Skip to main content
Elsevier - PMC COVID-19 Collection logoLink to Elsevier - PMC COVID-19 Collection
letter
. 2020 Apr 18;87:56–58. doi: 10.1016/j.bbi.2020.04.045

The immediate mental health impacts of the COVID-19 pandemic among people with or without quarantine managements

Shen Zhu a, Yue Wu a, Chun-yan Zhu d, Wan-chu Hong a, Zhi-xi Yu a, Zhi-ke Chen a, Zhen-lei Chen a, De-guo Jiang b,⁎⁎, Yong-guang Wang c,e,
PMCID: PMC7165285  PMID: 32315758

Highlights

  • High prevalence of mental health problems was found in people.

  • Quarantine was not related with the prevalence of mental health problems.

  • Impacts on daily life predicted mental health problems significantly.


In China, the Corona Virus Disease 2019 (COVID-19) was first identified in the city of Wuhan and had spread rapidly across the whole country. To control COVID-19 pandemic, Chinese government had implemented a range of strict quarantine managements for different population. Patients with COVID-19 were isolated in hospital, whereas close-contacts and the frontline medical personnel were quarantined in hotel. Notably, all the residents were under home-quarantine during the peak of pandemic, except those who guaranteed the basic functions of a city. These critical control measures substantially mitigated the spread of COVID-19, with conceivable impacts on people’s daily life. We, here, use a mental health survey data to test that whether the mental health problems were related to quarantine or not.

Data was gathered with a mobile app called “Sojump” (www.sojump.com) after obtaining informed consent (from Feb. 12, 2020 to Mar. 17, 2020). In total, 1443 participants with quarantine (i.e., 206 close-contacts and 320 frontline medical personnel under hotel-quarantine, and 917 public residents under home-quarantine) and 836 participants without quarantine were recruited (i.e., 538 non-frontline medical personnel and 298 community support workers). The survey was completed after more than 10 days in quarantine and the same month for the participants with and without quarantine, respectively. The current work was approved by the ethics committees of the Fifth Hospital of Ruian. The 20-item Self-Report Questionnaire (SRQ-20), 7-item Generalized Anxiety Disorder Scale (GAD-7), and 9-item Patient Health Questionnaire (PHQ-9), were administered to screen the general psychological symptoms (i.e., ≥7 in SRQ-20), anxiety (i.e., ≥5 in GAD-7) and depression (i.e., ≥5 in PHQ-9), respectively. The Cronbach’s alpha for SRQ-20, GAD-7, and PHQ-9 was 0.884, 0.935, and 0.913, separately. In addition, participants were required to rate their subjective perception of impacts on daily life due to COVID-19 pandemic (0 – not at all; 1 – affected a little; 2 – affected a lot; and 3 – extremely affected).

No significant difference was found for the screening-positive rate of SRQ-20, GAD-7, and PHQ-9 between participants with and without quarantine (all p ≥ 0.303). Logistic regression revealed that the screening-positive rate of SRQ-20 (OR = 3.593, 95% CI = 3.020–4.276), GAD-7 (OR = 4.686, 95% CI = 3.937–5.579), and PHQ-9 (OR = 4.313, 95% CI = 3.640–5.111) were significantly associated with impacts on daily life (all p < 0.001), but not the variable of with/without quarantine (all p ≥ 0.303) or different-group (all p ≥ 0.614). The characteristics for each group and the statistical results were shown in Table 1 .

Table 1.

The characteristics for each group and the statistical results.

Participants with quarantine
Participants without quarantine
Statistics
Overall CC FMP PR Overall CSW nFMP With vs. without quarantine Among groups Multiple comparisons
(Hotel-quarantine)
(Home-quarantine)
(n = 1443) (n = 206) (n = 320) (n = 917) (n = 836) (n = 298) (n = 538)
Gender χ2 = 0.059, p = 0.808 χ2 = 114.821, p < 0.001 nFMP > FMP/PR/CC > CSW, all p < 0.05
 The ratio of female 859 (59.5%) 105 (51.0%) 204 (63.7%) 550 (60.0%) 502 (60.0%) 109 (36.6%) 393 (73.0%)



Age-bracket χ2 = 1.268, p = 0.260 χ2 = 0.340, p = 0.560 /
≤30 years  old 330 (22.9%) 49 (23.8%) 85 (26.6%) 196 (21.4%) 181 (21.7%) 30 (10.1%) 151 (28.1%)
 31–40 years old 629 (43.6%) 85 (41.3%) 150 (46.9%) 394 (43.0%) 346 (41.4%) 122 (40.9%) 224 (41.6%)
 41–50 years old 354 (24.5%) 61 (29.6%) 83 (25.9%) 210 (22.9%) 236(28.2%) 97 (32.6%) 139 (25.8%)
 ≥51 years old 130 (9.0%) 11 (5.3%) 2 (0.6%) 117 (12.8%) 73(8.7%) 49 (16.4%) 24 (4.5%)



Educational level without > with χ2 = 223.825, p < 0.001 χ2 = 319.992, p < 0.001 FMP/nFMP > CSW > PR > CC, all p < 0.05
 Primary school level 68 (4.7%) 40 (19.4%) 0 (0%) 28 (3.1%) 5 (0.6%) 5 (1.7%) 0 (0%)
 Second school level 487 (33.8%) 135 (65.5%) 7 (2.2%) 345 (37.6%) 65 (7.8%) 56 (18.8%) 9 (1.7%)
 High school level 888 (61.5%) 31 (15.1%) 313 (97.8%) 544 (59.3%) 766 (91.6%) 237 (79.5%) 529 (98.3%)



Impacts on daily life χ2 = 1.402, p = 0.236 χ2 = 2.208, p = 0.137 /
 Not at all 379 (26.3%) 63 (30.6%) 94 (29.4%) 222 (24.2%) 235 (28.1%) 80 (26.8%) 155 (28.8%)
 Affected a little 818 (56.7%) 94 (45.6%) 178 (55.6%) 546 (59.5%) 471 (56.4%) 149 (50.0%) 322 (59.9%)
 Affected a lot 203 (14.0%) 44 (21.4%) 42 (13.1%) 117 (12.8%) 108 (12.9%) 55 (18.5%) 53 (9.9%)
 Extremely affected 43 (3.0%) 5 (2.4%) 6 (1.9%) 32 (3.5%) 22 (2.6%) 14 (4.7%) 8 (1.5%)



Rate of screening-positive
 SRQ-20 216 (15.0%) 14 (6.8%) 41 (12.8%) 161 (17.6%) 112 (13.4%) 58 (19.5%) 54 (10.0%) χ2 = 1.061, p = 0.303 χ2 = 32.252, p < 0.001 PR/CSW > CC/nFMP, all p < 0.05
 GAD-7 320 (22.2%) 38 (18.4%) 63 (19.7%) 219 (23.9%) 174 (20.8%) 82 (27.5%) 92 (17.1%) χ2 = 0.579, p = 0.447 χ2 = 17.262, p = 0.002 all p greater than 0.05
 PHQ-9 319 (22.1%) 26 (12.6%) 68 (21.3%) 225 (24.5%) 174 (20.8%) 77 (25.8%) 97 (18.0%) χ2 = 0.522, p = 0.470 χ2 = 21.686, p < 0.001 PR/CSW > CC, PR > nFMP, all p < 0.05

Notes for Table 1: CC, group of close-contacts; FMP, group of frontline medical personnel; PR, group of public residents; CSW, group of community support workers; nFMP, group of non-frontline medical personnel; Pearson chi-square test for ratio; linear-by-linear association test for distribution; Bonferroni correction for multiple comparisons.

Consistent with other reports (e.g., Li et al., 2020, Wang et al., 2020, Zhang et al., 2020), our results show a relative high prevalence of mental health problems in our sample. However, these mental health problems were not related with the control measure of quarantine, but the impacts on daily life. This finding is unusual but not unique (e.g., Wang et al., 2011, Li et al., 2020). During the H1N1 epidemic, we also found no immediate negative psychological effect of quarantine in college students (Wang et al., 2011). Instead, the dissatisfaction with control measures significantly predicted their negative psychological consequences. We endorse that, if quarantine is essential, the officials should take measures to ensure that this experience is acceptable and tolerable. Further studies should pay more attention to identify the potential psychological risk factors associated with the mental health problems under quarantine.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This work was supported by the Science and Technology Bureau of Ruian (Grant no. MS2020024).

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbi.2020.04.045.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Supplementary data 1
mmc1.xml (199B, xml)

References

  1. Li Z., Ge M., Yang M., Feng J., Qiao M., Jiang R., Bi J., Zhan G., Xu X., Wang L., Zhou Q., Zhou C., Pan Y., Liu S., Zhang H., Yang J., Zhu B., Hu Y., Hashimoto K., Jia Y., Wang H., Wang R., Liu C., Yang C. Vicarious traumatization in the general public, members, and non-members of medical teams aiding in COVID-19 control. Brain Behav. Immun. 2020 doi: 10.1016/j.bbi.2020.03.007. (In press) [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Wang C., Pan R., Wan X., Tan Y., Xu L., Mclntyre R.S., Choo F.N., Tran B., Ho R., Sharma V.K., Ho C. A longitudinal study on the mental health of general population during the COVID-19 epidemic in China. Brain Behav. Immun. 2020 doi: 10.1016/j.bbi.2020.04.028. (In press) [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Wang Y., Xu B., Zhao G., Cao R., He X., Fu S. Is quarantine related to immediate negative psychological consequences during the 2009 H1N1 epidemic? Gen. Hosp. Psychiatry. 2011;33:75–77. doi: 10.1016/j.genhosppsych.2010.11.001. [DOI] [PubMed] [Google Scholar]
  4. Zhang J., Lu H., Zeng H., Zhang S., Du Q., Jiang T., Du B. The differential psychological distress of populations affected by the COVID-19 pandemic. Brain Behav. Immun. 2020 doi: 10.1016/j.bbi.2020.04.031. (In press) [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary data 1
mmc1.xml (199B, xml)

Articles from Brain, Behavior, and Immunity are provided here courtesy of Elsevier

RESOURCES