Global burden and inequities for PTSD among Healthcare Workers: A Systematic Review and Meta-Analysis

Global burden and inequities for PTSD among Healthcare Workers: A Systematic Review and Meta-Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Global burden and inequities for PTSD among Healthcare Workers: A Systematic Review and Meta-Analysis Jie Sun, Hua-An Fang, Yongbo Zheng, Karina Pereira-Lima, Si-Qi Tong, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8729203/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Posttraumatic stress disorder (PTSD) is a critical occupational health concern among health care workers (HCWs). Quantifying global prevalence and identifying risk factors is critical for guiding intervention and policy strategies. A systematic review and meta-analysis was performed following PRISMA guidelines (PROSPERO CRD42024587810). A literature search of PubMed, Embase, PsycINFO, Web of Science, and Cochrane Library databases was performed from database inception to March 11, 2025. Observational studies reporting PTSD prevalence and odds ratios (ORs) for PTSD risk factors among HCWs were included. The primary outcome was p ooled prevalence of PTSD and ORs for risk factors among HCWs. A total of 308 studies from 60 countries were included, comprising 371,211 HCWs. The pooled PTSD prevalence was 27.2% (95% CI, 25.3%–29.2%). Higher prevalence was observed among female (31.5%), nurses (28.6%), HCWs in low- and middle-income countries (30.0%), and those in Africa (40.8%). Prevalence increased from 20.2% (95% CI, 14.4%–26.0%) before COVID-19 to 27.8% (95% CI, 25.8%–29.8%) after its onset, with meta-regression showing a significant upward trend over time (β = 9.94*10 -4 , P = 0.012). The strongest risk factors for PTSD included a history of mental disorder (OR, 2.08; 95% CI, 1.54–2.80), nursing occupation (OR, 1.60; 95% CI, 1.41–1.82), and symptomatic family or friends (OR, 1.53; 95% CI, 1.22–1.90). These findings indicate a substantial psychological burden among HCWs and identify subgroups with higher vulnerability across settings. Health sciences/Diseases/Psychiatric disorders Health sciences/Diseases Health sciences/Diseases/Psychiatric disorders Health sciences/Diseases Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Healthcare workers (HCWs) routinely face intense occupational stress, including exposure to patient suffering, death, and high-stakes decision-making. While often praised for their resilience, HCWs are not immune to the psychological toll of their profession[1]. Recurrent exposure to trauma, ethical dilemmas, long work hours, and moral injury can accumulate into significant increased risk for mental health problems, including posttraumatic stress disorder (PTSD)[2–4]. Emerging evidence[5–7] suggests that PTSD prevalence among HCWs exceeds that of the general population. PTSD symptoms in HCWs have been associated with burnout, reduced job satisfaction, and decreased quality of patient care[8, 9]. At a system level, widespread psychological distress among HCWs may disrupt workforce stability and undermine health system performance[10]. Studies suggest that these challenges were further exacerbated by the COVID-19 pandemic[4, 5, 11, 12], which introduced unprecedented stressors including surges in patient volumes, heightened personal risk, and resource shortages. In response, the World Health Organization (WHO) has characterized the post-pandemic state of HCWs as a “long-standing crisis of burnout, exhaustion and moral injury.” While the pandemic brought renewed attention to HCW mental health, much of the existing literature has focused narrowly on COVID-specific stressors[4, 11], leaving the broader and ongoing burden of PTSD underexplored. Key research questions remain. First, what are the baseline rates of PTSD among HCWs outside pandemic conditions? Second, how has the prevalence of PTSD among HCWs evolved over recent years, and how do these trends differ across occupational roles? Third, which risk factors consistently associate with PTSD risk across both routine and crisis conditions? This systematic review and meta-analysis address these questions through a comprehensive synthesis of global data. Specifically, by analyzing data from diverse clinical settings and time periods, we aimed to estimate pooled global PTSD prevalence among HCWs, examine variation by demographic, occupational, and contextual factors, and evaluate temporal trends. Our goal is to inform future mental health interventions and policies supporting HCWs across diverse settings and phases of healthcare delivery. Methods Study design and ethics This systematic review and meta-analysis followed the Meta-Analyses of Observational Studies in Epidemiology (MOOSE) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (eTable 1 and eTable2). The review protocol was prospectively registered in the PROSPERO database (CRD42024587810). Search Strategy and Selection Criteria Two authors (HAF and YYS) independently identified observational studies published before March 11, 2025, that reported on PTSD prevalence among healthcare workers and its associated risk factors. We systematically searched PubMed, Embase, PsycINFO, Web of Science, and Cochrane Library databases. The search strategy combined terms related to healthcare workers and PTSD (see eMethod). The reference lists of included articles and relevant reviews were also manually screened. The Peking University Third Hospital Institutional Review Board deemed this study exempt because it collected and synthesized nonidentifiable data from previously published studies. We included observational peer-reviewed studies that (1) reported the prevalence of PTSD among HCWs and/or (2) provided ORs or sufficient raw data to calculate ORs for possible risk and protective factors. Studies were excluded if they were case reports, reviews, conference abstracts, dissertations, trial registry records, notes, preprints, letters, or lacked sufficient data to calculate PTSD prevalence or odds ratios. For multiple publications using the same dataset, only the most comprehensive report was included. For longitudinal studies, only baseline PTSD data were extracted. The study selection process is illustrated in Figure 1. Data Extraction and Quality Assessment Four authors (HAF, YNZ, SYF, JZ) independently extracted data on study characteristics, including demographic, occupational, and traumatic exposure types, along with PTSD prevalence and odds ratios for associated factors. Extracted data were cross-checked by two additional reviewers (LYW and YX). Discrepancies were resolved by consensus. Two authors (SQT and SNZ) independently assessed the quality using the 11-item Agency for Healthcare Research and Quality (AHRQ) tool (eTable 4). Any discrepancies were resolved through discussions and consensus. Data Analysis Given the potential clinical and methodological heterogeneity, random-effects meta-analyses were conducted using the DerSimonian and Laird method to estimate pooled PTSD prevalence and associated 95% confidence intervals (CIs). Heterogeneity was quantified using the I 2 statistic (values 75% indicate considerable heterogeneity[13, 14]) and τ². Subgroup random-effect meta-analyses of PTSD prevalence were performed across key demographic (e.g., sex, age, marital status, parental status), occupational (e.g., role, education level, average weekly working hours, years of practice, income), traumatic-related (e.g. epidemic, work-related exposure and mass security incidents), PTSD assessment tool, and geographic variables (e.g., country income level, continent). Stratified meta-regression analyses examined changes in PTSD prevalence within each subgroup. Detailed categorization criteria for all variables can be found in eTable 5. To assess temporal trends, meta-regression was conducted using assessment year as continuous moderator. Multivariable meta-regression examined potential sources of heterogeneity, incorporating covariates including female proportion, investigating year, geographic region, and PTSD assessment method. To comprehensively evaluate the effect of COVID-19, we compared pooled PTSD prevalence estimates from studies conducted before (prior to January 1, 2020) and after the onset of COVID-19 (January 1, 2020, and onward) using random-effects models. Additionally, a meta-regression used a binary indicator for the pandemic period as a moderator. Subgroup random-effects meta-analyses of ORs for demographic and occupational factors used the same subgroups and methods described above. For multi-category variables such as occupation, we created dummy variables with physicians as the reference group to allow pairwise comparisons in meta-regression models. Additionally, we analyzed health-related factors (e.g., smoking, alcohol use, physical activity, and history of physical and mental disorders) and pandemic-related factors (e.g., COVID-19 infection status, quarantine, frontline work, use of personal protective measures, and infection among family, friends, or close contacts). The definitions of key terms used in the studies are listed in eTable 5. We used Egger’s test and visual inspection of funnel plots to assess potential publication bias. The trim-and-fill method was further applied to the overall analysis to estimate and adjust for potential missing studies due to publication bias. We also performed sensitivity analyses by sequentially removing individual studies to evaluate the robustness of pooled estimates. All analyses were performed using the meta-analysis package in Stata 18 software. A two-tailed P-value < 0.05 was considered statistically significant. Role of the funding source The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Results Study Characteristics Of 13,556 articles initially identified, 308 studies comprising 371,211 individuals across 60 countries were included in the final analysis (Figure 1). Most studies were cross-sectional (N = 274), with 34 longitudinal studies. Sample sizes ranged from 22 to 19,379 participants (median = 387, IQR = 211-992). Included studies were published between 1995 and early 2025, with a sharp increase in publications post-COVID-19 onset. Only one cohort study spanned both pre-pandemic and pandemic periods, precluding separate analysis of pandemic-spanning cohorts. Participants included nurses (107 studies), physicians (103 studies), and other HCWs (65 studies) from various settings (e.g., hospital wards, emergency departments, ICUs, outpatient clinics, and community health centers). Regarding traumatic exposure type, 267 studies investigated PTSD related to COVID-19, 6 other epidemics (SARS, H7N9, MERS), 21 work-related trauma (e.g., workplace violence, interpersonal pressure, ICU clinical experience, among others), and 12 focused on mass casualty incidents (e.g., war, terrorist attacks, explosions, earthquakes, and fires). Geographically, 165 studies were conducted in high-income countries (HICs), while 113 were from low- and middle-income countries (LMICs). The regional distribution included Asia (N = 110), Europe (N = 110), North America (N = 49), South America (N = 11), Africa (N = 14), Australia (N = 9), and multiple continents (N = 5). PTSD assessment utilized a range of validated tools and varying diagnostic cutoffs. Nearly all studies (N = 298) used self-reported assessments, with only 10 relying on clinician-administered tools. Detailed study characteristics are summarized in eTable 3, and quality assessments in eTable 4. Overall Prevalence The pooled prevalence of PTSD in HCWs was 27.2% (95% CI, 25.3%-29.2%), with substantial heterogeneity (I² = 99.7%, τ² = 0.032). Subgroup analyses were performed based on demographic characteristics, occupational factors, traumatic-related exposures, PTSD assessment tools and geographic features (Figure 2, and eFigure 1). Demographic Characteristics Female HCWs had a significantly higher PTSD prevalence (31.5%; 95% CI, 27.4%-35.6%, I² = 99.6%, τ² = 0.042) than males (24.7%; 95% CI, 21.3%-28.1%, I² = 98.2%, τ² = 0.028; P = 0.014). No significant differences were observed by age, marital or parental status. Occupational Factors Compared to physicians (20.4%; 95% CI, 17.0%-23.8%, I² = 98.3%, τ² = 0.025), nurses (28.6%; 95% CI, 24.8%-32.4%, I² = 99.4%, τ² = 0.035) and other HCWs (25.1%; 95% CI, 20.5%-29.7%, I² = 99.0%, τ² = 0.029) exhibited significantly higher PTSD prevalence ( P = 0.008). No significant differences were observed in subgroup analyses by educational level, working hours per week, years of practice, or personal income. Traumatic-related Characteristics Mass casualty incidents showed the highest PTSD prevalence (33.4%; 95% CI, 19.3%-47.5%, I² = 99.6%, τ² = 0.061), followed by epidemic (27.5%; 95% CI, 25.4%-29.5%, I² = 99.6%, τ² = 0.028), and work-related factors (21.4%; 95% CI, 15.2%-27.6%, I² = 98.7%, τ² = 0.020). However, differences across trauma types were not significant ( P = 0.141). Self-reported assessments yielded higher PTSD prevalence (27.5%, 95% CI: 25.5%-29.5%, I² = 99.6%, τ² = 0.029) compared to clinician-administered assessments (18.5%, 95% CI: 10.5%-26.5%, I² = 98.9%, τ² = 0.016; P = 0.115 ). Geographic Features PTSD prevalence was significantly higher in LMICs (30.0%; 95% CI, 26.5%-33.5%, I² = 99.7%, τ² = 0.037) compared with HICs (25.4%; 95% CI, 23.2%-27.6%, I² = 99.3%, τ² = 0.023; P = 0.024). Continental differences were significant ( P = 0.034), with Africa showing the highest prevalence (40.8%; 95% CI, 30.4%-51.3%, I² = 98.9%, τ² = 0.039) and North America the lowest (23.0%; 95% CI, 18.9%-27.2%, I² = 99.3%, τ² = 0.021). Temporal trend and COVID-19 Time-trend analysis demonstrated a significant increase in PTSD prevalence among HCWs (Figure 3A, β = 9.94*10 -4 , P = 0.012). No significant temporal trend was observed before COVID-19 (Figure 3B, β = 1.29*10 -4 , P = 0.695), whereas an upward trend was noted after the onset of COVID-19 (Figure 3C, β = 18.22*10 -4 , P = 0.094). Multivariable meta-regression showed high heterogeneity (I² = 99.5%) with low explanatory power (R² = 2.6%). Only investigation time was significantly associated with prevalence (exp(b) = 1.012; P = 0.010) (eTable 6). The prevalence of PTSD among HCWs was significantly higher after the onset of COVID-19 (27.8%; 95% CI, 25.8%-29.8%, I² = 99.6%, τ² = 0.029) compared to the pre-pandemic period (20.2%; 95% CI, 14.4%-26.0%, I² = 97.1%, τ² = 0.020, P = 0.046) (Figure 4, eFigure 2). Subgroup analyses revealed that compared to pre-pandemic, after the onset of COVID-19, PTSD prevalence was significantly higher among those exposed to mass casualty incidents (from 17.4% to 48.4%; P = 0.027), working in high-income countries (from 17.7% to 26.2%; P = 0.026) and North America (from 12.9% to 25.0%; P = 0.046)(Figure 4, eFigure 3). Risk Factors for PTSD Figure 5 and eFigure 4 summarize PTSD risk factors among HCWs. Female sex was consistently associated with increased PTSD risk (OR, 1.35; 95% CI, 1.22-1.49), evident both before COVID-19 (OR, 1.99; 95% CI, 1.15-3.43) and after the onset of the COVID-19 (OR, 1.34; 95% CI, 1.22–1.48). Age≥ 40 years, marital status and parental status were not significant predictors. Occupational role was a strong correlate of PTSD. Compared with physicians, nurses (OR, 1.60; 95% CI, 1.41–1.82) and other HCWs (OR, 1.29; 95% CI, 1.09–1.53) had elevated odds. These associations remained robust after the onset of the COVID-19. Educational attainment showed a modest protective effect. HCWs with postgraduate education had lower odds of PTSD (OR, 0.86; 95% CI, 0.78–0.95). Working hours ≥ 40 hours/week, practicing ≥ 10 years, and higher income were not significantly associated with PTSD risk. Several pandemic-specific exposures were notable. Prior mental illness (OR, 2.08; 95% CI, 1.54–2.80), COVID-19 infection (OR, 1.48; 95% CI, 1.23–1.78), frontline work (OR, 1.27; 95% CI, 1.01–1.60), exposure to infected individuals (OR, 1.43; 95% CI, 1.16–1.77), and having symptomatic family or friends (OR, 1.53; 95% CI, 1.22–1.90) were all associated with significantly elevated PTSD risk, while smoking and alcohol use were not. Sensitivity Analyses and Publication Bias Publication bias assessment revealed generally symmetrical distributions for most analyses. Significant publication bias was detected for overall PTSD prevalence (P < 0.001), pre-COVID-19 period ( P = 0.018), COVID-19-period prevalence (P < 0.001), and subgroup analyses. Detailed results are listed in eFigure 5 and eTable 7. After trim-and-fill adjustment for publication bias (k = 141 imputed studies), the pooled prevalence decreased substantially from 27.2% to 11.9% while maintaining statistical publication bias significance (P < 0.001). Sensitivity analyses demonstrated robust findings, with no single study significantly altering the pooled estimates (eFigure 6). Discussion This systematic review and meta-analysis synthesizes evidence on the global prevalence and risk factors for PTSD among HCWs. Across 308 studies representing over 370,000 HCWs from 60 countries, the pooled prevalence of PTSD was 27.2%. Prevalence estimates varied across subgroups, with higher estimates reported among female HCWs, nurses, those in low- and middle-income countries, and those in Africa. PTSD prevalence significantly increased over time, with a sharper rise after the COVID-19 onset. A history of mental disorders, nursing occupation, female sex, and COVID-19-related exposures were associated with increased odds of PTSD. These results provide important insights for guiding mental health policies and interventions. The prevalence estimates observed in this study are broadly consistent with previous reports indicating that healthcare workers experience higher levels of trauma-related mental health symptoms than the general population[ 4 , 5 , 15 , 16 ]. Prior studies have suggested that occupational stressors inherent to healthcare settings, including repeated exposure to patient suffering, high workload, and ethical challenges, may contribute to increased PTSD risk[ 17 , 18 ]. Nurses exhibited 1.6-fold greater odds of PTSD than physicians, possibly related to differences in trauma exposure, training, and institutional support[ 19 – 21 ]. Higher educational attainment was associated with a modest protective effect, potentially due to enhanced professional resilience, autonomy, or access to resources[ 22 – 24 ]. Female HCWs had 1.35-fold increased odds of PTSD compared to males, consistent with prior research[ 4 , 25 ]. While this may partly reflect biological differences, sociocultural dynamics, including the overrepresentation of women in high-risk healthcare roles such as nursing may contribute to this sex difference[ 26 – 28 ]. In our study, variables such as younger age, marital status, and parental status were not significantly associated with PTSD, despite theoretical expectations that work–family conflict and early career stressors might increase vulnerability to PTSD[ 29 – 31 ]. Evidence on protective factors was limited; physical activity was examined in a small number of studies and appeared to be associated with lower odds of PTSD, although data were insufficient to draw firm conclusions[ 32 – 34 ]. PTSD risk also varied by trauma type. Mass casualty events were associated with the highest prevalence, followed by epidemic and work-related trauma. Although differences across trauma types did not reach statistical significance, this trend likely reflects variations in trauma severity, duration, and cumulative exposure. Epidemics, particularly COVID-19, with prolonged uncertainty and repeated moral stressors, uniquely contributed to psychological burden[ 35 , 36 ]. Additionally, self-reported assessments yielded higher PTSD estimates than clinician-administered assessments, possibly due to greater disclosure through anonymous formats[ 11 , 37 ]. PTSD prevalence estimates differed across geographic and economic contexts. PTSD prevalence was significantly higher in LMICs and especially elevated in Africa. These patterns may reflect variation in healthcare workforce capacity, access to mental health services, and clinical workload across settings[ 38 – 43 ]. Temporal analyses confirmed a significant rise in PTSD prevalence following the onset of the COVID-19 pandemic. Before the pandemic, prevalence estimates remained relatively stable; however, after January 2020, a clear upward trajectory emerged. Although prevalence levels remained higher in low- and middle-income countries, a statistically significant pre–post increase was observed in high-income countries, with pooled prevalence rising from 17.7% before COVID-19 to 26.2% after its onset. This pattern may reflect lower pre-pandemic baseline prevalence in high-income settings and pandemic-related changes in working conditions and service organisation[ 44 – 46 ]. COVID-19-specific exposures were consistently associated with elevated PTSD risk, including prior infection, quarantine, frontline work, and infection among family or friends[ 6 , 17 , 47 – 50 ] HCWs with a prior mental health diagnosis were more than twice as likely to develop PTSD, indicating increased vulnerability among individuals with pre-existing mental health conditions. This study has several limitations. Substantial heterogeneity was observed across analyses, which is expected given the large number of studies. Publication bias was suggested by funnel plot asymmetry and addressed via trim-and-fill analysis, which imputed 141 studies and yielded a lower pooled estimate. In contrast, risk factor analyses showed lower heterogeneity, with female sex, lower educational attainment, and nursing occupation consistently associated with higher risk. The convergence of findings from prevalence and risk factor analyses supports the consistency of observed associations, although publication bias suggests caution in interpretation. In addition, only one study included longitudinal data spanning pre- and post-COVID-19 onset periods, limiting within-cohort comparisons. Some subgroup analyses were underpowered, and variability in the reporting of age and trauma exposure constrained more detailed modelling. Despite these limitations, this study represents one of the most comprehensive syntheses to date on PTSD among HCWs. The large, globally representative sample and consistent findings across sensitivity analyses strengthen the robustness and generalizability of the findings. This systematic review and meta-analysis found that PTSD was common among healthcare workers across settings, with higher prevalence observed among female healthcare workers, nurses, and those working in LMIC countries, particularly in Africa. Comparisons of studies conducted before and after the onset of the COVID-19 pandemic indicated higher PTSD prevalence estimates after the pandemic onset. These findings describe patterns of psychological burden and vulnerability among healthcare workers across occupational, geographic, and temporal contexts, and may inform public health monitoring and workforce-related mental health policy planning. Declarations Contributors Lu, J Sun, and Fang conceptualised and designed the study. J Sun and Fang developed the methodology and conducted the literature search. Fang, Y N Zhang, Fan, Zhao, Y Y Sun, Tong, Z L Wang, Yang, S N Zhang, L Y Wang, and Li participated in study screening, data extraction, and risk-of-bias assessment. Fang, Y N Zhang, Fan, Zhao, Tong, Wei, Yang and Y Zhang performed the statistical analyses. J Sun, Fang, and Zheng interpreted the data and wrote the original draft of the manuscript. Bao, Y M Wang, Zheng, J Sun, Lu, Sen, and Lima critically reviewed and revised the manuscript for important intellectual content. Dr Lu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Dr J.Sun, Fang, and Zheng are co-first authors. contributed equally to this work. All authors approved the final version of the manuscript and had final responsibility for the decision to submit for publication. Data sharing No datasets were generated or analyzed during the current study. All data used were obtained from previously published studies and are publicly available. Further information about the data sources can be obtained from the corresponding author upon reasonable request. Acknowledgments This work was supported by the STI2030–Major Projects (2021ZD0200800) and the National Natural Science Foundation of China (82201644 and 82471505). Conflict of interests We declare no competing interests. Funding: This work was supported by the STI2030-Major Projects (2021ZD0200800) and the National Natural Science Foundation of China (82201644 and 82471505). Acknowledgments This work was supported by the STI2030–Major Projects (2021ZD0200800) and the National Natural Science Foundation of China (82201644 and 82471505). References Harvey SB, Epstein RM, Glozier N, Petrie K, Strudwick J, Gayed A, et al. Mental illness and suicide among physicians. The Lancet. 2021;398:920–930. Vance MC, Mash HBH, Ursano RJ, Zhao Z, Miller JT, Clarion MJD, et al. Exposure to Workplace Trauma and Posttraumatic Stress Disorder Among Intern Physicians. JAMA Network Open. 2021;4:e2112837. Greenberg N, Docherty M, Gnanapragasam S, Wessely S. Managing mental health challenges faced by healthcare workers during covid-19 pandemic. BMJ. 2020;368:m1211. Kamra M, Dhaliwal S, Li W, Acharya S, Wong A, Zhu A, et al. Physician posttraumatic stress disorder during COVID-19: a systematic review and meta-analysis. 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Ito M, Katayanagi A, Miyamae M, Inomata T, Takagishi Y, Kikuchi A, et al. Cognitive processing therapy for posttraumatic stress disorder in Japan: a randomized clinical trial. JAMA Netw Open. 2025;8:e2458059. Kola L, Kohrt BA, Hanlon C, Naslund JA, Sikander S, Balaji M, et al. COVID-19 mental health impact and responses in low-income and middle-income countries: reimagining global mental health. Lancet, Psychiatry. 2021;8:535–550. Mehta LS, Churchwell K, Coleman D, Davidson J, Furie K, Ijioma NN, et al. Fostering psychological safety and supporting mental health among cardiovascular health care workers: a science advisory from the American heart association. Circulation. 2024. 9 July 2024. https://doi.org/10.1161/CIR.0000000000001259. Rugulies R, Aust B, Greiner BA, Arensman E, Kawakami N, LaMontagne AD, et al. Work-related causes of mental health conditions and interventions for their improvement in workplaces. Lancet (Lond Engl). 2023;402:1368–1381. Brauer R, Alfageh B, Blais JE, Chan EW, Chui CSL, Hayes JF, et al. Psychotropic medicine consumption in 65 countries and regions, 2008-19: a longitudinal study. Lancet, Psychiatry. 2021;8:1071–1082. Bryant RA, Nickerson A, Morina N, Liddell B. Posttraumatic stress disorder in refugees. Annu Rev Clin Psychol. 2023;19:413–436. Sun J, Rose-Clarke K, Bao Y, Wang Z, Lu L. Child and adolescent mental health policy advancement in China. Lancet Psychiatry. 2025;12:810–811. Zhang L, Ma M, Li D, Xin Z. The psychological typhoon eye effect during the COVID-19 outbreak in China: the role of coping efficacy and perceived threat. Global Health. 2020;16:105. Piscitello GM, Kapania EM, Miller WD, Rojas JC, Siegler M, Parker WF. Variation in ventilator allocation guidelines by US state during the coronavirus disease 2019 pandemic: a systematic review. JAMA Netw Open. 2020;3:e2012606. Papa A, Barile JP, Jia H, Thompson WW, Guerin RJ. Gaps in mental health care-seeking among health care providers during the COVID-19 pandemic - United states, September 2022-may 2023. MMWR Morb Mortal Wkly Rep. 2025;74:19–25. Monk EJM, Foulkes S, Munro K, Atti A, Islam J, Hopkins S, et al. Characterisation of the SARS-CoV-2 pandemic in healthcare workers within the United Kingdom: risk factors for infection during four successive waves. J Infect. 2025;90:106393. Rudberg A-S, Havervall S, Månberg A, Jernbom Falk A, Aguilera K, Ng H, et al. SARS-CoV-2 exposure, symptoms and seroprevalence in healthcare workers in Sweden. Nat Commun. 2020;11:5064. Draper H, Wilson S, Ives J, Gratus C, Greenfield S, Parry J, et al. Healthcare workers’ attitudes towards working during pandemic influenza: a multi method study. BMC Public Health. 2008;8:192. Breslow AS, Simkovic S, Franz PJ, Cavic E, Liu Q, Ramsey N, et al. Racial and ethnic disparities in COVID-19-related stressor exposure and adverse mental health outcomes among health care workers. Am J Psychiatry. 2023;180:896–905. Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files SupplementaryMP.pdf Supplemental Online Content Cite Share Download PDF Status: Under Review Version 1 posted Reviewer # 4 agreed at journal 29 Apr, 2026 Reviewer # 3 agreed at journal 16 Apr, 2026 Reviewer # 2 agreed at journal 12 Feb, 2026 Reviewer # 1 agreed at journal 10 Feb, 2026 Reviewers invited by journal 10 Feb, 2026 Editor assigned by journal 01 Feb, 2026 Submission checks completed at journal 01 Feb, 2026 First submitted to journal 30 Jan, 2026 Unknown event 29 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8729203","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":588826513,"identity":"938e0d28-00b8-4b50-aba6-45951639b34f","order_by":0,"name":"Jie Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACxmYQWQFmPmBgYAPSB4jScoZBgoGB2YA4LRB9baRoYW5nPvyZd15dHf/sZsbHFWUMcnw3Egg5jC1NmnfbYQmJO4eZDc+cYzCWJKyFx4yZd9sBCYYb+cckG9sYEjcQ1sL/+TPvnDoJ+RvJbCAt9URo4WGQ5m1gljCAakkwIMIvZpJzjh2W3Hgjmdmw4ZyE4cwzD/BrMew//PjDm5o6frkbyYwPG8ps5PmOE7DFsAGVL4FfOQjIE1YyCkbBKBgFIx4AAOJCQMjsMleLAAAAAElFTkSuQmCC","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jie","middleName":"","lastName":"Sun","suffix":""},{"id":588826536,"identity":"efca4f3a-2724-4515-b743-11b5961f057a","order_by":1,"name":"Hua-An Fang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hua-An","middleName":"","lastName":"Fang","suffix":""},{"id":588826537,"identity":"3cbf3c1a-8e08-4c36-a018-27be08b66301","order_by":2,"name":"Yongbo 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University","correspondingAuthor":false,"prefix":"","firstName":"Yanping","middleName":"","lastName":"Bao","suffix":""},{"id":588826531,"identity":"e1512bae-0c7e-476f-8507-d1deee61300b","order_by":17,"name":"Daniel J Clauw","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"J","lastName":"Clauw","suffix":""},{"id":588826532,"identity":"fd1aae2e-e898-4b47-a00d-3014e75459cf","order_by":18,"name":"Srijan Sen","email":"","orcid":"https://orcid.org/0000-0003-4495-495X","institution":"University of Michigan-Ann Arbor","correspondingAuthor":false,"prefix":"","firstName":"Srijan","middleName":"","lastName":"Sen","suffix":""},{"id":588826533,"identity":"baa85fb7-853d-44c3-b0ea-57148f3d335d","order_by":19,"name":"Lin Lu","email":"","orcid":"https://orcid.org/0000-0003-0742-9072","institution":"Peking University Sixth Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2026-01-29 08:50:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8729203/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8729203/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103013523,"identity":"111925e8-6df3-475e-8582-127a54470425","added_by":"auto","created_at":"2026-02-19 16:00:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":116402,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow Diagram of Study Selection Process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis figure shows the systematic screening and selection process of studies included in the meta-analysis, following PRISMA guidelines. Records were identified through database searches, screened by title and abstract, and reviewed for full-text eligibility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviation\u003c/strong\u003e: PTSD, posttraumatic stress disorder.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8729203/v1/238ba0675a6bbb131e8ebf9c.png"},{"id":103013521,"identity":"a9ebf447-8915-42cc-98bf-a3e4dce55a1f","added_by":"auto","created_at":"2026-02-19 16:00:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":183356,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall Prevalence of Posttraumatic Stress Disorder among Healthcare Workers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis figure presents the pooled prevalence estimates of PTSD among healthcare workers, overall and stratified by demographic, occupational, and contextual characteristics. Subgroups include sex, age, marital status, parental status, occupation, education level, weekly working hours, years of practice, income level, type of traumatic event, PTSD assessment method, country income level, and continent. Prevalence estimates are reported with 95% confidence intervals (CIs), heterogeneity index (I²), and between-study variance (τ²).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: CI, confidence interval; I², heterogeneity index; τ², between-study variance.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8729203/v1/262588db011357b99d2710ed.png"},{"id":103050195,"identity":"445b886c-6f09-479b-aabb-8a5a62fbbc65","added_by":"auto","created_at":"2026-02-20 07:48:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":112046,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMeta-regression Analysis of Prevalence of Posttraumatic Stress Disorder among Healthcare Workers Estimated by Time\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis figure displays results from meta-regression analyses assessing temporal trends in PTSD prevalence among healthcare workers:\u003cbr\u003e\n(A) Overall meta-regression analysis shows a significant increase in PTSD prevalence among healthcare workers over time (β = 9.94 × 10⁻⁴, \u003cem\u003eP \u003c/em\u003e= 0.012).\u003c/p\u003e\n\u003cp\u003e(B) No significant temporal trend was observed before COVID-19 (β = 1.29 × 10⁻⁴, \u003cem\u003eP\u003c/em\u003e = 0.695).\u003c/p\u003e\n\u003cp\u003e(C) An upward trend was noted after the onset of COVID-19 (β = 18.22 × 10⁻⁴, \u003cem\u003eP\u003c/em\u003e = 0.094).\u003cbr\u003e\nRegression coefficients (β) and associated \u003cem\u003eP\u003c/em\u003e values are reported to indicate the direction and significance of change over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviation\u003c/strong\u003e: CI, confidence interval; Adjusted R\u003csup\u003e2\u003c/sup\u003e = goodness of fit; P \u0026lt; 0.05 indicates statistically significant.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8729203/v1/0fdb2b10c356e974c511d20d.png"},{"id":103013524,"identity":"8b20f285-df8e-47fe-9a8d-385d5cdca342","added_by":"auto","created_at":"2026-02-19 16:00:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":228503,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of Posttraumatic Stress Disorder among Healthcare Workers Before and After the Onset of COVID-19\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis figure compares the pooled prevalence of PTSD before and after the onset of the COVID-19 pandemic, stratified by sex, age, marital status, parental status, occupation, education, weekly working hours, years of practice, income level, type of traumatic event, PTSD assessment method, country income level, and continent. Estimates include 95% CIs, I², and τ² for each subgroup. \u003cem\u003eP\u003c/em\u003e values indicate statistical differences between time periods based on intergroup regression analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: CI, confidence interval; NA, not available.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8729203/v1/164e6323ae76b952651e6841.png"},{"id":103013527,"identity":"4e29fb68-2912-4d14-a3ad-82562b22c5fa","added_by":"auto","created_at":"2026-02-19 16:00:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":163961,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFactors Associated with Posttraumatic Stress Disorder among Healthcare Workers (Overall, Before, and After the Onset of COVID-19)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis figure summarizes the pooled ORs and 95% CIs for individual-level and contextual risk factors associated with PTSD in healthcare workers. Subgroup analyses were performed for female sex, age ≥40 years, marital and parental status, occupation, education level, income level, health history, COVID-19 exposure, and protective factors. Results are reported overall, before COVID-19, and after its onset. Heterogeneity statistics (I², τ²) and \u003cem\u003eP\u003c/em\u003e values from intergroup regression analyses are presented to assess effect size differences across periods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: CI, confidence interval; I², heterogeneity index; OR, odds ratio; PTSD, posttraumatic stress disorder; NA, not available.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8729203/v1/e2e681b5046f96c060b1dc1a.png"},{"id":103051309,"identity":"09b54f45-ffab-4d1f-ad80-dcf37b9eabc7","added_by":"auto","created_at":"2026-02-20 07:59:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1404363,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8729203/v1/f9d842d9-817a-44c7-af10-d42d632aa2df.pdf"},{"id":103013525,"identity":"e22539c1-b6e3-43db-8ba6-f6615af22cdf","added_by":"auto","created_at":"2026-02-19 16:00:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11845535,"visible":true,"origin":"","legend":"Supplemental Online Content","description":"","filename":"SupplementaryMP.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8729203/v1/b07bb2a4e09e5e8ab7780762.pdf"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Global burden and inequities for PTSD among Healthcare Workers: A Systematic Review and Meta-Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHealthcare workers (HCWs) routinely face intense occupational stress, including exposure to patient suffering, death, and high-stakes decision-making.\u0026nbsp;While often praised for their resilience, HCWs are not immune to the psychological toll of their profession[1]. Recurrent exposure to trauma, ethical dilemmas, long work hours, and moral injury can accumulate into significant increased risk for mental health problems, including posttraumatic stress disorder (PTSD)[2–4].\u003c/p\u003e\n\u003cp\u003eEmerging evidence[5–7] suggests that PTSD prevalence among HCWs exceeds that of the general population. PTSD symptoms in HCWs have been associated with burnout, reduced job satisfaction, and decreased quality of patient care[8, 9]. At a system level, widespread psychological distress among HCWs may disrupt workforce stability and undermine health system performance[10].\u003c/p\u003e\n\u003cp\u003eStudies suggest that these challenges were further exacerbated by the COVID-19 pandemic[4, 5, 11, 12], which introduced unprecedented stressors including surges in patient volumes, heightened personal risk, and resource shortages. In response, the World Health Organization (WHO) has characterized the post-pandemic state of HCWs as a “long-standing crisis of burnout, exhaustion and moral injury.” While the pandemic brought renewed attention to HCW mental health, much of the existing literature has focused narrowly on COVID-specific stressors[4, 11], leaving the broader and ongoing burden of PTSD underexplored. Key research questions remain. First, what are the baseline rates of PTSD among HCWs outside pandemic conditions? Second, how has the prevalence of PTSD among HCWs evolved over recent years, and how do these trends differ across occupational roles? Third, which risk factors consistently associate with PTSD risk across both routine and crisis conditions?\u003c/p\u003e\n\u003cp\u003eThis systematic review and meta-analysis address these questions through a comprehensive synthesis of global data. Specifically, by analyzing data from diverse clinical settings and time periods, we aimed to estimate pooled global PTSD prevalence among HCWs, examine variation by demographic, occupational, and contextual factors, and evaluate temporal trends. Our goal is to inform future mental health interventions and policies supporting HCWs across diverse settings and phases of healthcare delivery.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and ethics\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis systematic review and meta-analysis followed the Meta-Analyses of Observational Studies in Epidemiology (MOOSE) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (eTable 1 and eTable2). The review protocol was prospectively registered in the PROSPERO database (CRD42024587810).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSearch Strategy and Selection Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo authors (HAF and YYS) independently identified observational studies published before March 11, 2025, that reported on PTSD prevalence among healthcare workers and its associated risk factors. We systematically searched PubMed, Embase, PsycINFO, Web of Science, and Cochrane Library databases. The search strategy combined terms related to healthcare workers and PTSD (see eMethod). The reference lists of included articles and relevant reviews were also manually screened. The Peking University Third Hospital Institutional Review Board deemed this study exempt because it collected and synthesized nonidentifiable data from previously published studies. We included observational peer-reviewed studies that (1) reported the prevalence of PTSD among HCWs and/or (2) provided ORs or sufficient raw data to calculate ORs for possible risk and protective factors. Studies were excluded if they were case reports, reviews, conference abstracts, dissertations, trial registry records, notes, preprints, letters, or lacked sufficient data to calculate PTSD prevalence or odds ratios. For multiple publications using the same dataset, only the most comprehensive report was included. For longitudinal studies, only baseline PTSD data were extracted. The study selection process is illustrated in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Extraction and Quality Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour authors (HAF, YNZ, SYF, JZ) independently extracted data on study characteristics, including demographic, occupational, and traumatic exposure types, along with PTSD prevalence and odds ratios for associated factors. Extracted data were cross-checked by two additional reviewers (LYW and YX). Discrepancies were resolved by consensus.\u003c/p\u003e\n\u003cp\u003eTwo authors (SQT and SNZ) independently assessed the quality using the 11-item Agency for Healthcare Research and Quality (AHRQ) tool (eTable 4). Any discrepancies were resolved through discussions and consensus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the potential clinical and methodological heterogeneity, random-effects meta-analyses were conducted using the DerSimonian and Laird method to estimate pooled PTSD prevalence and associated 95% confidence intervals (CIs). Heterogeneity was quantified using the I\u003csup\u003e2\u003c/sup\u003e statistic (values \u0026lt; 25% indicate low; 25%\u0026ndash;75% indicate moderate, and \u0026gt; 75% indicate considerable heterogeneity[13, 14]) and \u0026tau;\u0026sup2;. Subgroup random-effect meta-analyses of PTSD prevalence were performed across key demographic (e.g., sex, age, marital status, parental status), occupational (e.g., role, education level, average weekly working hours, years of practice, income), traumatic-related (e.g. epidemic, work-related exposure and mass security incidents), PTSD assessment tool, and geographic variables (e.g., country income level, continent). Stratified meta-regression analyses examined changes in PTSD prevalence within each subgroup. Detailed categorization criteria for all variables can be found in eTable 5.\u003c/p\u003e\n\u003cp\u003eTo assess temporal trends, meta-regression was conducted using assessment year as continuous moderator. Multivariable meta-regression examined potential sources of heterogeneity, incorporating covariates including female proportion, investigating year, geographic region, and PTSD assessment method. To comprehensively evaluate the effect of COVID-19, we compared pooled PTSD prevalence estimates from studies conducted before (prior to January 1, 2020) and after the onset of COVID-19 (January 1, 2020, and onward) using random-effects models. Additionally, a meta-regression used a binary indicator for the pandemic period as a moderator.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSubgroup random-effects meta-analyses of ORs for demographic and occupational factors used the same subgroups and methods described above. For multi-category variables such as occupation, we created dummy variables with physicians as the reference group to allow pairwise comparisons in meta-regression models. Additionally, we analyzed health-related factors (e.g., smoking, alcohol use, physical activity, and history of physical and mental disorders) and pandemic-related factors (e.g., COVID-19 infection status, quarantine, frontline work, use of personal protective measures, and infection among family, friends, or close contacts). The definitions of key terms used in the studies are listed in eTable 5.\u003c/p\u003e\n\u003cp\u003eWe used Egger\u0026rsquo;s test and visual inspection of funnel plots to assess potential publication bias. The trim-and-fill method was further applied to the overall analysis to estimate and adjust for potential missing studies due to publication bias. We also performed sensitivity analyses by sequentially removing individual studies to evaluate the robustness of pooled estimates. All analyses were performed using the meta-analysis package in Stata 18 software. A two-tailed P-value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of the funding source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf 13,556 articles initially identified, 308 studies comprising 371,211 individuals across 60 countries were included in the final analysis (Figure 1). Most studies were cross-sectional (N = 274), with 34 longitudinal studies. Sample sizes ranged from 22 to 19,379 participants (median = 387, IQR = 211-992). Included studies were published between 1995 and early 2025, with a sharp increase in publications post-COVID-19 onset. Only one cohort study spanned both pre-pandemic and pandemic periods, precluding separate analysis of pandemic-spanning cohorts. Participants included nurses (107 studies), physicians (103 studies), and other HCWs (65 studies) from various settings (e.g., hospital wards, emergency departments, ICUs, outpatient clinics, and community health centers). Regarding traumatic exposure type, 267 studies investigated PTSD related to COVID-19, 6 other epidemics (SARS, H7N9, MERS), 21 work-related trauma (e.g., workplace violence, interpersonal pressure, ICU clinical experience, among others), and 12 focused on mass casualty incidents (e.g., war, terrorist attacks, explosions, earthquakes, and fires). Geographically, 165 studies were conducted in high-income countries (HICs), while 113 were from low- and middle-income countries (LMICs). The regional distribution included Asia (N = 110), Europe (N = 110), North America (N = 49), South America (N = 11), Africa (N = 14), Australia (N = 9), and multiple continents (N = 5). PTSD assessment utilized a range of validated tools and varying diagnostic cutoffs. Nearly all studies (N = 298) used self-reported assessments, with only 10 relying on clinician-administered tools. Detailed study characteristics are summarized in eTable 3, and quality assessments in eTable 4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverall Prevalence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of PTSD in HCWs was 27.2% (95% CI, 25.3%-29.2%), with substantial heterogeneity (I² = 99.7%, τ² = 0.032). Subgroup analyses were performed based on demographic characteristics, occupational factors, traumatic-related exposures, PTSD assessment tools and geographic features (Figure 2, and eFigure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFemale HCWs had a significantly higher PTSD prevalence (31.5%; 95% CI, 27.4%-35.6%, I² = 99.6%, τ² = 0.042) than males (24.7%; 95% CI, 21.3%-28.1%, I² = 98.2%, τ² = 0.028; \u003cem\u003eP =\u003c/em\u003e 0.014). No significant differences were observed by age, marital or parental status.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOccupational Factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared to physicians (20.4%; 95% CI, 17.0%-23.8%, I² = 98.3%, τ² = 0.025), nurses (28.6%; 95% CI, 24.8%-32.4%, I² = 99.4%, τ² = 0.035) and other HCWs (25.1%; 95% CI, 20.5%-29.7%, I² = 99.0%, τ² = 0.029) exhibited significantly higher PTSD prevalence (\u003cem\u003eP =\u003c/em\u003e 0.008). No significant differences were observed in subgroup analyses by educational level, working hours per week, years of practice, or personal income.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTraumatic-related Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMass casualty incidents showed the highest PTSD prevalence (33.4%; 95% CI, 19.3%-47.5%, I² = 99.6%, τ² = 0.061), followed by epidemic (27.5%; 95% CI, 25.4%-29.5%, I² = 99.6%, τ² = 0.028), and work-related factors (21.4%; 95% CI, 15.2%-27.6%, I² = 98.7%, τ² = 0.020). However, differences across trauma types were not significant (\u003cem\u003eP =\u003c/em\u003e 0.141). Self-reported assessments yielded higher PTSD prevalence (27.5%, 95% CI: 25.5%-29.5%, I² = 99.6%, τ² = 0.029) compared to clinician-administered assessments (18.5%, 95% CI: 10.5%-26.5%, I² = 98.9%, τ² = 0.016; \u003cem\u003eP =\u003c/em\u003e 0.115 ).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeographic Features\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePTSD prevalence was significantly higher in LMICs (30.0%; 95% CI, 26.5%-33.5%, I² = 99.7%, τ² = 0.037) compared with HICs (25.4%; 95% CI, 23.2%-27.6%, I² = 99.3%, τ² = 0.023; \u003cem\u003eP =\u003c/em\u003e 0.024). Continental differences were significant (\u003cem\u003eP =\u003c/em\u003e 0.034), with Africa showing the highest prevalence (40.8%; 95% CI, 30.4%-51.3%, I² = 98.9%, τ² = 0.039) and North America the lowest (23.0%; 95% CI, 18.9%-27.2%, I² = 99.3%, τ² = 0.021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTemporal trend and COVID-19\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTime-trend analysis demonstrated a significant increase in PTSD prevalence among HCWs (Figure 3A, β = 9.94*10\u003csup\u003e-4\u003c/sup\u003e, \u003cem\u003eP =\u003c/em\u003e 0.012). No significant temporal trend was observed before COVID-19 (Figure 3B, β = 1.29*10\u003csup\u003e-4\u003c/sup\u003e, \u003cem\u003eP =\u003c/em\u003e 0.695), whereas an upward trend was noted after the onset of COVID-19 (Figure 3C, β = 18.22*10\u003csup\u003e-4\u003c/sup\u003e, \u003cem\u003eP =\u003c/em\u003e 0.094). Multivariable meta-regression showed high heterogeneity (I² = 99.5%) with low explanatory power (R² = 2.6%). Only investigation time was significantly associated with prevalence (exp(b) = 1.012; \u003cem\u003eP\u003c/em\u003e = 0.010) (eTable 6).\u003c/p\u003e\n\u003cp\u003eThe prevalence of PTSD among HCWs was significantly higher after the onset of COVID-19 (27.8%; 95% CI, 25.8%-29.8%, I² = 99.6%, τ² = 0.029) compared to the pre-pandemic period (20.2%; 95% CI, 14.4%-26.0%, I² = 97.1%, τ² = 0.020, \u003cem\u003eP =\u003c/em\u003e 0.046) (Figure 4, eFigure 2). Subgroup analyses revealed that compared to pre-pandemic, after the onset of COVID-19, PTSD prevalence was significantly higher among those exposed to mass casualty incidents (from 17.4% to 48.4%; \u003cem\u003eP =\u003c/em\u003e 0.027), working in high-income countries (from 17.7% to 26.2%; \u003cem\u003eP =\u003c/em\u003e 0.026) and North America (from 12.9% to 25.0%; \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.046)(Figure 4, eFigure 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk Factors for PTSD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 5 and eFigure 4 summarize PTSD risk factors among HCWs. Female sex was consistently associated with increased PTSD risk (OR, 1.35; 95% CI, 1.22-1.49), evident both before COVID-19 (OR, 1.99; 95% CI, 1.15-3.43) and after the onset of the COVID-19 (OR, 1.34; 95% CI, 1.22–1.48). Age≥ 40 years, marital status and parental status were not significant predictors.\u003c/p\u003e\n\u003cp\u003eOccupational role was a strong correlate of PTSD. Compared with physicians, nurses (OR, 1.60; 95% CI, 1.41–1.82) and other HCWs (OR, 1.29; 95% CI, 1.09–1.53) had elevated odds. These associations remained robust after the onset of the COVID-19. Educational attainment showed a modest protective effect. HCWs with postgraduate education had lower odds of PTSD (OR, 0.86; 95% CI, 0.78–0.95). Working hours\u0026nbsp;≥\u0026nbsp;40 hours/week, practicing\u0026nbsp;≥\u0026nbsp;10 years, and higher income were not significantly associated with PTSD risk.\u003c/p\u003e\n\u003cp\u003eSeveral pandemic-specific exposures were notable. Prior mental illness (OR, 2.08; 95% CI, 1.54–2.80), COVID-19 infection (OR, 1.48; 95% CI, 1.23–1.78), frontline work (OR, 1.27; 95% CI, 1.01–1.60), exposure to infected individuals (OR, 1.43; 95% CI, 1.16–1.77), and having symptomatic family or friends (OR, 1.53; 95% CI, 1.22–1.90) were all associated with significantly elevated PTSD risk, while smoking and alcohol use were not.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity Analyses and Publication Bias\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublication bias assessment revealed generally symmetrical distributions for most analyses. Significant publication bias was detected for overall PTSD prevalence (P \u0026lt; 0.001), pre-COVID-19 period (\u003cem\u003eP =\u003c/em\u003e 0.018), COVID-19-period prevalence (P \u0026lt; 0.001), and subgroup analyses. Detailed results are listed in eFigure 5 and eTable 7. After trim-and-fill adjustment for publication bias (k = 141 imputed studies), the pooled prevalence decreased substantially from 27.2% to 11.9% while maintaining statistical publication bias significance (P \u0026lt; 0.001). Sensitivity analyses demonstrated robust findings, with no single study significantly altering the pooled estimates (eFigure 6).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis systematic review and meta-analysis synthesizes evidence on the global prevalence and risk factors for PTSD among HCWs. Across 308 studies representing over 370,000 HCWs from 60 countries, the pooled prevalence of PTSD was 27.2%. Prevalence estimates varied across subgroups, with higher estimates reported among female HCWs, nurses, those in low- and middle-income countries, and those in Africa. PTSD prevalence significantly increased over time, with a sharper rise after the COVID-19 onset. A history of mental disorders, nursing occupation, female sex, and COVID-19-related exposures were associated with increased odds of PTSD. These results provide important insights for guiding mental health policies and interventions.\u003c/p\u003e \u003cp\u003eThe prevalence estimates observed in this study are broadly consistent with previous reports indicating that healthcare workers experience higher levels of trauma-related mental health symptoms than the general population[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Prior studies have suggested that occupational stressors inherent to healthcare settings, including repeated exposure to patient suffering, high workload, and ethical challenges, may contribute to increased PTSD risk[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Nurses exhibited 1.6-fold greater odds of PTSD than physicians, possibly related to differences in trauma exposure, training, and institutional support[\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Higher educational attainment was associated with a modest protective effect, potentially due to enhanced professional resilience, autonomy, or access to resources[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFemale HCWs had 1.35-fold increased odds of PTSD compared to males, consistent with prior research[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. While this may partly reflect biological differences, sociocultural dynamics, including the overrepresentation of women in high-risk healthcare roles such as nursing may contribute to this sex difference[\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In our study, variables such as younger age, marital status, and parental status were not significantly associated with PTSD, despite theoretical expectations that work\u0026ndash;family conflict and early career stressors might increase vulnerability to PTSD[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Evidence on protective factors was limited; physical activity was examined in a small number of studies and appeared to be associated with lower odds of PTSD, although data were insufficient to draw firm conclusions[\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePTSD risk also varied by trauma type. Mass casualty events were associated with the highest prevalence, followed by epidemic and work-related trauma. Although differences across trauma types did not reach statistical significance, this trend likely reflects variations in trauma severity, duration, and cumulative exposure. Epidemics, particularly COVID-19, with prolonged uncertainty and repeated moral stressors, uniquely contributed to psychological burden[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Additionally, self-reported assessments yielded higher PTSD estimates than clinician-administered assessments, possibly due to greater disclosure through anonymous formats[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePTSD prevalence estimates differed across geographic and economic contexts. PTSD prevalence was significantly higher in LMICs and especially elevated in Africa. These patterns may reflect variation in healthcare workforce capacity, access to mental health services, and clinical workload across settings[\u003cspan additionalcitationids=\"CR39 CR40 CR41 CR42\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Temporal analyses confirmed a significant rise in PTSD prevalence following the onset of the COVID-19 pandemic. Before the pandemic, prevalence estimates remained relatively stable; however, after January 2020, a clear upward trajectory emerged. Although prevalence levels remained higher in low- and middle-income countries, a statistically significant pre\u0026ndash;post increase was observed in high-income countries, with pooled prevalence rising from 17.7% before COVID-19 to 26.2% after its onset. This pattern may reflect lower pre-pandemic baseline prevalence in high-income settings and pandemic-related changes in working conditions and service organisation[\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCOVID-19-specific exposures were consistently associated with elevated PTSD risk, including prior infection, quarantine, frontline work, and infection among family or friends[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] HCWs with a prior mental health diagnosis were more than twice as likely to develop PTSD, indicating increased vulnerability among individuals with pre-existing mental health conditions.\u003c/p\u003e \u003cp\u003eThis study has several limitations. Substantial heterogeneity was observed across analyses, which is expected given the large number of studies. Publication bias was suggested by funnel plot asymmetry and addressed via trim-and-fill analysis, which imputed 141 studies and yielded a lower pooled estimate. In contrast, risk factor analyses showed lower heterogeneity, with female sex, lower educational attainment, and nursing occupation consistently associated with higher risk. The convergence of findings from prevalence and risk factor analyses supports the consistency of observed associations, although publication bias suggests caution in interpretation. In addition, only one study included longitudinal data spanning pre- and post-COVID-19 onset periods, limiting within-cohort comparisons. Some subgroup analyses were underpowered, and variability in the reporting of age and trauma exposure constrained more detailed modelling.\u003c/p\u003e \u003cp\u003eDespite these limitations, this study represents one of the most comprehensive syntheses to date on PTSD among HCWs. The large, globally representative sample and consistent findings across sensitivity analyses strengthen the robustness and generalizability of the findings. This systematic review and meta-analysis found that PTSD was common among healthcare workers across settings, with higher prevalence observed among female healthcare workers, nurses, and those working in LMIC countries, particularly in Africa. Comparisons of studies conducted before and after the onset of the COVID-19 pandemic indicated higher PTSD prevalence estimates after the pandemic onset. These findings describe patterns of psychological burden and vulnerability among healthcare workers across occupational, geographic, and temporal contexts, and may inform public health monitoring and workforce-related mental health policy planning.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eContributors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLu, J Sun, and Fang conceptualised and designed the study. J Sun and Fang developed the methodology and conducted the literature search. Fang, Y N Zhang, Fan, Zhao, Y Y Sun, Tong, Z L Wang, Yang, S N Zhang, L Y Wang, and Li participated in study screening, data extraction, and risk-of-bias assessment. Fang, Y N Zhang, Fan, Zhao, Tong, Wei, Yang and Y Zhang performed the statistical analyses. J Sun, Fang, and Zheng interpreted the data and wrote the original draft of the manuscript. Bao, Y M Wang, Zheng, J Sun, Lu, Sen, and Lima critically reviewed and revised the manuscript for important intellectual content. Dr Lu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Dr J.Sun, Fang, and Zheng are co-first authors. contributed equally to this work. All authors approved the final version of the manuscript and had final responsibility for the decision to submit for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated or analyzed during the current study. All data used were obtained from previously published studies and are publicly available. Further information about the data sources can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the STI2030\u0026ndash;Major Projects (2021ZD0200800) and the National Natural Science Foundation of China (82201644 and 82471505).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare no competing interests.\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by the STI2030-Major Projects (2021ZD0200800) and the National Natural Science Foundation of China (82201644 and 82471505).\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis work was supported by the STI2030\u0026ndash;Major Projects (2021ZD0200800) and the National Natural Science Foundation of China (82201644 and 82471505).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHarvey SB, Epstein RM, Glozier N, Petrie K, Strudwick J, Gayed A, et al. 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Am J Psychiatry. 2023;180:896\u0026ndash;905.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"mp","sideBox":"Learn more about [Molecular Psychiatry](http://www.nature.com/mp/)","snPcode":"41380","submissionUrl":"https://mts-mp.nature.com/cgi-bin/main.plex","title":"Molecular Psychiatry","twitterHandle":"@molpsychiatry","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8729203/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8729203/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePosttraumatic stress disorder (PTSD) is a critical occupational health concern among health care workers (HCWs). Quantifying global prevalence and identifying risk factors is critical for guiding intervention and policy strategies. \u003cstrong\u003eA systematic review and meta-analysis was performed following PRISMA guidelines\u003c/strong\u003e (PROSPERO CRD42024587810). A literature search of PubMed, Embase, PsycINFO, Web of Science, and Cochrane Library databases was performed from database inception to March 11, 2025.\u003cstrong\u003e \u003c/strong\u003eObservational studies reporting PTSD prevalence and odds ratios (ORs) for PTSD risk factors among HCWs were included. The primary outcome\u003cstrong\u003e was p\u003c/strong\u003eooled prevalence of PTSD and ORs for risk factors among HCWs.\u003cstrong\u003e \u003c/strong\u003eA total of 308 studies from 60 countries were included, comprising 371,211 HCWs. The pooled PTSD prevalence was 27.2% (95% CI, 25.3%–29.2%). Higher prevalence was observed among female (31.5%), nurses (28.6%), HCWs in low- and middle-income countries (30.0%), and those in Africa (40.8%). Prevalence increased from 20.2% (95% CI, 14.4%–26.0%) before COVID-19 to 27.8% (95% CI, 25.8%–29.8%) after its onset, with meta-regression showing a significant upward trend over time (β = 9.94*10\u003csup\u003e-4\u003c/sup\u003e, \u003cem\u003eP =\u003c/em\u003e 0.012). The strongest risk factors for PTSD included a history of mental disorder (OR, 2.08; 95% CI, 1.54–2.80), nursing occupation (OR, 1.60; 95% CI, 1.41–1.82), and symptomatic family or friends (OR, 1.53; 95% CI, 1.22–1.90).\u003cstrong\u003e \u003c/strong\u003eThese findings indicate a substantial psychological burden among HCWs and identify subgroups with higher vulnerability across settings.\u003c/p\u003e","manuscriptTitle":"Global burden and inequities for PTSD among Healthcare Workers: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 16:00:38","doi":"10.21203/rs.3.rs-8729203/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-04-29T06:47:40+00:00","index":4,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-04-16T11:58:50+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-13T03:13:40+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-10T09:02:34+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-02-10T08:54:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-01T12:51:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-01T12:50:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Psychiatry","date":"2026-01-31T03:28:44+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2026-01-29T15:53:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"mp","sideBox":"Learn more about [Molecular Psychiatry](http://www.nature.com/mp/)","snPcode":"41380","submissionUrl":"https://mts-mp.nature.com/cgi-bin/main.plex","title":"Molecular Psychiatry","twitterHandle":"@molpsychiatry","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0061e305-2992-40fe-87b0-f0fe4b661106","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":62643439,"name":"Health sciences/Diseases/Psychiatric disorders"},{"id":62643440,"name":"Health sciences/Diseases"},{"id":62643441,"name":"Health sciences/Diseases/Psychiatric disorders"},{"id":62643442,"name":"Health sciences/Diseases"}],"tags":[],"updatedAt":"2026-02-19T16:00:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 16:00:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8729203","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8729203","identity":"rs-8729203","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}