Attitudes towards suicide attempts broadcast on social media: an exploratory study of Chinese microblogs.
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ABSTRACT:
SUBMITTER: Li A
PROVIDER: S-EPMC4570843 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
Attitudes towards suicide attempts broadcast on social media: an exploratory study of Chinese microblogs.
Li Ang A Huang Xiaoxiao X Hao Bibo B O'Dea Bridianne B Christensen Helen H Zhu Tingshao T
PeerJ 20150908
Introduction. Broadcasting a suicide attempt on social media has become a public health concern in many countries, particularly in China. In these cases, social media users are likely to be the first to witness the suicide attempt, and their attitudes may determine their likelihood of joining rescue efforts. This paper examines Chinese social media (Weibo) users' attitudes towards suicide attempts broadcast on Weibo. Methods. A total of 4,969 Weibo posts were selected from a customised Weibo Use ...[more]
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Project description:BackgroundThe COVID-19 infodemic has been disseminating rapidly on social media and posing a significant threat to people's health and governance systems.ObjectiveThis study aimed to investigate and analyze posts related to COVID-19 misinformation on major Chinese social media platforms in order to characterize the COVID-19 infodemic.MethodsWe collected posts related to COVID-19 misinformation published on major Chinese social media platforms from January 20 to May 28, 2020, by using PythonToolkit. We used content analysis to identify the quantity and source of prevalent posts and topic modeling to cluster themes related to the COVID-19 infodemic. Furthermore, we explored the quantity, sources, and theme characteristics of the COVID-19 infodemic over time.ResultsThe daily number of social media posts related to the COVID-19 infodemic was positively correlated with the daily number of newly confirmed (r=0.672, P<.01) and newly suspected (r=0.497, P<.01) COVID-19 cases. The COVID-19 infodemic showed a characteristic of gradual progress, which can be divided into 5 stages: incubation, outbreak, stalemate, control, and recovery. The sources of the COVID-19 infodemic can be divided into 5 types: chat platforms (1100/2745, 40.07%), video-sharing platforms (642/2745, 23.39%), news-sharing platforms (607/2745, 22.11%), health care platforms (239/2745, 8.71%), and Q&A platforms (157/2745, 5.72%), which slightly differed at each stage. The themes related to the COVID-19 infodemic were clustered into 8 categories: "conspiracy theories" (648/2745, 23.61%), "government response" (544/2745, 19.82%), "prevention action" (411/2745, 14.97%), "new cases" (365/2745, 13.30%), "transmission routes" (244/2745, 8.89%), "origin and nomenclature" (228/2745, 8.30%), "vaccines and medicines" (154/2745, 5.61%), and "symptoms and detection" (151/2745, 5.50%), which were prominently diverse at different stages. Additionally, the COVID-19 infodemic showed the characteristic of repeated fluctuations.ConclusionsOur study found that the COVID-19 infodemic on Chinese social media was characterized by gradual progress, videoization, and repeated fluctuations. Furthermore, our findings suggest that the COVID-19 infodemic is paralleled to the propagation of the COVID-19 epidemic. We have tracked the COVID-19 infodemic across Chinese social media, providing critical new insights into the characteristics of the infodemic and pointing out opportunities for preventing and controlling the COVID-19 infodemic.
| S-EPMC7869922 | biostudies-literature
Project description:BackgroundSocial media is increasingly being used by young people for health-related issues, including communicating about suicide. Due to the concerns about causing distress or inducing suicidal thoughts or behaviors, to date young people neither have been engaged in the development of social media-based suicide prevention interventions nor have interventions focused on educating young people about safe ways to communicate about suicide online. Given the potential that social media holds to deliver messages to vast numbers of people across space and time and the fact that young people often prefer to seek help from their friends and peers, safely educating and engaging young people to develop suicide prevention messages that can be delivered via social media is an obvious next step.ObjectivesThe objectives of this study were to (1) provide education to a small number of secondary school students about safe ways to communicate about suicide via social media; (2) engage the same young people in the development of a suite of social media-based suicide prevention multimedia messages; (3) assess the impact of this on participants; and (4) assess the acceptability and safety of the messages developed.MethodsThis study involved two phases. In phase 1, 20 participants recruited from two schools took part in an 8- to 10-week program during which they were provided with psychoeducation about mental health and suicide, including how to talk safely about suicide online, and they were then supported to design and develop their own media messages. These participants completed an evaluation questionnaire at the conclusion of the program. In phase 2, a larger group of participants (n=69), recruited via an opt-in process, viewed the media messages and completed a short questionnaire about each one.ResultsParticipants in phase 1 enjoyed the program and reported that they learned new skills, such as how to talk safely about suicide online, and felt more able to provide emotional support to others (16/20, 80%). No participants reported that the program made them feel suicidal. Participants in phase 2 generally rated the media messages as safe and acceptable, although some messages were rated more highly than others.ConclusionsThis study suggests that young people can be safely engaged in developing suicide prevention messages, which can be disseminated via social media. Engaging young people in this process may improve the traction that such campaigns will have with other young people. The study also suggests that educating young people regarding how to talk safely about suicide online has multiple benefits and is not associated with distress. Overall, these findings pave the way for new approaches to prevent suicide among young people.
| S-EPMC5647460 | biostudies-literature
Project description:Introduction. Suicide has become a serious worldwide epidemic. Early detection of individual suicide risk in population is important for reducing suicide rates. Traditional methods are ineffective in identifying suicide risk in time, suggesting a need for novel techniques. This paper proposes to detect suicide risk on social media using a Chinese suicide dictionary. Methods. To build the Chinese suicide dictionary, eight researchers were recruited to select initial words from 4,653 posts published on Sina Weibo (the largest social media service provider in China) and two Chinese sentiment dictionaries (HowNet and NTUSD). Then, another three researchers were recruited to filter out irrelevant words. Finally, remaining words were further expanded using a corpus-based method. After building the Chinese suicide dictionary, we tested its performance in identifying suicide risk on Weibo. First, we made a comparison of the performance in both detecting suicidal expression in Weibo posts and evaluating individual levels of suicide risk between the dictionary-based identifications and the expert ratings. Second, to differentiate between individuals with high and non-high scores on self-rating measure of suicide risk (Suicidal Possibility Scale, SPS), we built Support Vector Machines (SVM) models on the Chinese suicide dictionary and the Simplified Chinese Linguistic Inquiry and Word Count (SCLIWC) program, respectively. After that, we made a comparison of the classification performance between two types of SVM models. Results and Discussion. Dictionary-based identifications were significantly correlated with expert ratings in terms of both detecting suicidal expression (r = 0.507) and evaluating individual suicide risk (r = 0.455). For the differentiation between individuals with high and non-high scores on SPS, the Chinese suicide dictionary (t1: F 1 = 0.48; t2: F 1 = 0.56) produced a more accurate identification than SCLIWC (t1: F 1 = 0.41; t2: F 1 = 0.48) on different observation windows. Conclusions. This paper confirms that, using social media, it is possible to implement real-time monitoring individual suicide risk in population. Results of this study may be useful to improve Chinese suicide prevention programs and may be insightful for other countries.
| S-EPMC4690390 | biostudies-literature
Project description:Early identification and intervention are imperative for suicide prevention. However, at-risk people often neither seek help nor take professional assessment. A tool to automatically assess their risk levels in natural settings can increase the opportunity for early intervention.The aim of this study was to explore whether computerized language analysis methods can be utilized to assess one's suicide risk and emotional distress in Chinese social media.A Web-based survey of Chinese social media (ie, Weibo) users was conducted to measure their suicide risk factors including suicide probability, Weibo suicide communication (WSC), depression, anxiety, and stress levels. Participants' Weibo posts published in the public domain were also downloaded with their consent. The Weibo posts were parsed and fitted into Simplified Chinese-Linguistic Inquiry and Word Count (SC-LIWC) categories. The associations between SC-LIWC features and the 5 suicide risk factors were examined by logistic regression. Furthermore, the support vector machine (SVM) model was applied based on the language features to automatically classify whether a Weibo user exhibited any of the 5 risk factors.A total of 974 Weibo users participated in the survey. Those with high suicide probability were marked by a higher usage of pronoun (odds ratio, OR=1.18, P=.001), prepend words (OR=1.49, P=.02), multifunction words (OR=1.12, P=.04), a lower usage of verb (OR=0.78, P<.001), and a greater total word count (OR=1.007, P=.008). Second-person plural was positively associated with severe depression (OR=8.36, P=.01) and stress (OR=11, P=.005), whereas work-related words were negatively associated with WSC (OR=0.71, P=.008), severe depression (OR=0.56, P=.005), and anxiety (OR=0.77, P=.02). Inconsistently, third-person plural was found to be negatively associated with WSC (OR=0.02, P=.047) but positively with severe stress (OR=41.3, P=.04). Achievement-related words were positively associated with depression (OR=1.68, P=.003), whereas health- (OR=2.36, P=.004) and death-related (OR=2.60, P=.01) words positively associated with stress. The machine classifiers did not achieve satisfying performance in the full sample set but could classify high suicide probability (area under the curve, AUC=0.61, P=.04) and severe anxiety (AUC=0.75, P<.001) among those who have exhibited WSC.SC-LIWC is useful to examine language markers of suicide risk and emotional distress in Chinese social media and can identify characteristics different from previous findings in the English literature. Some findings are leading to new hypotheses for future verification. Machine classifiers based on SC-LIWC features are promising but still require further optimization for application in real life.
| S-EPMC5525005 | biostudies-other
Project description:Facing the COVID-19 pandemic, Taiwan demonstrated resilience at the initial stage of epidemic prevention, and effectively slowed down its spread. This study aims to document public epidemic awareness of COVID-19 in Taiwan through collecting social media- and Internet-based data, and provide valuable experience of Taiwan's response to COVID-19, involving citizens, news media, and the government, to aid the public in overcoming COVID-19, or infectious diseases that may emerge in the future. The volume of Google searches related to COVID-19 and face masks was regarded as an indicator of public epidemic awareness in the study. A time-series analysis was used to explore the relationships among public epidemic awareness and other COVID-19 relevant variables, which were collected based on big data analysis. Additionally, the content analysis was adopted to analyze the transmission of different types of fear information related to COVID-19 and their effects on the public. Our results indicate that public epidemic awareness was significantly correlated with the number of confirmed cases in Taiwan and the number of news reports on COVID-19 (correlation coefficient: .33-.56). Additionally, the findings from the content analysis suggested that the fear of the loss of control best explains why panic behavior occurs among the public. When confronting the highly infectious COVID-19, public epidemic awareness is vital. While fear is an inevitable result when an emerging infectious disease occurs, the government can convert resistance into assistance by understanding why fear arises and which fear factors cause excessive public panic. Moreover, in the digitalization era, online and social media activities could reflect public epidemic awareness that can e harnessed for epidemic control.
| S-EPMC8136722 | biostudies-literature
Project description:BackgroundAlthough a number of studies have investigated how consumers use social media for health-related purposes, there is a paucity of studies in the Australian context.ObjectiveThis study aimed to explore how Australian consumers used social media for health-related purposes, specifically how they identified social media platforms, which were used, and which health-related activities commonly took place.MethodsA total of 5 focus groups (n=36 participants), each lasting 60 to 90 minutes, were conducted in the Sydney metropolitan area. The group discussions were audiorecorded and transcribed verbatim. The transcripts were coded line-by-line and thematically analyzed.ResultsParticipants used general search engines to locate health-related social media platforms. They accessed a wide range of social media on a daily basis, using several electronic devices (in particular, mobile phones). Although privacy was a concern, it did not prevent consumers from fully engaging in social media for health-related purposes. Blogs were used to learn from other people's experiences with the same condition. Facebook allowed consumers to follow health-related pages and to participate in disease-specific group discussions. Wikipedia was used for factual information about diseases and treatments. YouTube was accessed to learn about medical procedures such as surgery. No participant reported editing or contributing to Wikipedia or posting YouTube videos related to health topics. Twitter was rarely used for health-related purposes. Social media allowed consumers to obtain and provide disease and treatment-related information and social and emotional support for those living with the same condition. Most considered their participation as observational, but some also contributed (eg, responded to people's questions).ConclusionsParticipants used a wide range of social media for health-related purposes. Medical information exchange (eg, disease and treatment) and social and emotional support were the cornerstones of their online activities. Social media appears to be used as a key tool to support disease self-management.
| S-EPMC5660293 | biostudies-literature
Project description:BackgroundSocial media may be a powerful platform to combat parents' and children's low physical activity levels.ObjectiveThis study surveyed parents' beliefs about physical activity in order to expand the extant literature concerning the interest in and the design of an effective and feasible social media physical activity (SMPA) program.MethodsPrimary caregivers (n=250; 215 [86%] mothers, 164 [65.6%] White) of children aged 6-12 years completed an online questionnaire. Interest was examined through responses on the questionnaire; beliefs (ie, perceptions, knowledge, and support) about physical activity were examined using Spearman correlations; and to support the SMPA program design, researchers examined a combination of multiple-choice and free-response questions. For the free-response questions, the researchers performed open coding related to perceived benefits, barriers, and motivators.ResultsParent respondents (n=215, 86%) were interested in a SMPA program tailored for families. Regarding beliefs, parents exhibited a monotonic relationship between 2 questions related to perceptions of physical activity levels in their children (rs(250)=.310, P<.001), knowledge about physical activity and motor skills (rs(250)=.328, P<.001), and support of physical activity and motor skills (rs(250)=.385, P<.001). Parents perceived benefits of a SMPA program, highlighting family time and health. Barriers included time constraints, a lack of motivation, and environmental factors.ConclusionsParents are interested in supporting healthy family behaviors using a SMPA program. An effective program should emphasize motor skill activities, be fun and family oriented, and incorporate incentives, goal setting, and advice and tips. SMPA also needs to address identified barriers, such as those regarding time and environment.
| S-EPMC8887632 | biostudies-literature
Project description:BackgroundEffective suicide risk assessments and interventions are vital for suicide prevention. Although assessing such risks is best done by health care professionals, people experiencing suicidal ideation may not seek help. Hence, machine learning (ML) and computational linguistics can provide analytical tools for understanding and analyzing risks. This, therefore, facilitates suicide intervention and prevention.ObjectiveThis study aims to explore, using statistical analyses and ML, whether computerized language analysis could be applied to assess and better understand a person's suicide risk on social media.MethodsWe used the University of Maryland Suicidality Dataset comprising text posts written by users (N=866) of mental health-related forums on Reddit. Each user was classified with a suicide risk rating (no, low, moderate, or severe) by either medical experts or crowdsourced annotators, denoting their estimated likelihood of dying by suicide. In language analysis, the Linguistic Inquiry and Word Count lexicon assessed sentiment, thinking styles, and part of speech, whereas readability was explored using the TextStat library. The Mann-Whitney U test identified differences between at-risk (low, moderate, and severe risk) and no-risk users. Meanwhile, the Kruskal-Wallis test and Spearman correlation coefficient were used for granular analysis between risk levels and to identify redundancy, respectively. In the ML experiments, gradient boost, random forest, and support vector machine models were trained using 10-fold cross validation. The area under the receiver operator curve and F1-score were the primary measures. Finally, permutation importance uncovered the features that contributed the most to each model's decision-making.ResultsStatistically significant differences (P<.05) were identified between the at-risk (671/866, 77.5%) and no-risk groups (195/866, 22.5%). This was true for both the crowd- and expert-annotated samples. Overall, at-risk users had higher median values for most variables (authenticity, first-person pronouns, and negation), with a notable exception of clout, which indicated that at-risk users were less likely to engage in social posturing. A high positive correlation (ρ>0.84) was present between the part of speech variables, which implied redundancy and demonstrated the utility of aggregate features. All ML models performed similarly in their area under the curve (0.66-0.68); however, the random forest and gradient boost models were noticeably better in their F1-score (0.65 and 0.62) than the support vector machine (0.52). The features that contributed the most to the ML models were authenticity, clout, and negative emotions.ConclusionsIn summary, our statistical analyses found linguistic features associated with suicide risk, such as social posturing (eg, authenticity and clout), first-person singular pronouns, and negation. This increased our understanding of the behavioral and thought patterns of social media users and provided insights into the mechanisms behind ML models. We also demonstrated the applicative potential of ML in assisting health care professionals to assess and manage individuals experiencing suicide risk.
| S-EPMC9472054 | biostudies-literature
Project description:BackgroundVaccine hesitancy continues to limit global efforts in combatting the COVID-19 pandemic. Emerging research demonstrates the role of social media in disseminating information and potentially influencing people's attitudes towards public health campaigns. This systematic review sought to synthesize the current evidence regarding the potential role of social media in shaping COVID-19 vaccination attitudes, and to explore its potential for shaping public health interventions to address the issue of vaccine hesitancy.MethodsWe performed a systematic review of the studies published from inception to 13 of March2022 by searching PubMed, Web of Science, Embase, PsychNET, Scopus, CINAHL, and MEDLINE. Studies that reported outcomes related to coronavirus disease 2019 (COVID-19) vaccine (attitudes, opinion, etc.) gathered from the social media platforms, and those analyzing the relationship between social media use and COVID-19 hesitancy/acceptance were included. Studies that reported no outcome of interest or analyzed data from sources other than social media (websites, newspapers, etc.) will be excluded. The Newcastle Ottawa Scale (NOS) was used to assess the quality of all cross-sectional studies included in this review. This study is registered with PROSPERO (CRD42021283219).FindingsOf the 2539 records identified, a total of 156 articles fully met the inclusion criteria. Overall, the quality of the cross-sectional studies was moderate - 2 studies received 10 stars, 5 studies received 9 stars, 9 studies were evaluated with 8, 12 studies with 7,16 studies with 6, 11 studies with 5, and 6 studies with 4 stars. The included studies were categorized into four categories. Cross-sectional studies reporting the association between reliance on social media and vaccine intentions mainly observed a negative relationship. Studies that performed thematic analyses of extracted social media data, mainly observed a domination of vaccine hesitant topics. Studies that explored the degree of polarization of specific social media contents related to COVID-19 vaccines observed a similar degree of content for both positive and negative tone posted on different social media platforms. Finally, studies that explored the fluctuations of vaccination attitudes/opinions gathered from social media identified specific events as significant cofactors that affect and shape vaccination intentions of individuals.InterpretationThis thorough examination of the various roles social media can play in disseminating information to the public, as well as how individuals behave on social media in the context of public health events, articulates the potential of social media as a platform of public health intervention to address vaccine hesitancy.FundingNone.
| S-EPMC9120591 | biostudies-literature
Project description:Suicidal behavior (SB) has a complex etiology of genes, environment or both. One of the genetic components in SB could be copy number variations (CNVs), since CNVs are implicated in a range of neurodevelopmental disorders. However, a recently published genome-wide and case-control study failed to observe a significant role of CNVs in SB (see E-MTAB-3519). Here we complement those initial observations by conducting a brief CNV-association study, for the first time in a family-based trio-sample with severe suicide attempt (SA) outcome in offspring (n=660 trios; the \GISS\ sample, see http://www.ncbi.nlm.nih.gov/pubmed/23422793 and refs therein). For association testing, we here used the FBAT-CNV methodology (http://www.ncbi.nlm.nih.gov/pubmed/18228561), which allows for CNV association testing directly on the raw intensity values (Illumina \log R ratio\), evaluating any type of CNVs (e.g. de novo or inherited) without reliance on CNV calling algorithms and robust to control selection biases. Here we have deposited these raw logR-values for 88,450 on-chip CNV-loci of the HumanOmni1-Quad_v1 chip, arranged in a standard pedigree format used as input for FBAT-CNV analysis in SVS software (goldenhelix.com): column 1 is the family ID, column 2 is the Subject type (1 = offspring, 2 = mother, 3 = father), column 3 is the father ID (? for missing), column 4 is the mother ID (? for missing), column 5 is the sex (1 = female, 0 = male), column 6 is the affection status (1 = suicide attempt, 0 = not affected) and columns 7 and onward are the logR-values for each CNV-loci as is listed in the header row. We observed experiment-wide significant association (P ≤ 5.6 x 10-7) of two proximal CNVs at chromosome 14 (Illumina markers cnvi0108946 and cnvi0118308, with NCBI 36.3 start positions 22794779 and 22582820). However, these CNV-associations mapped to T-cell receptor regions, and therefore most likely reflect inter-individual variation in somatic rearrangements occurring in white blood cells (as our source of DNA was blood), rather than association with SA. In conclusion, our results did not suggest any major role of CNVs in SA etiology, in line with the results of the recent case-control study (see E-MTAB-3519).
2015-10-30 | E-MTAB-3744 | biostudies-arrayexpress