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. 2021 Apr 13;9:e11154. doi: 10.7717/peerj.11154

The prevalence of fatigue among Chinese nursing students in post-COVID-19 era

Shou Liu 1,2,3,#, Hai-Tao Xi 4,#, Qian-Qian Zhu 5,6, Mengmeng Ji 7, Hongyan Zhang 8, Bing-Xiang Yang 9, Wei Bai 2,3, Hong Cai 2,3, Yan-Jie Zhao 2,3, Li Chen 4, Zong-Mei Ge 4, Zhiwen Wang 7, Lin Han 8, Pan Chen 9, Shuo Liu 9, Teris Cheung 10, Brian J Hall 11, Feng-Rong An 6,, Yu-Tao Xiang 2,3,
Editor: Bao-Liang Zhong
PMCID: PMC8051357  PMID: 33954035

Abstract

Background

Due to the COVID-19 outbreak, all teaching activities in nursing schools were suspended in China, and many nursing students were summoned to work in hospitals to compensate for the shortage of manpower. This study examined the prevalence of fatigue and its association with quality of life (QOL) among nursing students during the post-COVID-19 era in China.

Methods

This was a multicenter, cross-sectional study. Nursing students in five Chinese universities were invited to participate. Fatigue, depressive and anxiety symptoms, pain and QOL were measured using standardized instruments.

Results

A total of 1,070 nursing students participated. The prevalence of fatigue was 67.3% (95% CI [64.4–70.0]). Multiple logistic regression analysis revealed that male gender (P = 0.003, OR = 1.73, 95% CI [1.20–2.49]), and being a senior nursing student (second year: OR = 2.20, 95% CI [1.46–3.33], P < 0.001; third year: OR = 3.53, 95% CI [2.31–5.41], P < 0.001; and fourth year OR = 3.59, 95% CI [2.39–5.40], P < 0.001) were significantly associated with more severe fatigue. In addition, moderate economic loss during the COVID-19 pandemic (OR = 1.48, 95% CI [1.08–3.33], P < 0.015; compared to low loss), participants with more severe depressive (OR = 1.48, 95% CI [1.22–1.78], P < 0.001) and anxiety symptoms (OR = 1.12, 95% CI [1.05–1.20], P = 0.001), and more severe pain (OR = 1.67, 95%CI [1.46–1.91], P < 0.001) were significantly associated with reported more severe fatigue. After controlling for covariates, nursing students with fatigue had a lower overall QOL score compared to those without (F(1, 1070) = 31.4, P < 0.001).

Conclusion

Fatigue was common among nursing students in the post-COVID-19 era. Considering the negative impact of fatigue on QOL and daily functioning, routine physical and mental health screening should be conducted for nursing students. Effective stress-reduction measures should be enforced to assist this subpopulation to combat fatigue and restore optimal health.

Keywords: Fatigue, Quality of life, Nursing students, COVID-19 pandemic

Introduction

Fatigue refers to abnormal exhaustion following normal activities (Cavanaugh, 2002; Shapiro et al., 2005). Fatigue is associated with lifestyle factors (e.g., physical exertion, lack of sleep, use of antidepressants), physical health problems (e.g., anemia, autoimmune disorders, and chronic obstructive pulmonary disease), and mental health problems (e.g., sleep disorders, anxiety, and depression) (De Venter et al., 2017; Friedberg et al., 2016). All of these factors could lead to additional detrimental outcomes such as headache, faintness, shortness of breath, and increased risk of suicidality (Zhu, Han & Li, 2019).

The prevalence of fatigue varies in different populations. For instance, the prevalence of fatigue ranged from 15% to 30% in teenagers (Findlay, 2008; Ghandour et al., 2004); 11.9% in adults, with 8.5% in men, and 14.9% in women (Wendt et al., 2019). The prevalence of fatigue was usually more common in certain subpopulations. For instance, the Australian Medical Association found that out of 716 doctors, 53% were at higher risk of fatigue whilst on duty (Australian Medical Association, 2017). In another study, around 85% of patients with head and neck cancer experienced fatigue (Bossi et al., 2019). In addition, college students, particularly those enrolled in health-related subjects, often suffered from fatigue (Dol, 2016; Pallant, Sullivan & Kaluzny, 2020; Shim et al., 2019). For example, one study found that the prevalence of fatigue was 16.5% among medical students (Tanaka et al., 2008), while the corresponding figure was even higher among nursing students (39.1%) (De Moraes Amaducci, De Correa Mota & De Mattos Pimenta, 2010).

Coronavirus Disease 2019 (COVID-19) was first reported in Wuhan, China in December, 2019 (Huang et al., 2020) and then found in more than 200 countries and territories (World Health Organization, 2020). Since April 2020, COVID-19 has been well-contained in China (National Health Commission of China, 2020). To lower the risk of contagion between students, the spring semester was postponed in all universities in China in early 2020. Further, all classroom teaching was suspended, and replaced by online teaching and learning (Xinhuanet, 2020a, 2020b). Due to lockdown measures, outdoor/physical activities were prohibited in many areas of China. In addition to sudden changes of traditional face-to-face learning modes, students were exposed to high level of academic stress (Brooks et al., 2020; Wang et al., 2020a), which may trigger negative health outcomes including fatigue (Elhai et al., 2020; Király et al., 2020; Miao et al., 2020a, 2020b). Compared to those enrolling in other non-health related subjects, students in health-related majors, such as nursing, may be at higher risks of fatigue due to higher curriculum demand and academic workload from the faculty of nursing.

In order to reduce the likelihood of negative health outcomes caused by fatigue, it is important to understand its prevalence and associated factors. To date, however, fatigue among nursing students in the post- COVID-19 era has not been investigated. Therefore, the aims of this study were to: (1) examine the prevalence of fatigue among nursing students in the post COVID-19 era in China and (2) explore the association between fatigue and quality of life (QOL) among nursing students.

Methods

Participants and study settings

This was a multicenter, cross-sectional study conducted between September 14 and October 7, 2020 across five university nursing schools (Peking University, Capital Medical University, Jilin University, Lanzhou University, and Wuhan University) in China. In order to avoid contagion during the COVID-19 pandemic, face-to-face interviews were not plausible. Consistent with other studies (Bo et al., 2020; Ma et al., 2020), data were collected using the Questionnaire Star Application embedded in WeChat, which is a widely used social communication application with over 1 billion users in China. WeChat had been used as a teaching tool in the participating nursing schools, therefore, all students were WeChat users. Nursing students in the participating nursing schools were consecutively invited to participate in this study, and those who electronically signed the online written informed consent could access the assessment. To be eligible, participants were (1) undergraduate nursing students, (2) aged between 15 and 28 years, (3) able to understand the content of the assessments, and (4) able to provide written informed consent. The study protocol (No:2020-10) was approved by the Institutional Review Board (IRB) at Beijing Anding Hospital of Capital Medical University and all collaborating university nursing schools.

Measurement tools

Basic socio-demographic data, such as gender, age, year of study, perceived economic status were collected based on self-report. COVID-19 related experiences were asked using standardized questions, including (1) whether they were volunteers in clinical settings during the COVID-19 pandemic; (2) whether they had negative experiences (e.g., such as verbal abuse and threats) during the COVID-19 pandemic; (3) whether they experienced economic loss during the COVID-19 pandemic; (4) whether they used social media frequently to obtain relevant information during the COVID-19 pandemic; and (5) economic status and perceived health status were also asked using standardized questions.

Fatigue was measured using the numeric rating scale (NRS), scoring from “0” (not suffering from fatigue) to “10” (unbearable suffering from fatigue) (Berger et al., 2010). Higher scores indicated more severe fatigue, and a score of ≥4 was considered “clinically relevant fatigue” (“having fatigue” hereafter) (Oldenmenger et al., 2013). Another NRS was adopted to evaluate severity of overall body pain (pain hereafter) (Haefeli & Elfering, 2006), which was scored from “0” (no pain) to “10” (worst pain imaginable), with a higher score indicating more severe pain (Li, Herr & Chen, 2009; Li, Liu & Herr, 2007; Liu & Li, 2004).

The Chinese version of the Patient Health Questionnaire (PHQ-2) was used to measure depressive symptoms (Chen, Sheng & Qu, 2015; Kroenke, Spitzer & Williams, 2001). Each item scored from 0 (not at all) to 3 (nearly every day). The total score ranged from 0 to 6, with a higher score representing more severe depressive symptoms. The Chinese version of the Generalized Anxiety Disorder scale seven items (GAD-7) was used to assess anxiety symptoms. Each item scored from 0 (not at all) to 3 (almost every day), with a higher score indicating more severe anxiety symptoms (He et al., 2010; Spitzer et al., 2006). QOL was measured using the first two items on overall QOL of the World Health Organization Quality of Life-brief version (WHOQOL-BREF) (Fang & Hao, 1999; Harper, Power & The WHOQOL group, 1998; Xia et al., 2012), with higher scores indicating greater QOL.

Statistical analysis

Data were analyzed using the IBM Statistical Package for Social Science (SPSS) program, version 24.0. The comparisons between nursing students with and without fatigue were conducted using two independent samples t tests, Mann-Whitney U Tests, and Chi-square tests, as appropriate. Analysis of covariance (ANCOVA) was conducted to examine the independent association between fatigue and QOL, after adjusting for variables with significant group differences in univariate analyses. Binary logistic regression analysis with the “enter” method was performed to test the independent correlates of fatigue, with fatigue as the dependent variable, and those with significant group differences in the univariate analyses as independent variables. Significance level was set at 0.05 (two-tailed).

Results

Altogether, 1,121 nursing students were consecutively invited to participate in this study; of whom, 1,070 met the study criteria and completed the assessment, yielding a response rate of 95.5%. The prevalence of fatigue was 67.3% (95% CI [64.4–70.0]). There were significant differences between fatigue and no fatigue groups in terms of gender, age, year of study, economic loss during COVID-19 pandemic, financial perception, health perception, and the PHQ-2, GAD-7, and pain total scores (Table 1). After controlling for covariates, nursing students with fatigue had lower QOL (F(1, 1070) = 31.4, P < 0.001) than those without.

Table 1. Socio-demographical and scale’ scores of nursing students.

Variables Total Non Fatigue Fatigue Univariate analyses
(N = 1,070) (N = 350) (N = 720)
N % N % N % χ2 df P
Male gender 265 24.8 63 18.0 202 28.1 12.78 1 <0.001
Rural residence 457 42.7 145 41.4 312 43.2 0.35 1 0.555
Only Child 457 42.7 147 42.0 310 43.1 0.11 1 0.742
Year of Study 64.11 3 <0.001
First year 287 26.8 147 42.0 140 19.4
Second year 237 22.1 72 20.6 165 22.9
Third year 249 23.3 60 17.1 189 26.3
Fourth year 297 27.9 71 20.3 226 31.4
Being volunteer during COVID-19 pandemic 231 21.6 66 18.9 165 22.9 2.29 1 0.130
Having negative experiences during COVID-19 pandemic 188 17.6 51 14.6 137 19.0 3.23 1 0.073
Economic loss during COVID-19 pandemic 18.35 2 <0.001
Not or mild 444 41.5 177 50.6 267 37.1
Moderate 557 52.1 157 44.9 400 55.6
Great 69 6.4 16 4.6 53 7.4
Frequent use of social media during COVID-19 pandemic 778 72.7 252 72.0 526 73.1 0.13 1 0.716
Perceived economic status 8.90 2 0.012
Poor 218 20.4 63 18.0 155 21.5
Fair 776 72.5 251 71.7 525 72.9
Rich 76 7.1 36 10.3 40 5.6
Perceived health status 45.70 2 <0.001
Poor 23 2.1 4 4.1 19 2.6
Fair 449 42.0 99 28.3 350 48.6
Good 598 55.9 247 70.6 351 48.8
Mean SD Mean SD Mean SD t/Z df P
Age (years) 19.7 1.4 19.4 1.5 19.9 1.4 5.55 1068 <0.001
Fatigue total 4.8 2.1 2.5 0.7 6.0 1.5 51.48 1068 <0.001
PHQ-2 total 1.0 1.2 0.5 0.8 1.3 1.3 10.76 --a <0.001
GAD-7 total 3.1 3.9 1.4 2.5 4.0 4.2 11.09 --a <0.001
Pain total 2.4 1.8 1.6 1.0 2.8 1.9 9.76 --a <0.001
QOL total 6.7 1.5 7.5 1.3 6.4 1.5 12.58 1068 <0.001

Notes:

a

Mann-Whitney U test.

Bolded values: <0.05.

COVID-19, Coronavirus Disease 2019; df, degree of freedom PHQ-2, the 2-item Patient Health Questionnaire; QOL, quality of life; GAD-7, 7-item Generalized Anxiety Disorder; SD, standard deviation.

Multiple logistic regression analysis revealed that men (Odds Ratio (OR) = 1.73, 95% CI [1.20–2.49], P = 0.003), students in their 2nd (OR = 2.20, 95% CI [1.46–3.33], P < 0.001), 3rd (OR = 3.53, 95% CI [2.31–5.41], P < 0.001) and 4th year (OR = 3.59, 95% CI [2.39–5.40], P < 0.001; compared to students in their first year), moderate economic loss during the COVID-19 pandemic (OR = 1.48, 95% CI [1.08–3.33], P = 0.015; compared to low loss), more severe depressive (OR = 1.48, 95% CI [1.22–1.78], P < 0.001), and anxiety symptoms (OR = 1.12, 95% CI [1.05–1.20], P = 0.001), and more severe pain (OR = 1.67, 95% CI [1.46–1.91], P < 0.001) were significantly associated with more severe fatigue (Table 2).

Table 2. Independent correlates of fatigue by multiple logistic regression analysis.

Variables Multiple logistic regression analysis
P OR 95% CI
Male gender 0.003 1.73 [1.20–2.49]
Year of study
First year 1.0
Second year <0.001 2.20 [1.46–3.33]
Third year <0.001 3.53 [2.31–5.41]
Fourth year <0.001 3.59 [2.39–5.40]
Economic loss during COVID-19 pandemic
Not or mild 1.0
Moderate 0.015 1.48 [1.08–2.02]
Great 0.352 1.41 [0.68–2.91]
Perceived economic status
Poor 1.0
Fair 0.100 1.41 [0.94–2.13]
Rich 0.495 1.26 [0.65–2.44]
Perceived health status
Poor 1.0
Fair 0.151 2.70 [0.70–10.50]
Good 0.312 2.02 [0.52–7.86]
PHQ-2 total <0.001 1.48 [1.22–1.78]
GAD-7 total 0.001 1.12 [1.05–1.20]
Pain total <0.001 1.67 [1.46–1.91]

Notes:

Bolded values: <0.05.

CI, confidential interval; OR, odds ratio; PHQ-2, the 2-item Patient Health Questionnaire; QOL, quality of life; GAD-7, 7-item Generalized Anxiety Disorder Scale. There was collinearity between age and grade, therefore age was not entered in the model as an independent variable.

Discussion

This study examined the prevalence of fatigue among nursing students in post-COVID-19 era. We found that 67.3% of nursing students reported fatigue, which is almost double the prevalence of fatigue (36%) in qualified nurses on shift work assessed by the Occupational Fatigue Exhaustion Recovery scale (Geiger-Brown et al., 2012). Our finding was similar to the corresponding figure (73.7%) in frontline staff (including doctors, nurses, police officers, volunteers, community workers, and journalists) during COVID-19 outbreak in China as measured by the Fatigue Self-Assessment Scale (Teng et al., 2020). In contrast, the level of fatigue among medical students was relatively low (13.8%) before the COVID-19 outbreak (Abdali, Nobahar & Ghorbani, 2020). Owing to different measurement tools on fatigue, direct comparisons between studies should be interpreted with caution.

Fatigue appeared to be common among nursing students in the post-COVID-19 era and this can be attributed to several reasons. First, previous studies found that fatigue among students who majored in health-related subjects was usually related to poor academic performance and related problems, such as absenteeism, and having a sedentary lifestyle (e.g., lack of physical exercise) (Cruz et al., 2018). Sudden shifting from traditional classroom learning to online learning coupled with limited outdoor physical activities during the COVID-19 outbreak in China may have led to poorer academic performance, and increased absenteeism, which is often linked with sedentary lifestyle, and this in turn may have led to more fatigue among nursing students. Second, many nursing and medical students served as volunteers in clinical settings during the COVID-19 outbreak. Persistent high levels of stress and anxiety (Cao et al., 2020) at work could further exacerbate the risk of fatigue (Abdali, Nobahar & Ghorbani, 2020; Doerr et al., 2015; Nijrolder, Van der Horst & Van der Windt, 2008). In addition, potential risk of susceptibility to COVID-19 infection on top of a heavy clinical workload may have also escalated the risk of fatigue amidst the COVID-19 outbreak. Third, daily infection precautionary measures at work (e.g., face mask wearing, frequent hand-washing, full gear personal protection equipment adherence), reduced social etiquette practices (e.g., shaking hands) and social distancing, could lead to boredom (Miao et al., 2020b), anxiety, frustration (Aristovnik et al., 2020), and mental fatigue.

In this study, we found that male students were more likely to report fatigue than their female counterparts. In China, nursing students are predominantly women. In traditional Chinese culture, men have been ascribed the social status of “pillars” within the family and in the society; therefore, they were often expected to be responsible for more heavy tasks and challenges than women in public health crisis situations (e.g., COVID-19 outbreak). In addition, female students who major in health-related subjects usually have a better academic performance than male students (Alzahrani, Soo Park & Tekian, 2018; Voyer & Voyer, 2014). Such gender differences in academic performance suggests that female students may adapt better than male students in the switching of learning modes. These social and educational factors could result in greater fatigue in male students. Similar to previous findings (Labrague & Ballad, 2020), we found that the 2nd (OR = 2.20), 3rd (OR = 3.53) and 4th year students (OR = 3.59) were more likely to report fatigue than 1st year students. Senior nursing students receive more crisis response and medical training compared to junior students. As such, they usually undertook a greater responsibility in combating the COVID-19 outbreak, which possibly explained the differences in the level of fatigue between years of study.

As expected, more severe fatigue was associated with greater economic loss, more severe depressive and anxiety symptoms, and more severe pain among nursing students in this study. Greater economic loss could lead to psychological distress, which may in turn increase the risk of fatigue. Similar findings were found in university students (Shim et al., 2019) before and during COVID-19 outbreak (Verma, 2020; Wang et al., 2020b). The relationship between fatigue and depression/anxiety were bidirectional (Thorsteinsson et al., 2019) (i.e., fatigue could increase the risk of depression and anxiety, and vice versa). Consistent with previous findings (Kaasa et al., 1999; Yoon et al., 2019), in this study more severe pain was associated with a higher risk of fatigue in nursing students. Pain is defined as an unpleasant sensory and emotional experience usually associated with actual or potential tissue damage (Raja et al., 2020) caused by internal and/or external factors (e.g., cold, heat, physical pressure and lesions). Adjustment mechanisms in the human body attempt to relieve pain through the central brain feedback system (Mauger, 2013; Rainville, 2002). If the predisposing factors cannot be addressed and remain chronic, the adjustment/restoration system will be out of balance and the body will be fatigued (Aaronson et al., 1999; Sharpe & Wilks, 2002).

Similar to previous findings (Kratz et al., 2017; Nunes et al., 2017), we found that nursing students with fatigue had a lower overall QOL than those without. As a widely used health outcome measure, QOL is closely associated with the interactions between protective factors (e.g., better social support) and risk factors (e.g., physical distress) (Hatoum et al., 1998). Fatigue was also associated with physical and mental distress, which could lower QOL.

The strengths of this study included the multi-site design, relatively large sample size and use of standardized instruments. However, several methodological limitations should be acknowledged. First, casual relationships between fatigue and other variables could not be established due to cross-sectional design. Second, only five university nursing schools were included, and hence, our findings may not be generalizable to all nursing students in China. Third, some factors (e.g., academic pressure and social support) associated with fatigue were not assessed due to logistical reasons.

Conclusion

Fatigue was common among nursing students in post-COVID-19 era. Considering the negative impact of fatigue on QOL and daily functioning, routine physical and mental health screening should be conducted for nursing students. Effective stress-reduction strategies should be executed to assist nursing students to combat fatigue and restore optimal health.

Supplemental Information

Supplemental Information 1. Raw data.
DOI: 10.7717/peerj.11154/supp-1
Supplemental Information 2. Questionnaire.
DOI: 10.7717/peerj.11154/supp-2

Funding Statement

The study was supported by the National Science and Technology Major Project for investigational new drug (2018ZX09201-014), the Beijing Municipal Science & Technology Commission (No. Z181100001518005), the 2020 Higher Education Teaching Achievement Cultivation Project of Gansu Province, the Fundamental Research Funds for the Central Universities (2020YJ065), the University of Macau (MYRG2019-00066-FHS) and the National Natural Science Foundation of China (81860606). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Contributor Information

Feng-Rong An, Email: afrylm@sina.com.

Yu-Tao Xiang, Email: xyutly@gmail.com.

Additional Information and Declarations

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

Shou Liu conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Hai-Tao Xi performed the experiments, analyzed the data, prepared figures and/or tables, and approved the final draft.

Qian-Qian Zhu performed the experiments, analyzed the data, prepared figures and/or tables, and approved the final draft.

Mengmeng Ji performed the experiments, analyzed the data, prepared figures and/or tables, and approved the final draft.

Hongyan Zhang performed the experiments, analyzed the data, prepared figures and/or tables, and approved the final draft.

Bing-Xiang Yang performed the experiments, analyzed the data, prepared figures and/or tables, and approved the final draft.

Wei Bai performed the experiments, analyzed the data, prepared figures and/or tables, and approved the final draft.

Hong Cai performed the experiments, prepared figures and/or tables, and approved the final draft.

Yan-Jie Zhao performed the experiments, prepared figures and/or tables, and approved the final draft.

Li Chen performed the experiments, prepared figures and/or tables, and approved the final draft.

Zong-Mei Ge performed the experiments, prepared figures and/or tables, and approved the final draft.

Zhiwen Wang performed the experiments, prepared figures and/or tables, and approved the final draft.

Lin Han performed the experiments, prepared figures and/or tables, and approved the final draft.

Pan Chen performed the experiments, prepared figures and/or tables, and approved the final draft.

Shuo Liu performed the experiments, prepared figures and/or tables, and approved the final draft.

Teris Cheung conceived and designed the experiments, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Brian J. Hall conceived and designed the experiments, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Feng-Rong An conceived and designed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Yu-Tao Xiang conceived and designed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Human Ethics

The following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers):

The study protocol was approved by the Institutional Review Board (IRB) at Beijing Anding Hospital of Capital Medical University and all collaborating university nursing schools (2020-10).

Data Availability

The following information was supplied regarding data availability:

Raw data and the questionnaire are available in the Supplemental Files.

References

  • Aaronson et al. (1999).Aaronson LS, Teel CS, Cassmeyer V, Neuberger GB, Pallikkathayil L, Pierce J, Press AN, Williams PD, Wingate A. Defining and measuring fatigue. Image: The Journal of Nursing Scholarship. 1999;31(1):45–50. doi: 10.1111/j.1547-5069.1999.tb00420.x. [DOI] [PubMed] [Google Scholar]
  • Abdali, Nobahar & Ghorbani (2020).Abdali N, Nobahar M, Ghorbani R. Evaluation of emotional intelligence, sleep quality, and fatigue among Iranian medical, nursing, and paramedical students: a cross-sectional study. Qatar Medical Journal. 2020;2019(3):15. doi: 10.5339/qmj.2019.15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Alzahrani, Soo Park & Tekian (2018).Alzahrani SS, Soo Park Y, Tekian A. Study habits and academic achievement among medical students: a comparison between male and female subjects. Medical Teacher. 2018;40(Suppl. 1):S1–S9. doi: 10.1080/0142159X.2018.1464650. [DOI] [PubMed] [Google Scholar]
  • Aristovnik et al. (2020).Aristovnik A, Keržič D, Ravšelj D, Tomaževič N, Umek L. Impacts of the COVID-19 pandemic on life of higher education students: a global perspective. Sustainability. 2020;12(20):8438. doi: 10.3390/su12208438. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Australian Medical Association (2017).Australian Medical Association . Managing the risks of fatigue in the medical workforce 2016: AMA safe hours audit. Barton: AMA; 2017. [Google Scholar]
  • Berger et al. (2010).Berger AM, Abernethy AP, Atkinson A, Barsevick AM, Breitbart WS, Cella D, Cimprich B, Cleeland C, Eisenberger MA, Escalante CP, Jacobsen PB, Kaldor P, Ligibel JA, Murphy BA, O’Connor T, Pirl WF, Rodler E, Rugo HS, Thomas J, Wagner LI. NCCN clinical practice guidelines cancer-related fatigue. Journal of the National Comprehensive Cancer Network. 2010;8(8):904–931. doi: 10.6004/jnccn.2010.0067. [DOI] [PubMed] [Google Scholar]
  • Bo et al. (2020).Bo HX, Li W, Yang Y, Wang Y, Zhang Q, Cheung T, Wu X, Xiang YT. Posttraumatic stress symptoms and attitude toward crisis mental health services among clinically stable patients with COVID-19 in China. Psychological Medicine. 2020:1–2. doi: 10.1017/S0033291720000999. Epub ahead of print 27 March 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Bossi et al. (2019).Bossi P, Di Pede P, Guglielmo M, Granata R, Alfieri S, Iacovelli NA, Orlandi E, Guzzo M, Bianchi R, Ferella L, Infante G, Miceli R, Licitra L, Ripamonti CI. Prevalence of fatigue in head and neck cancer survivors. Annals of Otology, Rhinology & Laryngology. 2019;128(5):413–419. doi: 10.1177/0003489419826138. [DOI] [PubMed] [Google Scholar]
  • Brooks et al. (2020).Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, Rubin GJ. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet. 2020;395(10227):912–920. doi: 10.1016/S0140-6736(20)30460-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Cao et al. (2020).Cao W, Fang Z, Hou G, Han M, Xu X, Dong J, Zheng J. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research. 2020;112934(10224):112934. doi: 10.1016/j.psychres.2020.112934. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Cavanaugh (2002).Cavanaugh RM., Jr Evaluating adolescents with fatigue: ever get tired of it? Pediatrics in Review. 2002;23(10):9–348. doi: 10.1542/pir.23-10-337. [DOI] [PubMed] [Google Scholar]
  • Chen, Sheng & Qu (2015).Chen M, Sheng L, Qu S. Diagnostic test of screening depressive disorder in general hospital with the patient health questionnaire (in Chinese) Chinese Mental Health. 2015;29(4):241–245. [Google Scholar]
  • Cruz et al. (2018).Cruz JP, Felicilda-Reynaldo RFD, Lam SC, Contreras FAM, Cecily HSJ, Papathanasiou IV, Fouly HA, Kamau SM, Valdez GFD, Adams KA. Quality of life of nursing students from nine countries: a cross-sectional study. Nurse Education Today. 2018;66(6):135–142. doi: 10.1016/j.nedt.2018.04.016. [DOI] [PubMed] [Google Scholar]
  • De Moraes Amaducci, De Correa Mota & De Mattos Pimenta (2010).De Moraes Amaducci C, De Correa Mota DDF, De Mattos Pimenta CA. Fatigue among nursing undergraduate students. Revista da Escola de Enfermagem da USP. 2010;44(4):1052–1058. doi: 10.1590/S0080-62342010000400028. [DOI] [PubMed] [Google Scholar]
  • De Venter et al. (2017).De Venter M, Illegems J, Van Royen R, Moorkens G, Sabbe BG, Van Den Eede F. Differential effects of childhood trauma subtypes on fatigue and physical functioning in chronic fatigue syndrome. Comprehensive Psychiatry. 2017;78:76–82. doi: 10.1016/j.comppsych.2017.07.006. [DOI] [PubMed] [Google Scholar]
  • Doerr et al. (2015).Doerr JM, Ditzen B, Strahler J, Linnemann A, Ziemek J, Skoluda N, Hoppmann CA, Nater UM. Reciprocal relationship between acute stress and acute fatigue in everyday life in a sample of university students. Biological Psychology. 2015;110(45):42–49. doi: 10.1016/j.biopsycho.2015.06.009. [DOI] [PubMed] [Google Scholar]
  • Dol (2016).Dol KS. Fatigue and pain related to Internet usage among university students. Journal of Physical Therapy Science. 2016;28(4):1233–1237. doi: 10.1589/jpts.28.1233. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Elhai et al. (2020).Elhai JD, Yang H, McKay D, Asmundson GJG. COVID-19 anxiety symptoms associated with problematic smartphone use severity in Chinese adults. Journal of Affective Disorders. 2020;274:576–582. doi: 10.1016/j.jad.2020.05.080. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Fang & Hao (1999).Fang JQ, Hao YA. Reliability and validity for Chinese version of WHO quality of life scale (in Chinese) Chinese Mental Health Journal. 1999;13(4):203–209. [Google Scholar]
  • Findlay (2008).Findlay SM. The tired teen: a review of the assessment and management of the adolescent with sleepiness and fatigue. Paediatrics & Child Health. 2008;13(1):37–42. doi: 10.1093/pch/13.1.37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Friedberg et al. (2016).Friedberg F, Adamowicz JL, Caikauskaite I, Napoli A, Shapira O, Hobbs M, Bromet E, Kotov R, Gonzalez A, Clouston S. Fatigue severity in World Trade Center (9/11) responders: a preliminary study. Fatigue: Biomedicine, Health & Behavior. 2016;4(2):70–79. doi: 10.1080/21641846.2016.1169726. [DOI] [Google Scholar]
  • Geiger-Brown et al. (2012).Geiger-Brown J, Rogers VE, Trinkoff AM, Kane RL, Bausell RB, Scharf SM. Sleep, sleepiness, fatigue, and performance of 12-hour-shift nurses. Chronobiology International. 2012;29(2):211–219. doi: 10.3109/07420528.2011.645752. [DOI] [PubMed] [Google Scholar]
  • Ghandour et al. (2004).Ghandour RM, Overpeck MD, Huang ZJ, Kogan MD, Scheidt PC, Medicine A. Headache, stomachache, backache, and morning fatigue among adolescent girls in the United States: associations with behavioral, sociodemographic, and environmental factors. Archives of Pediatrics & Adolescent Medicine. 2004;158(8):797–803. doi: 10.1001/archpedi.158.8.797. [DOI] [PubMed] [Google Scholar]
  • Haefeli & Elfering (2006).Haefeli M, Elfering A. Pain assessment. European Spine Journal. 2006;15(1):S17–S24. doi: 10.1007/s00586-005-1044-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Harper, Power & The WHOQOL group (1998).Harper A, Power M, The WHOQOL group Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychological Medicine. 1998;28(3):551–558. doi: 10.1017/S0033291798006667. [DOI] [PubMed] [Google Scholar]
  • Hatoum et al. (1998).Hatoum HT, Kong SX, Kania CM, Wong JM, Mendelson WB. Insomnia, health-related quality of life and healthcare resource consumption. Pharmacoeconomics. 1998;14(6):629–637. doi: 10.2165/00019053-199814060-00004. [DOI] [PubMed] [Google Scholar]
  • He et al. (2010).He XY, Li CB, Qian J, Cui HS, Wu WY. Reliability an dvalidity of a generalized anxiety disorder scale in general haspital outpatients. Shanghai Archives of Psychiatry. 2010;22(4):200–203. [Google Scholar]
  • Huang et al. (2020).Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506. doi: 10.1016/S0140-6736(20)30183-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kaasa et al. (1999).Kaasa S, Loge JH, Knobel H, Jordhøy M, Brenne E. Fatigue. Measures and relation to pain. Acta Anaesthesiologica Scandinavica. 1999;43(9):939–947. doi: 10.1034/j.1399-6576.1999.430911.x. [DOI] [PubMed] [Google Scholar]
  • Király et al. (2020).Király O, Potenza MN, Stein DJ, King DL, Hodgins DC, Saunders JB, Griffiths MD, Gjoneska B, Billieux J, Brand M. Preventing problematic internet use during the COVID-19 pandemic: consensus guidance. Comprehensive Psychiatry. 2020;100:152180. doi: 10.1016/j.comppsych.2020.152180. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kratz et al. (2017).Kratz AL, Braley TJ, Foxen-Craft E, Scott E, Murphy JF. How do pain, fatigue, depressive, and cognitive symptoms relate to well-being and social and physical functioning in the daily lives of individuals with multiple sclerosis? Archives of Physical Medicine and Rehabilitation. 2017;98(11):2160–2166. doi: 10.1016/j.apmr.2017.07.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kroenke, Spitzer & Williams (2001).Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine. 2001;16(9):606–613. doi: 10.1046/j.1525-1497.2001.016009606.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Labrague & Ballad (2020).Labrague L, Ballad CA. Lockdown fatigue among college students during the covid-19 pandemic: predictive role of personal resilience, coping behaviours, and health. MedRxiv. 2020 doi: 10.1101/2020.10.18.20213942. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Li, Herr & Chen (2009).Li L, Herr K, Chen P. Postoperative pain assessment with three intensity scales in Chinese elders. Journal of Nursing Scholarship. 2009;41(3):241–249. doi: 10.1111/j.1547-5069.2009.01280.x. [DOI] [PubMed] [Google Scholar]
  • Li, Liu & Herr (2007).Li L, Liu X, Herr K. Postoperative pain intensity assessment: a comparison of four scales in Chinese adults. Pain Medicine. 2007;8(3):223–234. doi: 10.1111/j.1526-4637.2007.00296.x. [DOI] [PubMed] [Google Scholar]
  • Liu & Li (2004).Liu X-Q, Li L. The selection of pain intensity assessment scales in Chinese elders (in Chinese) Chinese Journal of Nursing. 2004;39(3):165–167. [Google Scholar]
  • Ma et al. (2020).Ma YF, Li W, Deng HB, Wang L, Wang Y, Wang PH, Bo HX, Cao J, Wang Y, Zhu LY, Yang Y, Cheung T, Ng CH, Wu X, Xiang YT. Prevalence of depression and its association with quality of life in clinically stable patients with COVID-19. Journal of Affective Disorders. 2020;275:145–148. doi: 10.1016/j.jad.2020.06.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Mauger (2013).Mauger AR. Fatigue is a pain—the use of novel neurophysiological techniques to understand the fatigue-pain relationship. Frontiers in Physiology. 2013;4:104. doi: 10.3389/fphys.2013.00104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Miao et al. (2020a).Miao C, Xueming C, Tour L, Haibo Y, Hall BJ. Media use and acute psychological outcomes during COVID-19 outbreak in China. Journal of Anxiety Disorders. 2020a;74(4):102248. doi: 10.1016/j.janxdis.2020.102248. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Miao et al. (2020b).Miao C, Xueming C, Tour L, Haibo Y, Hall BJ. Psychological distress and state boredom during the COVID-19 outbreak in China: the role of meaning in life and media use. European Journal of Psychotraumatology. 2020b;11(1):1769379. doi: 10.1080/20008198.2020.1769379. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • National Health Commission of China (2020).National Health Commission of China Interpretation of the circular on further strengthening the work of infection prevention and control in medical institutions in order to implement the requirements of regular epidemic prevention and control (in Chinese), National Health Commission of China. 2020. http://www.nhc.gov.cn/yzygj/s3594/202005/4f8326122836421c9d50bf1a074402ee.shtml http://www.nhc.gov.cn/yzygj/s3594/202005/4f8326122836421c9d50bf1a074402ee.shtml
  • Nijrolder, Van der Horst & Van der Windt (2008).Nijrolder I, Van der Horst H, Van der Windt D. Prognosis of fatigue: a systematic review. Journal of Psychosomatic Research. 2008;64(4):335–349. doi: 10.1016/j.jpsychores.2007.11.001. [DOI] [PubMed] [Google Scholar]
  • Nunes et al. (2017).Nunes MDR, Jacob E, Bomfim EO, Lopes-Junior LC, De Lima RAG, Floria-Santos M, Nascimento LC. Fatigue and health related quality of life in children and adolescents with cancer. European Journal of Oncology Nursing. 2017;29(6):39–46. doi: 10.1016/j.ejon.2017.05.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Oldenmenger et al. (2013).Oldenmenger WH, De Raaf PJ, De Klerk C, Van der Rijt CC. Cut points on 0-10 numeric rating scales for symptoms included in the Edmonton Symptom Assessment Scale in cancer patients: a systematic review. Journal Pain Symptom Manage. 2013;45(6):1083–1093. doi: 10.1016/j.jpainsymman.2012.06.007. [DOI] [PubMed] [Google Scholar]
  • Pallant, Sullivan & Kaluzny (2020).Pallant A, Sullivan T, Kaluzny A. Nutritional deficiency presenting as acute pain, fatigue and bruising in a college health clinic. Journal of American College Health. 2020:1–3. doi: 10.1080/07448481.2020.1767111. Epub ahead of print 20 May 2020. [DOI] [PubMed] [Google Scholar]
  • Rainville (2002).Rainville P. Brain mechanisms of pain affect and pain modulation. Current Opinion in Neurobiology. 2002;12(2):195–204. doi: 10.1016/S0959-4388(02)00313-6. [DOI] [PubMed] [Google Scholar]
  • Raja et al. (2020).Raja SN, Carr DB, Cohen M, Finnerup NB, Flor H, Gibson S, Keefe FJ, Mogil JS, Ringkamp M, Sluka KA. The revised International Association for the Study of Pain definition of pain: concepts, challenges, and compromises. Pain. 2020;161(9):1976–1982. doi: 10.1097/j.pain.0000000000001939. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Shapiro et al. (2005).Shapiro C, Ohayon M, Huterer N, Grunstein R. Fighting fatigue and sleepiness. Practical strategies for minimizing sleepiness and fatigue. Ontario: Joli joco publications Inc; 2005. [Google Scholar]
  • Sharpe & Wilks (2002).Sharpe M, Wilks D. Fatigue. BMJ. 2002;325(7362):480–483. doi: 10.1136/bmj.325.7362.480. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Shim et al. (2019).Shim E-J, Noh H-L, Yoon J, Mun HS, Hahm B-J. A longitudinal analysis of the relationships among daytime dysfunction, fatigue, and depression in college students. Journal of American College Health. 2019;67(1):51–58. doi: 10.1080/07448481.2018.1462819. [DOI] [PubMed] [Google Scholar]
  • Spitzer et al. (2006).Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of Internal Medicine. 2006;166(10):1092–1097. doi: 10.1001/archinte.166.10.1092. [DOI] [PubMed] [Google Scholar]
  • Tanaka et al. (2008).Tanaka M, Mizuno K, Fukuda S, Shigihara Y, Watanabe Y. Relationships between dietary habits and the prevalence of fatigue in medical students. Nutrition. 2008;24(10):985–989. doi: 10.1016/j.nut.2008.05.003. [DOI] [PubMed] [Google Scholar]
  • Teng et al. (2020).Teng Z, Wei Z, Qiu Y, Tan Y, Chen J, Tang H, Wu H, Wu R, Huang J. Psychological status and fatigue of frontline staff two months after the COVID-19 pandemic outbreak in China: a cross-sectional study. Journal of Affective Disorders. 2020;275:247–252. doi: 10.1016/j.jad.2020.06.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Thorsteinsson et al. (2019).Thorsteinsson EB, Brown RF, Owens MT, disease m. Modeling the effects of stress, anxiety, and depression on rumination, sleep, and fatigue in a nonclinical sample. Journal of Nervous. 2019;207(5):355–359. doi: 10.1097/NMD.0000000000000973. [DOI] [PubMed] [Google Scholar]
  • Verma (2020).Verma K. The mental health impact of the COVID-19 epidemic on college students in India. Asian Journal of Psychiatry. 2020;53(7):102398. doi: 10.1016/j.ajp.2020.102398. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Voyer & Voyer (2014).Voyer D, Voyer SD. Gender differences in scholastic achievement: a meta-analysis. Psychological Bulletin. 2014;140(4):1174–1204. doi: 10.1037/a0036620. [DOI] [PubMed] [Google Scholar]
  • Wang et al. (2020a).Wang G, Zhang Y, Zhao J, Zhang J, Jiang F. Mitigate the effects of home confinement on children during the COVID-19 outbreak. Lancet. 2020a;395(10228):945–947. doi: 10.1016/S0140-6736(20)30547-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Wang et al. (2020b).Wang Z-H, Yang H-L, Yang Y-Q, Liu D, Li Z-H, Zhang X-R, Zhang Y-J, Shen D, Chen P-L, Song W-Q. Prevalence of anxiety and depression symptom, and the demands for psychological knowledge and interventions in college students during COVID-19 epidemic: a large cross-sectional study. Journal of Affective Disorders. 2020b;275:188–193. doi: 10.1016/j.jad.2020.06.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Wendt et al. (2019).Wendt A, Costa CS, Machado AKF, Costa FS, Neves RG, Flores TR, Santos I, Wehrmeister FC. Sleep disturbances and daytime fatigue: data from the Brazilian National Health Survey, 2013. Cadernos de Saúde Pública. 2019;35(3):e00086918. doi: 10.1590/0102-311x00086918. [DOI] [PubMed] [Google Scholar]
  • World Health Organization (2020).World Health Organization Weekly operational update on COVID-19–30 October 2020. World Health Organization. 2020. https://www.who.int/publications/m/item/weekly-operational-update---30-october-2020 https://www.who.int/publications/m/item/weekly-operational-update---30-october-2020
  • Xia et al. (2012).Xia P, Li N, Hau K-T, Liu C, Lu Y. Quality of life of Chinese urban community residents: a psychometric study of the mainland Chinese version of the WHOQOL-BREF. BMC Medical Research Methodology. 2012;12(1):37. doi: 10.1186/1471-2288-12-37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Xinhuanet (2020a).Xinhuanet Schools start online courses as epidemic control postpones new semester. 2020a. http://www.xinhuanet.com/english/2020-02/17/c_138792006.htm. [1 March 2020]. http://www.xinhuanet.com/english/2020-02/17/c_138792006.htm
  • Xinhuanet (2020b).Xinhuanet China postpones school semester amid novel coronavirus outbreak. 2020b. http://www.xinhuanet.com/english/2020-01/28/c_138738646.htm. [1 March 2020]. http://www.xinhuanet.com/english/2020-01/28/c_138738646.htm
  • Yoon et al. (2019).Yoon IA, Sturgeon JA, Feinstein AB, Bhandari RP. The role of fatigue in functional outcomes for youth with chronic pain. European Journal of Pain. 2019;23(8):1548–1562. doi: 10.1002/ejp.1431. [DOI] [PubMed] [Google Scholar]
  • Zhu, Han & Li (2019).Zhu H, Han G, Li S. Chronic fatigue stress and sudden death, effects of stress on human health. London: IntechOpen; 2019. [Google Scholar]

Associated Data

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

Supplementary Materials

Supplemental Information 1. Raw data.
DOI: 10.7717/peerj.11154/supp-1
Supplemental Information 2. Questionnaire.
DOI: 10.7717/peerj.11154/supp-2

Data Availability Statement

The following information was supplied regarding data availability:

Raw data and the questionnaire are available in the Supplemental Files.


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