TY - JOUR
T1 - Mining voices from self-expressed messages on social-media
T2 - Diagnostics of mental distress during COVID-19
AU - Kumar, Rahul
AU - Mukherjee, Shubhadeep
AU - Choi, Tsan Ming
AU - Dhamotharan, Lalitha
PY - 2022/11
Y1 - 2022/11
N2 - The COVID-19 pandemic has had a severe impact on mankind, causing physical suffering and deaths across the globe. Even those who have not contracted the virus have experienced its far-reaching impacts, particularly on their mental health. The increased incidences of psychological problems, anxiety associated with the infection, social restrictions, economic downturn, etc., are likely to aggravate with the virus spread and leave a longer impact on humankind. These reasons in aggregation have raised concerns on mental health and created a need to identify novel precursors of depression and suicidal tendencies during COVID-19. Identifying factors affecting mental health and causing suicidal ideation is of paramount importance for timely intervention and suicide prevention. This study, thus, bridges this gap by utilizing computational intelligence and Natural Language Processing (NLP) to unveil the factors underlying mental health issues. We observed that the pandemic and subsequent lockdown anxiety emerged as significant factors leading to poor mental health outcomes after the onset of COVID-19. Consistent with previous works, we found that psychological disorders have remained pre-eminent. Interestingly, financial burden was found to cause suicidal ideation before the pandemic, while it led to higher odds of depressive (non-suicidal) thoughts for individuals who lost their jobs. This study offers significant implications for health policy makers, governments, psychiatric practitioners, and psychologists.
AB - The COVID-19 pandemic has had a severe impact on mankind, causing physical suffering and deaths across the globe. Even those who have not contracted the virus have experienced its far-reaching impacts, particularly on their mental health. The increased incidences of psychological problems, anxiety associated with the infection, social restrictions, economic downturn, etc., are likely to aggravate with the virus spread and leave a longer impact on humankind. These reasons in aggregation have raised concerns on mental health and created a need to identify novel precursors of depression and suicidal tendencies during COVID-19. Identifying factors affecting mental health and causing suicidal ideation is of paramount importance for timely intervention and suicide prevention. This study, thus, bridges this gap by utilizing computational intelligence and Natural Language Processing (NLP) to unveil the factors underlying mental health issues. We observed that the pandemic and subsequent lockdown anxiety emerged as significant factors leading to poor mental health outcomes after the onset of COVID-19. Consistent with previous works, we found that psychological disorders have remained pre-eminent. Interestingly, financial burden was found to cause suicidal ideation before the pandemic, while it led to higher odds of depressive (non-suicidal) thoughts for individuals who lost their jobs. This study offers significant implications for health policy makers, governments, psychiatric practitioners, and psychologists.
KW - COVID-19
KW - Depression
KW - Mental health
KW - Natural language processing
KW - Pandemic
KW - Social-media
KW - Suicidal ideation
UR - http://www.scopus.com/inward/record.url?scp=85131808914&partnerID=8YFLogxK
UR - https://www.sciencedirect.com/science/article/pii/S016792362200063X?via%3Dihub
U2 - 10.1016/j.dss.2022.113792
DO - 10.1016/j.dss.2022.113792
M3 - Article
AN - SCOPUS:85131808914
SN - 0167-9236
VL - 162
JO - Decision Support Systems
JF - Decision Support Systems
M1 - 113792
ER -