety and depression in busy outpatient settings, thereby enabling early intervention and enhancing quality of life.

Towards precision in the diagnostic profiling of patients: leveraging symptom dynamics as a clinical characterisation dimension in the assessment of major depressive disorder

BACKGROUND

International guidelines present overall symptom severity as the key dimension for clinical characterisation of major depressive disorder (MDD). However, differences may reside within severity levels related to how symptoms interact in an individual patient, called symptom dynamics.

AIMS

To investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same overall symptom severity.

METHOD

Participants with MDD (n = 73; mean age 34.6 years, s.d. = 13.1; 56.2% female) rated their baseline symptom severity using the Inventory for Depressive Symptomatology Self-Report (IDS-SR). Momentary indicators for depressive symptoms were then collected through ecological momentary assessments five times per day for 28 days; 8395 observations were conducted (average per person: 115; s.d. = 16.8). Each participant's symptom dynamics were estimated using person-specific dynamic network models. Individual differences in these symptom relationship patterns in groups of participants sharing the same symptom severity levels were estimated using individual network invariance tests. Subsequently, the overall proportion of participants that displayed differential symptom dynamics while sharing the same symptom severity was calculated. A supplementary simulation study was conducted to investigate the accuracy of our methodology against false-positive results.

RESULTS

Differential symptom dynamics were identified across 63.0% (95% bootstrapped CI 41.0-82.1) of participants within the same severity group. The average false detection of individual differences was 2.2%.

CONCLUSIONS

The majority of participants within the same depressive symptom severity group displayed differential symptom dynamics. Examining symptom dynamics provides information about person-specific psychopathological expression beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may be a promising new dimension for clinical characterisation, warranting replication in independent samples. To inform personalised treatment planning, a next step concerns linking different symptom relationship patterns to treatment response and clinical course, including patterns related to spontaneous recovery and forms of disorder progression.

Subgrouping with Chain Graphical VAR Models

Recent years have seen the emergence of an "idio-thetic" class of methods to bridge the gap between nomothetic and idiographic inference. These methods describe nomothetic trends in idiographic processes by pooling intraindividual information across individuals to inform group-level inference or vice versa. The current work introduces a novel "idio-thetic" model: the subgrouped chain graphical vector autoregression (scGVAR). The scGVAR is unique in its ability to identify subgroups of individuals who share common dynamic network structures in both lag(1) and contemporaneous effects. Results from Monte Carlo simulations indicate that the scGVAR shows promise over similar approaches when clusters of individuals differ in their contemporaneous dynamics and in showing increased sensitivity in detecting nuanced group differences while keeping Type-I error rates low. In contrast, a competing approach-the Alternating Least Squares VAR (ALS VAR) performs well when groups were separated by larger distances. Further considerations are provided regarding applications of the ALS VAR and scGVAR on real data and the strengths and limitations of both methods.

Coping, (mal)adaptive personality and identity in young adults: A network analysis

Coping, personality, and identity are three well-known constructs within the field of psychology. Yet, findings regarding how these constructs relate to each other have been inconsistent. The present study employs network analysis to investigate coping, adaptive and maladaptive personality, and identity and how they are related, using data from the Flemish Study on Parenting, Personality, and Development (FSPPD; Prinzie et al., 2003; 1999-current). Young adults (N = 457; 47% male), aged between 17-23 years old, completed a survey on coping, adaptive and maladaptive personality, and identity. Results indicate clear associations between coping and both adaptive and maladaptive personality within the network, suggesting coping and personality are distinct, yet highly related constructs whereas identity proved largely unrelated. Potential implications and suggestions for future research are discussed.

Prevalence of and risk factors for suicidal ideation in adolescents during the COVID-19 pandemic: a cross-sectional study

BACKGROUND AND OBJECTIVES

Pandemic-related life changes may have had a deleterious impact on suicidal behaviours. Early detection of suicidal ideation and identification of subgroups at increased risk could help prevent suicide, one of the leading causes of death among adolescents worldwide. Here, we aimed to investigate the prevalence of and risk factors for suicidal ideation in adolescents using a population-based sample from Switzerland, two years into the pandemic.

METHODS

Between December 2021 and June 2022, adolescents aged 14 to 17 years already enrolled in a population-based cohort study (State of Geneva, Switzerland) were asked about suicidal ideation over the previous year. In addition to a regression model, we conducted a network analysis of exposures which identified direct and indirect risk factors for suicidal ideation (i.e. those connected through intermediate risk factors) using mixed graphical models.

RESULTS

Among 492 adolescents, 14.4% (95% CI: 11.5-17.8) declared having experienced suicidal ideation over the previous year. Using network analysis, we found that high psychological distress, low self-esteem, identifying as lesbian, gay or bisexual, suffering from bullying, extensive screen time and a severe COVID-19 pandemic impact were major risk factors for suicidal ideation, with parent-adolescent relationship having the highest centrality strength in the network.

CONCLUSION

Our results show that a significant proportion of adolescents experience suicidal ideation, yet these rates are comparable with pre-pandemic results. Providing psychological support is fundamental, with a focus on improving parent-adolescent relationships.

The associations between daily reports of loneliness and psychotic experiences in the early risk stages for psychosis

AIM

Bi-directional associations between loneliness and psychotic experiences (PEs) have been reported, but the mechanisms underlying these associations are unknown. This study aims to explore associations between daily reports of loneliness and PEs, and test differences in this association across young adult individuals at different levels of risk for psychosis.

METHODS

We analysed 90-day diary data on loneliness and PEs from N = 96 participants (mean age 24.7, range 18-35, 77% female) divided into 4 subgroups, each indexing increased levels of risk for psychosis according to the clinical staging model: 'psychometric' (n = 25), 'low' (n = 27), 'mild' (n = 24), and 'ultra-high'(n = 20) risk. Multilevel vector autoregressive models examined within-day (contemporaneous) and between-day (temporal) associations between loneliness and PEs for the total sample. Next, these associations were compared across subgroups.

RESULTS

Loneliness and PEs were significantly associated contemporaneously (partial correlation B = 0.14) but not temporally. Subgroup membership moderated both contemporaneous and temporal associations. The contemporaneous association between loneliness and PEs was stronger in the low-risk subgroup compared to the mild-risk (B = -0.35, p < .01) and ultra-high-risk (B = -0.36, p < .01) subgroups. The temporal association between loneliness on the previous day and PEs on the current day was stronger in mild-risk subgroup compared to the ultra-high-risk subgroup (B = -0.03, p = .03). After adjusting for multiple testing, only the contemporaneous-but not the temporal-associations remained statistically significant.

CONCLUSIONS

Loneliness is associated with PEs in individuals at risk for psychosis, particularly in those with low to mild symptoms. Our findings tentatively suggest that especially individuals with low expressions of PEs may be more sensitive to social context, but future studies are needed to replicate and further unravel the potentially stage-specific interplay between social context and PEs.

A longitudinal network analysis of suicide risk factors among service members and veterans sampled for suicidal ideation or attempt

BACKGROUND

Suicidal thoughts and behaviors are elevated among active-duty service members (ADSM) and veterans compared to the general population. Hence, it is a priority to examine maintenance factors underlying suicidal ideation among ADSM and veterans to develop effective, targeted interventions. In particular, interpersonal risk factors, hopelessness, and overarousal have been robustly connected to suicidal ideation and intent.

METHODS

To identify the suicidal ideation risk factors that are most relevant, we employed network analysis to examine between-subjects (cross-sectional), contemporaneous (within seconds), and temporal (across four hours) group-level networks of suicidal ideation and related risk factors in a sample of ADSM and veterans (participant n = 92, observations n = 10 650). Participants completed ecological momentary assessment (EMA) surveys four times a day for 30 days, where they answered questions related to suicidal ideation, interpersonal risk factors, hopelessness, and overarousal.

RESULTS

The between-subjects and contemporaneous networks identified agitation, not feeling close to others, and ineffectiveness as the most central symptoms. The temporal network revealed that feeling ineffective was most likely to influence other symptoms in the network over time.

CONCLUSION

Our findings suggest that ineffectiveness, low belongingness, and agitation are important drivers of moment-to-moment and longitudinal relations between risk factors for suicidal ideation in ADSM and veterans. Targeting these symptoms may disrupt suicidal ideation.

The comorbid network characteristics of anxiety and depressive symptoms among Chinese college freshmen

BACKGROUND

This study aimed to investigate the interplay between anxiety and depressive symptoms in Chinese college freshmen using the causal system perspective (CSP), which differs from the traditional common cause perspective (CCP) by providing an alternative explanation by attributing comorbidity to direct interactions among symptoms.

METHODS

A convenience sample of 2,082 Chinese college freshmen (39.51% male, Mage = 18.61) from a normal university completed the Generalized Anxiety Disorder 7-Item Scale (GAD-7) and the Patient Health Questionnaire (PHQ-9). Network analysis was conducted and evaluated as to centrality, stability, node predictability, and bridging features. Moreover, the moderated network model (MNM) was utilized to detect the moderation effects of gender in the comorbidity network.

RESULTS

The network of anxiety and depressive symptoms exhibited stability, characterized by the core symptoms of "restlessness", "lack of energy", and "excessive worry about control", as well as the bridging symptoms of "fearfulness", "sad mood", and "irritability". Notably, the nodes representing "uncontrollable worry" and "difficulty in relaxation" demonstrated the highest predictive power. Gender did not exert any moderating effects on the anxiety and depressive symptom network.

CONCLUSION

These results reinforce that certain anxiety or depressive symptoms are more central than others, and thus play a more vital role in the comorbid network. These findings highlight underlying potential targeting symptoms to consider in future interventions.

Network Inference With the Lasso

Calculating confidence intervals and p-values of edges in networks is useful to decide their presence or absence and it is a natural way to quantify uncertainty. Since lasso estimation is often used to obtain edges in a network, and the underlying distribution of lasso estimates is discontinuous and has probability one at zero when the estimate is zero, obtaining p-values and confidence intervals is problematic. It is also not always desirable to use the lasso to select the edges because there are assumptions required for correct identification of network edges that may not be warranted for the data at hand. Here, we review three methods that either use a modified lasso estimate (desparsified or debiased lasso) or a method that uses the lasso for selection and then determines p-values without the lasso. We compare these three methods with popular methods to estimate Gaussian Graphical Models in simulations and conclude that the desparsified lasso and its bootstrapped version appear to be the best choices for selection and quantifying uncertainty with confidence intervals and p-values.

Psychological flexibility and cognitive-affective processes in young adults' daily lives

Psychological flexibility plays a crucial role in how young adults adapt to their evolving cognitive and emotional landscapes. Our study investigated a core aspect of psychological flexibility in young adults: adaptive variability and maladaptive rigidity in the capacity for behavior change. We examined the interplay of these elements with cognitive-affective processes within a dynamic network, uncovering their manifestation in everyday life. Through an Ecological Momentary Assessment design, we collected intensive longitudinal data over 3 weeks from 114 young adults ages 19 to 32. Using a dynamic network approach, we assessed the temporal dynamics and individual variability in flexibility in relation to cognitive-affective processes in this sample. Rigidity exhibited the strongest directed association with other variables in the temporal network as well as highest strength centrality, demonstrating particularly strong associations to other variables in the contemporaneous network. In conclusion, the results of this study suggest that rigidity in young adults is associated with negative affect and cognitions at the same time point and the immediate future.

Interrelatedness of Family and Parenting Risk Factors for Juvenile Delinquency: A Network Study in U.S. and Dutch Juveniles

Family interventions that address a diversity of family and parenting factors are often used to prevent juvenile delinquency, but are effective to only a limited extent. This study applied a network approach to risk factors for juvenile delinquency and examined the interrelatedness of specifically family and parenting risk factors in a U.S. and separate Dutch sample of juveniles and their family members. Differences in interrelatedness between these samples were examined as well. Secondary analyses were conducted on data collected in the United States with the Washington State Juvenile Court Assessment (WSJCA) and on data collected in the Netherlands with a Dutch-adapted translation of the WSJCA. Network analyses were performed, separately for the U.S. (N = 13,613) and Dutch (N = 3,630) sample, on seven risk factors that were assessed with a three-point Likert scale ranging from each factor's protective side to a corresponding risk side. In the U.S. sample network, "inadequate parental punishment" and "lack of parental supervision" that both refer to an authoritarian parenting style were the most "central" factors and had the strongest associations with the other risk factors. In the Dutch sample network, "the family not providing opportunities" and "inadequate parental reward" were the most "central" factors, which refer to an authoritative parenting style. The family and parenting factors identified as most central in the networks may be promising to address in family interventions, as it can be expected that both the directly addressed problems and their correlated problems will improve. The current results may inform attempts to strengthen family interventions for juvenile delinquency in the United States and the Netherlands.

Multilayer depressive symptom networks in adults with bodily pain living in precarious housing or homelessness

Housing insecurity is associated with co-occurring depression and pain interfering with daily activities. Network analysis of depressive symptoms along with associated risk or protective exposures may identify potential targets for intervention in patients with co-occurring bodily pain. In a community-based sample of adults (n = 408) living in precarious housing or homelessness in Vancouver, Canada, depressive symptoms were measured by the Beck Depression Inventory; bodily pain and impact were assessed with the 36-item Short Form Health Survey. Network and bootstrap permutation analyses were used to compare depressive symptoms endorsed by Low versus Moderate-to-Severe (Mod + Pain) groups. Multilayer networks estimated the effects of risk and protective factors. The overall sample was comprised of 78% men, mean age 40.7 years, with 53% opioid use disorder and 14% major depressive disorder. The Mod + Pain group was characterized by multiple types of pain, more persistent pain, more severe depressive symptoms and a higher rate of suicidal ideation. Global network connectivity did not differ between the two pain groups. Suicidal ideation was a network hub only in the Mod + Pain group, with high centrality and a direct association with exposure to lifetime trauma. Antidepressant medications had limited impact on suicidal ideation. Guilt and increased feelings of failure represented symptoms from two other communities of network nodes, and completed the shortest pathway from trauma exposure through suicidal ideation, to the non-prescribed opioid exposure node. Interventions targeting these risk factors and symptoms could affect the progression of depression among precariously housed patients.

Sleepiness should be reinvestigated through the lens of clinical neurophysiology: A mixed expertal and big-data Natural Language Processing approach

Historically, the field of sleep medicine has revolved around electrophysiological tools. However, the use of these tools as a neurophysiological method of investigation seems to be underrepresented today, from both international recommendations and sleep centers, in contrast to behavioral and psychometric tools. The aim of this article is to combine a data-driven approach and neurophysiological and sleep medicine expertise to confirm or refute the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness, despite the use of electrophysiological tools. Using Natural Language Processing methods, we analyzed the abstracts of the 18,370 articles indexed by PubMed containing the terms 'sleepiness' or 'sleepy' in the title, abstract, or keywords. For this purpose, we examined these abstracts using two methods: a lexical network, enabling the identification of concepts (neurophysiological or clinical) related to sleepiness in these articles and their interconnections; furthermore, we analyzed the temporal evolution of these concepts to extract historical trends. These results confirm the hypothesis that neurophysiology has declined in favor of behavioral or self-reported dimensions in sleep medicine for the investigation of sleepiness. In order to bring sleepiness measurements closer to brain functioning and to reintroduce neurophysiology into sleep medicine, we discuss two strategies: the first is reanalyzing electrophysiological signals collected during the standard sleep electrophysiological test; the second takes advantage of the current trend towards dimensional models of sleepiness to situate clinical neurophysiology at the heart of the redefinition of sleepiness.

The Mediating Role of Anxiety/Depression Between Auditory Verbal Hallucinations and the Level of Insight in Schizophrenia

OBJECTIVE

Auditory verbal hallucination (AVH) is a prominent symptom of schizophrenia causing profound distress. The influence of AVHs on insight appears to be intricate and contingent on other accompanying symptoms. This study investigated the relationship and possible mediators between AVHs and the degree of insight.

METHODS

One hundred patients with schizophrenia participated in the study. Scales were used to evaluate the hallucinatory experience, the level of insight and other psychopathology. Complex relationships between variables were envisaged as a path model, whose initial structure was constructed via Gaussian Graphical Model. The validity of the final model was verified by Structural Equation Modeling. Separate analyses were performed for self-reported and clinician-rated data to enhance the model's robustness.

RESULTS

The greater the severity of the physical aspects of AVHs, the lower the level of insight observed. Conversely, higher emotional distress was associated with increased insight. These relationships were only evident in the self-reported results and were not reflected in the clinician-rated results. The path model suggested that the Positive and Negative Syndrome Scale (PANSS) anxiety/depression factor was an important mediator that linked the found association. Notably, the PANSS negative symptom had the opposite effect on the PANSS anxiety/depression factor and insight, making it difficult to define its overall effect.

CONCLUSION

The findings of this study provided one possible route for the positive influence of AVH experience in gaining insight. The mediating role of anxiety/depression modified by negative symptoms emerged as a valuable concept for clarifying this intricate relationship.

Temporal network of experience sampling methodology identifies sleep disturbance as a central symptom in generalized anxiety disorder

BACKGROUND

A temporal network of generalized anxiety disorder (GAD) symptoms could provide valuable understanding of the occurrence and maintenance of GAD. We aim to obtain an exploratory conceptualization of temporal GAD network and identify the central symptom.

METHODS

A sample of participants (n = 115) with elevated GAD-7 scores (Generalized Anxiety Disorder 7-Item Questionnaire [GAD-7] ≥ 10) participated in an online daily diary study in which they reported their GAD symptoms based on DSM-5 diagnostic criteria (eight symptoms in total) for 50 consecutive days. We used a multilevel VAR model to obtain the temporal network.

RESULTS

In temporal network, a lot of lagged relationships exist among GAD symptoms and these lagged relationships are all positive. All symptoms have autocorrelations and there are also some interesting feedback loops in temporal network. Sleep disturbance has the highest Out-strength centrality.

CONCLUSIONS

This study indicates how GAD symptoms interact with each other and strengthen themselves over time, and particularly highlights the relationships between sleep disturbance and other GAD symptoms. Sleep disturbance may play an important role in the dynamic development and maintenance process of GAD. The present study may develop the knowledge of the theoretical model, diagnosis, prevention and intervention of GAD from a temporal symptoms network perspective.

How are irritability and anhedonia symptoms linked? A network approach

BACKGROUND

Anhedonia and irritability are two prevalent symptoms of major depressive disorder (MDD) that predict greater depression severity and poor outcomes, including suicidality. Although both symptoms have been proposed to result from paradoxical reward processing dysfunctions, the interactions between these symptoms remain unclear. Anhedonia is a multifaceted symptom reflecting impairments in multiple dimensions of reward processing (e.g., pleasure, desire, motivation, and effort) across distinct reward types (e.g., food, sensory experiences, social activities, hobbies) that may differentially interact with irritability. This study investigated the complex associations between anhedonia and irritability using network analysis.

METHOD

Participants (N = 448, Mage = 33.29, SD = 14.58) reported their symptoms of irritability on the Brief Irritability Test (Holtzman et al., 2015) and anhedonia (i.e., pleasure, desire, motivation, and effort dimensions across four reward types) on the Dimensional Anhedonia Rating Scale (Rizvi et al., 2015). A regularized Gaussian Graphical Model was built to estimate the network structure between items.

RESULTS

Irritability was negatively related to willingness to expand effort to obtain food/drinks (estimate = -0.18), social activities (-0.13), and hobbies (-0.12) rewards. Irritability was positively associated with a desire for food/drinks (0.12).

LIMITATIONS

Only a small proportion (5.8%) of our sample was clinical and the study design was cross-sectional.

CONCLUSION

A specific link between irritability and the effort dimension of the hedonic response across three reward types was identified. Investigating effort expenditure deficits with experimental paradigms may help us understand the mechanisms underlying the comorbidity between irritability and anhedonia in the context of MDD.

Fear of disease in patients with epilepsy - a network analysis

Background

Disease-related fear among patients with epilepsy has significantly impacted their quality of life. The Disease-Related Fear Scale (D-RFS), comprising three dimensions, serves as a relatively well-established tool for assessing fear in these patients. However, certain problems potentially exist within the D-RFS's attribution of items, and its internal structure is still unclear. To establish an appropriate dimensional structure and gain deeper comprehension of its internal structure-particularly its core variables-is vital for developing more effective interventions aimed at alleviating disease-related fear among patients with epilepsy.

Methods

This study employed a cross-sectional survey involving 609 patients with epilepsy. All participants underwent assessment using the Chinese version of the D-RFS. We used exploratory network analysis to discover a new structure and network analysis to investigate the interrelationships among fear symptom domains. In addition to the regularized partial correlation network, we also estimated the node and bridge centrality index to identify the importance of each item within the network. Finally, it was applied to analyze the differences in network analysis outcomes among epilepsy patients with different seizure frequencies.

Results

The research findings indicate that nodes within the network of disease-related fear symptoms are interconnected, and there are no isolated nodes. Nodes within groups 3 and 4 present the strongest centrality. Additionally, a tight interconnection exists among fear symptoms within each group. Moreover, the frequency of epileptic episodes does not significantly impact the network structure.

Conclusion

In this study, a new 5-dimension structure was constructed for D-RFS, and the fear of disease in patients with epilepsy has been conceptualized through a network perspective. The goal is to identify potential targets for relevant interventions and gain insights for future research.

The Role of Anxiety and Depression in Shaping the Sleep-Pain Connection in Patients with Nonspecific Chronic Spinal Pain and Comorbid Insomnia: A Cross-Sectional Analysis

(1) Background: This exploratory study aims to explore the relationship between nonspecific chronic spinal pain (nCSP) and insomnia symptoms, by examining the interconnections, strengths, and directional dependence of the symptoms. In addition, we aim to identify the key symptoms of the nCSP-insomnia relationship and shed light on the bidirectional nature of this relationship. (2) Methods: This study is a secondary analysis of the baseline data (cross-sectional) from a randomized controlled trial, which examined the added value of Cognitive Behavioral Therapy for Insomnia (CBT-I) combined with cognition-targeted exercise therapy, conducted in collaboration with the Universiteit Gent and Vrije Universiteit Brussel (Belgium). One hundred and twenty-three nCSP patients with comorbid insomnia were recruited through the participating hospitals, advertisements, announcements in local newspapers, pharmacies, publications from support groups, and primary care. To explore the interconnections and directionality between symptoms and the strengths of the relationships, we estimated a regularized Gaussian graphical model and a directed acyclic graph. (3) Results: We found only one direct, but weak, link between sleep and pain, namely, between average pain and difficulties maintaining sleep. (4) Conclusions: Despite the lack of strong direct links between sleep and pain, pain and sleep seem to be indirectly linked via anxiety and depression symptoms, acting as presumable mediators in the network of nCSP and comorbid insomnia. Furthermore, feeling slowed down and fatigue emerged as terminal nodes, implying their role as consequences of the network.

A Network Study of Family Affect Systems in Daily Life

Adolescence is a time period characterized by extremes in affect and increasing prevalence of mental health problems. Prior studies have illustrated how affect states of adolescents are related to interactions with parents. However, it remains unclear how affect states among family triads, that is adolescents and their parents, are related in daily life. This study investigated affect state dynamics (happy, sad, relaxed, and irritated) of 60 family triads, including 60 adolescents (Mage = 15.92, 63.3% females), fathers and mothers (Mage = 49.16). The families participated in the RE-PAIR study, where they reported their affect states in four ecological momentary assessments per day for 14 days. First, we used multilevel vector-autoregressive network models to estimate affect dynamics across all families, and for each family individually. Resulting models elucidated how family affect states were related at the same moment, and over time. We identified relations from parents to adolescents and vice versa, while considering family variation in these relations. Second, we evaluated the statistical performance of the network model via a simulation study, varying the percentage missing data, the number of families, and the number of time points. We conclude with substantive and statistical recommendations for future research on family affect dynamics.

The association between team cohesion and performance: A network analysis of nurses

Team cohesion, as a necessary condition for the cooperation and development of a team, has been shown to have a strong association with team performance. However, the mechanism of this internal correlation is unclear and more in-depth studies are lacking. The study aimed to explore the complex links between the dimensions of team cohesion and performance in nurses. A total of 1639 practice nurses from 118 nursing teams were included in this cross-sectional study. Data were collected using the Team Cohesion Scale (including consistency of affection, behavior, and cognition) and the Team Effectiveness Scale (including cooperation satisfaction, and task performance). Using network analysis, the team cohesion and performance network was constructed, and the strength and bridge strength of nodes were calculated. The results showed that the edges between team cohesion and performance dimensions were all positively correlated. Cooperation satisfaction and consistency of affection are the core variables in the network. Interventions targeting cooperation satisfaction and consistency of affection need to be developed at the team level to maximize team cohesion and performance among nurses.

Improving the Walktrap Algorithm Using K-Means Clustering

The walktrap algorithm is one of the most popular community-detection methods in psychological research. Several simulation studies have shown that it is often effective at determining the correct number of communities and assigning items to their proper community. Nevertheless, it is important to recognize that the walktrap algorithm relies on hierarchical clustering because it was originally developed for networks much larger than those encountered in psychological research. In this paper, we present and demonstrate a computational alternative to the hierarchical algorithm that is conceptually easier to understand. More importantly, we show that better solutions to the sum-of-squares optimization problem that is heuristically tackled by hierarchical clustering in the walktrap algorithm can often be obtained using exact or approximate methods for K-means clustering. Three simulation studies and analyses of empirical networks were completed to assess the impact of better sum-of-squares solutions.

When eco-anger (but not eco-anxiety nor eco-sadness) makes you change! A temporal network approach to the emotional experience of climate change

Research on the emotional experience of climate change has become a hot topic. Yet uncertainties remain regarding the interplay between climate change-related emotions (i.e., eco-anxiety, eco-anger, eco-sadness), general emotions (i.e., regardless of climate change), and pro-environmental behaviors. Most previous research has focused on cross-sectional studies, and eco-emotions in everyday life have seldom been considered. In this preregistered study, 102 participants from the general population rated their eco-emotions (i.e., eco-anxiety, eco-anger, eco-sadness), general emotions (i.e., anxiety, anger, sadness), and pro-environmental intentions and behaviors daily over a 60-day period. Using a multilevel vector autoregressive approach, we computed three network models representing temporal (i.e., from one time-point to the next), contemporaneous (i.e., during the same time-frame), and between-subject (i.e., similar to cross-sectional approach) associations between variables. Results show that eco-anger was the only predictor of pro-environmental intentions and behaviors over time. At the contemporaneous level, the momentary experience of each eco-emotion was associated with the momentary emotional experience of the corresponding general emotion, indicating the distinctiveness of each eco-emotion and the correspondence between its experience and that of its general, non-climate-related emotion. Overall, our findings 1) emphasize the driving role of eco-anger in prompting pro-environmental behaviors over time, 2) suggest a functional and experiential distinction between eco-emotions, and 3) provide data-driven clues for the field's larger quest to establish the scientific foundations of eco-emotions.

Clinical and psychological implications of post-traumatic stress in firefighters: a moderated network study

Firefighters are frequently exposed to trauma and may experience a unique symptom presentation of post-traumatic stress. Prior research has identified stronger associations between certain post-traumatic stress symptoms (e.g. detachment, intrusions, physiological reactivity) using network analysis. However, little is known about the effects of symptom severity and emergency work-related trauma on symptom networks. The present study probed the network structure of post-traumatic stress symptoms in trauma-exposed firefighters (N = 871) to model the dynamic interactions of psychological symptoms. We developed a network of post-traumatic stress symptoms and a network of post-traumatic stress with clinical covariates and used moderated network modelling to assess the effects of having PTSD and experiencing work-related trauma on the networks. We identified high edge correlations between several nodes (e.g. startle/hypervigilance, internal/external cue avoidance, detachment/lack of interest) and high centrality of detachment, external cue avoidance, and flashbacks. Additionally, having PTSD moderated positive network associations between risk-taking and suicidality and between distorted blame and post-traumatic cognitions. Work-related trauma moderated negative associations between appetite gain and loss and appetite loss and suicidality. Findings suggest that targeting specific symptoms of detachment, external cue avoidance, and flashbacks could allow for the development of effective trauma-informed interventions for these populations.

Skewness and Staging: Does the Floor Effect Induce Bias in Multilevel AR(1) Models?

Multilevel autoregressive models are popular choices for the analysis of intensive longitudinal data in psychology. Empirical studies have found a positive correlation between autoregressive parameters of affective time series and the between-person measures of psychopathology, a phenomenon known as the staging effect. However, it has been argued that such findings may represent a statistical artifact: Although common models assume normal error distributions, empirical data (for instance, measurements of negative affect among healthy individuals) often exhibit the floor effect, that is response distributions with high skewness, low mean, and low variability. In this paper, we investigated whether-and to what extent-the floor effect leads to erroneous conclusions by means of a simulation study. We describe three dynamic models which have meaningful substantive interpretations and can produce floor-effect data. We simulate multilevel data from these models, varying skewness independent of individuals' autoregressive parameters, while also varying the number of time points and cases. Analyzing these data with the standard multilevel AR(1) model we found that positive bias only occurs when modeling with random residual variance, whereas modeling with fixed residual variance leads to negative bias. We discuss the implications of our study for data collection and modeling choices.

Sex differences in symptom network structure of depression, anxiety, and self-efficacy among people with diabetes: a network analysis

Aims

The present study aims to explore the relations between symptoms of depression and anxiety and self-efficacy among people with diabetes. At the same time, we also examined the sex difference between network structures.

Methods

This study recruited 413 participants with diabetes, and they completed Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire (PHQ-9), and the Self-efficacy for Diabetes (SED). Symptom network analysis and network comparison test were used to construct and compare the depression-anxiety symptom network models of the female and male groups. Finally, we conducted flow diagrams to explore the symptoms directly or indirectly related to self-efficacy.

Results

The strongest edges in the depression-anxiety symptom networks are the edge between "GAD3" (Excessive worry) and "GAD4" (Trouble relaxing) and the edge between "PHQ1" (Anhedonia) and "PHQ4" (Energy) in the female and male groups, respectively. Most of the symptoms with the highest EI and bridge EI are related to worry and nervousness. Additionally, in the flow diagram of the female group, "PHQ6" (Guilt) has a high negative association with self-efficacy.

Conclusion

Females with diabetes are more vulnerable to depression and anxiety. Interventions targeting key symptoms in the network may be helpful in relieving the psychological problems among people with diabetes.

Effects of empathy on the bidirectional relationships between problematic smartphone use and aggression among secondary school students: a moderated network approach

Background

Existing literature on the relationship between problematic smartphone use (PSU) and aggression has primarily focused on examining their unidirectional association, with limited attention paid to the bidirectional nature of this relationship, particularly when considering the role of empathy. This study employs a novel moderated network approach to examine the bidirectional relationship between problematic smartphone use and aggression, while also investigating the moderating mechanism of empathy.

Methods

A total of 2,469 students (49.1% female, Mean age = 13.83, SD age = 1.48) from 35 junior and senior high schools in Harbin, China, participated in this study. Empathy level, aggressiveness, and PSU symptoms were assessed using the Basic Empathy Scale, the Buss-Warren Aggression Questionnaire, and the Mobile Phone Addiction Index.

Results

Analysis revealed that the relationship between PSU and aggression was complex and bidirectional. The strongest association was observed between "hostility" and "withdrawal/escape". In addition, "anger" had the highest Expected Influence (EI) in both affective and cognitive moderate network models. An important discovery was also made regarding the conditional effect of "productive loss" and "physical aggression" across different levels of affective empathy. Specifically, at lower levels of affective empathy, a positive bidirectional relationship was found between "productive loss" and "physical aggression". However, this relationship turned negative and bidirectional at higher levels of affective empathy.

Conclusion

The findings contribute to a more comprehensive understanding of the complex dynamics between PSU and aggression and highlight the need for targeted interventions that promote affective empathy to mitigate the negative consequences of excessive smartphone use.

The Role of Ageist Sexual Stereotypes in the Network of Sexual Difficulties, Sex and Relationship Satisfaction Among Adults Aged 50

As people age, their sexual activity, including sexual and relationship satisfaction, may change due to the onset of health and sexual difficulties and the activation of internalized ageist sexual stereotypes. We studied whether ageist sexual stereotypes were relevant for the importance of sex for people aged 50+ and how sexual and relationship satisfaction are interlinked with health and sexual difficulties when ageist sexual stereotypes are considered. Data for the network analysis were collected from a sample of 897 Czechs and Slovaks aged 50-96 (52% men, mean age = 62.01). Two models were analyzed - with and without the inclusion of ageist sexual stereotypes. The findings indicated that ageist sexual stereotypes play an important role in the sexuality of women and men aged 50 + .The fewer ageist sexual stereotypes people had, the less sexual difficulties they reported and the more they perceived sex as important. The inclusion of stereotypes into the models, however, weakened the negative link between sexual difficulties and the importance of sex for both women and men. These findings show that the effect of ageist sexual stereotypes are likely complex in the sexual lives of people aged 50 +.

The dynamics of psychological attributes and symptomatic comorbidity of depression in children and adolescents

PURPOSE

This investigation aimed to explore attribute dynamics and symptomatic comorbidity of depression with internalizing, externalizing, and other personal-contextual problems in children and adolescents from a network analysis.

METHODS

We tested an attribute network of regularized partial correlations, standard and alternative centrality measures, and comorbidity bridge symptoms according to centrality bridge measures.

RESULTS

Regularized partial correlation network and a centrality measures graph shown the prominent position of social problems and anxiety-depression. Minimum spanning tree (MST) found a hierarchical dynamics between attributes where mixed anxiety-depression was identified as the core and the other attributes were hierarchically connected to it by being positioned in six branches that are differentiated according to their theoretical contents. The most central connections are established with the attributes of their own community or theoretical groups, and 37 bridge symptoms were identified in all networks.

CONCLUSIONS

A significant role of mixed anxiety depression as an activator and intermediary of psychopathologies was supported as a central attribute of internalizing problems. Aggressive behavior as part of the broad externalizing dimension was one of the constructs that most intensively activate the network, and social problems were also distinguished as a relevant factor not only in terms of connections and central attributes but also in terms of bridge symptoms and comorbidity. This framework extends to the study of symptomatic "comorbidity."

The network dynamics of self-compassion components and psychological symptoms during an intervention

The change process of psychological interventions is complex and should be understood with a systems perspective. This study sought to examine the network dynamics of self-compassion components and psychological symptoms during an intervention. A total of 139 participants completed daily assessments during a 28-day intervention. Utilizing multilevel vector autoregressive (VAR) model, temporal and contemporaneous networks were generated and group differences in network dynamics were evaluated through descriptive assessment and permutation tests. The intervention group displayed a significant increase in self-compassion and decrease in psychological symptoms, with self-compassion mediating the intervention effects on symptoms. Network analysis revealed some network dynamics that might be relevant to desirable therapeutic changes in the intervention group. The intervention group demonstrated a significantly less connected contemporaneous depression network, indicating a decreased vulnerability to symptom activation. Additionally, the intervention group showed significantly more temporal connections from self-compassion to anxiety, indicating an increased influence of self-compassion on anxiety. These findings suggest that the intervention may have reshaped the interconnection pattern of symptoms and that between self-compassion components and symptoms.

A novel approach for constructing personalized networks from longitudinal perceived causal relations

Personalized networks of psychological symptoms aim to advance therapy by identifying treatment targets for specific patients. Statistical relations in such networks can be estimated from intensive longitudinal data, but their causal interpretation is limited by strong statistical assumptions. An alternative is to create networks from patient perceptions, which comes with other limitations such as retrospective bias. We introduce the Longitudinal Perceived Causal Problem Networks (L-PECAN) approach to address both these concerns. 20 participants screening positive for depression completed 4 weeks day of brief daily assessments of perceived symptom interactions. Quality criteria of this new method are introduced, answering questions such as "Which symptoms should be included in networks?", "How many datapoints need to be collected to achieve stable networks?", and "Does the network change over time?". Accordingly, about 40% of respondents achieved stable networks and only few respondents exhibited network structure that changed during the assessment period. The method was time-efficient (on average 7.4 min per day), and well received. Overall, L-PECAN addresses several of the prevailing issues found in statistical networks and therefore provides a clinically meaningful method for personalization.

Dynamic Individual Risk Networks: Personalized Network Modelling Based on Experience Sampling Data

Following a network perspective, risk of sexual reoffending can be understood as a construct that emerges from the interactions between risk factors. If these interrelationships are validly mapped out, this leads to an increased understanding of the risk and thus may contribute to more effective and/or more efficient interventions. This paper reports on personalized network modeling mapping the interrelationships of dynamic risk factors for an individual convicted of sexual offenses, using experience sampling (ESM) based on Stable-2007 items. The longitudinal character of ESM enables both the assessment of interrelations between risk factors within a timeframe and the relationships between risk factors over time. Networks are calculated and compared to the clinical assessment of interrelationships between the risk factors.

White matter and literacy: A dynamic system in flux

Cross-sectional studies have linked differences in white matter tissue properties to reading skills. However, past studies have reported a range of, sometimes conflicting, results. Some studies suggest that white matter properties act as individual-level traits predictive of reading skill, whereas others suggest that reading skill and white matter develop as a function of an individual's educational experience. In the present study, we tested two hypotheses: a) that diffusion properties of the white matter reflect stable brain characteristics that relate to stable individual differences in reading ability or b) that white matter is a dynamic system, linked with learning over time. To answer these questions, we examined the relationship between white matter and reading in a five-year longitudinal dataset and a series of large-scale, single-observation, cross-sectional datasets (N = 14,249 total participants). We find that gains in reading skill correspond to longitudinal changes in the white matter. However, in the cross-sectional datasets, we find no evidence for the hypothesis that individual differences in white matter predict reading skill. These findings highlight the link between dynamic processes in the white matter and learning.

Clarifying directional dependence among measures of early auditory processing and cognition in schizophrenia: leveraging Gaussian graphical models and Bayesian networks

BACKGROUND

Research using latent variable models demonstrates that pre-attentive measures of early auditory processing (EAP) and cognition may initiate a cascading effect on daily functioning in schizophrenia. However, such models fail to account for relationships among individual measures of cognition and EAP, thereby limiting their utility. Hence, EAP and cognition may function as complementary and interacting measures of brain function rather than independent stages of information processing. Here, we apply a data-driven approach to identifying directional relationships among neurophysiologic and cognitive variables.

METHODS

Using data from the Consortium on the Genetics of Schizophrenia 2, we estimated Gaussian Graphical Models and Bayesian networks to examine undirected and directed connections between measures of EAP, including mismatch negativity and P3a, and cognition in 663 outpatients with schizophrenia and 630 control participants.

RESULTS

Chain structures emerged among EAP and attention/vigilance measures in schizophrenia and control groups. Concerning differences between the groups, object memory was an influential variable in schizophrenia upon which other cognitive domains depended, and working memory was an influential variable in controls.

CONCLUSIONS

Measures of EAP and attention/vigilance are conditionally independent of other cognitive domains that were used in this study. Findings also revealed additional causal assumptions among measures of cognition that could help guide statistical control and ultimately help identify early-stage targets or surrogate endpoints in schizophrenia.

Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Background

The move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidities. The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide potential targets for prevention and intervention for depression and anxiety.

Methods

This study used a cross-sectional design with data from the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depressive and anxiety symptoms was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Depressive and anxiety symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Seven-Item Generalized Anxiety Disorder Scale (GAD-7), respectively. Expected influence (EI) and bridge expected influence (BEI) indices were calculated for each symptom.

Results

According to cutoff scores indicating the presence of depression and anxiety, the prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. "Feeling blue/depressed", "Nervousness or anxiety", "Uncontrollable worry", "Trouble relaxing", and "Worry too much" had the highest EI values. "Nervousness or anxiety" and "Everything was an effort" exhibited the highest BEI values.

Conclusion

Central and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or currently have depressive and anxiety symptoms.

New psychometric evidence from the Revised Mental Health Inventory (R-MHI-5) in Peruvian adolescents from a network psychometrics approach

BACKGROUND

Mental health is an aspect that has been relegated in recent years, prioritizing physical health care. However, there are more and more mental problems and disorders worldwide. In this context, adolescents are considered at risk for developing psychological difficulties due to the important transition stage they are going through. Given this, an adequate measurement of mental health in the adolescent population is necessary. This research aims to evaluate the internal structure and estimate the reliability of the R-MHI-5.

METHOD

The sample covered 662 adolescents (55.2% men and 44.7% women) aged 12 to 17 years (M = 14.5; SD = 1.6).

RESULTS

Exploratory graph analysis revealed a two-dimensional structure encompassing well-being and psychological distress. Furthermore, confirmatory factor analysis results indicated that a model with two related factors demonstrated superior fit indices (CFI = 0.99; TLI = 0.99; SRMR = 0.04; RMSEA = 0.101) in comparison to a one-dimensional model (CFI = 0.85; TLI = 0.71; SRMR = 0.23; RMSEA = 0.451). Additionally, adequate values were found in the reliability of the dimensions.

CONCLUSION

It is concluded that the R-MHI-5 is an instrument with robust psychometric evidence from the perspective of the EGA and CFA, providing adequate evidence of reliability and validity so that it can be used effectively in future research and prevention and intervention processes. Furthermore, our study is the first to provide psychometric evidence of the scale from a media approach in Peruvian adolescents.

Exploring Interrelationships between Mental Health Symptoms and Cognitive Impairment in Aging People Living with HIV in China

INTRODUCTION

Mental health symptoms and cognitive impairment are highly prevalent and intertwined among aging people living with HIV (PLWH). This study aimed to assess the interrelationships and strength of connections between individual mental health symptoms and cognitive impairment. We sought to identify specific symptoms linking mental health and cognitive impairment in aging PLWH.

METHODS

Participants in the Sichuan Older People with HIV Infections Cohort Study (SOHICS) were recruited between November 2018 and April 2021 in China. Mental health symptoms, including depression and anxiety, were assessed by the Patient Health Questionnaire (PHQ-9) and General Anxiety Disorder-7 (GAD-7), respectively. Cognitive impairment was assessed by the Montreal Cognitive Assessment-Basic (MoCA-B). Partial correlation networks were used to depict the interrelationships between mental health symptoms and cognitive impairment, and bridge strength was used to identify specific symptoms linking mental health and cognitive impairment.

RESULTS

Of the 1,587 recruited participants with a mean age of 63.0 years old, 47.0% had mild or severe cognitive impairment. Network analysis revealed that cognitive function, visual perception, and problem-solving task of the MoCA-B were negatively correlated with appetite, energy, and motor of the PHQ-9, respectively. Based on their interrelationships, problem-solving task and motor acted as bridge symptoms.

CONCLUSION

Problem-solving task and motor may be potential intervention targets to reduce the overall risk of mental health symptoms and cognitive impairment. Future research could assess the feasibility and effectiveness of specific interventions designed for the two symptoms of aging PLWH.