A systematic analysis of online broadcasts of suicidality in China

Mind the gap: Exploring differences in suicide literacy between cybersuicide and offline suicide

Introduction

The highly public nature of cybersuicide contradicts long-held beliefs of offline suicide, which may cause differences in the way people perceive and respond to both of them. However, knowledge of whether and how suicide literacy differs between cybersuicide and offline suicide is limited.

Methods

By analyzing social media data, this paper focused on livestreamed suicide and aimed to compare suicide literacy between cybersuicide and offline suicide on three aspects, including false knowledge structure, extent of association with stigma, and linguistic expression pattern. 7,236 Sina Weibo posts with relevant keywords were downloaded and analyzed. First, a content analysis was performed by human coders to determine whether each post reflected suicide-related false knowledge and stigma. Second, a text analysis was conducted using the Simplified Chinese version of LIWC software to automatically extract psycholinguistic features from each post. Third, based on selected features, classification models were developed using machine learning techniques to differentiate false knowledge of cybersuicide from that of offline suicide.

Results

Results showed that, first, cybersuicide-related posts generally reflected more false knowledge than offline suicide-related posts ( χ 1 2 = 255.13, p < 0.001). Significant differences were also observed in seven false knowledge types. Second, among posts reflecting false knowledge, cybersuicide-related posts generally carried more stigma than offline suicide-related posts ( χ 1 2 = 116.77, p < 0.001). Significant differences were also observed in three false knowledge types. Third, among established classification models, the highest F1 value reached 0.70.

Discussion

The findings provide evidence of differences in suicide literacy between cybersuicide and offline suicide, and indicate the need for public awareness campaigns that specifically target cybersuicide.

Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo

Background

The new reality of cybersuicide raises challenges to ideologies about the traditional form of suicide that does not involve the internet (offline suicide), which may lead to changes in audience’s attitudes. However, knowledge on whether stigmatizing attitudes differ between cybersuicides and offline suicides remains limited.

Objective

This study aims to consider livestreamed suicide as a typical representative of cybersuicide and use social media data (Sina Weibo) to investigate the differences in stigmatizing attitudes across cybersuicides and offline suicides in terms of attitude types and linguistic characteristics.

Methods

A total of 4393 cybersuicide-related and 2843 offline suicide-related Weibo posts were collected and analyzed. First, human coders were recruited and trained to perform a content analysis on the collected posts to determine whether each of them reflected stigma. Second, a text analysis tool was used to automatically extract a number of psycholinguistic features from each post. Subsequently, based on the selected features, a series of classification models were constructed for different purposes: differentiating the general stigma of cybersuicide from that of offline suicide and differentiating the negative stereotypes of cybersuicide from that of offline suicide.

Results

In terms of attitude types, cybersuicide was observed to carry more stigma than offline suicide (χ²₁=179.8; P<.001). Between cybersuicides and offline suicides, there were significant differences in the proportion of posts associated with five different negative stereotypes, including stupid and shallow (χ²₁=28.9; P<.001), false representation (χ²₁=144.4; P<.001), weak and pathetic (χ²₁=20.4; P<.001), glorified and normalized (χ²₁=177.6; P<.001), and immoral (χ²₁=11.8; P=.001). Similar results were also found for different genders and regions. In terms of linguistic characteristics, the F-measure values of the classification models ranged from 0.81 to 0.85.

Conclusions

The way people perceive cybersuicide differs from how they perceive offline suicide. The results of this study have implications for reducing the stigma against suicide.

Appropriate Strategies for Reducing the Negative Impact of Online Reports of Suicide and Public Opinion From Social Media in China

Suicide events may have a negative impact on all of society. The media plays a significant role in suicide prevention. Therefore, the aims of this study are (a) to understand the association between characteristics of suicide events and characteristics of who committed suicide, and event impact indexes (EIIs) of suicide reported on the internet; (b) to analyze violation of recommendations for reporting suicide by Weibo, and (c) to investigate the effect of online reports of suicide on public opinion. We carried out a content analysis of online reports of suicide. This study analyzed 113 suicide events, 300 news reports of suicide, and 2,654 Weibo comments about suicide collected from the WeiboReach between 2015 and 2020. We used a t-test and analysis of variance (ANOVA) to explore the potential factors associated with the EIIs of suicide events. The results found that (a) The suicide events reported on the internet during COVID-19 and those related to celebrities and students tend to have higher EIIs; (b) suicide reports on Weibo frequently violated WHO recommendations for suicide reporting in the media; and (c) public opinion of suicide reporting in the online media was mostly emotional and irrational, which is not beneficial for public mental health and suicide prevention. In conclusion, first, the situation of many people working from home or studying from home and spreading more time online during COVID-19 may lead to suicide events obtain more public attention. Online media could further improve public responsible reporting and daily media-content surveillance, especially taking particular care in those suicide events during COVID-19, and related to celebrities and students, which may have a higher event impact on the internet. Second, health managers should regular assessment of observance of the WHO recommendations for suicide reporting by online social media to prevent suicide. Third, health communication managers should use big data to identify, assess, and manage harmful information about suicide; and track anyone affected by suicide-related reports on social media to reduce the negative impact of public opinion to intervene suicide in the early stage of suicide.

The consequences of cyberbullying and traditional bullying victimization among adolescents: Gender differences in psychological symptoms, self-harm and suicidality

This study aimed to examine the effects of different types of bullying victimization (direct, relational, and cyber) on psychological symptoms, self-harm, and suicidality (including suicidal ideation and attempts) among adolescents, and to explore whether these effects may vary by gender. The data were obtained from a cross-sectional study of adolescents (n = 11,248, 46.7% females) with a mean age of 13.83 years from grade 5 to 12 in Henan, China. A series of binary logistic regression models were conducted to estimate the associations between different types of bullying victimization and psychological symptoms, self-harm, suicidal ideation, and suicidal attempts, after adjusting for demographic covariates. All three types of bullying victimization were significantly associated with psychological symptoms, self-harm, suicidal ideation, and suicidal attempts. Adolescents who suffered from cyberbullying victimization were more likely to commit self-harm and suicidal attempts as compared to direct and relational victimization. Female adolescents who suffered from relational bullying tend to have a higher risk of suicidal attempts than male adolescents. The current study demonstrated the negative effect of bullying victimization on adolescents' adverse psychological outcomes and gender difference need to be taken into account in developing targeted intervention strategies to address bullying victimization.

HPA Axis in the Pathomechanism of Depression and Schizophrenia: New Therapeutic Strategies Based on Its Participation

The hypothalamic-pituitary-adrenal (HPA) axis is involved in the pathophysiology of many neuropsychiatric disorders. Increased HPA axis activity can be observed during chronic stress, which plays a key role in the pathophysiology of depression. Overactivity of the HPA axis occurs in major depressive disorder (MDD), leading to cognitive dysfunction and reduced mood. There is also a correlation between the HPA axis activation and gut microbiota, which has a significant impact on the development of MDD. It is believed that the gut microbiota can influence the HPA axis function through the activity of cytokines, prostaglandins, or bacterial antigens of various microbial species. The activity of the HPA axis in schizophrenia varies and depends mainly on the severity of the disease. This review summarizes the involvement of the HPA axis in the pathogenesis of neuropsychiatric disorders, focusing on major depression and schizophrenia, and highlights a possible correlation between these conditions. Although many effective antidepressants are available, a large proportion of patients do not respond to initial treatment. This review also discusses new therapeutic strategies that affect the HPA axis, such as glucocorticoid receptor (GR) antagonists, vasopressin V1B receptor antagonists and non-psychoactive CB1 receptor agonists in depression and/or schizophrenia.

Prevalence of comorbid depression in schizophrenia: A meta-analysis of observational studies

INTRODUCTION

Comorbid depressive symptoms (depression thereafter) often occur in schizophrenia and are associated with negative outcomes. This meta-analysis estimated the prevalence of comorbid depression and its associated factors in schizophrenia.

METHODS

Both international (PubMed, EMBASE, PsycINFO, and Web of Science) and Chinese (WANFANG and CNKI) databases were systematically searched. Studies with data on the prevalence of comorbid depression in schizophrenia measured with the Calgary Depression Scale for Schizophrenia (CDSS) were included. Random-effects models were used in all analyses.

RESULTS

Fifty-three studies covering 9,879 patients were included. The pooled prevalence of comorbid depression was 28.6% (95%CI: 25.3%-32.2%). Subgroup analyses revealed that studies examining inpatients, being published in Chinese language, or those with lower CDSS cut-od values reported higher depression rates. Meta-regression analyses indicated that the rate of depression was positively associated with publication year, proportion of males, mean age, and severity of psychotic symptoms, and negatively associated with illness duration and study quality.

CONCLUSION

Comorbid depression is common in schizophrenia. Due to its negative impact on patients' quality of life and prognosis, regular screening and effective treatment for comorbid depression should be implemented in patients with schizophrenia.

Mediation Effect of Suicide-Related Social Media Use Behaviors on the Association Between Suicidal Ideation and Suicide Attempt: Cross-Sectional Questionnaire Study

Background

A limited number of studies have examined the differences in suicide-related social media use behaviors between suicide ideators and suicide attempters or have sought to elucidate how these social media usage behaviors contributed to the transition from suicidal ideation to suicide attempt.

Objective

Suicide attempts can be acquired through suicide-related social media use behaviors. This study aimed to propose 3 suicide-related social media use behaviors (ie, attending to suicide information, commenting on or reposting suicide information, or talking about suicide) based on social cognitive theory, which proposes that successive processes governing behavior transition include attentional, retention, production, and motivational processes.

Methods

We aimed to examine the mediating role of suicide-related social media use behaviors in Chinese social media users with suicidal risks. A sample of 569 Chinese social media users with suicidal ideation completed measures on suicidal ideation, suicide attempt, and suicide-related social media use behaviors.

Results

The results demonstrated that suicide attempters showed a significantly higher level of suicidal ideation (t_563.64=5.04; P<.001; two-tailed) and more suicide-related social media use behaviors, which included attending to suicide information (t₅₆₇=1.94; P=.05; two-tailed), commenting on or reposting suicide information (t₅₆₇=2.12; P=.03; two-tailed), or talking about suicide (t_542.22=5.12; P<.001; two-tailed). Suicidal ideation also affected suicide attempts through the mediational chains.

Conclusions

Our findings thus support the social cognitive theory, and there are implications for population-based suicide prevention that can be achieved by identifying behavioral signals.

Unmedicated patients with schizophrenia in economically underdeveloped areas of China

OBJECTIVES

Untreated schizophrenia commonly leads to poor prognosis. The medication treatment rate of schizophrenia patients in economically underdeveloped areas of China has not been well-studied. This study aimed to examine the pattern of unmedicated schizophrenia patients in economically underdeveloped rural and urban areas of China.

METHOD

A total of 4240 schizophrenia patients in Lanzhou (1720 rural and 2520 urban patients) registered in the community mental-health service system in Lanzhou, Gansu province were included. Their socio-demographic and clinical characteristics including medication treatment status were collected and analyzed.

RESULTS

The proportion of unmedicated schizophrenia patients was 22.5% (n = 953) in the whole sample, with 32.3% (556/1720) in rural and 15.8% (397/2520) in urban patients (X²=161.1, P < 0.001). Multiple logistic regression analyses revealed that unmedicated schizophrenia patients in rural area were more likely to be older (OR=1.02, 95%CI: 1.01-1.03), male (OR=1.35, 95%CI: 1.07-1.71), unmarried (OR=0.71, 95%CI: 0.55-0.91), and have lower educational level (OR=0.39, 95%CI: 0.24-0.65), longer illness duration (OR=1.01, 95%CI: 1.00-1.02) and less frequent admissions (OR=0.46, 95%CI: 0.38-0.54). In contrast, unmedicated patients in urban area were more likely to be older (OR=1.01, 95%CI: 1.00-1.02), unmarried (OR=0.77, 95%CI: 0.61-0.98), employed (OR=2.38, 95%CI: 1.87-3.04), and have lower educational level (OR=0.49, 95%CI: 0.37-0.65), better financial status (OR=0.60, 95%CI: 0.48-0.76) and less frequent admissions (OR=0.81, 95%CI: 0.75-0.87).

CONCLUSIONS

The rate of unmedicated schizophrenia patients is high in economically underdeveloped areas of China, particularly in rural areas. Effective policies and measures should be implemented urgently to improve the treatment rate in this population.

A Psycholinguistic Analysis of Responses to Live-Stream Suicides on Social Media

Live-stream suicide has become an emerging public health problem in many countries. Regular users are often the first to witness and respond to such suicides, emphasizing their impact on the success of crisis intervention. In order to reduce the likelihood of suicide deaths, this paper aims to use psycholinguistic analysis methods to facilitate automatic detection of negative expressions in responses to live-stream suicides on social media. In this paper, a total of 7212 comments posted on suicide-related messages were collected and analyzed. First, a content analysis was performed to investigate the nature of each comment (negative or not). Second, the simplified Chinese version of the LIWC software was used to extract 75 psycholinguistic features from each comment. Third, based on 19 selected key features, four classification models were established to differentiate between comments with and without negative expressions. Results showed that 19.55% of 7212 comments were recognized as "making negative responses". Among the four classification models, the highest values of Precision, Recall, F-Measure, and Screening Efficacy reached 69.8%, 85.9%, 72.9%, and 47.1%, respectively. This paper confirms the need for campaigns to reduce negative responses to live-stream suicides and support the use of psycholinguistic analysis methods to improve suicide prevention efforts.

Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps

PURPOSE OF REVIEW

As rates of suicide continue to rise, there is urgent need for innovative approaches to better understand, predict, and care for those at high risk of suicide. Numerous mobile and sensor technology solutions have already been proposed, are in development, or are already available today. This review seeks to assess their clinical evidence and help the reader understand the current state of the field.

RECENT FINDINGS

Advances in smartphone sensing, machine learning methods, and mobile apps directed towards reducing suicide offer promising evidence; however, most of these innovative approaches are still nascent. Further replication and validation of preliminary results is needed. Whereas numerous promising mobile and sensor technology based solutions for real time understanding, predicting, and caring for those at highest risk of suicide are being studied today, their clinical utility remains largely unproven. However, given both the rapid pace and vast scale of current research efforts, we expect clinicians will soon see useful and impactful digital tools for this space within the next 2 to 5 years.