Suicide prevention and COVID-19

Declining suicide rates in China (1990-2017): Gender and age specific analyses

BACKGROUND

In China suicide rates have been declining for about three decades. Patterns of suicide for women and men across the lifespan over time however have not been systematically documented.

METHODS

Official suicide mortality data (from 1990 to 2017) available via China CDC were used to examine suicide patterns by gender and age in each of the 33 provincial-level regions. Suicide data were aggregated by five years, except for the year of 2017. The bar graphs were used to descriptive the change tread of the suicide rate.

RESULTS

In the past three decades, the decline in female suicide rates was greater than that in the male rates, with the overall male to female (M/F) ratio changing from 0.88 in 1996 to 1.56 in 2017. The overall suicide rate of male was 8.82 and female was 5.65 per 100,000 persons in 2017. However the decline of suicide rates for people aged 70 and older was the greatest declination (33.73/per 100,000 persons) among all the age groups in China.

CONCLUSION

Overall suicide rates have declined over the three decades in China, particularly among females and individuals age 70+ years. Suicide rates continue to be higher among individuals aged 50 and older (particularly among men), and this population should continue to the focus for prevention.

Depression and anxiety among Macau residents during the COVID-19 outbreak: A network analysis perspective

Background

The 2019 novel coronavirus disease (COVID-19) outbreak affected people's lifestyles and increased their risk for depressive and anxiety symptoms (depression and anxiety, respectively hereafter). We assessed depression and anxiety in residents of Macau during "the 6.18 COVID-19 outbreak" period and explored inter-connections of different symptoms from the perspective of network analysis.

Methods

In this cross-sectional study, 1,008 Macau residents completed an online survey comprising the nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalized Anxiety Disorder Scale (GAD-7) to measure depression and anxiety, respectively. Central and bridge symptoms of the depression-anxiety network model were evaluated based on Expected Influence (EI) statistics, while a bootstrap procedure was used to test the stability and accuracy of the network model.

Results

Descriptive analyses indicated the prevalence of depression was 62.5% [95% confidence interval (CI) = 59.47-65.44%], the prevalence of anxiety was 50.2% [95%CI = 47.12-53.28%], and 45.1% [95%CI = 42.09-48.22%] of participants experienced comorbid depression and anxiety. "Nervousness-Uncontrollable worry" (GADC) (EI = 1.15), "Irritability" (GAD6) (EI = 1.03), and "Excessive worry" (GAD3) (EI = 1.02) were the most central symptoms, while "Irritability" (GAD6) (bridge EI = 0.43), "restlessness" (GAD5) (bridge EI = 0.35), and "Sad Mood" (PHQ2) (bridge EI = 0.30) were key bridge symptoms that emerged in the network model.

Conclusion

Nearly half of residents in Macau experienced comorbid depression and anxiety during the 6.18 COVID-19 outbreak. Central and bridge symptoms identified in this network analysis are plausible, specific targets for treatment and prevention of comorbid depression and anxiety related to this outbreak.

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

BACKGROUND

Persons with suicidality including suicidal ideation (SI), suicide plans (SP) and/or suicide attempts (SA) are at higher risk for future suicide than those without suicidality. To reduce the risk of future suicide, it is important to understand symptoms of emotional distress that have the strongest links with SI, SP and SA. This network analysis examined item-level relations of depressive and anxiety symptoms with suicidality among adolescents during the COVID-19 pandemic.

METHODS

Adolescents between 12 and 20 years of age were assessed with the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and individual binary reponse (no/yes) items assessing SI, SP, and SA during the pandemic. The structure of depressive symptoms, anxiety symptoms and suicidality was characterized using "Expected Influence" and "Bridge Expected Influence" as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Node-specific predictive betweenness was computed to examine short paths of anhedonia, other depressive symptoms and anxiety symptoms with suicidality. A Network Comparison Test (NCT) was conducted to examine whether network characteristics differed based on gender.

RESULTS

Prevalence rates of depressive symptoms, anxiety symptoms, and suicidality were 44.60 % (95% confidence interval (CI) = 41.53-47.67 %), 31.12 % (95%CI = 28.26-33.98 %), and 16.95 % (95%CI = 14.63-19.26 %), respectively, in the study sample. The network analysis identified GAD3 ("Worry too much") as the most central symptom, followed by GAD6 ("Irritability") and PHQ6 ("Guilt") in the sample. Additionally, PHQ6 ("Guilt"), GAD6 ("Irritability"), and PHQ2 ("Sad mood") were bridge nodes linking depressive and anxiety symptoms with suicidality. A flow network indicated that the connection between S ("Suicidality") and PHQ6 ("Guilt") reflected the strongest connection, followed by connections of S ("Suicidality") with GAD2 ("Uncontrollable worrying"), and S ("Suicidality") with PHQ2 ("Sad mood"). Finally, PHQ2 ("Sad mood") was the main bridge node linking anhedonia with other depressive and anxiety symptoms and suicidality in the sample.

CONCLUSIONS

Findings highlight the potential importance of reducing specific depressive and anxiety symptoms as possible means of reducing suicidality among adolescents during the pandemic. Central symptoms and key bridge symptoms identified in this study should be targeted in suicide prevention for at-risk adolescents.

Cyberbully victimization and its association with residual depressive symptoms among clinically stable adolescents with psychiatric disorders during the COVID-19 pandemic: A perspective from network analysis

Objective

This study examined the prevalence of cyberbullying and its relationship with residual depressive symptoms in this patient population during the COVID-19 outbreak using network analysis.

Methods

This was a multicenter, cross-sectional study. Adolescent patients attending maintenance treatment at outpatient departments of three major psychiatric hospitals were included. Experience of cyberbullying was measured with a standard question, while the severity of Internet addiction and depressive symptoms were measured using the Internet Addiction Test and the Patient Health Questionnaire-9, respectively. The network structure of depression and cyberbully were characterized and indices of "Expected Influence" was used to identify symptoms central to the network. To identify particular symptoms that were directly associated with cyberbully, the flow function was used.

Results

Altogether 1,265 patients completed the assessments. The overall prevalence of cyberbullying was 92.3% (95% confidence interval (CI): 90.8-93.7%). Multiple logistic regression analysis revealed that male gender (p = 0.04, OR = 1.72, 95%CI: 1.04-2.85) was significantly associated with higher risk of cyberbullying, while a relapse of illness during the COVID-19 pandemic was significantly associated with a lower risk of cyberbullying (p = 0.03, OR = 0.50, 95%CI: 0.27-0.93). In the network of depression and cyberbully, "Sad mood," "Anhedonia" and "Energy" were the most central (influential) symptoms. Furthermore, "Suicidal ideation" had the strongest negative association with cyberbully followed by "Guilt".

Conclusion

During the COVID-19 pandemic, the experience of cyberbullying was highly prevalent among clinically stable adolescent psychiatric patients, particularly male patients. This finding should raise awareness of this issue emphasizing the need for regular screening and interventions for adolescent patients. Central symptoms (e.g., "Sad mood," "Anhedonia" and "Energy") identified in this study should be targeted in interventions and preventive measures.

Mental health status among non-medical college students returning to school during the COVID-19 pandemic in Zhanjiang city: A cross-sectional study

The coronavirus disease-2019 (COVID-19) pandemic has brought huge and continuous damage to mental health. The mental health of non-medical college students after returning to school remains largely unknown and the influencing factors were awaited to be deciphered. This cross-sectional study was launched among 1,083 non-medical students in Zhanjiang city by means of online survey (WeChat App) from August 1st, 2022 to August 7th, 2022. Knowledge about COVID-19 and attitude toward COVID-19 were assessed by using 7-items and 5-items questionnaires, respectively. Sleep quality, anxiety and depression symptoms were evaluated by Pittsburgh sleep quality index (PSQI), Hamilton depression rating scale-17 (HDRS-17) and self-rating anxiety scale (SAS), respectively. The results showed that more than half of the participants were knowledgeable about COVID-19. The majority of the participants held positive attitude toward COVID-19. The data demonstrated that 6.8% students had poor sleep quality, and 1.86, 0.37 and 0.37% students had mild, moderate and severe anxiety, respectively. About 26.7, 4.7 and 1.7% students had minimal, mild-moderate and severe depression. Female students showed higher proportions of anxiety (p = 0.02) and depression (p < 0.0001) than male students. Students with monthly household income below 3,000 RMB were more vulnerable to anxiety (p = 0.017) and depression (p = 0.004). Correlation analysis and Multivariate logistic regression analysis results showed that lower grade was positively related with anxiety and depression. Female students, income lower than 3,000 RMB/month, poor knowledge about COVID-19 and negative attitude toward COVID-19 were associated with insomnia, anxiety and depression. This study indicated that during the COVID-19 pandemic, a majority of non-medical students returning to school remained good sleep quality and a small number of students suffered from depression and anxiety. To our knowledge, this is a novel study revealing the mental health of non-medical college students concerning COVID-19 in Zhanjiang.

Suicidality in clinically stable bipolar disorder and schizophrenia patients during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic has a disproportionate impact on vulnerable subpopulations, including those with severe mental illness (SMI). This study examined the one-year prevalence of suicidal ideation (SI), suicide plans (SP), and suicide attempts (SA) in bipolar disorder (BD) and schizophrenia (SCZ) patients during the pandemic. Prevalence rates were compared between the two disorders and associated factors were examined. A survey was conducted in six tertiary psychiatric hospitals and psychiatric units. People with a diagnosis of BD or SCZ were invited to participate. SI, SP, and SA (suicidality for short) were assessed and associated factors were examined using binary logistical regression. The 1-year prevalence of SI, SP and SA in BD patients were 58.3%, (95% CI: 54.1-62.6%), 38.4% (95% CI: 34.3-42.6%) and 38.6% (95% CI: 34.5-42.8%), respectively, which were higher than the corresponding figures in SCZ patients (SI: 33.2%, 95% CI: 28.6-37.8%; SP: 16.8%, 95% CI: 13.2-20.5%; SA: 19.4%, 95% CI: 15.5-23.3%). Patients with younger age, experience of cyberbullying, a history of SA among family or friends, a higher fatigue and physical pain score, inpatient status, and severe depressive symptoms were more likely to have suicidality. The COVID-19 pandemic was associated with increased risk of suicidality, particularly in BD patients. It is of importance to regularly screen suicidality in BD and SCZ patients during the pandemic even if they are clinically stable.

Antidepressants for COVID-19: A systematic review

OBJECTIVE

To systematically examine the efficacy and safety of antidepressants for the treatment of coronavirus disease 2019 (COVID-19).

METHODS

A systematic search was performed independently by two researchers based on Chinese Journal Net, WanFang, PsycINFO, Cochrane Library, PubMed, and EMBASE.

RESULTS

Seven studies (n = 92,947) including three retrospective studies (n = 91,083), two randomized clinical trials (RCTs, n = 1649), two prospective cohort study (n = 215) involving (n = 92,947) patients with COVID-19 were examined. For RCTs, fluvoxamine outperformed placebo in reducing clinical deterioration and hospitalisation for COVID-19 patients. For retrospective studies, antidepressants (2 studies) and fluoxetine (1 study) possibly reduced the risk of mortality in patients with COVID-19. Results from two remaining studies supported the superiority of fluvoxamine in reducing risk of mortality in COVID-19 patients. The two RCTs that examined the safety of fluvoxamine for COVID-19 patients found inconsistent results but no significant group differences in the dropout rate.

CONCLUSION

This systematic review found emerging evidence for fluvoxamine in reducing the risk of mortality and hospitalisation in COVID-19 patients, but inconsistent evidence for the safety of fluvoxamine in COVID-19 patients. More studies are needed to determine the efficacy and safety of antidepressants for the treatment of COVID-19.

Network Analysis of Depressive Symptoms Among Residents of Wuhan in the Later Stage of the COVID-19 Pandemic

Background: Depression has been a common mental health problem during the COVID-19 epidemic. From a network perspective, depression can be conceptualized as the result of mutual interactions among individual symptoms, an approach that may elucidate the structure and mechanisms underlying this disorder. This study aimed to examine the structure of depression among residents in Wuhan, the epicenter of the COVID-19 outbreak in China, in the later stage of the COVID-19 pandemic. Methods: A total of 2,515 participants were recruited from the community via snowball sampling. The Patient Health Questionnaire was used to assess self-reported depressive symptoms with the QuestionnaireStar program. The network structure and relevant centrality indices of depression were examined in this sample. Results: Network analysis revealed Fatigue, Sad mood, Guilt and Motor disturbances as the most central symptoms, while Suicide and Sleep problems had the lowest centrality. No significant differences were found between women and men regarding network structure (maximum difference = 0.11, p = 0.44) and global strength (global strength difference = 0.04; female vs. male: 3.78 vs. 3.83, p = 0.51), a finding that suggests there are no gender differences in the structure or centrality of depressive symptoms. Limitations: Due to the cross-sectional study design, causal relationships between these depressive symptoms or dynamic changes in networks over time could not be established. Conclusions: Fatigue, Sad mood, Guilt, and Motor disturbances should be prioritized as targets in interventions and prevention efforts to reduce depression among residents in Wuhan, in the later stage of the COVID-19 pandemic.