Abstract
Background
The prolonged COVID-19 pandemic has burdened health professionals mentally and physically. This study aims to explore the relationship between moral injury (MI) and suicidal ideation (SI), and the role of mental health conditions in this relationship.
Methods
Three-wave repeated online cross-sectional study with a total of 10,388 health professionals were conducted in different stages (2020–2022) of the COVID-19 pandemic in mainland China. Participants completed the Chinese version of the Moral Injury Symptoms Scale-Health Professional, Post-Traumatic Stress Disorder (PTSD) Checklist for DSM-5 coupled with a blanket of scales.
Results
The prevalence of SI and MI among health professionals was 9.8 % and 40.2 %, respectively. The prevalence risk of SI was lower in wave 2 (OR = 0.64, 95 % CI: 0.54–0.77) and wave 3 (OR = 0.71, 95 % CI: 0.60–0.84) when compared with wave 1. MI (OR = 4.66, 95 % CI: 3.99–5.43), medical error (OR = 1.15, 95 % CI: 1.00–1.32), workplace violence (OR = 1.13, 95 % CI: 0.97–1.32), depression (OR = 94.08, 95 % CI: 63.37–139.69), anxiety (OR = 25.54, 95 % CI: 21.22–30.74), PTSD (OR = 24.51, 95 % CI: 19.01–31.60) were associated with a higher risk of SI. The mediation model revealed that depressive, anxiety, and PTSD symptoms explained 90.6 % of the total variance in the relationship between MI and SI.
Conclusions
The risk of SI has reduced among health professionals since the first peak of the COVID-19 pandemic in China. MI may contribute to prevalent SI, and mental health conditions, especially depressive symptoms, play a significant role as mediators.
Limitations
Cross-sectional design precludes the investigation of casual relationships. The nonrandom sampling method limits the generalization.
Keywords: Moral injury, Suicidal ideation, Depression, Mediation effect, Health professional
1. Background
Suicide is a serious public health problem that killed approximately 703,000 people 2019 (World Health Organization, 2021). At the same time, studies have indicated that health professionals (HPs) are at higher risk of suicide than the general population (Rose and Rosow, 1973; Schernhammer and Colditz, 2004). The prolonged COVID-19 pandemic may worsen the psychological crisis due to the increased psychological distress, anxiety, depression, and insomnia among health professionals (Farooq et al., 2021; Liu et al., 2019). As one of the pre-conditions for suicide, early identifying and intervening in suicidal ideation (SI) is a critical step, according to the ideation-to-action framework (Beck et al., 1999; Gunnell et al., 2020). One study found that 12.3 % of junior doctors in Australia had experienced SI in the last 12 months (Petrie et al., 2020). Moreover, 12.0 % of the Chinese frontline healthcare reported SI at the early stage of the COVID-19 pandemic (Cai et al., 2020). However, studies about trends of SI among HPs during the different stages of the COVID-19 pandemic are rare.
Moral injury (MI), the psychological consequence of transgressing moral values or witnessing such transgressions, has been increasingly recognized in a range of occupations (military personnel, health care workers, first responders, etc.) (Koenig and Al Zaben, 2021). MI among HPs has attracted considerable attention in recent years (Kopacz et al., 2019) and has been found to be a prevalent occupational functional impairment (Sert-Ozen and Kalaycioglu, 2022). A disaster like the COVID-19 pandemic has confronted HPs with increased exposure to potentially moral injurious events (PMIEs) (Mantri et al., 2021; Spilg et al., 2022). Under challenging circumstances, frontline health professionals have been forced to make medical decisions that have moral significance, which in some cases has resulted in a loss of trust by patients and painful feelings about themselves (Ch et al., 2022; Lancaster and Miller, 2020). Studies have found MI was associated with several adverse mental health conditions among military personnel (Battles et al., 2018; Bryan et al., 2014; Currier et al., 2019), as well as other vulnerable groups (McEwen et al., 2022). Few studies have indicated that MI was an understudied contributor to suicide risk in the varied population. One study found that MI was associated with a significantly higher risk of SI among National Guard personnel (Bryan et al., 2018). Another study revealed that three core symptoms of MI (transgressions by self, others, and betrayal) were associated with an increased risk of SI among US combat veterans (Nichter et al., 2021). Additionally, primary evidence among civilians revealed the same association between MI and suicidal behaviors (Fani et al., 2021).
Several possible psycho-social mechanisms have been presented to explain how MI leads to an increased risk of SI. First, as mentioned again, the symptoms of MI include difficulty in forgiveness, anger, loss of trust, and so on directly lead to suicidal thoughts. Second, according to the strain theory, the decision made under exposure to PMIEs may cause religious strain, leading to suicidal behaviors (Lancaster and Miller, 2020). Finally, the co-exist adverse mental outcomes played a role in the relationship between MI and SI. Studies have found that MI interaction with PTSD increases the risk of suicidal behaviors in military personnel. While this pathway still needs further evidence outside the military-related population. Thus, one study revealed that more MI symptoms are linked to higher levels of anxiety/depression symptoms among HPs (Levi-Belz and Zerach, 2022), in turn, contributes to suicide risk.
To our knowledge, no study has yet explored the trends of SI among health professionals in the different stages of the pandemic in China. The present study sought to do precisely that and test mental health conditions' role in the relationship between MI and SI. We hypothesized that the risk of suicidal ideation differed in different stages of the pandemic, and moral injury increased the risk of SI through several adverse mental health conditions.
2. Methods
2.1. Participants and procedure
Adults who self-identified as health professionals (HPs), including physicians, medical technicians, and nurses were recruited from social media, email lists, and newsletters across mainland China. We excluded those who were absent from practice for six months or longer due to any reason in the past two years; or those without a current active license. Due to the risk of infection, traditional face-to-face interviews were not employed (even though the pandemic was largely under control).
According to the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) (Eysenbach, 2004), a three-wave repeated online survey was developed to collect the data in different stages of the pandemic, the first wave opened from March 27 to April 26, 2020 (one month after the first peak of the pandemic in China). The second wave opened from March 27th to April 26th 2021 (the zero-COVID policy and regular epidemic prevention and control rules applied nationally). And the third wave opened from April 1st to April 30th 2022 (the second peak of the pandemic happened in China). The detailed procedure of participant enrollment has been reported (Qin et al., 2023), in summary, a total of 51,685 potential participants were invited to attend the study, and 12,411 agreed and completed the survey (response rates were 24.0 % in total, 20.2 %, 25.1 %, and 27.4 % in wave 1, wave 2, and wave 3, respectively). We excluded 2023 records due to missing values and exclusion criteria, and the final sample of 10,388 participants (3006 in the first wave, 3465 in the second wave, and 3917 in the third wave) in this study.
2.2. Measures
2.2.1. Moral injury
MI was assessed using the 10-item Chinese version of the Moral Injury Symptoms Scale-Health Professional (MISS-HP) (Zhizhong et al., 2020). This measure assesses ten dimensions of MI: betrayal, guilt, shame, moral concerns, loss of trust, loss of meaning, difficulty forgiving, self-condemnation, faith struggle, and loss of faith (Mantri et al., 2020). Response options for each of the ten items range from 1 to 10, indicating agreement or disagreement, resulting in a total score ranging from 10 to 100, with higher scores indicating more severe MI symptoms. The Chinese version of MISS-HP is a well-validated instrument applicable to health professionals with a Cronbach's alpha of 0.71; a test-retest coefficient of 0.77; and a cutoff value of 50 indicative of significant MI symptoms (Zhizhong et al., 2020). The Cronbach's alpha in the present study was 0.72.
2.2.2. Mental health condition
A battery of instruments was used to measure the mental health condition. The short-form PTSD Checklist for DSM-5 (PCL-5-SF) was used to assess the symptoms of PTSD (Zuromski et al., 2019). This four-item instrument assessed the core symptoms of PTSD and is well-suited for epidemiological study. Each item is scored from 0 to 4 (not at all, a little bit, moderately, quite a bit, extremely), resulting in a total score ranging from 0 to 16; a cut-off score of 6 indicates clinically significant PTSD symptoms. The Chinese version of the PCL-5-SF has acceptable psychometric properties (Li et al., 2019). The 9-item Patient Health Questionnaire (PHQ-9) was used to measure depressive symptoms and severity in the past 2 weeks. Each item is rated on a 4-point Likert scale from 0 (Not at All) to 3 (Nearly Every Day), resulting in a total score of 0–27, while equal or over 10 indicates clinically significant depressive symptoms (Kroenke et al., 2001). The 7-item Generalized Anxiety Disorder (GAD-7) was used to measure the severity of generalized anxiety disorders and was also shown to be a reliable screening tool for panic and social anxiety. Each item is rated on a 4-point Likert scale for how often each symptom has occurred in the past 2 weeks, from 0 (Not at All) to 3 (Nearly Every Day), with a total score of 0–21. Equal or over 10 indicates clinically significant anxiety symptom (Spitzer et al., 2006). The Chinese version of PHQ-9 and GAD-7scale both have internal solid and test-retest reliability as well as construct and factor structure validity in patients and the general population (He et al., 2010; Zhang et al., 2013). In this study, the Cronbach alpha for PCL-5-SF was 0.90, 0.91 for PHQ-9, and 0.94 for GAD-7.
2.2.3. Suicidal ideation
One question abstracted from the PHQ-9 “Over the last two weeks how often have you been bothered by this problem: thoughts that you would be better off dead or hurting yourself in some way?” to measure the suicidal ideation. Participant response more than half the days or nearly every day was considered to reflect a positive response regarding possible suicidal ideation. This item has been found to be acceptable validation in various populations (Louzon et al., 2016; Th et al., 2023).
2.2.4. Covariates
Sociodemographic characteristics included age, sex, marital status, educational attainment, ethnicity (Chinese Han vs minority ethnicity), work in ICU/emergency room, physician or nurses, length of practice, exposure to patients with COVID-19, lifetime workplace violence experience, and witness of workplace violence experience were collected using a standard questionnaire.
2.3. Data analysis
Descriptive statistics were performed by calculating means, standard deviations (SD), and proportions. The chi-square test was used to test the distribution of suicidal ideation. The hierarchical unconditional logistic regression model was employed to test the association after controlling for covariates. We included all the covariate variables in the model (model 1), then added PTSD, depression, and anxiety separately in the model (model 2). We summarized the model index in the final report. Odds ratios (OR) with 95 % confidence intervals (95 % CIs) were calculated. Bootstrap methods were employed to examine the mediating effect of PTSD, depression, and anxiety in the relationship between moral injury and suicidal ideation. The chi-square test and logistic regression analysis were performed under IBM SPSS 23.0 software. The mediation analysis was performed under Mplus 8 software. The alpha level for statistically significant was set at 0.05.
3. Results
3.1. The Socio-demographical characteristics and the prevalence of suicidal ideation
The age of the participants in this study spanned from 20 to 60 years, with a mean of 35.5 years (SD = 8.1). The average length of practice among these participants was 11.0 years (SD = 8.4), varying between 2 and 40 years. The socio-demographical characteristics and prevalence of suicidal ideation among health professionals are shown in Table 1 . The final sample consisted of 3032(29.2 %) males and 7356 (70.8 %) females, most reporting being married (74.0 %), of Han ethnicity (82.9 %) and originating from western China (66.2 %). A relatively small proportion (9.5 %) declared a religious affiliation. Of the total sample, 3578 (34.4 %) were registered nurses, and 571(5.5 %) were psychiatrists. Only a limited number of participants reported directly providing healthcare to individuals diagnosed with COVID-19 (16.4 %), and a small number of participants worked in the ICU or emergency room (9.8 %). A significant proportion of the participants in the study experienced or witnessed WPV (55.4 %, 69.0 %). Approximately half of the participants reported being involved in a medical error (9.8 %). Moral injury is prevalent among HPs, with a prevalence of 40.2 %. Nearly one-quarter of the participants reported anxiety symptoms (22.5 %), while one-third reported symptoms of depression (34.9 %).
Table 1.
The socio-demographical characteristics and prevalence of suicidal ideation among health professionals (n = 10,388).
| Variable | Overall n (%) | Suicidal ideation n (%) | χ2 | P |
|---|---|---|---|---|
| Wave | 24.10 | <0.001 | ||
| Wave 1 | 3006 (28.9) | 328 (10.9) | ||
| Wave 2 | 3465 (33.4) | 262 (7.6) | ||
| Wave 3 | 3917 (37.7) | 328 (8.4) | ||
| Age group (year) | 22.47 | <0.001 | ||
| ≤30 | 3510 (33.8) | 335 (9.5) | ||
| 30–40 | 4364 (42.0) | 414 (9.5) | ||
| 40–50 | 1916 (18.4) | 141 (7.4) | ||
| ≥50 | 598 (5.8) | 28 (4.7) | ||
| LOP (year) | 6.20 | 0.045 | ||
| ≤5 | 2977 (28.7) | 289 (9.7) | ||
| 5–10 | 1896 (18.3) | 177 (9.3) | ||
| ≥10 | 5515 (53.1) | 452 (8.2) | ||
| Sex | 22.99 | <0.001 | ||
| Male | 3032 (29.2) | 331 (10.9) | ||
| Female | 7356 (70.8) | 587 (8.0) | ||
| Area | 11.37 | 0.003 | ||
| East | 2540 (24.5) | 183 (7.2) | ||
| Middle | 973 (9.4) | 87 (8.9) | ||
| West | 6875 (66.2) | 648 (9.4) | ||
| Marital status | 10.63 | 0.005 | ||
| Unmarried | 2305 (22.2) | 220 (9.5) | ||
| Married | 7692 (74.0) | 648 (8.4) | ||
| Div/wid | 391 (3.8) | 50 (12.8) | ||
| Education | 0.85 | 0.655 | ||
| Bachelor | 7883 (75.9) | 708 (9.0) | ||
| Master | 2091 (20.1) | 175 (8.4) | ||
| Ph.D. | 414 (4.0) | 35 (8.5) | ||
| Religious affiliation | 3.23 | 0.072 | ||
| Yes | 982 (9.5) | 102 (10.4) | ||
| No | 9406 (90.5) | 816 (8.7) | ||
| Ethnicity | 0.16 | 0.692 | ||
| Han | 8615 (82.9) | 757 (8.8) | ||
| Minorities | 1773 (17.1) | 161 (9.1) | ||
| ICU/emergency | 22.30 | <0.001 | ||
| No | 9366 (90.2) | 787 (8.4) | ||
| Yes | 1022 (9.8) | 131 (12.8) | ||
| Nurse | 4.09 | 0.043 | ||
| Yes | 3578 (34.4) | 574 (16.0) | ||
| No | 6810 (65.6) | 344 (5.1) | ||
| Psychiatrist | 3.57 | 0.059 | ||
| Yes | 571 (5.5) | 38 (6.7) | ||
| No | 9817 (94.5) | 880 (9.0) | ||
| COVID-19 care | 0.08 | 0.775 | ||
| Yes | 1708 (16.4) | 154 (9.0) | ||
| No | 8680 (83.6) | 764 (8.8) | ||
| Medical error | 7.49 | 0.006 | ||
| Yes | 4200 (40.4) | 410 (9.8) | ||
| No | 6188 (59.6) | 508 (8.2) | ||
| WPV | 15.00 | <0.001 | ||
| Yes | 5752 (55.4) | 564 (9.8) | ||
| No | 4636 (44.6) | 354 (7.6) | ||
| Witness WPV | 3.99 | 0.046 | ||
| Yes | 7166 (69.0) | 660 (9.2) | ||
| No | 3222 (31.0) | 258 (8.0) | ||
| Depression | 1715.04 | <0.001 | ||
| Yes | 3630 (34.9) | 892 (24.6) | ||
| No | 6758 (65.1) | 26 (0.4) | ||
| Anxiety | 2150.32 | <0.001 | ||
| Yes | 2336 (22.5) | 767 (32.8) | ||
| No | 8052 (77.5) | 151 (1.9) | ||
| PTSD* | 1172.30 | <0.001 | ||
| Yes | 2023 (19.5) | 518 (25.6) | ||
| No | 5359 (51.6) | 72 (1.3) | ||
| Moral injury | 478.49 | <0.001 | ||
| Yes | 4173 (40.2) | 679 (16.3) | ||
| No | 6215 (59.8) | 239 (3.8) |
Note: LOP: Length of practice; div/wid: divorced/widow; WPV: Workplace violence; PTSD: Post-traumatic Stress Disease; *PTSD was measured in wave2 and wave3 (n = 7382); the Chi-square test was performed to examine the association between suicidal ideation and socio-demographic characteristics.
The prevalence of suicidal ideation is higher among participants who brought in wave 1 (10.9 %) than wave 2 (7.6 %), and wave 3 (8.4 %). Males, Younger, with fewer practice years, living in the western area, divorced or widowed had a higher prevalence. HPs worked in the ICU/emergency room, were nurses, had experienced a medical error, workplace violence, and witnessed workplace violence with a higher prevalence of suicidal ideation. The prevalence of suicidal ideation is much higher in those with any mental health conditions, 24.6 % in those with significant depressive symptoms, 32.8 % in those with significant anxiety symptoms, and 25.6 % in those with significant PTSD symptoms. HPs met MI criteria had a higher prevalence of suicidal ideation than those who did not (16.3 % vs 3.8 %, P < 0.05).
3.2. The multivariate logistic regression
As shown in Table 2 , under controlling the covariates of socio-demographic (model 1), the prevalence risk of suicidal ideation is lower in wave 2 (OR = 0.64) and wave 3 (OR = 0.71). When considering the mental health conditions, moral injury, and the work-related adverse experience (workplace violence, medical error), the prevalence risk of suicidal ideation decreased with the pandemic prolonged (compared with wave1, OR is 0.69 for wave 2, P < 0.001, OR is 0.72 for wave 3, P < 0.001) (model 2). Being male, living in western China, divorced or widowed, working in the ICU or emergency room, and being a nurse are associated with a higher risk of suicidal ideation. Participants aged up to 50 were less likely to report suicidal behaviors, while medical error (OR = 1.15, 95 % CI: 1.00–1.32), WPV (OR = 1.13, 95 % CI: 0.97–1.32), depression (OR = 94.08, 95 % CI: 63.37–139.69), anxiety (OR = 25.54, 95 % CI: 21.22–30.74), PTSD (OR = 24.51, 95 % CI: 19.01–31.60) and MI (OR = 4.66, 95 % CI: 3.99–5.43) were found to be strong predictors of suicidal ideation (model 2).
Table 2.
The hierarchical unconditional logistic regression model (n = 10,388).
| Variables | Model 1 |
Model 2 |
||
|---|---|---|---|---|
| P | OR (95 % CI) | P | OR (95 % CI) | |
| Wave (wave 1 ref) | ||||
| Wave 2 | <0.001 | 0.64 (0.54–0.77) | <0.001 | 0.69 (0.57–0.82) |
| Wave 3 | <0.001 | 0.71 (0.60–0.84) | <0.001 | 0.72 (0.60–0.85) |
| Age group (≤30 ref) | ||||
| 30–40 | 0.476 | 1.10 (0.85–1.41) | 0.462 | 1.10 (0.85–1.42) |
| 40–50 | 0.229 | 0.82 (0.58–1.14) | 0.325 | 0.84 (0.60–1.19) |
| ≥50 | 0.005 | 0.51 (0.31–0.81) | 0.022 | 0.57 (0.35–0.92) |
| LOP (≤5 ref) | ||||
| 5–10 | 0.416 | 0.91 (0.72–1.15) | 0.295 | 0.88 (0.69–1.12) |
| ≥10 | 0.464 | 0.90 (0.68–1.20) | 0.340 | 0.87 (0.65–1.16) |
| Sex (male) | <0.001 | 1.65 (1.41–1.94) | <0.001 | 1.54 (1.30–1.82) |
| Area (east ref) | ||||
| Middle | 0.204 | 1.19 (0.91–1.56) | 0.412 | 1.12 (0.85–1.48) |
| West | 0.003 | 1.30 (1.09–1.56) | 0.016 | 1.25 (1.04–1.50) |
| Marital status (unmarried ref) | ||||
| Married | 0.627 | 0.95 (0.78–1.16) | 0.993 | 1.00 (0.82–1.23) |
| Div/wid | 0.002 | 1.79 (1.24–2.58) | 0.002 | 1.84 (1.26–2.68) |
| Education (bachelor ref) | ||||
| Master | 0.545 | 0.94 (0.78–1.14) | 0.759 | 0.97 (0.80–1.18) |
| Ph.D. | 0.991 | 1.00 (0.69–1.44) | 0.836 | 1.04 (0.71–1.52) |
| Religious affiliation (yes) | 0.291 | 1.14 (0.89–1.47) | 0.658 | 1.06 (0.82–1.36) |
| Ethnicity (minority) | 0.609 | 0.95 (0.77–1.17) | 0.965 | 1.00 (0.81–1.23) |
| ICU/emergency (yes) | <0.001 | 1.45 (1.18–1.77) | 0.001 | 1.42 (1.15–1.75) |
| Nurse (yes) | 0.001 | 1.36 (1.13–1.62) | 0.001 | 1.38 (1.15–1.66) |
| Psychiatry (yes) | 0.229 | 0.81 (0.57–1.14) | 0.406 | 0.86 (0.61–1.23) |
| COVID-19 care (yes) | 0.368 | 0.92 (0.76–1.11) | 0.665 | 0.96 (0.79–1.16) |
| Medical error (yes) | NA | NA | 0.050 | 1.15 (1.00–1.32) |
| WPV (yes) | NA | NA | <0.001 | 1.30 (1.13–1.50) |
| Witness WPV (yes) | NA | NA | 0.118 | 1.13 (0.97–1.32) |
| Depression (yes) | NA | NA | <0.001 | 94.08 (63.37–139.69) |
| Anxiety (yes) | NA | NA | <0.001 | 25.54 (21.22–30.74) |
| PTSD (yes)a | NA | NA | <0.001 | 24.51 (19.01–31.60) |
| Moral injury (yes) | NA | NA | <0.001 | 4.66 (3.99–5.43) |
Note. Model 1: demographic characteristics entered model; Model 2: adjusted for demographic characteristics; LOP: length of practice; div/wid: divorced/widow; WPV: workplace violence; PTSD: post-traumatic stress disease.
PTSD was measured in wave2 and wave3 (n = 7382).
3.3. The mediation model
A multi-variable mediation model was employed to explore the mediating effects of depression, anxiety and PTSD on the relationship between moral injury and suicidal ideation. As shown in Fig. 1 , after adjusting the socio-demographic characteristics, moral injury was associated with depression (a1), anxiety (a2), and PTSD (a3) significantly, then those mental conditions partly bridged the association between moral injury and suicidal ideation. Both the direct effects (β = 0.737, p < 0.001) and indirect effects (mediation effect: 3.907 + 1.726 + 1.453) of moral injury on suicidal ideation were significant. Further, depression explained 49.9 % of the total variance, anxiety explained 22.1 % of the total variance, and PTSD explained 18.6 % of the total variance (Table 3 ).
Fig. 1.
Mediating effects of mental conditions on the relationship between Moral Injury and Suicidal Ideation (n = 7382) Socio-demographic variables were adjusted in this mediation model, the independent and mediating variables were analyzed as categorical. The mediation effect of depression, anxiety, and PTSD were a1 ∗ b1, a2 ∗ b2, and a3 ∗ b3, respectively; The total effect of moral injury on suicidal ideation is a1 ∗ b1 + a2 ∗ b2 + a3 ∗ b3 + c.
Table 3.
Mediating effects of relationship between moral injury and suicidal ideation (n = 7382).
| Model pathways | Point estimate | Product of coefficients |
95 % CI |
P | Proportion (%) | ||
|---|---|---|---|---|---|---|---|
| SE | Z | Lower | Upper | ||||
| Total effect | 7.824 | 0.437 | 17.919 | 6.981 | 8.659 | <0.001 | 100.0 |
| Direct effect | 0.737 | 0.121 | 6.094 | 0.493 | 0.967 | <0.001 | 9.4 |
| Depression | 3.907 | 0.363 | 10.758 | 3.246 | 4.665 | <0.001 | 49.9 |
| Anxiety | 1.726 | 0.203 | 8.492 | 1.333 | 2.12 | <0.001 | 22.1 |
| PTSD | 1.453 | 0.208 | 6.978 | 1.058 | 1.87 | <0.001 | 18.6 |
Note: The mediation analysis was conducted after controlling for socio-demographic characteristics, the independent and mediating variables were analyzed as categorical data.
3.4. Sensitivity analysis
The results of the sensitivity analysis are available in the supplementary file. As demonstrated in Table S1, while analyzing in an all-enter model, we conducted three logistic regression analyses respectively for three waves. The results of work-related experience features exhibited no significance, while the mental health conditions symptoms proved to be statistically significant in all three waves. We changed the cutoff point of SI as the response of some days or over (item 9 scores equal 1 or over), repeated the regression models, and found similar results, as shown in Table S2. As for the regression model, we also repeated the mediation model at this time, and a similar result was also found in the sensitivity analysis shown in Table S3. Furthermore, we conducted sensitivity analyses with the depression measurement modified. As mentioned, the PHQ-9 scale was employed to measure depression in our study, while the ninth item of PHQ-9 was used to measure suicidal ideation. As a result, we excluded the ninth item of the PHQ-9 scale and renamed it PHQ in order to demonstrate the stability of the result. PHQ scores were treated as continuous data in the absence of an established cutoff for this particular measurement of depression. The sensitivity analyses were conducted using a multivariate logistic regression model and a mediation model. The result was consistent with those obtained in other analyses, as presented in Tables S4, and S5.
4. Discussion
Public health crises like the COVID-19 pandemic may increase the risk of suicidal behaviors and moral injury among health professionals. This study showed that the prevalence risk of suicidal ideation decreased with the prolonged pandemic. Compared with the early stage of the pandemic, the prevalence risk was lower when the zero-COVID-19 policy and regular epidemic prevention and control rules were applied nationally, and the stage two years after the first peak of the pandemic in mainland China. Also, over half of the health professionals reported experiencing a significant symptom of MI, as the study reported during the early stage of the pandemic when healthcare resources were minimal, and the number of positive cases increased rapidly (Wang et al., 2022). Consistent with previous studies, we found that MI linking with a higher risk of suicidal ideation in the total sample as well as the three separate samples. Moreover, mental health conditions (primarily depressive symptoms) mediated this relationship (Hall et al., 2022). To the best of our knowledge, this is the first study that sustained monitored the risk and potential correlators of suicidal ideation among health professionals in the high-stake situations.
Previous studies investigated the association between MI and SI (Kelley et al., 2021; Schwartz et al., 2022). Besides, our study is further substantiated by the results of the first longitudinal study on the mental health of health professionals in the United States during the COVID-19, which confirmed that high levels of MI are strongly associated with SI, particularly among those with self-reported COVID-19 exposure (Amsalem et al., 2021). Demonstrates evidence for MI as a distinct trauma-related response that may independently contribute to the risk for suicidal behavior. The connection between mental health disorders (such as depression (Shoib et al., 2021), anxiety (Kanwar et al., 2013), PTSD (Bryan et al., 2018)) and SI is also significant that an estimated approximately half of suicides in high-income countries can be attributed to mental illnesses (Levi-Belz and Zerach, 2018). Since the COVID-19 pandemic brings out massive pressure on healthcare system, an increased vulnerability among health professionals in confronting the COVID-19 pandemic might occur (Qin et al., 2023). Although few studies have explored the association between MI, mental health conditions and SI, the role of mental health conditions in the relationship between moral injury and suicidal ideation remain unclear.
Results of the present study indicate that mental disorders, including depression, anxiety, and PTSD, play a crucial mediating role in this association (P < 0.001). An increase in moral injury scores was found to correspond with an increased risk of prevalence of mental disorders, which in turn elevates the risk of suicidal ideation. Depression was a significant contributing factor to suicidality, accounting for approximately half of the indirect effect of suicidal ideation on moral injury (proportion = 49.9 %). Levi-Belz's (Levi-Belz and Zerach, 2018) study of combat veterans found that depression also served as a mediator in the association of MI and SI. While things happen differently, depression has also been shown to play a mediating role in the relationship between alcohol dependence and suicidal ideation (Cohen et al., 2017). Anxiety, as well as PTSD, was also identified as a significant mediator in the relationship between moral injury and suicidal ideation (proportion = 22.1 % and 18.6 %, respectively). While in other research, anxiety was found to be the mediator account for the link between PTSD and SI (Raines et al., 2017; Stanley et al., 2017). However, the direct link between MI and SI was relatively small, contributing only 9.4 % to the total effect, and with limited research on the subject, suggesting the need for further research to understand the mediating factors better.
Several socio-demographic correlators of suicidal ideation among health professionals were identified in this study, including being male, younger, having fewer practice years, living in the western area, divorced or widowed. The prevalence difference in gender is consistent with a US study, finding that the prevalence of male suicide was greater than that of female suicide (Ivey-Stephenson et al., 2017). However, a systematic review indicated that female physicians had higher rates of suicidal ideation than male physicians, but this declined over time (Duarte et al., 2020). Young health professionals had higher rates of SI, with a report of about 9.5 % of participants younger than 40, consistent with previous research that has shown suicide is the second leading cause of death globally among people aged 15–29 years (Aggarwal et al., 2017). The increased prevalence of suicidal ideation among young health professionals may be due to academic stress, lower psychological resilience, and lack of experience (Pekrun et al., 2002). Furthermore, the study also revealed that health professionals with <5 years of work experience had the highest levels of SI, which may be linked to an increase in depressive symptoms among junior doctors (Mata et al., 2015). Additionally, previous research has demonstrated the correlation between high levels of occupational stress and negative impacts on both physical and mental health conditions, as well as a reduction in self-assessed health (Milner et al., 2017), which is also indicated in our study.
Our findings provide preliminary evidence supporting the call to include creating a workplace culture that values ethical and moral principles in the development of preventative strategies for suicide among health professionals and also extend the implications of moral injury targeted treatment for mental disorders outside of the military personnel (Williamson et al., 2021). Suggesting that organizations save healthcare workforces by providing training and support for HPs (particularly those working in the ICU or emergency room, with negative life experiences, and young HPs) to help them navigate ethical dilemmas or supporting groups to help individuals process and heal from their experiences in the post-pandemic era.
5. Limitations
Several aspects of the present study limit the generalizability of these findings, thereby influencing both research and clinical implications. First, the cross-sectional design prevents making causal inferences in that prospective studies will be needed to determine whether MI symptoms cause a higher risk of PTSD and suicidal behaviors or vice versa or whether effects are bidirectional in nature. Second, the selective bias cannot be ignored due to the nonrandom sampling method and the online survey applied here, which requires cautious generalization to service members in other areas of China and health professionals outside of China. Third, as the previous study suggested, the ninth item of PHQ-9 was used to measure suicidal ideation instead of a gold standard measurement, further research is needed on its sensitivity. Finally, like all self-report measures, the accuracy of responses cannot be guaranteed where external factors may influence the report of symptoms (even though the survey was anonymous).
6. Conclusions
The risk of suicidal ideation among health professionals has decreased slightly since the first peak of the COVID-19 pandemic in mainland China. Moral injury may contribute to prevalent suicidal ideation and mental health conditions. The mediation model revealed a possible role of mental health conditions (especially depressive symptoms) in the relationship between moral injury and suicidal ideation. These findings underscore the need to identify and address symptoms of moral injury and mental health conditions among health professionals, with the terminate target of reducing the risk of suicidal behaviors and associated adverse outcomes. The study also highlights the long-term mental health impact of the COVID-19 pandemic, which poses a challenge to rebuilding the health system in the coming years.
CRediT authorship contribution statement
Study concept and design: Zhizhong Wang, Zhehao He.
Acquisition of subjects and data collection: Zhizhong Wang, Jun Liu, Xiuquan Shi, Hu Xue, Mengyun Xiong.
Analysis and interpretation of data: Zhehao He, Qiuhui Lei.
Preparation of manuscript: Zhehao He, Hu Xue, Qiuhui Lei, Mengyun Xiong.
Revision of the manuscript for critical intellectual content: Zhizhong Wang, Xiuquan Shi, Jing Wen, Jun Liu.
Approval of the final version of publication: all authors.
Conflict of interest
The authors declare that they have no competing interests.
Acknowledgments
Acknowledgments
We would like to thank colleagues at the General Hospital of Ningxia Medical University for their assistance in data collection.
Funding
This work was supported by Funds for Ph.D. researchers of Guangdong Medical University in 2022 (Project number: GDMUB2022049, Recipient: ZW) and the China Medical Board (Project number: CMB16-254, Recipient: ZW).
Availability of data and materials
The datasets generated and/or analyzed during the current study are not publicly available due to institutional restriction but are available from the corresponding author upon reasonable request (wzhzh_lion@126.com).
Ethics approval and consent to participants
The survey was anonymous. The potential risks and benefits of the survey were described on the first page of the survey. Online informed consent was obtained by asking participants to check a box on the device's screen with the response (I agree to participate in the study; I do not agree to participate in the survey). If the answer was “I do not agree”, the survey was immediately terminated automatically. The study was approved by the institutional review board of Ningxia Medical University (approval #2020-112).
Consent for publication
Not apply.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jad.2023.04.033.
Appendix A. Supplementary data
Supplementary tables
References
- Aggarwal S., Patton G., Reavley N., Sreenivasan S.A., Berk M. Youth self-harm in low- and middle-income countries: systematic review of the risk and protective factors. Int. J. Soc. Psychiatry. 2017;63:359–375. doi: 10.1177/0020764017700175. [DOI] [PubMed] [Google Scholar]
- Amsalem D., Lazarov A., Markowitz J.C., Naiman A., Smith T.E., Dixon L.B., Neria Y. Psychiatric symptoms and moral injury among US healthcare workers in the COVID-19 era. BMC Psychiatry. 2021;21:546. doi: 10.1186/s12888-021-03565-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Battles A.R., Bravo A.J., Kelley M.L., White T.D., Braitman A.L., Hamrick H.C. Moral injury and PTSD as mediators of the associations between morally injurious experiences and mental health and substance use. Traumatology. 2018;24:246–254. doi: 10.1037/trm0000153. [DOI] [Google Scholar]
- Beck A.T., Brown G.K., Steer R.A., Dahlsgaard K.K., Grisham J.R. Suicide ideation at its worst point: a predictor of eventual suicide in psychiatric outpatients. Suicide Life Threat Behav. 1999;29:1–9. [PubMed] [Google Scholar]
- Bryan A.O., Bryan C.J., Morrow C.E., Etienne N., Ray-Sannerud B. Moral injury, suicidal ideation, and suicide attempts in a military sample. Traumatology. 2014;20:154–160. doi: 10.1037/h0099852. [DOI] [Google Scholar]
- Bryan C.J., Bryan A.O., Roberge E., Leifker F.R., Rozek D.C. Moral injury, posttraumatic stress disorder, and suicidal behavior among national guard personnel. Psychol. Trauma. 2018;10:36–45. doi: 10.1037/tra0000290. [DOI] [PubMed] [Google Scholar]
- Cai Q., Feng H., Huang J., Wang M., Wang Q., Lu X., Xie Y., Wang X., Liu Z., Hou B., Ouyang K., Pan J., Li Q., Fu B., Deng Y., Liu Y. The mental health of frontline and non-frontline medical workers during the coronavirus disease 2019 (COVID-19) outbreak in China: a case-control study. J. Affect. Disord. 2020;275:210–215. doi: 10.1016/j.jad.2020.06.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ch R., Ta T., Im A., Ke N., D B., A V., D S., Cd L., Gc H. Moral injury and moral resilience in health care workers during COVID-19 Pandemic. J. Palliat. Medicine. 2022;25 doi: 10.1089/jpm.2021.0076. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cohen G.H., Fink D.S., Sampson L., Tamburrino M., Liberzon I., Calabrese J.R., Galea S. Coincident alcohol dependence and depression increases risk of suicidal ideation among army national guard soldiers. Ann. Epidemiol. 2017;27:157–163.e1. doi: 10.1016/j.annepidem.2016.12.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Currier J.M., McDermott R.C., Farnsworth J.K., Borges L.M. Temporal associations between moral injury and posttraumatic stress disorder symptom clusters in military veterans. J. Trauma. Stress. 2019;32:382–392. doi: 10.1002/jts.22367. [DOI] [PubMed] [Google Scholar]
- Duarte D., El-Hagrassy M.M., Couto T.C.E., Gurgel W., Fregni F., Correa H. Male and female physician suicidality: a systematic review and meta-analysis. JAMA Psychiatry. 2020;77:587–597. doi: 10.1001/jamapsychiatry.2020.0011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Eysenbach G. Improving the quality of web surveys: the checklist for reporting results of internet E-surveys (CHERRIES) J. Med. Internet Res. 2004;6 doi: 10.2196/jmir.6.3.e34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fani N., Currier J.M., Turner M.D., Guelfo A., Kloess M., Jain J., Mekawi Y., Kuzyk E., Hinrichs R., Bradley B., Powers A., Stevens J.S., Michopoulos V., Turner J.A. Moral injury in civilians: associations with trauma exposure, PTSD, and suicide behavior. Eur. J. Psychotraumatol. 2021;12:1965464. doi: 10.1080/20008198.2021.1965464. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Farooq S., Tunmore J., Wajid Ali M., Ayub M. Suicide, self-harm and suicidal ideation during COVID-19: a systematic review. Psychiatry Res. 2021;306 doi: 10.1016/j.psychres.2021.114228. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gunnell D., Appleby L., Arensman E., Hawton K., John A., Kapur N., Khan M., O’Connor R.C., Pirkis J., Appleby L., Arensman E., Caine E.D., Chan L.F., Chang S.-S., Chen Y.-Y., Christensen H., Dandona R., Eddleston M., Erlangsen A., Gunnell D., Harkavy-Friedman J., Hawton K., John A., Kapur N., Khan M., Kirtley O.J., Knipe D., Konradsen F., Liu S., McManus S., Mehlum L., Miller M., Moran P., Morrissey J., Moutier C., Niederkrotenthaler T., Nordentoft M., O’Connor R.C., O’Neill S., Page A., Phillips M.R., Pirkis J., Platt S., Pompili M., Qin P., Rezaeian M., Silverman M., Sinyor M., Stack S., Townsend E., Turecki G., Vijayakumar L., Yip P.S. Suicide risk and prevention during the COVID-19 pandemic. Lancet Psychiatry. 2020;7:468–471. doi: 10.1016/S2215-0366(20)30171-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hall N.A., Everson A.T., Billingsley M.R., Miller M.B. Moral injury, mental health and behavioural health outcomes: a systematic review of the literature. Clin. Psychol. Psychother. 2022;29:92–110. doi: 10.1002/cpp.2607. [DOI] [PubMed] [Google Scholar]
- He X., Li C., Qian J., Cui H.S., Wu W. Reliability and validity of a generalized anxiety scale in general hospital outpatients. Shanghai Arch. Psychiatry. 2010;22:200–203. doi: 10.3969/j.issn.1002-0829.2010.04.002. [DOI] [Google Scholar]
- Ivey-Stephenson A.Z., Crosby A.E., Jack S.P.D., Haileyesus T., Kresnow-Sedacca M.-J. Suicide trends among and within urbanization levels by sex, race/ethnicity, age group, and mechanism of death - United States, 2001–2015. MMWR Surveill. Summ. 2017;66:1–16. doi: 10.15585/mmwr.ss6618a1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kanwar A., Malik S., Prokop L.J., Sim L.A., Feldstein D., Wang Z., Murad M.H. The association between anxiety disorders and suicidal behaviors: a systematic review and meta-analysis. Depress Anxiety. 2013;30:917–929. doi: 10.1002/da.22074. [DOI] [PubMed] [Google Scholar]
- Kelley M.L., Chae J.W., Bravo A.J., Milam A.L., Agha E., Gaylord S.A., Vinci C., Currier J.M. Own soul's warning: moral injury, suicidal ideation, and meaning in life. Psychol. Trauma. 2021;13:740–748. doi: 10.1037/tra0001047. [DOI] [PubMed] [Google Scholar]
- Koenig H.G., Al Zaben F. Moral injury: an increasingly recognized and widespread syndrome. J. Relig. Health. 2021;60:2989–3011. doi: 10.1007/s10943-021-01328-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kopacz M.S., Ames D., Koenig H.G. It’s time to talk about physician burnout and moral injury. Lancet Psychiatry. 2019;6 doi: 10.1016/S2215-0366(19)30385-2. [DOI] [PubMed] [Google Scholar]
- Kroenke K., Spitzer R.L., Williams J.B. The PHQ-9: validity of a brief depression severity measure. J. Gen. Intern. Med. 2001;16:606–613. doi: 10.1046/j.1525-1497.2001.016009606.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lancaster S.L., Miller M. Moral decision making, religious strain, and the experience of moral injury. Psychol. Trauma. 2020;12:156–164. doi: 10.1037/tra0000518. [DOI] [PubMed] [Google Scholar]
- Levi-Belz Y., Zerach G. The wounded helper: moral injury contributes to depression and anxiety among israeli health and social care workers during the COVID-19 pandemic. Anxiety Stress Coping. 2022;35:518–532. doi: 10.1080/10615806.2022.2035371. [DOI] [PubMed] [Google Scholar]
- Levi-Belz Y., Zerach G. Moral injury, suicide ideation, and behavior among combat veterans: the mediating roles of entrapment and depression. Psychiatry Res. 2018;269:508–516. doi: 10.1016/j.psychres.2018.08.105. [DOI] [PubMed] [Google Scholar]
- Li J., Zhang W., Chen W., Yuan H., Zhang S., Tian M., Qu Z. Applications of the Chinese version of the primary care PTSD screen for DSM-5 (PC-PTSD-5) for children. J. Affect. Disord. 2019;254:109–114. doi: 10.1016/j.jad.2019.05.021. [DOI] [PubMed] [Google Scholar]
- Liu Y., Zhang J., Hennessy D.A., Zhao S., Ji H. Psychological strains, depressive symptoms, and suicidal ideation among medical and non-medical staff in urban China. J. Affect. Disord. 2019;245:22–27. doi: 10.1016/j.jad.2018.10.111. [DOI] [PubMed] [Google Scholar]
- Louzon S.A., Bossarte R., McCarthy J.F., Katz I.R. Does suicidal ideation as measured by the PHQ-9 predict suicide among VA patients? Psychiatr. Serv. 2016;67:517–522. doi: 10.1176/appi.ps.201500149. [DOI] [PubMed] [Google Scholar]
- Mantri S., Lawson J.M., Wang Z., Koenig H.G. Identifying moral injury in healthcare professionals: the moral injury symptom scale-HP. J. Relig. Health. 2020;59:2323–2340. doi: 10.1007/s10943-020-01065-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mantri S., Song Y.K., Lawson J.M., Berger E.J., Koenig H.G. Moral injury and burnout in health care professionals during the COVID-19 pandemic. J. Nerv. Ment. Dis. 2021;209:720–726. doi: 10.1097/NMD.0000000000001367. [DOI] [PubMed] [Google Scholar]
- Mata D.A., Ramos M.A., Bansal N., Khan R., Guille C., Di Angelantonio E., Sen S. Prevalence of depression and depressive symptoms among resident physicians: a systematic review and meta-analysis. JAMA. 2015;314:2373–2383. doi: 10.1001/jama.2015.15845. [DOI] [PMC free article] [PubMed] [Google Scholar]
- McEwen C., Alisic E., Jobson L. Moderating role of moral injury in the mental health of adolescent refugees. J. Clin. Psychol. 2022;78:1478–1490. doi: 10.1002/jclp.23306. [DOI] [PubMed] [Google Scholar]
- Milner A., Witt K., Spittal M.J., Bismark M., Graham M., LaMontagne A.D. The relationship between working conditions and self-rated health among medical doctors: evidence from seven waves of the medicine in Australia balancing employment and life (Mabel) survey. BMC Health Serv. Res. 2017;17:609. doi: 10.1186/s12913-017-2554-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Nichter B., Norman S.B., Maguen S., Pietrzak R.H. Moral injury and suicidal behavior among US combat veterans: results from the 2019–2020 national health and resilience in veterans study. Depress Anxiety. 2021;38:606–614. doi: 10.1002/da.23145. [DOI] [PubMed] [Google Scholar]
- Pekrun R., Goetz T., Titz W., Perry R.P. Academic emotions in students’ self-regulated learning and achievement: a program of qualitative and quantitative research. Educ. Psychol. 2002;37:91–105. doi: 10.1207/S15326985EP3702_4. [DOI] [Google Scholar]
- Petrie K., Crawford J., LaMontagne A.D., Milner A., Dean J., Veness B.G., Christensen H., Harvey S.B. Working hours, common mental disorder and suicidal ideation among junior doctors in Australia: a cross-sectional survey. BMJ Open. 2020;10 doi: 10.1136/bmjopen-2019-033525. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Qin Z., He Z., Yang Q., Meng Z., Lei Q., Wen J., Shi X., Liu J., Wang Z. The trends of burnout among health professionals during the pandemic: three-wave cross-sectional study. Asian J. Psychiatr. 2023;81 doi: 10.1016/j.ajp.2023.103458. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Raines A.M., Capron D.W., Stentz L.A., Walton J.L., Allan N.P., McManus E.S., Uddo M., True G., Franklin C.L. Posttraumatic stress disorder and suicidal ideation, plans, and impulses: the mediating role of anxiety sensitivity cognitive concerns among veterans. J. Affect. Disord. 2017;222:57–62. doi: 10.1016/j.jad.2017.06.035. [DOI] [PubMed] [Google Scholar]
- Rose K.D., Rosow I. Physicians who kill themselves. Arch. Gen. Psychiatry. 1973;29:800–805. doi: 10.1001/archpsyc.1973.04200060072011. [DOI] [PubMed] [Google Scholar]
- Schernhammer E.S., Colditz G.A. Suicide rates among physicians: a quantitative and gender assessment (meta-analysis) Am. J. Psychiatry. 2004;161:2295–2302. doi: 10.1176/appi.ajp.161.12.2295. [DOI] [PubMed] [Google Scholar]
- Schwartz G., Halperin E., Levi-Belz Y. Moral injury and suicide ideation among combat veterans: the role of trauma-related shame and collective hatred. J. Interpers. Violence. 2022;37:NP13952–NP13977. doi: 10.1177/08862605211007932. [DOI] [PubMed] [Google Scholar]
- Sert-Ozen A., Kalaycioglu O. The effect of occupational moral injury on career abandonment intention among physicians in the context of the COVID-19 pandemic. Saf. Health Work. 2022 doi: 10.1016/j.shaw.2022.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Shoib S., Islam S.M.S., Arafat S.Y., Hakak S.A. Depression and suicidal ideation among the geriatric population of Kashmir, India. Int. J. Soc. Psychiatry. 2021;67:651–655. doi: 10.1177/0020764020968592. [DOI] [PubMed] [Google Scholar]
- Spilg E.G., Rushton C.H., Phillips J.L., Kendzerska T., Saad M., Gifford W., Gautam M., Bhatla R., Edwards J.D., Quilty L., Leveille C., Robillard R. The new frontline: exploring the links between moral distress, moral resilience and mental health in healthcare workers during the COVID-19 pandemic. BMC Psychiatry. 2022;22:19. doi: 10.1186/s12888-021-03637-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Spitzer R.L., Kroenke K., Williams J.B.W., Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch. Intern. Med. 2006;166:1092–1097. doi: 10.1001/archinte.166.10.1092. [DOI] [PubMed] [Google Scholar]
- Stanley I.H., Hom M.A., Spencer-Thomas S., Joiner T.E. Examining anxiety sensitivity as a mediator of the association between PTSD symptoms and suicide risk among women firefighters. J Anxiety Disord. 2017;50:94–102. doi: 10.1016/j.janxdis.2017.06.003. [DOI] [PubMed] [Google Scholar]
- Th C., K H., Yc L., A M., F N., Jm D.F., Hc W., Wh C., Jc S., S S. A validation study of PHQ-9 suicide item with the Columbia Suicide Severity Rating Scale in outpatients with mood disorders at National Network of Depression Centers. Journal of Affective Disord. 2023;320 doi: 10.1016/j.jad.2022.09.131. [DOI] [PubMed] [Google Scholar]
- Wang Z., Koenig H.G., Tong Y., Wen J., Sui M., Liu H., Zaben F.A., Liu G. Moral injury in chinese health professionals during the COVID-19 pandemic. Psychol. Trauma. 2022;14:250–257. doi: 10.1037/tra0001026. [DOI] [PubMed] [Google Scholar]
- Williamson V., Murphy D., Phelps A., Forbes D., Greenberg N. Moral injury: the effect on mental health and implications for treatment. Lancet Psychiatry. 2021;8:453–455. doi: 10.1016/S2215-0366(21)00113-9. [DOI] [PubMed] [Google Scholar]
- World Health Organization Suicide worldwide in 2019. 2021. https://www.who.int/publications-detail-redirect/9789240026643 (accessed 6 Feb 2023)
- Zhang Ying-Li, Liang W., Chen Z.-M., Zhang H.-M., Zhang J.-H., Weng X.-Q., Yang S.-C., Zhang L., Shen L.-J., Zhang Ya-Lin. Validity and reliability of patient health Questionnaire-9 and patient health Questionnaire-2 to screen for depression among college students in China. Asia Pac. Psychiatry. 2013;5:268–275. doi: 10.1111/appy.12103. [DOI] [PubMed] [Google Scholar]
- Zhizhong W., Koenig H.G., Yan T., Jing W., Mu S., Hongyu L., Guangtian L. Psychometric properties of the moral injury symptom scale among chinese health professionals during the COVID-19 pandemic. BMC Psychiatry. 2020;20:556. doi: 10.1186/s12888-020-02954-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zuromski K.L., Ustun B., Hwang I., Keane T.M., Marx B.P., Stein M.B., Ursano R.J., Kessler R.C. Developing an optimal short-form of the PTSD checklist for DSM-5 (PCL-5) Depress Anxiety. 2019;36:790–800. doi: 10.1002/da.22942. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary tables
Data Availability Statement
The datasets generated and/or analyzed during the current study are not publicly available due to institutional restriction but are available from the corresponding author upon reasonable request (wzhzh_lion@126.com).