Literature DB >> 33326407

Time Trends of the Public's Attention Toward Suicide During the COVID-19 Pandemic: Retrospective, Longitudinal Time-Series Study.

Dayle Burnett1, Valsamma Eapen2,3, Ping-I Lin2,3.   

Abstract

BACKGROUND: The COVID-19 pandemic has overwhelmed health care systems around the world. Emerging evidence has suggested that substantially few patients seek help for suicidality at clinical settings during the COVID-19 pandemic, which has elicited concerns of an imminent mental health crisis as the course of the pandemic continues to unfold. Clarifying the relationship between the public's attention to knowledge about suicide and the public's attention to knowledge about the COVID-19 pandemic may provide insight into developing prevention strategies for a putative surge of suicide in relation to the impact of the COVID-19 pandemic.
OBJECTIVE: The goal of this retrospective, longitudinal time-series study is to understand the relationship between temporal trends of interest for the search term "suicide" and those of COVID-19-related terms, such as "social distancing," "school closure," and "lockdown."
METHODS: We used the Google Trends platform to collect data on daily interest levels for search terms related to suicide, several other mental health-related issues, and COVID-19 over the period between February 14, 2020 and May 13, 2020. A correlational analysis was performed to determine the association between the search term ''suicide'' and COVID-19-related search terms in 16 countries. The Mann-Kendall test was used to examine significant differences between interest levels for the search term "suicide" before and after school closure.
RESULTS: We found that interest levels for the search term "suicide" statistically significantly inversely correlated with interest levels for the search terms "COVID-19" or "coronavirus" in nearly all countries between February 14, 2020 and May 13, 2020. Additionally, search interest for the term ''suicide'' significantly and negatively correlated with that of many COVID-19-related search terms, and search interest varied between countries. The Mann-Kendall test was used to examine significant differences between search interest levels for the term "suicide" before and after school closure. The Netherlands (P=.19), New Zealand (P=.003), the United Kingdom (P=.006), and the United States (P=.049) showed significant negative trends in interest levels for suicide in the 2-week period preceding school closures. In contrast, interest levels for suicide had a significant positive trend in Canada (P<.001) and the United States (P=.002) after school closures.
CONCLUSIONS: The public's attention to suicide might inversely correlate with the public's attention to COVID-19-related issues. Additionally, several anticontagion policies, such as school closure, might have led to a turning point for mental health crises, because the attention to suicidality increased after restrictions were implemented. Our results suggest that an increased risk of suicidal ideation may ensue due to the ongoing anticontagion policies. Timely intervention strategies for suicides should therefore be an integral part of efforts to flatten the epidemic curve. ©Dayle Burnett, Valsamma Eapen, Ping-I Lin. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 30.12.2020.

Entities:  

Keywords:  COVID-19; Google Trends; attention; crisis; infodemiology; infoveillance; mental health; school closure; suicide; time series; time trend

Year:  2020        PMID: 33326407     DOI: 10.2196/24694

Source DB:  PubMed          Journal:  JMIR Public Health Surveill        ISSN: 2369-2960


  4 in total

1.  Mental Health Interest and Its Prediction during the COVID-19 Pandemic Using Google Trends.

Authors:  Magdalena Sycińska-Dziarnowska; Liliana Szyszka-Sommerfeld; Karolina Kłoda; Michele Simeone; Krzysztof Woźniak; Gianrico Spagnuolo
Journal:  Int J Environ Res Public Health       Date:  2021-11-24       Impact factor: 3.390

2.  Predicting the Number of Suicides in Japan Using Internet Search Queries: Vector Autoregression Time Series Model.

Authors:  Kazuya Taira; Rikuya Hosokawa; Tomoya Itatani; Sumio Fujita
Journal:  JMIR Public Health Surveill       Date:  2021-12-03

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

Authors:  Meijie Chu; Hongye Li; Shengnan Lin; Xinlan Cai; Xian Li; Shih-Han Chen; Xiaoke Zhang; Qingli Man; Chun-Yang Lee; Yi-Chen Chiang
Journal:  Front Public Health       Date:  2021-12-03

4.  Suicide Attempts Assisted By Firefighters According to Traumatic Brain Injury.

Authors:  Tiago Regis Franco de Almeida; Adriana Leandro de Araújo; Diógenes Munhoz; Pedro Gomes Andrade; Gabriela Arantes Wagner
Journal:  J Prev (2022)       Date:  2022-08-29
  4 in total

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