Skip to main content
Download PDF
Download ePub
  • Systematic Review
  • Open access
  • Published:

Severity and associated factors of moral injury in healthcare workers during the coronavirus pandemic: a comprehensive meta-analysis

Archives of Public Health volume 83, Article number: 37 (2025) Cite this article

Abstract

Background

The COVID-19 pandemic has placed significant emotional and ethical burdens on healthcare workers (HCWs), leading to the emergence of moral injury (MI). Understanding the pooled mean and factors associated with MI is crucial for developing interventions and support systems for HCWs. This meta-analysis aims to examine the extent of MI among HCWs during the COVID-19 pandemic and identify potential contributing factors.

Methods

A systematic literature search was conducted, and relevant studies reporting on MI in HCWs during the COVID-19 pandemic were included. Pooled means were calculated using random-effects or fixed effect models. Subgroup analyses were conducted based on demographic variables, such as gender, profession, and geographical region. Further, Sensitivity analysis was run to assess the individual study effect.

Results

A total of 36 studies met the inclusion criteria and were included in the meta-analysis. The pooled mean of MI among HCWs during the COVID-19 pandemic was ranged from 3.06 (CI95%: 2.35–3.77) to 119.17 (CI95%: 103.04–135.30), based on the instrument types. Further analyses revealed that females (P = 0.21), younger HCWs (P = 0.13), nurses (P = 0.55), and those in developing countries (P = 0.02) experienced higher levels of MI.

Conclusion

This meta-analysis highlights the substantial MI experienced by healthcare workers (HCWs) during the COVID-19 pandemic, with nurses, younger HCWs, and those in developing countries being particularly affected. Although statistical significance was not observed in subgroup differences, trends suggest a heightened vulnerability among specific groups. These findings underscore the urgent need for targeted interventions and policies to support HCWs, particularly in high-risk demographics, and emphasize the importance of standardized MI assessment tools for future research.

Peer Review reports

Text box 1. Contributions to the literature

• Highlights moral injury (MI) as a significant, under-recognized issue for healthcare workers (HCWs) beyond military contexts, particularly exacerbated by the COVID-19 pandemic.

• Synthesizes MI data across diverse measurement tools, underscoring the need for standardized MI assessments in healthcare.

• Identifies demographic subgroups, such as nurses, younger HCWs, and those in developing countries, as particularly vulnerable, supporting targeted interventions.

• Advocates for future studies to adopt consistent MI definitions and validated instruments, enhancing cross-study comparability and evidence-based support strategies.

Introduction

The COVID-19 pandemic unleashed a global health crisis that challenged healthcare systems and placed an immense burden on healthcare workers (HCWs) worldwide [1, 2]. As the frontline responders, HCWs worked tirelessly to provide patient care, make critical decisions, and mitigate the virus’s spread [3, 4]. However, the relentless demands and unprecedented circumstances have taken a significant toll on HCWs, leading to physical exhaustion, psychological strain, and emotional distress [5, 6].

HCWs faced an extraordinary work burden, prolonged isolation, and high levels of stress, which significantly affected their well-being [7]. Resident doctors, in particular, were prematurely empowered to take on critical responsibilities, amplifying their vulnerability to mental health challenges [8]. Moreover, during the peak of the pandemic, resource scarcity forced HCWs to make ethically challenging decisions, such as prioritizing patients for intensive care. These experiences intensified their risk of moral injury(MI) [4]. In the later stages of the pandemic, vaccination mandates added another layer of complexity, with some HCWs facing employment risks or reduced pay due to insufficient vaccination coverage [9]. This, combined with the perceived infringement of personal rights, further exacerbated MI. MI refers to the profound psychological distress caused by witnessing or engaging in actions that conflict with an individual’s moral or ethical principles. It often manifests as a deep sense of guilt, shame, or betrayal, potentially leading to long-lasting emotional harm [10]. In the context of HCWs, MI may arise from ethical dilemmas, such as allocating limited resources [11] or balancing patient care with personal safety [12,13,14]. Including studies that align with this conceptual framework ensures a comprehensive understanding of MI in healthcare settings.

Recent studies indicate that the prevalence of MI among HCWs has reached critical levels, with rates varying by profession, demographic factors, and healthcare setting. For instance, Lennon et al. reported that 40.9% of 1,945 HCWs experienced MI according to the Moral Injury Symptom Checklist (MISC) [15]. Other studies estimate MI prevalence among HCWs during the COVID-19 pandemic to range from 13 to 50%, depending on the population and measurement tools used [16,17,18]. In one study, Wang et al. (2020) found that 20.4% of participants reported clinically significant MI that severely impaired their social and occupational functioning. These elevated levels of MI contribute to a cascade of negative outcomes, including burnout, mental health issues, and an increased likelihood of leaving the profession [19].

Understanding the magnitude and impact of MI experienced by HCWs during the COVID-19 crisis is essential for developing targeted interventions and support systems to address their specific challenges and promote well-being. Current literature includes numerous studies [20,21,22,23,24,25,26,27,28,29] that report varying mean MI scores among HCWs, measured with diverse instruments such as the Moral Injury Symptom Scale for Healthcare Providers (MISS-HP), Moral Distress Thermometer (MDT), Moral Injury Events Scale (MIES), and Moral Distress Scale (MDS). However, the use of different instruments has posed challenges for comparing and interpreting these scores consistently. Therefore, a meta-analysis is warranted to synthesize findings and estimate pooled mean MI scores by instrument. This analysis would provide a clearer, more comprehensive understanding of MI levels among HCWs during this unprecedented period.

Existing literature includes two meta-analyses examining MI among HCWs during the COVID-19 pandemic, each with a distinct focus. One meta-analysis explored the pooled correlation between MI and various mental health factors among HCWs, examining the relationship between MI and psychological variables [30]. Another focused on estimating the pooled mean of MI specifically in nurses during the early stages of the pandemic, though with limited studies available [31]. In contrast, our study aims to address gaps in the literature by pursuing objectives that have not been extensively examined. Specifically, we seek to estimate the pooled mean MI scores based on different instruments among HCWs and examine the variation in MI levels by factors such as profession and demographic variables.

This study aims to provide a comprehensive meta-analysis of MI among HCWs during the COVID-19 pandemic. The primary objectives are to estimate pooled mean scores of MI using diverse assessment tools, identify key demographic and professional factors associated with MI, and analyze subgroup differences, including age, sex, and profession. By addressing these objectives, this study seeks to highlight vulnerable groups and inform the development of targeted interventions.

Methods

Design and registration

The current meta-analysis covers studies conducted from the onset of the COVID-19 pandemic through 2023. The research protocol was registered in the PROSPERO database under the code CRD42023387480. The primary outcome was the estimation of pooled MI among HCWs using reliable instruments, while secondary outcomes included comparing MI across professions, age groups, sex, and the developmental stage of countries.

Search strategy

A comprehensive search was conducted across Scopus, PubMed, ProQuest, ISI Web of Knowledge, and PsycInfo, covering the period from the onset of the COVID-19 pandemic through the end of 2023. Additional searches were performed on Google and Google Scholar. To ensure a systematic approach, the search question and query were formulated using the PECO-S framework, which includes Population (P), Exposure (E), Comparison (C), Outcome (O), and Study design (S), enabling a thorough and structured search strategy [32]. The study population included HCWs, with a focus on physicians and nurses. Comparisons were made between physicians and nurses, as well as between male and female HCWs. The primary outcomes of interest were the mean and standardized mean difference (SMD) of MI scores, assessed using various instruments. The exposure of interest was working during the COVID-19 pandemic. The study design considered was observational studies. The main search terms for this study were derived from PubMed Medical Subject Heading terms (Mesh), focusing on two primary components: P (HCWs) and O (MI). The specific search query utilized Boolean operators (AND/OR/NOT) to combine these terms effectively. The main search terms employed in the query were “moral distress” and “nurses.” By employing these search terms and appropriate Boolean operators, a comprehensive and targeted search strategy was developed to identify relevant studies pertaining to the intersection of moral distress and nursing. The core search syntax was (staff* OR healthcare work* OR healthcare professional* OR healthcare team OR nurse* OR doctor* OR medic* OR professional* OR health personnel OR HCW* OR HCSW* OR care work* OR worker*) AND Moral injur* OR Morally injur* OR Moral distress* OR Morally distress* OR Moral* pain* OR Moral dilemma* OR Moral transgres* OR Moral identit OR Moral* conflict* OR Moral* challeng* OR Moral Consequence* OR Ethical* difficult* OR Ethical dilemma OR Ethical* concern* OR Ethical* challeng* OR Ethical* distress*). Then search syntax was customized based on the advanced search attributes of each database. Additionally, reference lists of included studies, Open Grey and NYAM were searched as gray literature to increase the comprehensiveness of search. The search syntax was adjusted according to advanced search attributes of each database. Additionally, the reference lists of the included studies as well as gray literature repositories such as Open Grey and NYAM were checked.

Eligibility criteria

The inclusion criteria for the study focused on HCWs, including physicians, nurses, and other professionals directly involved in the care of COVID-19 patients across various healthcare settings such as hospitals, clinics, long-term care facilities, and emergency departments. The study design included cross-sectional studies that investigated MI in HCWs during the COVID-19 pandemic, with outcomes measured through validated scales, questionnaires, or qualitative methods.

Study selection process

A pre-designed excel sheet form was prepared to extract data including first author’s name, collection date, study design, country, number of participants, percent of female participants, mean age, scale used to assess MI, and numerical results regarding the means and standard deviations of MI scores. In studies in which nurses were a subgroup of participants, numerical findings related to nurses were extracted. Three steps of study selection, quality assessment, and data extraction were done independently by two reviewers. In the process, disagreements were resolved through discussion involving the two reviewers. Furthermore, two authors (M.J-O and M.J) evaluated the quality of the included studies utilizing the Joanna Briggs Institute (JBI) Critical Appraisal checklist for Analytical Cross-Sectional studies [33] in a systematic manner. The checklist, consisting of eight items, was scored dichotomously, with a total possible score ranging from 0 to 8. A higher score indicates a higher level of quality. In the event of any discrepancies, a consensus was reached through mutual discussion.

Data synthesis

To estimate the pooled measure, mean score of MI and SMD as effect sizes were used with 95% confidence intervals. Meta-analyses were performed using both random effect models and fixed effect models to account for within-study and between-study variances. Statistical heterogeneity was assessed using the Q Cochrane test, and the degree of heterogeneity was estimated using the I2 index. The I2 index was categorized as mild (I2 < 25%), moderate (25 < I2 < 50%), severe (50 < I2 < 75%), and highly severe (I2 > 75%) [34]. In the analyses of homogeneous (I < 50% and P > 0.05) and heterogeneous (I > 50% and P < 0.05) data, the fixed-effects and random-effects models were used, respectively [35]. The scoring method varied among the different instruments, necessitating estimation of pooled MI estimation to each instrument, individually. In total, 13 types instruments were utilized to measure MI in HCWs during the COVID-19 pandemic. Among these, seven types were used in multiple samples, and therefore, their pooled estimation were calculated. The other types of instruments were categorized as a group called “others.” We were unable to assess publication bias for all forest plots since at least 10 studies are required to assess publication bias [36]. Sensitivity analysis was conducted using the Jackknife method, also known as the “leave one out” method, with the Metaninf module [37]. This involved estimating the pooled effect size for the entire sample and then iteratively computing the pooled effect size when each study was removed from the sample.

Results

Study selection

In the study selection process, a total of 1,500 records were initially identified from databases. After removing duplicates (205 records) and excluding ineligible records (number not specified), 1,265 records were screened for eligibility. Of these, 985 records were excluded based on predetermined criteria. From the remaining 280 records, attempts were made to retrieve reports, but 657 reports could not be accessed. Of the 70 retrieved reports, 8 were excluded for reporting only medians, 10 were not accessible, 2 were in letter format, and 8 were related to tool development. Ultimately, 35 studies were included in the review, resulting in 58 reports (Fig. 1).

Fig. 1
figure 1

Flow Diagram Depicting the Study Selection Process for Meta-Analysis of Moral Injury in Healthcare Workers During the COVID-19 Pandemic (2019–2023)

Full size image

Study characteristics

The present meta-analysis included a total of 35 studies, which were conducted between 2019 and 2023. The characteristics of the included studies are summarized in the Supplementary Table 1. The studies were conducted in various locations, including USA [24, 27, 38,39,40,41,42,43,44,45,46], Indonesia [47], Netherlands [25, 26, 48], China [17, 28], Italy [49], Romania [16], Pakistan [20], Iran [22, 23, 50, 51], Greece [52], Norway [53], Spain [54], Canada [55], and the UK [56]. The sample sizes varied across studies, ranging from 33 [48] to 12,965 [56] participants. Different measures of MI were employed across the studies, such as the MISS-HP, MDT, MIES, MDS, and others. The participants in the studies included healthcare professionals such as nurses, physicians, and other healthcare workers. Several sociodemographic and work-related variables were assessed in relation to MI, including sex, marital status, hospital type, profession, specialty, workplace, age, education level, adequacy of personal protective equipment (PPE), and exposure to COVID-19 patients. The quality ratings of the included studies varied, with some studies receiving ratings of 4 or 5 on a scale of 1 to 8, reflecting differences in the methodological rigor across the studies.

Pooled means of MI

Among the different MI instruments examined, we were able to calculate the pooled mean for the following instruments: MISS-HP (Supplementary Fig. 1), MDT (Supplementary Fig. 2), MMD-HP (Supplementary Fig. 3), MIAS (Supplementary Fig. 4), and extended MMD-HP (Supplementary Fig. 5). However, the included primary studies have not a similar scoring method for other instruments such as MDS, as indicated in the Supplementary Table 1. Regarding the MIAS, MIES and extended MMD-HP instruments, De groot 2022 [48], Amsalem et al. [38] and Donkers et al. [25] reported mean estimates at different time points or for various groups. Therefore, we included them in the separate forest plot to provide a comprehensive representation of the data.

According to Table 1, the pooled estimated mean scores for MI ranged from 3.06, as determined by the extended MMD-HP, to 119.17, as measured by the MMD-HP. In the one-leave-out analysis, we did not observe any significant influence from individual studies on the pooled means.

Sensitivity analysis

As shown in the last column of Table 1, a sensitivity analysis was performed to assess the robustness of the pooled mean MI scores and evaluate the impact of individual studies on the overall results. Using the ‘leave-one-out’ method, we recalculated the pooled effect size by iteratively removing each study from the sample. This analysis confirmed that no single study had a disproportionate influence on the pooled mean estimates, underscoring the stability and reliability of our findings. The consistent results across sensitivity analyses further reinforce the robustness of the reported MI prevalence and subgroup differences.

Table 1 Summary of Pooled Mean scores of Moral Injury based on Assessment instruments during the COVID-19 pandemic (2019–2023)
Full size table

Subgroup analysis

According to Table 2, subgroup analysis was performed based on profession (total HCWs, physicians, and nurses) (Supplementary Figs. 6–8), sex (Supplementary Fig. 9), age (Supplementary Fig. 10), and the developmental stage of the countries (Supplementary Figs. 11–12) where the studies were conducted. The pooled mean scores of MI exhibited variation across different professions. For HCWs, the pooled mean scores ranged from 3.51 to 130.51 depending on the instrument used. Among physicians, the pooled mean scores ranged from 3.51 to 27.07. For nurses, the pooled mean scores ranged from 4.68 to 113.41 based on the instrument utilized. Other profession categories had pooled mean scores ranging from 3.51 to 27.26. In the subgroup analysis based on sex, the pooled mean score of MI using the MDT instrument for males was estimated to be 4.71 (95% CI: 4.53–4.89) with no observed heterogeneity (I2 = 0%), using a fixed (inverse-variance) model. For females, the pooled mean score was 3.87 (95% CI: 2.15–5.60) with high heterogeneity (I2 = 98.92%) using a random-effects REML model. Based on age, the pooled mean score of the MI using the MDT instrument for individuals aged ≤ 33 was estimated to be 3.98 (95% CI: 2.45–5.51) with high heterogeneity (I2 = 98.56%), while individuals aged > 33, the pooled MI was 3.72 (95% CI: 1.91–5.54) with even higher heterogeneity (I2 = 99.14%). In the subgroup analysis based on developing stage, the pooled means of MI scores ranged from 3.06 to 121.62, with varying degrees of heterogeneity. In developing countries, the pooled mean scores ranged from 4.37 to 113.66, with moderate to high heterogeneity observed.

Table 2 Subgroup Analysis of Pooled Mean Scores of Moral Injury among Healthcare Workers, Physicians, and nurses during the COVID-19 pandemic (2019–2023)
Full size table

Difference of pooled MI based on profession, sex, age, developing stage

The analysis revealed non-significant (p > 0.05) differences in the pooled SMD of MI scores based on profession, sex, and age. The results indicated that being a nurse was associated with higher levels of MI compared to being a physician during the COVID-19 pandemic (SMD = 0.09, 95% CI = -0.20–0.38, I^2 = 92.05%, random-effects REML, P = 0.55) (Supplementary Fig. 13). Female HCWs were associated with slightly higher MI levels compared to male HCWs, as indicated by the MDT instrument (SMD = -0.13, 95% CI = -0.33–0.07, I^2 = 76.13%, random-effects REML, P = 0.21) (Supplementary Fig. 14). Additionally, being 33 years or younger was associated with slightly higher MI levels among HCWs compared to older counterparts (SMD = 0.08, 95% CI = -0.02–0.17, I^2 = 0, fixed model, P = 0.13) (Supplementary Fig. 15). However, according to Supplementary Fig. 16, HCWs in developing countries were associated with higher levels of MI compared to those in developed countries (SMD = 0.45, 95% CI = 0.09–0.82, I^2 = 90.71%, random-effects REML, P = 0.02).

Discussion

In this meta-analysis, we estimated the pooled mean scores of MI using various assessment instruments. Additionally, we aimed to estimate the mean scores of MI based on subgroups and conducted analyses considering factors such as age, sex, and the developmental stage of countries. A total of 58 distinct reports were identified from 35 eligible articles sourced from 13 different countries. From these articles, we extracted 32 effect sizes for inclusion in our analysis.

Higher scores on the MI instruments generally indicate a greater degree of MI. Among the included instruments, only the MISS-HP [20] and MDT [22] reported designated cutoff scores. A score of 36 or higher on the MISS-HP and 4 or higher on the MDT were considered indicative of clinically significant MI. Based on the MISS-HP instrument, the estimated pooled mean was found to be higher than the designated cut-off score, suggesting a significant burden of MI distress. Additionally, based on the MDT instrument, the mean pooled estimation was close to the cutoff score, indicating a potential presence of MI distress. For the other instruments, the mean MI scores were as follows: 119.17 on a 0–432 scale for MMD-HP, 20.56 on a 9–36 scale for MIAS, 3.06 on a 0–16 scale for extended MMD-HP, and 17.34 on a 9–18 scale. Except for the pooled MIAS and MIES, the other estimated pooled effects showed a high level of heterogeneity. This indicates significant variability among the studies’ findings, suggesting the presence of additional factors that may influence the observed effects. To address this heterogeneity, we conducted subgroup analyses based on available reported data, including profession, sex, age, and the developmental stage of countries. While the subgroup analyses led to a relative decrease in the level of heterogeneity (as indicated by I²), several estimated pooled means still exhibited high heterogeneity. Previous studies have consistently highlighted the significant prevalence of MI among HCWs [17, 23, 57,58,59,60]. These findings suggest that a substantial proportion of HCWs experience and suffer from MI, underscoring the importance of addressing this issue within the healthcare profession. All of our estimated pooled means were higher than the previously reported estimate in a study conducted by a previous meta-analysis [21], which reported a mean of 1.80 (CI95%: 1.42; 2.18). However, it is important to note that their analysis only included nine studies.

While previous meta-analyses have examined MI among HCWs during the COVID-19 pandemic, this study provides several unique contributions to the field. Unlike other reviews, this meta-analysis synthesizes MI data from a wide range of assessment tools to estimate pooled mean scores specifically across multiple MI instruments, allowing for more comprehensive and nuanced insights. We incorporated data from various MI measurement tools, such as the MIES and MDT, to examine instrument-based variations and assess the comparability and validity of different MI measures across studies. Additionally, our study explores subgroup differences by demographic and professional variables (e.g., age, sex, occupation, and geographic setting), which previous meta-analyses have not extensively covered. This approach identifies specific HCW groups at greater risk of MI, such as nurses, younger individuals, and those in developing countries, emphasizing targeted intervention needs. Furthermore, this study highlights the heterogeneity in MI scoring and calls for standardized measurement approaches, addressing a crucial gap in existing research. By doing so, this review not only deepens understanding of MI but also establishes a basis for improving MI assessment methodologies and tailoring support systems for HCWs in diverse healthcare settings.

The variations observed in the pooled levels of MI across different instruments can be attributed to several factors, including the timing of the studies relative to the phase of the COVID-19 outbreak, the duration and intensity of exposure to COVID-19 patients, the type of study design employed, the characteristics of the study population, the specific assessment tools used, and potential sociocultural differences. These factors contribute to the heterogeneity in the reported levels of MI, underscoring the complex nature of this phenomenon and the need for a comprehensive understanding when interpreting and comparing findings across different studies.

While moral distress and MI are conceptually distinct, with MD often referring to the discomfort experienced when external factors compel actions against one’s ethical beliefs, the two constructs share overlapping characteristics, particularly in high-stakes healthcare settings. MI involves a deeper psychological impact, often leading to long-lasting moral and emotional harm, whereas MD is commonly associated with more immediate psychological discomfort. The MDT has traditionally been used to assess MD; however, it can offer insights into MI levels, especially when HCWs repeatedly encounter ethical conflicts that go unresolved, potentially transitioning MD into MI.

In this meta-analysis, we included MDT data as it provides valuable quantitative measures of moral challenges faced by HCWs during the COVID-19 pandemic. Although MDT was not designed explicitly for MI, the context and frequency of distressing ethical dilemmas during the pandemic may have intensified MD to a point where it reflects MI. Therefore, we recognize MDT’s limitations in capturing the full scope of MI but believe it offers relevant data on the moral struggles that HCWs faced, providing an approximate measure in the absence of more universally applied MI-specific instruments.

The results of the subgroup analysis revealed significant findings regarding MI symptoms among HCWs. Specifically, based on the MISS-HP instrument, being a nurse was associated with a higher level of MI compared to other HCWs. Furthermore, the pooled MDT scores indicated that being a physician was associated with less intense MI compared to HCWs in general. However, when considering both the pooled MDT and MISS-HP scores, being a nurse was associated with a higher level of intensified MI compared to HCWs, except for the pooled MMD-HP scores. These findings underscore the unique challenges faced by HCWs in relation to MI, with nurses being particularly susceptible to its effects. Consistent with our study, another investigation revealed that nurses experienced higher levels of anxiety, stress, depression, and MI compared to medical interns and residents [17, 61]. This distinction may be attributed to several factors, such as the nature of their roles and responsibilities, the intensity of patient interactions, prolonged patient care, and the ethical dilemmas they encounter on a daily basis.

In relation to sex, the findings of the present study indicated that being female was associated with a non-significantly higher level of MI compared to being male, as evidenced by the pooled MDT scores. According to Wang et al. [24], female HCWs exhibited greater vulnerability to MI during the COVID-19 pandemic. Additionally, other research investigations [62, 63] demonstrated higher levels of psychometric distress among female HCPs amidst the pandemic. This pattern of heightened psychological distress among women was not limited to the healthcare field, as similar trends have been observed in the general population. It is widely assumed that women are more susceptible to developing anxiety, stress, and depression compared to men [64,65,66]. The non-significant finding in our study may be attributed to several factors that warrant further investigation. For instance, the complex interplay of social, cultural, and systemic factors may contribute to the observed non-significant findings. Future research should explore these factors in greater depth to better understand the nuanced relationship between sex and MI among HCWs during the COVID-19 pandemic.

Additionally, our study found that age was not significantly associated with the experience of MI, although younger HCWs reported higher levels of MI compared to their older counterparts. A previous study reported that resilience significantly decreased in younger caregivers [22]. Other studies have found that being under the age of 18 [67, 68], or being younger [69,70,71,72] was associated with higher levels of stress during the COVID-19 pandemic. The non-significant finding in our study may be attributed to the limited number of studies included in the analysis. However, it is important to note that this non-significant result may also stem from the relatively small sample size. Further research incorporating a larger and more diverse sample of HCWs is needed to explore the relationship between age and MI more comprehensively.

Furthermore, HCWs in both developing and developed countries were associated with clinically significant MI symptoms. Interestingly, MI levels for HCWs in developing countries were found to be higher than those in developed countries, suggesting a potentially greater impact of MI in the context of developing nations. Akhtar et al. reported no significant differences in the level of MI experienced by health professionals in different roles, including doctors, nurses, and paramedical staff. This suggests that all these professionals are equally grappling with challenges imposed by constraints such as shortages of supplies and staff, as well as other shortcomings resulting from the pandemic [20].

While COVID-19 may persist in some form, it is likely that society will adapt, and healthcare systems will shift toward a post-pandemic state. However, the findings from this study have significant implications beyond COVID-19, as MI is not exclusive to pandemic situations. Healthcare workers routinely face ethical challenges, resource constraints, and emotionally demanding decisions in their daily practice, independent of pandemic conditions. For example, decisions involving end-of-life care, balancing professional responsibilities with personal values, and navigating resource limitations often lead to moral conflicts and distress [73]. Persistent exposure to such challenges can result in long-term psychological impacts, including burnout, depression, and anxiety, as well as reduced job satisfaction and increased turnover intentions [3, 4, 74, 75]. Addressing these ongoing issues necessitates systemic interventions, such as ethical training, supportive leadership, and mental health programs, to foster resilience and mitigate the impact of MI in healthcare settings.

The elevated MI rates observed during COVID-19 highlight vulnerabilities that could emerge in any healthcare crisis or high-stress scenario, from natural disasters to patient surges. Understanding MI’s prevalence and its demographic associations—such as higher susceptibility among nurses and younger HCWs—can inform the development of preventive interventions and support mechanisms tailored to specific groups. Standardizing MI assessment tools and incorporating routine mental health support for HCWs could mitigate the effects of MI in future crises and everyday healthcare challenges, ultimately promoting a more resilient healthcare workforce.

Strengths and limitations

This study provides a comprehensive analysis of MI among HCWs during the COVID-19 pandemic by synthesizing data from various measurement tools and exploring subgroup differences. By examining the pooled mean scores across diverse instruments, the study offers nuanced insights into MI prevalence, highlighting specific vulnerabilities among nurses, younger individuals, and HCWs in developing countries. Furthermore, the study emphasizes the importance of standardized MI assessment tools, contributing to future research and practical interventions. Several limitations should be considered when interpreting the findings of our study. Firstly, the lack of standardized scoring methods for certain instruments prevented a consistent comparison of results. Additionally, limited demographic data across studies restricted subgroup analyses. The relatively small number of included studies for some analyses and the inability to fully assess publication bias may have influenced the results.

Conclusion

In our meta-analysis of pooled MI among HCWs during the COVID-19 pandemic, we found a variety of instruments used globally to measure MI. While most demonstrated validity and reliability, some consisted of a single item without established psychometric properties, and scoring methods varied, particularly for instruments like MIES. This lack of standardization made forest plot analysis challenging. Our analysis revealed high MI levels among HCWs, surpassing the MISS-HP cut-off scores in most cases. Significant heterogeneity was observed, highlighting the need for cautious interpretation. Subgroup analysis showed that HCWs in developing countries, especially nurses, females, and younger individuals, reported higher MI levels. These findings highlight the specific groups within the HCW population that may be particularly vulnerable to MI during the pandemic. This study underscores the need for targeted interventions, such as resilience training, mental health support, and routine MI assessments, to protect vulnerable HCWs, particularly nurses, younger workers, and those in developing countries. Standardized MI assessment tools are crucial for consistent research and effective support. Future studies should explore additional demographic factors and conduct longitudinal analyses to assess MI’s long-term effects and intervention impacts. These efforts will enhance understanding and inform strategies to support HCWs’ well-being in both crisis and routine care.

Data availability

No datasets were generated or analysed during the current study.

References

  1. Jafari-Oori M, Ebadi A, Moradian ST, Jafari M, Dehi M, Fard FG. Psychiatric distress in family caregivers of patients with COVID-19. Arch Psychiatr Nurs. 2022;37:69–75.

    Article  PubMed  Google Scholar 

  2. Gebru AA, Birhanu T, Wendimu E, Ayalew AF, Mulat S, Abasimel HZ, et al. Global burden of COVID-19: situational analyis and review. Hum Antib. 2021;29(2):139–48.

    Article  CAS  Google Scholar 

  3. Chemali S, Mari-Sáez A, El Bcheraoui C, Weishaar H. Health care workers’ experiences during the COVID-19 pandemic: a scoping review. Hum Resour Health. 2022;20(1):27.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Brophy JT, Keith MM, Hurley M, McArthur JE, Sacrificed. Ontario healthcare workers in the time of COVID-19. NEW SOLUTIONS: J Environ Occup Health Policy. 2021;30(4):267–81.

    Article  Google Scholar 

  5. Gouda D, Singh PM, Gouda P, Goudra B. An overview of health care worker reported deaths during the COVID-19 pandemic. J Am Board Family Med. 2021;34(Supplement):S244–6.

    Article  Google Scholar 

  6. Tan BY, Chew NW, Lee GK, Jing M, Goh Y, Yeo LL, et al. Psychological impact of the COVID-19 pandemic on health care workers in Singapore. Ann Intern Med. 2020;173(4):317–20.

    Article  PubMed  Google Scholar 

  7. Cioffi A. COVID-19, mentally ill and mental health workers. Psychiatria Danubina. 2020;32(2):307.

    PubMed  Google Scholar 

  8. Cioffi A. Professional autonomy and liability of the resident doctor: between the hammer and the anvil. J Forensic Leg Med. 2020;72:101965.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cioffi A, Cecannecchia C. Compulsory vaccination against SARS-CoV-2 in health care professionals in Italy: bioethical-legal issues. Med Sci Law. 2023;63(1):81–5.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Koenig HG, Al Zaben F. Moral injury: an increasingly recognized and widespread syndrome. J Relig Health. 2021;60(5):2989–3011.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Supady A, Curtis JR, Abrams D, Lorusso R, Bein T, Boldt J, et al. Allocating scarce intensive care resources during the COVID-19 pandemic: practical challenges to theoretical frameworks. Lancet Respiratory Med. 2021;9(4):430–4.

    Article  CAS  Google Scholar 

  12. McDougall RJ, Gillam L, Ko D, Holmes I, Delany C. Balancing health worker well-being and duty to care: an ethical approach to staff safety in COVID-19 and beyond. J Med Ethics. 2020.

  13. Kucewicz-Czech E, Damps M. Triage during the COVID-19 pandemic. Anaesthesiol Intensive Ther. 2020;52(4):312–5.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Lemmo D, Vitale R, Girardi C, Salsano R, Auriemma E. Moral distress events and emotional trajectories in nursing narratives during the COVID-19 pandemic. Int J Environ Res Public Health. 2022;19(14):8349.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Lennon RP, Parascando J, Talbot SG, Zhou S, Wasserman E, Mantri S, et al. Prevalence of moral injury, burnout, anxiety, and depression in healthcare workers 2 years in to the COVID-19 pandemic. J Nerv Ment Dis. 2023;211(12):981–4.

    Article  PubMed  Google Scholar 

  16. Maftei A, Holman A-C. The prevalence of exposure to potentially morally injurious events among physicians during the COVID-19 pandemic. Eur J Psychotraumatology. 2021;12(1):1898791.

    Article  Google Scholar 

  17. Wang Z, Koenig HG, Tong Y, Wen J, Sui M, Liu H, et al. Moral injury in Chinese health professionals during the COVID-19 pandemic. Psychol Trauma: Theory Res Pract Policy. 2022;14(2):250.

    Article  Google Scholar 

  18. Zahiriharsini A, Gilbert-Ouimet M, Langlois L, Biron C, Pelletier J, Beaulieu M, et al. Associations between psychosocial stressors at work and moral injury in frontline healthcare workers and leaders facing the COVID-19 pandemic in Quebec, Canada: a cross-sectional study. J Psychiatr Res. 2022;155:269–78.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Zhizhong W, Koenig HG, Yan T, Jing W, Mu S, Hongyu L, et al. Psychometric properties of the moral injury symptom scale among Chinese health professionals during the COVID-19 pandemic. BMC Psychiatry. 2020;20:1–10.

    Article  Google Scholar 

  20. Akhtar M, Faize FA, Malik RZ, Tabusam A. Moral injury and psychological resilience among healthcare professionals amid COVID-19 pandemic. Pakistan J Med Sci. 2022;38(5):1338.

    Google Scholar 

  21. Alimoradi ZJE, Lin CY, Rajabi R, Marznaki ZH, Soodmand M, Potenza MN, Pakpour AH. Estimation of moral distress among nurses: a systematic review and meta-analysis. Nurs Ethics. 2021;30(3):334–57.

    Article  Google Scholar 

  22. Alrjoub W, Alarjeh G, Ammar K, Shamieh A, Harding R, Booth C et al. Stress, resilience, and moral distress among health care providers in oncology during the COVID-19 pandemic. Front Public Health. 2023;11.

  23. Behnampour A, Ebrahimi S, Bazrafshan A, Kamyab A, Pakdin M, Ebrahimi A. Evaluating the Association of Depressive Disorder Symptoms and Moral Injuries in Healthcare Workers during COVID-19 pandemic. medRxiv. 2023;2023(05):20–23290269.

    Google Scholar 

  24. Clark P, Crawford TN, Hulse B, Polivka BJ. Resilience, moral distress, and workplace engagement in emergency department nurses. West J Nurs Res. 2021;43(5):442–51.

    Article  PubMed  Google Scholar 

  25. Donkers MA, Gilissen VJ, Candel MJ, van Dijk NM, Kling H, Heijnen-Panis R, et al. Moral distress and ethical climate in intensive care medicine during COVID-19: a nationwide study. BMC Med Ethics. 2021;22(1):1–12.

    Article  Google Scholar 

  26. Kok N, Van Gurp J, van der Hoeven JG, Fuchs M, Hoedemaekers C, Zegers M. Complex interplay between moral distress and other risk factors of burnout in ICU professionals: findings from a cross-sectional survey study. BMJ Qual Saf. 2023;32(4):225–34.

    Article  PubMed  Google Scholar 

  27. Litam SDA, Balkin RS. Moral injury in health-care workers during COVID-19 pandemic. Traumatology. 2021;27(1):14.

    Article  Google Scholar 

  28. Ma W, Koenig HG, Wen J, Liu J, Shi X, Wang Z. The Moral Injury, PTSD, and Suicidal Behaviors in Health Professionals 1 Year After the COVID-19 Pandemic Peak in China. 2022.

  29. Petrișor C, Breazu C, Doroftei M, Mărieș I, Popescu C, editors. Association of moral distress with anxiety, depression, and an intention to leave among nurses working in intensive care units during the COVID-19 pandemic. Healthcare: MDPI; 2021.

    Google Scholar 

  30. Coimbra BM, Zylberstajn C, van Zuiden M, Hoeboer CM, Mello AF, Mello MF, et al. Moral injury and mental health among health-care workers during the COVID-19 pandemic: meta-analysis. Eur J Psychotraumatology. 2024;15(1):2299659.

    Article  Google Scholar 

  31. Alimoradi Z, Jafari E, Lin C-Y, Rajabi R, Marznaki ZH, Soodmand M, et al. Estimation of moral distress among nurses: a systematic review and meta-analysis. Nurs Ethics. 2023;30(3):334–57.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Morgan RL, Whaley P, Thayer KA, Schünemann HJ. Identifying the PECO: a framework for formulating good questions to explore the association of environmental and other exposures with health outcomes. Environ Int. 2018;121(Pt 1):1027.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K, Sfetcu R, et al. Chapter 7: systematic reviews of etiology and risk. Joanna Briggs Inst Reviewer’s Man Joanna Briggs Inst. 2017;5:217–69.

    Google Scholar 

  34. Huedo-Medina TB, Sánchez-Meca J, Marín-Martínez F, Botella J. Assessing heterogeneity in meta-analysis: Q statistic or I² index? Psychol Methods. 2006;11(2):193.

    Article  PubMed  Google Scholar 

  35. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58.

    Article  PubMed  Google Scholar 

  36. Valentine JC, Pigott TD, Rothstein HR. How many studies do you need? A primer on statistical power for meta-analysis. J Educational Behav Stat. 2010;35(2):215–47.

    Article  Google Scholar 

  37. Hedges LV, Olkin I. Statistical methods for meta-analysis. Academic; 2014.

  38. Amsalem D, Lazarov A, Markowitz JC, Naiman A, Smith TE, Dixon LB, et al. Psychiatric symptoms and moral injury among US healthcare workers in the COVID-19 era. BMC Psychiatry. 2021;21(1):1–8.

    Article  Google Scholar 

  39. Chandrabhatla T, Asgedom H, Gaudiano ZP, de Avila L, Roach KL, Venkatesan C, et al. Second victim experiences and moral injury as predictors of hospitalist burnout before and during the COVID-19 pandemic. PLoS ONE. 2022;17(10):e0275494.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Hines SE, Chin KH, Glick DR, Wickwire EM. Trends in moral injury, distress, and resilience factors among healthcare workers at the beginning of the COVID-19 pandemic. Int J Environ Res Public Health. 2021;18(2):488.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Mantri S, Lawson JM, Wang Z, Koenig HG. Identifying moral injury in healthcare professionals: the moral injury symptom scale-HP. J Relig Health. 2020;59:2323–40.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Ness MM, Saylor J, DiFusco LA, Evans K. Leadership, professional quality of life and moral distress during COVID-19: a mixed‐methods approach. J Nurs Adm Manag. 2021;29(8):2412–22.

    Article  Google Scholar 

  43. Sheppard KN, Runk BG, Maduro RS, Fancher M, Mayo AN, Wilmoth DD, et al. Nursing moral distress and intent to leave employment during the COVID-19 pandemic. J Nurs Care Qual. 2022;37(1):28.

    Article  PubMed  Google Scholar 

  44. Showalter BL, Malecha A, Cesario S, Clutter P. Moral distress in clinical research nurses. Nurs Ethics. 2022;29(7–8):1697–708.

    Article  PubMed  Google Scholar 

  45. Sonis J, Pathman DE, Read S, Gaynes BN. A national study of moral distress among US internal medicine physicians during the COVID-19 pandemic. PLoS ONE. 2022;17(5):e0268375.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Wilson CA, Metwally H, Heavner S, Kennedy AB, Britt TW. Chronicling moral distress among healthcare providers during the COVID-19 pandemic: a longitudinal analysis of mental health strain, burnout, and maladaptive coping behaviours. Int J Ment Health Nurs. 2022;31(1):111–27.

    Article  PubMed  Google Scholar 

  47. Arafat R, Tahir T, Harisa A. Moral distress among nurses in caring COVID-19 patients. Clin Ethics. 2023;18(1):62–6.

    Article  PubMed  PubMed Central  Google Scholar 

  48. de Groot J. Moral injury in frontline workers of the COVID-19 pandemic and predicting factors 2021.

  49. Maffoni M, Fiabane E, Setti I, Martelli S, Pistarini C, Sommovigo V. Moral Distress among Frontline Physicians and nurses in the early phase of COVID-19 pandemic in Italy. Int J Environ Res Public Health. 2022;19(15):9682.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Asadi N, Salmani F, Asgari N, Salmani M. Alarm fatigue and moral distress in ICU nurses in COVID-19 pandemic. BMC Nurs. 2022;21(1):1–7.

    Article  Google Scholar 

  51. Nemati R, Moradi A, Marzban M, Farhadi A. The association between moral distress and mental health among nurses working at selected hospitals in Iran during the COVID-19 pandemic. Work. 2021;70(4):1039–46.

    PubMed  Google Scholar 

  52. Malliarou M, Nikolentzos A, Papadopoulos D, Bekiari T, Sarafis P. ICU nurse’s moral distress as an occupational hazard threatening professional quality of life in the time of pandemic COVID 19. Materia socio-medica. 2021;33(2):88.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Miljeteig I, Forthun I, Hufthammer KO, Engelund IE, Schanche E, Schaufel M, et al. Priority-setting dilemmas, moral distress and support experienced by nurses and physicians in the early phase of the COVID-19 pandemic in Norway. Nurs Ethics. 2021;28(1):66–81.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Romero-García M, Delgado-Hito P, Gálvez-Herrer M, Ángel-Sesmero JA, Velasco-Sanz TR, Benito-Aracil L, et al. Moral distress, emotional impact and coping in intensive care unit staff during the outbreak of COVID-19. Intensive Crit Care Nurs. 2022;70:103206.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Plouffe RA, Nazarov A, Forchuk CA, Gargala D, Deda E, Le T, et al. Impacts of morally distressing experiences on the mental health of Canadian health care workers during the COVID-19 pandemic. Eur J Psychotraumatology. 2021;12(1):1984667.

    Article  Google Scholar 

  56. Williamson V, Lamb D, Hotopf M, Raine R, Stevelink S, Wessely S et al. Moral injury and psychological wellbeing in UK healthcare staff. J Mental Health. 2023:1–9.

  57. Menzies RE, Sharpe L, Dar-Nimrod I. The relationship between death anxiety and severity of mental illnesses. Br J Clin Psychol. 2019;58(4):452–67.

    Article  PubMed  Google Scholar 

  58. Lesley M. Psychoanalytic perspectives on moral injury in nurses on the frontlines of the COVID-19 pandemic. J Am Psychiatr Nurses Assoc. 2021;27(1):72–6.

    Article  PubMed  Google Scholar 

  59. Borges LM, Barnes SM, Farnsworth JK, Bahraini NH, Brenner LA. A commentary on moral injury among health care providers during the COVID-19 pandemic. Psychol Trauma: Theory Res Pract Policy. 2020;12(S1):S138.

    Article  Google Scholar 

  60. Roycroft M, Wilkes D, Pattani S, Fleming S, Olsson-Brown A. Limiting moral injury in healthcare professionals during the COVID-19 pandemic. Oxford University Press UK; 2020. pp. 312–4.

  61. Xiao X, Zhu X, Fu S, Hu Y, Li X, Xiao J. Psychological impact of healthcare workers in China during COVID-19 pneumonia epidemic: a multi-center cross-sectional survey investigation. J Affect Disord. 2020;274:405–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Elbay RY, Kurtulmuş A, Arpacıoğlu S, Karadere E. Depression, anxiety, stress levels of physicians and associated factors in Covid-19 pandemics. Psychiatry Res. 2020;290:113130.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Özdin S, Bayrak Özdin Ş. Levels and predictors of anxiety, depression and health anxiety during COVID-19 pandemic in Turkish society: the importance of gender. Int J Soc Psychiatry. 2020;66(5):504–11.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Albert PR. Why is depression more prevalent in women? J Psychiatry Neurosci; 2015. pp. 219–21.

  65. McLean CP, Asnaani A, Litz BT, Hofmann SG. Gender differences in anxiety disorders: prevalence, course of illness, comorbidity and burden of illness. J Psychiatr Res. 2011;45(8):1027–35.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Costa C, Briguglio G, Mondello S, Teodoro M, Pollicino M, Canalella A, et al. Perceived stress in a gender perspective: a survey in a population of unemployed subjects of Southern Italy. Front Public Health. 2021;9:640454.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Babore A, Lombardi L, Viceconti ML, Pignataro S, Marino V, Crudele M, et al. Psychological effects of the COVID-2019 pandemic: perceived stress and coping strategies among healthcare professionals. Psychiatry Res. 2020;293:113366.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Flesia L, Monaro M, Mazza C, Fietta V, Colicino E, Segatto B, et al. Predicting perceived stress related to the Covid-19 outbreak through stable psychological traits and machine learning models. J Clin Med. 2020;9(10):3350.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Liu X, Kakade M, Fuller CJ, Fan B, Fang Y, Kong J, et al. Depression after exposure to stressful events: lessons learned from the severe acute respiratory syndrome epidemic. Compr Psychiatr. 2012;53(1):15–23.

    Article  Google Scholar 

  70. Croghan IT, Chesak SS, Adusumalli J, Fischer KM, Beck EW, Patel SR, et al. Stress, resilience, and coping of healthcare workers during the COVID-19 pandemic. J Prim Care Community Health. 2021;12:21501327211008448.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Liu N, Zhang F, Wei C, Jia Y, Shang Z, Sun L, et al. Prevalence and predictors of PTSS during COVID-19 outbreak in China hardest-hit areas: gender differences matter. Psychiatry Res. 2020;287:112921.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Qiu J, Shen B, Zhao M, Wang Z, Xie B, Xu Y. A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: implications and policy recommendations. Gen Psychiatry. 2020;33(2).

  73. Whitehead PB, Herbertson RK, Hamric AB, Epstein EG, Fisher JM. Moral distress among healthcare professionals: report of an institution-wide survey. J Nurs Scholarsh. 2015;47(2):117–25.

    Article  PubMed  Google Scholar 

  74. Dalmolin GdL, Lunardi VL, Lunardi GL, Barlem ELD, Silveira Rsd. Moral distress and burnout syndrome: are there relationships between these phenomena in nursing workers? Rev Latinoam Enferm. 2014;22(01):35–42.

    Article  Google Scholar 

  75. Fumis RRL, Junqueira Amarante GA, de Fátima Nascimento A, Vieira Junior JM. Moral distress and its contribution to the development of burnout syndrome among critical care providers. Ann Intensiv Care. 2017;7:1–8.

    Article  Google Scholar 

  76. Lake ET, Narva AM, Holland S, Smith JG, Cramer E, Rosenbaum KEF, et al. Hospital nurses’ moral distress and mental health during COVID-19. J Adv Nurs. 2022;78(3):799–809.

    Article  PubMed  Google Scholar 

  77. Ulusoy S, Çelik Z. The Silent Cry of Healthcare workers: a cross-sectional study on levels and determinants of burnout among Healthcare Workers after First Year of the pandemic in Turkey. Psychiatry Clin Psychopharmacol. 2022;32(1):63–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Zerach G, Levi-Belz Y. Moral injury and mental health outcomes among Israeli health and social care workers during the COVID-19 pandemic: a latent class analysis approach. Eur J Psychotraumatology. 2021;12(1):1945749.

    Article  Google Scholar 

  79. Schneider JN, Hiebel N, Kriegsmann-Rabe M, Schmuck J, Erim Y, Morawa E, et al. Moral distress in hospitals during the first wave of the COVID-19 pandemic: a web-based survey among 3,293 healthcare workers within the German network university medicine. Front Psychol. 2021;12:775204.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Sert Özen A, Kalaycıoğlu O. The effect of occupational moral injury on career abandonment intention among physicians in the context of the COVID-19 pandemic. 2023.

  81. Jovarauskaite L, Murphy D, Truskauskaite-Kuneviciene I, Dumarkaite A, Andersson G, Kazlauskas E. Associations between moral injury and ICD-11 post-traumatic stress disorder (PTSD) and complex PTSD among help-seeking nurses: a cross-sectional study. BMJ open. 2022;12(5):e056289.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study is an approved project of Bam University of Medical Sciences. The authors hereby express their gratitude to the Bam University of Medical Sciences.

Funding

Bam University of Medical Sciences.

Author information

Authors and Affiliations

  1. Department of Nursing, Bam University of Medical Sciences, Bam, Iran

    Mojtaba Jafari & Asra Nassehi

  2. Non-Communicable Diseases Research Center, Bam University of Medical Sciences, Bam, Iran

    Mojtaba Jafari

  3. Department of Nursing, Zahedan University of Medical Sciences, Zahedan, Iran

    Javad Jafari

  4. Nursing Care Research Center, Clinical Sciences Institute, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran

    Mehdi Jafari-Oori

Authors
  1. Mojtaba Jafari
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Asra Nassehi
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Javad Jafari
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Mehdi Jafari-Oori
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Study design: JJ, AN. Data extraction and collection: MJ, MJO, and JJ. Data analysis and interpretation: MJO, AN, and MJ. Manuscript writing: MJ, AN. and MJO. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Mehdi Jafari-Oori.

Ethics declarations

Ethics approval

This study was approved by the Ethics Committee of Bam University of Medical Sciences, Bam, Iran (Ethics code: IR.MUBAM.REC.1403.012).

Consent for participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jafari, M., Nassehi, A., Jafari, J. et al. Severity and associated factors of moral injury in healthcare workers during the coronavirus pandemic: a comprehensive meta-analysis. Arch Public Health 83, 37 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13690-025-01518-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13690-025-01518-2

Keywords

Archives of Public Health

ISSN: 2049-3258