Inter-relationships of depressive and anxiety symptoms with suicidality among adolescents: A network perspective

A simulation-based network analysis of intervention targets for adolescent depressive and anxiety symptoms

Although previous research has well explored central and bridge symptoms of mental health problems, little examined whether these symptoms can serve as effective targets for intervention practices. Based on the Ising model, this study constructed a network structure of depressive and anxiety symptoms. The NodeIdentifyR algorithm (NIRA) was used to simulate interventions within this network, examining the effects of alleviating or aggravating specific symptoms on the network's sum scores. In this study, a total of 15,569 participants were recruited from China (50.87 % females, Mage = 13.44; SD = 0.97). The Ising model demonstrated that "sad mood" had the highest expected influence, and "irritability" had the highest bridge expected influence. Alleviating interventions suggested that decreasing the symptom value of "nervousness" resulted in the greatest projected reduction in network symptom activation, which may be a potential target symptom for treatment. Aggravating interventions indicated that elevating the symptom value of "sad mood" had the most projected increase in network activation, which may be a potential target for prevention. Additionally, network structure indices (e.g., central or bridge symptoms) need to be interpreted with more caution as intervention targets, since they may not be exactly the same. These findings enriched the comprehension of the depressive and anxiety network in Chinese adolescents, offering valuable insights for designing effective interventions.

A network analysis of the interrelationships between depression, anxiety, insomnia and quality of life among fire service recruits

Background

Research on the mental health and quality of life (hereafter QOL) among fire service recruits after the end of the COVID-19 restrictions is lacking. This study explored the network structure of depression, anxiety and insomnia, and their interconnections with QOL among fire service recruits in the post-COVID-19 era.

Methods

This cross-sectional study used a consecutive sampling of fire service recruits across China. We measured the severity of depression, anxiety and insomnia symptoms, and overall QOL using the nine-item Patient Health Questionnaire (PHQ-9), seven-item Generalized Anxiety Disorder scale (GAD-7), Insomnia Severity Index (ISI) questionnaire, and World Health Organization Quality of Life-brief version (WHOQOL-BREF), respectively. We estimated the most central symptoms using the centrality index of expected influence (EI), and the symptoms connecting depression, anxiety and insomnia symptoms using bridge EI.

Results

In total, 1,560 fire service recruits participated in the study. The prevalence of depression (PHQ-9 ≥ 5) was 15.2% (95% CI: 13.5-17.1%), while the prevalence of anxiety (GAD-7 ≥ 5) was 11.2% (95% CI: 9.6-12.8%). GAD4 ("Trouble relaxing") had the highest EI in the whole network model, followed by ISI5 ("Interference with daytime functioning") and GAD6 ("Irritability"). In contrast, PHQ4 ("Fatigue") had the highest bridge EI values in the network, followed by GAD4 ("Trouble relaxing") and ISI5 ("Interference with daytime functioning"). Additionally, ISI4 "Sleep dissatisfaction" (average edge weight = -1.335), which was the central symptom with the highest intensity value, had the strongest negative correlation with QOL.

Conclusion

Depression and anxiety were important mental health issues to address among fire service recruits in the post-COVID-19 era in China. Targeting central and bridge symptoms identified in network analysis could help address depression and anxiety among fire service recruits in the post-COVID-19 era.

Characteristics of drug overdose suicide attempts presenting to the psychiatric emergency department of Beijing Anding Hospital

BACKGROUND

Overdose-related suicide attempts represent a significant portion of self-harm presentations in the psychiatric emergency department (ED). Identifying specific patient characteristics associated with these attempts holds promise for pinpointing drug classes with elevated risk and paving the way for tailored suicide prevention interventions. This study aims to examine the demographic profiles of ED patients who had experienced overdose-related suicide attempts.

METHODS

This retrospective study was conducted at Beijing Anding Hospital, Capital Medical University, from January 2020 to December 2021. Patients with psychiatric drug overdose suicide attempts presenting to the psychiatric ED were included. Sociodemographic characteristics and the specific classes of drugs involved were collected, and analysed descriptively.

RESULTS

This study examined 252 overdose patients, excluding 51 patients treated with alcohol or nonpsychiatric drugs, and a total 201 cases were included. The mean age of the patients was 28 ± 16 years (median 23, range 12-78), and 82% (n = 165) of the sample were females. Notably, nearly half (45%) of the patients were aged ≤ 20 years. While the number of cases decreased with increasing age, a significant increase was observed in 2021 compared to 2020. Benzodiazepines (BZDs) were the most frequently implicated substance class (n = 126, 63%), followed by antidepressants (n = 96, 48%), antipsychotics (n = 44, 22%), Z-drugs (n = 43, 21%), and mood stabilizers (n = 36, 18%). For adolescents, antidepressants (n = 52, 71%) overtook BZDs (n = 38, 52%) as the most common drug. The monthly distribution of cases revealed peaks in April and November. Furthermore, 21% (n = 42) of patients ingested more than two psychotropic medications concurrently. Finally, approximately half (n = 92) of the patients required inpatient admission for further treatment. Comparisons between hospitalized and nonhospitalized patients did not reveal any significant differences.

CONCLUSIONS

The present study revealed a greater prevalence of suicide overdose attempts among young females receiving prescriptions for antidepressants and/or BZDs. This finding suggests a potential need for enhanced monitoring of suicidal behaviour in this specific population when prescribing psychotropic medications. These findings contribute to the growing body of knowledge regarding drug overdose suicide attempts in psychiatric emergency settings and underscore the importance of further research to develop targeted prevention interventions.

Prevalence and network structure of depression, insomnia and suicidality among mental health professionals who recovered from COVID-19: a national survey in China

Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09-48.06%) and 36.2% (95%CI = 35.35-37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31-8.37%). The key central nodes included "Distress caused by the sleep difficulties" (ISI7) (EI = 1.34), "Interference with daytime functioning" (ISI5) (EI = 1.08), and "Sleep dissatisfaction" (ISI4) (EI = 0.74). "Fatigue" (PHQ4) (Bridge EI = 1.98), "Distress caused by sleep difficulties" (ISI7) (Bridge EI = 1.71), and "Motor Disturbances" (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of "Suicidality" (SU) and "Guilt" (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by "Suicidality" (SU) - "Sad mood" (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.

Depression, anxiety and suicidality among Chinese mental health professionals immediately after China's dynamic zero-COVID policy: A network perspective

BACKGROUND

Using network analysis, the interactions between mental health problems at the symptom level can be explored in depth. This study examined the network structure of depressive and anxiety symptoms and suicidality among mental health professionals after the end of China's Dynamic Zero-COVID Policy.

METHODS

A total of 10,647 mental health professionals were recruited nationwide from January to February 2023. Depression and anxiety were assessed using the 9-item Patient Health Questionnaire (PHQ-9) and 7-item Generalized Anxiety Disorder Scale (GAD-7), respectively, while suicidality was defined by a 'yes' response to any of the standard questions regarding suicidal ideation (SI), suicide plan (SP) and suicide attempt (SA). Expected Influence (EI) and Bridge Expected Influence (bEI) were used as centrality indices in the symptom network to characterize the structure of the symptoms.

RESULTS

The prevalence of depression, anxiety, and suicidality were 45.99 %, 28.40 %, and 7.71 %, respectively. The network analysis identified GAD5 ("Restlessness") as the most central symptom, followed by PHQ4 ("Fatigue") and GAD7 ("Feeling afraid"). Additionally, PHQ6 ("Guilt"), GAD5 ("Restlessness"), and PHQ8 ("Motor disturbance") were bridge nodes linking depressive and anxiety symptoms with suicidality. The flow network indicated that the strongest connections of S ("Suicidality") was with PHQ6 ("Guilt"), GAD7 ("Feeling afraid"), and PHQ2 ("Sad mood").

CONCLUSIONS

Depression, anxiety, and suicidality among mental health professionals were highly prevalent after China's Dynamic Zero-COVID Policy ended. Effective measures should target central and bridge symptoms identified in this network model to address the mental health problems in those at-risk.

Network analysis of suicide ideation and depression-anxiety symptoms among Chinese adolescents

Background

The co-occurrence of depression and anxiety among adolescents is typically associated with suicide ideation.

Aims

The study aimed to investigate the symptom-level relationship between suicide ideation and the comorbidity of depression and anxiety.

Methods

1501 adolescents aged 12-19 years were assessed using the Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder Scale, and 716 adolescents who scored ≥5 on both scales were selected as participants. Network analysis was used to identify the network structure of depressive symptoms and anxiety symptoms. Participants were categorised into either the suicide ideation or non-suicide ideation groups based on their scoring on the suicide-related item in PHQ-9. A comparison was made between the depression-anxiety symptom networks of the two groups.

Results

'Restlessness', 'sad mood' and 'trouble relaxing' were the most prominent central symptoms in the depression-anxiety symptom network, and 'restlessness', 'nervousness' and 'reduced movement' were the bridge symptoms in this network. 'Sad mood' was found to be directly related to 'suicide ideation' with the highest variance. The network structure was significantly different in properties between the suicide ideation group and the non-suicide ideation group, with 'restlessness' and 'sad mood' exhibiting significantly higher influence in the network of the suicide ideation group than that in the non-suicide ideation group.

Conclusion

Restlessness and sad mood could be targeted for the intervention of depression-anxiety symptoms among adolescents with suicide ideation.

Interactive changes in depression and loneliness symptoms prior to and during the COVID-19 pandemic: A longitudinal network analysis

OBJECTIVES

Depression and loneliness co-occur frequently. This study examined interactive changes between depression and loneliness among older adults prior to and during the COVID-19 pandemic from a longitudinal network perspective.

METHODS

This network study was based on data from three waves (2016-2017, 2018-2019, and 2020) of the English Longitudinal Study of Ageing (ELSA). Depression and loneliness were measured with the eight-item version of the Center for Epidemiologic Studies Depression Scale (CESD-8) and three item version of the University of California Los Angeles (UCLA) Loneliness Scale, respectively. A network model was constructed using an Ising Model while network differences were assessed using a Network Comparison Test. Central symptoms were identified via Expected Influence (EI).

RESULTS

A total of 4,293 older adults were included in this study. The prevalence and network of depression and loneliness did not change significantly between the baseline and pre-pandemic assessments but increased significantly from the pre-pandemic assessment to during COVID-19 assessment. The central symptom with the strongest increase from pre-pandemic to pandemic assessments was "Inability to get going" (CESD8) and the edge with the highest increase across depression-loneliness symptom communities was "Lack companionship" (UCLA1) - "Inability to get going" (CESD8). Finally, "Feeling depressed" (CESD1) and "Everything was an effort" (CESD2) were the most central symptoms over the three assessment periods.

CONCLUSIONS

The COVID-19 pandemic was associated with significant changes in the depression-loneliness network model. The most changed symptoms and edges could be treatment targets for reducing the risk of depression and loneliness in older adults.

The Inter-Relationships Between Depressive Symptoms and Suicidality Among Macau Residents After the "Relatively Static Management" COVID-19 Strategy: A Perspective of Network Analysis

Background

Suicidality is a global public health problem which has increased considerably during the coronavirus disease 2019 (COVID-19) pandemic. This study examined the inter-relationships between depressive symptoms and suicidality using network analysis among Macau residents after the "relatively static management" COVID-19 strategy.

Methods

An assessment of suicidal ideation (SI), suicide plan (SP), suicide attempt (SA) and depressive symptoms was conducted with the use of individual binary response items (yes/no) and Patient Health Questionnaire (PHQ-9). In the network analysis, central and bridge symptoms were identified in the network through "Expected Influence" and "Bridge Expected Influence", and specific symptoms that were directly associated with suicidality were identified via the flow function. Network Comparison Tests (NCT) were conducted to examine the gender differences in network characteristics.

Results

The study sample included a total of 1008 Macau residents. The prevalence of depressive symptoms and suicidality were 62.50% (95% CI = 59.4-65.5%) and 8.9% (95% CI = 7.2-10.9%), respectively. A network analysis of the sample identified SI ("Suicidal ideation") as the most central symptom, followed by SP ("Suicide plan") and PHQ4 ("Fatigue"). SI ("Suicidal ideation") and PHQ6 ("Guilt") were bridge nodes connecting depressive symptoms and suicidality. A flow network revealed that the strongest connection was between S ("Suicidality") and PHQ6 ("Guilt"), followed by S ("Suicidality") and PHQ 7 ("Concentration"), and S ("Suicidality") and PHQ3 ("Sleep").

Conclusion

The findings indicated that reduction of specific depressive symptoms and suicidal thoughts may be relevant in decreasing suicidality among adults. Further, suicide assessment and prevention measures should address the central and bridge symptoms identified in this study.

Understanding Comorbidity Between Non-Suicidal Self-Injury and Depressive Symptoms in a Clinical Sample of Adolescents: A Network Analysis

Background

Non-suicidal self-injury (NSSI) and depression often co-occur among adolescents with more severe clinical symptoms. This study examined the network structures of NSSI and depressive symptoms in adolescents.

Methods

Participants were recruited in the psychiatric outpatient clinics of three tertiary hospitals between April 10 and July 10, 2023. All participants been already found with self-injury behaviors in outpatient when enrolled. NSSI diagnostic criteria and Patient Health Questionnaire-9 (PHQ-9) were utilized to collect NSSI and depressive symptoms separately. We performed a network analysis to visualize the correlation between each symptom and to identify core and bridging symptoms in comorbidities.

Results

A total of 248 patients were enrolled in the study, with a mean age of 15.48 (SD = 1.62). Based on the PHQ-9 scores and grades, our results showed that the incidence of depression in adolescents with non-suicidal self-injury behavior was relatively high (N=235, 94.76%), with the majority having severe depression. The network analysis revealed that nodes D-6 "feeling bad, failing or letting yourself or your family down", D-1 "little interest or pleasure" and D-4 "feeling tired" were the most vital and most central symptoms. The most crucial bridging symptom is the node NSSI-8 "frequent thinking about self-injury", which connects the NSSI to the depression comorbid network.

Conclusion

This study offers a significant symptom-level conceptualization of the association between NSSI and depressive symptoms in a clinical sample of adolescents, which not only enhances our understanding of the comorbid but also identifies potential treatment targets to prevent and treat comorbidity between adolescent NSSI and depression.

Prevalence of COVID-19 fear and its association with quality of life and network structure among Chinese mental health professionals after ending China's dynamic zero-COVID policy: a national survey

Background

China recorded a massive COVID-19 pandemic wave after ending its Dynamic Zero-COVID Policy on January 8, 2023. As a result, mental health professionals (MHPs) experienced negative mental health consequences, including an increased level of fear related to COVID-19. This study aimed to explore the prevalence and correlates of COVID-19 fear among MHPs following the end of the Policy, and its association with quality of life (QoL) from a network analysis perspective.

Methods

A cross-sectional national study was conducted across China. The correlates of COVID-19 fear were examined using both univariate and multivariate analyses. An analysis of covariance (ANCOVA) was conducted to determine the relationship between fear of COVID-19 and QoL. Central symptoms were identified using network analysis through the "Expected Influence" of the network model while specific symptoms directly correlated with QoL were identified through the "flow function."

Results

A total of 10,647 Chinese MHPs were included. The overall prevalence of COVID-19 fear (FCV-19S total score ≥ 16) was 60.8% (95% CI = 59.9-61.8%). The binary logistic regression analysis found that MHPs with fear of COVID-19 were more likely to be married (OR = 1.198; p < 0.001) and having COVID-19 infection (OR = 1.235; p = 0.005) and quarantine experience (OR = 1.189; p < 0.001). Having better economic status (good vs. poor: OR = 0.479; p < 0.001; fair vs. poor: OR = 0.646; p < 0.001) and health status (good vs. poor: OR = 0.410; p < 0.001; fair vs. poor: OR = 0.617; p < 0.001) were significantly associated with a lower risk of COVID-19 fear. The ANCOVA showed that MHPs with fear of COVID-19 had lower QoL [F = 228.0, p < 0.001]. "Palpitation when thinking about COVID-19" was the most central symptom in the COVID-19 fear network model, while "Uncomfortable thinking about COVID-19" had the strongest negative association with QoL (average edge weight = -0.048).

Conclusion

This study found a high prevalence of COVID-19 fear among Chinese MHPs following the end of China's Dynamic Zero-COVID Policy. Developing effective prevention and intervention measures that target the central symptoms as well as symptoms correlated with QoL in our network structure would be important to address COVID-19 fear and improve QoL.

Prevalence of COVID-19 fear and its association with quality of life among fire service recruits after ceasing the dynamic zero-COVID policy in China

Background

In December 2022, China terminated its dynamic zero-COVID policy. To date, however, no research has been conducted upon mental health issues and their relationship with quality of life (hereafter QoL) among fire service recruits since the dynamic zero-COVID policy ended. This study explored fear of COVID-19 (FOC) prevalence and correlates as well as its network structure and interconnections with QoL among fire service recruits.

Methods

A cross-sectional survey design was used to assess fire service recruits in Beijing and Sichuan, Guangxi and Guizhou provinces of China between February 13 and 16, 2023. Fear of COVID-19 was measured using the Fear of COVID-19 Scale, depression was assessed with the Patient Health Questionnaire, anxiety was examined using the Generalized Anxiety Disorder scale, and QOL was evaluated with the World Health Organization Quality of Life-brief version. Univariate and multivariate analyses were used to explore correlates of COVID-19 fear. Network analysis assessed the structure of fear of COVID-19 and its associations with QoL.

Results

A total of 1,560 participants were included in this study. The overall prevalence of fear of COVID-19 was 38.85% (n = 606; 95% CI = 36.42-41.32%). Being afraid of COVID-19 was significantly related to depression (OR = 1.084; p < O.OO1) and physical fatigue (OR = 1.063; p = 0.026). Fire service recruits with more fear of COVID-19 had lower QOL (F = 18.061 p < 0.001) than those with less fear of COVID-19 did. The most central symptoms included FOC6 ("Sleep difficulties caused by worry about COVID-19"), FOC7 ("Palpitations when thinking about COVID-19") and FOC2 ("Uncomfortable to think about COVID-19"). The top three symptoms negatively associated with QoL were FOC4 ("Afraid of losing life because of COVID-19"), FOC6 ("Sleep difficulties caused by worry about COVID-19") and FOC2 ("Uncomfortable to think about COVID-19").

Conclusion

Over one-third of fire service recruits reported fear of COVID-19 after China's dynamic zero-COVID policy had terminated. Poorer QoL was related to fear of COVID-19. Targeting core symptoms of the fear network structure could help improve the physical and mental health of fire service recruits during public health crises.

Health behavior in Russia during the COVID-19 pandemic

In this article, we report results from a nationwide survey on pandemic-related health behavior in Russia. A total of 2,771 respondents aged 18 to 82 were interviewed between January 21 and March 3, 2021. The survey included questions on perceived vulnerability to coronavirus, prevention-related health behavior, readiness for vaccination, and general awareness about COVID-19. Descriptive data showed that 21.2% of respondents reported high vulnerability to the coronavirus, and 25% expressed fear. Moreover, 38.7% of the surveyed individuals reported low trust in vaccination efficacy, and 57.5% were unwilling to take a vaccine, which was much higher than the official data. Based on the evidence obtained, four types of health behavior during the pandemic were constructed. Rational (29.3%) and denying (28.6%) behaviors prevailed in men, while women were found to more likely behave with a vaccine-hesitant demeanor (35.7%). Educational background affected the proportion of respondents with the denying type of health behavior, who were also of younger age. The rational behavioral type was found to be more common among respondents aged above 50 years and prevailed as well among individuals with university degrees. The middle-aged population of Russia was highly compliant with prevention-related health practices; however, vaccine hesitancy was also high among them. Furthermore, health behaviors varied significantly across the Federal Districts of Russia. We are convinced that our results contribute to existing public health practices and may help improve communication campaigns to cause positive health behaviors.