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Open Access

Peer-reviewed

Research Article

Prevalence of depression, anxiety, stress, and suicide tendency among individual with long-COVID and determinants: A systematic review and meta-analysis

  • Razieh Bidhendi-Yarandi,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliations Psychosis Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran, Department of Biostatistics and Epidemiology, School of Social Health, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

    ⨯
  • Akbar Biglarian,

    Roles Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliations Department of Biostatistics and Epidemiology, School of Social Health, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran, Social Determinants of Health Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

    ⨯
  • Jannike Lie Karlstad,

    Roles Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Faculty of Nursing and Health Sciences, Nord University, Bodø, Norway

    ⨯
  • Cathrine Fredriksen Moe,

    Roles Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Faculty of Nursing and Health Sciences, Nord University, Bodø, Norway

    ⨯
  • Enayatollah Bakhshi,

    Roles Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Department of Biostatistics and Epidemiology, School of Social Health, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

    ⨯
  • Mohammad-Reza Khodaei-Ardakani,

    Roles Data curation, Formal analysis, Funding acquisition, Investigation, Writing – original draft, Writing – review & editing

    Affiliation Razi Psychiatric Hospital, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran

    ⨯
  • Samira Behboudi-Gandevani

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing

    samira.behboudi-gandevani@nord.no

    Affiliation Faculty of Nursing and Health Sciences, Nord University, Bodø, Norway

    ⨯

Abstract

Background

While mental health alterations during active COVID-19 infection have been documented, the prevalence of long-term mental health consequences remains unclear. This study aimed to determine the prevalence of mental health symptoms—depression, anxiety, stress, and suicidal tendencies—and to identify their trends and associated risk factors in individuals with long-COVID.

Methods

We conducted a systematic literature search of databases including PubMed, EMBASE, Scopus, CINAHL, Cochrane Library, Web of Science, and PsycINFO up to August 2024, targeting observational studies published in English. Study quality was assessed using structured standard tools. The primary outcome was the pooled prevalence of depression, anxiety, stress, and suicidal tendencies in individuals with long-COVID. Secondary outcomes included trends in these mental health problems over time and identification of associated determinants.

Results

A total of 94 eligible studies were included in the analysis. The pooled prevalence estimates, regardless of follow up times duration, were as follows: depression, 25% (95%CI:22–28%; PI:1–59%); anxiety (adjusted via trim and fill method), 23%(95%CI:21–25%;PI:2–35%); composite outcomes of depression and/or anxiety, 25% (95%CI:23–27%;PI:2–51%); stress, 26%(95%CI:13–39%;PI:1–69%); and suicidality, 19%(95%CI:15–22%;PI:13–25%). The results of meta-regression analyses revealed a statistically significant trend showing a gradual decrease in the prevalence of the composite outcome of anxiety and/or depression over time (RD = -0.004,P = 0.022). Meta-regression results indicated that being female and younger age were significantly associated with a higher prevalence of mental health symptoms. Study design and study setting did not contribute to heterogeneity.

Conclusion

One-fourth of individual with long-COVID experience mental health symptoms, including depression, anxiety, and stress, which remain prevalent even two years post-infection despite a slight decreasing trend. Factors such as female gender and younger age were linked to higher rates of anxiety and depression. These findings indicate the need for ongoing mental health screening and early interventions to mitigate long-term psychological distress in long-COVID patients.

Citation: Bidhendi-Yarandi R, Biglarian A, Karlstad JL, Moe CF, Bakhshi E, Khodaei-Ardakani M-R, et al. (2025) Prevalence of depression, anxiety, stress, and suicide tendency among individual with long-COVID and determinants: A systematic review and meta-analysis. PLoS ONE 20(1): e0312351. https://doi.org/10.1371/journal.pone.0312351

Editor: Shibajee Debbarma, All India Institute of Medical Sciences - Patna, INDIA

Received: June 28, 2024; Accepted: October 4, 2024; Published: January 28, 2025

Copyright: © 2025 Bidhendi-Yarandi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The authors received no specific funding for this work. Nord University covered the processing charge in this article.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The COVID-19 pandemic is regarded as an unprecedented natural disaster in the current century, with far-reaching and catastrophic consequences for the global population. As reported by the World Health Organization (WHO), more than 750 million people have been infected globally, and the death toll has tragically surpassed 6 million [1, 2]. While most patients recovered in the weeks following acute infection, evidence quickly emerged that some people reported persistence or appearance of a wide variety of symptoms with variable intensity, regardless of the initial disease severity [1, 3]. The term “long-COVID” was introduced in May 2020 [3]. According to the WHO it was defined as the presence of symptoms lasting for at least 2 months in individuals with a history of probable or confirmed SARS-CoV-2 infection, which usually manifests 3 months from the onset of acute illness, yet cannot be explained by an alternative diagnosis [4].

In this respect, emerging evidence reported a high prevalence of prolonged psychiatric symptoms in individuals who had preliminary COVID-19 or have recovered from the acute infection, that could last for weeks, even months, after recovery [5–7]. For instance, Badenoch et al. (2021) in a meta-analysis reported that among patients experiencing persistent neuropsychiatric symptoms after an initial 2-week infection period (with a median follow-up time of 77 days, ranging from 14 to 182 days), the pooled prevalence of anxiety was 19% [19.1% (13.3–26.8%)] [8].

However, the prevalence of some significant mental health symptoms, such as depression, anxiety, stress, and suicidal tendencies, in individuals with long-COVID, are not fully determined. While some studies have identified specific associated risk factors for mental health problems, a thorough understanding of their prevalence and contributing factors in long COVID patients is still missing. Therefore, the aim of this study was to determine the prevalence and trend of mental health symptoms, including depression, anxiety, stress, and suicidal tendencies, and to identify their associated risk factors among individuals with long-COVID. By addressing this gap, we hope to provide a clearer picture of the mental health issues in long COVID patients and inform better clinical practices and public health strategies.

Material and methods

Design and registration

This systematic review and meta-analysis adhere to the 2020 preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines [9]. The protocol of this review was registered with the International Prospective Register of Systematic Reviews (PROSPERO): (PROSPERO ID: CRD42022346858).

Data source, search strategy and study selection

We conducted a comprehensive search across seven electronic databases (PubMed including Medline, EMBASE, Scopus, CINAHL, Cochrane Library, Web of Science, and PsycINFO) from inception to August 2024. Additionally, we manually searched the reference lists of relevant articles, including backward and forward citation searches. All identified studies were exported into EndNote Software for duplicate removal, screening, full-text review, and data extraction. Three independent reviewers conducted title and abstract screening, full-text review was completed by two other independent reviewers against the inclusion and exclusion criteria. Disagreements or conflicts were resolved through discussion and consensus. A detailed information is provided in the S1 File.

Selection criteria

All observational (cross-sectional, case–control, or cohort) Studies were considered for inclusion in this review if they met the following criteria: (i) reported the occurrence or provided adequate data to estimate the prevalence of outcomes among the general adult population, and (ii) utilized validated measurement tools for outcome assessment. Additionally, studies that recruited college students and healthcare providers were also included. We excluded studies that (i) were non-primary research articles (brief communications, commentary, editorials, and reviews); (ii) did not adhere to the defined criteria for long-COVID; (iii) Did not clearly specify the follow-up duration; (iv) studies published in languages other than English. If studies had overlapping participants and survey periods, then the study with the most detailed and relevant information was used. In cases where studies had overlapping participants and survey periods, preference was given to the study providing the most detailed and relevant information.

Data extraction

After identifying eligible studies through full-text review, two reviewer (SB-G and RB-Y) extracted data. The third reviewer double-checked 15% subsample of the extracted information to check the consistency. General information that was extracted for each study included: the first author, year of publication, sample size, country, and study population. Information on event occurrences such as severity of preliminary infection, follow up time, measurement tools, and associated factors were also extracted.

Outcome variables and measures

Long-COVID was defined as conditions that occur in individuals with a history of probable or confirmed SARS-CoV-2 infection 3 months from the onset of COVID-19 that last for 2 months and cannot be explained by an alternative diagnosis [10, 11].

For the endpoint outcomes of the study, including anxiety, depression, stress, and suicide tendency, we utilized the definitions employed in each original study, due to the heterogeneity of definitions used across different studies, at different time points.

Quality assessment

The quality of the included studies was evaluated using the Newcastle–Ottawa Scale (NOS) for observational studies [12]. The NOS consists of eight items classified into three domains of study population/ group selection, study group comparability of study group, and determination of outcome or exposure. This tool evaluates the methodological quality of studies using a star system, providing a semi-quantitative assessment. Scores range from zero to nine stars for cohort and case-control studies and zero to eight for cross-sectional studies. The studies were categorized into four quality levels based on their scores: high (75–100% scores), moderate (50–74% scores), low (25–49% scores), and very low (0–24% scores). Quality assessment involved two reviewers (CFM and JLK), with a third reviewer (SB-G) double-assessing 15% of the articles to ensure consistency.

Synthesis of results/data analysis

A narrative synthesis was performed for the results of studies to summarize the determinant associated with outcomes. This involved systematically reviewing and integrating findings from the included studies. Initially, we extracted and tabulated key data from each study, then identified and analyzed recurring themes and patterns across the studies, comparing findings to explore consistencies and discrepancies. Finally, to generate a consistent effect measure across studies, meta-analyses was performed.

Heterogeneity was evaluated using the Chi-square test. Publication bias was also assessed by both funnel plot and Egger’s test. The random effect model was used to estimate the pooled proportion in case of significant heterogeneity. In addition, Freeman-Tukey (double arcsine) transformation for proportions was applied to stabilize the variances. Trim and fill method applied in case of significant publication bias. Meta-regression analysis was also run to assess the effect of extracted determinants as the potential sources of heterogeneity. R software metaphor package version 4.3.3 was used to conduct statistical analysis.

Results

Search results and characteristics of the included studies

The initial literature search yielded 3857 studies, 250 of which were further evaluated by retrieving their full text and 156 of these were excluded. Eventually, 97 eligible studies were included in the systematic review and offered extractable data for the meta-analysis [5–7, 13–103], involving 660484 participants. A flow diagram of this process is present in Fig 1. The main characteristics of included studies are summarized in Table 1.

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Fig 1. Flowchart of the search process.

https://doi.org/10.1371/journal.pone.0312351.g001

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Table 1. Characteristics of studied included.

https://doi.org/10.1371/journal.pone.0312351.t001

Fifty studies were conducted in Europe including Norway, UK, Switzerland, Italy, Spain, Germany, Hungary, Turkey, Netherlands, France, Ireland, Sweden [5, 6, 13, 19–22, 24–27, 32–34, 39, 43, 44, 47–50, 52, 53, 58, 60–70, 73, 75, 77, 78, 80, 81, 84, 87, 91, 92, 96–99, 102], fifteen in the United States and Canada [16, 29, 35–37, 41, 42, 46, 76, 82, 86, 88, 89, 101, 103], nineteen in Asia including Iraq, Thailand, China, Malaysia, Japan, Bangladesh, Republic of Korea, Indonesia, Saudi Arabia and Vietnam [7, 14, 23, 38, 45, 51, 54–56, 59, 66, 71, 72, 90, 93–95, 100, 104], four in Africa including Egypt, Morrocco, south Africa [15, 17, 18, 57], and six in South America including Brazil, Mexico [28, 30, 31, 40, 74, 83]. Follow-up time ranged from 2 to 24 months (Table 1).

All included studies reported on the prevalence of depression or anxiety, with only seven studies also addressing stress [5, 58, 64, 71, 82, 100, 104] and two studies examining the prevalence of suicidality [39, 42].

Quality appraisal, publication bias and heterogeneity

The quality appraisal of the included studies is presented in S1-S3 Tables in S1 File. Among them, 32.9% (31/94) of studies were judged as high quality, 56.3% (53/94) were assessed as moderate quality, and 10.6% (10/94) were classified as low quality. None of the studies were considered very low quality, resulting in all studies being included in the final analysis.

Based on the funnel plot (Fig 2) and Egger’s test (Table 2), no statistically significant publication bias was observed among the studies for any of the outcomes. Due to insufficient data, publication bias for the outcome of suicidality was not performed. Heterogeneity tests for all outcomes were statistically significant (P < 0.001); therefore, all estimations were obtained using the random effects method.

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Fig 2. Funnel plot for testing asymmetry hypothesis using Freeman-Tukey double arcsine transformation for proportions.

A: Depression, B: Anxiety, C: Anxiety and/or Depression D: Stress.

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Table 2. Results of random effect meta-analysis using Freeman-Tukey double arcsine transformation for proportions, regardless of the duration of their symptoms.

https://doi.org/10.1371/journal.pone.0312351.t002

Results of meta-analysis, subgroup analysis and meta-regression analysis

Table 2 provides a summary of the overall prevalence of depression, anxiety, stress, and suicidality in individuals with long-COVID, regardless of the duration of their symptoms depression, 25% (95% CI: 22–28%; PI:1–59%); anxiety (adjusted via trim and fill method), 23% (95% CI:21–25%; PI: 2–35%); composite outcomes of depression and/or anxiety, 25% (95% CI: 23–27%; PI: 2–51%); stress, 26% (95% CI: 13–39%; PI: 1–69%); and suicidality, 19% (95% CI: 15–22%; PI: 13–25%).

The results of the subgroup and meta-regression analyses, stratified by follow-up duration, age, gender, study design, and study setting, are summarized in Table 3 and Fig 3. Regarding the depression, the pooled prevalence of depression at follow-up intervals of up to 6 months, 6–12 months, and 12–24 months was 27% (95% CI: 23–31%), 23% (95% CI: 20–26%), and 15% (95% CI: 9–21%), respectively, exhibiting a non-significant decreasing trend over time (Beta = -0.04, P = 0.06). Meta-regression analyses revealed studies with a higher proportion of female participants reported a significantly higher prevalence of depression compared to those with a greater proportion of male participants (27% vs. 20%, P = 0.025). Additionally, individuals aged ≤50 years exhibited a significantly higher prevalence of depression compared to those >50 years (27% vs. 22%, P = 0.033). Population-based studies reported a slightly lower prevalence compared to non-population-based studies (21% vs. 28%, P = 0.07), though this difference was not statistically significant. Finally, there were minimal setting-related differences, with a pooled prevalence of 25% for studies conducted in both developing and non-developing countries, showing no significant differences by study setting.

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Fig 3.

Subgroup and meta-regression analysis of depression, anxiety, and composite outcomes of depression and/or anxiety results stratified by: (A) gender (Studies with more women participants vs, Studies with more men participants), (B) Study setting (living in developing vs. developed countries), (C) Study design, (population-based vs. non-population-based), (D) Age (< = 50 yr vs. >50 yr), and (E) Follow-up time (up to 6 months, 6–12 months, and 12–24 months) in individuals with long covid. RD: risk difference.

https://doi.org/10.1371/journal.pone.0312351.g003

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Table 3. The results of the subgroup and meta-regression analyses, stratified by follow-up duration, age, gender, study design, and study setting.

https://doi.org/10.1371/journal.pone.0312351.t003

Regarding anxiety, the pooled prevalence at follow-up duration of up to 6 months, 6–12 months, and 12–24 months was 25% (95% CI: 21–29%), 21% (95% CI: 19–23%), and 21% (95% CI: 12–29%), respectively, showing a non-significant decreasing trend over time (Beta = -0.03, P = 0.205). Meta-regression analyses revealed that studies with a higher proportion of female participants reported a significantly higher prevalence of anxiety compared to those with a higher proportion of male participants (27% vs. 20%, P = 0.025). While individuals aged ≤50 years had a non-significantly higher prevalence of anxiety compared to those >50 years (25% vs. 20%, P = 0.159), this difference did not reach statistical significance. Population-based studies reported a slightly lower prevalence compared to non-population-based studies (25% vs. 20%, P = 0.072), although this difference was also not statistically significant. Lastly, studies conducted in developed countries had a higher, but non-significant, pooled prevalence of anxiety compared to those in developing countries (24% vs. 20%, P = 0.254).

The composite outcome of depression and/or anxiety demonstrated a consistent pattern, with pooled prevalence rates at follow-up intervals of up to 6 months, 6–12 months, and 12–24 months being 27% (95% CI: 25–30%), 23% (95% CI: 21–24%), and 20% (95% CI: 16–24%), respectively, indicating a significant decreasing trend over time (Beta = -0.04, P = 0.022). Studies with a higher proportion of female participants reported a significantly higher prevalence of the composite outcome compared to those with a higher proportion of male participants (28% vs. 22%, P = 0.007). Meta-regression analyses revealed that individuals aged ≤50 years exhibited a significantly higher prevalence compared to those >50 years (28% vs. 22%, P = 0.011). Setting-related and study design differences were minimal, with both population-based and non-population-based studies showing a pooled prevalence of 24%, and studies from developing and developed countries showing pooled prevalences of 24% and 25%, respectively, with no statistically significant difference.

Due to a lack of data, we could not perform those analysis for stress and suicidality.

Determinants of outcomes

Moste of the studies presented factors associated with persistent psychological symptoms in patients with long-COVID which categories as 4 factors, including:

(i) Demographic and socioeconomic factors.

It was included: male gender [14, 96], female gender [17, 28, 36, 44, 55, 61, 62, 71, 93, 94], Older patients [18, 28, 36, 55, 90], younger patients [41, 66, 94, 96], lower educational level [28, 75], life stressors including death of a close contact and new disability, negative experiences with medical professionals, family, friends, partners and employers [36, 96], patients living alone [7, 72], Specific demographic groups (people of color such as African American/ Black individuals and sexual and gender minorities such as non-binary gender) [16, 83, 96];

(ii) Lifestyle and health status factors.

It was included: lower income and financial insecurity [16, 71, 96], unemployment [96], inactivity [72, 96], low quality of life [81], Suffering from one or multi co-morbidities [71] such as type 2 diabetes [17, 18], kidney diseases [18], Respiratory complaints [39], arterial hypertension, obesity [44, 94, 99], previous psychiatric diagnosis or pre-existing depression or anxiety [62, 67, 83, 96, 97] and negative attitude towards the pandemic [72], perceiving to have poorer health [94, 96];

(iii) Acute COVID-19 infection characteristics.

It was included: oxygen support or mechanically ventilated [17, 99], admitted to Intensive Care Unit (ICU) [18, 80], hospitalization or stayed a long duration in the hospital [18, 80, 102], severe and longer duration of symptoms in acute phase [18, 36, 55, 62, 91, 96, 103], used Chloroquine [18], neurological complications during index hospitalization [36], Favipiravir prescription [7], Outpatient care [78];

(iv) Disease progression factors.

It was included: numbers of persistent symptoms [39, 75, 90], presence of psychopathology such as depressive symptoms, fatigue and cognitive impairment after acute phase [44, 62, 81, 99], Hypoechogenic brainstem raphe alterations in transcranial sonography (TCS) [73], affective affectation [75].

Discussion

This systematic review and meta-analysis estimated the prevalence of significant mental health symptoms in individuals with long-COVID. Additionally, it provided evidence on the trends of these problems over time and identified key determinants. The results of our study showed that one-fourth of patients suffering from long-COVID experienced mental health symptoms, including depression, anxiety, and stress. Additionally, although the results were inconclusive due to a lack of data, one-fifth of these patients exhibited suicidality. Furthermore, longer follow-up, up to 24 months, indicated that the trend of these symptoms slightly decreased over time. Being a woman and younger age were significantly associated with a higher prevalence of mental health issues.

After a while since the first cases emerged, the direct effects of COVID-19 on mental health were starting to become apparent [105]. Uncertainty, social distancing, economic disruptions, stringent infection control, and national lockdowns and disruption to mental health services induced by the COVID-19 pandemic, led to heightened levels psychological challenges [106, 107]. In one of the preliminary reports, Nochaiwong et al. (2020) conducted a systematic review and meta-analysis of 107 observational studies spanning 32 countries. Their findings revealed prevalence estimates of 28.0% for depression, 26.9% for anxiety, and 36.5% for stress among individuals who had experienced preliminary COVID- 19 infection. These results highlighted a notable increase in the prevalence of common mental health problems during the pandemic compared to the pre-COVID-19 era [108].

Nevertheless, emerging evidence has demonstrated that a spectrum of sequelae and complications can persist long after the acute infection, irrespective of the severity of the initial illness, collectively referred to as long- COVID [109]. Similar to acute COVID-19, long- COVID can affect multiple organs and systems, resulting in a wide range of symptoms, including mental health symptoms.

While accurately reporting long-COVID symptoms is challenging due to accuracy of diagnosis, reporting systems, population assessed, accuracy of self-reporting and length of follow-up period, our meta-analysis revealed that approximately 25% of patients with persistent symptoms experience mental health problems including anxiety and/or depression and stress. This condition may pose a significant public health concern, affecting millions of individuals worldwide. In a recent published study, Zheng et al. (2023), in a meta-analysis and systematic review of 40 studies with 12,424 individuals, reported that the pooled prevalence of any long COVID and psychiatric symptoms in children and adolescents with long covid were 23.36% (95% CI: 15.27–32.53) and (12.30%, 95% CI: 5.38–21.37), respectively [110].

Although the underlying mechanisms of mental problems in individual with COVID remain unclear, some evidence suggests that the virus can infect the central nervous system (CNS) via hematogenous or neuronal retrograde neuro-invasive routes. This infection can also induce septic encephalopathy and may affect the permeability of the blood-brain barrier, allowing peripheral cytokines and other blood-derived substances to enter the CNS and contribute to neuroinflammation [111–113].

Additionally, the pandemic itself has had a negative impact on mental health. Living through a global health crisis, experiencing hospitalization, quarantine, isolation, social distancing, loneliness, reduced physical activity, and financial insecurity all potentially increase the risk of anxiety and depression [107, 111]. These processes may collectively contribute to the development of long-term mental health issues following COVID-19.

Despite inconclusive results due to data limitations, our study found a concerning prevalence of suicidality among individuals with long-COVID, affecting one-fifth of the patient population. Suicidality is a complex outcome influenced by multiple factors, including the interplay of physical health sequelae, psychological distress, and social determinants [114, 115]. Future longitudinal studies with robust methodologies are warranted to confirm this finding and to elucidate the causal pathways and identify effective strategies for suicide prevention in this vulnerable population.

Furthermore, although we observed a gradual decrease in the prevalence of mental health problems over time, the prevalence remained high even after 24 months of follow-up. This persistent prevalence underscores the long-term impact of COVID-19 on mental health and highlights the need for sustained mental health support for these individuals. However, the slight yet significant decrease in mental health symptoms may reflect natural recovery processes or the positive effects of ongoing medical and psychological interventions. However, the high prevalence of these issues after two years suggests that many individuals continue to experience substantial psychological distress long after their initial COVID-19 infection.

In addition, our systematic review identified several key factors associated with persistent psychological symptoms in individuals with Long COVID. These factors can be broadly categorized into four main domains of demographic and socioeconomic factors, lifestyle and health status factors, acute COVID-19 infection characteristics, and disease progression factors. These findings highlight the multifaceted nature of psychological sequelae in Long COVID, influenced by a complex interplay of demographic, socioeconomic, health-related, and disease-specific factors, which is crucial for informing clinical practice and public health strategies. Specifically, being female and residing in developed countries were significantly linked to increased rates of depression among individuals with long-COVID. This gender disparity may reflect broader trends observed in mental health, where females are generally more susceptible to depression due to a combination of biological, hormonal, and psychosocial factors. The higher prevalence of depression in developed countries could be attributed to various factors. These include greater awareness and reporting of mental health issues, better diagnostic capabilities, and possibly higher levels of stress and lifestyle changes associated with the pandemic in these regions.

We observed a lower prevalence of these mental health symptoms in population-based studies compared to clinical or hospital-based studies. This difference likely reflects the broader inclusion of asymptomatic and mild cases in population-based research, whereas clinical studies tend to focus on more severe COVID-19 cases prone to persistent mental health issues.

In the current meta-analysis, we assessed publication bias across the included studies. Except for anxiety, where some evidence of publication bias was detected, no significant publication bias was found for depression, stress, or suicidality. For anxiety, the bias was adjusted using the trim and fill method, ensuring that the overall findings remain robust and reliable.

It should be noted that the included studies exhibited heterogeneity. Subgroup analysis suggested that variations in populations, particularly younger age, follow-up duration and female gender, may contribute to this heterogeneity. However, other potential factors, such as ethnicity, socioeconomic status, and lifestyle, could also play a role but were not fully explored. Additionally, the use of different questionnaires and assessment tools to gather data likely contributed to the observed heterogenicity. Variations in study design, sample size, and regional healthcare practices might also have played a role in increasing heterogeneity among the studies.

Our study had some limitations. Despite conducting an extensive literature search, certain unpublished studies that and those written in languages other than English were not included. Additionally, the number of studies that assessed stress and suicidality prevalence was limited, restricting our ability to perform additional analyses. Furthermore, different tools have been used to assess mental health symptoms across studies, leading to potential inconsistencies and variations in reported prevalence rates. Additionally, data on individuals who had severe forms of COVID-19 and subsequently died are lacking. This absence potentially underrepresents the most severe cases in existing research. Furthermore, there were limitations in the data collected, as most of the papers did not present data related to determinants and associated factors specifically for mental health in individuals with long-COVID. Finally, the findings do not generalize to patients who have had COVID-19 but were not diagnosed.

Conclusion

In conclusion, we found that one-fourth of individuals with long-COVID suffer from mental health symptoms, including depression, anxiety, and stress. Although these symptoms showed a slight decreasing trend over time, their prevalence remained high even two years after the initial infection. While various factors contribute to mental health symptoms in these patients, our analysis highlighted that women and being younger are particularly vulnerable to higher rates of anxiety and depression. These findings emphasize the need for screening and providing adequate support or early intervention for individuals with long COVID to address and reduce long-term psychological distress.

Acknowledgments

The authors would like to extend their gratitude to the Nord University Library for their assistance in gathering the articles.

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