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Review

Challenges and Implications of the COVID-19 Pandemic on Mental Health: A Systematic Review

by
Abdullahi Rabiu Abubakar
1,
Maryam Abba Tor
2,
Joyce Ogidigo
3,
Ibrahim Haruna Sani
4,
Adekunle Babajide Rowaiye
3,
Mansur Aliyu Ramalan
1,
Sani Yahaya Najib
5,
Ahmed Danbala
6,
Fatima Adamu
7,
Adnan Abdullah
8,
Mohammed Irfan
9,
Santosh Kumar
10,
Ayukafangha Etando
11,
Sayeeda Rahman
12,
Susmita Sinha
13 and
Mainul Haque
14,*
1
Department of Pharmacology and Therapeutics, Faculty of Pharmaceutical Sciences, Bayero University, Kano-700233, Kano PMB 3452, Nigeria
2
Department of Health and Biosciences, University of East London, University Way, London E16 2RD, UK
3
National Biotechnology Development Agency, Abuja 09004, Nigeria
4
Department of Clinical Pharmacology and Therapeutics, College of Health Sciences, Yusuf Maitama Sule University, Kofar Kansakali-700282, Kano PMB 3220, Nigeria
5
Department of Pharmaceutical and Medicinal Chemistry, Bayero University, Kano 700233, Nigeria
6
Department of Pharmacology and Toxicology, Faculty of Pharmaceutical Sciences, Kaduna State University, Kaduna 800283, Nigeria
7
Department of Community Medicine, Aminu Kano Teaching Hospital, Kano 700233, Nigeria
8
Unit of Occupational Medicine, Faculty of Medicine and Defence Health, Universiti Pertahanan Nasional Malaysia (National Defence University of Malaysia), Kuala Lumpur 57000, Malaysia
9
Instituto Odontologico das Américas (IOA-Pelotas), 1399—Centro, Pelotas 96020-360, RS, Brazil
10
Department of Periodontology and Implantology, Karnavati School of Dentistry, Karnavati University, 907/A, Uvarsad, Gandhinagar 382422, Gujarat, India
11
Department of Medical Laboratory Sciences, Faculty of Health Sciences, Eswatini Medical Christian University, P.O. Box A624, Swazi Plaza Mbabane, Mbabane H101, Hhohho, Eswatini
12
Department of Pharmacology and Public Health, School of Medicine, American University of Integrative Sciences (AUIS), Bridgetown BB 11114, Barbados
13
Department of Physiology, Khulna City Medical College and Hospital, 33 KDA Avenue, Hotel Royal Mor, Khulna Sadar, Khulna 9100, Bangladesh
14
Unit of Pharmacology, Faculty of Medicine and Defence Health, Universiti Pertahanan Nasional Malaysia (National Defence University of Malaysia), Kuala Lumpur 57000, Malaysia
 
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Author to whom correspondence should be addressed.
Psych 2022, 4(3), 435-464; https://doi.org/10.3390/psych4030035
Submission received: 19 June 2022 / Revised: 27 July 2022 / Accepted: 28 July 2022 / Published: 1 August 2022
(This article belongs to the Special Issue Feature Paper Collection in Contemporary Mental Health Illnesses and Brain Disorders (MHBD))
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Abstract

:
The measures put in place to contain the rapid spread of COVID-19 infection, such as quarantine, self-isolation, and lockdown, were supportive but have significantly affected the mental wellbeing of individuals. The primary goal of this study was to review the impact of COVID-19 on mental health. An intensive literature search was conducted using PsycINFO, PsyciatryOnline, PubMed, and the China National Knowledge Infrastructure (CNKI) databases. Articles published between January 2020 and June 2022 were retrieved and appraised. Reviews and retrospective studies were excluded. One hundred and twenty-two (122) relevant articles that fulfilled the inclusion criteria were finally selected. A high prevalence of anxiety, depression, insomnia, and post-traumatic stress disorders was reported. Alcohol and substance abuse, domestic violence, stigmatization, and suicidal tendencies have all been identified as direct consequences of lockdown. The eminent risk factors for mental health disorders identified during COVID-19 include fear of infection, history of mental illness, poor financial status, female gender, and alcohol drinking. The protective factors for mental health include higher income levels, public awareness, psychological counseling, social and government support. Overall, the COVID-19 pandemic has caused a number of mental disorders in addition to economic hardship. This strongly suggests the need to monitor the long-term impact of the COVID-19 pandemic on mental health.

1. Introduction

The severe acute respiratory syndrome caused by coronavirus 2 (SARS-CoV-2) was first discovered in late 2019 in Hubei Province, Wuhan, China. The infection spread rapidly across the globe, and on March 11, 2020 was named the COVID-19 pandemic by the World Health Organization (WHO) [1,2,3]. The SARS-CoV-2 and the earlier SARS-CoV-1 are both zoonotic viruses, and evidence suggests that about half of zoonotic viruses are neurotropic because they invade the central nervous system. The neurotropic viruses infect brainstem nuclei, disrupting the regular rhythms and homeostatic control of respiration. During SARS-CoV-1 in 2003 and Middle East Respiratory Syndrome in 2012, many patients exhibited neurotoxic symptoms, leading to neurological and mental disorders [4,5,6,7,8]. However, scientists have yet to establish whether SARS-CoV-2 infection in the brain, in addition to lockdown, causes neurodegenerative or mental disorders. Therefore, there is a need to monitor the long-term impact of SARS-CoV-2 infection in the brain [4,5,6,7,8,9]. In general, the neurological symptoms of viral infection in the central nervous system (CNS) include delirium, dizziness, loss of smell and taste, headache, loss of consciousness, generalized body weakness, muscle pain, and cerebrovascular complications, Figure 1 [4,5].
The SARS-CoV-2 infection has undoubtedly caused unprecedented morbidity and mortality worldwide. As a result, WHO and countries strategized suitable countermeasures to curb the fast spread of the SARS-CoV-2 infection. These include travel restrictions and the closure of public places such as markets, schools, train stations, airports, seaports, etc. Others are physical distancing, self-isolation, use of facemasks, and hygienic practices like frequent hand washing and hand sanitizer [1,3,9]. Indisputably, these have led to the social and economic shutdown which is very detrimental to the individual’s mental health. Several factors were responsible for the association between the COVID-19 pandemic and mental illness. These include anger, hopelessness, sleepless nights, loneliness, and a significant increase in house chores in the presence of everyone being at home [1,3,9,10]. Mental disorders are highly prevalent and are one of the most neglected diseases worldwide. Common examples of mental illnesses include stress, insomnia, anxiety, depression, and post-traumatic stress disorders (PTSD); see Figure 2. These mental disorders are frequently associated with substance use, and in some cases suicidal tendencies [1,3,6,9,10,11,12,13]. Notably, a number of recent reviews and meta-analyses have reported a high prevalence of mental disorders [14,15,16,17,18,19,20,21].
Studies involving the CNS have reported neurological symptoms of COVID-19 infection with different levels of severity. Butowt et al. reported anosmia and ageusia, indicating that the infection has invaded the neurons [22]. Delirium and post-infectious Guillain-Barre syndrome (GBS) were identified as late symptoms [23,24]. Sabel et al. revealed that post-coverage cognitive deficits were also common in some cases [25]. Cao et al. observed that the pro-inflammatory cytokines directly affect the brain, and later thrombogenesis may cause stroke [26]. The overall effect of COVID-19 pandemic on the brain suggests that the virus may produce mental disorders in the long run. The SARS-CoV-2 virus directly attaches to the angiotensin-converting enzyme (ACE) receptor from where it enters a cell and replicates. The host cells then release a suppressed T-cell implying a decreased personal immunity and consequently leading to the CNS invasion [27]. Remarkably, SARS-CoV-2 viruses directly affect sympathetic activity, which decreases serotonin and dopamine concentrations and causes stress [28]. Accordingly, stress directly stimulates the pituitary gland and causes the release of corticotrophin-releasing hormone (CRH) and adrenocorticotropic hormone (ACTH), leading to increased cortisol and vulnerability to further infection [10]. The combined effect of these physiological changes will ultimately cause mental disorders. This study was carried out to investigate the prevalence of mental disorders caused by lockdown, movement restriction, alcohol and substance use.

2. Objectives of Study

The first objective of this study is to review published articles on mental disorders due to the COVID-19 pandemic. The second objective is to establish the most commonly reported mental disorders. The third is to establish risk factors for developing mental disorders. The last objective is to establish protective factors for mental disorders.

3. Materials and Methods

3.1. Search Strategy

Online searches were conducted according to the PRISMA guidelines (Prisma-p, 2015) (Moher et al., 2015) [29]. The first two authors [ARA & MAT] conducted the initial electronic searches using four scientific literature databases, including PsycINFO, PsyciatryOnline, PubMed, and China National Knowledge Infrastructure (CNKI) to obtain the relevant articles. The search terms used include ‘COVID-19 pandemic’, ‘SARS-CoV-2’, ‘mental health’, ‘mental disorders’, ‘psychological disturbance’, ‘substance use’, ‘incidence of suicide’, ‘lockdown’, ‘quarantine’, ‘self-isolation’, ‘stress’, ‘anxiety’, ‘depression’, ‘PTSD’, ‘insomnia’, ‘worry’, ‘fear’, ‘obsessive-compulsive disorder’, and ‘eating disorder’.

3.2. Study Selection

The authors screened the titles and abstracts of the relevant articles retrieved. In the case of uncertainty, full texts were reviewed. Finally, all authors read the full texts of the eligible studies individually and selected the number of articles for the final review. A manual search of the reference sections of the suitable papers was conducted to identify studies not found through the database searches. This review included preprinted articles where necessary because research on the COVID-19 pandemic is a novel area of study. The quality of the articles retrieved were examined using the Newcastle Ottawa Scale except for the preprinted articles [30,31]. The quality of the pre-printed manuscripts was assessed based on their study design, the instrument used, the sample size, and the track record of the authors. In the course of this review, certain terms were used interchangeably, such as ‘sleep disturbance’ and ‘insomnia’; ‘stress’ and ‘distress’; ‘psychological distress’ and ‘psychological disturbances’; ‘post-traumatic stress disorders’ and ‘post-traumatic and related disorders’. The article retrieval, screening, and inclusion flow chart is shown in Figure 3 [32,33,34,35,36,37,38].

3.3. Inclusion and Exclusion Criteria

Inclusion Criteria: i. Original studies. ii. Studies published between January 2020 and June 2022. iii. Quantitative studies. iv. Studies published in the English language. Exclusion Criteria: i. Retrospective studies. ii. Studies that didn’t focus on the prevalence of mental health. iii. Review articles.

3.4. Data Synthesis

Initially, 206 articles were independently retrieved from the selected databases by the first two authors (Figure 3). In addition, 39 more articles were obtained through the manual search by reading the reference sections of the first sets of articles, making a total of 245 articles. After cross-checking the retrieved articles, a total of 53 duplicate articles were screened and removed. An additional 28 articles were excluded because they don’t have full text. Subsequently, 42 articles were excluded because they were not surveys, had a faulty method, or had poor study design. Some of the excluded studies were conducted either through verbal interviews or focused group discussion; others did not report the prevalence of mental disorders, and only abstracts were available among the rest. Finally, 122 published studies that met the inclusion criteria were reviewed (Table 1). Studies were grouped under the most relevant subheadings; however, there was an overlap in some studies (Table 2).

4. Results

In this review, a number of surveys outcome were summarized, including the prevalence, risks, and protective factors for mental health disorders (Table 1). A survey conducted in China reported an increased incidence of anxiety (45%), depression (50%), and insomnia (34%) [32]. Another longitudinal study indicated an increased level of anxiety (53%), depression (56%), and insomnia (79%) [33]. A study conducted in Australia reported a high rate of anxiety (40%), psychological distress (48%), and insomnia (41%) [34]. An online survey conducted in Malaysia also revealed a high level of anxiety (55%), depression (59%), and stress (31%) [35]. A study conducted in Iran indicated an increased incidence of anxiety (43%), depression (45%), and stress 35% [36]. Another study from Canada accounted for high level of anxiety (52%) [3]. Nonetheless, a quantitative online survey conducted in Germany reported a low incidence of anxiety (11%), depression (24%), and PTSD 5%) [37]. Another longitudinal survey from Spain also accounted for a moderate prevalence of anxiety (21%), depression (34%), and stress (28%) [38]. This is in line with other reviews that reported a global survey conducted among 31 nations [11,148].
During this study, various articles reviewed reported a wide range of mental disorders associated with the COVID-19 pandemic. Anxiety was the most commonly reported disorder by 35.9% of the articles reviewed. This indicated that anxiety was the most frequently encountered mental disorder during the COVID-19 pandemic. Depression was reported by 29.7% of the studies reviewed, making it the second most documented mental disorder. Stress is another mental disorder moderately revealed by 12.5% of the publications reviewed. However, PSTD, psychological disturbance, and insomnia were reported by only 6.3%, 5.5%, and 5.0% of the articles published, respectively. Generally, low reports of 2.3% documented worry, and only 2% of the articles reviewed reported the incidence of fear. Lastly, both OCD and eating disorders were reported by only 0.4% of the articles reviewed, respectively. This made them rare mental disorders during the COVID-19 pandemic (Table 2). This result reflects recent findings from other studies [14,15,16,17,18,19,20,21].

5. Discussion

The public health measures taken during the COVID-19 pandemic to curb the spread of SARS-CoV-2 infection such as quarantine, self-isolation, and total lockdown have caused detrimental effects on mental health. This review focused on the states mostly affected by the SARS-CoV-2 infection across the globe. The novelty in this research is to find the prevalence of mental disorders and to see if the prevalence is related to lockdown or high incidence of infection. Countries strongly affected by the COVID-19 pandemic include the USA, India, Brazil, France, the UK, Russia, Turkey, Italy, Spain, Germany, Argentina, and Iran. These countries recorded more COVID-19 cases and fatalities than others [150]. Several countries such as China, Australia, Malaysia, Iran, Germany, Spain, and Canada adopted total lockdown as a countermeasure which strongly affected their mental well-being. Generally, this review reported a high prevalence of wide ranges of mental disorders. These include anxiety, depression, stress, PSTD, psychological disturbance, insomnia, worry, fear, OCD, and eating disorders. Additionally, a number of negative consequences of total lockdowns, such as suicidal tendencies, alcohol and substance use, and stigmatization were documented. This has made mental disorders one of the areas of global public health concern. Thus, the outcome is in line with a recent meta-analysis comprising 146,139 subjects worldwide which established a high prevalence of anxiety, depression, insomnia, and PTSD [15]. In addition, a recent report by the Organization for the Economic Cooperation and Development (OECD) that mapped out the strategy to improve public health also reported a high prevalence of anxiety and depression ranging between 5–50% and 3–36.8%, respectively [9]. Several studies carried out, however, have found a moderate prevalence of anxiety and depression [41,45,57,58,59]. Furthermore, a number of articles documented a very low prevalence of anxiety and depression [57,60,75,77,119,140,149]. Notably, separate studies carried out to describe the mental health of frontline workers reported a high rate of anxiety, depression, and PTSD [11,17,151,152]. The causes identified include shortage of PPE, inadequate testing kits, increased hospital duration, increased workload, lack of social and moral support, fear of infection, and stigmatization. Overall, mental health disorders have led to poor work performance, absconding from duty, job loss, and even suicide [6,9,11,13,15,17,152]. These deleterious outcomes will have a negative impact on people’s quality of life, and by extension the global economy. Consequently, there is a need for a renewed effort by the United Nations, WHO, and individual nations to address the menace of mental disorders by increasing public welfare. Notably, addressing the high prevalence of mental disorders will improve individuals’ quality of life, reduce the burden of public health and prevent or minimize the incidence of suicide, alcohol and substance use.
The prevalence of stress varies from high to moderate to low incidences. In this review, an extremely high prevalence of stress was reported [32,47,88]. Also, a number of longitudinal surveys revealed a moderately high incidence of stress [36,72,80,90,94,95,96]. However, the outcome of various online studies on mental health illnesses reported a moderate prevalence of stress, while several other studies accounted for a very low prevalence of stress [54,57,58,64,67,80,84,92,119]. Although stress is widely reported, a higher percentage might have overlapped as one of the general symptoms of other mental disorders. On this note, governments and other relevant stakeholders need to make a quick move to address increased hardships through the distribution of palliatives and giving incentives to people that have lost their jobs.
The media in general, have played vital role in spreading information and misinformation about the COVID-19 pandemic. Notable memories of various scenes of bloody pneumonia witnessed in Wuhan, China; mass graves repeatedly broadcast in Italy, Brazil, and Argentina; and the cremation of dead bodies in India resulted in horrific thoughts and flashbacks across the globe known as PTSD. In line with this, several longitudinal surveys reported moderate incidences of PTSD [42,96,97,99,111,138,139]. Nonetheless, a number of articles reviewed reported only a low incidence of PTSD [33,37,49,82,120,140,143]. Insomnia is one of the most acute symptoms of all mental disorders. Consequently, a report of an extremely high incidence of of insomnia was documented [65]. In addition, several others surveys revealed moderate incidences of insomnia [11,13,34,43,59,61,62,116]. Whereas few other longitudinal studies found a low prevalence of insomnia [75,84,96,108]. The high prevalence of insomnia has led to the misuse of drugs and substance abuse in an attempt to induce sleep. There was also hype about the efficacy of some medicines, such as chloroquine and hydroxychloroquine [2]. In general, there was a dire need to strengthen the guidelines and regulations guiding drug prescriptions and dispensing to counter panic buying by the public. The government also needs to regulate the contents broadcast by the media houses and impose sanctions where necessary to curb the spread of unnecessary panic and fake news.
Confining everyone indoors to enforce lockdown during the early days of COVID-19 has resulted in indiscriminate alcohol and other substance use to alleviate boredom. Consequently, in this review, a survey reported a high incidence of alcohol and substance use [121]. In addition, a number of surveys have found moderate incidences of substance use [138,139]. COVID-19 pandemic is a global phenomenon and has affected almost every country, which made it known to almost every community across the globe. Despite this, a high incidence of stigmatization was reported [36]. Although only a few studies investigated the rate of suicide thought as a direct consequence of total lockdown and loss of freedom, most of the articles reviewed reported only low prevalence of suicide [3,59,114,134,138,139]. Generally, there is a need to further investigate the incidences of suicide, possibly due to agony, hopelessness, and despair caused by grief, bereavement and domestic violence linked to the COVID-19 pandemic.
In the course of this review, several risk factors for developing mental illness were identified. These include fear of infection, history of mental illness, poor financial status, female gender, alcohol drinking, younger age, lack of experience, comorbidities, and physical disability [3,6,11,12,32,33,35,36,37,80,125]. Accordingly, the OECD advocated for the need to identify and alleviate these risk factors [9,153,154]. In addition, the risk factors should be studied extensively and included in the strategic plan in preparation for the future pandemic.
This study also identified several protective factors against developing mental disorders, including higher income, public awareness, psychological counseling, social support, and government support [3,6,11,12,32,33,35,36,37,80,125]. There is strong advocacy to support vulnerable groups such as young adults, females, and elderly people regarding education, employment, and mental health support [9,153,154]. Governments and stakeholders must prioritize these protective factors when providing emergency relief and intervention during COVID-19 and future pandemics. Several coping strategies were identified and assessed for their effectiveness in reducing the global burden of mental health during COVID-19. These include awareness of the disease, indoor physical activities, online games, music concerts, online classes, and lectures [1,6,9,15,153,154].
Furthermore, various government interventions tried during the previous pandemics were identified and evaluated to see if they could be repurposed. In addition, various preventive measures aimed at reducing the negative impacts of horrible news of COVID-19 disease via traditional and social media were documented. This will guide the general public and media houses in identifying correct sources of information to avoid fake news. Also, it will reduce the broadcast of horrible hospital scenes and terrifying burial grounds. Overall, these will help significantly to prevent and reduce mental disorders caused by the COVID-19 pandemic [1,6,9,15,153,154].

6. Conclusions

COVID-19 pandemic, has revolutionized the global approach to healthcare and social issues. Lockdown and movement restrictions imposed by various governments have significantly affected the mental well-being of individuals. During the COVID-19 pandemic, anxiety was the most prevalent mental disorder, followed by depression, stress, and insomnia. In addition, a moderate incidence of psychological disturbance and PTSD was documented. Alcohol and substance use, domestic violence, stigmatization, and suicidal tendencies have all been identified as direct consequences of lockdown. These problems have significantly affected individuals’ well-being and shut down the global economy. The eminent risk factors for mental health disorders identified include fear of infection, history of mental illness, poor financial status, female gender, and alcohol drinking. The documented protective factors were the higher-income level, public awareness, psychological counseling, social and government support. The primary focus of the government and other policymakers should utilize these protective factors in providing palliatives and incentives to cushion the economic impact of the lockdown. Overall, there is a need to monitor the long-term impact of COVID-19 pandemic on mental health during and after the COVID-19 pandemic.

7. Limitations of this Research

i. Several studies focused on specific people like healthcare workers and parents with children aged 18 years instead of the general population. ii. The selected articles’ methodology includes self-report questionnaires or an instrument with cut-off points for stress, anxiety, or depression scores. Hence not homogenous. iii. The articles did not assess the reported mental disorders using a definitive psychiatric diagnosis by a specialist.

8. Article Highlights

I. The review highlighted the origin of the COVID-19 pandemic and the virulent nature of the SARS-CoV-2 virus. II. The COVID-19 pandemic has ravaged the global and individual economies, skyrocketing the global poverty index. III. The high prevalence of anxiety, depression, insomnia, and PTSD were reported during the COVID-19 pandemic, which calls for the urgent need for action. IV. Major risk factors for developing mental disorders include fear of infection, history of mental illness, female gender, younger age, comorbidities, and physical disability. V. Mental health interventions during the COVID-19 pandemic should focus on effective risk communication, continuous testing and assessment, unique approaches for vulnerable groups, community partnerships, online health applications, government policies, public welfare, and funding.

Author Contributions

A.R.A. and M.A.T. designed the study, searched for all the relevant articles, printed them, and screened the article for their eligibility based on inclusion and exclusion criteria. J.O., I.H.S., A.B.R., M.A.R., S.Y.N., A.A., A.D. and F.A. reviewed the articles, and constructed Table 1 and Table 2 and wrote the discussion section. A.A., M.I., S.K. and A.E. reviewed and wrote the literature and all the references. A.R.A., M.A.T., S.R., S.S. and M.H. developed the research idea, wrote an abstract, and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

No applicated.

Informed Consent Statement

No applicated.

Data Availability Statement

Data is contained within the article.

Acknowledgments

We are grateful to the Department of Pharmacology and Therapeutics, Faculty of Pharmaceutical Sciences, Bayero University, Kano, Nigeria.

Conflicts of Interest

The authors declared no conflict of interest.

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Figure 1. Some neurological signs of COVID-19 infection.
Figure 1. Some neurological signs of COVID-19 infection.
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Figure 2. Mental disorders and impacts of lockdown associated with COVID-19.
Figure 2. Mental disorders and impacts of lockdown associated with COVID-19.
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Figure 3. Articles retrieval and screening flowchart.
Figure 3. Articles retrieval and screening flowchart.
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Table
Table 1. Surveys Outcomes Showing the Prevalence, Risks, and Protective Factors to Mental Health Disorders.
Table 1. Surveys Outcomes Showing the Prevalence, Risks, and Protective Factors to Mental Health Disorders.
S/NStudyCountryStudy PopulationFindings
Prevalence (%)Risk FactorsProtective Factors
1.Dawel et al., 2020 [39]Australia1296i. Generalized Anxiety Disorder (16%)
ii. Major Depressive Disorder (20%)		i. Financial distress
ii. Loss of job		Government support
2.Li et al., 2021 [34]Australia760i. Anxiety (40%)
ii. Psychological distress (48%)
iii. Sleep disturbance (41%)		History of mental healthi. Mental health support
ii Government support
3.Wilson et al., 2022 [40]Australia555i. Anxiety/Depression (mild, 85%)
ii. Alcohol Use (Moderate, 80%)		i. Unemployment
ii. Financial difficulties
iii. Reduced accessibility to hobbies		i. Avoid distress,
ii. Do things differently
4.Simon et al., 2021 [41]Austria560i. Anxiety (16%)
ii. Depression (11%)		i. History of mental
health
ii. Wellbeing reduction		i. Mental health support
ii. Social support
5.Jassim et al., 2021 [42]Bahrain502i. Depression (40%)
ii. PTSD (20%)
iii. Perceived stigma (53%)		i. Female gender
ii. History of mental health issues
iii. Young adult		Psychological interventions
6.Islam et al., 2021 [43]Bangladesh975i. Anxiety (5%)
ii. Poor sleep (44–55%)
iii. Fear (59%)		i. Female gender
ii. Fear of infection
iii. Poor income
iv. Poor physical illness		i. Online counseling
ii. Government support
7.Das et al., 2021 [44]Bangladesh672i. Anxiety (64%)
ii. Depression (38%)
iii. Insomnia (73%)		i. Female sex
ii. Unemployment
iii. Being a student
iv. Obesity
v. Living without a family		Supportive programs
8.Islam et al., 2020 [45]Bangladesh475i. Anxiety (18%)
ii. Depression (15%)		i. Living with families
ii. Being a student		i. Online classes
ii. Government support
9.Mehareen et al., 2021 [46]Bangladesh333i. Anxiety (Public University 54%, Private University 33%)
ii. Depression (Public university 59%, Private University 31%)		i. Female gender
ii. Level of study
iii. Nuclear families		i. Psychological interventions
ii. Government support
10.Lopes et al., 2021 [47]Brazil1224i. Anxiety (53%)
ii. Depression (61%)
iii. Stress (58%)		i. Female gender
ii. Younger age
iii. Having a chronic diseases		i. Educational actions
ii. Increasing psychological wellbeing
11.Gadermann et al., 2021 [3]Canada3000i. Deteriorated mental health (44.3%)
ii. Anxiety and worry (52%)
iii. Suicidal thoughts (8%)		i. Having children <18 years
ii. Alcohol consumption		i. Free digital technologies
ii Government supports
12.Maximova et al., 2021 [48]Canada1095i. Boredom (Girls 48%, Boys 36%)
ii. Trouble paying attention (Girls 36%, Boys 39%)		 Playing video games
13.Song et al., 2020 [49]China14,825i. Depression (25%)
ii. PTSD (9%)		i. Male gender
ii. Old age
iii. Working in Hubei province
iv. Low social support		i. Psychological interventions
ii. Mental health promotion
14.Cao et al., 2020 [50]China7143i. Severe Anxiety (1%)
ii. Moderate Anxiety (3%)
iii. Mild Anxiety (21%)		i. Having infected acquaintances
ii. Worry about economy
iii. Worry about school 		i. Living in a city
ii. Higher level of income
iii. Living with parents
iv. Government support
15.Li et al., 2021b [51]China7090i. Anxiety (19%)
ii. Depression (21%)
iii. Poor self-rated health (10%)		Fear of infection
Work intensity		Improve the working condition
16.Huang et al., 2020 [52]China6261i. Anxiety (Moderate 14%, Severe 5%)
ii. Depression (Moderate 17%, Severe 8%)		i. Being single
ii. People from Hubei province
ii. Infected people 		Psychological intervention
17.Zhu et al., 2020 [53]China5062i. Anxiety (24%)
ii. Depression (14%)
iii. Stress (30%)		i. Female gender
ii. Chronic diseases
iii. Fear of infection
iv. History of mental disorders		i. Psychological support
ii. Government support
18.Liu et al. 2020a [54]China4679i. Anxiety (16%)
ii. Depression (35%)
iii. Psychological distress (16%)		i. Divorce/widow
ii. Younger age
iii. Nurse
iv. Not living with family		psychiatric interventions
19.Ren et al., 2020 [55]China3600i. Anxiety (Mild 19%, Moderate 5%, Severe 1%).
ii. Depression (Mild 17%, Moderate 4%, Severe 1%)		i.Surgical nurses
ii. Divorce/widowed
iii. Care for COVID-19
patients		Mental health support
20.Duan et al., 2020 [56]China3254i. Anxiety (31%)
ii. Depression (22%)		i. Resident in Hubei province
ii. Infected family member
ii. Internet addiction
iii. Old age		I. Psychological interventions
ii. Conducting research
21.Huang et al., 2021 [57]China3113i. Anxiety (13%)
ii. Depression (15%)
iii. Stress (7%)		i. Smoking
ii. Alcohol drinking		i. Family support
ii. Psycho intervention
22.Hou et al., 2020 [58]China3063i. Anxiety (13%)
ii. Depression (14%)
iii. Stress (7%)		i. Female gender
ii. Old age
iii. Unemployment
iv. Exposure to COVID-19 news		i. Limit exposure to social media
ii. Mental health prevention
23.Cai et al., 2020 [59]China2346i. Anxiety (Frontline workers 16%, Non-Frontline workers 7%)
ii. Depression (Frontline workers 14%, Non-Frontline workers 10%)
iii. Insomnia (Frontline workers 47%, Non-Frontline workers 29%)
iv. Suicidal ideation (Frontline workers 12%, Non-Frontline workers 9%)		i. Frontline worker
ii. Working in Wuhan		i. Mental health support
24.Lu et al., 2020a [60]China2299i. Anxiety (Moderate 26%, Severe 3%)
ii. Depression (Mild 12%, Moderate 0.3%)		i. Healthcare workers
ii. Working in ICU		Improving the mental health
25.Que et al., 2020 [61]China2285i. Anxiety 46%,
ii. Depression 45%,
iii. Insomnia 29% 		Front-line
healthcare		i. Timely interventions
ii. Proper information feedback.
26.Zhang et al., 2020a [62]China2182Medical vs. Nonmedical Workers
i. Anxiety (13% vs. 9%)
ii. Depression (12% vs. 10%)
iii. Insomnia (38% vs. 31%)
iv. OCD (5% vs. 2%)		I. Health worker
ii. Organic disease
iii. Living in rural area		Recovery programs
27.Liu et al., 2020b [63]China2031i. Anxiety (18%)
ii. Depression (15%)
iii. Stress (10%)		i. Health worker
ii. Older age
iii. Working in frontline		Psychological
crisis interventions
28.Wang et al., 2020a [64]China1738i. Anxiety (29%)
ii. Depression (17%)
iii. Stress (8%) 		i. Physical symptoms
ii. Low knowledge about the infection		Government Financial support
29.Wang et al., 2020b [65]China1599i. Feel nervous (57%)
ii. Bad dreams (38%)
iii. Emotional disturbances (48%)		i. Unmarried
ii. Younger age
iii. History of the visit to
Wuhan		Psychological interventions
30.Lai et al., 2020 [32]China1257i. Anxiety (45%)
ii. Depression (50%)
iii. Distress (72%)
iv. Insomnia (34%)		i. Female gender
ii. Nurses
iii. Frontline health care workers
iv. Working in Wuhan		i. Mental health intervention
ii. Special attention to women and nurses
31.Guo et al., 2021 [33]China1091i. Anxiety (53%)
ii. Depression (56%)
iii. PTSD (11%)
iv. Insomnia (79%) 		iii. Having higher degrees
iv. Working in Wuhan		Early mental health intervention
32.Kang et al., 2020 [66]China994Mild psychological disturbance (34%)
ii. Moderate psychological disturbance (22%)
iii. Severe psychological disturbance and (6%) 		i. Low access to mental healthcare
ii. Dealing with confirmed cases		Mental health interventions
33.Du et al., 2020 [67]China 687i. Anxiety (30%)
ii. Depression (18%)
iii. Stress (14%)		i. Female gender
ii. Healthcare worker
ii. Medical students		i. Preventive measures
ii. Active
coping strategies
34.Ning et al., 2020 [68]China612i. Anxiety (Neurological nurses (20%, Doctors 13%)
ii. Depression (Neurological nurses 30%, 20%)		i. Female gender
ii. Nurses
iii. Younger age
iv. Junior Health worker		i. Provision of PPE
ii. Psychological assistance.
35.Liang et al., 2020 [69]China584i. Psychological problems (40%)
ii. PTSD (14%)		i. Low level of education
ii. Employment status
iii. Marital status		i. Government support
ii. Psychological counseling
36.Liu et al., 2020c [70]China512i. Mild Anxiety (10%),
ii. Moderate Anxiety (1.4%)
ii. Severe Anxiety (0.8%).		i. Working in Hubei province
ii. Direct
contact treating infected patients		i. Psychological support
ii. Government support
37.Juan et al., 2020 [71]China456i. Anxiety (32%)
ii. Depression (30%)
iii. Stress (43%)
iv. Psychological distress		i. Female gender
ii. Low income
iii. Younger adults
iv. Fear of infecting others		i. Social support
ii. Psychological intervention
38.Zhang et al., 2020b [72]China263Apprehension (52%)Old agei. Family Support
ii. Attention to mental health
39.Liu et al., 2020d [73]China217i. Anxiety (Male 20%, Female 24%),
ii. Depression (Male 30%, Female 39%)		i. Female gender
ii. Living in Hubei Province
ii. Level in school		Effective screening procedures
40.Rodriguez-Hidalgo et al., 2020 [74]Ecuador640i. Anxiety (60%)
ii. Depression (80%)		i. Female gender
ii. Fear of infection		i. Psychological training
ii. Counseling program
41.Deek et al., 2021 [75]Egypt, Lebanon, Libya, Saudi Arabia,
Sudan		2783i. Anxiety (3–8%)
ii. Depression (2–7%)
iii. Insomnia (2–9%)		i. Poverty
ii. Change of Government		Government support
42.Herbert et al., 2021 [76]Egypt, Germany220i. Anxiety (50%)
ii. Depression (52%)
Depressive symptoms (65.5%)		i. Worries about health
ii. Difficulties in identifying feelings
iii. Difficulties in learning behavior 		Psychological interventions
43.Fancourt et al., 2020 [77]England36,520i. Anxiety (Moderate 12%, Severe 10%)
ii. Depression (Moderate 13%, Severe 8%)		i. Female gender
ii. Lower education
iii. Younger adults
iv. Existing mental illness		Mental health support
44.Zaninotto et al., 2021 [78]England5146i. Anxiety (9–11%)
ii. Depression (23–29%)		i. Women
ii. Being Single
iii. Pre-existing health issues
iv. Poor economic status		i. Mental health screening
ii. Psychological support
45.Assefa et al., 2021 [79]Ethiopia710i. Anxiety (35%)
ii. Depression (30%)
iii. Stress (38%)		i. Married
ii. Old age
iii. Low level of education
iv. History of mental disorders		i. Psychological counseling
ii. Coping strategies
46.Girma et al.,2021 [80]Ethiopia610i. Moderate stress (68%)
ii. Severe stress (14%)		i. Large family size
ii. Chronic diseases
iii. Old age		i. Prevention of psychological impacts of COVID-19
ii. Mental health counseling
47.Geweniger et al., 2022 [81]Germany1619i. Children mental health problems (57%)
ii. Parent depression (31%)		i. Low socioeconomic status
ii. Complex chronic disease
iii. Parents with depression		Political measures to help children
48.Schäfer et al., 2020 [82]Germany1591i. Psychopathological symptoms (10%)
ii. PTSD (15%)		i. Younger age
ii. Female gender		Social support
49.Rek et al., 2021 [37]Germany511i. Anxiety (11%)
ii. Depression (24%)
ii. PTSD (5%)
iii. Substance use (1%)
iv. Eating disorder (4%)		i. Political restriction
ii. Existing psychiatric illness
iii. Conspiracy beliefs		Self-assessment
50.Knolle et al., 2021 [83]Germany, UK782i. Psychological symptoms, Germany, UK (25%)
ii. Depression, Germany, UK (20–50%)		i. High consumption of Marijuana ii. Use of social mediai. Being older,
ii. Having a better education
51.Magklara et al., 2020 [84]Greece1232i. Sleep problems (8%)
ii. Stress (6%)		i. Mental health history
ii. Unemployment
iii. Family conflict 		Public health policies
52.Reddy et al., 2020 [85]India 891i. Anxiety (15%)
ii. Depression (22%)
iii. Anxiety and Depression (28%)		i. Being single
ii. Worries regarding school opening
iii. Online teaching		Timely Psychological intervention.
53.Saraswathi et al., 2020 [86]India 217i. Anxiety (33%)
ii. Depression (36%)
iii. Stress (25%)		Direct contact with COVID-19 patientsMental health intervention
54.Zukhra et al., 2021 [87]Indonesia247i. Mild Anxiety (30%)
ii. Moderate Anxiety (5%)
iii. Severe Anxiety (0.4%)		i. Female gender
ii. Younger age
iii. Living in COVID-19 red zone		i. Psychological support
ii. Mental health counseling
55.Sharif Nia et al., 2021 [88]Iran70,180i. Anxiety (Moderate 21%, Severe 59%)
ii. Depression (Mild 18%, Moderate 18%)
iii. Stress (Moderate 59%, Severe 7%)		i. Female gender
ii. Married
iii. Level of education		Psychological interventions
56.Shahriarirad et al., 2021 [12]Iran8591i. Anxiety (20%)
ii. Depression (15%)		i. Female gender
ii. Healthcare worker		i. Older age
ii. Being Married
iii. Getting information from medical journals
57.Azizi et al., 2021 [36]Iran 7626i. Anxiety (43%)
ii. Depression (45%)
iii. Stress (35%)		i. Female gender
ii. Younger age
iii. Physical illness
iv. History of mental disorders		i. Psychological screening
ii. Government support
58.Hassannia et al., 2020 [89]Iran2045i. Anxiety (66%)
ii. Depression (42%)
iii. Stress (35%)		i. Female gender
ii. Younger age
iii. Doctors and nurses
iv. Infected individuals		i. Psychological intervention
ii. Helping vulnerable people
59.Salehian et al., 2021 [90]Iran1910i. Anxiety (40%)
ii. Depression (22%)
iii. PTSD (62%)		i. Women,
ii. Younger age
iii. Divorced/widowed
iv. History of psychiatric disorders		Continuous monitoring of the psychological consequences of corvid-19
60.Mani et al., 2020 [91]Iran922i. Anxiety (19%)
ii. Depression (6%)		i. Old age
ii. Female gender
iii. Lack of trust in Government		Government support
61.Kausar et al., 2021 [92]Iran500i. Anxiety (Mild 11%, Moderate 13%)
ii. Depression (Mild 18%, Moderate 18%)
iii. Stress (Mild 11%, Moderate 4%)		 Counseling services
62.Chen et al., 2021 [93]Iran474i. Anxiety (43%)
ii. Depression (45%)
iii. Stress (35%)		i. Old age
ii. Female gender
iii. Chronic diseases		Social support
63.Mohammadi et al., 2020 [94]Iran462i. Anxiety (General population 96%, COVID-19 patients 98%)
ii. Depression (General population 52%, COVID-19 patients 54%)
iii. Stress (General population 49%, COVID-19 patients 47%)		i. Female gender
ii. Younger age
iii. Comorbidity diseases		Psychological interventions
64.Orgilés et al., 2020 [95]Italy, Spain1114i. Anxiety (28%)
ii. Worry (30%)
iii. Stress (Children 11%, Parents 35%)		Fear of infectionUse of mobile phones and computers
65.Rossi et al., 2020 [96]Italy 18,147i. Anxiety (21%),
ii. Depression (17%)
iii. Stress (22%)
iv. PTSD (37%)
v. Insomnia (7%)		i. Female Gender
ii. Younger age
iii. Quarantine 		Monitoring of the mental health status
66.Davico et al., 2021 [97]Italy2419i. Psychological impact (33%)
ii. PTSD (31%)		i. Fear of infection
ii. Home confinement		Physiological intervention
67.Villani et al., 2021 [98]Italy501i. Anxiety (35%)
ii. Depression (73%)		i. Female gender
ii. Students
iii. Inability to see partner		Physical activity
68.Giusti et al., 2020 [99]Italy330i. Anxiety (31%)
ii. Depression (27%)
iii. Stress (34%)
iv. PTSD (37%) 		i. Female gender,
ii. Being a nurse,
iii. Contact with COVID-19 patients		Monitoring and timely treatment
69.Levkovich and Shinan-Altman, 2021 [100]Israel 1407i. Anxiety and Worry (40%)
ii. High level of fear (20%)		i. Fears of infection
ii. Adjustment to the new reality		Government intervention
70.Basheti et al., 2021 [101]Jordan450i. Anxiety (34%)
ii. Depression (26%)		i. Smoking
ii. Low income 		Government intervention
71.Shah et al., 2021 [11]Kenya433i. Anxiety (44%)
ii. Depression (54%)
iii. Insomnia (41%)		i. Hospital workers
ii. Female gender		i. Government support
ii. Doctors’ welfare
72.Wong et al., 2021 [35]Malaysia1163i. Anxiety (55%)
ii. Depression (59%)
iii. Stress (31%)		i. Young people
ii. Females
iii. Poor financial conditions		i. Psychological counselling
ii. Government support
73.Bahar Moni et al., 2021 [102]Malaysia720i. Moderate psychological distress (62%)
ii. High levels of fear (27%)		i. Alcohol drinking
ii. Fear of infection
iii. Care of COVID-19 patient
iii. Poor financial situation		Behavioral interventions
74.Sundarasen et al., 2020 [103]Malaysia983i. Mild to moderate anxiety (20%)
ii. Severe anxiety (7%)
iii. Extreme anxiety (3%) 		i. Financial constraints
ii. Remote online teaching 		i. Mental health support
ii. Government support
75.Baloch et al., 2021 [104]Malaysia494i. Mild to moderate anxiety (25%)
ii. Severe anxiety (9%)
iii. Extreme anxiety (7%)		i. Online teaching
ii. Uncertainty about their academic performance		Mental health interventions
76.Norhayati et al., 2021 [105]Malaysia306Depressive symptoms (Frontline healthcare 28%, Non-frontline healthcare 38%) Psychological support
77.Chinna et al., 2021 [106]Malaysia,
Saudi Arabia, Pakistan, Bangladesh, China, India, and Indonesia		3679i. Mild to moderate anxiety (22%)
ii. Severe anxiety (14%)		i. Female gender
ii. Substance use		i. Social Support
ii. Government support
78.Cortés-Álvarez et al., 2021 [107]Mexico1105i. Moderate-severe depression (16%)
ii. Moderate-severe anxiety (23%)
iii. Moderate-severe stress (20%)		i. Female gender
ii. Older age
iii. Contact with a confirmed case		i. Hand hygiene
ii. Wearing masks
79.Khanal et al., 2021 [108]Nepal475i. Anxiety (33%)
ii. Insomnia (7%)		i. Nurses
ii. family members with chronic diseases
ii. stigma		i. Monitor the psychological illness
ii. Psychological intervention
80.Khanal et al., 2020 [13]Nepal475i. Anxiety (42)
ii. Depression (38%)
iii. Insomnia (34%)		i. History of mental health problems
ii. Stigma		i. Government support system
ii. Availability of PPE
81.Van der Goot et al., 2021 [109]Netherland259i. Mild Psychological
distress (28–50%)
ii. Moderate Psychological
distress (7–20%)
iii. Severe Psychological
distress(13–30%)		 Psychological support
82.Tobin et al., 2021 [110]Nigeria543i. Anxiety (24%)
ii. Depression (17%)		i. Female gender
ii. Alcohol use
iii. Currently on medication		Psychological support
83.Olaseni et al., 2020 [111]Nigeria502i. Anxiety (49–51%),
ii. Depression (Males 7–12%, Females 5–14%)
iii. Moderate PTSD (Males 18–22%, Females 19–29%)		i. Female gender
ii. Increase in number reported cases		Government support
84.Durowade et al., 2021 [112]Nigeria335Psychological effects (84%) i. Diabetes, asthma, cancers
ii. Contact with a confirmed case		i. Public awareness,
ii. Subsidizing PPEs
iii. Financial stimulus
85.Adewale et al., 2021 [113]Nigeria322i. Severe anxiety (6%)
ii. Severe depression (3%)
iii. Severe psychological impact (20%)		i. Increase in time spent on social media and TV
ii. Decrease in physical activity		i. Psychosocial support
ii. Government support
86.Fadipe et al., 2021 [114]Nigeria160i. Depression (28%)
ii. Anxiety (28%)
iii. Suicidal ideation (4%)		i. Fear of infecting ii. Employment status
iii. History of negative emotion		Nigeria
87.Afolabi, 2020 [115]Nigeria132i. Poor mental wellbeing (55%)
ii. Worries (71%)		Sleeplessnessi. Government support
ii. Social support
88.Khamis et al., 2020 [116]Oman402i. Mild Anxiety 40%
ii. Moderate Anxiety 19%
iii. Severe Anxiety 9%
iv. Poor sleep 39%		i. Care for COVID-19 patients
ii. Being a citizen		Mental health support
89.Hayat et al., 2021 [117]Pakistan1094i. Anxiety (Moderate to Severe 33%)
ii. Depression (Mild 45%, Moderate 12%)		i. Female gender
ii. Old age
iii. Married		i. Psychotherapy
ii. Counselling services
90.Majeed and Ashraf, 2020 [118]Pakistan 63i. Anxiety (60%)
ii. Fear (70%)		i. Uncertainty
ii. Misinformation
iii. Social distancing/isolation 		i. Psychosocial interventions ii. Government support
91.Radwan et al., 2021 [119]Palestine420i. Anxiety (Mild 1.6%, Severe 12%)
ii. Depression (Mild%, Severe 9%)
iii. Stress (Mild 12%, Severe 13%)		i. Female gender
ii. Family poor income
iii. large Family size
iv. Younger age		Mental health support
92.Villarreal-Zegarra et al., 2021 [120]Peru830i. Depression (16%)
ii. Anxiety (12%)
iii. PTSD (15%)		i. Healthcare workers
ii. Fear infection		i. Preventive actions
ii. Surveillance of mental health
93.Stack et al., 2020 [121]Poland36Substance use (17–52%)Availability of substancesGovernment support
94.Karpenko et al., 2020 [122]Russia 352i. Anxiety (30%)
ii. Depression (17)		i. Fear of infection
ii. Self-isolation
iii. Fear of financial problems 		i. Mental health support
ii. Social support
95.Alkhamees et al., 2020 [123]Saudi Arabia1160i. Moderate to severe anxiety (24%)
ii. Moderate to severe depression (28%)
iii. Moderate to severe stress (22%) 		i. Female gender
ii. High-school students
iii. Healthcare workers		Psychological interventions
96.Al-Rahimi et al., 2021 [38]Saudi Arabia1030i. Anxiety (21%)
ii. Worrying thoughts (20%) 		i. Female gender
ii. Lower education
iii. Middle-aged
iv. Divorced or widowed
v. Chronic diseases		Psychological interventions
97.Alyoubi et al., 2021 [124]Saudi Arabia582i. Anxiety (22%)
ii. Depression (25%)
iii. Stress (18%)		i. Pre-existing mental health condition
ii. Learning difficulties
iii. Insomnia		i. Psychological interventions
ii. Government support
98.Odriozola-González et al., 2020 [125]Spain2530i. Anxiety (21%)
ii. Depression (34%)
iii. Stress (28%)		i. Course of study
ii. Year of study		i. Self-isolation
ii. Social distancing
99.Muñoz-Violent et al., 2021 [126]Spain996i. Anxiety (39%)
ii. Depression (12%)		i. Female gender
ii. Large family size
iii. History of mental illness
iv. Fear of infection		Coping skills
100.Visser and Wyk, 2021 [127]South Africa5074i. Anxiety (46%)
ii. Depression (35%)		Fear of infectionPsychological interventions
101.Posel et al., 2021 [128]South Africa2213Depression (24%)Job lossi. Mental health interventions
ii. Re-employment
102.Werling et al., 2022 [129]Switzerland i. Anxiety (Severe, 33.6%)
ii. Depression (Moderate, 44.3%)
iii. Stress (Moderate, 50.8%)		i. Loneliness/isolation of the child ii. Worry about child’s education iii. Increased media use
iv. Missing recreational activities 		i. Adequate medical supply
ii. Support for families
103.Krifa et al., 2022 [130]Tunisia366i. Anxiety (Severe, 33.6%)
ii. Depression (Moderate, 44.3%)
iii. Stress (Moderate, 50.8%)		i. Fear of infection
ii. Examination stress
iii. Low response to students’ needs 		i. Social support
ii. Psychological support
iii. Counseling
104.Al Dhaheri et al., 2021 [131]United Arab Emirates6142i. Psychological Distress (31%)
ii. Felt horrified (62%)
iii. Stress (60%)		i. Female gender
ii. Young adults		Support from family
105.Saddik et al., 2021 [132]United Arab Emirates481i. Anxiety (Mild 66%, Severe 32%)
ii. Psychological distress (Mild 49%, Severe 37%)		i. Worry about COVID-19
ii. Being isolated
iii. Contracting COVID-19
iv. Feeling stigmatized		i. Mental health preventive policies
ii. Psychological support
106.O’Connor et al. 2022 [133]UK3077i. Anxiety (17–22%)
ii. Suicidal ideation (13–14%)
iii. Depression (23–26%) 		i. Female gender
ii. Younger age
iii. Pre-existing mental health 		Psychological interventions
107.Niedzwiedz et al., 2021 [134]UK9748Psychological distress (31%)Lockdown measures i. Psychological support,
ii. Access to mental health services
108.Chen and Lucock, 2022 [135]UK1178i. Anxiety (50%)
ii. Depression (50%)		i. Low exercising
ii. High tobacco use
iii. Financial concerns
iv. Worse personal relations
v. Cancellation of an event		i. Social support
ii. Psychological therapy
iii. Counseling
109.Morgül et al., 2020 [136]UK927i. Anxiety (45%)
ii. Worried (52%),
iii. Angry (49%),		i. Impact of the quarantine
ii. Children’s screen use time
iii. Physical activity		Development of intervention programs
110.Prasad et al., 2021 [137]USA20,947i. Anxiety or depression (38%)
ii. Burnout (49%)		i. Fear of exposure
ii. Female gender
iii. Black race and Latino		Government support
111.Czeisler et al., 2020 [138]USA5412i. Anxiety or Depression (31%)
ii. PTSD (26%)
iii. Substance use (13%)
iv. Suicide tendency (11%)		i. Young adult
ii. Ethnic minority
iii. Pre-existing psychiatric conditions
iv. Unpaid caregivers		i. Community intervention
ii. Government support
112.Czeisler et al., 2021 [139]USA5186i. Anxiety or Depression (33%)
ii. PTSD (30%)
iii. Substance use (15%)
iv. Suicide tendency (12%)		i. Wrong coping strategy
ii. Employment status
iii. History of mental illness		Government support
113.Vahia et al., 2020 [140]USA3840i. Anxiety disorder (6%)
ii. Depressive disorder (6%)
iii. PTSD (9%)		i. Isolation
ii. longer-term physical and financial wellbeing		i. Utilizing technology to maintain contact
ii. Mental health services
114.Dickey-Chasins et al., 2022 [141]USA3006Anxiety/depressive (Moderate, 29.1%) i. Females gender
ii. Democrats
iii. Sexual minorities
iv. Unemployment
v. Single/unmarried 		i. Social support
ii. Government Intervention
115.Browning et al., 2021 [142]USA2534i. Anxiety (22%)
ii. Depression (25%)
iii. Stress (18%)		i. Female gender
ii. Younger age
iii. Comorbidity diseases
iv. Poor income		i. Mental health support
ii. Educational support
116.Lopez-Castro et al., 2021 [143]USA909i. Depression (90%)
ii. Anxiety (66%)
iii. PTSD (5%)		i. History of infection
ii. Emotional Health issues
ii. Poor wellbeing		Social support
117.Son et al., 2020 [144]USA195i. Anxiety and Stress (71%)
ii. Depressive thoughts (44%)		i. Disruptions of sleeping
ii. Fear of infection
iii. Decreased social interactions 		i. Mental health counseling
ii. Self-Management
iii. Seeking support
118.Hamm et al., 2020 [145]USA73i. Anxiety (75%)
ii. Depression (44%)
iii. Social Isolation (36%)		i. Fear of losing the job
ii. Financial problems		i. Internet surfing
ii. Avoid negative emotions
ii. Exercises
119.Jow et al., 2022 [146]USA38i. Anxiety (75%)
ii. Depression (44%)
iii. Social Isolation (36%)		i. Occupational stress
ii. concerns for health and safety
iii. Additional work
iv. Psychological toll of caring for patients 		I. Support and guide
ii. Policy changes
120.Nikolaidis et al., 2021 [147]USA, UK3423i. Worry US (8–10%), UK (12–17%)
ii. Mood changes (50–57%)		With age and sex, Mood StatesGovernment support
121.Rahman et al., 2021 [148]17 Asian countries8559i. Psychological distress (69%)
ii. Fear (24%)		i. Old age
ii. Poor financial status
iii. Nurses		Medical and social
support
122.van Mulukom et al., 2021 [149]79 Countries8229i. Anxiety (8%)
ii. Depression (7%)		i. Self-isolation
ii. Poor coping strategy		i. Positive coping strategy
ii. Government support
Table
Table 2. Summary of Mental Disorders and Number of Studies Reported.
Table 2. Summary of Mental Disorders and Number of Studies Reported.
S/NMental DisorderNo. of Studies that ReportedPercentage
1Anxiety9235.9
2Depression7629.7
3Stress3212.5
4Posttraumatic Stress Disorder166.3
5Psychological Disturbance145.5
6Insomnia135.0
7Worry62.3
8Fear52.0
9Obsessive-Compulsive Disorder10.4
10Eating Disorder10.4
Total256100%
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Rabiu Abubakar, A.; Tor, M.A.; Ogidigo, J.; Sani, I.H.; Rowaiye, A.B.; Ramalan, M.A.; Najib, S.Y.; Danbala, A.; Adamu, F.; Abdullah, A.; et al. Challenges and Implications of the COVID-19 Pandemic on Mental Health: A Systematic Review. Psych 2022, 4, 435-464. https://doi.org/10.3390/psych4030035

AMA Style

Rabiu Abubakar A, Tor MA, Ogidigo J, Sani IH, Rowaiye AB, Ramalan MA, Najib SY, Danbala A, Adamu F, Abdullah A, et al. Challenges and Implications of the COVID-19 Pandemic on Mental Health: A Systematic Review. Psych. 2022; 4(3):435-464. https://doi.org/10.3390/psych4030035

Chicago/Turabian Style

Rabiu Abubakar, Abdullahi, Maryam Abba Tor, Joyce Ogidigo, Ibrahim Haruna Sani, Adekunle Babajide Rowaiye, Mansur Aliyu Ramalan, Sani Yahaya Najib, Ahmed Danbala, Fatima Adamu, Adnan Abdullah, and et al. 2022. "Challenges and Implications of the COVID-19 Pandemic on Mental Health: A Systematic Review" Psych 4, no. 3: 435-464. https://doi.org/10.3390/psych4030035

APA Style

Rabiu Abubakar, A., Tor, M. A., Ogidigo, J., Sani, I. H., Rowaiye, A. B., Ramalan, M. A., Najib, S. Y., Danbala, A., Adamu, F., Abdullah, A., Irfan, M., Kumar, S., Etando, A., Rahman, S., Sinha, S., & Haque, M. (2022). Challenges and Implications of the COVID-19 Pandemic on Mental Health: A Systematic Review. Psych, 4(3), 435-464. https://doi.org/10.3390/psych4030035

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