Mental health status among non-medical college students during the COVID-19 pandemic in Zhanjiang city

Abstract

Objectives: The coronavirus disease-2019 (COVID-19) pandemic has brought great changes to people's lifestyles. Previous reports implied that college students are more vulnerable to mental disorders. We aimed to evaluate the mental status of non-medical college students during the outbreak of COVID-19 in Zhanjiang city.

Methods: 1083 non-medical college students aged 18-25 years old were enrolled in this study. An online survey was applied to collect demographic data. Sleep quality, anxiety and depression symptoms were analyzed by pittsburgh sleep quality index (PSQI), hamilton depression rating scale-17 (HDRS-17) and self rating anxiety scale (SAS), respectively.

Results: There are 93.2% students had good sleep quality, 6.8% students had poor sleep quality. There are 97.4% students had no anxiety, 1.86%, 0.37% and 0.37% students had mild, moderate and severe anxiety, respectively. 66.9% students had no depression, 26.7%, 4.7% and 1.7% students had minimal, mild-moderate and severe depression. The sleep quality of students in different grades showed no statistical significance. Female students had higher proportions of anxiety (p=0.02) and depression (p>0.0001) than male students. No statistical difference was found in different educational levels regarding to anxiety and depression. The students whose household income that lower than 3000 RMB were more vulnerable to anxiety (p=0.017) and depression (p=0.004).

Conclusions: During the COVID-19 pandemic, a majority of students remain good sleep quality and positive mental health and a small number of students showed depression. Female students and lower household income were positively related to the prevalence of anxiety and depression. To our knowledge, this is the novel study revealing the mental health of non-medical college students concerning COVID-19 in Zhanjiang.

Introduction

2019 coronavirus disease (COVID-19) was first reported in Wuhan, China in December 2019. COVID-19 was an infectious disease which mainly transmitted through respiratory droplets and direct contact. As of June 04, 2022, a total of 45,048,617 person diagnosed with COVID-19 and 6319091 died of this deadly infectious disease. In Zhanjiang, Guangdong, a total of 109 positive cases were reported, including 85 confirmed cases and 24 asymptomatic cases. Recent studies have reported that there is increasing levels of stress or mental illness due to the COVID-19 pandemic.¹ The mental health of vulnerable populations, especially college students have aroused public’s concern. Anxiety, depression and insomnia has become the most common issues among college students. Therefore, to evaluate the mental health of college students is of great importance.

Several retrospective studies suggested that infection was closely related with subsequent mood deterioration, including depression.² It is reported that approximately 340 million people suffer from depression and this mental illness is a major cause of disability, and contributes a lot to health burden.^3,4 A systematic review and meta-analysis implied that the prevalence of anxiety, depression, and insomnia symptoms among healthcare workers during COVID-19 pandemic were 23.2%, 22.8%, and 38.9% respectively.⁵ A study has shown that infectious disease like HIV could increase depression level of patients tested by Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7) questionnaire.⁶ Income stability and high educational level were negatively related with anxiety and depression levels and poor sleep quality.⁷ However, the participants enrolled in the above studies mainly fucus on medical workers or patients, the mental health under the COVID-19 pandemic await to be assessed among non-medical students.

The aim of this study was to evaluate the mental health status among non-medical college students during the COVID-19 pandemic in Zhanjiang city and distinguish the students who might need psychological intervention.

Methods

Sample size calculation

The sample size was calculated using Power Analysis and Sample Size (PASS) 11.0, with reference to previous studies, the prevalence of anxiety in college students was 23.8%.⁸ The PASS operating parameters were as follows: “Proportions” --- "one proportion” --- "Confidence Intervals for one proportion”, 1-α = 0.95, Confidence interval width = 0.1, p = 0.238. Results showed that at least 297 people were required to meet statistical differences. Considering the 10% drop-out rate, we should at least enroll 327 students.

Study population and enrollment criteria

This cross-sectional study was launched by means of online survey (WeChat App) between April 1, 2022-june 1, 2022. The mental health status (insomnia, depression and anxiety) of non-medical students in Zhanjiang city was evaluated during the pandemic of COVID-19. The inclusion criteria are as follows: Age ≥18 years old and voluntarily participate in this study. Exclusion criteria are as follows: Students with no capacity or visual impairment or history of mental illness. The validity of the questionnaires for each participant was limited to one week as longer period might affect the psychological condition of the participants.

Insomnia, depression and anxiety evaluation

Insomnia was assessed by pittsburgh sleep quality index (PSQI). Depression and anxiety were evaluated by hamilton depression rating scale-17 (HDRS-17) and self rating anxiety scale (SAS), respectively. These scales were frequently applied and considered as valuable screening instruments among various population for insomnia, depression and anxiety.^9-11 In furtherance, the demographics information including age, gender, educational level, grade and household income were collected.

The sleep quality was identified by PSQI. There are 19 questions in this scale and higher score implied worse sleep quality. PSQI score were calculated and score > 5 and ≤ 5 were considered as poor and good sleep quality, respectively.⁹ The contents of HDRS-17 include depressed mood, feelings of guilt, suicide, agitation et, al. HDRS-17 score ＜8 indicates no depression,¹⁰ score 8-16 indicates minimal depression, score 17-24 indicates mild-moderate depression,¹² score ≥25 indicates severe depression.¹³ SAS was appplied to assess anxiety, with the definition of normal (≤ 49), mild (50-59), moderate (60-70) and severe anxiety (≥ 70) .¹¹

The informed consent of each study population was obtained and the answers to the specific demographic questions and insomnia, depression and anxiety scales were collected electronically. Study objectives was extensively explained at the beginning of the survey.

Statistical analysis

Statistical analysis was performed by using GraphPad Prism 7.0 and SPSS 22.0 (SPSS Inc., Chicago IL, USA). Kolmogorov–Smirnov test was used to examine the data normality. The chi-square test or Fisher's exact test was used to compare the sleep quality, anxiety and depression among different educational levels, grades, gender and household income. Differences with p < 0.05 were considered statistically significant.

Results

Prevalence Of Sleep Quality, Anxiety And Depression Among The Participants

As presented in Table 2, most participants had good sleep quality (n = 1010, 93.2%), and 73 people (6.8%) had poor sleep quality. The prevalence of anxiety among the participants was as follows: no anxiety (n = 1055, 97.4%), mild anxiety (n = 20, 1.86%), moderate anxiety (n = 4, 0.37%) and severe anxiety (n = 4, 0.37%). The proportions of no, minimal, mild-moderate and severe depression were 66.9%, 26.7%, 4.7% and 1.7%, respectively.

As shown in Fig. 1, there was no significant differences among different grades (freshman, sophomore, junior or above) regarding to sleep quality (Chi-square test, p = 0.054). There was 3 and 48 of 402 male students had anxiety (0.75%) and depression (2.8%), respectively, and there was 19 and 310 of 681 female students showed anxiety (11.9%) and depression (45.5%). Female students obviously represented more anxiety and depression emotion than male students (anxiety: Fisher’s exact test, p = 0.02, Fig. 2A; depression: Chi-square test, p < 0.0001, Fig. 2B). There was no statistically significant difference in sleep quality between genders (data not shown). The prevalence of anxiety of technical secondary school degree students showed no statistical difference compared with junior college or above degree students (Fisher’s exact test, p = 0.14, Fig. 3A). There were no statistical differences between educational levels in depression (Fisher’s exact test, p > 0.99, Fig. 3B). Furthermore, the participants whose household income that lower than 3000 RMB showed significantly higher anxiety and depression than the participants over 3000 RMB per month (anxiety: Fisher’s exact test, p = 0.017, Fig. 4A; depression: Fisher’s exact test, p = 0.004, Fig. 4B).

Discussion

In this study, we demonstrated that the majority of the non-medical college students presented with good sleep quality, no anxiety or depression during the prevalence of coronavirus COVID-19 in Zhanjiang city. There is no statistical difference in the sleep quality of students of different grades. No marked difference was found in anxiety or depression in terms of educational levels. Female students and the participants whose household income that lower than 3000 RMB per month were more vulnerable to anxiety and depression.

Previous study reported that 21.6% college students showed various depressive symptoms.¹⁴ Our findings showed a higher proportion of respondents with different levels of depression among non-medical college students. During the prevalence of COVID-19, the students accepted live online learning instead of face-to-face classes, and their activities in public places were restricted.^15,16 We suggested that these altered lifestyle and social patterns might contributed to the development of depression. Depression could lead to reduced quality of life and higher healthcare burden.¹⁷ Therefore, providing early recognition and support for the vulnerable students to manage their mental health is a vital need. One research pointed out that students in higher grades had a lower prevalence of sleep disturbance compared with those in the lower grades.¹⁸ The sleep quality among different grades in this study did not show statistical difference, this implied that the freshmen enrolled were quite adaptable to the new circumstances during the COVID-19 pandemic. The local government and colleges/universities might play important roles in prevention and health education of COVID-19. Low educational level was reported to be related with both anxiety and depression.¹⁹ The prevalence of anxiety and depression showed no statistical significance in our data probably owing to the imbalance in the educational levels of the included subjects.

We found that female students were more prone to anxiety and depression. This result was in accordance with the previous study demonstrating that women were approximately twice as likely to experience mood disturbance as men, including sleep problems, anxiety and depression.^20,21 This sexual discrepancy might due to different sex steroids levels. For example, testosterone has been regarded as an important sex steroid to resist anxiety and depression.²² The influence of economic status of the participants on anxiety and depression should be noted. It is demonstrated that the diabetic patients of Higher-income showed a significant decline for anxiety.²³ People with low socioeconomic status have a high incidence of anxiety and depression.²⁴ Similarly, our result also revealed that subjects with higher household incomes had lower rates of anxiety and depression. Given the use of a online survey, there might exist some response bias. Furthermore, mood disturbance was reported to be associated with inflammatory processes.²⁵ We suggest that it would be interesting to study the immunological changes in the participants in the next study. To our knowledge, this is the novel cross-sectional study aiming at evaluating the mental health problems among non-medical college students in Zhanjiang. The results from this study might help in guiding healthcare practitioners and policymakers to work out appropriate and feasible interventions to recognize and treat the students with mental disorders.

Declarations

Conflict of interest 

The authors declared no potential conflicts of interest of this article

Acknowledgments

We would like to thank the participants who voluntarily participated and professor Jia-yuan Wu for his support in statistics. 

Author contributions

Xiaojun Deng and Huiting Zhang designed the study. Xiaojun Deng developed the questionnaire, recruited the participants and wrote the main manuscript text. Huiting Zhang revised the manuscript and analyzed the data. The corresponding author (Huiting Zhang) had full access to all the data in the study and had final responsibility for the decision to submit for publication. All authors reviewed and approved the final manuscript.

Funding

This work was supported by Guangdong Medical Research Foundation, Grant/Award Number: B2018048; Science and technology research project of Zhanjiang City, Grant/Award Number: 2018B01012; Research Foundation of Guangdong Medical University, Grant/Award Number: GDMUM201807.

Competing interests

The author(s) declare no competing interests.

Ethics approval 

This study was in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The ethics committee of the Affiliated Hospital of Guangdong Medical University approved and supervised this study. 

Consent for publication

Not applicable.

Data availability statement

The dataset used and analyzed during the current study are available from the corresponding author on reasonable request.

References

1. Wang, X. et al. Investigating Mental Health of US College Students During the COVID-19 Pandemic: Cross-Sectional Survey Study. Journal of medical Internet research 22, e22817, doi:10.2196/22817 (2020).
2. Gunaratne, P., Lloyd, A. & Vollmer-Conna, U. Mood disturbance after infection. The Australian and New Zealand journal of psychiatry 47, 1152–1164, doi:10.1177/0004867413503718 (2013).
3. Chiriţă, A., Gheorman, V., Bondari, D. & Rogoveanu, I. Current understanding of the neurobiology of major depressive disorder. Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie 56, 651–658 (2015).
4. Zheng, P. et al. Gut microbiome remodeling induces depressive-like behaviors through a pathway mediated by the host's metabolism. Molecular psychiatry 21, 786–796, doi:10.1038/mp.2016.44 (2016).
5. Pappa, S. et al. Prevalence of depression, anxiety, and insomnia among healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. Brain, behavior, and immunity 88, 901–907, doi:10.1016/j.bbi.2020.05.026 (2020).
6. Cholera, R. et al. Validity of the Patient Health Questionnaire-9 to screen for depression in a high-HIV burden primary healthcare clinic in Johannesburg, South Africa. Journal of affective disorders 167, 160–166, doi:10.1016/j.jad.2014.06.003 (2014).
7. Sun, N. et al. Prevalence and determinants of depressive and anxiety symptoms in adults with type 2 diabetes in China: a cross-sectional study. BMJ open 6, e012540, doi:10.1136/bmjopen-2016-012540 (2016).
8. Naser, A. et al. Mental health status of the general population, healthcare professionals, and university students during 2019 coronavirus disease outbreak in Jordan: A cross-sectional study. Brain and behavior 10, e01730, doi:10.1002/brb3.1730 (2020).
9. Han, Q. et al. Pittsburgh Sleep Quality Index score predicts all-cause mortality in Chinese dialysis patients. International urology and nephrology 53, 2369–2376, doi:10.1007/s11255-021-02842-6 (2021).
10. Huang, J. et al. Predictors of Remission of Early-Onset Poststroke Depression and the Interaction Between Depression and Cognition During Follow-Up. Frontiers in psychiatry 9, 738, doi:10.3389/fpsyt.2018.00738 (2018).
11. Liu, C. et al. The prevalence and influencing factors in anxiety in medical workers fighting COVID-19 in China: a cross-sectional survey. Epidemiology and infection 148, e98, doi:10.1017/s0950268820001107 (2020).
12. Sampaio-Junior, B. et al. Efficacy and Safety of Transcranial Direct Current Stimulation as an Add-on Treatment for Bipolar Depression: A Randomized Clinical Trial. JAMA psychiatry 75, 158–166, doi:10.1001/jamapsychiatry.2017.4040 (2018).
13. Versiani, M., Moreno, R., Ramakers-van Moorsel, C. & Schutte, A. Comparison of the effects of mirtazapine and fluoxetine in severely depressed patients. CNS drugs 19, 137–146, doi:10.2165/00023210-200519020-00004 (2005).
14. Li, Y. et al. Mental Health Among College Students During the COVID-19 Pandemic in China: A 2-Wave Longitudinal Survey. Journal of affective disorders 281, 597–604, doi:10.1016/j.jad.2020.11.109 (2021).
15. Regmi, K. & Lwin, C. Factors Associated with the Implementation of Non-Pharmaceutical Interventions for Reducing Coronavirus Disease 2019 (COVID-19): A Systematic Review. International journal of environmental research and public health 18, doi:10.3390/ijerph18084274 (2021).
16. Qin, Z. et al. Prevalence and Risk Factors Associated With Self-reported Psychological Distress Among Children and Adolescents During the COVID-19 Pandemic in China. JAMA network open 4, e2035487, doi:10.1001/jamanetworkopen.2020.35487 (2021).
17. Rodrigues, G., Gebara, O., Gerbi, C., Pierri, H. & Wajngarten, M. Depression as a Clinical Determinant of Dependence and Low Quality of Life in Elderly Patients with Cardiovascular Disease. Arquivos brasileiros de cardiologia 104, 443–449, doi:10.5935/abc.20150034 (2015).
18. Li, Y. et al. Prevalence and correlates of poor sleep quality among college students: a cross-sectional survey. Health and quality of life outcomes 18, 210, doi:10.1186/s12955-020-01465-2 (2020).
19. Bjelland, I. et al. Does a higher educational level protect against anxiety and depression? The HUNT study. Social science & medicine (1982) 66, 1334–1345, doi:10.1016/j.socscimed.2007.12.019 (2008).
20. Serpytis, P. et al. Gender-Based Differences in Anxiety and Depression Following Acute Myocardial Infarction. Arquivos brasileiros de cardiologia 111, 676–683, doi:10.5935/abc.20180161 (2018).
21. Mong, J. & Cusmano, D. Sex differences in sleep: impact of biological sex and sex steroids. Philosophical transactions of the Royal Society of London. Series B, Biological sciences 371, 20150110, doi:10.1098/rstb.2015.0110 (2016).
22. Zarrouf, F., Artz, S., Griffith, J., Sirbu, C. & Kommor, M. Testosterone and depression: systematic review and meta-analysis. Journal of psychiatric practice 15, 289–305, doi:10.1097/01.pra.0000358315.88931.fc (2009).
23. Al-Ayed, M., Moosa, S., Robert, A. & Al Dawish, M. Anxiety, depression and their associated risk factors among patients with diabetic foot ulcer: A two center cross-sectional study in Jordan and Saudi Arabia. Diabetes & metabolic syndrome 15, 237–242, doi:10.1016/j.dsx.2020.12.034 (2021).
24. Linder, A., Gerdtham, U., Trygg, N., Fritzell, S. & Saha, S. Inequalities in the economic consequences of depression and anxiety in Europe: a systematic scoping review. European journal of public health 30, 767–777, doi:10.1093/eurpub/ckz127 (2020).
25. Beurel, E., Toups, M. & Nemeroff, C. The Bidirectional Relationship of Depression and Inflammation: Double Trouble. Neuron 107, 234–256, doi:10.1016/j.neuron.2020.06.002 (2020).