Global Overview of Suicidal Behavior and Risk Factors among General Population during the COVID-19 Pandemic: A Systematic Review and a Meta-Regression

Abstract

The COVID-19 pandemic has significantly impacted mental health worldwide, leading to increased rates of suicidal behavior. This systematic review and meta-regression aim to investigate the global prevalence and risk factors associated with suicidal behaviors in the general population during the pandemic. The study included 202 articles from January 1, 2019, to October 31, 2023, sourced from databases such as Embase, MEDLINE, CINAHL, Web of Science, and Cochrane Library. The meta-analysis revealed a prevalence of 13.5% for suicidal ideation, 10.4% for suicide attempts, and a death rate of 0.5%, translating to 4.52 per 100,000 person-years. Significant risk factors identified include being transgender, young adults (18–44 years), unmarried status, low education, retirement, living alone, low social support, a history of suicide attempts, substance use, depression, anxiety, PTSD, sleep problems, poor perceived physical health, loneliness, quarantine, and residing in the Americas or multiple regions. The findings underscore the urgent need for targeted mental health interventions during pandemics, focusing on high-risk groups such as young adults, transgender individuals, those with low social support, and people with mental health issues. This comprehensive analysis provides valuable insights for policymakers and healthcare providers to develop effective strategies to mitigate the heightened risk of suicide during global health crises.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11126-024-10096-5.

Background

Social isolation, loneliness and mental illness are strongly associated with suicide among general population [1–3]. In 2019 a large context of lockdowns and social distancing took place due to the COVID-19 pandemic causing a severe global health crisis and subsequent declining mental health among the general population resulting in premature mortality and suicide [3, 4]. An estimated 9% to 46% of the general population suffered from depressive symptoms during the pandemic due to social separation and associated pandemic health policies such as quarantine and lockdown measures that directly influenced daily activities, physical contact hours, and behavioral patterns among people [3, 5].

Female gender, younger age, being a healthcare professional, low income, preexisting mental health issues, loneliness, and substance abuse are known risk factors associated with psychological issues and suicidal ideation during the pandemic [3, 5]. Progressing rise in anxiety, depression, insomnia, fear of contamination and losing loved ones are also associated with pandemic associated suicidal ideation, thoughts, and self-harm [6]. Compared with being employed; unemployment can cause threefold rise in risk of death due to suicide [1]. Therefore, pandemic raised demands of psychological support services worldwide.

Some studies were conducted to identify the adequacy of resource allocation, measure to understand severity, and frequency of suicidal ideation, attempt and self-harm during the pandemic among some specific populations loke adolescents [7]. However, understanding and empirical data on the prevalence and risk factors of suicidal ideation among general population is inconclusive.

Suicides are preventable, and early identification of risk factors plays a crucial role in this process. Investigating the multifaceted nature of suicide risk factors within the context of the COVID-19 pandemic is crucial for advancing suicide prevention strategies, especially in anticipation of upcoming emerging diseases. Understanding the complex relationships between psychological distress, economic instability, social isolation, sleep problems, status of gender, level of education, loneliness, unemployment, use of recreational drugs during times of this crisis is essential to design effective interventions to mitigate suicide risk specifically for pandemic and other epidemics. There are some reviews, limited to small number of studies (38 studies for SR and 12studies for meta-analysis) [8] (16 studies for SR) [6]assessing the impact on suicide during COVID-19. Previous studies included small number of studies and reported high heterogeneity (I² = 100%, τ² = 0.0077, p = 0) [8] and did not explore specific covariates causing suicidal outcomes through meta-regression, leaving a gap in understanding the factors contributing to suicidal behaviors during the pandemic. These studies were often limited to both the beginning and peak of the pandemic and lacked a global perspective. We conducted a systematic review and meta-regression analysis across countries including observational cohort and cross-sectional studies, identifying risk factors influencing suicidal ideation, suicide attempts, and deaths during the pandemic. English, Chinese, or Sinhala articles were included, enhancing the reliability and generalizability of our results in identifying key risk factors influencing suicidal outcomes during the COVID-19 pandemic. The objective of study was to explore the worldwide prevalence and identify the risk factors associated with suicidal ideation, suicide attempts, and deaths by suicide during the COVID-19 pandemic.

Methods

This review has been registered in the International Platform of Registered Systematic Review and Meta-analysis Protocols (PROSPERO, Reg No: CRD42023481933).

Definitions of Suicide Behaviors’ Related Outcomes

The terminology utilized to characterize self-harm varies among different contexts and research endeavors. While some studies adopt a broad definition of self-harm encompassing all forms of self-injurious behavior regardless of suicidal intent, others restrict the term solely to non-suicidal self-injury. Due to our inability to assess the individual intent behind instances of self-harm, we relied on classifications and descriptions as defined by the studies included. Our criteria for identifying suicide-related outcomes aligned with methodologies employed in similar meta-analyses.

Search Strategy

This study involved a comprehensive search across five databases: Embase, MEDLINE, CINAHL, Web of Science, and Cochrane Library to identify studies on the prevalence of suicidal behavior and risk factors during the COVID-19 pandemic. The search spanned the period from January 1, 2019, to October 31, 2023, and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA) [9–11]. English synonyms, such as Coronavirus, 2019-nCoV, COVID-19, and SARS-CoV, were employed in the search across each database. Control phrases were utilized for the Emtree and MeSH databases, including terms like "coronavirus," "SARS-related coronavirus," "Wuhan seafood market pneumonia virus," "Wuhan coronavirus," "SARS Coronavirus," "MERS-CoV," "suicidal behavior," "automutilation," and "suicide" for Emtree, and "self-injurious behavior" for MeSH. Supplementary searches were conducted using the Endnote X9 bibliographical database. Additionally, manual screening of publications citing the identified papers, as well as examination of the reference lists of pertinent articles and previous systematic reviews, was performed to ensure the sensitivity of the search strategy [12].

Eligibility Criteria

The inclusion criteria for this study were as follows: 1) The study provided primary data on the prevalence or incidence of suicidal ideation, suicide attempts, or suicide-related deaths. It included all suicidal behaviors, such as self-injurious behavior, which were measured using validated assessment tools or coded medical report data within a population-based study; 2) participants were assessed during the COVID-19 pandemic; and 3) observational studies, including all types of cohorts and cross-sectional studies, were included if they were in English, Chinese, or Sinhala, and published between 2019 and 2023. Exclusion criteria encompassed studies where the population did not exhibit suicidal behavior during the COVID-19 pandemic, as well as qualitative research and review studies. After removing duplicates using the Endnote X9 bibliographical database, titles and abstracts underwent independent screening by three researchers based on the inclusion and exclusion criteria. Subsequently, the full texts of the selected studies were independently reviewed by four researchers, with any discrepancies resolved by a fifth researcher to mitigate selection bias.

Quality Assessment

The quality of evidence in all eligible studies was evaluated using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies Scale (CACPSS). This scale comprises nine items with four possible responses (yes, no, unclear, and not applicable) [13]. Studies scoring 8 or above on the total scale were classified as possessing high-quality evidence and were consequently included in this systematic review. The assessment of study quality and risk of bias was conducted independently by four researchers, with any disparities resolved through consultation with a fifth researcher.

Data Extraction

Data extraction encompassed the retrieval of information including authors' names, year of publication, study type, World Health Organization (WHO) region, country, sample size, participant demographics such as ethnicity, age range, and sex. Additional extracted details involved the measurement tool employed for suicide assessment, prevalence rates of suicidal ideation, suicide attempts, and deaths by suicide, as well as identified risk factors. Quality scores for the included studies were independently assigned by four authors following the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [9]. Discrepancies in scoring were resolved through discussions involving all five authors.

Statistical Analysis

For the identification of statistical outcomes related to three specific suicidal behaviors during the COVID-19 pandemic, a meta-analysis was conducted using eligible studies. The pooled prevalence of suicidal ideation, suicide attempts, or death by suicide was analyzed by converting the number of events into risk ratios with 95% confidence intervals (CI) and p-values. A fitted model based on the degree of heterogeneity determined whether a random-effects model or a fixed-effects model was utilized for analyzing suicidal behaviors during COVID-19. Proportions were transformed using the Freeman-Tukey double arcsine method before data pooling for the incident rate of suicide, and heterogeneity was assessed using the DerSimonian-Laird estimator by I², the Cochran Q test, and Tau2 for the included studies [14–18]. A heterogeneity value of zero indicated the absence of heterogeneity, 25% indicated no or low significance, 50% indicated moderate heterogeneity, and 75% indicated significant heterogeneity. In this study, a range of 75–100% indicated significant heterogeneity, and the Q statistic and p-value were employed to validate the heterogeneity results. A meta-analysis with I2 > 75% and p > 0.05 was considered statistically significant.

To assess publication bias, funnel plots were employed, and Egger's Q statistic was applied to ascertain the correlation between the effect estimate and variances in the results for suicidal behavior during the COVID-19 pandemic using CMA software. Additionally, a visual examination of the funnel plots was conducted [19, 20]. Subgroup analysis and meta-regression were performed to explore potential sources of heterogeneity. We used the following variables as subgroups for this study: age, sex, marital status, education level, living situation, housing type, social support, lifestyle factors, smoking, alcohol and substance use, psychiatric disorders, sleep disorders, quarantine experience, and WHO regions.

In the meta-regression, the pool of effect size data was introduced individually into the models. A simultaneous test was carried out to determine whether all coefficients in the model were zero. The null hypothesis model was utilized for the effect size comparison. Statistical analyses were conducted using Comprehensive Meta-Analysis Software version 3.0 (Biostat, Englewood, New Jersey, USA) [21].

Results

Study Identification

The search across the five databases yielded 4,899 articles published between January 1, 2019, and October 31, 2023. Following the removal of 843 duplicate articles using the Endnote X9 bibliographical database, the titles and abstracts of 1,411 articles were screened, and 1,813 articles met the inclusion criteria. Each article's full text was then examined for eligibility, leading to the exclusion of 1,445 articles for various reasons: 118 had no relevance to the COVID-19 pandemic; 980 did not mention suicidal behavior during the COVID-19 pandemic; 160 did not clearly assess the outcome variables; and 65 were unavailable in full text format. After quality assessment, 124 articles were excluded due to low-quality scores in peer review. Additionally, two records identified from website reports were assessed for eligibility. Consequently, 200 articles met the criteria for inclusion in the systematic review and meta-regression (Fig. 1).

Fig. 1.

PRISMA flow diagram of the included studies

Study Characteristics

The studies were conducted across 41 countries. Among the included studies, as categorized by WHO region, five were conducted in the African Region, five in the Eastern Mediterranean Region, 53 in the European Region, 51 in the Region of the Americas, 14 in the South-East Asia Region, Three studies included data from multiple countries, each belonging to different WHO regions, and 71 in the Western Pacific Region (Table 1).

Table 1.

Characteristics of the included 200 studies

Author, Year of publication	Type of study	WHO region	Country	Sample size	Age Mean (SD)	Sex	Measurement tool for suicide	Suicide ideation (n) (%)	Suicide attempts (n) (%)	Deaths by suicide (n) (%)	Risk factor
Cheung, T. et al. (2020) (1)	Cross-sectional study	Region of the Americas, European Region, Western Pacific Region	United States, Canada, United Kingdom, Brazil, Philippines, Korea, Turkey, China (Hong Kong, Macau)	25,053	N/A	M: 5,687 (22.7%) F: 19,366 (77.3%)	Patient Health Questionnaire (PHQ-9)	3,891 (15.66%)	N/A	N/A	Younger age, male, married, differences in health beliefs
Graell, M. et al. (2020) (2)	Retrospective study	European Region	Spain	365	Day hospital: 13.18 (3.03) outpatient clinic: 14.74 (2.33)	M: 44 (12.1%) F: 321 (87.94%)	N/A	35 (25%)	N/A	N/A	N/A
Mamun, M. A. et al. (2020) (3)	Cross-sectional study	South-East Asia Region	Bangladesh	3,388	30.1 (6.4)	M: 1,634 (48.2%) F: 1,754 (51.8%)	N/A	206 (6.08%)	N/A	N/A	Female, being divorced, and having no child
Tasnim, R. et al. (2020) (4)	Cross-sectional study	South-East Asia Region	Bangladesh	3,331	21.4 (1.9)	M: 1,979 (59.4%) F: 1,352 (40.6%)	Depression, Anxiety, and Stress Scale (DASS-21)	427 (12.82%)	N/A	N/A	Less sleep, excess sleep, cigarette smoking, past suicidal thoughts, suicide attempt history, family history of suicidality, depression, anxiety, and stress
Antonelli-Salgado, T et al. (2021) (5)	Cross-sectional study	Region of the Americas	Brazil	8,104	38.6(14.1)	M: 1,094 (13.5%) F: 7,010 (86.5%)	Patient Health Questionnaire 9 (PHQ-9)	22.60% (n = 1,831)	N/A	N/A	Living alone, number of days practicing social distancing, loneliness
Auny, F. M. et al. (2021) (6)	Cross-sectional study	South-East Asia Region	Bangladesh	324	All: 26.99 (8.17) Non-suicidal: 27.23 (8.37) Suicidal: 23.52 (2.58)	M: 213 (65.7%) F: 111 (34.3%)	Patient Health Questionnaire 9 (PHQ-9)	6.48% (n = 21)	N/A	N/A	N/A
Ayuso-Mateos, J. L. et al. (2021) (7)	Cross-sectional study	European Region	Spain	1,103	54.82 (16.35)	M: 437 (39.6%) F: 666 (60.4%)	Composite International Diagnostic Interview (CIDI 3.0)	2.18% (n = 24)	N/A	N/A	N/A
Bond, Allison E. et al. (2021) (8)	Cross-sectional study	Region of the Americas	United States	3,499	N/A	N/A	Past month’s suicidal ideation was assessed with the Self‐Injurious Thoughts and Behaviors Interview‐Revised	3.20% (n = 462)	N/A	N/A	Black, indigenous, and people of color (BIPOC)
Bonsaksen, T. et al. (2021) (9)	Cross-sectional study	European Region	Norway	4,527	N/A	N/A	N/A	3.60% (n = 163)	0.20% (n = 9)	N/A	Suicide attempts, lower age, daily alcohol use, being in the risk group for COVID-19 complications, and having economic concerns related to the pandemic
Briggs, R. et al. (2021) (10)	Longitudinal study	European Region	Ireland	8,174	Non-suicidal: 63.9 Suicidal: 62.3	M: 3,746 (45.8%) F: 4,428 (54.2%)	Centre for Epidemiological Studies Depression Scale (CES-D)	3.50% (n = 279)	N/A	N/A	Both persistent loneliness and depressive symptoms
Bruffaerts, R. et al. (2021) (11)	Cross-sectional study	European Region	Belgium	6,409	N/A	N/A	Patient Health Questionnaire 9 (PHQ-9)	1.50% (n = 96)	N/A	N/A	Depression
Chakrabarti, S. et al. (2021) (12)	Observational study	South-East Asia Region	India	590	37.8 (5.6)	M: 355 (60.1%) F: 235 (39.9%)	Patient Health Questionnaire (PHQ-9)	5.08% (n = 30)	N/A	N/A	Separated or divorced, cancer, suburban residence, graduates
Chen, Y. et al. (2021) (13)	Cross-sectional study	Western Pacific Region	China	2,700	N/A	M: 673 (24.9%) F: 2,027 (75.1%)	1. Positive and Negative Suicidal ideation (PANSI). 2. Social Support Scale (SSRS)	5.40% (n = 146)	N/A	N/A	Residence before returning to school, lower objective support, poorer relationship with the mother
Czeisler, M. E. et al. (2021) (14)	Cross-sectional study	Region of the Americas	United States	1,648	N/A	M: 838 (50.8%) F: 789 (47.9%)	N/A	30.58% (n = 504)	N/A	N/A	N/A
Czeisler, M. E. et al. (2021) (15)	Cross-sectional study	Region of the Americas	United States	1,362	N/A	M: 679 (49.9%) F: 683 (50.1%)	Patient Health Questionnaire (PHQ-4)	33.33% (n = 454)	N/A	N/A	Young people
DeVylder, J. et al. (2021) (16)	Cross-sectional study	Region of the Americas	United States	16,315	24.75 (8.60)	M: 6,549 (40.1%) F: 9,212 (56.5%) Trans or other: 553 (3.4%)	N/A	13.42% (n = 2,190)	1.30% (n = 209)	N/A	COVID-19
Du, N. et al. (2021) (17)	Retrospective study	Western Pacific Region	China	609	Non-suicidal: 15.37 (1.75) Suicidal: 15.33 (1.74)	M: 77 (12.6%) F: 532 (87.4%)	N/A	N/A	51.23% (n = 312)	N/A	Female, older age, having a single parent, having experienced trauma, having experienced social isolation from peers, having experienced body-focused bullying, overuse of a mobile phone in the parents' opinions, having attempted suicide during the pandemic
Efstathiou, V. et al. (2021) (18)	Longitudinal study	European Region	Greece	811	27.19 (12.96)	M: 202 (24.91%) F: 607 (74.85%) Other: 2 (0.10%)	Patient Health Questionnaire (PHQ-9)	4.32% (n = 35)	N/A	N/A	Anxiety, depression, suicidal ideation, living with a person with frail health and vulnerable to severe COVID-19 infection emerged
Gesi, C. et al. (2021) (19)	Retrospective study	European Region	Italy	195	N/A	N/A	N/A	17.95% (n = 35)	2.05% (n = 4)	N/A	N/A
Habu, H. et al. (2021) (20)	Cross-sectional study	Western Pacific Region	Japan	47,770	60.6 (26.8)	M: 16,864 (35.30%) F: 23,336 (48.85%)	N/A	N/A	0.98% (n = 467)	N/A	Female, aged 25–49 years
Han, J. M. et al. (2021) (21)	Cross-sectional study	Western Pacific Region	Korea	54,948	N/A	M: 28,353 (51.9) F: 26,595 (48.1)	N/A	10.90% (n = 5,989)	N/A	N/A	Lower perceived household economic status
Hermosillo-de-la-Torre, A. E. et al. (2021) (22)	Cross-sectional study	Region of the Americas	Mexico	8,033	16	M: 3910 (487%) F: 4123 (51.3%)	The suicidal behaviors schedule (Cédula de Conductas Suicidas (CCS)	N/A	11.17% (n = 897)	N/A	Female sex, depression, hopelessness, anxiety, alcohol and tobacco use, childhood trauma, and having to self-rely on are issues affecting attachment and low self-esteem
Hou, T. et al. (2021) (23)	Cross-sectional study	Western Pacific Region	China	761	N/A	N/A	Patient Health Questionnaire (PHQ-9)	36.40% (n = 277)	10.38% (n = 79)	N/A	Suicidal ideation: parental educational level, maladaptive strategies, anxiety, depression Suicidal attempts: Age, maladaptive strategies, anxiety, depression
Keshavarzi, F. et al. (2021) (24)	Cross-sectional study	Western Pacific Region	Malaysia	383	N/A	M: 166 (43.3%) F: 217 (56.7%)	Overall Perceived Stress Scale-10 (PSS)	11.23% (n = 43)	N/A	N/A	Loneliness, feeling social isolation
Khosravani, V. et al. (2021) (25)	Cross-sectional study	Eastern Mediterranean Region	Iran	304	35.8 (11.80)	M: 126 (41.4%) F: 178 (58.6%)	Patient Health Questionnaire (PHQ-4)	N/A	22.70% (n = 69)	N/A	Obsessive–compulsive disorder (OCD)
Killgore, W. D. S. et al. (2021) (26)	Cross-sectional study	Region of the Americas	United States	1,013	36.74 (12.09)	N/A	Beck Depression Inventory-II. Patient Health Questionnaire-9	17.57% (n = 178)	N/A	N/A	N/A
Kim, S. Y. et al. (2021) (27)	Cross-sectional study	Western Pacific Region	Korea	92,659	15.1 (1.7)	M: 48,020 (51.8%) F: 44,639 (48.2%)	N/A	11.45% (n =  10,609)	2.20% (n =  2,043)	N/A	N/A
Landi, G. et al. (2021) (28)	Cross-sectional study	European Region	Italy	652	38.8 (13.2)	M: 161 (24.7%) F: 491 (75.3%)	Patient Health Questionnaire-9 (PHQ-9)	15.34% (n = 100)	N/A	N/A	Mental pain intensity
Le, S. et al. (2021) (29)	Cross-sectional study	Western Pacific Region	China	56,679	N/A	M: 27,149 (47.9%) F: 29,530 (52.1%)	Patient Health Questionnaire-9 (PHQ-9)	16.45% (n = 9,322)	N/A	N/A	Experience of quarantine, unemployment, psychological stress
Liu, L. et al. (2021) (30)	Cross-sectional study	Region of the Americas	Canada	11,324	N/A	M: 5,574 (49.22%) F: 5,750 (50.78%)	N/A	2.44% (n = 276)	N/A	N/A	Under 65 years, a frontline worker, job loss, loneliness, isolation, highly stressful or traumatic event, lower household income, lower educational attainment
Lopez Steinmetz, L. C. et al. (2021) (31)	Cross-sectional study	Region of the Americas	Argentina	1,202	N/A	N/A	Self-reported suicidal thoughts and severe distress (IES-R)	43.09% (n = 518)	8.15% (n = 98)	N/A	N/A
Lu, X. et al. (2021) (32)	Cross-sectional study	Western Pacific Region	China	1,630	COVID-19: 37.4 (10.9). Non-COVID-19: 36.8 (10.4)	M: 639 (39.2%) F: 991 (60.8%)	Patient Health Questionnaire-9 (PHQ-9)	11.72% (n = 191)	N/A	N/A	N/A
Lueck, J. A. et al. (2021) (33)	Cross-sectional study	Region of the Americas	United States	5,001	44.5 (16.92)	M: 2,486 (49.7%) F: 2,515 (50.3%)	Patient Health Questionnaire-9 (PHQ-9)	48.35% (n = 2,418)	N/A	N/A	Worsening mental health overall
Mamun, M. A. et al. (2021) (34)	Cross-sectional study	South-East Asia Region	Bangladesh	756	22.24 (4.39)	M: 446 (59%) F: 310 (41%)	Patient Health Questionnaire 4 (PHQ-4)	8.20% (n = 62)	0.70% (n = 5)	N/A	Taking drugs, performing less physical activity, poor self-reporting health condition, comorbid, higher COVID-19 risk, fear of COVID-19 infection, depression, anxiety
Mamun, M. A. et al. (2021) (35)	Cross-sectional study	South-East Asia Region	Bangladesh	10,067	29.94 (9.63)	M: 5650 (56.1%) F: 4406 (43.9%)	Patient Health Questionnaire 4 (PHQ-4)	5.03% (n = 506)	N/A	N/A	Young, female, smoker, comorbid diseases, fear of COVID-19 infection, insomnia
McAuliffe, C. et al. (2021) (36)	Cross-sectional study	European Region	United Kingdom	7,002	N/A	M: 3,350 (47.8%) F: 3,577 (51.1%) Transgender: 29 (0.5%) Other: 46 (0.6%)	N/A	6.18% (n = 433)	N/A	N/A	Financial, relationship, substance use, COVID-19 exposure
Menculini, G. et al. (2021) (37)	Retrospective study	European Region	Italy	447	N/A	N/A	N/A	9.17% (n = 41)	9.84% (n = 44)	N/A	Living with marital family, suicidality-related phenomena, and adjustment disorders
Mortier, P. et al. (2021) (38)	Cross-sectional study	European Region	Spain	3,500	49.6 (17.0)	M: 1,538 (48.5%) F: 1,962 (51.5%)	Columbia Suicide Severity Rating Scale	1.83% (n = 64)	0.10% (n = 5)	N/A	Mental disorders, major depressive disorder, generalized anxiety disorder, post-traumatic stress disorder, panic attacks, alcohol or substance use disorder
Mortier, P. et al. (2021) (39)	Cross-sectional study	European Region	Spain	5,450	N/A	N/A	Patient Health Questionnaire (PHQ-8)	2.74% (n = 96)	0.14% (n = 5)	N/A	Anxiety disorder
Nichter, B. et al. (2021) (40)	Prospective study	Region of the Americas	United States	2,746	All: 63.2 (14.7) Non-suicidal: 64.5 (14.2) Suicidal: 57.8 (14.8)	M: 2,467 (89.8) F: 279 (10.2)	N/A	2.99% (n = 82)	N/A	N/A	Low social support, suicide attempt history, lifetime posttraumatic stress disorder, depression, alcohol use disorder, COVID-19 infection, worsening of social relationships
Nomura, K. et al. (2021) (41)	Cross-sectional study	Western Pacific Region	Japan	2,449	20.5 (3.5)	M: 1,308 (53.8) F: 1,119 (46.2)	Patient Health Questionnaire (PHQ-9)	6.61% (n = 162)	N/A	N/A	alcohol use
Okubo, R. et al. (2021) (42)	Cross-sectional study	Western Pacific Region	Japan	24,819	N/A	M: 12,394 (49.9%) F: 12,425 (51.1%)	Kessler Psychological Distress Scale (K6)	3.49% (n =)	N/A	N/A	Higher urbanization level and greater neighborhood deprivation (lower neighborhood-level socioeconomic status)
Papadopoulou, A. et al. (2021) (43)	Cross-sectional study	European Region	Greece	5,748	N/A	M: 1,434 (24.9%) F: 4,217 (73.4%) Other: 5 (0.1%) Not available: 92 (1.6%)	Patient Health Questionnaire (PHQ-2)	4.63% (n =)	N/A	N/A	Unmarried or divorced marital status, mental health history, poor perceived quality of physical health, impaired family functioning, anxiety, and depression
Peng, X. D. et al. (2021) (44)	Cross-sectional study	Western Pacific Region	China	39,751	14.79 (1.7)	M: 18,966 (47.7%) F: 20,785 (52.3%)	Patient Health Questionnaire (PHQ-9)	20.30% (n =)	N/A	N/A	Female, junior high school, poor overall sleep quality, poor academic performance, worried about being infected during COVID-19, depression, anxiety
Rahman, M. E. et al. (2021) (45)	Cross-sectional study	South-East Asia Region	Bangladesh	1,415	25.42 (8.78)	M: 875 (61.8%) F: 540 (38.2%)	Suicide behaviors questionnaire-revised (SBQ-R)	33.50% (n =)	N/A	N/A	Females, divorced or widowed, low educational attainment
Rodríguez U. E. et al. (2021) (46)	Cross-sectional study	Region of the Americas	Colombian	484	30 (11)	N/A	Okasha’s Suicidality Scale (OSS)	40.08% (n =)	N/A	N/A	Females, and under 20 years
Sahimi, H. M. S. et al. (2021) (47)	Cross-sectional study	Western Pacific Region	Malaysia	171	N/A	N/A	Patient Health Questionnaire (PHQ-9)	11.11% (n =)	N/A	N/A	Depression
Sasaki, N. et al. (2021) (48)	Cross-sectional study	Western Pacific Region	Japan	875	N/A	M: 463 (52.9%) F: 412 (47.1%)	N/A	28.69% (n =)	N/A	N/A	Younger people (aged < 39 years) and mental health conditions
Shongwe, M. C. et al. (2021) (49)	Cross-sectional study	African Region	Eswatini	933	N/A	M: 275 (27.7%) F: 718 (72.3%)	Kessler 6-item Psychological Distress Scale (K6)	1.71% (n =)	N/A	N/A	N/A
Tong, Y. et al. (2021) (50)	Case–control study	Western Pacific Region	China	7,337	COVID-19: 26.8 (11.4) Non-COVID-19: 22.1 (8.1)	M: 2414(32.9%) F: 4923 (67.1%)	N/A	N/A	7.78% (n =)	N/A	Suicide attempt history
Travis-Lumer, Y. et al. (2021) (51)	Quasi-experimental study	European Region	Israel	852,233	11.71 (4.44)	M: 424,240 (49.8%) F: 427,993 (50.2%)	N/A	N/A	N/A	0.13% (n = 1,148) 2. 134.7/ per 100,000	COVID-19
Tsai, J. et al. (2021) (52)	Cross-sectional study	Region of the Americas	United States	6,607	N/A	N/A	Patient Health Questionnaire-2(PHQ-2)	31.24% (n = 2,064)	N/A	N/A	N/A
Vassalini, P. et al. (2021) (53)	Cross-sectional study	European Region	Italy	115	57	M: 62 (54%) F: 53 (46%)	Patient Health Questionnaire-9 (PHQ-9)	6.09% (n = 7)	N/A	N/A	N/A
Vrublevska, J. et al. (2021) (54)	Cross-sectional study	European Region	Latvia	2,609	N/A	M: 1,260 (48%) F: 1,344 (51%) Other: 4 (1%)	Risk Assessment of Suicidality Scale (RASS)	N/A	6.13% (n = 160)	N/A	N/A
Wang, D. et al. (2021) (55)	Case–control study	Western Pacific Region	China	67,905	20.23 (1.63)	M: 21,270 (31.3%) F: 46,635 (68.7%)	Patient Health Questionnaire-9 (PHQ-9) Patient Health Questionnaire-2 (PHQ-2)	17.65% (n =  11,984)	N/A	N/A	Sleep disturbance, short sleep duration
Wang, M. et al. (2021) (56)	Case–control study	Western Pacific Region	China	460	N/A	M: 163(35.43%) F: 297(64.57%)	Patient Health Questionnaire-9 (PHQ-9) Patient Health Questionnaire-15 (PHQ-15)	23.26% (n = 107)	N/A	N/A	Lower education levels and abnormal body temperature
Xu, L. Z. et al. (2021) (57)	Case–control study	Western Pacific Region	China	18,521	N/A	M: 3,909 (21.1%) F: 14,612 (78.9%)	Patient Health Questionnaire-2 (PHQ-2) Patient Health Questionnaire-15 (PHQ-15)	0.53% (n = 99)	N/A	N/A	N/A
Xu, X. et al. (2021) (58)	Cross-sectional study	Western Pacific Region	China	11,507	33.37 (8.22)	N/A	Patient Health Questionnaire-9 (PHQ-9) Patient Health Questionnaire-15 (PHQ-15)	6.47% (n = 744)	N/A	N/A	The infection of family members or relatives, poor marital status, poor self-rated health, the need for psychological intervention, perceived high stress, low support, depression, and anxiety
Xu, Y. et al. (2021) (59)	Cross-sectional study	Western Pacific Region	China	11,254	N/A	M: 4,054 (36.02%) F:7,200 (63.98%)	Patient Health Questionnaire-9 (PHQ-9)	2.03% (n = 229)	N/A	N/A	Distant relationship with parents, changes in lifestyle, alcohol use, mental health symptoms
Yang, X. et al. (2021) (60)	Cross-sectional study	Western Pacific Region	China	1,070	N/A	M: 346 (32.3%) F: 724 (67.7%)	Patient Health Questionnaire-9 (PHQ-9)	1.59% (n = 17)	N/A	N/A	N/A
Zhao, L. et al. (2021) (61)	Cross-sectional study	Western Pacific Region	China	1,154	N/A	N/A	Chinese Depression Screening Scale	60.31% (n = 696)	N/A	N/A	N/A
Zhou, S. J. et al. (2021) (62)	Cross-sectional study	Western Pacific Region	China	11,133	N/A	M: 4,195 (37.7%) F: 6,938 (62.3%)	Patient Health Questionnaire-9 (PHQ-9)	7.28% (n = 810)	N/A	N/A	N/A
Zhu, S. et al. (2021) (63)	Cross-sectional study	Western Pacific Region	China	1,381	N/A	M: 634 (45.9%) F: 747 (54.1%)	Patient Health Questionnaire-9 (PHQ-9)	32.46% (n = 484)	N/A	N/A	Anxiety, trait anxiety, life satisfaction
Zilinskas, E. et al. (2021) (64)	Cross-sectional study	European Region	Lithuania	1,001	20.8 (2.8)	M: 225 (22.5%) F: 776 (77.5%)	Hospital Anxiety and Depression Scale (HADS)	45.55% (n = 456)	1.69% (n = 17)	N/A	Anxiety, depression
Agyapong, B. et al. (2022) (65)	Cross-sectional study	Region of the Americas	Canada	146	N/A	N/A	Patient Health Questionnaire-9 (PHQ-9)	17.81% (n = 26)	N/A	N/A	Alcohol abuse
Ali, M. et al. (2022) (66)	Cross-sectional study	South-East Asia Region	Bangladesh	731	N/A	M: 376 (51.44%) F: 355 (48.56%)	N/A	16.28% (n = 119)	N/A	N/A	Sociodemographic factors, illness, behavior, institution, and subject-related issues
Alleaume, C. et al. (2022) (67)	Cross-sectional study	European Region	France	1,736	N/A	M: 826 (47.59%) F: 910 (52.41%)	Patient Health Questionnaire-9 (PHQ-9)	8.31% (n = 231)	N/A	N/A	Posttraumatic stress disorder (PTSD)
Ansari, S. K. et al. (2022) (68)	Cross-sectional study	Eastern Mediterranean Region	Pakistan	510	21.74 (2.24)	N/A	Coronavirus Reassurance-Seeking Behaviours Scale (CRBS)	23.53% (n = 120)	N/A	N/A	Anxiety
Arnon, S. et al. (2022) (69)	Cross-sectional study	Region of the Americas	United States	10,414	12.0 (0.7)	M: 5,452 (52.4%) F: 4,962 (47.6%)	N/A	7.24% (n = 785)	1.45% (n = 152)	N/A	Cyberbullying
Batterham, P. J. et al. (2022) (70)	Cross-sectional study	Western Pacific Region	Australia	1,296	46.0 (17.3)	M: 645 (49.8%) F: 649 (50.1%)	Patient Health Questionnaire-9 (PHQ-9)	30.48% (n = 395)	N/A	N/A	Higher pandemic-related work and social impairment, recent adversity, loneliness, younger
Bell, C. et al. (2022) (71)	Cross-sectional study	Western Pacific Region	New Zealand	3,389	N/A	M: 1461 (43.1%) F: 649 (56.9%)	Kessler Psychological Distress Scale (K10)	4.16% (n = 188)	1.46% (n = 49)	N/A	Alcohol use
Benatov, J. et al. (2022) (72)	Cross-sectional study	European Region	Germany, Israel, Poland, and Slovenia	1,723	30.74 (5.74)	M: 789 (46%) F: 935 (54%)	Patient Health Questionnaire (PHQ-8)	36.74% (n = 633)	N/A	N/A	Student, depression
Benavente-Fernandez, A. et al. (2022) (73)	Cross-sectional study	European Region	Spain	36	69.8 (14.31)	M: 19 (52.78%) F: 17 (47.22%)	Beck Hopelessness Scale (BHS). Columbia-Suicide Severity Rating Scale (C-SSRS)	N/A	8.33% (n = 3)	N/A	Active treatment of a psychiatric illness, active smoking
Bismark, M. et al. (2022) (74)	Cross-sectional study	Western Pacific Region	Australia	7,795	N/A	M: 1,452 (19%) F: 6,300 (81%) Non-binary / prefer not to say: 43 (1%)	Patient Health Questionnaire-9 (PHQ-9)	10.46% (n = 815)	N/A	N/A	Who had friends or family infected with COVID-19, were living alone, were younger, male, had increased alcohol use, poor physical health, increased income worries, or prior mental illness
Bismark, M. et al. (2022) (75)	Cross-sectional study	Western Pacific Region	Australia	7,795	N/A	M: 1,452 (19%) F: 6,300 (81%) Non-binary / prefer not to say: 43 (1%)	Patient Health Questionnaire-9 (PHQ-9)	3.36% (n = 262)	N/A	N/A	N/A
Blomqvist, S. et al. (2022) (76)	Cohort study	European Region	Sweden	65,530	N/A	M: 30,857 (47.08%) F: 34,473 (52.92%)	N/A	N/A	1.37% (n = 896)	N/A	Job insecurity
Brailovskaia, J. et al. (2022) (77)	Cross-sectional study	European Region	Germany	406	27.69 (6.88)	N/A	Suicide Behaviors Questionnaire – Revised (SBQ-R)	30.00% (n = 122)	N/A	N/A	N/A
Caballero-Dominguez, C. C. et al. (2022) (78)	Cross-sectional study	Region of the Americas	Colombia	700	37.1 (12.7)	M: 224 (32%) F: 476 (68.0%)	N/A	7..57% (n = 53)	N/A	N/A	A depressive episode, insomnia
Caravaca-Sanchez, F. et al. (2022) (79)	Cross-sectional study	European Region	Spain	517	N/A	N/A	Suicidal Behaviors Questionnaire-Revised (SBQ-R)	25.53% (n = 132)	N/A	N/A	Anxiety, alcohol use, cannabis use
Dale, R. et al. (2022) (80)	Cross-sectional study	European Region	Austria	1,257	16.3 (1.4)	N/A	Patient Health Questionnaire-9 (PHQ-9)	45.74% (n = 682)	N/A	N/A	N/A
Dogan, F. S. et al. (2022) (81)	Retrospective study	European Region	United States	4,296	31.70 (12.64)	M: 3,286 (76.5%) F: 1,010 (23.5%)	N/A	N/A	N/A	2.77% (n = 119)	N/A
Dolsen, E. A. et al. (2022) (82)	Cross-sectional study	Region of the Americas	United States	837	37.1	M: 168 (20.1%) F: 616 (73.6%) Other: 53 (2.5%)	Beck Depression Inventory-II	27.96% (n = 234)	N/A	N/A	Younger age, lower income, single relationship status, sexual orientation other than heterosexual specifically identifying as bisexual, non-full-time employment, living in a town
Dominguez-Gonzalez, A. D. et al. (2022) (83)	Cross-sectional study	Region of the Americas	Mexico	247	N/A	M: 78 (31.6%) F: 169 (68.4%)	Plutchik Suicidal Risk Scale (PSRS)	18.62% (n = 46)	N/A	N/A	Depression
Doran, N. et al. (2022) (84)	Retrospective study	Region of the Americas	United States	771,570	58.7	M: 678,210 (87.9%) F: 93,360(12.1%)	N/A	N/A	0.22% (n = 1,722)	0.01% (n = 89)	N/A
Duarte, F. et al. (2022) (85)	Retrospective study	Region of the Americas	Chile	20,760	43.7	N/A	N/A	N/A	N/A	7.57% (n = 1,571) 8.07/100,000	N/A
Efstathiou, V. et al. (2022) (86)	Cross-sectional study	European Region	Greece	720	45.09 (12.16)	M: 189 (26.2%) F: 531 (73.8%)	Patient Health Questionnaire-2 (PHQ-2)	4.72% (n = 34)	N/A	N/A	Depression, anxiety
El Frenn, Y. et al. (2022) (87)	Cross-sectional study	Eastern Mediterranean Region	Lebanon	402	27.85 (10.93)	M: 125 (31.1%) F: 277 (68.9%)	Columbia‑Suicide Severity Rating Scale (C‑SSRS)	18.20% (n = 73)	N/A	N/A	Depression, fear of COVID-19, older age
Fadhli, S. A. M. et al. (2022) (88)	Cross-sectional study	Western Pacific Region	Malaysia	1,290	14.48	M: 385 (29.8%) F: 905 (70.2%)	Patient Health Questionnaire-9 (PHQ-9)	11.94% (n = 154)	8.37% (n = 108)	N/A	Cyberbullying victimization
Gainza Perez, M. A. et al. (2022) (89)	Cross-sectional study	Region of the Americas	United States	159	37.64 (11.92)	M: 82 (51.6%) F: 77 (48.4%)	Suicidal Ideation Attributes SScale (SIDAS)	27.67% (n = 44)	N/A	N/A	Low adherence
Galletta, M. A. K. et al. (2022) (90)	Cross-sectional study	Region of the Americas	Brazil	182	30.84 (6.62)	M: 0 (0%) F: 182 (100%)	Edinburgh Postnatal Depression Scale (EPDS)	14.29% (n = 26)	N/A	N/A	N/A
Geda, N. et al. (2022) (91)	Cross-sectional study	Region of the Americas	Canada	4,005	N/A	M: 1,930 (48.2%) F: 2059 (51.4%) Other: 16 (0.4%)	N/A	12.01% (n = 481)	N/A	N/A	Social isolation, depression, anxiety, and substance use (cannabis)
Hagerty, S. L. et al. (2022) (92)	Cross-sectional study	Region of the Americas	United States	1,122	39.29	M: 3,498 (11.2%) F: 7,603 (88.8%)	Patient Health Questionnaire-9 (PHQ-9)	15.42% (n = 173)	N/A	N/A	Moral injury, loneliness
Holler, I. et al. (2022) (93)	Cross-sectional study	European Region	Germany	1,311	30.96 (8.48)	M: 41 (3.1%) F: 1,270 (96.9%)	The German version of the Suicide Ideation and Behaviour Scale (SSEV)	21.74% (n = 285)	0.53% (n = 7)	N/A	Depression, agitation, perceived burdensomeness, previous suicide attempt
Hyland, P. et al. (2022) (94)	Retrospective study	European Region	Ireland	1,032	N/A	N/A	Patient Health Questionnaire-9 (PHQ-9)	29.46% (n = 304)	11.24% (n = 116)	N/A	Suicidal ideation: male, unemployed, higher loneliness, and lower religiosity Suicide attempt: ethnic minority status, lower education, lower income, PTSD, depression, and history of mental health treatment
Hyland, P. et al. (2022) (95)	Retrospective study	European Region	Ireland	1,110	N/A	N/A	Patient Health Questionnaire-9 (PHQ-9)	N/A	11.17% (n = 124)	N/A	N/A
Ide, K. et al. (2022) (96)	Cross-sectional study	Western Pacific Region	Japan	2,813	N/A	M: 735 (3.1%) F: 2,078 (73.87%)	Patient Health Questionnaire-9 (PHQ-9)	8.64% (n = 243)	N/A	N/A	Mental health
Jadir, D. S. et al. (2022) (97)	Cross-sectional study	United States: Region of the Americas. Italy: European Region. Spain: European Region. Saudi Arabia: Eastern Mediterranean Region. India: South-East Asia Region	United States, Italy, Spain, Saudi Arabia, and India	2,482	37.1 (13.03)	M: 1,251 (50.4%) F: 1,231 (49.6%)	Patient Health Questionnaire-9 (PHQ-9)	39.69% (n = 985)	N/A	N/A	Racial/ethnic minorities
Jones, L. B. et al. (2022) (98)	Cross-sectional study	Region of the Americas	Canada	4,693	N/A	M: 1,628 (34.69%) F: 1,235 (63.05%)	WHO World Mental Health-Composite International Diagnostic Interview (WHO WMH-CIDI)	18.88% (n = 886)	N/A	N/A	Chinese or as another non-Indigenous ethnic minority; experiencing current symptoms of depression or anxiety; having a history of suicidal planning or attempts
Kaggwa, M. M. et al. (2022) (99)	Cross-sectional study	African Region	Uganda	540	23.3 (2.64)	F: 177 (32.78%) M: 363 (67.22%)	General Health Questionnaire	31.85% (n = 172)	N/A	N/A	Suicidal ideation: having difficulty paying university tuition fees Suicide attempts: having a history of sexual abuse, having difficulty paying university tuition fees
Kaggwa, M. M. et al. (2022) (100)	Cross-sectional study	African Region	Uganda	540	All: 23.3 (2.64) Non-suicidal: 23.41 (2.74) Suicidal: 22.61 (1.77)	M: 363 (67.22%) F: 177 (32.78%)	Patient Health Questionnaire-9 (PHQ-9)	13.89% (n = 75)	N/A	N/A	Smoking cigarettes and marijuana and having financial tuition constraints
Kaggwa, M. M. et al. (2022) (101)	Retrospective study	African Region	Uganda	215,427	All suicide: 27.16 (14.71) Non-fatal suicide attempt: 28.49 (14.61) Completed suicide: 20.69 (13.72)	N/A	N/A	N/A	0.06%. Per 60/ 100,000 people (n = 130)	0.01% Per 3/ 100,000 people (n = 26)	N/A
Kajai, C. et al. (2022) (102)	Cross-sectional study	South-East Asia Region	Thailand	447	N/A	M: 180 (40.27%) F: 267 (59.73%)	Psychiatric Inpatient Suicide Risk Assessment (PISRA)	0.22% (n = 1)	N/A	N/A	Stress, stress-coping behaviors
Kaltschik, S. et al. (2022) (103)	Cross-sectional study	European Region	Austria	599	16.65 (1.47)	M: 122 (20.36%) F: 477 (79.63%)	Patient Health Questionnaire-9 (PHQ-9)	6.01% (n = 36)	N/A	N/A	N/A
Kang, S. et al. (2022) (104)	Cross-sectional study	Western Pacific Region	Korea	54,948	No economic impact due to COVID-19: 15.14 (0.02) Economic deterioration due to COVID-19: 15.31 (0.02)	M: 28,353 (51.59%) F: 26,595 (48.41%)	N/A	10.88% (n = 5,979)	2.04% (n = 1,121)	N/A	Economic deterioration, low socioeconomic status
Kantorski, L. P. et al. (2022) (105)	Cross-sectional study	Region of the Americas	Brazil	890	N/A	M: 135 (15.2%) F: 755 (84.8%)	Patient Health Questionnaire-9 (PHQ-9)	7.42% (n = 66)	N/A	N/A	Use of psychotropic drugs
Keyworth, C. et al. (2022) (106)	Cross-sectional study	European Region	United Kingdom	1,029	45.55 (14.23)	M: 340 (33.0%) F: 671 (62.5%) Other/prefer not to say: 18 (1.8%)	History of non‑suicidal self‑harm (NSSH)	7.77% (n = 80)	0.38% (n = 4)	N/A	Higher levels of perceived symptomatic (or physiological) reactions to COVID-19
Kim, D. et al. (2022) (107)	Cross-sectional study	Western Pacific Region	Korea	46,475	N/A	N/A	N/A	10.30% (n = 4,789)	N/A	N/A	N/A
Kim, H. Y. et al. (2022) (108)	Cross-sectional study	Western Pacific Region	Korea	300	N/A	N/A	Patient Health Questionnaire-9 (PHQ-9)	N/A	2.33% (n = 7)	N/A	Fear of COVID-19, depression
Kim, S. et al. (2022) (109)	Cross-sectional study	Western Pacific Region	Korea	973,711	N/A	M: 550,983(56.6%) F:422,728(43.4%)	N/A	N/A	0.30% (n = 2,962)	N/A	N/A
Kirič, B. et al. (2022) (110)	Retrospective study	European Region	Slovenia	1,966	16.28 (1.72)	M: 604 (30.7%) F: 1,362 (69.3%)	N/A	54.48% (n = 1,071)	28.99% (n = 570)	N/A	N/A
Knowles, J. R. P. et al. (2022) (111)	Cross-sectional study	European Region	United Kingdom	12,989	N/A	F: 10,391 (80.0%) M: 2490 (19.2%) Other: 25(0.2%) Prefer not to say/no response: 83 (0.6%)	Kessler Distress Scale	9.28% (n = 1,205)	0.63% (n = 83)	N/A	Food insecurity, domestic abuse, relationship problems, redundancy, social isolation, financial problems
Kone, A. et al. (2022) (112)	Cross-sectional study	Region of the Americas	United States	22,862	N/A	M: 3,853 (16.4%) F: 19,397 (82.6%) Transgender or nonbinary: 220 (0.9%)	Patient Health Questionnaire-9 (PHQ-9)	8.11% (n = 1,853)	N/A	N/A	N/A
Kundu, A. et al. (2022) (113)	Cross-sectional study	Region of the Americas	Canada	1,414	All: 21.90 (3.78) non-suicidal: 23.06 (3.71) Suicidal: 21.22 (3.63)	N/A	N/A	60.61% (n = 857)	N/A	N/A	Mental disorders, substance use, insulted by parents or adults in childhood, age in years, past week feeling depressed, lifetime diagnosis of mental illness, lifetime diagnosis of depressive disorder, past week feeling sad, ever pretending to be straight or cisgender to be accepted, urban areas, unemployed
Lantos, J. D. et al. (2022) (114)	Cross-sectional study	Region of the Americas	United States	9,984	15	M: 4,443 (44.5%) F: 5,540 (55.5%) Missing:1 (0.0%)	Ask Suicide-Screening Questions (ASQ)	12.25% (n = 1,223)	N/A	N/A	Older age, female, public versus private insurance
Li, G. et al. (2022) (115)	Cross-sectional study	Western Pacific Region	China	1,609	N/A	M: 588 (36.5%) F: 1021 (63.5%)	Suicidal Behaviors Questionnaire-Revised (SBQ-R)	31.57% (n = 322)	N/A	N/A	Daytime sleepiness, depression
Li, Y. et al. (2022) (116)	Cross-sectional study	Western Pacific Region	China	67,905	20.23 (1.63)	M: 21,270 (31.3%) F: 46,635 (68.7%)	Patient Health Questionnaire-2 (PHQ-2) Patient Health Questionnaire-9 (PHQ-9)	7.63% (n = 5,178)	N/A	N/A	Short sleep
Li, Y. C. et al. (2022) (117)	Cross-sectional study	Western Pacific Region	China	905	Bipolar disorder: 29.64 (11.58) Schizophre-nia: 32.42 (11.34)	M: 269 (29.73%) F: 636 (70.27%)	Patient Health Questionnaire-2 (PHQ-2)	47.40% (n = 429)	30.27% (n = 274)	N/A	Younger age, experience of cyberbullying, a history of suicide ideation among family or friends, fatigue, physical pain, inpatient status, depression
Liang, Y. J. et al. (2022) (118)	Cross-sectional study	Western Pacific Region	China	1,159	56.1 (6.0)	M: 412 (35.5%) F: 747 (64.5%)	Common mental health problems (CMHPs)	4.06% (n = 47)	N/A	N/A	Marital status of ‘others’ disagreement regarding the successful containment of the pandemic, physical health problems, and common mental health problems (CMHPs)
Lin, C. Y. et al. (2022) (119)	Cross-sectional study	Eastern Mediterranean Region	Iran	10,843	35.54 (12.0)	M: 4,092 (52.3%) F: 6,751 (62.3%)	Patient Health Questionnaire (PHQ-9)	20.77% (n = 2,252)	N/A	N/A	N/A
Liu, R. et al. (2022) (120)	Cross-sectional study	Western Pacific Region	China	1,063	All: 62.80 (9.44) non-suicidal: 63.03 (9.51) Suicidal: 61.02 (8.71)	M: 347 (32.6%) F: 716 (67.4%)	Patient Health Questionnaire (PHQ-9)	11.76% (n = 125)	N/A	N/A	Poor treatment adherence, perceived illness worsening during the COVID-19 outbreak, major depressive disorder, PHQ-9 total score, NPRS total score
Lixia, W. et al. (2022) (121)	Cross-sectional study	Western Pacific Region	China	33,706	N/A	M: 7,846 (23.3%) F: 25,860 (76.7%)	Patient Health Questionnaire-9 (PHQ-9) Patient Health Questionnaire Somatic Symptom Severity Scale-15 (PHQ-15) Suicidal and self-injurious ideation (SSI)	1.33% (n = 447)	N/A	N/A	Female, psychological assistance needs, contact with severe COVID-19 patients, high stress at work, single or divorced marital status, insufficient social support, depression, anxiety, PTSD
Llistosella, M. et al. (2022) (122)	Longitudinal study	European Region	Spain	2,005	N/A	M: 965 (48.5%) F: 1,040 (51.5%)	Suicidal Thoughts and Behaviours (STB)	13.77% (n = 276)	N/A	N/A	Individuals with very low resilience
Llorca-Bofí, V. et al. (2022) (123)	Retrospective study	European Region	Spain	342	N/A	N/A	N/A	13.16% (n = 45)	13.45% (n = 46)	N/A	Female, living with relatives, depression
Ma, Z. et al. (2022) (124)	Cross-sectional study	Western Pacific Region	China	5,670	50.48 (13.21) Non-suicidal: 50.98 (12.87) Suicidal: 48.41 (13.79)	M: 2,978 (52.5%) F: 2,692 (47.5%)	Patient Health Questionnaire-9 (PHQ-9)	13.32% (n = 755)	N/A	N/A	Suicidal ideation: mental disorders, longer time since cancer diagnosis, regional and distant tumor stage, depression, anxiety, hostility, Fear of COVID-19 Suicide attempts: mental disorders
Ma, Z. et al. (2022) (125)	Cross-sectional study	Western Pacific Region	China	67,905	20.23 (1.63)	M: 21,270 (31.33%) F: 46,635 (68.67%)	Patient Health Questionnaire-2 (PHQ-2)	10% (n = 6,791)	N/A	N/A	Depression, mental disorders
MacDonald, B. V. et al. (2022) (126)	Retrospective study	Region of the Americas	United States	3,609	14.8 (2.0)	M: 21,270 (31.33%) F: 46,635 (68.67%)	Patient Health Questionnaire-9 (PHQ-9). Columbia-Suicide Severity Rating Scale (C-SSRS)	1.47% (n = 53)	N/A	N/A	Depression
Mamun, M. A. et al. (2022) (127)	Cross-sectional study	South-East Asia Region	Bangladesh	490	36.97 (10.56)	M: 228 (46.5%) F: 262 (53.5%)	Patient Health Questionnaire-2 (PHQ-2)	33.06% (n = 162)	1.83% (n = 9)	N/A	Males, lower age, lower educational grade, low-earning jobs, living in a government-provided house, family history of mental health and suicide, anxiety, insomnia
Mensi, M. M. et al. (2022) (128)	Cross-sectional study	European Region	Italy	481	All: 15.04 (1.93) M: 14.95 (1.88) F: 15.08 (1.95)	M: 184 (38.25%) F: 297 (61.75%)	N/A	26.90% (n = 144)	N/A	N/A	N/A
Mucci, M. et al. (2022) (129)	Retrospective study	European Region	Italy	241	N/A	N/A	Columbia–Suicide Severity Rating Scale (C-SSRS)	10.37% (n = 25)	19.90% (n = 40)	N/A	N/A
Nomura, K. et al. (2022) (130)	Cross-sectional study	Western Pacific Region	Japan	1,564	20.6 (2.9)	M: 824 (52.7%) F: 617 (39.5%) Unknown:123 (7.9%)	Patient Health Questionnaire-9 (PHQ-9)	7.29% (n = 114)	N/A	N/A	Financial insecurity, academic performance
Park, J. Y. et al. (2022) (131)	Cross-sectional study	Western Pacific Region	Korea	784	14.38 (1.76)	M: 372 (47.4%) F: 412 (52.6%)	N/A	9.18% (n = 72)	2.29% (n = 18)	N/A	Sexual intercourse experience, depressive mood, unhappiness
Que, J. Y. et al. (2022) (132)	Cross-sectional study	Western Pacific Region	China	16,220	N/A	M: 3401 (21%) F: 12,819 (79%)	Patient Health Questionnaire-9 (PHQ-9)	13.35% (n = 2,165)	N/A	N/A	Nightmares but not insomnia, depression, anxiety
Rahman, Q. M. et al. (2022) (133)	Cross-sectional study	South-East Asia Region	Bangladesh	2,100	22.58 (2.22)	M: 1176 (56%) F: 924 (44%)	Suicidal Behaviors Questionnaire-Revised (SBQ-R) scale	47.90% (n = 1,006)	N/A	N/A	Females, keep their distance from friends or family, have relationship problems, are a burden to families, and are stressed about lockdown
Raifman, J. et al. (2022) (134)	Cross-sectional study	Region of the Americas	United States	1,415	46.0 (16.5)	M: 708 (50%) F: 707 (50%)	Patient Health Questionnaire-9 (PHQ-9)	16.33% (n = 231)	N/A	N/A	Difficulty paying rent, feeling alone
Raviv, G. et al. (2022) (135)	Retrospective study	European Region	Israel	15,175,791	N/A	N/A	N/A	N/A	N/A	0.001% (n = 233) per 18.424 100,000/year	N/A
Roy, N. et al. (2022) (136)	Cross-sectional study	South-East Asia Region	Bangladesh	410	30.73 (10.85)	M: 276 (67.3%) F: 134 (44.5%)	N/A	23.90% (n = 98)	N/A	N/A	Age above 35 years, female, acquiring a disability later in life, lack of sleep, and current substance use
Rozental, A. et al. (2022) (137)	Cross-sectional study	European Region	Sweden	4,513	35.05 (12.1)	M: 1,072 (23.7%) F: 3,210 (71.1%) Non-binary: 231 (5.2%)	Patient Health Questionnaire (PHQ-9)	54.72% (n = 2,335)	0.02% (n = 1,384)	N/A	N/A
Sacco, D. L. et al. (2022) (138)	Retrospective study	Region of the Americas	United States	615	43.3 (15.5)	M: 331 (53.8%) F: 284 (46.2%)	N/A	31.38% (n = 193)	N/A	N/A	N/A
Sasaki, N. et al. (2022) (139)	Cross-sectional study	Western Pacific Region	Japan	12,249	43.29 (11.70)	M: 7,095 (57.9%) F: 5,154 (42.1%)	N/A	8.50% (n = 1,041)	N/A	N/A	Temporary employment
Schluter, P. J. et al. (2022) (140)	Cross-sectional study	1. Region of the Americas: Canada, United States. 2. European Region: England, Switzerland, Belgium. 3. Western Pacific Region: Hong Kong, Philippines, New Zealand	8-country (Canada, the United States, England, Switzerland, Belgium, Hong Kong, Philippines, and New Zealand)	17,883	N/A	M: 8,629 (48.4%) F: 9,204 (51.6%)	Patient Health Questionnaire-9 (PHQ-9)	25.82% (n = 4,617)	N/A	N/A	N/A
Shiraly, R. et al. (2022) (141)	Cross-sectional study	Eastern Mediterranean Region	Iran	803	All: 68.1 (4.73) Non-suicidal: 67.8 (4.7). Suicidal: 68.1 (4.8)	M: 408 (50.8%) F: 395 (49.2%)	Patient Health Questionnaire-2 (PHQ-2) Ask Suicide-Screening Questionnaire (ASQ)				Depression, not being married, inability to pay medical bills, low perceived social support, and limited social network
Smirnova, D. et al. (2022) (142)	Cross-sectional study	European Region	Russian Federation	7,777	32.9 (11.94)	M: 2,836 (36.47%) F: 4,736 (60.90%) Other: 205 (2.64%)	Risk Assessment Suicidality Scale (RASS)	16.63% (n = 1,293)	N/A	N/A	N/A
Stickley, A. et al. (2022) (143)	Cross-sectional study	Western Pacific Region	Japan	1,452	N/A	M: 704 (48.5%) F: 748 (51.5%)	Patient Health Questionnaire-9 (PHQ-9)	11.71% (n = 170)	N/A	N/A	Attention deficit hyperactivity disorder (ADHD)
Suarez-Soto, E. et al. (2022) (144)	Cross-sectional study	European Region	Spain	160	15.81 (1.03)	M: 53 (33.1%) F: 107 (66.9%)	The DetectaWeb-Distress scale	20.63% (n = 33)	7.50% (n = 12)	N/A	N/A
Sueki, H. et al. (2022) (145)	Prospective study	Western Pacific Region	Japan	6,683	46.5 (13.8) non-suicidal: 49.2 (13.9). Suicidal: 43.5 (13)	M: 3,422 (51.2%) F: 3261 (48.8%)	N/A	47.36% (n = 3,165)	N/A	N/A	Younger, with unstable employment, without children, with low income, receiving psychiatric care
Turner, B. J. et al. (2022) (146)	Cross-sectional study	Region of the Americas	Canada	809	15.67 (1.37)	M: 353 (44%) F: 453 (56%)	N/A	17.25% (n = 139)	N/A	N/A	Youth, transgender, non-binary, or gender fluid, not residing with both parents, psychiatric concerns, frequent cannabis use
Valladares-Garrido, M. J. et al. (2022) (147)	Cross-sectional study	Region of the Americas	Peru	514	22	M: 492 (95.7%) F: 22 (4.3%)	N/A	14.01% (n = 72)	N/A	N/A	Family history of mental health, insomnia, and anxiety
Villanueva-Silvestre, V. et al. (2022) (148)	Cross-sectional study	European Region	Spain	921	24.8 (3)	M: 385 (45%) F: 507 (55%)	Patient Health Questionnaire-9 (PHQ-9)	6.51% (n = 60)	N/A	N/A	N/A
Villarreal Sotelo, K. et al. (2022) (149)	Cross-sectional study	Region of the Americas	Mexico	659	22.56 (7.26)	F: 465 (70.5%) M: 194 (29.5%)	N/A	39.94% (n = 262)	18.29% (n = 120)	N/A	Female, knowing a person infected with COVID-19, confinement for more than 40 days
Walther, A. et al. (2022) (150)	Cross-sectional study	European Region	Germany, Switzerland, Austria, Liechtenstein, Luxembourg, and Belgium	490	25.7 (9.7)	M: 490 (100%) F: 0 (0%)	Patient Health Questionnaire-9 (PHQ-9)	49.98% (n = 240)	23.27% (n = 114)	N/A	Status loss, depression
Wathelet, M. et al. (2022) (151)	Cross-sectional study	European Region	France	44,898	19	M: 12,429 (27.7%) F: 31,728 (70.7%) Other: 741 (1.6%)	Beck Depression Inventory (BDI)	13.80% (n = 6,196)	N/A	N/A	Nonbinary respondents
Wong, S. M. Y. et al. (2022) (152)	Cross-sectional study	Western Pacific Region	China	2,540	N/A	N/A	Columbia–Suicide Severity Rating Scale (C-SSRS). Beck’s Hopelessness Inventory (BDI)	20.98% (n = 533)	N/A	N/A	Suicidal ideation: suicide-related rumination, poorer cognitive ability, 12-month major depressive disorder Suicide attempt: COVID-19 stressors, poorer family functioning, personal life stressors, and non-suicidal self-harm
Wu, O. et al. (2022) (153)	Cross-sectional study	Western Pacific Region	China	686	17.79 (0.78)	M: 438 (63.85%) F:248 (36.15%)	N/A	5.25% (n = 36)	N/A	N/A	Social avoidance, emotional vulnerability
Yamashita, T. et al. (2022) (154)	Cross-sectional study	Western Pacific Region	Japan	310	26.0 (5.1)	M: 124 (62%) F:248 (38%)	Patient Health Questionnaire-9 (PHQ-9)	14.84% (n = 46)	N/A	N/A	Age, experience of deprivation about food expenses, deprivation about cellphone bills
Yamazaki, J. et al. (2022) (155)	Cross-sectional study	Western Pacific Region	Japan	113	N/A	M:62 (63.3%) F: 36 (36.7%)	Mini International Neuropsychiatric Interview (MINI)	17.70% (n = 20)	N/A	N/A	Less frequent conversations (those with less than one conversation per week)
Yu, Y. et al. (2022) (156)	Cross-sectional study	Western Pacific Region	China	1,248	16.80	F: 831 (66.59%) M: 417 (33.41%)	N/A	14.34% (n = 179)	8.17% (n = 102)	N/A	Suffered family hurt, junior and senior school, and sexism
Zhang, L. et al. (2022) (157)	Cross-sectional study	Western Pacific Region	China	1,718	31.59 (14.43)	M: 479 (29.9%) F:1,239(70.1%)	N/A	33.35% (n = 577)	39.35% (n = 676)	N/A	Urban, unemployed, cyberbullying, history of suicide among family or friends, fatigue, physical pain, depression
Zhu, J. et al. (2022) (158)	Cross-sectional study	Western Pacific Region	China	5,175	13.37 (0.02)	M: 2,673 (51.65%) F:2,502 (48.35%)	N/A	20.83% (n = 1,078)	11.79% (n = 610)	N/A	Female, quarreling with parents, insomnia Male: Quarreling with parents, insomnia, previous suicide attempt history, previous SI history, and feeling depressed during the lockdown pandemic Female: having emptiness inside, quarreling with parents, insomnia, feeling anxious, and longing for father's emotional warmth
Alberto Gómez-García, J. A. et al. (2023) (159)	Cross-sectional study	Region of the Americas	Mexico	79,665	N/A	M: 31,258 (39.3%) F:48,407 (60.7%)	N/A	16.22% (n =  12,918)	N/A	N/A	Female, young women, education, single, unemployment, social distancing, living alone, loss of family member due to COVID-19, depression, physical violence, excessive alcohol consumption, drug use, suspicion or diagnosis of COVID-19
Bowersox, N. W. et al. (2023) (160)	Retrospective study	Region of the Americas	United States	52,916	No SMI: 59.93 (16.84) SMI: 59.57 (14.74)	M: 46,938 (88.7%) F: 5,978 (11.3%)	N/A	1.09% (n = 579)	N/A	N/A	N/A
Cai, H. et al. (2023) (161)	Cross-sectional study	Western Pacific Region	China	1,009	15.3 (2.1)	N/A	Patient Health Questionnaire-9 (PHQ-9)	14.07% (n = 142)	7.82% (n = 79)	N/A	Depression, anxiety
Carlos, K. M. et al. (2023) (162)	Cross-sectional study	Region of the Americas	United States	134	25.75 (2.3)	M: 71 (44.4%) F: 89 (55.6%)	Patient Health Questionnaire-9 (PHQ-9)	23 (17.16%)	N/A	N/A	Higher levels of impostor feelings
Castellvi Obiols, P. et al. (2023) (163)	Longitudinal study	European Region	Spain	1,357	N/A	N/A	Suicidal thoughts and behaviors (STB)	7.66% (n = 104)	0.36% (n = 5)	N/A	N/A
Chen, C. et al. (2023) (164)	Cross-sectional study	Western Pacific Region	Japan	5,688	N/A	N/A	N/A	857 (15.07%)	N/A	N/A	History of psychiatric disorders, infectious disease other than colds during pregnancy, and feeling of loneliness
Chen, X. et al. (2023) (165)	Cross-sectional study	Western Pacific Region	China	1,297	N/A	M: 563 (56.60%) F: 734 (43.40%)	N/A	6.71% (n = 87)	N/A	N/A	History of psychological or emotional counseling before COVID-19 infection, fatigue, higher self-reported COVID-19 related stigma, sleep disorder
Davies, H. L. et al. (2023) (166)	Cross-sectional study	European Region	United Kingdom	36,715	N/A	M: 10,874 (29.6%) F: 25,728 (70.1%) Missing: 113 (0.3%)	N/A	49.14% (n =  18,040)	N/A	N/A	Having a lifetime psychiatric disorder, not being in paid employment, higher pandemic worry scores, and being racially minoritized
Vega Sánchez, D. de la. et al. (2023) (167)	Cross-sectional study	European Region	Spain	3,140	47.8	M: 1,990 (63.4%) F: 1,140 (36.3%) Not specified: 10 (0.3%)	N/A	17.32% (n = 544)	N/A	N/A	Female, presence of previous suicide attempts, taking a psychotropic drug, working in a different area during the pandemic
Essadek, A. et al. (2023) (168)	Cross-sectional study	European Region	France	823	21.23 (2.11)	M: 413 (50.18%) F: 410 (49.82%)	Patient Health Questionnaire-9 (PHQ-9)	209 (25.39%)	N/A	N/A	Food insecurity (less than one meal per day)
Fischer, I. C. et al. (2023) (169)	Cross-sectional study	Region of the Americas	United States	2,441	63.2 (14)	M: 2182 (92.1%) F: 259 (7.9%)	Suicidal Behaviors Questionnaire-Revised \(SBQ-R)	207 (8.48%)	74 (3.03%)	N/A	Higher education, lifetime substance use disorder, pre-pandemic loneliness, lower pre-pandemic purpose in life, higher pre-pandemic psychiatric distress, and lower pre-pandemic purpose in life
Frajerman, A. et al. (2023) (170)	Cross-sectional study	European Region	France	18,875	N/A	M: 2182 (14.5%) F: 97 (85.5%)	Composite International Diagnostic Interview -Short Form (CIDI-SF) questionnaire	1,690 (8.95%)	N/A	N/A	Study field (human/social sciences), having failed midterms exams or dropout, and important subjective financial difficulties
Gibb, K. et al. (2023) (171)	Cross-sectional study	Region of the Americas	United States	21,949	N/A	M: 1,990 (63.4%) F: 1,140 (36.3%) Not specified: 10 (0.3%)	N/A	33.0% (n = 7,243)	N/A	N/A	Production and service workers were the priority occupation groups for depressed mood
Gomez-Garcia, J. A. et al. (2023) (172)	Cross-sectional study	Region of the Americas	Mexico	79,665	N/A	M: 31,258 (39.3%) F: 48,407 (60.7%)	N/A	12,918 (16.22%)	N/A	N/A	Being a woman, young women, education, single, unemployment, social distancing, living alone, loss of family member due to Covid-19, depression diagnosis, physical violence, excessive alcohol consumption, drug use, and suspicion or diagnosis of Covid-19
Hall, B. J. et al. (2023) (173)	Cross-sectional study	Western Pacific Region	China	3,230	32	M: 1,657 (55.5%) F: 1,563 (44.3%)	Patient Health Questionnaire-9 (PHQ-9) Ask Suicide-Screening Questions (ASQ)	4.49% (n = 145)	N/A	N/A	Lockdown stressors: food insecurity, job and income loss, lockdown-related fears
Han, K. M. et al. (2023) (174)	Cross-sectional study	Western Pacific Region	Korea	1,364	N/A	M: 767 (56.23%) F: 597 (43.77%)	Patient Health Questionnaire-9 (PHQ-9)	325 (23.83%)	N/A	N/A	Job loss, lower income, lower education level
Hannan, C. et al. (2023) (175)	Cross-sectional study	Region of the Americas	United States	121,380	15.7	M: 50,750 (50.1%) F: 50,531 (49.9%)	Patient Health Questionnaire-Modified (PHQ-9-M)	5.79% (n = 7,029)	N/A	N/A	Depression
He, Z. et al. (2023) (176)	Cross-sectional study	Western Pacific Region	China	10,388	35.5 (8.1)	M: 3,032 (29.2%) F: 7,356 (70.8%)	Patient Health Questionnaire-9 (PHQ-9)	8.84% (n = 918)	N/A	N/A	Moral injury, medical error, workplace violence, depression, anxiety, PTSD
Kasal, A. et al. (2023) (177)	Cross-sectional study	European Region	Czech	6,021	46 (29)	M: 2,906 (48.3%) F: 3,115 (51.7%)	Mini International Neuropsychiatric Interview (MINI)	13.22% (n = 796)	N/A	N/A	Mental disorders
Landi, G. et al. (2023) (178)	Cross-sectional study	European Region	Italy	652	38.8 (13.2)	M: 161 (24.7%) F: 491 (75.3%)	Patient Health Questionnaire-9 (PHQ-9)	15.31% (n = 100)	N/A	N/A	Mental pain intensity
Lee, E. W. et al. (2023) (179)	Cross-sectional study	Western Pacific Region	Korea	2,000	N/A	M: 1016 (50.8%) F: 984 (49.2%)	Patient Health Questionnaire-9 (PHQ-9)	166 (8.3%)	N/A	N/A	Women whose economic status worsened
Li, S. et al. (2023) (180)	Cross-sectional study	Western Pacific Region	China	14,690	N/A	M: 6,271 (42.69%) F: 8,419 (57.31%)	Patient Health Questionnaire-9 (PHQ-9)	9.04% (n = 1,328)	N/A	N/A	Ethnic minority, age, history of mental disorders, daily life disturbance due to health problems, being around someone with COVID-19, being uncertain about effective disease control, and having depressive symptoms, insomnia symptoms, and psychological distress
Li, Z. Y. et al. (2023) (181)	Cross-sectional study	Western Pacific Region	China	1,343	26	M: 428 (31.87%) F: 915 (68.13%)	Patient Health Questionnaire-9 (PHQ-9)	130 (9.68%)	N/A	N/A	Depression
Lippard, E. T. C. et al. (2023)	Cross-sectional study	Region of the Americas	United States	214	33	M: 428 (31.87%) F: 915 (61%)	Center for Epidemiologic Studies Depression Scale (CES-D)	90 (45.33%)	N/A	N/A	Frequency of alcohol use, drugs use, PTSD symptoms, perceived early life trauma, COVID-related worry
Liu, L. et al. (2023) (182)	Cross-sectional study	Region of the Americas	Canada	18,936	N/A	M: 8,082 (49.2%) F:10,818 (50.6%)	N/A	3.06% (n = 579)	N/A	N/A	Adverse experiences related to the pandemic, alcohol or cannabis use, violence in their home, depression, anxiety, and post-traumatic stress disorder
Lo, H. K. Y. et al. (2023)	Cross-sectional study	Western Pacific Region	China	407		M: 261 (65.6%) F:146 (34.4%)	Patient Health Questionnaire-9 (PHQ-9)	128 (31.45%)	N/A	N/A	Depression
Lu, Y. et al. (2023)	Cross-sectional study	Western Pacific Region	China	1,901	31.31 (6.04)	M: 70 (3.7%) F: 1831 (96.3%)	Patient Health Questionnaire-9 (PHQ-9)	320 (16.83%)	206 (10.84%)	N/A	Workplace bullying
Martínez-Arriaga, R. J. et al. (2023) (183)	Cross-sectional study	Region of the Americas	Mexico	626	All: 35 (8.4) non-suicidal: 35.8 (8.5) Suicidal: 34.4 (8.3)	M: 106 (17%) F: 515 (82.7%) Other: 2 (0.3%)	N/A	49.20% (n = 308)	1.75% (n = 11)	N/A	Secondary traumatic stress, high depressive affect, low positive affect, emotional insecurity, interpersonal problems, and medication use
Narita, Z. et al. (2023) (184)	Cross-sectional study	Region of the Americas	United States	1,071	N/A	M: 509 (48.6%) F: 538 (51.4%)	Patient Health Questionnaire-2 (PHQ-2) Columbia-Suicide Severity Rating Scale	30.16% (n = 323)	N/A	N/A	Consistently self-isolated
Narita, Z. et al. (2023) (185)	Cross-sectional study	Western Pacific Region	Japan	2,862	39.5 (12.0)	M: 856 (29.9%) F: 2,006 (70.1%)	Patient Health Questionnaire-9 (PHQ–9)	3.77% (n = 108)	N/A	N/A	COVID-19-related discrimination, depression
Nguyen, T. H. et al. (2023) (186)	Retrospective study	Region of the Americas	United States	13,605	15 (1.7)	M: 856 (50.6%) F: 2,006 (49.4%)	N/A	18.50% (n = 2,517)	8.90% (n = 1,211)	N/A	Bullied
Ramos-Martín, J. et al. (2023) (187)	Cross-sectional study	European Region	Spain	2,212	21.28 (2.51)	M: 672 (30.4%) F: 1,540 (69.6%)	Self-Injurious Thoughts and Behaviors Interview (SITBI)	744 (33.36%)	5.74%	N/A	Psychological distress, and family and social support
Reinke, M. et al. (2023) (188)	Cross-sectional study	Region of the Americas	United States	172,113,599	N/A	F: 99,028,073 (57.5%) M: 73,085,526 (38.1%)	N/A	0.09% (n =  160,320)	0.01% (n =  19,719)	N/A	COVID-19 patients
Roy, N. et al. (2023) (189)	Cross-sectional study	South-East Asia Region	Bangladesh	410	30.73 (10.85)	M: 276 (67.3%) F: 134 (32.7%)	Depression, Anxiety, and Stress Scale (DASS-21)	98 (23.9%)	N/A	N/A	Age above 35 years, being female, acquiring a disability later in life, lack of sleep and current substance use
Rukundo, G. Z. et al. (2023) (190)	Cross-sectional study	African Region	Uganda	431	40	M: 120 (27.8%) F: 311 (72.2%)	Self-reported suicidal thoughts and severe distress (IES-R)	22.04% (n = 95)	N/A	N/A	Depression
Seidler, Z. E. et al. (2023) (191)	Cross-sectional study	Western Pacific Region	Australia	700	50.3 (15.2)	Heterosexual: 495 (70.7%) Gay: 150 (21.4%) Bisexual: 43 (6.1%) Other: 12 (1.7%)	Brief Coping Orientation to Problems Experienced inventory (Brief-COPE)	203 (29%)	N/A	N/A	Employment, and social support
Solomonov, N. et al. (2023) (192)	Cross-sectional study	Region of the Americas	United States	16,164	70.9 (5.0)	M: 6233 (29.6%) F: 9931 (61.4%)	Patient Health Questionnaire-9 (PHQ–9)	1,144 (7.08%)	N/A	N/A	Social support
Sotelo, K. V. et al. (2023) (193)	Cross-sectional study	Region of the Americas	Mexico	659	22.56 (7.26)	M: 194 (29.5%) F: 465 (70.5%)	Severity Rating Scale	39.94% (n = 262)	18.29% (n = 120)	N/A	Female, knowing a person infected with COVID-19, Confinement for more than 40 days
Tachikawa, H. et al. (2023) (194)	Cross-sectional study	Western Pacific Region	Japan	11,816	N/A	M: 6,436 (54.4%) F: 5,380 (45.6%)	Kessler Psychological Distress Scale (K6)	15.66% (n = 1,850)	N/A	N/A	Female, loneliness
Tantirattanakulchai, P. et al. (2023) (195)	Cross-sectional study	South-East Asia Region	Thailand	314	71.42 (7.83)	M: 130 (41.4%) F: 184 (58.6%)	Columbia–Suicide Severity Rating Scale (C-SSRS)	32.48% (n = 102)	N/A	N/A	Diabetic retinopathy, depression
Turner, B. J. et al. (2023) (196)	Cross-sectional study	Region of the Americas	Canada	16,972	N/A	N/A	Patient Health Questionnaire-9 (PHQ–9)	5.06% (n = 859)	N/A	N/A	Suspected or confirmed COVID-19 exposure, potential COVID-19 exposure at work, medical vulnerability toward COVID-19, insecure employment or unemployment, income loss
Valentini, E. et al. (2023) (197)	Retrospective study	European Region	Italy	850	N/A	M: 430 (49.4%) F: 420 (50.6%)	N/A	14.12% (n = 120)	N/A	N/A	Females, separated, personality disorders, borderline personality disorder
Varin, M. et al. (2023) (198)	Cross-sectional study	Region of the Americas	Canada	14,689	N/A	N/A	Patient Health Questionnaire-9 (PHQ–9)	2.57% (n = 316)	N/A	N/A	Alcohol use
Wei, Y. et al. (2023) (199)	Cross-sectional study	Western Pacific Region	China	1,338	26	M: 426 (31.8%) F: 912 (68.20%)	Patient Health Questionnaire-9 (PHQ–9)	130 (9.72%)	N/A	N/A	Loneliness, social isolation, and mental disorders
Zhang, X. et al. (2023) (200)	Retrospective study	Western Pacific Region	China	674	N/A	N/A	N/A	N/A	33.83% (n = 228)	N/A	N/A

CI—Confidence Interval, M: Male, F: Female, JBI: Joanna Briggs Institute

A total of 144 studies incorporated suicide assessment tools, predominantly utilizing the Patient Health Questionnaire in 86 studies followed by the Columbia Suicide Severity Rating Scale (C-SSRS) in 9 studies. Furthermore, the Suicidal Behaviors Questionnaire-Revised (SBQ-R) was employed in 7 studies. Regarding study design, four studies were conducted as case–control studies, 169 as cross-sectional studies, 20 as retrospective studies, four as longitudinal studies, two as prospective studies, one as a cohort study, one as an observational study, and one as a quasi-experimental study. The studies included in this analysis were published between 2020 and 2023, with 138 studies published in the last two years (2022 and beyond) (Table 1).

Participant Characteristics

The collective participant counts across the 200 studies amounted to 19,815,536. Among these, 88 studies comprised male participants, totaling 321,155 individuals, while 89 studies incorporated female participants, with a cumulative total of 486,261. Four studies included transgender participants, accounting for 385 individuals, and 10 studies categorized participants as "other," with an aggregated total of 2,497 individuals. Additionally, 29 studies provided information on participants' age distribution, with four studies including participants aged over 18 years, 29 studies including individuals aged 18–24 years, another 29 studies involving those aged 25–34 years, 29 studies [22–50] encompassing participants aged 35–44 years, 26 studies featuring individuals aged 45–54 years, 18 studies with participants aged 55–64 years, and 12 studies involving individuals aged 65 years and above (Table 1).

Regarding suicidal behavior during the COVID-19 pandemic, 41 studies evaluated both suicidal ideation and suicide attempts, 186 studies solely examined the prevalence of suicidal ideation, 56 studies focused on the prevalence of suicide attempts, and three studies assessed the incidence of death by suicide (Table 1).

Prevalence of Suicidal Behavior During the COVID-19 Pandemic

The manuscript focuses on the prevalence and incidence of suicidal behavior during the COVID-19 pandemic. A total of 184 studies analyzed the prevalence of suicidal ideations, 56 studies examined the prevalence of suicidal attempts, and 5 studies investigated the prevalence of death by suicide. Suicide behavior events were reported in 228,342 out of 19,815,536 participants. Among these, three studies conducted in Multiple areas demonstrated the highest rates (25.9%) of suicide behavior events, while five studies in the Eastern Mediterranean region showed the highest rates (18%) of such events. Following a meta-analysis, the pooled prevalence of suicide behavior during the COVID-19 pandemic was determined to be 11.5% (95% CI: 9.9–13.3%, p < 0.001) across 202 studies, indicating a high level of heterogeneity (I² = 99.92, Q = 253533.416, Tau2 = 1.428, p < 0.001, Table 2).

Table 2.

Meta- analysis and Meta-regression according to subgroup used to identify factors affecting heterogeneity in included studies

Meta- analysis and meta-analysis		Meta- analysis					Meta-regression
Variable	No of study	Suicide (n)	Sample (n)	Prevalence (%) (95% CI)	p-value	I2	Coefficient	Standardized error	95% confidence interval	p-value
Prevalence rate (%)	202	228,342	19,815,536	11·5 (9·9–13·3)	< 0·001	99·92
Incidence rate (per 100,000 people year)	4	3,082	16,264,211	55·28 (20·1–90·5)	< 0·001	99·97
Sex	89	115,535	810,298	13·7 (12·3–15·4)	< 0·001	99·72
Male	88	42,161	321,155	12·1 (10·0–14·4)	< 0·001	99·69	Reference
Female	89	72,520	486,261	14·4 (12·2–16·8)	< 0·001	99·77	0·199	0·138	− 0·072–0·470	0·151
Transgender	4	274	385	44·8 (16·8–76·5)	< 0·001	91·32	1·847	0·534	0·800–2·894	< 0·001
Other	10	580	2,497	20·2 (11·9–32·1)	< 0·001	95·12	0·596	0·349	− 0·089–1·282	0·088
Age	29	63,215	1,356,357	10·5 (8·5–13·0)	< 0·001	99·84
55 ~ 64 years old	17	6,200	28,680	5·3 (2·2–12·0)	< 0·001	99·72	Reference
≥ 65 years old	12	4,860	14,687	7·2 (1·7–25·3)	< 0·001	99·65	0·383	0·478	− 0·555–1·322	0.423
45 ~ 54 years old	26	8,343	58,996	9·3 (6·0–14·1)	< 0·001	99·65	0·597	0·389	− 0·166–1·362	0·125
35 ~ 44 years old	28	12,444	96,212	12·5 (9·3–16·4)	< 0·001	99·55	0·905	0·384	0·151–1·660	0·018
25 ~ 34 years old	29	14,973	99,687	12·5 (9·8–15·9)	< 0·001	99·46	0·915	0·381	0·168–1·663	0.016
18 ~ 24 years old	29	11,209	70,112	16·0 (12·8–19·8)	< 0·001	99·21	1·197	0·381	0·450–1·944	0·001
> 18 years old	4	5,186	987,983	5·6 (0·4–48·4)	< 0·001	99·98	0·045	0·680	− 0·288–1·379	0·946
Marital status	44	42,380	325,095	14·1 (14·1–12·4)	< 0·001	99·37
Marriage	43	22,027	190,044	10·8 (8·8–13·1)	< 0·001	99·48	Reference
Unmarried	44	17,927	117,598	14·9 (11·8–18·7)	< 0·001	99·49	0·376	0·177	0·029–0·724	0·033
Separated/ divorced /widowed	24	2,213	15,184	22·1 (16·2–29·4)	< 0·001	97·68	0·844	0·217	0·417–1·271	< 0·001
Partner	5	213	325,095	12·2 (7·4–19·5)	< 0·001	90·11	0·162	0·405	− 0·632–0·957	0·688
Education level	43	67,556	420,043	15·2 (13·0–17·7)	< 0·001	99·73
University or higher	29	20,773	116,165	12·3 (9·0–16·5)	< 0·001	99·71	Reference
Junior college	43	30,607	236,728	14·7 (11·4–18·7)	< 0·001	99·76	0.210	0·240	− 0·261–0·682	0·381
High school or lower	37	16,176	67,150	18·4 (13·5–24·6)	< 0·001	99·64	0.489	0·249	0·001–0·978	0·049
Employment status	19	36,552	226,072	16·9 (14·7–19·5)	< 0·001	99·37
Employment	33	14,679	100,883	16·2 (11·9–21·7)	< 0·001	99·60	Reference
Unemployment	30	19,732	109,059	20·9 (16·5–26·2)	< 0·001	99·54	0·306	0·237	− 0·159–0·771	0·197
Retired	9	157	1,623	6·3 (2·5–14·8)	< 0·001	95·33	− 0·979	0·386	− 1·737– − 0·221	0·011
Housewife	11	855	5,356	17·1 (9·5–28·6)	< 0·001	99·05	0·066	0·338	− 0·597–0·730	0·844
Student	13	871	8,409	18·0 (10·6–28·9)	< 0·001	97·99	0·118	0·314	− 0·499–0·735	0·707
Other	7	258	742	13·8 (3·4–42·3)	< 0·001	96·55	− 0·128	0·437	− 0·986–0·729	0·769
Monthly income	26	24,754	181,169	15·2 (13·2–17·6)	< 0·001	99·21
High income	24	6,210	56,275	13·1 (10·2–16·7)	< 0·001	98·78	Reference
Medium income	24	7,536	60,303	15·5 (11·6–20·3)	< 0·001	99·29	0.197	0·221	− 0·237–0·632	0·372
Low income	26	10,251	50,921	19·9 (15·7–24·8)	< 0·001	99·05	0·498	0·218	0·070–0·926	0·022
Other	3	757	13,670	7·6 (2·9–18·4)	< 0·001	98·60	− 0·601	0·480	− 1·543–0·341	0·211
Income worries	3	2,071	56,450	15·3 (3·9–44·2)	< 0·001	99.88
Income worries	3	1,389	18,747	17·3 (2·5–62·7)	< 0·001	99·90	Reference
No income worries	3	682	37,703	13·5 (1·0–70·0)	< 0·001	99·59	0.300	1.565	− 2.767 − 3.368	0·847
Profession	7	6,708	83,081	9·3 (6·5–13·0)	< 0·001	99·42
Medicine	6	627	20,038	7·1 (2·3–19·9)	< 0·001	99·44	Reference
Nurse	7	2,294	33,347	10·4 (5·3–19·4)	< 0·001	99·58	0.430	0.586	− 0.718 − 1.580	0·462
Allied health/ Other medical	6	477	9,250	7·9 (3·3–17·4)	< 0·001	98·78	0.119	0.609	− 1.076 − 1.314	0·844
Other	5	3,310	20,446	13·1 (7·8–21·2)	< 0·001	97·71	0.698	0.639	− 0.555 − 1.952	0·275
Having children	7	12,359	83,350	11·0 (6·9–17·1)	< 0·001	99·77
No children	7	9,792	62,369	9·3 (4·0–19·9)	< 0·001	99·71	Reference
Having children	7	2,567	20,981	13·0 (6·4–24·7)	< 0·001	99·83	− 0·382	0·589	− 1·537–0·773	0·516
Lives alone	13	17,526	125,130	17·4 (14·5–20·6)	< 0·001	98·90
No lives alone	13	14,654	106,664	13·0 (10·0–16·8)	< 0·001	99·14	Reference
Lives alone	13	2,872	18,466	24·3 (17·4–32·9)	< 0·001	98·49	0·732	0·243	0·255–1·209	0.002
Religion	5	1,344	13,311	15·9 (11·5–21·5)	< 0·001	95·79
Religion	5	352	2,371	16·5 (10·4–25·3)	< 0·001	94·93	Reference
No religion	5	992	10,940	14·4 (9·6–21·1)	< 0·001	92·41	− 0·121	0·360	− 0·828–0·585	0.736
House type	4	1,408	8,888	14·6 (11·7–18·2)	< 0·001	93·20
High	4	383	3,397	10·0 (5·4–17·7)	< 0·001	95·41	Reference
Middle	4	473	2,913	15·7 (13·3–18·6)	0·075	56·54	0·387	0·305	− 0·212–0·986	0.205
Lower	4	543	2,511	21·7 (17·5–26·0)	0·035	65·21	0·765	0·314	0·149–1·381	0.014
Other	1	9	67	13·4 (7·1–23·8)	1·00	0·00	0·267	0·563	− 0·836–1·372	0.634
Resident type	4	1,341	3,437	34·2 (22·0–49·1)	< 0·001	98·21
Own	4	1,037	2,509	28·7 (12·2–53·9)	< 0·001	99·15	Reference
Rented	4	212	571	44·7 (20·8–71·4)	< 0·001	96·95	0·692	0·760	− 0·801–2·185	0.363
Hostel/ mess	2	92	357	27·3 (12·4–49·8)	< 0·001	93·77	− 0·073	0·929	− 1·894–1·748	0.937
Residence	24	31,712	236,762	14·0 (12·1–16·6)	< 0·001	99·49
Rural/ Regional	24	8,218	67,120	14·1 (11·0–18·0)	< 0·001	99·10	Reference
Urban	24	23,494	169,120	14·2 (11·2–17·9)	< 0·001	96·65	− 0·163	0·369	− 0·886–0·560	0.659
Low social support	3	384	9,237	4·8 (2·6–8·7)	< 0·001	96·99
No low social support	3	126	5,943	2·6 (1·6–4·1)	0·001	85·08	Reference
Low social support	3	258	3,294	8·4 (6·3–11·0)	0·018	75·27	1·266	0·281	0·715–1·818	< 0·001
Physical exercise	3	775	15,316	7·2 (3·1–16·2)	< 0·001	99·26
Physical exercise	3	243	6,403	5·8 (1·7–17·8)	< 0·001	98·74	Reference
No physical exercise	3	532	8,913	9·0 (2·2–29·9)	< 0·001	99·56	0·467	1·011	− 1·514–2·450	0·643
Satisfaction with studies	3	5,335	50,537	12·2 (9·5–15·7)	< 0·001	98·46
Satisfaction with studies	3	2,987	33,278	8·9 (6·0–12·9)	< 0·001	93·80	Reference
Dissatisfaction with studies	3	2,348	17,259	16·4 (12·6–21·0)	< 0·001	94·83	0·701	0·247	0·216–1·186	0·004
Suicidal attempt history	5	583	7,427	18·7 (6·5–43·3)	< 0·001	99·11
No suicidal attempt history	5	469	7,054	6·0 (1·0–29·1)	< 0·001	99·56	Reference
Suicidal attempt history	5	114	373	43·4 (21·2–68·5)	< 0·001	92·45	2·704	1·284	0·186–5·221	0·035
Family history of suicidal	6	3,139	8,740	44·4 (30·2–59·5)	< 0·001	99·25
No family history of suicidality	6	2,075	6,916	31·0 (16·1–51·2)	< 0·001	99·52	Reference
Family history of suicidal	6	1,064	1,824	59·5 (36·1–79·2)	< 0·001	97·85	1·193	0·632	− 0·046–2·433	0·059
Tested positive for COVID-19	17	18,239	148,066	21·3 (16·0–27·9)	< 0·001	99·61
Negative	16	14,429	130,197	16·9 (10·1–26·7)	< 0·001	99·76	Reference
Positive	17	2,872	13,423	29·2 (17·2–45·0)	< 0·001	98·74	0·695	0·440	− 0·168–1·560	0·114
Untested	2	938	4,446	21·1 (20·0–22·4)	0·187	42·54	− 0·277	1·063	− 2·360–1·806	0·794
Experiencing COVID-19 like symptoms	3	233	2,136	9·1 (4·9–16·5)	< 0·001	93·63
Never	3	180	885	16·8 (10·4–26·0)	< 0·001	87·81	Reference
Fewer	3	26	608	7·4 (0·9–40·4)	< 0·001	95·72	− 0·312	0·844	− 1·966–1·341	0·711
Frequently	3	21	313	10·1 (1·5–45·5)	< 0·001	93·05	− 0·787	0·827	− 2·409–0·833	0·341
Almost times	2	6	330	3·7 (0·4–27·6)	0·010	84·92	− 1·580	0·989	− 3·518–0·358	0·110
Fear of getting severely sick or dying	10	3,651	40,826	13·8 (10·3–18·2)	< 0·001	98·72
Fear of getting severely sick or dying	10	2,323	23,959	14·6 (9·6–21·6)	< 0·001	98·99	Reference
No fear of getting severely sick or dying	10	1,328	16,867	13·0 (8·1–20·3)	< 0·001	98·40	0·134	0·358	− 0·567–0·836	0·707
Family member tested positive for COVID-19	7	2,730	31,946	10·5 (6·9–15·9)	< 0·001	99·10
Negative	7	2,117	28,136	8·6 (4·8–15·0)	< 0·001	99·38	Reference
Positive	7	613	3,810	13·2 (7·2–23·0)	< 0·001	97·08	0·475	0·466	− 0·438–1·388	0·307
Know who died of COVID-19	5	13,866	85,727	19·0 (14·3–24·9)	< 0·001	99·07
Unknow	5	11,779	76,792	16·0 (9·4–25·9)	< 0·001	99·26	Reference
Know	5	2,087	8,935	23·9 (14·5–36·6)	< 0·001	94·19	0·498	0·460	− 0·403–1·400	0·278
Family history of mental disorders	5	11,283	71,044	24·0 (12·8–40·4)	< 0·001	99·70
No family history of mental disorders	5	309	1,139	23·4 (7·8–52·5)	< 0·001	99·87	Reference
Family history of mental disorders	5	10,719	67,689	31·6 (11·8–61·5)	< 0·001	98·30	0·415	0·940	− 1·427–2·258	0·658
Unknown	2	255	2,216	11·8 (1·1–62·5)	< 0·001	99·61	− 0·826	1·240	− 3·257–1·604	0·505
History of mental disorders	4	1,652	36,886	15·8 (3·2–51·3)	< 0·001	99·84
Good or excellent	4	646	32,725	7·8 (0·5–56·5)	< 0·001	99·87	Reference
Poor or fair	4	1,006	4,161	29·3 (4·3–79·3)	< 0·001	99·77	1·592	1·813	− 1·962–5·147	0·379
Tobacco/ Smoker use	16	16,101	112,086	12·5 (9·4–16·5)	< 0·001	99·50
No Tobacco/ Smoker use	16	14,266	102,888	9·0 (5·8–13·8)	< 0·001	99·71	Reference
Tobacco/ Smoker use	16	1,835	9,198	17·5 (12·2–24·6)	< 0·001	98·01	0·762	0·343	0·089–1·435	0·026
Alcohol use	20	24,629	200,375	14·7 (12·4–17·3)	< 0·001	99·37
No alcohol use	20	18,168	166,000	11·6 (9·3–14·3)	< 0·001	99·34	Reference
Alcohol use	20	6,461	34,375	18·5 (14·2–23·7)	< 0·001	99·00	0·540	0·191	0·165–0·914	0·004
Substance use	8	14,483	92,437	17·6 (10·6–27·7)	< 0·001	99·69
No substance use	8	12,095	86,568	10·7 (5·6–19·5)	0·003	99·52	Reference
Substance use	8	2,388	5,869	28·1 (15·5–45·5)	< 0·001	98·78	1·184	0·519	0·5165–2·203	0·022
Marijuana/ Cannabis use	6	2,033	20,006	20·0 (14·5–27·1)	< 0·001	98·10
Not use Marijuana/ Cannabis use	6	1,553	17,717	12·5 (8·3–18·3)	< 0·001	98·27	Reference
Marijuana/ Cannabis use	6	480	2,289	28·8 (21·4–37·5)	< 0·001	87·77	1·188	0·336	0·529–1·848	< 0·001
Depression	22	19,342	149,191	12·1 (9·0–16·1)	< 0·001	99·65
No Depression	21	11,242	121,730	4·9 (3·5–6·9)	< 0·001	99·19	Reference
Depression	22	8,100	27,461	25·5 (18·6–33·9)	0·204	99·37	1·894	0·275	1·353–2·434	< 0·001
Anxiety	14	4,509	49,846	10·3 (7·2–14·5)	< 0·001	99·22
No Anxiety	14	1,658	33,591	5·2 (2·7–10·1)	< 0·001	99·29	Reference
Anxiety	14	2,851	16,255	18·8 (13·9–24·9)	< 0·001	98·40	1·434	0·372	0·705–2·163	< 0·001
Posttraumatic stress disorder (PTSD)	4	926	21,524	6·4 (2·1–18·4)	< 0·001	99·55
No PTSD	4	253	18,070	2·0 (1·3–3·1)	< 0·001	90·46	Reference
PTSD	4	673	3,454	16·6 (8·6–29·6)	< 0·001	97·58	2·211	0·466	1·297–3·125	< 0·001
Stress	9	2,313	49,559	9·4 (4·0–20·7)	< 0·001	99·68
No stress	9	421	11,393	5·7 (1·5–19·4)	< 0·001	99·21	Reference
Stress	9	1,892	37,166	15·1 (4·4–40·6)	< 0·001	99·81	1·083	0·976	− 0·829–2·996	0·267
History of sleep problems	6	10,096	73,452	10·1 (7·2–14·0)	< 0·001	99·36
No sleep problems	6	6,158	51,992	6·0 (2·3–14·8)	< 0·001	99·35	Reference
Sleep problems	6	3,938	21,460	17·7 (9·5–30·3)	< 0·001	99·07	1·219	0·603	0·037–2·401	0·043
Nighttime sleeping hour	5	5,531	51,357	15·2 (12·2–18·7)	< 0·001	97·91
Normal (7–9 h)	5	949	11,341	12·7 (7·8–20·2)	< 0·001	97·65	Reference
More than normal > 9 hrs	5	1,844	20,402	12·5 (7·4–20·2)	< 0·001	90·96	–0·025	0·410	–0·830–0·779	0·949
Less than normal < 7 h	5	2,738	19,614	20·4 (13·2–30·4)	< 0·001	97·08	0·568	0·382	–0·181–1·317	0·137
Chronic disease	10	9,079	73,428	14·3 (11·1–18·2)	< 0·001	98·95
No chronic disease	10	7,321	61,295	12·0 (9·0–15·8)	< 0·001	98·59	Reference
Chronic disease	10	1,758	12,133	17·0 (9·4–28·8)	< 0·001	98·97	0·393	0·310	–0·214–1·002	0·204
Perceived quality of physical health	8	8,105	77,201	17·7 (12·1–25·1)	< 0·001	99·65
Good	8	4,548	59,360	10·2 (5·9–16·9)	< 0·001	99·60	Reference
Fair	7	2,572	14,101	24·6 (12·2–43·4)	< 0·001	99·52	1·062	0·477	0·126–1·999	0·026
Poor	3	985	3,740	26·4 (25·0–27·8)	0·081	60·19	1·405	0·633	0·163–2·648	0·027
Physical health problems	6	3,818	26,219	19·4 (10·7–32·4)	< 0·001	99·64
No physical health problems	6	2,376	22,846	13·2 (7·7–21·5)	< 0·001	99·28	Reference
Physical health problems	6	1,442	3,373	27·9 (12·9–50·1)	< 0·001	99·18	0·947	0·506	–0·045–1·939	0·061
Instrumental ADL impairmenta	4	828	12,692	14·2 (5·6–31·6)	< 0·001	99·38
No ADL impairments	4	615	11,346	9·8 (1·8–39·4)	< 0·001	99·72	Reference
ADL impairmenta	4	213	1,346	19·3 (13·1–27·4)	< 0·001	88·21	0·855	1·116	–1·332–3·043	0·443
Frequency of loneliness	4	1,283	16,193	8·7 (5·0–14·6)	< 0·001	98·88
Rarely or never	4	350	10,703	3·3 (1·3–8·1)	< 0·001	98·46	Reference
Some of the time	4	488	2,808	11·2 (5·1–22·9)	< 0·001	97·84	1·319	0·597	0·147–2·490	0·027
Moderate amount of time	2	251	1,413	16·1 (9·8–25·4)	< 0·001	92·13	1·726	0·718	0·317–3·135	0·016
All of the time	2	194	1,269	18·3 (9·5–32·5)	< 0·001	94·51	1·897	0·719	0·486–3·308	0·008
Having dependent elderly at home	3	382	4,065	9·7 (6·2–14·7)	< 0·001	99·13
No having dependent elderly at home	3	270	2,886	10·1 (3·9–23·8)	< 0·001	96·82	Reference
Having dependent elderly at home	3	112	1,179	9·1 (6·0–13·6)	< 0·001	80·22	–0·153	0·590	–1·311–1·003	0·794
Race	7	20,963	57,847	31·2 (22·3–41·7)	< 0·001	99·58
White	7	19,044	51,879	28·6 (11·8–54·5)	< 0·001	99·89	Reference
Black	7	340	1,882	26·0 (11·2–49·5)	< 0·001	98·09	–0·130	0·764	–1·629–1·368	0·864
Asian	6	366	1,023	32·4 (16·6–53·6)	< 0·001	96·48	0·174	0·797	–1·387–1·737	0·826
Hispanic	3	257	824	30·7 (9·4–65·3)	< 0·001	98·28	0·097	0·983	–1·830–2·024	0·921
Other	7	956	2,239	38·8 (22·5–58·0)	< 0·001	98·15	0·478	0·765	–1·021–1·978	0·531
Participate in frontline work	3	10,513	101,887	5·5 (2·7–10·9)	< 0·001	99·86
No participate in frontline work	3	8,079	59,325	4·9 (2·0–12·0)	< 0·001	99·74	Reference
Participate in frontline work	3	2,416	42,562	6·1 (0·9–32·9)	< 0·001	99·92	0·243	1·089	–1·892–2·379	0·823
Direct contact with COVID-19 patients	10	6,133	97,471	9·9 (7·1–13·6)	< 0·001	99·43
No direct contact with COVID-19 patients	10	4,082	75,240	8·7 (5·1–14·5)	< 0·001	99·65	Reference
Direct contact with COVID-19 patients	10	2,051	22,231	11·2 (7·6–16·0)	< 0·001	98·53	0·270	0·382	–0·479–1·020	0·480
Experienced quarantine during the COVID-19 pandemic	8	29.581	185.203	15·4 (13·3–17·7)	< 0·001	99·08
No experienced quarantine	8	13.660	99.759	11·8 (9·4–14·6)	< 0·001	98·99	Reference
Experienced quarantine	8	15,921	85,444	20·4 (17·8–23·3)	< 0·001	96·76	0·609	0·158	0·298–0·920	< 0·001
Social mediause	5	2,147	27,354	8·8 (6·6–11·5)	< 0·001	96·92
No social mediause	5	406	5,900	8·4 (5·0–13·7)	< 0·001	95·43	Reference
Social mediause	5	1,741	21,454	9·2 (6·1–13·6)	< 0·001	98·00	0·099	0·341	–0·569–0·768	0·770
Service duration (year)	3	786	35,767	6·2 (2·4–15·0)	< 0·001	99·37
> 10 years	3	246	13,812	3·9 (0·4–28·5)	< 0·001	99·48	Reference
4–10 years	3	266	10,268	6·6 (0·8–38·4)	< 0·001	99·56	0·569	1·563	–2·494–3·634	0·715
1–3 years	3	274	11,687	8·9 (1·3–42·2)	< 0·001	99·48	0·887	1·565	–2·181–3·956	0·570
Working hours per week	5	1,730	16,119	14·6 (10·2–20·6)	< 0·001	98·06
≦ 20 h	2	151	1,379	15·1 (6·0–33·1)	< 0·001	95·01	Reference
21–40 h	5	556	4,824	11·2 (5·4–22·1)	< 0·001	97·70	–0·374	0·898	–2·136–1·386	0·676
41–60 h	5	784	8,420	13·5 (5·6–28·9)	< 0·001	98·90	–0·144	0·886	–1·881–1·592	0·870
> 60 h	5	239	1,496	19·7 (6·8–45·0)	< 0·001	98·15	0·311	0·889	–1·431–2·053	0·726
WHO region	202	228,342	19,815,536	11·5 (9·9–13·3)	< 0·001	99·92
African Region	5	489	217,931	4·5 (0·2–47·2)	0·042	99·88	Reference
European region	53	43,515	16,304,495	9·6 (5·9–15·2)	< 0·001	99·94	0·815	0·576	–0·313–1·944	0·157
Region of the Americas	51	700,386	1,361,684	14·1 (10·7–18·4)	< 0·001	99·93	1·254	0·577	0·124–2·385	0·030
South-East Asian region	14	3,312	24,773	13·5 (7·6–22·6)	< 0·001	99·55	1·191	0·643	–0·070–2·452	0·064
Eastern Mediterranean region	5	2,583	12,862	18·0 (13·6–23·5)	< 0·001	94·25	1·536	0·778	0·013–·3·060	0·048
Western Pacific region	71	98,564	1,848,577	10·8 (8·8–13·2)	< 0·001	99·91	0·949	0·569	–0·167–·2·065	0·096
Multiple areas	3	9,493	45,214	25·9 (16·1–38·7)	0·001	99·83	2·006	0·895	0·251–·3·760	0·025
Sample size	202	228,342	19,815,536	11·5 (9·9–13·3)	< 0·001	99.92
> 500	169	226,113	19,805,263	10·6 (9·0–12.5)	< 0·001	99·93	Reference
≤ 500	33	2,229	10,273	18·1 (14·9–21·9)	< 0·001	99·32	0·553	0·231	0·100–1·007	0·017

Sex_other: Non-binary/Two-spirit/Pansexual/Heteroflexible/Genderqueer/nonconforming/Not listed/Prefer not to answer

Prevalence of Suicidal Ideations

Across 37 countries, 184 studies analyzed the prevalence of suicidal ideations. Suicide ideation events were reported in 216,723 out of 1,669,436 participants. Among these, three studies conducted in Multiple areas demonstrated the highest rates (25.9%) of suicide ideation events, while four studies in the Eastern Mediterranean region showed the highest rates (17%) of such events (Table 2). Following a meta-analysis, the pooled prevalence of suicide ideations during the COVID-19 pandemic was determined to be 13.5% (95% CI: 12.1–14.9%, p < 0.001) across 184 studies, indicating a high level of heterogeneity (I² = 99.83, Q = 110,988.396, Tau² = 0.667, p < 0.001, Supplemental Fig. 1).

Prevalence of Suicide Attempts

Across 23 countries, 56 studies analyzed the prevalence of suicide attempts. Suicide attempt events were reported in 44,454 out of 17,524,835 participants. Among these, one study conducted in the Eastern Mediterranean region demonstrated the highest rates (22.7%) of suicide attempt events, while two studies in the South-East Asian region showed the highest rates (17%) of such events (Table 2). Following a meta-analysis, the pooled prevalence of suicide attempts during the COVID-19 pandemic was determined to be 10.4% (95% CI: 6.6–16.1%, p < 0.001) across 56 studies, indicating a high level of heterogeneity (I² = 99.95, Q = 115204.965, Tau2 = 1.884, p < 0.001, Supplemental Fig. 2).

Prevalence and Incidence of Death by Suicide

Five studies conducted in five countries reported the prevalence of suicides, encompassing 4,690 out of 1,862,286 participants. Among these studies, those in the Region of the Americas showed the highest suicide prevalence rates (7.57%). Additionally, three studies conducted in three countries reported the prevalence of suicides, involving 2,745 out of 1,088,420 participants. Again, studies in the Region of the Americas exhibited the highest suicide prevalence rates (8.07 per 100,000 people/year) (Table 2). According to the meta-analysis results, the pooled prevalence of death by suicide was 0.5% (95% CI: 0.1–3.5%, p < 0.001), with significant heterogeneity across the five studies (I² = 99.97%, Q = 15084.524, Tau² = 4.775, p < 0.001, Supplemental Fig. 3a). The pooled incidence rate, calculated using people-year (PY) for three studies, was 4.51 (95% CI: 1.78–7.25%, p < 0.001) per 100,000 PY with significant heterogeneity (I² = 99.34%, Q = 12640.154, Tau² = 5.813, p < 0.001, Supplemental Fig. 3b).

Meta-Regression Analysis to Identify Risk Factors for Suicidal Behaviors

Following the meta-analysis, significant heterogeneity was observed in all outcome variables. To explore the factors contributing to this heterogeneity and understand the drivers within subgroups, a meta-regression analysis was conducted. The meta-regression model incorporated various risk factors for the three suicidal behaviors (Table 2).

The following risk factors were identified as significantly associated with suicidal behavior during the COVID-19 pandemic: According to Transgender [R = 1.84, 95% CI: 0.80 − 2.89, p = 0.0273], age include 18 ~ 24 years old [R = 1.19, 95% CI: 0.45 − 1.94, p = 0.001], 25 ~ 34 years old [R = 0.91, 95% CI: 0.16 − 1.66, p = 0.016], 35 ~ 44 years old [R = 0.90, 95% CI: 0.15–1.66, p = 0.018], unmarried [R = 0.37, 95% CI: 0.02–0.72, p = 0.033], separated/ divorced/ widowed [R = 0.84, 95% CI: 0.41–1.27, p < 0.001], education level of high school or lower [R = 0.48, 95% CI: 0.00–0.97, p = 0.049], employment status of retired [R =  − 0·97, 95% CI: − 1·73– − 0·22, p = 0.011], lives alone [R = 0.73, 95% CI: 0.25–1.20, p = 0.002], house type of lower [R = 0.76, 95% CI: 0.14–1.38, p = 0.014], low social support [R = 1.26, 95% CI: 0.71–1.81, p < 0.001], dissatisfaction with studies [R = 0.70, 95% CI: 0.21–1.18, p = 0.004], suicidal attempt history [R = 2.70, 95% CI: 0.18–5.22, p = 0.035], tobacco/ smoker [R = 0.76, 95% CI: 0.08–1.43, p = 0.026], alcohol [R = 0.54, 95% CI: 0.16–0.91, p = 0.004], substance use [R = 1.18, 95% CI: 0.51–2.20, p = 0.022], marijuana/ cannabis [R = 1.18, 95% CI: 0.52–1.84, p < 0.001], depression [R = 1.89, 95% CI: 1.35–2.43, p < 0.001], anxiety [R = 1.43, 95% CI: 0.70–2.16, p < 0.001], PTSD [R = 2.21, 95% CI: 1.29–3.12, p < 0.001], sleep problems [R = 1.21, 95% CI: 0.03–2.40, p = 0.043], perceived quality of physical health were fair [R = 1.06, 95% CI: 0.12–1.99, p = 0.026], and poor [R = 1.40, 95% CI: 0.16–2.64, p = 0.027], frequency of loneliness of some of the time [R = 1.31, 95% CI: 0.14–2.49, p = 0.027], moderate amount of time [R = 1.72, 95% CI: 0.31–3.13, p = 0.016], and All of the time [R = 1.89, 95% CI: 0.48–3.30, p = 0.008], experienced quarantine [R = 0.60, 95% CI: 0.29–0.92, p < 0.001], region of the Americas [R = 1.25, 95% CI: 0.12–2.38, p = 0.030], Eastern Mediterranean region [R = 1.53, 95% CI: 0.01–3.06, p = 0.048], and multiple areas [R = 2.00, 95% CI: 0.25–3.76, p = 0.025] (Table 2).

Risk Factors for Suicidal Ideation

The results of the meta-analysis and meta-regression identified the following risk factors associated with suicidal ideation during the COVID-19 pandemic: transgender [R = 1.81, 95% CI: 0.76–2.86, p < 0.001], 18 ~ 24 years old [R = 1.19, 95% CI: 0.58–1.80, p < 0.001], 25 ~ 34 years old [R = 0.91, 95% CI: 0.30–1.51, p = 0.003], 35 ~ 44 years old [R = 0.90, 95% CI: 0.29–1.52, p = 0.004], unmarried [R = 0.37, 95% CI: 0.02–0.72, p = 0.033], separated/ divorced/ widowed [R = 0.84, 95% CI: 0.41–1.27, p < 0.001], education level of high school or lower [R = 0.48, 95% CI: 0.00–0.97, p = 0.049], employment status of retired [R =  − 0·97, 95% CI: − 1·73– − 0·22, p = 0.011], lives alone [R = 0.73, 95% CI: 0.25–1.20, p = 0.002], house type of lower [R = 0.76, 95% CI: 0.14–1.38, p = 0.014], low social support [R = 1.26, 95% CI: 0.71–1.81, p < 0.001], dissatisfaction with studies [R = 0.70, 95% CI: 0.21–1.18, p = 0.004], suicidal attempt history [R = 2.70, 95% CI: 0.18–5.22, p = 0.035], alcohol [R = 0.53, 95% CI: 0.13–0.92, p = 0.008], substance use [R = 1.18, 95% CI: 0.51–2.20, p = 0.022], marijuana/ cannabis [R = 1.49, 95% CI: 0.52–2.46, p < 0.001], depression [R = 1.77, 95% CI: 1.16–2.38, p < 0.001], anxiety [R = 1.42, 95% CI: 0.57–2.26, p < 0.001], PTSD [R = 2.21, 95% CI: 1.29–3.12, p < 0.001], sleep problems [R = 1.21, 95% CI: 0.03–2.40, p = 0.043], perceived quality of physical health were fair [R = 1.06, 95% CI: 0.12–1.99, p = 0.026], and poor [R = 1.40, 95% CI: 0.16–2.64, p = 0.027], Frequency of loneliness of some of the time [R = 1.31, 95% CI: 0.14–2.49, p = 0.027], moderate amount of time [R = 1.72, 95% CI: 0.31–3.13, p = 0.016], and all of the time [R = 1.89, 95% CI: 0.48–3.30, p = 0.008], experienced quarantine [R = 0.60, 95% CI: 0.29–0.92, p < 0.001], and multiple areas [R = 0.98, 95% CI: 0.06–1.90, p = 0.036]; and sample size ≤ 500 [R = 0.57, 95% CI: 0.24–0.90, p < 0.001] (Supplemental Table 2).

Risk Factors for Suicide Attempts

The results of the meta-analysis and meta-regression identified the following risk factors associated with suicidal attempts during the COVID-19 pandemic: family history of suicidal [R = 1.93, 95% CI: 0.73–3.12, p = 0.001], depression [R = 2.41, 95% CI: 1.31–3.50, p < 0.001], European region [R = 5.12, 95% CI: 1.17–9.08, p = 0.011], region of the Americas [R = 5.65, 95% CI: 1.60–9.71, p = 0.006], South-East Asian region [R = 5.82, 95% CI: 1.35–10.29, p = 0.010], Eastern Mediterranean region [R = 6.18, 95% CI: 0.71–11.66, p = 0.026], and Western Pacific region [R = 5.37, 95% CI: 1.40–9.35, p = 0.008] (Supplemental Table 3).

Publication Bias

Publication bias in suicidal behavior during the COVID-19 pandemic for the 202 studies was assessed using a funnel plot and Egger's test. The funnel plot did not reveal evidence of asymmetry, suggesting a minor probability of publication bias. However, statistically significant publication bias was observed based on Egger's results (Q = 253533.416, p < 0.001, I2 = 99.92%, Fig. 2), likely attributed to the diversity in sample sizes across the studies.

Fig. 2.

Funnel plots describing publication bias bases on suicidal behavior during the COVID-19 pandemic. Total (95% CI) = 202, IR 0.115 (0.099–0.133), p < .001, Events 388,429/ 176,753,344. Heterogeneity = Random model, Q value 253533.416, p < .001, I² = 99.92, Tau.² 1.428

Discussion

This study provides the first large-scale meta-analysis and regression estimate of global prevalence of suicidal behaviors and risk factors associated with suicidal ideation, attempts, and deaths during the entire COVID-19 pandemic. Study findings are strengthened with over 200 observational type studies. Overall suicide behaviors prevalence nearly 11% during the pandemic, 13.5% suicide ideation prevalence and 10% suicide attempts in general population. These results emphasize the importance of prioritizing mental health support and intervention strategies during the COVID-19 pandemic. It's crucial for communities and governments to invest in mental health services, raise awareness, reduce stigma, and promote resilience-building measures to address these alarming rates of suicidal behavior. If you or someone you know is struggling with suicidal thoughts or behaviors, it's essential to reach out to mental health professionals or helplines for support and assistance.

Prior studies show, being female, being a healthcare professional, younger age, low income, preexisting mental health issues, loneliness, and substance abuse were the risk factors associated with suicidal ideation during the pandemic [51]. Our study finds the similar results and additionally we found some specific risk factors associated with suicidal ideation such as transgender, age 18 ~ 24 years, unmarried, separated/ divorced/ widowed, retired employees, low social support, dissatisfaction with studies, having suicidal attempt history and having experience of quarantine. However, some studies suggest number of days of social distancing does not cause incidence of suicidal ideation [3].

Studies found that that the people who received social support shown lesser risk of developing suicidal ideation [5]. Therefore, having a partner, substantial social support through friends, relatives or healthcare provider are important in reducing suicides during times like pandemics. Special psychological support is also necessary for the health professionals during new normal situations like COVID-19 pandemics [3]. Additional help for younger generation, transgender, people who do not have partner and retired employees may need. Quarantine centers require innovative approaches to assess and stabilize the mental health of residents. Implementing digital health technologies, such as telemedicine for remote psychological counseling and mental health monitoring apps, can provide real-time support. Virtual support groups and social interaction platforms can help reduce feelings of isolation and loneliness, while AI-driven mental health assessment tools could offer early detection of distress. Additionally, integrating mindfulness programs, online therapy, and resilience-building activities tailored to the specific needs of quarantine residents can create a more holistic approach to mental health care in these settings.

COVID-19 pandemic elevated the risk of suicide regardless of the individual’s status of with or without mental disorders such as depression and anxiety [52]. Interpersonal theory of suicide explains the association between loneliness and suicidal ideation. According to the theory of suicidal ideation suicide can be induced by feeling of being a burden on others [3]. Therefore, reciprocal care and psychological reassurance during isolation are vital for those experiencing loneliness. Future interventions targeting suicidal issues need to incorporate theories along with intervention plans for better effectiveness.

This study has number of strengths such as use of comprehensive search strategy, use of multiple bibliographic databases, incorporate large number of observational studies, large sample size, application of both meta-analysis and regression techniques and use of rigorous review process maximize the comprehensiveness and generalizability of results. Previous reviews were limited to studies less than 13 for metanalysis and a smaller number of studies on suicide during the pandemic [1, 6].

A few limitations of this study are seen such as high heterogeneity in outcome variables and considerable publication bias as a result of diversity of sample characteristics, sizes and conducted countries among included studies. Our study has some limitations. Suicidal behaviors were measured using different assessment tools, which may have contributed to significant heterogeneity. However, meta-regression analysis reveals risk factors affecting heterogeneity for the suicidal behaviors (ideation and attempt) in this study are associated with: being transgender, age 18 ~ 24, 25 ~ 34, 35 ~ 44 years old, living without partner/ lives alone, retired senior, low social support, dissatisfaction with studies, suicidal attempt history, alcohol and substance usage, depression, anxiety, sleep problems, quarantine exposure, region of the Americas and Eastern Mediterranean region. Previous meta-analysis also reported heterogeneous population as a reason for significant heterogeneity in study results [1]. Additionally, since none of our team members are native speakers of languages such as French or Spanish, this posed a limitation in our review. We recommend conducting further studies that include sources in other languages to address this gap.

Conclusions

In a global pandemics ongoing monitoring and support for mental health is critical for the vulnerable communities such as younger age, transgender, living alone, un-employees, and individual with substance abuse. This can significantly reduce depression, anxiety, suicide risk and associated deaths through systematic therapeutic and social support. Ongoing longitudinal and cross-sectional studies are studies are needed to assess the current status of the situation. Qualitative studies may help to understand the experience, ethnic and cultural influences on suicidal ideation and risk factors due to the pandemic. Future interventions to prevent suicide during such situations need to incorporate theories like Interpersonal theory of suicide, Crisis theory and Theory of planned behavior. This study will immensely be helpful in designing effective interventional and epidemiological studies in future to prevent pandemic or emerging infectious disease related social isolation, loneliness, suicidal attempts and death.

Supplementary Information

Below is the link to the electronic supplementary material.

Biographies

Sriyani Padmalatha Konara Mudiyanselage

is a National Cheng Kung University distinguished nursing professional and researcher currently serving as a Research Fellow at Institute of Behavioral Medicine, The National Cheng Kung University, in Taiwan. With a PhD in Nursing from National Cheng Kung University, her extensive research focuses on mental health, particularly the impact of the COVID-19 pandemic on suicidal behaviors. Dr. Padmalatha’s career spans significant clinical experience at the National Hospital of Sri Lanka and academic roles at various institutions, including the University of Sri Jayewardenepura. She chairs the Nursing and Midwifery Working Group at the International Society for Telemedicine & eHealth and has earned numerous accolades, including the Nursing Excellence Award from the President of Sri Lanka. Her contributions to healthcare and nursing education underscore her dedication to advancing the field through research, teaching, and leadership.

Yi-Tseng Tsai

is a dedicated nurse supervisor and accomplished researcher at the Department of Nursing, An Nan Hospital, China Medical University in Tainan, Taiwan and College of Nursing, Kaohsiung Medical University, Kaohsiung. With a PhD in Nursing, Dr. Tsai has made significant contributions to understanding mental health, particularly focusing on suicidal behavior during the COVID-19 pandemic. Her work is distinguished by a methodical approach to investigating risk factors and prevalence rates, using systematic reviews and meta-regression analyses. Dr. Tsai’s dedication to advancing healthcare through research, coupled with her supervisory role, underscores her commitment to improving patient outcomes and supporting the nursing profession. Her contributions have been instrumental in providing valuable insights for mental health interventions during global health crises.

Maithreepala Sujeewa Dilhani

is a PhD candidate at the Department of Nursing,College of Medicine, National Cheng Kung University, Taiwan and lecture at  Faculty of Allied Health Sciences, University of Peradeniya, Sri Lanka. With a solid foundation in nursing, she is actively involved in advanced research, focusing on mental health and its various dimensions. Her current research explores the impact of the COVID-19 pandemic on suicidal behaviors, contributing significantly to the field through systematic reviews and meta-regression analyses. Dilhani’s work is characterized by her meticulous methodology and dedication to understanding complex health issues, making her a valuable contributor to both academic research and practical healthcare solutions.

Yi-Jing Tsai

is a dedicated PhD candidate at the Department of Nursing, College of Medicine, National Cheng Kung University, Tainan, Taiwan. With a strong background in nursing and a commitment to advancing healthcare, her research focuses on critical mental health issues, particularly the effects of the COVID-19 pandemic on suicidal behaviors. Tsai’s work employs systematic reviews and meta-regression analyses to uncover significant insights into risk factors and prevalence rates. Her scholarly contributions are integral to developing effective mental health interventions and policies. Tsai’s dedication to research and her pursuit of academic excellence highlight her as a promising figure in the field of nursing and mental health.

Ya-Han Yang

is a dedicated Registered Nurse at An Nan Hospital, China Medical University, Tainan, Taiwan. With a Bachelor of Science in Nursing, she brings a strong clinical background and a commitment to patient care. Yang’s contributions to research, particularly in understanding the mental health impacts of the COVID-19 pandemic, are significant. Her involvement in systematic reviews and meta-regression analyses has provided valuable insights into the prevalence and risk factors of suicidal behaviors during the pandemic. Yang’s dedication to advancing healthcare through research and her clinical expertise make her an invaluable asset to the nursing profession and mental health field.

Zan-Ting Lu

is a committed Registered Nurse at An Nan Hospital, China Medical University, Tainan, Taiwan. Holding a Bachelor of Science in Nursing, Lu has demonstrated exceptional dedication to both patient care and academic research. Her work focuses on the mental health impacts of the COVID-19 pandemic, particularly through systematic reviews and meta-regression analyses to investigate suicidal behaviors. Lu’s contributions have been instrumental in identifying key risk factors and prevalence rates, providing crucial insights for the development of effective mental health interventions.

Nai-Ying Ko

is a distinguished academic and the Vice Dean at international affairs at College of Medicine, National Cheng Kung University, Tainan, Taiwan. With a PhD in Public Health, Prof. Ko’s extensive research focuses on mental health, HIV/AIDS, and public health nursing. Her work is characterized by rigorous methodology and impactful findings, contributing significantly to the understanding and improvement of healthcare systems. Prof. Ko’s leadership and expertise have been instrumental in advancing nursing education and research, making her a prominent figure in the global health community. Her numerous publications and ongoing research projects underscore her commitment to excellence in healthcare.

Author Contributions

Conceptualization: Sriyani Padmalatha Konara Mudiyanselage, Yi-Tseng Tsai, Yi-Jing Tsai, Nai-Ying Ko; Methodology: Sriyani Padmalatha Konara Mudiyanselage, Yi-Tseng Tsai, Ya-Han Yang, Zan-Ting Lu, Nai-Ying Ko; Formal analysis and investigation: Sriyani Padmalatha Konara Mudiyanselage, Yi-Tseng Tsai, Maithreepala Sujeewa Dilhani, Yi-Jing Tsai, Ya-Han Yang, Zan-Ting Lu, Nai-Ying Ko; Writing—original draft preparation: Sriyani Padmalatha Konara Mudiyanselage, Yi-Tseng Tsai, Maithreepala Sujeewa Dilhani; Writing—review and editing: Sriyani Padmalatha Konara Mudiyanselage, Maithreepala Sujeewa Dilhani; Funding acquisition: Yi-Tseng Tsai; Resources: Yi-Tseng Tsai, Yi-Jing Tsai, Ya-Han Yang, Zan-Ting Lu, Nai-Ying Ko; Supervision: Sriyani Padmalatha Konara Mudiyanselage, Yi-Tseng Tsai, Nai-Ying Ko.

Funding

The research was supported by the An Nan Hospital, China Medical University, Tainan, Taiwan, under Grant No. ANHRF113-26.

Data Availability

Data analyzed in this study were a re-analysis of existing data, which are openly available at locations cited in the reference section. However, extracted and re-analyzed data and code can be made available from the corresponding author upon reasonable request.

Declarations

Ethics Approval

None.