Reddit Users’ Experiences of Suicidal Thoughts During the COVID-19 Pandemic: A Qualitative Analysis of r/Covid19_support Posts (Preprint)

2021 ◽  
Author(s):  
Allie Slemon ◽  
Corey McAuliffe ◽  
Trevor Goodyear ◽  
Liza McGuinness ◽  
Elizabeth Shaffer ◽  
...  
Keyword(s):  
Mental Health ◽  
Qualitative Research ◽  
Social Media ◽  
Coping Strategies ◽  
Health Resources ◽  
Population Level ◽  
Epidemiological Data ◽  
Qualitative Inquiry ◽  
Search Term ◽  
Suicidal Thoughts

BACKGROUND The COVID-19 pandemic is having considerable impacts on population-level mental health, with research illustrating an increased prevalence in suicidal thoughts due to pandemic stressors. While the drivers of suicidal thoughts amid the pandemic are poorly understood, qualitative research holds great potential for expanding upon projections from pre-pandemic work and contextualizing emerging epidemiological data. Despite calls for qualitative inquiry, there is a paucity of qualitative research examining experiences of suicidality related to COVID-19. The use of publicly available data from social media offers timely and pertinent information into ongoing pandemic-related mental health, including individual experiences of suicidal thoughts. OBJECTIVE The objective of this paper is to examine online posts that discuss suicidal thoughts within one Reddit community r/COVID19_support with the aim to identify contributing stressors and coping strategies related to the COVID-19 pandemic. METHODS This study draws on online posts from within the Reddit community r/COVID19_support that describe users’ suicidal thoughts during and related to the COVID-19 pandemic. Data were collected from creation of this subreddit on February 12, 2020 until December 31, 2020. Using the search term “suicide”, we used the NCapture add-on tool, hosted by NVivo, to conduct our investigation. A qualitative thematic analysis, as described by Braun and Clarke, was conducted to generate themes reflecting users’ experiences of suicidal thoughts. RESULTS A total of 83 posts from 57 users were included in the analysis. Reddit posts described a range of users’ lived experiences of suicidal thoughts related to the pandemic, including deterioration in mental health, complex emotions associated with suicidal thinking, and concern that suicidal thoughts may progress to action. Seven prominent and compounding stressors were identified as contributing to Reddit users’ suicidal thoughts, including social isolation, employment and finances, virus exposure and COVID-19 illness, uncertain timeline of the pandemic, news and social media, pre-existing mental health conditions, and lack of access to mental health resources. Some users described individual coping strategies used in attempt to manage suicidal thoughts, however these were recognized as insufficient for addressing the multilevel stressors of the pandemic. CONCLUSIONS Multiple and intersecting stressors have contributed to individuals’ experiences of suicidal thoughts in the context of the COVID-19 pandemic, requiring thoughtful and complex public health and policy responses. While ongoing challenges exist with self-disclosure of mental health challenges on social media, Reddit and other online platforms may a supportive space for users to share suicidal thoughts and discuss potential coping strategies.

scholarly journals Reddit Users' Experiences of Suicidal Thoughts During the COVID-19 Pandemic: A Qualitative Analysis of r/Covid19_support Posts

2021 ◽  
Vol 9 ◽  
Author(s):  
Allie Slemon ◽  
Corey McAuliffe ◽  
Trevor Goodyear ◽  
Liza McGuinness ◽  
Elizabeth Shaffer ◽  
...  
Keyword(s):  
Mental Health ◽  
Qualitative Research ◽  
Social Media ◽  
Coping Strategies ◽  
Health Resources ◽  
Population Level ◽  
Epidemiological Data ◽  
Qualitative Inquiry ◽  
Suicidal Thoughts ◽  
Self Disclosure

Background: The COVID-19 pandemic is having considerable impacts on population-level mental health, with research illustrating an increased prevalence in suicidal thoughts due to pandemic stressors. While the drivers of suicidal thoughts amid the pandemic are poorly understood, qualitative research holds great potential for expanding upon projections from pre-pandemic work and nuancing emerging epidemiological data. Despite calls for qualitative inquiry, there is a paucity of qualitative research examining experiences of suicidality related to COVID-19. The use of publicly available data from social media offers timely and pertinent information into ongoing pandemic-related mental health, including individual experiences of suicidal thoughts.Objective: To examine how Reddit users within the r/COVID19_support community describe their experiences of suicidal thoughts amid the COVID-19 pandemic.Methods: This study draws on online posts from within r/COVID19_support that describe users' suicidal thoughts during and related to the COVID-19 pandemic. Data were collected from creation of this subreddit on February 12, 2020 until December 31, 2020. A qualitative thematic analysis was conducted to generate themes reflecting users' experiences of suicidal thoughts.Results: A total of 83 posts from 57 users were included in the analysis. Posts described a range of users' lived and living experiences of suicidal thoughts related to the pandemic, including deterioration in mental health and complex emotions associated with suicidal thinking. Reddit users situated their experiences of suicidal thoughts within various pandemic stressors: social isolation, employment and finances, virus exposure and COVID-19 illness, uncertain timeline of the pandemic, news and social media, pre-existing mental health conditions, and lack of access to mental health resources. Some users described individual coping strategies and supports used in attempt to manage suicidal thoughts, however these were recognized as insufficient for addressing the multilevel stressors of the pandemic.Conclusions: Multiple and intersecting stressors have contributed to individuals' experiences of suicidal thoughts amid the COVID-19 pandemic, requiring thoughtful and complex public health responses. While ongoing challenges exist with self-disclosure of mental health challenges on social media, Reddit and other online platforms may offer a space for users to share suicidal thoughts and discuss potential coping strategies.

scholarly journals Recruitment of Participants and Delivery of Online Mental Health Resources for Depressed Individuals Using Tumblr: Pilot Randomized Control Trial (Preprint)

2017 ◽  
Author(s):  
Erin Kelleher ◽  
Megan Moreno ◽  
Megan Pumper Wilt
Keyword(s):  
Mental Health ◽  
At Risk ◽  
Social Media ◽  
Young People ◽  
Intervention Group ◽  
Health Resources ◽  
Depression Symptoms ◽  
Depression Symptom ◽  
Search Term ◽  
Risk For Depression

BACKGROUND Adolescents and young adults frequently post depression symptom references on social media; previous studies show positive associations between depression posts and self-reported depression symptoms. Depression is common among young people and this population often experiences many barriers to mental health care. Thus, social media may be a new resource to identify, recruit, and intervene with young people at risk for depression. OBJECTIVE The purpose of this pilot study was to test a social media intervention on Tumblr. We used social media to identify and recruit participants and to deliver the intervention of online depression resources. METHODS This randomized pilot intervention identified Tumblr users age 15-23 who posted about depression using the search term “#depress”. Eligible participants were recruited via Tumblr messages; consented participants completed depression surveys and were then randomized to an intervention of online mental health resources delivered via a Tumblr message, while control participants did not receive resources. Postintervention online surveys assessed resource access and usefulness and control groups were asked whether they would have liked to receive resources. Analyses included t tests. RESULTS A total of 25 participants met eligibility criteria. The mean age of the participants was 17.5 (SD 1.9) and 65% were female with average score on the Patient Health Questionnaire-9 of 17.5 (SD 5.9). Among the 11 intervention participants, 36% (4/11) reported accessing intervention resources and 64% (7/11) felt the intervention was acceptable. Among the 14 control participants, only 29% (4/14) of reported that receiving resources online would be acceptable (P=.02). Participants suggested anonymity and ease of use as important characteristics in an online depression resource. CONCLUSIONS The intervention was appropriately targeted to young people at risk for depression, and recruitment via Tumblr was feasible. Most participants in the intervention group felt the social media approach was acceptable, and about a third utilized the online resources. Participants who had not experienced the intervention were less likely to find it acceptable. Future studies should explore this approach in larger samples. Social media may be an appropriate platform for online depression interventions for young people.

scholarly journals Mining Social Media Data for Biomedical Signals and Health-Related Behavior

2020 ◽  
Vol 3 (1) ◽  
pp. 433-458 ◽  
Author(s):  
Rion Brattig Correia ◽  
Ian B. Wood ◽  
Johan Bollen ◽  
Luis M. Rocha
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Population Level ◽  
Data Access ◽  
Health Conditions ◽  
Social Phenomena ◽  
Medical Treatments ◽  
Social Media Data ◽  
Health Related ◽  
Media Data

Social media data have been increasingly used to study biomedical and health-related phenomena. From cohort-level discussions of a condition to population-level analyses of sentiment, social media have provided scientists with unprecedented amounts of data to study human behavior associated with a variety of health conditions and medical treatments. Here we review recent work in mining social media for biomedical, epidemiological, and social phenomena information relevant to the multilevel complexity of human health. We pay particular attention to topics where social media data analysis has shown the most progress, including pharmacovigilance and sentiment analysis, especially for mental health. We also discuss a variety of innovative uses of social media data for health-related applications as well as important limitations of social media data access and use.

scholarly journals Quantifying Suicidal Ideation on Social Media using Machine Learning: A Critical Review

2021 ◽  
pp. 4092-4100
Author(s):  
Syed Tanzeel Rabani ◽  
Qamar Rayees Khan ◽  
Akib Mohi Ud Din Khanday
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Social Media ◽  
Suicidal Ideation ◽  
Social Isolation ◽  
Suicide Prevention ◽  
Online Social Networks ◽  
Public Information ◽  
Machine Learning Techniques ◽  
Suicidal Thoughts

Suicidal ideation is one of the severe mental health issues and a serious social problem faced by our society. This problem has been usually dealt with through the psychological point of view, using clinical face to face settings. There are various risk factors associated with suicides, including social isolation, anxiety, depression, etc., that decrease the threshold for suicide. The COVID-19 pandemic further increases social isolation, posing a great threat to the human population. Posting suicidal thoughts on social media is gaining much attention due to the social stigma associated with the mental health. Online Social Networks (OSN) are increasingly used to express the suicidal thoughts. Recently, a top Indian actor industry took the harsh step of suicide. The last Instagram posts revealed signs of depression, which if anticipated could have saved the precious life. Recent research indicated that the public information on social media provides valuable insights on detecting the users with the suicidal ideation. The motive of this study is to provide a systematic review of the work done already in the use of social media for suicide prevention and propose a novel classification approach that classifies the suicide related tweets/ posts into three levels of distress. Moreover, our proposed classification task which was implemented through various machine learning techniques revealed high accuracy in classifying the suicidal posts. Among all algorithms, the best performing algorithm was that of the decision tree, with an F1 score ranging 0.95-0.97. After thoroughly studying the work achieved by different researchers in the area of suicide prevention, our study critically analyses those works and finds various research gaps and solves some of them. We believe that our work will motivate research community to look into other gaps that will in turn help psychiatrists, psychologists, and counsellors to protect individuals suffering from suicidal ideation.

Towards Approximating Population-Level Mental Health in Thailand Using Large-Scale Social Media Data

2021 ◽  
pp. 334-343
Author(s):  
Krittin Chatrinan ◽  
Anon Kangpanich ◽  
Tanawin Wichit ◽  
Thanapon Noraset ◽  
Suppawong Tuarob ◽  
...  
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Large Scale ◽  
Population Level ◽  
Social Media Data ◽  
Media Data

scholarly journals Humanizing Digital Mental Health through Social Media: Centering Experiences of Gang-Involved Youth Exposed to High Rates of Violence

2018 ◽  
Vol 10 ◽  
pp. 117822261879707 ◽  
Author(s):  
William R Frey
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Social Behavior ◽  
Young People ◽  
Community Violence ◽  
Health Resources ◽  
Community Violence Exposure ◽  
Ethical Challenges ◽  
Digital Interventions ◽  
Access To Health

As the lives of young people expand further into digital spaces, our understandings of their expressions and language on social media become more consequential for providing individualized and applicable mental health resources. This holds true for young people exposed to high rates of community violence who may also lack access to health resources offline. Social media may provide insights into the impacts of community violence exposure on mental health. However, much of what is shared on social media contains localized language and context, which poses challenges regarding interpretation. In this perspective, I offer insights gained from the Beyond the Bullets: The Complexities and Ethical Challenges of Interpreting Social Media Posts workshop during the Digital Interventions in Mental Health conference in London, England: (1) social media as an underutilized environmental context in mental health services; (2) interpreting the meaning of social media posts is challenging, and there are additional challenges when users are exposed to offline violence and (3) the importance of having various perspectives when interpreting social media posts to build contextually nuanced and theoretically based understandings of digital social behavior.

scholarly journals Mental Health and the SARS-COV-2 Epidemic—Polish Research Study

2020 ◽  
Vol 17 (19) ◽  
pp. 7015
Author(s):  
Monika Talarowska ◽  
Jan Chodkiewicz ◽  
Natalia Nawrocka ◽  
Joanna Miniszewska ◽  
Przemysław Biliński
Keyword(s):  
Mental Health ◽  
Coping Strategies ◽  
Mental State ◽  
Psychiatric Treatment ◽  
General Health Questionnaire ◽  
Well Being ◽  
Adaptive Coping ◽  
Mental Functioning ◽  
Suicidal Thoughts ◽  
Mental Well Being

Background: The aim of this study was to assess the mental state of Poles in the first weeks of the SARS-COV-2 epidemic. Methods: In the study, the General Health Questionnaire-28 (GHQ-18), The Perceived Stress Scale (PSS-10), and Mini-Cope were used. Results: The study was conducted on a group of 443 individuals, including 348 women (78.6%) and 95 men (21.4%). There were more women (χ2 = 6.42, p = 0.02) in the group of people with high results in the GHQ-28 questionnaire and the differentiating factors between those with sten scores above 7 (significantly deteriorated mental health) and those with average or low results (sten score below 7) turned out to be: treatment for mental disorders before the pandemic (χ2 = 19.57, p < 0.001) and the use of psychotherapy during the pandemic (χ2 = 4.21, p = 0.04) and psychiatric pharmacotherapy (χ2 = 8.31, p = 0.01). The presence of suicidal thoughts since the appearance of the pandemic-related restraints and limitations significantly differentiates the compared groups (χ2 = 38.48, p < 0.001). Conclusions: Every fourth person in the examined group (over 26% of the respondents) recorded results that indicate a high probability of mental functioning disorders. Approximately 10% of the respondents signalled the occurrence of suicidal thoughts since the beginning of the pandemic. The respondents complain mainly about problems in everyday life, lack of satisfaction from one’s own activities, tension, trouble sleeping, and feelings of exhaustion. Individuals with significantly reduced mental well-being use non-adaptive coping strategies, such as denying problems, emotional discharge, taking substances, discontinuation of action, and blaming themselves for the situation. The risk factors for the deterioration of the mental state of the respondents during the pandemic include psychiatric treatment before the beginning of the pandemic, the presence of suicidal thoughts during forced isolation, and the use of non-adaptive coping strategies (denial of the existence of problems, emotional discharge, use of psychoactive substances, discontinuation of action, and blaming oneself for the situation).

scholarly journals Forecasting population need for mental health care: a Bayesian methodology applied to the epidemiology of psychotic disorders in England

2020 ◽  
Author(s):  
Keltie McDonald ◽  
Tao Ding ◽  
Hannah Ker ◽  
Rebecca Dliwayo ◽  
David Osborn ◽  
...  
Keyword(s):  
Mental Health ◽  
Small Area ◽  
Psychotic Disorders ◽  
Population Level ◽  
Epidemiological Data ◽  
First Episode ◽  
Data Set ◽  
Psychosis Risk ◽  
Small Area Level ◽  
Early Intervention In Psychosis

Background: Mental health service policymakers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable. We developed and validated a population-level prediction model to forecast need for early intervention in psychosis [EIP] services in England up to 2025.Methods: We fitted six candidate Bayesian Poisson regression models, combining epidemiological data on psychosis risk, to predict new annual caseload of referrals, assessed, treated, and probable first episode psychosis [FEP] cases in EIP services, aged 16-64 years at small-area level. Models were validated against observed NHS Mental Health Services Data Set [MHSDS] data at Clinical Commissioning Group [CCG] and national levels for 2017. Projections were made up to 2025, based on small-area demographic forecasts. Outcome: In 2017, our best-fitting model predicted 8,112 (95% interval: 7,623 to 8,597) individuals with probable FEP in England, compared with 8,038 observed in the MHSDS (difference: n=+74; +0·92%), after accounting for psychosis risk by age, sex, ethnicity, small area-level deprivation, social fragmentation and regional cannabis use. In 2020, this model forecasted 9,066 new treated FEP cases (8,485 to 9,618), rising 1% annually up to 2025. For every ten treated cases, we forecasted that 23 and 21 people would be referred to and assessed by EIP services, respectively, for “suspected FEP”. Interpretation: Our methodology provides an accurate, validated toolkit to inform planners, commissioners and providers about future population need for psychosis care at different stages of the referral pathway, based on local determinants of need.Funding: Wellcome Trust, Royal Society, National Institute for Health Research

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