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. 2023 Sep 15;23(1):1801.
doi: 10.1186/s12889-023-16699-0.

The impact of COVID-19 prevention and control policy adjustment on anxiety, depression and coping behavior in China: a cross-sectional online survey, 21-28 December, 2022

Affiliations

The impact of COVID-19 prevention and control policy adjustment on anxiety, depression and coping behavior in China: a cross-sectional online survey, 21-28 December, 2022

Mingyu Gu et al. BMC Public Health. .

Abstract

Background: Following external situation reports, individuals perceive risks, experience different emotional reactions, and further change their behaviors. Therefor people's psychology will also be affected by adjustment of COVID-19 epidemic prevention and control policy, but it remains unknown what kind of coping behaviors will be produced due to psychology. This study defines coping behavior as "medical behavior and irrational consumption behavior after the adjustment of COVID-19 epidemic prevention and control policy in China", assesses the prevalence of negative emotions in the Chinese population after policy adjustments, and explores how negative emotions affect people's coping behaviors, conducts baseline research, provides references and suggestions for policy formulation.

Methods: A cross-sectional online survey was conducted during 21-28 December 2022, included sociodemographic characteristics, COVID-19 infection and irrational purchase behavior, psychological assessment, and opinion polling. Depression and anxiety status are assessed by PHQ-9 and GAD-7. The relationship between anxiety, depression and coping behavior was analyzed by Pearson χ2 test, Fisher's exact test and logistic regression.

Results: A total of 3995 infected participants were included in this study, of which 2363(59.1%) and 1194(29.9%) had depression and anxiety. There was a significant difference in clinical treatment and irrational purchase behavior between different level of depression and anxiety. Depression was a risk factor for self- medication (OR = 1.254), seeking professional treatment (OR = 1.215), using online services of medical institutions (OR = 1.320), large-scale purchases of medicines (OR = 1.154) and masks (OR = 1.096). Anxiety was a risk factor for seeking professional treatment (OR = 1.285) and large-scale purchases of masks (OR = 1.168).

Conclusion: After the adjustment of COVID-19 epidemic prevention and control policy, patient risk perception can increase depression and anxiety. We found that associated with depression, COVID-19 patients are more likely to have medical behaviors such as self- medication, seeking professional treatment, using online services of medical institutions, and storage behaviors of medicines and masks; and anxiety associated with the coping behavior of patients to seek professional treatment and store masks in large quantities. We should improve people's mental health, and on the other hand, we should give people effective psychological education during the epidemic. Therefore, we should set up psychological outpatient clinics in community health institutions, expanding mental health screening and guidance; relying on the psychological outpatient clinic, establish groups of people with depression or anxiety to carry out COVID-19 health education and peer education, to reduce adverse drug reactions, avoid panic seeking professional treatment and irrational purchase behavior, and protect public mental health.

Trial registration: This study has been approved by the Medical Ethics Committee of Capital Medical University (2023SY086), and informed consent was obtained from the study subjects before the investigation.

Keywords: Anxiety; COVID-19; Coping behavior; Cross-sectional study; Depression; Policy adjustment.

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Conflict of interest statement

The authors declare no competing interests

Figures

Fig. 1
Fig. 1
Structure of the individual-based model with influences from the external situation and individual-based social networks
Fig. 2
Fig. 2
Flowchart of the study design
Fig. 3
Fig. 3
Questionnaire design and structure. The red part is the survey items included in this study; (n) represents the number of survey items
Fig. 4
Fig. 4
Participants’ self-medication (A), clinical treatment (B), and irrational purchase behavior (C)
Fig. 5
Fig. 5
Logistic regression of medical treatment: A shows logistic regression of self-medication. B shows logistic regression of medical institution visits. C shows logistic regression of online medical services
Fig. 6
Fig. 6
Logistic regression of irrational purchase behavior: A shows logistic regression of buying medicines in large quantities. B shows logistic regression of buying masks in large quantities

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