Analysis of Mental Health Status and Social Factors of Patients with COVID-19 Based on Big Data

DOI

10.2991/978-94-6463-064-0_50How to use a DOI?

Keywords

Mental health status; Social factors; Patients with COVID-19; Big Data

Abstract

Objective: To understand stress response, depression, anxiety and other mental health conditions of COVID-19 patients, social influencing factors and the correlation among them. Methods: A total of 172 patients with COVID-19 in isolation treatment were selected from 3 hospitals by SO JUMP and investigated with Stress Response Questionnaire (SRQ), Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS). Results: The patients with COVID-19 pressure response score was 50.31 ± 24.99, the SAS total score was 41.78 ± 8.90, and the SDS total score was 46.08 ± 8.36.FPR, SAS and SDS scores of “ ≥ 60” age group was higher than“ < 20”,“40 ~” (P < 0.05). FER, SAS and SDS score of patients with basic disease was higher than without basic disease patients (P < 0.05). Living in rural areas, low education, low income of COVID-19 patients, whose FER, FPR, SR, SAS and SDS scores were higher than other groups (P < 0.05).The scores of FER, FPR, FBR, SR, SAS and SDS of self-employed households were the highest among different occupations (P < 0.05).The days of isolation treatment ≤7 of COVID-19 patients, whose FER, FPR and SR scores were higher than >7 days (P < 0. 05). Total stress response score and various dimensions were positively correlated with anxiety and depression. Conclusions: In the face of COVID-19 epidemic, vulnerable groups such as self-employed people, the elderly, women, the sick, farmers, and people at the bottom of society have experienced varying degrees of psychological conditions. Early psychological intervention can effectively relieve stress response, anxiety and depression.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shu Tang
AU  - Le Chen
AU  - Xubo Dai
PY  - 2022
DA  - 2022/12/27
TI  - Analysis of Mental Health Status and Social Factors of Patients with COVID-19 Based on Big Data
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 488
EP  - 495
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_50
DO  - 10.2991/978-94-6463-064-0_50
ID  - Tang2022
ER  -