The network of stress-related states and depression and anxiety symptoms during the COVID-19 lockdown

Depression, anxiety, and insomnia symptoms among Chinese college students: A network analysis across pandemic stages

BACKGROUND

As the stages of the COVID-19 pandemic evolved, the symptoms of depression, anxiety, and insomnia have increasingly manifested among Chinese college students. The aim of this study is to investigate the relationships between these symptoms through network analysis among Chinese college students during COVID-19.

METHOD

A three-wave cross-sectional survey was conducted at 22 colleges in Guangdong Province, involving 381,152 students during three specific time intervals: T1 (baseline, February 3 to 10, 2020), T2 (19 months after baseline, June 10 to 18, 2021), and T3 (37 months after baseline, March 15 to April 22, 2023). Depression (PHQ-9), anxiety (GAD-7), and insomnia (YSIS) were used separately. We analyzed two key network indices: "Expected influence" and "Bridge expected influence". Network stability was assessed through a case-dropping bootstrap program.

RESULT

The effective sample sizes for the three periods were as follows: T1 - 164,101 (103,645 females, 63.2 %), T2 - 86,767 (52,146 females, 60.1 %), and T3 - 130,284 (76,720 females, 58.9 %). Across these three periods, the key central symptoms were "Fatigue" (PHQ4), "Restlessness" (GAD5), "Uncontrollable worrying" (GAD2), "Worry too much" (GAD3) and "Sleep insufficiency" (YSIS6). Notably, "Fatigue" (PHQ4), "Restlessness" (GAD5) and "Irritability" (GAD6) consistently served as bridge symptoms. In the T1 and T2 period, "Motor" (PHQ8) acted as a bridge symptom but weakened in T3.

CONCLUSION

Throughout the three periods, the mental health issues among Chinese college students displayed characteristics of somatization within the depression-anxiety-insomnia comorbidity network. Over time, anxiety symptoms appeared to become more prominent. Consequently, this study highlights the importance of accurately identifying and promptly intervening in these core symptoms of mental health among college students, as these symptoms may evolve across different stages of a pandemic.

A systematic review on the relationship between socioeconomic conditions and emotional disorder symptoms during Covid-19: unearthing the potential role of economic concerns and financial strain

BACKGROUND

Covid-19 has disrupted the lives of many and resulted in high prevalence rates of mental disorders. Despite a vast amount of research into the social determinants of mental health during Covid-19, little is known about whether the results are consistent with the social gradient in mental health. Here we report a systematic review of studies that investigated how socioeconomic condition (SEC)-a multifaceted construct that measures a person's socioeconomic standing in society, using indicators such as education and income, predicts emotional health (depression and anxiety) risk during the pandemic. Furthermore, we examined which classes of SEC indicators would best predict symptoms of emotional disorders.

METHODS

Following PRISMA guidelines, we conducted search over six databases, including Scopus, PubMed, etc., between November 4, 2021 and November 11, 2021 for studies that investigated how SEC indicators predict emotional health risks during Covid-19, after obtaining approval from PROSPERO (ID: CRD42021288508). Using Covidence as the platform, 362 articles (324 cross-sectional/repeated cross-sectional and 38 longitudinal) were included in this review according to the eligibility criteria. We categorized SEC indicators into 'actual versus perceived' and 'static versus fluid' classes to explore their differential effects on emotional health.

RESULTS

Out of the 1479 SEC indicators used in these 362 studies, our results showed that 43.68% of the SEC indicators showed 'expected' results (i.e., higher SEC predicting better emotional health outcomes); 51.86% reported non-significant results and 4.46% reported the reverse. Economic concerns (67.16% expected results) and financial strains (64.16%) emerged as the best predictors while education (26.85%) and living conditions (30.14%) were the worst.

CONCLUSIONS

This review summarizes how different SEC indicators influenced emotional health risks across 98 countries, with a total of 5,677,007 participants, ranging from high to low-income countries. Our findings showed that not all SEC indicators were strongly predictive of emotional health risks. In fact, over half of the SEC indicators studied showed a null effect. We found that perceived and fluid SEC indicators, particularly economic concerns and financial strain could best predict depressive and anxiety symptoms. These findings have implications for policymakers to further understand how different SEC classes affect mental health during a pandemic in order to tackle associated social issues effectively.

Network analysis of anxiety and depressive symptoms during the COVID-19 pandemic in older adults in the United Kingdom

The health crisis caused by COVID-19 in the United Kingdom and the confinement measures that were subsequently implemented had unprecedented effects on the mental health of older adults, leading to the emergence and exacerbation of different comorbid symptoms including depression and anxiety. This study examined and compared depression and anxiety symptom networks in two specific quarantine periods (June-July and November-December) in the older adult population in the United Kingdom. We used the database of the English Longitudinal Study of Aging COVID-19 Substudy, consisting of 5797 participants in the first stage (54% women) and 6512 participants in the second stage (56% women), all over 50 years of age. The symptoms with the highest centrality in both times were: "Nervousness (A1)" and "Inability to relax (A4)" in expected influence and predictability, and "depressed mood (D1"; bridging expected influence). The latter measure along with "Irritability (A6)" overlapped in both depression and anxiety clusters in both networks. In addition, a the cross-lagged panel network model was examined in which a more significant influence on the direction of the symptom "Nervousness (A1)" by the depressive symptoms of "Anhedonia (D6)", "Hopelessness (D7)", and "Sleep problems (D3)" was observed; the latter measure has the highest predictive capability of the network. The results report which symptoms had a higher degree of centrality and transdiagnostic overlap in the cross-sectional networks (invariants) and the cross-lagged panel network model of anxious and depressive symptomatology.

In-Person Social Interactions and Anxiety During the COVID-19 Pandemic: Exploring the Role of Household Size and Virtual Social Contact Among Midlife and Older Black South African Adults

OBJECTIVES

The current study investigates how physical distancing during the coronavirus disease 2019 (COVID-19) pandemic was associated with increased anxiety among a cohort of midlife older Black South African adults and the extent to which household size and virtual social contact modify this association for men and women.

METHODS

We analyze data from a phone survey conducted from July 2021 to March 2022 as part of Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (n = 2,080). We employ logistic regression to estimate the association between changes in in-person social interactions and anxiety symptoms and examine whether the association is modified by household size and changes in virtual social contact. We perform analyses separately for women and men.

RESULTS

Declines in in-person social interactions were associated with increased anxiety for women and men (odds ratios [OR] = 2.52, p < .001). For women only, declines were greater for those living in larger households (OR = 1.11, p = .032). Declines were buffered by increased virtual social contact for both women (OR = 0.55, p = .025) and men (OR = 0.45, p = .019).

DISCUSSION

Although the anxiety symptoms of women and men were similarly affected by declines in in-person social interaction, the modifying influence of household size is unique to women, likely due to gender-specific social roles. For women, living in larger households may mean greater caregiving burden, exacerbating the detrimental association between physical distancing and anxiety. On the other hand, both women and men may have used virtual means to connect with friends and family living outside their homes, buffering against increased anxiety.

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.

Relationships between psychopathological symptoms, pandemic-related stress, perceived social support, and COVID-19 infection history: a network analysis in Chinese college students

Introduction

Previous coronavirus, 2019 (COVID-19) research has applied network analysis to examine relationships between psychopathological symptoms but rarely extended to potential risk and protective factors or the influence of COVID-19 infection history. This study examined complex inter-relationships between psychopathological symptoms, COVID-19-related stressors, perceived social support, and COVID-19 infection history among Chinese university/college students during the peak of fifth pandemic wave using a network analysis approach.

Methods

A Least Absolute Shrinkage and Selection Operator-regularized partial correlation network using Gaussian graphical model was constructed in 1,395 Chinese university/college students in Hong Kong who completed a survey between 15 March and 3 April, 2022. Depressive, anxiety, and acute/traumatic stress symptoms were measured by Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Impact of Event Scale-6, respectively. COVID-19-related stressors and perceived social support were measured. Network differences by COVID-19 infection history (COVID-network vs. no_COVID-network) and network communities were examined.

Results

Our results showed that the most influential nodes were depressed mood, uncontrollable worries, and uncontrollable thoughts about COVID-19. The main bridging symptoms were concentration problems and psychomotor problems. The COVID-network, comprising participants with a history of COVID-19 infection only, was significantly stronger than the no_COVID-network. Perceived social support and stress from conflicts with family/friends formed a unique community with negative cognition and suicidal idea in the COVID-network only.

Conclusion

Our findings indicate that specific interventions targeting interpersonal conflicts and concentration problems as well as facilitating stress buffering effects of social support may represent effective strategies to reduce psychological distress in university/college students during COVID-19 and should be considered for future pandemic preparedness.

Depressive symptoms and loneliness among early adolescents: a psychometric network analysis approach

BACKGROUND

Previous studies demonstrate a high prevalence of depression and loneliness among adolescents. Although they often co-occur, the relationship between symptoms of depression and loneliness remains poorly understood. This study investigates: (a) the symptoms of depression that are connected to loneliness; (b) the role played by loneliness in the network of depression symptoms; and (c) whether the method used to measure loneliness (single-item direct or multi-item indirect) affects the relationship of loneliness with depressive symptoms.

METHODS

Participants were 496 Polish adolescents (50.8% girls) aged 11 to 13, who completed: (a) the 10-item Major Depressive Disorder subscale of the Revised Child Anxiety and Depression Scale; (b) the 11-item De Jong Gierveld Loneliness Scale (indirect loneliness), and (c) a single direct question evaluating loneliness: 'I'm lonely'. Networks were estimated using a Gaussian Graphical Model.

RESULTS

Loneliness shows a direct relationship with three affective symptoms of depression: sadness, worthlessness, and anhedonia, which mediate relationships with somatic symptoms. In contrast to previous studies, loneliness has the lowest level of centrality among all elements of the network. The method used to assess loneliness did not significantly affect the connections between loneliness and depressive symptoms.

CONCLUSIONS

Loneliness and depression overlap since they are formed by the same cognitive biases and deficits in emotion regulation but differ in the level of generality. In loneliness, they have an interpersonal context, while symptoms of depression can be intrapersonal. This helps us to understand why cognitive interventions, as compared to those which are social, are more effective in reducing loneliness.

A network model of depressive and anxiety symptoms: a statistical evaluation

BACKGROUND

Although network analysis studies of psychiatric syndromes have increased in recent years, most have emphasized centrality symptoms and robust edges. Broadening the focus to include bridge symptoms within a systematic review could help to elucidate symptoms having the strongest links in network models of psychiatric syndromes. We conducted this systematic review and statistical evaluation of network analyses on depressive and anxiety symptoms to identify the most central symptoms and bridge symptoms, as well as the most robust edge indices of networks.

METHODS

A systematic literature search was performed in PubMed, PsycINFO, Web of Science, and EMBASE databases from their inception to May 25, 2022. To determine the most influential symptoms and connections, we analyzed centrality and bridge centrality rankings and aggregated the most robust symptom connections into a summary network. After determining the most central symptoms and bridge symptoms across network models, heterogeneity across studies was examined using linear logistic regression.

RESULTS

Thirty-three studies with 78,721 participants were included in this systematic review. Seventeen studies with 23 cross-sectional networks based on the Patient Health Questionnaire (PHQ) and Generalized Anxiety Disorder (GAD-7) assessments of clinical and community samples were examined using centrality scores. Twelve cross-sectional networks based on the PHQ and GAD-7 assessments were examined using bridge centrality scores. We found substantial variability between study samples and network features. 'Sad mood', 'Uncontrollable worry', and 'Worrying too much' were the most central symptoms, while 'Sad mood', 'Restlessness', and 'Motor disturbance' were the most frequent bridge centrality symptoms. In addition, the connection between 'Sleep' and 'Fatigue' was the most frequent edge for the depressive and anxiety symptoms network model.

CONCLUSION

Central symptoms, bridge symptoms and robust edges identified in this systematic review can be viewed as potential intervention targets. We also identified gaps in the literature and future directions for network analysis of comorbid depression and anxiety.

Mapping PTSD, depression, and anxiety: A network analysis of co-occurring symptoms in treatment-seeking first responders

First responders are at high risk for a range of co-occurring mental health conditions due to their repeated exposure to traumatic events. When first responders present for treatment, their complex presentation of symptoms including posttraumatic stress disorder (PTSD), depression, and generalized anxiety disorder (GAD) can prove challenging to differentiate for clinical purposes. Network analysis provides a means to identify the nuanced associations between the symptoms of these conditions and to identify groups of related symptoms. In this study, a treatment-seeking sample of first responders (N = 432) completed self-report measures of PTSD, depression, and GAD. Network analysis was used to identify symptom clusters within the sample. Our cross-sectional data yielded six empirically distinct communities: depression symptoms, GAD symptoms, and four communities comprising PTSD symptoms - intrusion and avoidance; irritability and aggression; negative affect; and arousal and sleep. Network associations underscore the heterogeneity of PTSD and also highlight overlapping and diverging symptoms of depression and GAD. These findings are discussed within the context of existing research on first responders, and recommendations for further study and treatment interventions are provided.

Family function, anxiety and depression in adults with disabilities: a network analysis

Background

The prevalence of family dysfunction, anxiety and depression is high in people with disabilities due to long-term activity constraints and social difficulties. Recently, although studies have attempted to provide guidance for family therapy by focusing on the relationship between family function and negative emotions, the specific effects of improved family function during family therapy on alleviation of anxiety and depressive symptoms have been obscured. Thus, this study attempted to elucidate the impact of specific family functioning on specific symptoms of anxiety and depression through network analysis.

Methods

Family APGAR Index Questionnaire (APGAR), Generalized Anxiety Scale (GAD-7), and Patient Health Questionnaire Depression Scale (PHQ-9) were used to survey 897 adults with disabilities in Sichuan Province. Meanwhile, network analysis for studying the relationship between anxiety, depression and family functioning among the disabled via R software.

Results

The network analysis showed that (1) Nodes PHQ4 ("Energy"), APGAR3 ("Growth"), GAD1 ("Nervousness") and GAD4 ("Relaxing Trouble") were central nodes in the network model; (2) Bridge nodes linking family function, anxiety and depressive symptoms in the sample were PHQ9 ("Suicide ideation"), PHQ6 ("Worthlessness"), GAD1 ("Nervousness") and GAD5 ("Restlessness"); (3) The node APGAR5 ("Resolve") directly connects the bridge symptoms PHQ9 ("Suicide ideation") and PHQ8 ("Motor").

Conclusion

This study suggests that therapists could target the resolve of family members during family therapy to reduce suicidal ideation and enhance the level of activity of people with disabilities, thereby improving the network of anxiety and depression symptoms and alleviating negative emotions of people with disabilities.

Centrality depression-anxiety symptoms linked to suicidal ideation among depressed college students--A network approach

The long-term effects of the COVID-19 pandemic have caused severe mental health problems among college students, which can eventually cause suicidal ideation. Therefore, through network analysis, this study aims to explore the new characteristics of the depression-anxiety symptom network that arose during the long-term lockdown of the COVID-19 pandemic and to identify the most influential symptoms linked to suicidal ideation. We used a Patient Health Questionnaire (PHQ-9) score above 10 as the cutoff and screened 622 participants with an inclination toward depressive disorders from 7976 college students, and then divided the sample into suicidal and nonsuicidal groups based on the presence or absence of suicidal ideation. The General Anxiety Disorder scale (GAD-7) was also used. Network analysis was used to identify the network structure of anxiety-depression and which symptoms were directly related to suicidal ideation in the network. The prevalence of depression and anxiety among Chinese college students in the late stage of the COVID-19 pandemic was 7.8% and 17.8%, respectively. The most central symptoms in the nonsuicidal group were "excessive worry," "uncontrollable worry," and "nervousness," and in the suicidal group they were "excessive worry," "motor function," and "irritability." The network of the suicidal group was denser than that of the nonsuicidal group. The most influential symptom directly related to suicidal ideation was "guilt." The most influential central symptom of depression-anxiety comorbidity characteristics of Chinese adolescents showed a tendency to shift from depression-oriented (i.e., sad mood) to anxiety-oriented (i.e., excessive worry) with the continuation of the COVID-19 pandemic. Treatments or interventions focused on these critical symptoms could be useful in preventing college students from suicide risk.

Network of burnout, depression, anxiety, and dropout intention in medical undergraduates

BACKGROUND

Burnout, depression, and anxiety are highly prevalent among medical students, which often leads to their attrition. We aim to assess the inter-relationships of depression, burnout, and anxiety symptoms with dropout intention among Chinese medical undergraduates using the network analysis.

METHOD

A total of 3,648 Chinese medical undergraduates were recruited through snowball sampling. Learning burnout scale, 9-item Patient Health Questionnaire (PHQ-9), and General Anxiety Disorder Scale (GAD-7) was used to assess burnout, depression, and anxiety symptoms, respectively. We used the EBICglasso model to estimate the network. We compared the network based on gender, study phase, and clinical experience.

RESULTS

After removing repeated submissions and incorrect responses to the trap question, 3,536 participants were included in the final analysis. The prevalence of burnout, depression, anxiety, and dropout intention was 38, 62.7, 38.4, and 39% respectively, which is consistent with previous findings. Network analysis suggested that anxiety and depression items clustered together and displayed several strong bridge connections, while burnout items formed another cluster. All the strongest edges were within the respective distress. Cynicism symptoms 'I am fed up with study' and 'I want to study but I feel that studying is boring' were the most central symptoms, while 'fatigue' and 'worthless' were the bridge symptoms within the burnout-depression-anxiety network. Other central symptoms included 'worthless', 'I can handle my courses', 'nervous', and 'uncontrollable worry'. Cynicism symptoms 'I am interested in my major' and 'I feel that the knowledge I have learned is useless' were mostly related to dropout intention. Gender, study phase, and clinical experience didn't affect the global strength of the burnout-depression-anxiety network.

CONCLUSION

Our results indicated the predominance of cynicism symptoms within the burnout-depression-anxiety network and its substantial impact on dropout intention, suggesting that early detection and intervention for cynicism symptoms in Chinese medical students are in urgent need. Other central and bridge symptoms might also serve as potential targets for the prevention and treatment of burnout, depression, and anxiety among medical students. For example, studies suggest cognitive-behavioral therapy could quickly improve 'worthless', which might be beneficial in treating burnout, depression, and anxiety in medical students.

Network Analysis of Anxiety Symptoms in Front-Line Medical Staff during the COVID-19 Pandemic

BACKGROUND

This research analyses the relations between anxiety symptoms from the network perspective to deepen the understanding of anxiety in front-line medical staff during the COVID-19 pandemic and can also provide a reference for determining potential goals of clinical interventions.

METHODS

A convenience sampling was adopted, and the Generalized Anxiety Disorder 7-item scale (GAD-7) was administered to front-line medical staff through online platforms. A regularized partial correlation network of anxiety was constructed and then we evaluated its accuracy and stability. The expected influence and predictability were used to describe the relative importance and the controllability, using community detection to explore community structure. The gender-based differences and the directed acyclic graph were implemented.

RESULTS

The connections between A1 "Feeling nervous, anxious or on edge" and A2 "Not being able to stop or control worrying", A6 "Becoming easily annoyed or irritable" and A7 "Feeling afraid as if something awful might happen", etc., were relatively strong; A2 "Not being able to stop or control worrying" and A3 "Worrying too much about different things" had the highest expected influence, and A2 "Not being able to stop or control worrying" had the highest predictability. The community detection identified two communities. The results of the gender network comparison showed the overall intensity of the anxiety network in women was higher than that in men; DAG indicated that A2 "Not being able to stop or control worrying" had the highest probabilistic priority; the lines from A2 "Not being able to stop or control worrying" to A1 "Feeling nervous, anxious or on edge" and A2 "Not being able to stop or control worrying" to A7 "Feeling afraid as if something awful might happen" represented the most important arrows.

CONCLUSION

There exist broad interconnections among anxiety symptoms of front-line medical staff on the GAD-7. A2 "Not being able to stop or control worrying" might be the core symptom and a potential effective intervention target. It was possible to bring an optimal result for the entire GAD symptom network by interfering with A2 "Not being able to stop or control worrying". GAD may have two "subsystems". The modes of interconnection among anxiety may be consistent between genders.

Identification and comparison of pandemic-to-symptom networks of South Korea and the United States

Background

The Coronavirus (COVID-19) pandemic resulted in a dramatic increase in the prevalence of anxiety and depression globally. Although the impact on the mental health of young adults was especially strong, its underlying mechanisms remain elusive.

Materials and methods

Using a network approach, the present study investigated the putative pathways between pandemic-related factors and anxiety and depressive symptoms among young adults in South Korea and the U.S. Network analyses were conducted on cross-country data collected during the COVID-19 lockdown period (n = 1,036). Our model included depression symptoms (PHQ-9), generalized anxiety symptoms (GAD-7), and COVID-19-related factors (e.g., COVID-19-related traumatic stress, pandemic concerns, access to medical/mental health services).

Results

The overall structure of pandemic-to-symptom networks of South Korea and the U.S. were found to be similar. In both countries, COVID-related stress and negative future anticipation (an anxiety symptom) were identified as bridging nodes between pandemic-related factors and psychological distress. In addition, worry-related symptoms (e.g., excessive worry, uncontrollable worry) were identified as key contributors in maintaining the overall pandemic-to-symptom network in both countries.

Conclusion

The similar network structures and patterns observed in both countries imply that there may exist a stable relationship between the pandemic and internalizing symptoms above and beyond the sociocultural differences. The current findings provide new insights into the common potential pathway between the pandemic and internalizing symptoms in South Korea and in the U.S. and inform policymakers and mental health professionals of potential intervention targets to alleviate internalizing symptoms.

Temporal dynamics in mental health symptoms and loneliness during the COVID-19 pandemic in a longitudinal probability sample: a network analysis

Figuring out which symptoms are central for symptom escalation during the COVID-19 pandemic is important for targeting prevention and intervention. Previous studies have contributed to the understanding of the course of psychological distress during the pandemic, but less is known about key symptoms of psychological distress over time. Going beyond a pathogenetic pathway perspective, we applied the network approach to psychopathology to examine how psychological distress unfolds in a period of maximum stress (pre-pandemic to pandemic onset) and a period of repeated stress (pandemic peak to pandemic peak). We conducted secondary data analyses with the Understanding Society data (N = 17,761), a longitudinal probability study in the UK with data before (2019), at the onset of (April 2020), and during the COVID-19 pandemic (November 2020 & January 2021). Using the General Health Questionnaire and one loneliness item, we computed three temporal cross-lagged panel network models to analyze psychological distress over time. Specifically, we computed (1) a pre-COVID to first incidence peak network, (2) a first incidence peak to second incidence peak network, and (3) a second incidence peak to third incidence peak network. All networks were highly consistent over time. Loneliness and thinking of self as worthless displayed a high influence on other symptoms. Feeling depressed and not overcoming difficulties had many incoming connections, thus constituting an end-product of symptom cascades. Our findings highlight the importance of loneliness and self-worth for psychological distress during COVID-19, which may have important implications in therapy and prevention. Prevention and intervention measures are discussed, as single session interventions are available that specifically target loneliness and worthlessness to alleviate mental health problems.

The dynamic changes of psychosomatic symptoms in three waves of COVID-19 outbreak and fatigue caused by enduring pandemic in China

BACKGROUND

Two years have passed since the 2019 novel coronavirus disease (COVID-19) was first reported. The persistent pandemic might lead to severe psychosomatic problems and fatigue. In addition, the recent rapid rising COVID-19 cases in China have become a trending issue. Therefore, this study aimed to investigate the dynamic changes in psychosomatic problems at the initial and current stages of the pandemic.

METHODS

Three waves of cross-sectional online survey were conducted during the initial COVID outbreak in China. The psychosomatic symptom scale (PSSS), perceived stress scale (PSS), and pandemic fatigue scale (PFS) were used to assess the psychosomatic problems, stress, and fatigue.

RESULTS

4317, 1096, and 2172 participants completed the first, second, and third surveys. The prevalence of psychosomatic disorder was 22 %, 28 %, and 39 %, respectively. The network structure of PSSS symptoms has not significantly changed as the pandemic progresses. However, the global strength of the PSSS networks, indicating the overall connectivity, in the third wave was significantly higher than in the first wave (s = 0.54, P = 0.007). The most central symptoms in the first and third wave networks were depressed mood and tiredness. The PFS score was higher in the people concerned with indirect impact than those concerned with health (P < 0.001). PFS has positive relationships with PSSS and PSS score (R = 0.41, P < 0.001 and R = 0.35, P < 0.001, respectively).

CONCLUSIONS

The persistence of the pandemic caused critical psychosomatic issues, stress, and indirect burden over time, leading to inevitable fatigue. People endured needing immediate attention to prevent or reduce psychosomatic disorders.

Predictors of Cyberchondria during the COVID-19 pandemic: A cross-sectional study using supervised machine learning

BACKGROUND

Cyberchondria is characterized by repeated and compulsive online searches for health information, resulting in increased health anxiety and distress. It has been conceptualized as a multi-dimensional construct fueled by both anxiety and compulsivity-related factors and described as a "transdiagnostic compulsive behavioral syndrome" which is associated with health anxiety, problematic internet use and obsessive-compulsive symptoms. Cyberchondria is not included in the ICD-11 or the DSM-5, and its defining features, etiological mechanisms and assessment continue to be debated.

OBJECTIVE

This study aimed to investigate changes in the severity of cyberchondria during the pandemic and identify predictors of cyberchondria at this time.

METHODS

Data collection started on May 4, 2020 and ended on June 10, 2020, which corresponds to the first wave of the COVID-19 pandemic in Europe. At the time the present study took place, French-speaking countries in Europe (France, Switzerland, Belgium and Luxembourg) all implemented lockdown or semi-lockdown measures. The survey consisted of a questionnaire collecting demographic information (sex, age, education level and country of residence) and information on socioeconomic circumstances during the first lockdown (e.g., economic situation, housing and employment status), and was followed by several instruments assessing various psychological and health-related constructs. Inclusion criteria for the study were being at least 18 years of age and having a good understanding of French. Self-report data were collected from 725 participants aged 18 to 77 years (mean 33.29, SD 12.88 years), with females constituting the majority (416/725, 57.4%).

RESULTS

The results show that the COVID-19 pandemic affected various facets of cyberchondria: cyberchondria-related distress and interference with functioning increased (distress z=-3.651, P<.001; compulsion z=-5.697, P<.001), whereas the reassurance facet of cyberchondria decreased (z=-6.680, P<.001). Also, COVID-19-related fears and health anxiety emerged as the strongest predictors of cyberchondria-related distress and interference with functioning during the pandemic.

CONCLUSIONS

These findings provide evidence about the impact of the COVID-19 pandemic on cyberchondria and identify factors that should be considered in efforts to prevent and manage cyberchondria at times of public health crises. Also, they are consistent with the theoretical model of cyberchondria during the COVID-19 pandemic proposed by Starcevic and his colleagues in 2020. In addition, the findings have implications for the conceptualization and future assessment of cyberchondria.

A 16-month longitudinal investigation of risk and protective factors for mental health outcomes throughout three national lockdowns and a mass vaccination campaign: Evidence from a weighted Israeli sample during COVID-19

BACKGROUND

COVID-19 is an ongoing global crisis, with a multitude of factors that affect mental health worldwide. We explored potential predictors for the emergence and maintenance of depression, anxiety, and posttraumatic stress symptoms (PTSS) in the general population in Israel.

METHODS

Across the span of 16 months, 2478 people completed a repeated self-report survey which inquired psychiatric symptoms and pandemic related stress factors (PRSF). We applied mixed-effects models to assess how each stressor contributes to depression, anxiety and PTSS at each time point, and longitudinally assessed participants who completed at least two consecutive surveys (n = 400). We weighted our sample to increase representativeness of the population.

RESULTS

Fatigue was the strongest predictor for depression, anxiety and PTSS at all time points, and predicted deterioration overtime. Financial concerns associated with depression and anxiety at all time points, and with their deterioration overtime. Health related concerns were uniquely associated with anxiety and PTSS at all time points and their deterioration, but not with depression. Improvement in sense of protection overtime associated with decrease in depression and anxiety. Hesitancy towards vaccination was associated to higher financial concerns and lower sense of protection by the authorities.

CONCLUSIONS

Our findings accentuate the multitude of risk factors for psychiatric morbidity during COVID-19, and the centrality of fatigue in determining mental health outcomes.

Psychological impact of COVID-19: A cross-lagged network analysis from the English Longitudinal Study of Aging COVID-19 database

Background

The COVID-19 pandemic and its subsequent health restrictions had an unprecedented impact on mental health, contributing to the emergence and reinforcement of various psychopathological symptoms. This complex interaction needs to be examined especially in a vulnerable population such as older adults.

Objective

In the present study we analyzed network structures of depressive symptoms, anxiety, and loneliness from the English Longitudinal Study of Aging COVID-19 Substudy over two waves (Months of June-July and November-December 2020).

Methods

For this purpose, we use measures of centrality (expected and bridge-expected influence) in addition to the Clique Percolation method to identify overlapping symptoms between communities. We also use directed networks to identify direct effects between variables at the longitudinal level.

Results

UK adults aged >50 participated, Wave 1: 5,797 (54% female) and Wave 2: 6,512 (56% female). Cross-sectional findings indicated that difficulty relaxing, anxious mood, and excessive worry symptoms were the strongest and similar measures of centrality (Expected Influence) in both waves, while depressive mood was the one that allowed interconnection between all networks (bridge expected influence). On the other hand, sadness and difficulty sleeping were symptoms that reflected the highest comorbidity among all variables during the first and second waves, respectively. Finally, at the longitudinal level, we found a clear predictive effect in the direction of the nervousness symptom, which was reinforced by depressive symptoms (difficulties in enjoying life) and loneliness (feeling of being excluded or cut off from others).

Conclusion

Our findings suggest that depressive, anxious, and loneliness symptoms were dynamically reinforced as a function of pandemic context in older adults in the UK.

Impact of the COVID-19 pandemic on the consumption patterns of psychotropic drugs and predictors of limited access to medication

Background

Despite the efforts of the health system to improve access to medications during the coronavirus disease of 2019 (COVID-19) pandemic, such as online consultations, encouraging generic prescriptions, and other measures to limit the storage of medication, psychotropic patients faced significant challenges in accessing their medications.

Objectives

This study aimed (1) to compare the consumption of psychotropics before and during the pandemic, (2) to assess the association between having difficulties finding the medications and the general characteristics of the patients, and (3) to assess the predictors of these difficulties.

Design

A case-control study was performed in which 128 patients (cases) were recruited during the pandemic (July-October 2021), and 256 patients (controls) using psychotropics before the pandemic were matched for age and sex.

Methods

Data were collected using a uniform survey given to patients using psychotropics and filled out at their time and place preferences.

Results

More patients used antipsychotics and anti-anxiety medications before the pandemic, while antidepressants were used more during the pandemic. Almost half of the patients reported facing difficulties finding their medications in both time frames. Before the pandemic, these difficulties were noted per increase in age and being employed and were less faced if patients had medical assistance or lived in the north of Lebanon. However, more patients reported having difficulties accessing their medication during the pandemic, with no significant differences.

Conclusion

The consumption of psychotropic drugs was higher among cases. All patients faced challenges in accessing their medication throughout the pandemic, while older and employed patients had more limitations before the pandemic. Further investigations exploring viable solutions are recommended in order to maintain sustainable access to treatment.

Night shifts, insomnia, anxiety, and depression among Chinese nurses during the COVID-19 pandemic remission period: A network approach

Background

The outbreak of the COVID-19 pandemic imposed a heavy workload on nurses with more frequent night shifts, which led to higher levels of insomnia, depression, and anxiety among nurses. The study aimed to describe the symptom-symptom interaction of depression, anxiety, and insomnia among nurses and to evaluate the impact of night shifts on mental distress via a network model.

Methods

We recruited 4,188 nurses from six hospitals in December 2020. We used the Insomnia Severity Index, Patient Health Questionnaire-9, and Generalized Anxiety Disorder Scale-7 to assess insomnia, depression, and anxiety, respectively. We used the gaussian graphical model to estimate the network. Index expected influence and bridge expected influence was adapted to identify the central and bridge symptoms within the network. We assessed the impact of night shifts on mental distress and compared the network structure based on COVID-19 frontline experience.

Results

The prevalence of depression, anxiety, and insomnia was 59, 46, and 55%, respectively. Nurses with night shifts were at a higher risk for the three mental disorders. "Sleep maintenance" was the central symptom. "Fatigue," "Motor," "Restlessness," and "Feeling afraid" were bridge symptoms. Night shifts were strongly associated with sleep onset trouble. COVID-19 frontline experience did not affect the network structure.

Conclusion

"Sleep maintenance," "Fatigue," "Motor," and "Restlessness" were important in maintaining the symptom network of anxiety, depression, and insomnia in nurses. Further interventions should prioritize these symptoms.

Fear of contagion, emotional stress and coping strategies used by adults during the first wave of the COVID-19 pandemic in Nigeria

BACKGROUND

The COVID-19 pandemic has induced high levels of stress. The aim of the study was to assess the relationship between emotional stress (COVID-19 related fear, anger, frustration, and loneliness) and the use of coping strategies among adults in Nigeria during the COVID-19 pandemic.

METHODS

Data from adults aged 18 years and above were collected through an online survey from July to December 2020. The dependent variables were COVID-19 related fear (fear of infection and infecting others with COVID-19), anger, frustration, and loneliness. The independent variables were coping strategies (use of phones to communicate with family and others, video conferencing, indoor exercises, outdoor exercises, meditation/mindfulness practices, engaging in creative activities, learning a new skill, following media coverage related to COVID-19) and alcohol consumption. Five logistic regression models were developed to identify the factors associated with each dependent variables. All models were adjusted for sociodemographic variables (age, sex at birth, and the highest level of education).

RESULTS

Respondents who consumed alcohol, followed media coverage for COVID-19 related information, and who spoke with friends or family on the phone had higher odds of having fear of contracting COVID-19 or transmitting infection to others, and of feeling angry, frustrated, or lonely (p < 0.05). Respondents who exercised outdoors (AOR: 0.69) or learned a new skill (AOR: 0.79) had significantly lower odds of having fear of contracting COVID-19. Respondents who practiced meditation or mindfulness (AOR: 1.47) had significantly higher odds of feeling angry. Those who spoke with friends and family on the phone (AOR: 1.32) and exercised indoors (AOR: 1.23) had significantly higher odds of feeling frustrated. Those who did video conferencing (AOR: 1.41), exercised outdoors (AOR: 1.32) and engaged with creative activities (AOR: 1.25) had higher odds of feeling lonely.

CONCLUSION

Despite the significant association between emotional stress and use of coping strategies among adults in Nigeria during the COVID-19 pandemic, it appears that coping strategies were used to ameliorate rather than prevent emotional stress. Learning new skills and exercising outdoors were used to ameliorate the fear of contracting COVID-19 in older respondents.

A network analysis of anxiety and depression symptoms among Chinese nurses in the late stage of the COVID-19 pandemic

Background

Nurses are at high risk for depression and anxiety symptoms after the outbreak of the COVID-19 pandemic. We aimed to assess the network structure of anxiety and depression symptoms among Chinese nurses in the late stage of this pandemic.

Method

A total of 6,183 nurses were recruited across China from Oct 2020 to Apr 2021 through snowball sampling. We used Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. We used the Ising model to estimate the network. The index "expected influence" and "bridge expected influence" were applied to determine the central symptoms and bridge symptoms of the anxiety-depression network. We tested the stability and accuracy of the network via the case-dropping procedure and non-parametric bootstrapping procedure.

Result

The network had excellent stability and accuracy. Central symptoms included "restlessness", "trouble relaxing", "sad mood", and "uncontrollable worry". "Restlessness", "nervous", and "suicidal thoughts" served as bridge symptoms.

Conclusion

Restlessness emerged as the strongest central and bridge symptom in the anxiety-depression network of nurses. Intervention on depression and anxiety symptoms in nurses should prioritize this symptom.

COVID-19-Related Functional Impairment in a Community Sample of Korean Adults: Associations With Depression, COVID-19 Infection Fear, and Resilience

OBJECTIVE

We aimed to determine the effects of depression, COVID-19 infection fear, and resilience on COVID-19-related functional impairment.

METHODS

We obtained data from 476 community-dwelling adults aged 20-69 years living in Jeju, South Korea, and evaluated the relationships between COVID-19-related functional impairment (work/school, social, and home life) and sociodemographic and healthrelated characteristics, COVID-19-related life changes (financial difficulties since the pandemic, employment change, interpersonal conflict), and clinical characteristics, including depression, COVID-19 infection fear, and resilience.

RESULTS

Functional impairment in the home life domain was associated with marital status and monthly income. Greater work/school, social, and home life functional impairment was significantly associated with all COVID-19-related life changes. Regression analysis indicated that resilience modulated the positive associations of COVID-19-related functional impairment with symptoms of depression and COVID-19 infection fear when relevant factors were controlled for.

CONCLUSION

Our results suggest the importance of clinical characteristics, including depression, COVID-19 infection fear, and resilience for understanding functional impairment related to COVID-19. These results have important implications for interventions aimed at reducing depression and COVID-19 infection fear, and enhancing resilience.

Longitudinal changes in fear and anxiety among Chinese college students during the COVID-19 pandemic: a one-year follow-up study

There is growing evidence that levels of fear and anxiety have increased during the COVID-19 pandemic. However, given regular epidemic prevention and control measures, longitudinal changes and causal factors in the incidence of fear and anxiety need to be measured and explored. College students completed online surveys in two wave studies a year apart. The participants who completed both of the surveys numbered 22,578. The online surveys were completed at the pandemic's normalization/prevention stage (T1, from June 1 to 15, 2020) and during a phase of new local transmission of the disease in Guangdong Province (T2, from June 10 to 18, 2021). Multiple linear regressions were used to examine fear and anxiety predictors from demographic characteristics. Fear related to COVID-19 had significantly decreased at T2 (t = 66.64, p < 0.001), however, anxiety had significantly increased at T2 (t = -5.03, p < 0.001). In particular, not implementing preventive measures (e.g., handwashing) during the COVID-19 pandemic had the greatest impact in predicting the change in fear levels. By contrast, prior poor mental health status contributed the most in predicting the change in degree of anxiety. These results suggest different changes in anxiety levels (deterioration) and degree of fear (mitigation) occurred as the COVID-19 pandemic progressed. These findings have implications for planning mental health crisis provisions and have long-term impact beyond this pandemic.

Problematic Internet use and academic engagement during the COVID-19 lockdown: The indirect effects of depression, anxiety, and insomnia in early, middle, and late adolescence

BACKGROUND

During the COVID-19 pandemic, the transition of online learning introduces challenges for adolescents to engage in learning. The increased access and persistent Internet use could heighten the risk of problematic Internet use (PIU) that has been increasingly recognized as a risk factor for academic engagement. This study aims to investigate the direct and indirect relationships between PIU and academic engagement through psychopathological symptoms (i.e., depression, anxiety, insomnia) in early, middle, and late adolescence.

METHODS

In all, 4852 adolescents (51.5% females; M_age = 13.80 ± 2.38) from different regions of Chinese mainland participated in the study and completed questionnaires.

RESULTS

Depression and then insomnia as well as anxiety and then insomnia mediated the relationship between PIU and academic engagement. Anxiety exhibited a double-edged effect, that is, a positive relation with academic engagement directly and a negative relation with academic engagement indirectly through insomnia. Multigroup analyses showed that the indirect effects of PIU on academic engagement through depression and subsequent insomnia in middle and late adolescence were stronger than that in early adolescence, whereas the direct effect in early adolescence was stronger than that in middle adolescence.

LIMITATION

This study was cross-sectional in design and relied upon self-report measures.

CONCLUSION

These findings improve the understandings of how PIU relates to academic engagement through psychopathological symptoms and highlight developmental differences of adolescence.

How to improve the long-term quality of life, insomnia, and depression of survivors 10 years after the Wenchuan earthquake? A network analysis

BACKGROUND

Previous studies have found a negative effect of depression and insomnia on the psychological health domain of quality of life (QOL) among earthquake survivors. However, little is known about the symptom-to-symptom interactions among the above psychological outcomes. This study thus aimed to assess the interplay among the above three variables in survivors 10 years after the Wenchuan earthquake at the symptom level.

METHODS

A total of 744 survivors completed the questionnaire at 10 years post-earthquake, reporting depressive symptoms, insomnia symptoms, and the psychological health domain of QOL. All network structures were estimated and compared using the network analysis approach in R version 4.1.1.

RESULTS

Among the 744 survivors, 593 individuals did not have significant depressive and insomnia symptoms, while 151 individuals reported depressive and/or insomnia symptoms. "Little energy", "Suicidal ideation", and "Spirituality" were the key highest bridge symptoms in the three networks, respectively. Additionally, there were significant differences in network global strength, network structure, and individual edge weights between individuals with and without depression and/or insomnia.

CONCLUSIONS

Intervention programs aimed at treating symptoms, such as exercise therapy, cognitive behavioural therapy, and spirituality education, may improve the QOL of survivors following an earthquake.

Network analysis of depressive and anxiety symptoms in adolescents during and after the COVID-19 outbreak peak

BACKGROUND

This study examined the extent to which the network structure of anxiety and depression among adolescents identified during the peak of the COVID-19 pandemic could be cross-validated in a sample of adolescents assessed after the COVID-19 peak.

METHODS

Two cross-sectional surveys were conducted between February 20 and 27, 2020 and between April 11 and 19, 2020, respectively. Depressive and anxiety symptoms were assessed using the 20-item Center for Epidemiological Studies-Depression and 7-item Generalized Anxiety Disorder, respectively. Anxiety-depression networks of the first and second assessments were estimated separately using a sparse Graphical Gaussian Model combined with the graphical least absolute shrinkage and selection operator method. A Network Comparison Test was conducted to assess differences between the two networks.

RESULTS

The most central symptoms in the first and second survey networks were Depressed affect and Nervousness. Compared with connections in the first survey network, connections in the second survey network analysis between Relax-Nervousness-Depressed affect-Interpersonal problems (diff, contrast: second survey-first survey. diff=-0.04, P = 0.04; diff=-0.03, P = 0.03; diff=-0.03, P = 0.04), and Irritability-Somatic complaints (diff=-0.04, P = 0.02) were weaker while connections of Somatic complaints-Nervousness (diff=0.05, P<0.001), Somatic complaints-Depressed affect (diff=0.03, P = 0.009), and Irritability-Control worry-Restlessness (diff=0.02, P = 0.03; diff=0.05, P = 0.02) were stronger.

CONCLUSIONS

Depressed affect emerged as a robust central symptom and bridge symptom across Anxiety-Depression networks. Considering the negative impact of depression and anxiety on daily life, timely interventions targeting depressed affect should be implemented to reduce the co-occurrence of anxious and depressive symptoms among adolescents during the COVID-19 pandemic.

A Changing in Social Lifestyle for Men During the COVID-19 Lockdown and Its Relationship to Mental Health: Kuwaiti Diwaniyyah as an Example

During the COVID-19 pandemic, there is to detect negative impact of lifestyle disruption on individuals mental and emotional health during an enforced lockdown. The main aim of this study is to investigate the impact of the COVID-19 pandemic and complete lockdown on Kuwaiti men's lifestyle behavior. It investigated the major mental health as a result of not attending Diwaniyyah during this time. Diwaniyyah is defined as a place of men social and entertainment gathering. A non-random sample of 1,461 Kuwaiti men aged from 17 to 68 years was selected. An electronic questionnaire was the major investigative tool used in this study. Demographic variables and five scales were used, including the Mental Health Scale (MHS), Missing Diwaniyyah Scale (MDS), Importance of Diwaniyyah Scale (IDS), Losing Political Information Scale (LPIS), and Social Media Information Knowledge Scale (SMIKS). IBM SPSS software (Version 24) was used for data analysis. Significant differences between the respondents mental health and the types of Diwaniyyah (p < .001), age categories (p < .001), and Diwaniyyah ownership or lack of ownership (p < .001) were reported. There were significant relationships between the respondents mental health symptoms and all examined social and Diwaniyyah visiting behavior variables (p < .01). It can be concluded that the inability to attend Diwaniyyahs has a major effect on the mental health of Kuwaiti men. A change in lifestyle affects mental health in general, and the COVID-19 lockdown is a major event affecting mental health among men.

Mechanisms associated with the trajectory of depressive and anxiety symptoms: A linear mixed-effects model during the COVID-19 Pandemic

With the fluctuations in anxious and depressive symptomatology accompanied by the pandemic crises, studies on the trajectories of these symptom domains are warranted to monitor the development of mental health problems in the population. This pre-registered longitudinal study examines stable factors and mechanistic processes covarying with the trajectory of anxiety and depressive symptoms using linear-mixed effects models in 4936 adults from the pandemic's onset to four months into the COVID-19 pandemic in Norway. Prevalence estimates of moderate to severe levels of clinically impairing symptoms of anxiety and depression revealed high but reduced occurrence four months into the pandemic where social distancing protocols were substantially lightened in severity, revealing associations between symptoms and viral mitigation protocols after stringent control of plausible confounders. Subgroups at risk at the onset of the pandemic sustained their relative position compared to their counterparts four months into the pandemic, indicating prolonged suffering of these subgroups. Among mechanistic processes, key differences were identified regarding the trajectory of anxiety and depressive symptoms. Physical exercise was associated with long-term but not momentaneous alleviations in anxiety. In contrast, reductions in depressive symptoms were associated with both the simultaneous exertion as well as dose-increases in exercise over time. Increased knowledge about how to best cope with pandemic challenges was associated with greater improvement in depressive but not anxiety symptoms. Reductions in maladaptive coping strategies and negative metacognitive beliefs was substantially associated with greater improvement of both anxious and depressive symptomatology. Mechanistic processes divergently relate to the trajectory of depressive and anxious symptomatology, yielding domain-specific information of utility for preventive and interventive efforts aimed at impeding deleterious symptom levels.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12144-022-02732-9.

Evidence-Informed Approach to De-Prescribing of Atypical Antipsychotics (AAP) in the Management of Behavioral Expressions (BE) in Advanced Neurocognitive Disorders (NCD): Results of a Retrospective Study

The LuBAIR™ Paradigm is a novel approach to ascribe meaning to behavioral expressions in advanced neurocognitive disorders when the reliability of a clinical assessment is limited. The meaning ascribed to each behavioral category was used to identify those which are likely to respond to the use of atypical antipsychotics, in their management. De-prescribing was attempted on patients who qualified to enter this retrospective study. De-prescribing was defined as successful if individuals were completely withdrawn from AAP and remained off them for 60 days, without the re-emergence of behaviors. The LuBAIR™ Inventory was filled on two occasions. The data collected on the second occasion, in the successful and failed de-prescribed groups, were compared in this retrospective study. MANOVA, Chi-Square paired t-test statistical analyses were used to detect the differences in the behavioral categories between the two cohorts. Cohen d was used to measure effect size. Patients who did not have Mis-Identification and Goal-Directed Expressions were more likely to successfully de-prescribe: X2 (1, N = 40) = 29.119 p < 0.0001 and X2 (1, N = 40) = 32.374, p < 0.0001, respectively. Alternatively, the same behavioral categories were more likely to be present in patients who failed de-prescribing: MANOVA and paired t-test (p < 0.0001). Atypical antipsychotics, in their role as an antipsychotic and mood stabilizer, may be used to manage Mis-Identification and Goal-Directed Expressions, respectively.

Examining the impact of the COVID-19 pandemic through the lens of the network approach to psychopathology: Analysis of the Brazilian Longitudinal Study of Health (ELSA-Brasil) cohort over a 12-year timespan

Cohort studies have displayed mixed findings on changes in mental symptoms severity in 2020, when the COVID-19 pandemic outbreak started. Network approaches can provide additional insights by analyzing the connectivity of such symptoms. We assessed the network structure of mental symptoms in the Brazilian Longitudinal Study of Health (ELSA-Brasil) in 3 waves: 2008-2010, 2017-2019, and 2020, and hypothesized that the 2020 network would present connectivity changes. We used the Clinical Interview Scheduled-Revised (CIS-R) questionnaire to evaluates the severity of 14 common mental symptoms. Networks were graphed using unregularized Gaussian models and compared using centrality and connectivity measures. The predictive power of centrality measures and individual symptoms were also estimated. Among 2011 participants (mean age: 62.1 years, 58% females), the pandemic symptom 2020 network displayed higher overall connectivity, especially among symptoms that were related to general worries, with increased local connectivity between general worries and worries about health, as well as between anxiety and phobia symptoms. There was no difference between 2008 and 2010 and 2017-2019 networks. According to the network theory of mental disorders, external factors could explain why the network structure became more densely connected in 2020 compared to previous observations. We speculate that the COVID-19 pandemic and its innumerous social, economical, and political consequences were prominent external factors driving such changes; although further assessments are warranted.

Excessive Worrying as a Central Feature of Anxiety during the First COVID-19 Lockdown-Phase in Belgium: Insights from a Network Approach

Since the WHO declared the COVID-19 pandemic on March 11, 2020, the novel coronavirus, SARS-CoV-2, has profoundly impacted public health and the economy worldwide. But there are not the only ones to be hit. The COVID-19 pandemic has also substantially altered mental health, with anxiety symptoms being one of the most frequently reported problems. Especially, the number of people reporting anxiety symptoms increased significantly during the first lockdown-phase compared to similar data collected before the pandemic. Yet, most of these studies relied on a unitary approach to anxiety, wherein its different constitutive features (i.e., symptoms) were tallied into one sum-score, thus ignoring any possibility of interactions between them. Therefore, in this study, we seek to map the associations between the core features of anxiety during the first weeks of the first Belgian COVID-19 lockdown-phase (n = 2,829). To do so, we implemented, in a preregistered fashion, two distinct computational network approaches: a Gaussian graphical model and a Bayesian network modelling approach to estimate a directed acyclic graph. Despite their varying assumptions, constraints, and computational methods to determine nodes (i.e., the variables) and edges (i.e., the relations between them), both approaches pointed to excessive worrying as a node playing an especially influential role in the network system of the anxiety features. Altogether, our findings offer novel data-driven clues for the ongoing field's larger quest to examine, and eventually alleviate, the mental health consequences of the COVID-19 pandemic.