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Original Articles
35 (
3
); 147-152
doi:
10.25259/NMJI-35-3-147

Depression, anxiety, stress and resilience among undergraduate health sciences students of a rural tertiary healthcare centre in Maharashtra during the Covid-19 lockdown: A cross-sectional, online survey

Department of Psychiatry, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Sawangi, Wardha, Maharashtra, India
Department of Community Health Physiotherapy, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Sawangi, Wardha, Maharashtra, India
Department of Biochemistry, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Sawangi, Wardha, Maharashtra, India
Correspondence to AJINKYA SURESHRAO GHOGARE; ajinkyaghogaremd@gmail.com
Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

[To cite: Ghogare AS, Patil PS, Spoorthy MS, Aloney SA, Bele AW, Ambad RS. Depression, anxiety, stress and resilience among undergraduate health sciences students of a rural tertiary healthcare centre in Maharashtra during the Covid-19 lockdown: A cross-sectional, online survey. Natl Med J India 2022;35:147–52.]

Abstract

Background

The Covid-19 pandemic caused a rapidly evolving and confused situation. Health sciences students (HSSs) are not immune to depression, anxiety and stress during such a pandemic. We aimed to assess the relation between depression, anxiety, stress and resilience among undergraduate HSSs during the Covid-19 lockdown.

Methods

We conducted a cross-sectional, online survey at a rural tertiary healthcare centre in Maharashtra. Data were recorded from study participants on sociodemographic details using the 21-item Depression, Anxiety and Stress Scale (DASS-21) and the Brief Resilience Scale (BRS). Data were analysed using SPSS software version 15.0.

Results

A total of 381 students participated in the online survey. The prevalence of depression, anxiety and stress were 7.6%, 6.3% and 1.0%, respectively. There was a positive correlation between all three sub-scales of DASS-21. On BRS, 5 (1.3%) participants had high resilience, 216 (56.7%) had normal resilience and 160 (42.0%) had low resilience. Those respondents who had high resilience had lower rates of depression, anxiety and stress on DASS-21 sub-scales.

Conclusion

A proportion of HSSs had anxiety, depression and stress during the Covid-19 outbreak and lockdown. Respondents with high resilience had less frequent depression, anxiety and stress. In the long run, strengthening resilience of HSSs may be useful.

INTRODUCTION

In December 2019, the Covid-19 outbreak emerged in Wuhan, China.13 It was declared a public health emergency of concern and pandemic by WHO in March 2020.4,5 From 25 March 2020, there was a countrywide lockdown in India to contain the spread of Covid-19. Being socially isolated, working in high-risk situations and having contact with infected people are common causes of mental health problems among healthcare workers (HCWs).6,7 Many studies have recorded the psychological impact of Covid-19 on the mental health status of the general public, patients and HCWs.610 Similarly, undergraduate health sciences students (HSSs) were exposed to stressors during the virus outbreak, but this group is often overlooked.11 Continuous spread of Covid-19 globally and a strict lockdown delayed the schedules of universities, schools and colleges, including health sciences colleges across the world, including in India. However, there is little literature on the mental health status of HSSs during the Covid-19 pandemic. During the Covid-19 pandemic, gaps in mental health services have been widened, which are testing the resilience of many, including HSSs.12

Resilience is defined as ‘the ability to bounce back or recover from stress, to adapt to stressful circumstances, to not become ill despite significant adversity, and to function above the norm despite stress or adversity’.13 During the current pandemic, there has been an increase in mental health issues such as stress, anxiety and depression among many, including HSSs.14

In India, the first case of Covid-19 was detected in Kerala on 30 January 2020. Since then, the count is increasing. Nowadays, health sciences colleges and universities are facing the challenge of developing methods of guiding students to appropriately and effectively manage their emotions during the Covid-19 pandemic and avoid as well as tackle academic loss of HSSs. One study has found that delays in academic activities during the Covid-19 lockdown were associated with symptoms of anxiety.15 Therefore, we assessed the mental health status of undergraduate HSSs with the primary objective of assessing the magnitude of depression, anxiety, stress and its relation with resilience among HSSs during the Covid-19 lockdown at a rural tertiary healthcare centre in Maharashtra. Based on previous study findings,15 we hypothesized that respondents with high resilience will have lower rates of depression, anxiety and stress.

METHODS

Sample collection and study design

We conducted this cross-sectional, internet-based (www.surveymonkey.com) online survey over a period of 10 days from 4 April to 14 April 2020 through a pre-designed questionnaire, using consecutive sampling. It was approved by the Institutional Ethics Committee (reference letter no. DMIMS(DU)/IEC/2020/ 8700-A, dated 4 April 2020). The inclusion criteria adopted for the study were participants in the age group of 18–25 years, and those belonging to the undergraduate HSSs category. Each participant’s identity was kept anonymous. Before starting the survey, all study participants were provided details of the time taken to complete the survey, the nature of survey and information that filling in the survey implies the provision of informed consent by participants. The survey questionnaire was circulated using WhatsApp to HSSs of a rural tertiary healthcare centre in Maharashtra. It was an open and voluntary online survey.

The participants were not provided any incentives for participation in the survey. The participants could fill the survey form only once through a device, i.e. users with the same IP address were not able to access the survey twice, thus preventing duplication of responses. The survey was in the English language. We used two scales: the 21-item Depression, Anxiety and Stress Scale (DASS-21) and the Brief Resilience Scale (BRS).

The DASS-2116 has a set of three self-report sub-scales designed to measure depression, anxiety and stress. Each item is rated on a scale of 0–3. Each sub-scale contains seven items for depression, anxiety and stress. Scores of all three sub-scales are calculated by summing up scores for relevant items. Final scores are obtained by multiplying the total scores of all three sub-scales by two. Table I shows the recommended cut-off scores for conventional severity labels of depression, anxiety and stress.16

TABLE I. Cut-off scores for labelling the severity of depression, anxiety and stress by using DASS-21
Grade Depression Anxiety Stress
Normal 0–9 0–7 0–14
Mild 10–13 8–9 15–18
Moderate 14–20 10–14 19–25
Severe 21–27 15–19 26–33
Extremely severe 28+ 20+ 34+

DASS Depression, Anxiety and Stress Scale

Reliability of DASS-21 showed that it has excellent Cronbach alpha values of 0.81, 0.89 and 0.78 for sub-scales of depression, anxiety and stress, respectively.17 It has excellent internal consistency, discriminative, concurrent and convergent validities. Depression and anxiety sub-scales of DASS-21 had good correlations with self-rating depression scale and state-trait anxiety inventory.17 It is reliable, valid and easy to administer.17 Its utility by clinicians can enhance diagnoses of depression, anxiety and stress among university students.17

The BRS assesses the ability to bounce back or recover from stress.13 It provides unique, important information about people coping with health-related stressors. It is the measurement of coping with difficulties. The BRS consists of six items. Each item is rated on a scale of 1 to 5. For scoring, responses are added varying from 1 to 5 for all six items giving a range from 6 to 30. The total is then divided by the total number of questions/items answered. BRS scores of 1–2.99 indicate low resilience, 3–4.30 indicate normal resilience, and 4.31–5 indicate high resilience.13 Factor analysis reveals a single factor with eigenvalues above 1.0, which accounted for 73.54% of the total variance. Reliability analysis using Cronbach alpha was 0.93, indicating that the scale has good reliability.18 The study shows that the BRS is appropriate for use by college personnel and counsellors to examine and identify resilience among college students.18

Apart from the DASS-21 and BRS scales, we had observed a set of few Covid-19 lockdown-related common worries and concerns among undergraduate HSSs. We divided HSSs into medical, dental, physiotherapy and nursing faculties. We randomly chose 5 students of either gender from each faculty (i.e. a total of 20 undergraduates). The worries and concerns related to the Covid-19 lockdown included the worry related to academic loss as well as academic delay and future employment on a scale of 0–10, the worry about contracting Covid-19 to self, the worry about contracting Covid-19 by the family member(s), change in internet use, common ‘time pass’ activities, and affected sleep pattern. These common worries and concerns related to the Covid-19 lockdown were included in our study after a detailed discussion between all authors and a group of selected 20 undergraduate students, who were randomly chosen to gather their common worries and concerns regarding the Covid-19 lockdown. Data from those 20 students were not included in the final result of the present study.

Analysis

Data were entered using Microsoft Excel version 2007. Final data were analysed using SPSS statistical software version 15 (IBM, Chicago, Illinois, United States of America). A total of 430 responses were received; 49 responses were excluded as they were incomplete. Hence, the final sample size was 381. Continuous data were presented as mean and standard deviation, categorical data were presented as frequency and percentage. Chi-square test and Fisher exact test were used to determine the level of significance. Pearson test of correlation was used to test the correlation between three sub-scales of the DASS-21. Association of resilience with the presence of depression, anxiety and stress was assessed by Chi-square test and Fisher exact test. The level of significance was set at 0.05.

RESULTS

Sociodemographic parameters of the study population

A majority of study participants (59.1%) were in the age group of 18–21 years. A majority were girls (72.2%), medical students (61.2%), from urban residence (77.2%), from nuclear families (72.2%), and from Hindu religion (87.7%; Table II).

TABLE II. Sociodemographic data of the study participants (n=381)
Characteristic n(%)
Age group (years)
18–21 225 (59.1)
22–25 156 (40.9)
Mean (SD) 20.10 (1.49)
Gender
Men 106 (27.8)
Women 275 (72.2)
Faculty
Medical 233 (61.2)
Dental 8 (2.1)
Physiotherapy 92 (24.1)
Nursing 48 (12.6)
Residence
Rural 87 (22.8)
Urban 294 (77.2)
Family type
Nuclear 275 (72.2)
Joint 95 (24.9)
Extended 11 (2.9)
Religion
Hindu 334 (87.7)
Muslim 16 (4.2)
Christian 4 (1.0)
Others 27 (7.1)

Covid-19 lockdown-related parameters among the study participants

Table III shows that 30.4% of HSSs had rated ‘8’ on a scale of 0–10 points for the ‘worry about academic loss, academic delay and future employment because of Covid-19’. About 39% had the mild worry of contracting Covid-19 by themselves and by their family members (31.0%). About 47% had a moderate increase in internet use, 64.0% were sleeping less than usual during the lockdown, and boredom (31.2%) was the most common thing that bothered during the lockdown and to deal with it, the most common activity to pass the time was the use of internet (49.9%).

TABLE III. Covid-19 lockdown-related parameters among the study participants (n=381)
Lockdown-related parameter n (%)
Worry related to academic loss/delay and future employment due to the Covid-19 lockdown on the scale of 0–10
0 1 (0.3)
1 5 (1.3)
2 5 (1.3)
3 8 (2.1)
4 10 (2.6)
5 46 (12.1)
6 45 (11.8)
7 65 (17.1)
8 116 (30.4)
9 46 (12.1)
1 0 34 (8.9)
Worry about contracting Covid-19
None

31 (8.1)
Mild 148 (38.8)
Moderate 141 (37.0)
Severe 61 (16.0)
Worry about family member(s) contracting Covid-19
None

81(21.3)
Mild 118 (31.0)
Moderate 104 (27.3)
Severe 78 (20.5)
Change in internet use
No change

22 (5.8)
Mild 26 (6.8)
Moderate 178 (46.7)
Severe 155 (40.7)
Common activity to pass time
Watching television

30 (7.9)
Using the internet over mobile phone 190 (49.9)
Reading books/novels 56 (14.7)
Playing indoor games 50 (13.1)
Other 55 (14.4)
Sleep pattern affected
Not at all

84 (22.1)
Sleeping more than usual 33 (8.7)
Sleeping less than usual 244 (64.0)
Not able to fall asleep 20 (5.2)
Most bothersome thing
Boredom

119 (31.2)
Fatigue and bodyache 10 (2.6)
Thoughts about Covid-19 48 (12.6)
Sleep disturbances 41 (10.8)
Media news about Covid-19 111 (29.1)
Interpersonal conflicts 17 (4.5)
Non-availability of substances of abuse 1 (0.3)
Financial crisis 24 (6.3)
Non-availability of domestic needs 10 (2.6)

Distribution of DASS-21 sub-scale scores-based severity of depression, anxiety and stress

Table IV shows that 5.2% had mild and 2.4% had moderate depression. On the anxiety sub-scale of DASS-21, 2.9% had mild, 2.9% had moderate and 0.5% had severe anxiety. On the stress sub-scale of DASS-21, 0.8% had mild and 0.2% had moderate stress.

TABLE IV. Distribution of the severity of depression, anxiety and stress among the study participants (n=381)
Level Depression*, n(%) Anxiety†, n(%) Stress‡, n(%)
None 352 (92.4) 357 (93.7) 377 (99.0)
Mild 20 (5.2) 11 (2.9) 3 (0.8)
Moderate 9 (2.4) 11 (2.9) 1 (0.2)
Severe 0 2 (0.5) 0
Mean (SD) *3.34 (3.77) †2.46 (2.94) ‡3.39 (3.40)

Correlation between DASS-21 sub-scale scores of depression, anxiety and stress (n=381)

Table V shows that there was a high positive correlation between all three sub-scales of DASS-21. All correlations were significant at 0.01 level (2-tailed).

TABLE V. Correlation between depression, anxiety and stress sub-scales scores among the study participants
DASS-21 sub-scale Depression score Anxiety score Stress score
Depression
Correlation 1.0 0.753 0.823
Significance (2-tailed) <0.001 <0.001
Anxiety
Correlation 0.753 1.0 0.812
Significance (2-tailed) <0.001 <0.001
Stress
Correlation 0.823 0.812 1.0
Significance (2-tailed) <0.001 <0.001

DASS Depression, Anxiety and Stress Scale

Level of resilience among the study participants

On the BRS scale, 160 (42.0%) had low, 216 (56.7%) had normal and 5 (1.3%) had high resilience. The mean (SD) score on BRS was 2.89 (0.76).

Relation of resilience with depression, anxiety and stress among the study participants

Table VI shows that respondents with high resilience had less frequent depression, anxiety and stress. This suggests that an individual’s capacity to bounce back may protect him/her from experiencing depression, anxiety and stress.

TABLE VI. Relation of resilience with depression, anxiety and stress (n=381)
DASS-21 sub-scale High resilience (n=5) Normal resilience (n=216) Low resilience (n=160) p value
Depression
Present 3 (60.0) 22 (10.2) 4 (2.5) 0.000001
Absent 2 (40.0) 194 (89.8) 156 (97.5)
Anxiety
Present 2 (40.0) 21 (9.7) 1 (0.6) 0.00001
Absent 3 (60.0) 195 (90.3) 159 (99.4)
Stress
Present 2 (40.0) 1 (0.5) 1 (0.6) <0.0000001
Absent 3 (60.0) 215 (99.5) 159 (99.4)

DASS Depression, Anxiety and Stress Scale

DISCUSSION

The Covid-19 pandemic has brought on unbearable psychological pressure. Covid-19 has a mortality rate of 2%, but higher transmission and mortality rates than those combined of SARS and Middle East respiratory syndrome (MERS).19 Covid-19 has created a lot of stress among HSSs not only by creating delay in starting their college academic activities but by the postponement of their examinations. The literature has shown that HSSs were exposed to stressors during the virus outbreak, but this group is often neglected.11 Hence, there is need to pay attention to the psychological problems and the needs of HSSs during the Covid-19 pandemic.

Sociodemographic characteristics

A total of 381 of 430 study participants (88.6%) completed the survey. A survey done by Lai et al. had a completion rate of 68.7% response.20 The lower completion rate in their study might be due to its multicentric nature, as collecting data from multiple centres would be a tedious task. The majority of participants in our survey were women (72.2%). In the study by Lai et al. too women (76.7%) outnumbered men.20 Wong et al. also observed that a majority of healthcare personnel were women (65.7%).21 These findings suggest that women were more interested and responsive towards participating in the study. Our study was done at a rural tertiary healthcare centre in Maharashtra, but the majority of students had an urban residence (77.2%). A similar finding was observed by Lai et al. with the majority of the study participants from an urban area (97.1%).20 A majority of the study participants were from nuclear families (72.2%). Joint families obviously have more family members who might share responsibilities among themselves to take care of a person suffering from any physical and psychological problems. The study found that 11% of the participants came from joint families living with biological parents, while 89% of the study participants had some form of disruption in their family structure.22 Thus, family type plays an important role in the management of health problems, including psychological issues among sufferers, which holds true for HSSs also. Many researchers interested in relating the family type to mental health have studied nuclear family where mother and father were absent. Schneider concluded that there was a strong consensus among the study participants that the presence of the mother/father family was inherently superior.23

Covid-19 lockdown-related parameters among the study participants

HSSs were not able to attend their theory and practical classes and clinical postings due to the Covid-19 lockdown. Al-Rabiaah et al. stated that medical students were exposed to stressors during the virus outbreak because students had adverse effects on their academic achievement through increased avoidance of learning activities and reduced psychomotor concentration.11 Mei et al. observed that public health emergencies such as Covid-19 can have various psychological effects on college-going students and they might be expressed as anxiety, worry and fear among others.24 30.4% had rated their worry related to academic loss, academic delay and future employment due to the Covid-19 lockdown on the point of ‘8.0’ of Likert scale of 0– 10. Wong et al. had recorded mental distress caused by the virus outbreak by a single item 10-point Likert scale where the majority of respondents scored ‘6.19’, which was nearer to the value recorded in our study.21 Cornine et al. found that psychological issues of college students, mainly anxiety about Covid-19 was due to its effect on their studies.25 Wang et al. observed that psychological issues of college students, mainly anxiety about Covid-19, have been due to their effect on future employment.1 Depression, anxiety and stress among college students may have been caused by the gradually increasing social distance between students/peers, resulting from the ongoing Covid-19 lockdown. Xiao and Kmietowicz observed that among psychological issues of college students during the Covid-19 lockdown, anxiety disorders were more likely to occur and worsen in the absence of interpersonal interaction.26,27 As regards the worry about contracting Covid-19 by self, 38.8% had a ‘mild degree of worry’. As regards the worry about contracting Covid-19 by family members, 31.0% had a ‘mild degree of worry’. Wong et al. observed that sources of stress among health sciences personnel include feelings of vulnerability, loss of control and concerns about the health of self, others and family, spread of the virus, changes in work and being isolated from loved ones, which also holds true for HSSs during the Covid-19 lockdown.21 The most bothering thing during the Covid-19 lockdown was boredom (31.2%) and to cope with it, 49.9% had reported spending most of the time surfing the internet. About 46.7% reported a moderate increase in internet use during the Covid-19 lockdown. Al-Rabiaah et al. observed that students who use internet more often were more informed about the impact of viral disease, which might increase their psychological distress.11 Another study found that the more the disease was mentioned in the media, the more its seriousness was overlooked by students and vice versa.28

A majority of HSSs (64.0%) had reported that they were sleeping less than usual during the Covid-19 lockdown. Since the outbreak of the Covid-19 pandemic and its social consequence of home and institutional confinement/quarantine, a global stressful condition had developed. Being socially isolated, forced to stay at home for self-quarantine, studying from home, home-schooling, restricted outings, hampered social interaction, studying or attending classes for many hours online using smartphones/computers under stressful conditions, and facing own and family members’ health risks, would have a major impact on day-time functioning and on night-time sleep of HSSs. While spending many hours on online-classes or e-learning using smartphones/computers, there are high chances that HSSs might come across or surf on the internet the news related to the Covid-19 pandemic, which itself can act as an additional source of depression, anxiety, stress and insomnia. Huang et al. observed that being younger than 35 years of age and following Covid-19 news updates for >3 hours a day was associated with increased levels of anxiety, which could have resulted in sleep disturbances.29

Most of the studies that had investigated effects of the lockdown during the viral outbreak have not used specific sleep-related questionnaires and had focused on HCWs or those who were exposed to or suffered from the virus itself with a quarantine period of 10–14 days.30 No data are available on the assessment of sleep quality and severity of insomnia among HSSs during viral pandemics. This emphasizes the importance of using sleep specific questionnaires for HCWs and HSSs.

Distribution and the relation of depression, anxiety, stress and resilience

The DASS-21 total score ranged from 0 to 96, with a mean (SD) score of 9.14 (9.35). The total score on the depression sub-scale of DASS-21 ranged from 0 to 40 with a mean (SD) score of 3.34 (3.77); 20 respondents (5.2%) had mild and 9 (2.4%) had moderate depression. The prevalence of depression among HSSs was 7.6%. Tan et al. observed that 42 (8.9%) health sciences personnel had depression on the DASS-21 depression sub-scale. The mean (SD) score of depression sub-scale in their study was 2.54 (5.23).31 The total score on the anxiety sub-scale of DASS-21 ranged from 0 to 32, with a mean (SD) score of 2.46 (2.94); 11 respondents (2.9%) had mild, 11 (2.9%) had moderate and 2 (0.5%) had severe anxiety. The prevalence of anxiety among HSSs was 6.3%. Al-Rabiaah et al. observed that 134 (77.0%) had minimal, 32 (18.4%) had mild, 8 (4.6%) had moderate anxiety.11 Tan et al. found that 68 (14.5%) HCWs had anxiety based on the DASS-21 anxiety sub-scale, with a mean (SD) score of 2.45 (4.28).31 Not only HCWs working in isolation units and hospitals but HSSs also do not receive any training for maintaining their mental health.9

Anxiety among HSSs may rise following increased media reporting and an increasing number of new cases. Anxiety among HSSs may rise following the academic loss and academic delays due to the Covid-19 lockdown. Cornine et al. observed that anxiety due to the Covid-19 pandemic had affected the studies of college students.25 Wang et al. observed that Covid-19 had caused anxiety among college students as students perceived that they might not get future employment due to academic loss during the Covid-19 outbreak.1 Xiao and Kmietowicz found that anxiety disorders among college students had occurred and worsened in the Covid-19 lockdown due to the absence of interpersonal communication.26,27 Mass lockdown is likely to raise anxiety significantly. Increased anxiety may also have knock-on implications for other health measures, including mental health measures among HSSs.32

The total score on stress sub-scale of DASS-21 ranged from 0 to 42, with a mean (SD) score of 3.39 (3.40); 3 respondents (0.8%) had mild and 1 (0.2%) had moderate stress. The prevalence of stress among HSSs was 1.0%. Tan et al. found that 31 (6.6%) study participants had stress. The mean (SD) score of the stress sub-scale in respondents was 3.82 (5.74).31 In our study, there was a high positive correlation between all three sub-scales of DASS-21. All correlations were significant at the 0.01 level (2-tailed).

The government had taken many measures to limit the spread of Covid-19, which has included ban on travelling and extending the lockdown. However, it has disrupted routine life, inevitably resulting in anxiety in many, which was true for HSSs too.33 Many universities, including health sciences universities, have postponed classes and examinations and used distant or remote learning methods such as internet-based e-lectures.34 Such sudden and drastic change in the pattern of learning may have caused a major impact on education and growth of college students. Social support plays a pivotal role in everyone’s mental health, including that of HSSs. Cao et al.,15 Thompson et al.35 and Chen et al.8 observed that social support was negatively correlated with anxiety among college students.

Resilience among HSSs can be strengthened through social support programmes arranged by health sciences colleges and universities by taking professional help from people qualified in providing mental health support such as psychiatrists and psychologists. Social support not only decreases psychological burden but also leads to a change in attitude towards help-seeking behaviour among HSSs. Hence, HSSs should receive psychological, social support during public health emergencies such as the Covid-19 lockdown, which is consistent with the findings of a study by Bai et al.36

In our study, the total BRS score ranged from 1 to 5, with the mean (SD) score being 2.89 (0.76). Based on the BRS scores, 5 respondents (1.3%) had high, 216 (56.7%) had normal and 160 (42.0%) had low resilience. Liu et al. observed that the Covid-19 outbreak had highlighted potential gaps in mental health services during emergencies while testing the resilience of HCWs and the medical system, which included HSSs.12 In our study, the respondents who had high resilience had shown lower scores of depression, anxiety and stress. This suggests that an individual’s capacity to bounce back may protect him/ her from experiencing depression, anxiety and stress during a stressful period such as the Covid-19 lockdown. Duan et al. observed similar findings and stated that psychological problems such as depression, anxiety and stress had increased during the Covid-19 outbreak.14 Thus, resilience helps a person to cope with psychological problems. Peng et al. observed a similar finding that resilience moderated negative life events and mental health issues among Chinese HSSs.37 They concluded that promoting resilience among HSSs can be helpful for their psychological adjustments.37

Limitations

First, the study was conducted in a single centre, thus limiting the generalizability of the results found. Second, although respondents answered self-administered questionnaires based on their actual performance, overestimation or exaggeration may be a factor.

Conclusions

We recommend that health sciences colleges and health authorities should address the psychological needs of HSSs, especially during a crisis such as the Covid-19 lockdown. The results of our study highlight the importance of instituting psychological support programmes for HSSs during infectious disease outbreaks to strengthen their mental health through boosting their resilience. It is advisable that the government in collaboration with professional bodies and relevant experts develop a plan for implementation of psycho-educational programmes in emergency preparedness. Such programmes would help HSSs to deal effectively with depression, anxiety and stress through the strengthening of resilience and coping skills.

ACKNOWLEDGEMENT

We thank all the study participants for their cooperation.

Conflicts of interest

None declared

References

  1. , , , . A novel coronavirus outbreak of global health concern. Lancet. 2020;395:470-3.
    [CrossRef] [PubMed] [Google Scholar]
  2. , , , , , , et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med. 2020;382:1199-207.
    [CrossRef] [PubMed] [Google Scholar]
  3. , , , , , , et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382:727-33.
    [CrossRef] [PubMed] [Google Scholar]
  4. . Emerging understandings of 2019-nCoV. Lancet. 2020;395:311.
    [CrossRef] [PubMed] [Google Scholar]
  5. . Note from the editors: World Health Organization declares novel coronavirus (2019-nCoV) sixth public health emergency of international concern In: Euro Surveill. Vol 25. . p. :200131e.
    [CrossRef] [Google Scholar]
  6. , , , , , , et al. The psychological impact of the SARS epidemic on hospital employees in China: Exposure, risk perception, and altruistic acceptance of risk. Can J Psychiatry. 2009;54:302-11.
    [CrossRef] [PubMed] [Google Scholar]
  7. , , , , , , et al. The immediate psychological and occupational impact of the 2003 SARS outbreak in a teaching hospital. CMAJ. 2003;168:1245-51.
    [Google Scholar]
  8. , , , , , , et al. Mental health care for medical staff in China during the COVID-19 outbreak. Lancet Psychiatry. 2020;7:e15-6.
    [CrossRef] [PubMed] [Google Scholar]
  9. , , , , , . Mental health services for older adults in China during the COVID-19 outbreak. Lancet Psychiatry. 2020;7:e19.
    [CrossRef] [PubMed] [Google Scholar]
  10. , , , , , , et al. The psychological impact of COVID-19 and restrictive measures in the world. J Affect Disord. 2021;283:36-51.
    [CrossRef] [PubMed] [Google Scholar]
  11. , , , , , , et al. Middle East respiratory syndrome-corona virus (MERS-CoV) associated stress among medical students at a university teaching hospital in Saudi Arabia. J Infect Public Health. 2020;13:687-91.
    [CrossRef] [PubMed] [Google Scholar]
  12. , , , , , , et al. Online mental health services in China during the COVID-19 outbreak. Lancet Psychiatry. 2020;7:e17-8.
    [CrossRef] [PubMed] [Google Scholar]
  13. , , , , , . The brief resilience scale: Assessing the ability to bounce back. Int J Behav Med. 2008;15:194-200.
    [CrossRef] [PubMed] [Google Scholar]
  14. , . Psychological interventions for people affected by the COVID-19 epidemic. Lancet Psychiatry. 2020;7:300-2.
    [CrossRef] [PubMed] [Google Scholar]
  15. , , , , , , et al. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Res. 2020;287:112934.
    [CrossRef] [PubMed] [Google Scholar]
  16. , . Manual for the depression anxiety stress scales. (2nd ed). Sydney: Psychology Foundation; .
    [CrossRef] [Google Scholar]
  17. , , . Psychometric properties of the 21-item depression anxiety stress scale (DASS-21) Afr Res Rev. 2018;12:135-42.
    [CrossRef] [Google Scholar]
  18. , , , , . Evaluation and psychometric status of the brief resilience scale in a sample of Malaysian international students. Asian Soc Sci. 2014;10:1-7.
    [CrossRef] [Google Scholar]
  19. . Coronavirus Covid-19 has killed more people than SARS and MERS combined, despite lower case fatality rate. BMJ. 2020;368:m641.
    [CrossRef] [PubMed] [Google Scholar]
  20. , , , , , , et al. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA Netw Open. 2020;3:e203976.
    [CrossRef] [PubMed] [Google Scholar]
  21. , , , , , , et al. The psychological impact of severe acute respiratory syndrome outbreak on healthcare workers in emergency departments and how they cope. Eur J Emerg Med. 2005;12:13-18.
    [CrossRef] [PubMed] [Google Scholar]
  22. , , . Effects of family structure on mental health of children: A preliminary study. Indian J Psychol Med. 2017;39:457-63.
    [CrossRef] [PubMed] [Google Scholar]
  23. . American kinship: A cultural account In: Englewood Cliffs. NJ: Prentice-Hall; .
    [Google Scholar]
  24. , , , . Psychological investigation of university students in a university in Jilin province. J Med Soc. 2011;24:84-6.
    [Google Scholar]
  25. . Reducing nursing student anxiety in the clinical setting: An integrative review. Nurs Educ Perspect. 2020;41:229-34.
    [CrossRef] [PubMed] [Google Scholar]
  26. . A novel approach of consultation on 2019 novel coronavirus (COVID-19)-related psychological and mental problems: Structured letter therapy. Psychiatry Investig. 2020;17:175-6.
    [CrossRef] [PubMed] [Google Scholar]
  27. . Rules on isolation rooms for suspected covid-19 cases in GP surgeries to be relaxed. BMJ. 2020;368:m707.
    [CrossRef] [PubMed] [Google Scholar]
  28. , , . Medicine in the popular press: The influence of the media on perceptions of disease. PLoS One. 2008;3:e3552.
    [CrossRef] [PubMed] [Google Scholar]
  29. , . Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: A web-based cross-sectional survey. Psychiatry Res. 2020;288:112954.
    [CrossRef] [PubMed] [Google Scholar]
  30. , , , , , , et al. The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. Lancet. 2020;395:912-20.
    [CrossRef] [PubMed] [Google Scholar]
  31. , , , , , , et al. Psychological impact of the COVID-19 pandemic on health care workers in Singapore. Ann Intern Med. 2020;173:317-20.
    [CrossRef] [PubMed] [Google Scholar]
  32. , . Coronavirus: The psychological effects of quarantining a city. BMJ Opinion. 2020;368:m313.
    [CrossRef] [PubMed] [Google Scholar]
  33. , , , , , . An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov) Infect Dis Model. 2020;5:248-55.
    [CrossRef] [PubMed] [Google Scholar]
  34. , , , , . Novel coronavirus (2019-nCoV) cases in Hong Kong and implications for further spread. J Infect. 2020;80:671-93.
    [CrossRef] [PubMed] [Google Scholar]
  35. , , , . Resilience among medical students: The role of coping style and social support. Teach Learn Med. 2016;28:174-82.
    [CrossRef] [PubMed] [Google Scholar]
  36. , , , , , . Correlation between psychological changes of the community crowd and the social support in grave public health event. Inner Mongolia Med J. 2005;37:295-7.
    [Google Scholar]
  37. , , , , , , et al. Negative life events and mental health of Chinese medical students: The effect of resilience, personality and social support. Psychiatry Res. 2012;196:138-41.
    [CrossRef] [PubMed] [Google Scholar]
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