Insomnia during the COVID-19 pandemic: prevalence and correlates in a multi-ethnic population Singapore

Abstract

Background

Globally, the Coronavirus disease 2019 (COVID-19) pandemic had a significant impact on mental health. Sudden lifestyle changes, threatening information received through various sources, fear of infection and other stressors led to sleep disturbances such as insomnia. The current study aimed to assess the prevalence of insomnia and its associated risk factors during the first wave of COVID-19 pandemic among Singapore residents.

Methods

A cross-sectional study conducted online and in person, from May 2020 to June 2021, recruited Singapore citizens and permanent residents, aged 21 years and above, fluent in English, Chinese or Malay language. Respondents answered an interviewer-administered questionnaire, including Insomnia Severity Index (ISI), Generalised Anxiety Disorder-7 (GAD-7), Physical Health Questionnaire (PHQ-9), stress scale of the Depression, Anxiety and Stress Scales (DASS), chronic conditions checklist and COVID-19 related stressors (exposure to COVID-19, current and future perceived risk of infection). Chi-squared test followed by stepwise logistic regression analysis were conducted to determine factors associated with insomnia.

Results

The study recruited 1129 respondents. Prevalence of insomnia was noted to be 7.4% in the sample. Insomnia was significantly associated with psychological distress- depression (p < 0.001) and anxiety (p < 0.001), financial loss as a source of stress (p < 0.012), ever been diagnosed with asthma (p < 0.001) and backache (p < 0.002).

Conclusion

Insomnia was prevalent and associated with higher level of psychological distress among Singapore residents. These findings can be utilised to design effective targeted interventions like cognitive behavioural therapy, therapist assisted relaxation and meditation programs to improve sleep and reduce psychological distress. Interventions like these can be delivered via smartphone applications enabling easy access, delivery, and utilization by the vulnerable groups. Overall, these strategies would not only help people maintain better mental health and sleep quality during a pandemic but also build resilience, enhancing society’s ability to cope with future crises.

Introduction

Globally, during the COVID-19 pandemic, prevalence of sleep disturbances such as narcolepsy, restless leg syndrome, parasomnias, nightmares, obstructive sleep apnoea and insomnia ranged from 18 to 82% [1, 2]. Several international studies have reported a surge in sleep disturbances during the pandemic, with prevalence estimates ranging from 30 to 60% [3, 4]. Among the psychological sequelae of the pandemic, sleep disturbances, particularly insomnia, have drawn increasing attention. Insomnia is defined by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) as a persistent difficulty with sleep initiation, duration, consolidation, or quality despite adequate opportunity for sleep, leading to daytime impairment or distress [5]. The COVID-19 global crisis disrupted regular life patterns, and studies have shown significant associations between the pandemic and increased prevalence of insomnia [6–8]. The high prevalence of insomnia suggests a substantial impact on the psychological well-being of communities both, during and after pandemic [9].

The spread of the virus occurred in waves, with each wave of infection amplifying uncertainties, social isolation, and economic disruptions. During the pandemic’s first and second waves, global studies reported a marked increase in the prevalence of insomnia, with some estimates suggesting that nearly 40% of the general population was affected [3, 7]. Countries across the world experienced these waves differently due to varying public health responses, vaccination rollouts, and socio-political contexts. The progress of the COVID-19 pandemic has been strongly correlated with mental health conditions such as anxiety, depression post-traumatic stress disorder, which often negatively affect sleep, as sleep is considered a transdiagnostic factor directly linked to emotional regulation [10–12]. People’s emotional regulation during crisis was thus disrupted which interfered with the natural process of falling and staying asleep, leading to difficulties in sleeping [12]. Alterations in such regulatory processes may lead to significant detrimental effects ranging from daytime sleepiness to insomnia, cognitive impairment to immunosuppression and metabolic disorders [13, 14].

Multiple population-based studies during the COVID-19 pandemic observed deteriorated sleep health and increase in prevalence of insomnia-related symptoms often associated with psychological problems [2, 15–21]. In response to the association between insomnia and the COVID-19 pandemic, various terms have been coined such as, ‘Coronasomnia’ or ‘Covidsomnia’. Coronasomnia, a sleepless condition or insomnia that is aggravated by various severe concerns and stressors induced by the pandemic, such as fear and risk of infection, increased screen time, lack of physical activity, decreased exposure to daylight during periods of quarantine or confinement, stress, depression, anxiety, loneliness, isolation, and suicidality [8, 12, 22–25]. For instance, a person experiencing mental stress due to the pandemic may lose sleep as stress activates autonomic nervous system to release cortisol hormone that puts the system in fight or flight mode. In addition to this, rise in the levels of cortisol disrupts the production of sleep hormone melatonin, which is responsible for restful sleep [23]. As a result, falling asleep and in turn experiencing good sleep quality would be challenging.

Insomnia was observed among patients with COVID-19 and was seen to be associated with poor clinical prognosis [26]. Rates of insomnia were elevated among individuals who experienced high levels of social isolation and uncertainty regarding the future, as well as those directly impacted by the virus, such as healthcare workers and those with loved ones affected by COVID-19 [27, 28]. Existing evidence suggests that being a healthcare worker was an important risk factor for insomnia and psychological comorbidity during the COVID-19 pandemic, which can be explained by their nightshifts, increased workload as well as being in contact with patients infected with COVID-19 that might be associated with fear, anxiety, stress, and exhaustion [29, 30]. Apart from healthcare workers and COVID-19 patients, the general population experienced psychological distress and significant levels of anxiety, stress and sleeplessness due to substantial changes in their lifestyles, from over information or misinformation received about transmission of virus, infection rate, changing mandatory advisories etc [8, 25, 29]. Psychological distress is a concept embedded in the context of anxiety, stress, depression, and distress associated with other physical symptoms. COVID-19 pandemic caused severe psychological distress globally but only few studies investigated its associations with insomnia and other sleep problems [31, 32]. A population study in United States observed a dose response association between insomnia symptoms and the bio-psychosocial correlates such as somatic symptoms, depression, anxiety, and social loneliness [33]. Whereas as a Taiwanese cross-sectional study observed that insomnia severity mediated the relationship between fear of COVID-19, lower resilience, depression, and suicidal ideation [34]. In line with this, a model estimated COVID-19 related risk and fear, socio- demographic variables, behavioural factors along with mental health problems such as anxiety, stress, depression to be the predictors of insomnia during the COVID-19 pandemic [2, 22, 35].

Singapore, like many other countries, implemented strict mask requirements, a circuit breaker, quarantine measures, and social distancing to mitigate the spread of the virus. While these actions were necessary to contain the outbreak, they also contributed to heightened levels of stress, anxiety, and depression among the population, which are well-established risk factors for insomnia [36, 37]. Other factors that might have significantly contributed to increase in the risk of insomnia during Covid-19 pandemic were lifestyle disruptions such as social isolation to work-from-home arrangements [15, 38]. But there is lack of research conducted in Singapore examining the relationship between insomnia and its associations during the early phase of COVID-19 pandemic. Thus, the purpose of the present study is to address this gap by assessing the prevalence of insomnia in the general population of Singapore and investigating the factors associated with it during the first wave of COVID-19 pandemic.

Methodology

Participants

The current cross-sectional study was conducted among the general population of Singapore during the period of circuit breaker (i.e. partial lock down), from May 2020 to June 2021. Participants from the Singapore Mental Health Study (SMHS) 2016 [24, 29], a national psychiatric epidemiological study conducted in the general population of Singapore, who had agreed to be re-contacted (n = 3370) for future studies were invited to participate in the current study. The response rate was noted to be 54.8% as a total of 1129 participants agreed to participate in the study. The participants were contacted via emails and phone calls and invited to participate in the current study. The survey was administered by trained interviewers online via the Zoom platform. The participants who were not comfortable to participate in the survey online but were willing to do it in person, were contacted for face-to-face survey, after the easing of social restrictions. The inclusion criteria for this study reflected the criteria of the SMHS 2016 study- Singapore residents (citizens or permanent residents), aged 21 years and above, fluent in English, Chinese, or Malay language. Singapore residents who were uncontactable due to change in contact details, those on long-term hospitalisation or institutionalisation throughout the study period and those not fluent in English, Chinese, or Malay language were excluded from the study. The informed consent process was completed prior to the survey and all participants were provided with a copy of the consent online or in person. The survey data was captured using Question Pro software (QuestionPro, Austin, US). On completion of the survey, an inconvenience fee of SGD 40 was transferred to the participants digitally (e.g., PayNow or PayLah) or in-person.

Ethics approval (DSRB 2020/00462) was obtained from the Domain Specific Review Board of the National Healthcare Group, Singapore.

Measures

1. Socio-demographic information- Information was collected on age, gender, ethnicity (Chinese, Malay, Indian, and Others), marital status (single, married, divorced/separated, or widowed), educational level completed (primary and below, secondary, pre-university/junior college, vocational/ITE, diploma and university), employment status (employed, unemployed and economically inactive, i.e., students, homemakers, and retirees) and household income.

2. Insomnia Severity Index (ISI) - It consists of 7 domains with 1 item each assessing severity of sleep-onset, sleep maintenance, early morning awakening problems, sleep dissatisfaction, interference of sleep difficulties with daytime functioning, noticeability of sleep problems by others and distress caused by the sleep difficulties during daytime and night-time over the past 2 weeks [30]. Each of the 7 items are scored from 0 to 4, higher scores indicate greater severity of insomnia. Scores are summed up to obtain a total score that ranges from 0 to 28, where 0–7 is classified as no clinically significant insomnia; 8–14 as sub threshold insomnia; 15–21 as moderate clinical insomnia and 22–28 as severe clinical insomnia [30]. The scale has high internal consistency with a Cronbach’s alpha = 0.90 and is correlated with the individual items that range from 0.55 to 0.81 (mean 0.71). A cut off point of 10 is recommended which provides a sensitivity of 86.1% and specificity of 87.7% for detecting insomnia in a community sample [30]. This scale has been used in the Singapore’s population [39]. The Cronbach alpha for ISI was 0.89 in the current study sample.

3. Generalized Anxiety Disorder (GAD-7) - Is a 7-item self-report anxiety scale that assesess the patient’s health status during the past 2 weeks [40]. The items investigate the intensity of patient being bothered by feeling nervous, anxious or on edge, not being able to stop or control worrying, worrying too much about different things, having trouble relaxing, being so restless that it is hard to sit still, becoming easily annoyed or irritable and feeling afraid as if something awful might happen. Scores of 0, 1,2 or 3 are marked for experiencing symptoms ‘not at all’, for ‘several days’, for ‘more than half the days’ and for ‘nearly every day’, respectively. The scores are then added and presented from 0 to 21. Scores of 5, 10 and 15 represent cut-off points for mild, moderate, and severe anxiety. A cut-off points of 10 or greater is used for screening for an anxiety disorder. GAD-7 has good reliability and validity, with internal consistency (Cronbach’s alpha) being 0.79–0.91 [41]. In the current sample, the Cronbach’s alpha of the GAD-7 scale was 0.86.

4. Patient Health Questionnaire (PHQ-9) – It is 9-item scale for screening, diagnosing and monitoring the severity of depression [42]. Diagnosis of major depression is made if 5 or more out of the 9 depressive symptoms are present in the previous 2 weeks for at least “more than half the days” and 1 of the symptoms presented is depressed mood or anhedonia. Each of the 9 items of the scale are scored from 0 (not at all) to 3 (nearly every day), total score ranging from 0 to 27. PHQ-9 has good internal reliability with a Cronbach’s α of 0.89 [43]. In the current sample, the Cronbach’s alpha of the PHQ-9 scale was 0.81.

5. Depression Anxiety and Stress Scales (DASS) - The current study included the sub-scale for stress [44]. The scale has been validated in Singapore [45]. DASS has a good internal consistency with a Cronbach’s α of 0.52 for the stress subscale [45, 46]. In the current sample, the Cronbach’s alpha of the stress sub- scale was 0.85, which is better than that reported in the earlier study.

6. Chronic Condition Checklist (CCC) – It is an interviewer administered checklist used to assess chronic physical health conditions of the respondents [47]. The respondents were asked to report if a doctor had diagnosed them with any of the disorders listed in the checklist. The list consists of chronic medical conditions prevalent in Singapore which included asthma, high blood sugar or diabetes, hypertension etc. Details of the age of diagnosis and history of treatment were recorded for participants who had been diagnosed with that condition. This instrument has been used as part of the Singapore Mental health Study (SMHS) 2010 and 2016 in Singapore [29].

7. COVID-19 related stressors and exposure to COVID-19 infection – The questions assessed participant’s views about current and perceived risk of infection- and the risk in one month in the future, social distancing and preventive measures, exposure to COVID-19 cases in their neighbourhood, quarantine history, thoughts and concerns related to COVID-19 outbreak such as- ‘I might be infected with COVID-19’, ‘Family members or friends might be infected with COVID-19’, ‘I might die due to COVID-19’, ‘Family members or friends might die due to COVID-19’. Overseas travel restrictions, working from home, restriction on social gathering, unemployment, financial loss- losing work opportunities and having to take unpaid leave and school closure were also investigated as stressors.

Study sample size calculation

The sample size calculation was conducted to determine the sample needed to produce a precise estimate with a margin of error equal to 1% for different disorders. We used previously estimated prevalence rates of mental disorders from low prevalence (GAD = 1.6%) to high prevalence (MDD = 6.3%) disorders in the Singapore Mental Health Study [29] to estimate the parameters. The final adjusted sample size required to achieve this level of precision with an allowance of 30% incomplete data ranged from 1269 to 1663, respectively [29].

Statistical analysis

All statistical tests were carried out using the STATA software version 15. A weighted analysis was used to ensure that the survey findings were representative of the Singapore adult population. The weights were calculated using a post stratification weighing approach. In this approach, raking was applied for the sample to be representative of the 2020 population statistics from the Singapore Department of Statistics using age, sex, education, marital and ethnicity. Data analysis performed included descriptive analysis, chi-squared test, and logistic regression analysis. A series of multivariable logistic regression models were conducted using the backward stepwise method to identify the socio- demographic and clinical variables correlates of insomnia. In step one, that is, on full model of variables, univariate analysis with chi-squared test was performed. Following this, a series of backward stepwise logistic regression tests were performed, where variables with the highest p value > 1.0 were removed from the model and new model fits. The stepwise regression was used because it is a useful approach to reduce multicollinearity and risk of overfitting due to many predictors (k > 30) by selecting the most relevant significant variables with more parsimonious model. This was continued till all the variables in the model reach statistical significance with a p-value’ below 0.05.

Results

A total of 1129 participants were recruited in the current cross-sectional study. The prevalence of insomnia was noted to be 7.4% among Singapore residents during COVID-19 pandemic. The univariate analysis in step 1 showed significant socio-demographic correlation for age and marital status along with clinical correlates of insomnia which were COVID-19 related stressors, psychological distress- depression and anxiety, stress, chronic conditions (Table 1). The final model of the analysis revealed that those who reported being diagnosed with asthma (OR = 4.29, 95% CI = 1.89–9.72, p < 0.001) and backache (OR = 3.53, 95% CI = 1.62–7.70, p < 0.002); psychological distress- depression (OR = 9.79, 95% CI = 3.59–26.67, p < 0.001) and anxiety (OR = 5.73, 95% CI = 2.09–15.72, p < 0.001), and stated financial loss being a significant source of stress (OR = 2.91, 95% CI = 1.27–6.69, p < 0.012) were more likely to be associated with insomnia (Table 2).

Table 1.

Univariate analysis of socio demographic and clinical correlates of Insomnia

Variables	Insomnia				X2	P value
	No		Yes
	N	%	N	Weighted%
Age					19.79	0.02
21–34	376	87.55	50	12.45
35–49	340	92.33	21	7.67
50 and above	329	95.89	13	4.11
Marital Status					24.98	0.01
Never Married	316	86.35	47	13.65
Married	650	95.22	31	4.78
Divorced/ Separated/ Widowed	79	93.67	6	6.33
Depression					265.09	< 0.001
No	988	96.37	43	3.631
Yes	57	49.71	41	50.29
Anxiety					210.59	< 0.001
No	974	96.06	47	3.94
Yes	71	55.41	37	44.59
Stress					114.87	< 0.001
No	977	94.94	50	5.06
Yes	68	62.49	34	37.51
COVID-19 Related Stressors
I might be infected with COVID-19					8.45	0.05
No	715	94.15	41	5.85
Yes	330	89.25	43	10.75
Unemployment					10.24	0.04
No	585	94.7	25	5.30
Yes	460	89.64	59	10.36
Financial loss					24.27	< 0.001
No	553	95.97	18	4.03
Yes	492	88.24	66	11.76
School Closure					22.01	< 0.001
No	783	94.38	50	5.62
Yes	262	84.99	34	15.01
Exposure to COVID-19: Have you directly been in contact with any of the identified clusters in Singapore					5.10	0.01
No	997	92.96	75	7.04
Yes	36	80.08	8	19.92
Chronic Conditions
Asthma					18.30	< 0.001
No	940	93.7	68	6.30
Yes	104	82.27	16	17.73
Backache					32.63	< 0.001
No	917	94.31	70	5.69
Yes	124	80.9	14	19.1
Migraine					22.73	< 0.001
No	938	93.76	65	6.24
Yes	102	80.25	18	19.75
Future 1 month Risk of COVID-19 Infection					11.60	0.03
Never	706	93.96	39	6.044
50/50	217	87.44	31	12.56
Likely certain	90.85	33	8	9.15

*Only significant variables are reported in the table above

- The variables included in the Chi- squared test were age, gender, ethnicity, education, employment, marital status, income, PHQ-9, GAD-7, DASS, COVID-19 related stressors, Exposure to COVID-19 infection, Chronic conditions, Current perceived and future 1 month risk of COVID-19 infection.

Table 2.

Final logistic regression model of significant correlates of Insomnia

Correlates	Odds Ratio	P value	95% Confidence Interval
Depression	9.79	< 0.001	3.59	26.67
Anxiety	5.73	< 0.001	2.09	15.72
COVID-19 Related Stressors
Financial loss	2.91	0.01	1.27	6.69
Chronic Conditions
Asthma	4.29	< 0.001	1.89	9.72
Backache	3.53	< 0.001	1.62	7.70

Discussion

According to the current cross-sectional study conducted during the early phase of COVID-19 pandemic, prevalence of insomnia was noted to be 7.4% among the general population of Singapore. Insomnia was seen to be associated with psychological distress due to depression and anxiety. Apart from mental health conditions, correlates observed for insomnia were presence of underlying chronic health conditions - asthma and backache, and financial loss as a source of stress.

The general population across the globe had an increase in the prevalence of sleep problems, especially insomnia, as a result of the COVID-19 pandemic. The pooled prevalence rate of sleep problems and poor sleep quality calculated by a various meta-analyses ranged from 26 to 36.7% [48]. Prior to the outbreak of COVID-19 pandemic period, 27.6% of Singapore residents reported having poor sleep quality based on the Pittsburgh sleep quality index [49] whereas prevalence of severe insomnia was noted to be 15.3% [50]. The prevalence of insomnia during the COVID–19 outbreak inception was observed to range from 2.3 to 76.7% from the various population-based studies conducted in Bangladesh, Libya, and China [22, 51, 52]. However, the 7.4% prevalence of insomnia observed in the current study, is lower than those reported by most other studies during the COVID-19 pandemic. This can be attributed to differences in the study methodology, implementation time, assessment tools and different cut off scores used for assessments as well as the way assessment of insomnia was made.

The current study noted insomnia to be significantly associated with psychological distress. During COVID-19 outbreak, people experienced disruption to normal life activities, fear of infection due to the high risk of contagion linked with COVID-19, side effects of vaccination, social alienation, lack of availability of daily necessities, financial loss, job uncertainty etc [51, 52]. Such stressors are associated with detrimental psychological effects, and elevated stress, anxiety, and depression [52, 53] causing sleep problems [54], thus indicating the strong link between the neural pathways that control sleep and those controlling mood and essential brain functions [55]. Increased screen time due to long work hours, trying to stay updated with COVID-19 related news or higher consumption of digital entertainment in leisure time may impair melatonin secretion resulting in irregular sleep patterns and circadian misalignment. Disrupted circadian rhythm may cause higher dream recall frequency, a known precursor for poor sleep maintenance and insomnia [56, 57].

Financial loss or finance related stress due to retrenchment, pay cut or other unfruitful work-related changes may lead to increase in socio-economic stress among the population and can adversely affect people’s well-being and attitudes [58]. As per the current study findings, insomnia was seen to be associated with financial loss as a source of stress. Worry due to loss of work and decreased household income may give rise to sleep disturbances and insomnia. The possible explanation for this being that the reduced income may deteriorate an individual’s standard of living and inability to meet societal expectations might make them feel like a failure. Thus, disturbances at socio-economic, physical, and psychological level are seen to have significant impact on sleep contributing to distress and vice versa.

Infectious disease experts worldwide have suggested that individuals with pre-existing chronic health conditions or co-morbidities such as asthma, diabetes, hypertension etc. are more likely to contract COVID-19 disease and once infected, the disease progression is rapid with severe symptoms leading to worse prognosis, often fatality. Approximately, 34.6% of patients in the age group of 18 to 49 years, seeking treatment for COVID-19 infection had an underlying chronic lung disease, such as asthma [59, 60]. Individuals with asthma are at high risk from getting infected with the virus due to its affinity for their respiratory tract, leading to increase in frequency of asthma attacks, pneumonia, and acute respiratory distress [61]]. Our finding that respondents diagnosed with asthma were more likely to be associated with insomnia can be attributed to the worse prognosis and fear of death, perceived by these respondents which may lead to them getting stressed, and worried. Including this, the thought of financial burden that they may have to bear in future for the treatment of COVID-19 may cause stress and fear which can disrupt their sleep leading to insomnia. Furthermore, the worry and concern about getting timely medical care, if needed, due to surge in the number of positive cases but insufficient medical resources, may have also caused insomnia.

Prior research has highlighted the existence of bidirectional causal relationship between insomnia and backache [61]. Insomnia was seen to be associated with backache in the current study sample as well. One of the explanations for this is the association of lifestyle factors such as underlying chronic health conditions, sedentary jobs, low levels of physical activity etc [62]. During COVID-19 pandemic, the “circuit breaker” (i.e. partial lockdown), work from home, flexible work hours, social distancing etc. disrupted the daily routine of people. This led to long hours of online working, by sitting at one place in the home without any ergonomic supports, lack of physical activity and decreased socialising, in contrast to pre-Covid times, where people went out to travel to workplace and interacted with peers and colleagues.

Lack of physical activity/ exercise leads to stiffness and increase tension in the body muscles that may cause a decrease in neurotransmitters in the body [62–64]. Dopaminergic abnormality due to low levels of neurotransmitters may alter perception of pain modulation by decreasing the analgesic effect, which contributes to increased pain intensity, low pain threshold causing pain symptoms like backache [65]. Low dopamine levels are also seen to affect the quality of sleep. Thus, dopaminergic abnormality may act as a mediating factor in the link between insomnia and back ache [65, 66]. Additionally, the experience of chronic tension, stress, restlessness from facing various socio-economic challenges can activate the sympathetic nervous system which increases the secretion of norepinephrine, a known risk factor for pain [52]. Continuous arousal of sympathetic nervous system can lead to rise in the concentration levels of pro-inflammatory cytokines that are seen to be associated with inflammation, poor immunity and non –restorative sleep, a type of insomnia [65, 67].

Study limitations and strengths

The present study has some limitations that need to be noted. First, causality cannot be ascertained through the current cross-sectional study design. Further investigations are needed to ascertain the long-term effects of COVID-19 pandemic on the population. Respondents who did not agree to participate in the survey may be suffering from insomnia and psychological problems, hence more inclusive data may be needed to critically comment on the true prevalence of insomnia and its associations. Other limitation is that previous history of COVID-19 infection and effects of long COVID-19 are notable risk factors for insomnia, but this information was not collected in the current study. Thus, longitudinal design for future research would provide clear insights towards such temporal associations and self-report along with objective measures would enhance better identification of insomnia and sleep problems during pandemics. The administration of the survey was done online via Zoom by interviewers and hence there is a possibility of recall bias and social desirability bias may have affected the study findings. Nevertheless, despite these limitations the current study is the first one to investigate the prevalence and associations of insomnia among general population of Singapore during the first wave of the COVID-19 pandemic.

Conclusion and implications

The current study found the prevalence of insomnia to be 7.4% which was associated with psychological distress among Singapore residents. One of the key study implications is the need to develop of accessible, scalable interventions, such as online mental health support programs, mindfulness and relaxation resources, and educational campaigns on managing sleep and stress. The study findings can be utilised to design effective targeted interventions like cognitive behavioural therapy, therapist assisted relaxation and meditation programs to improve sleep and reduce psychological distress during pandemics and other stressful periods. These interventions can be delivered via smartphone applications enabling easy access, delivery, and utilization by the vulnerable groups. Maintenance of sleep diary on a weekly basis by patients must be incorporated in the insomnia screening regime, wherein documentation of time asleep, and wakeup, number of times wake up, caffeine, alcohol consumption etc. can be done. This can be shared remotely with the clinical team during tele-consultation and further line of treatment during such crisis periods can be planned. The clinicians can encourage the participants to take the actigraphy test that can be easily conducted at home, where in the sensor is worn on wrist which monitors sleep and wakefulness patterns depending on which further treatment can be planned. People must be made aware and educated about the importance of regulating their biological sleep-wake cycles and behavioural rhythms, which can yield significant health benefits. In addition to this, the current study highlights the need for enhanced preparedness strategies for future pandemics, particularly in addressing mental health impacts, needs assessment and public health agencies can prioritize resources that address both mental wellbeing and sleep hygiene during crisis. Overall, these strategies would not only help people maintain better mental health and sleep quality during a pandemic but also build resilience, enhancing society’s ability to cope with future crises.

Author contributions

PS wrote the manuscript, interpretated study findings and created the tables. MS conceived the study, wrote the protocol, and critically reviewed the article. EA analysed the data and assisted in the interpretation of the study findings. BYC assisted with data management for the study. All other co-authors- FD, YJZ, SS, ShS contributed to the article by providing comments and approved the submitted version.

Funding

The funding for the study was made available by the Temasek Foundation (Singapore), National center of infectious diseases and Ministry of health (Singapore).

Data availability

The research data supporting the findings of the study are included in the manuscript.

Declarations

Ethics and consent to participate

Ethics approval (DSRB 2020/00462) was obtained from the Domain Specific Review Board of the National Healthcare Group, Singapore. The current research study involving human participants is performed in accordance with the declaration of Helsinki. The ethical approval for the study was obtained from National Healthcare Group Domain Specific Review Board. All the participants completed the informed consent prior to the survey and all participants were provided with a copy of the consent online or in person.

Consent for publication

Not applicable.

Competing interests

None.