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European Journal of Psychotraumatology logoLink to European Journal of Psychotraumatology
. 2025 Sep 4;16(1):2546291. doi: 10.1080/20008066.2025.2546291

Longitudinal associations between potentially morally injurious events and posttraumatic stress among combat veterans: the mediating role of moral injury outcomes

Asociaciones longitudinales entre eventos de daño moral potenciales y estrés postraumático en veteranos de combate: El papel mediador de los resultados del daño moral

Yoav Levinstein a,b,CONTACT, Yossi Levi-Belz c, Ariel Ben Yehuda a,d, Rachel Dekel c, Gadi Zerach e
PMCID: PMC12412323  PMID: 40905762

ABSTRACT

Aim: Moral injury (MI), originally studied in military contexts, refers to emotional distress resulting from actions that conflict with one's core values. MI outcomes may help explain how potentially morally injurious events (PMIEs) contribute to mental health issues, yet empirical evidence remains limited. This longitudinal study examined whether MI outcomes mediate the relationship between PMIE exposure during combat and posttraumatic stress symptom (PTSS) clusters following discharge.

Method: We followed 374 male combat veterans over a five-year period. Pre-enlistment psychological characteristics were conducted 12 months prior to enlistment (T1). PMIE exposure was measured during the final month of military service (T2) using the Moral Injury Events Scale (MIES), capturing experiences throughout active duty. MI outcomes were assessed six months post-discharge (T3) using the Expressions of Moral Injury Scale–Military Version–Short Form (EMIS-M-SF). Finally, PTSS clusters were evaluated one year after discharge (T4) using the PTSD Checklist for DSM-5 (PCL-5).

Results: A total of 48.7% of participants reported exposure to PMIEs, while 8% met criteria for probable PTSD. Path analysis demonstrated a direct effect of PMIE-betrayal (T2) on arousal and reactivity as well as negative alterations in cognition and mood symptom clusters (T4). Results also showed indirect associations between exposure to all PMIE dimensions (T2) and PTSS clusters (T4) via MI outcomes (T3).

Conclusions: Findings underscore the role of MI outcomes in the development of specific PTSS clusters following PMIE exposure. Integrating MI-informed interventions may enhance treatment for veterans transitioning to civilian life.

KEYWORDS: Moral injury, potentially morally injurious events, posttraumatic stress symptoms, posttraumatic stress symptom clusters, veterans

HIGHLIGHTS

  • A prospective 5-year study explored moral injury events, outcomes, and PTSD among 374 combat veterans.

  • Combat service betrayal experiences directly predicted arousal and reactivity as well as mood-cognition symptom clusters.

  • Moral injury outcomes mediated the link between potentially morally injurious events and PTSD symptom clusters.

1. Introduction

In recent years, there has been an increasing awareness of moral injury (MI) among military combatants and veterans, denoting the enduring distress individuals may experience when they engage in, witness, or fail to prevent actions that violate their fundamental beliefs (Litz et al., 2009). According to the most accepted etiological model of MI (Litz et al., 2009), the combatant experiences acts of transgression in high-stakes situations, compromising his moral beliefs and assumptions about the world and human behaviour. These may lead to various levels of dissonance that eventually, in severe and untreated cases, evolve into emotional distress, including shame, guilt, self-loathing, and loss of trust. This emotional state is often followed by withdrawal, which prevents the combatant from finding a path to reconciliation or self-forgiveness (Litz et al., 2009).

Potentially morally injurious events (PMIEs) are experiences involving acts of commission (e.g. cruelty, violence), omission (e.g. failure to protect others), bearing witness to grave inhumanity or violence, or being a victim of such acts, all violating deeply held moral beliefs and expectations about right and wrong. PMIEs are commonly divided into three facets: (1) events that involve one's own actions (PMIE-self: committing or failing to prevent a transgressive act), (2) other's actions (PMIE-other: witnessing, learning about, or surviving a transgressive act), or (3) perceptions of betrayal from leaders, colleagues, or trusted others (PMIE-betrayal) (Litz et al., 2009, 2022; Nash et al., 2013; Shay, 2014).

According to the conceptual model proposed by Litz et al. (2009) exposure to PMIEs during military service can lead to moral dissonance, which, if unresolved, may result in MI outcomes, such as guilt, shame, disgust, and self-blame (Currier et al., 2020; Jinkerson, 2016; Maguen et al., 2024). Several systematic reviews and meta-analyses have found that exposure to PMIEs increases vulnerability to psychiatric conditions, including PTSD and depression symptoms (McEwen et al., 2021; Williamson et al., 2018). Moreover, MI outcomes have been identified as a potential mechanism underlying these adverse mental health outcomes (Litz & Kerig, 2019; McEwen et al., 2021). Specifically, longitudinal studies have indicated that the relationship between combat exposure and PTSD symptom severity is significantly mediated by involvement in wartime atrocities (Dennis et al., 2017). Additionally, MI outcomes have been shown to mediate the effects of PMIEs, such as failure to prevent harm and betrayal, on the emergence of posttraumatic stress symptoms (PTSS) (Battles et al., 2018). In this study, we use the term MI outcomes to refer specifically to the psychological and emotional consequences – such as guilt, shame, and self-blame – that result from exposure to PMIEs. This terminology is intended to distinguish the outcomes of moral injury from the broader and sometimes ambiguous use of ‘moral injury’ in the literature, which can refer to either the event, the experience, or the resulting symptoms.

Although both MI outcomes and posttraumatic stress symptoms (PTSS) may result from exposure to trauma, they reflect distinct constructs. PTSS are primarily fear-based reactions to life-threatening events, including intrusive memories, avoidance, and hyperarousal. In contrast, MI outcomes stem from violations of moral or ethical values and are characterized by guilt, shame, and self-blame following PMIEs. Unlike PTSS, MI outcomes centre on moral conflict and identity disruption rather than threat-based fear (Jinkerson, 2016; Litz et al., 2009).

The relationship between PMIEs, MI outcomes and PTSS clusters (intrusion, avoidance, arousal and reactivity, and negative alterations in mood and cognition) has been explored in various studies, with findings indicating associations between PTSS clusters, particularly the negative alterations in cognition and mood (NACM) cluster, and MI outcomes (Koenig et al., 2020). Furthermore, MI outcomes mediated relationships between PMIEs and the PTSS clusters of avoidance and re-experiencing among combat veterans (Battles et al., 2018). The symptomatic heterogeneity of PTSS suggests that it may be explained by multiple models, as different mechanisms likely underlie its variants (Friedman et al., 2011). Intrusion, avoidance, and arousal and reactivity symptoms are linked to biological changes, whereas NACM symptoms may stem from internal psychological conflict (Koenig et al., 2019). This suggests that PTSD may include subtypes based on trauma type (Graham et al., 2016), highlighting the need to explore the contribution of PMIEs to this heterogeneity. However, the cross-sectional nature of the studies examining these associations (Bhalla et al., 2018; Levi-Belz et al., 2020; Litz et al., 2018; Presseau et al., 2019) constrains their ability to establish causal relationships.

Research on MI has revealed a need for assessment tools that separately measure exposure to PMIEs and individual reactions to them (Currier et al., 2020). This distinction is essential for understanding the relationship between MI and psychiatric outcomes, such as PTSD. Just as trauma exposure alone does not equate to PTSD symptoms, PMIE exposure does not necessarily lead to MI outcomes. A key challenge in MI research is the absence of standardized tools to measure MI outcomes, making it difficult to determine their prevalence (Houle et al., 2024; Steen et al., 2024; Walker et al., 2024). Existing measures often fail to distinguish clearly between exposure to moral stressors and their resulting mental health impacts (Houle et al., 2024; Steen et al., 2024). Event scales, such as the Moral Injury Event Scale (MIES) (Shay, 2014) used in this study, assess exposure to or perceptions of events involving moral transgressions. In contrast, outcome scales like the Expressions of Moral Injury Scale-Military version- Short Form (EMIS-M-SF), utilized in this study, measure key emotional responses, beliefs, attitudes, and behaviours related to moral injury towards oneself and others (Currier et al., 2020). This study was designed following guidelines that emphasize the importance of separating exposure to PMIEs from MI outcomes. Following Litz and colleagues’ (Litz et al., 2009) conceptual model, we aimed to investigate the role of MI outcomes as a mediator in the association between PMIEs and PTSS among recently discharged veterans.

This study is part of a comprehensive study investigating moral injury among Israel Defense Forces (IDF) veterans (Levi-Belz, Levinstein, et al. 2024; Levinstein et al., 2024; Zerach, Levinstein, et al., 2023; Zerach et al., 2024). Our prospective study tracked a cohort of IDF veterans, assessing pre-enlistment screening data one year prior to enlistment (T1). In the final month of the participants' military service, data were collected on participants' PMIEs, combat exposure, and sociodemographic variables (T2). To evaluate the temporal relationships, we assessed MI outcomes six months after discharge (T3) and PTSS one year after discharge (T4). This approach allowed us to achieve a longitudinal perspective on the temporal links between combat veterans' military service experiences and their mental well-being. To our knowledge, no prior studies have examined this subject prospectively.

We posited the following hypotheses:

H1 – PMIEs at T2 will be positively associated with MI outcomes at T3; MI outcomes at T3 will be positively associated with PTSS at T4.

H2 – MI outcomes at T3 will mediate associations between PMIEs at T2 and the NACM PTSS cluster at T4. These associations will be examined while controlling for combat exposure and potentially traumatic life events at T2 and pre-enlistment psychological screening data at T1.

In addition to testing these primary hypotheses, we also conducted an exploratory analysis examining direct and indirect associations between specific PMIE facets at T2 and PTSS clusters at T4.

2. Methods

2.1. Participants

The final sample consisted of 374 male combat soldiers recruited from seven active-duty brigades within the Israel Defense Forces (IDF), encompassing four primary combat roles: infantry, armoured corps, special forces, and combat engineering. In Israel, male conscripts typically serve a mandatory 32-month term. Upon completion, individuals may choose to continue their service in professional military roles. Although the IDF comprises both professional and reserve components, the majority of active combatants are conscripts. Notably, all soldiers, whether they later serve professionally, as reservists, or as officers, begin their military careers as mandatory service members in combat roles. In line with IDF recruitment practices, individuals with severe psychiatric disorders are typically not assigned to combat service, and therefore our sample likely underrepresents such conditions.

It is important to clarify that the data for this study were collected prior to the outbreak of the Israel–Hamas war in 2023. Nevertheless, the experiences of the study population remain highly pertinent, as IDF combatants frequently operate in the West Bank, often engaged in complex missions within civilian contexts involving both Palestinian and Israeli populations (Zerach & Levi-Belz, 2019). These operations range from direct engagements with armed groups to apprehending suspected militants, managing checkpoints, conducting patrols, and performing policing duties (Schwartz et al., 2022).

Inclusion criteria required participants to be male combat soldiers who had completed at least 30 months of mandatory service and were surveyed approximately 3–4 weeks following discharge (T2).

2.2. Measures

Sociodemographic Information: At T2, participants provided sociodemographic and service-related data, including age, marital status, religiosity, education level, and military background (e.g. duration of service, unit affiliation, rank, and role).

Moral Injury Event Scale (MIES) (Nash et al., 2013): At T2, participants completed the 9-item Moral Injury Events Scale (MIES), a self-report instrument designed to assess morally injurious experiences encountered during military service. The MIES includes three subscales reflecting different domains of moral transgression: (1) transgressions committed by oneself (MIES-Self), (2) those committed by others (MIES-Other), and (3) perceived betrayal by military or non-military figures (MIES-Betrayal). Items are rated on a 6-point Likert scale from 1 (strongly disagree) to 6 (strongly agree), with scores calculated separately for each subscale. The MIES has demonstrated strong internal consistency, with Cronbach's alpha values ranging from .82 to .92 across subscales and .88 for the full scale (Steen et al., 2024). The Hebrew version of the scale has shown similar reliability, with previous studies reporting α coefficients between .83 and .90.30 In the present sample, internal consistency was α = .86 for the total MIES score, and for the subscales: α = .81 (Other), α = .86 (Self), and α = .78 (Betrayal).

Combat Experiences Scale (CES) (Hoge et al., 2004): At T2, combat exposure was assessed using the 18-item Combat Experiences Scale (CES), which covers a broad range of modern combat-related events that soldiers may encounter. Participants indicated whether they had experienced each event during their combat service, resulting in a cumulative score between 0 and 18. This scale has been widely utilized in studies involving Israeli veteran populations (Levi-Belz et al., 2020). In the current sample, the CES demonstrated acceptable internal consistency (Cronbach's α = .73).

Expressions of Moral Injury Scale-Military version- Short Form (EMIS-M-SF) (Currier et al., 2020): At T3, moral injury outcomes were assessed using the EMIS-M-SF, a brief 4-item self-report instrument designed to identify potential moral injury in military populations. The scale includes two items assessing self-directed moral injury (e.g. ‘I am ashamed of myself because of things that I did/saw during my military service’) and two items assessing other-directed injury (e.g. ‘The moral failures that I witnessed during my military service have left a bad taste in my mouth’). Responses are rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The EMIS-M-SF has shown strong internal consistency in prior research (α = .90–.94) (Currier et al., 2020). For the present study, the scale was translated into Hebrew using a standard back-translation procedure and reviewed by a panel of subject-matter experts. In our sample, internal reliability was satisfactory (α = .84).

PTSD Checklist for DSM-5 (PCL-5) (Blevins et al., 2015): The PCL-5 is a 20-item self-report instrument used to assess PTSD symptoms over the past month, in alignment with DSM-5 diagnostic criteria. Each item corresponds to a specific symptom cluster and is rated on a 5-point Likert scale ranging from 0 (not at all) to 4 (extremely), producing a total score between 0 and 80. The measure is widely regarded as reliable and valid for evaluating PTSD symptom severity and screening for probable PTSD in both veteran and active-duty military populations. Suggested cut-off scores for probable PTSD range from 31 to 33 (Blevins et al., 2015) Prior studies have reported excellent internal consistency [e.g. α = .94 (Zerach, Ben-Yehuda, et al., 2023); α = .96 (Bovin et al., 2016)], including in Israeli military samples (Dekel et al., 2016). In the current study, the PCL-5 was administered at both T2 and T4, yielding Cronbach's alpha coefficients of α = .93 at each time point.

Patient Health Questionnaire-8 (PHQ-8) (Kroenke et al., 2009). A widely used self-report scale measuring the frequency of core depressive symptoms (e.g. anhedonia, low mood, sleep and appetite disturbances) over the past two weeks. Items are rated on a 4-point Likert scale from 0 (‘not at all’) to 3 (‘nearly every day’), summed to yield a total score (range: 0–24), with higher scores indicating greater depressive severity. In this study, the PHQ-8 total score was analyzed as a continuous variable. Internal consistency was good (Cronbach's α = .86 at follow-up). Depression was not a primary outcome and was not included in the hypothesized mediation model; however, PHQ-8 scores were included in the bivariate correlation matrix to provide additional context on the associations among PMIEs, MIO, and PTSS.

2.3. Control variables

2.3.1. Pre-enlistment screening data

At T1, baseline cognitive and performance-related assessments were collected as part of the IDF's standardized pre-enlistment screening process. These assessments were conducted through a semi-structured interview administered by trained military psychology technicians and are routinely used to evaluate a soldier's potential for successful military service (Gal, 1986; Zerach, Ben-Yehuda, et al., 2023).

Cognitive Index (CI): This score reflects general intellectual ability and is considered a valid proxy for intelligence (Kroenke et al., 2009). Scores follow a normal distribution ranging from 10 to 90, with a mean of 50 and standard increments of 10 points (Gal, 1986).

Performance Prediction Score (PPS): A composite score derived from the interview and weighted components including the CI, suitability for combat roles, educational attainment, and proficiency in Hebrew. PPS values range from 42 to 56, with higher scores indicating greater predicted success and fitness for combat duty (Gal, 1986).

2.3.2. Life events checklist (LEC-5) (Weathers et al., 2014)

At T2, participants' exposure to potentially traumatic life events prior to military service was assessed using the LEC-5, a self-report questionnaire comprising 17 items. These events are associated with the risk of developing PTSD or psychological distress. Respondents indicated whether they personally experienced each event. The LEC-5 was employed in this study for statistical control. The Hebrew version of the scale has demonstrated good reliability (α = .81) in previous research (Zerach & Gordon-Shalev, 2022). In the current sample, Cronbach's alpha was α = .87.

2.4. Procedure

Pre-enlistment personal data were gathered for all participants upon receiving their consent (T1). Subsequent data were collected at three intervals: June 2021 (T2), February 2022 (T3), and July-August 2022 (T4).

Four measurements were collected: T2 was administered during the final month of the participants' active military service (T2). Participant recruitment took place during the first session of a five-day Preparation for Civilian Life seminar, conducted for combat soldiers approaching discharge from military service. Recruitment comprised two phases: (a) the P.I. explained the research and its importance in a group setting without the presence of the unit's officers or other commanders. It was emphasized that participation was voluntary and confidential; (b) a further explanation was given individually while signing the consent form, assuring that consenting or declining to participate would not affect the participant's future reserve military service in any way. For the 959 participants completing the T2 measures, we obtained pre-enlistment personal data (T1) through the Military Induction Center's (MIC) computerized records, which included the CI and PPS.

Data at T2 were collected using hard-copy questionnaires distributed individually by research assistants. T3 and T4 measurements occurred 6 and 12 months after discharge, respectively. Data for T3 and T4 were collected using the Qualtrics survey application (https://www.qualtrics.com). Inclusion criteria at T3 and T4 included all participants who completed a full questionnaire at T2. Participants at T3 and T4 were compensated with a gift card (50 NIS, approximately U.S. $13). Specific measures on all three measurements were monitored so that those yielding scores reflecting probable PTSD were individually and discreetly approached by the P.I., a clinical social worker experienced in PTSD. These individuals were offered personal consultation or referral to optional clinics specializing in PTSD treatment.

The groups in the various measurement waves exhibited variations in their mean pre-enlistment Cognitive Index scores, F(2, 767) = 12.01, p < .001: Participants who completed all three measurements displayed higher Cognitive Index scores (M = 60.18, SD = 15.51) than those who completed only two measurements (M = 55.47, SD = 15.92) or a single measurement (M = 53.86, SD = 16.73). Notably, significant differences in religiosity distinguished between participants who completed all measurements and those who did not, χ2(10) = 35.59, p < .001: Secular participants were more likely to complete all measurements (56.9%) than those completing one (32.8%) or two (38.5%) measurements. In contrast, no significant group differences were observed in CES, F(2, 956) = 0.05, p = .948, PMIE-self, F(2, 921) = 0.22, p = .804, PMIE-other, F(2, 922) = 1.26, p = .285, PMIE-betrayal, F(2, 921) = 2.16, p = .116, or PTSS T1, F(2, 935) = 0.64, p = .529.

All study procedures complied with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. The study was approved by the IDF Medical Corps Institutional Helsinki Committee (approval number 2139-2020) and by the Social and Community Institutional Review Board at Ruppin Academic Center.

2.5. Statistical analysis

First, the prevalence of PMIEs and PTSS was assessed, and associations between the study variables were examined in a series of Pearson correlation analyses. Second, path analysis (Arbuckle, 2009) with a maximum likelihood estimation method in AMOS 27 was used to test the hypothesized mediation model. To assess model fit, we used the following indices: χ2, normed fit index (NFI), comparative fit index (CFI), Tucker–Lewis index (TLI), and root mean square error of approximation (RMSEA). Model fit with NFI, CFI, and TLI equal to or greater than .95; RMSEA equal to or less than .06 indicates adequate fit to the data (Kline, 2015). Whereas the chi-square statistic is expected to be non-significant in the case of adequate fit, this index is generally no longer used to evaluate fit because of its hypersensitivity to sample size Kline (2015). A p-value of less than .05 was considered statistically significant. To examine the significance of the mediation effects, we followed MacKinnon’s (2012) recommendation and calculated 20,000 bootstrap replications to estimate the 95% bias-corrected and accelerated confidence interval (CI) of the indirect effects of PMIEs on PTSS through MI outcomes. When the value zero is not included in the 95% CI, the mediation effect is considered significant at α < .05. Missing data were handled using the full-information maximum likelihood method, a state-of-the-art method for obtaining estimates of the parameters (Schafer & Graham, 2002). This method uses all available data to calculate maximum likelihood parameter estimates with standard errors that are robust to nonnormality.

To calculate power for the indirect effect, we used the Monte Carlo Power Analysis in R (Schoemann et al., 2017). Assuming a moderate effect size (.25 in a correlation metric) between the research variables and α < .05, the current sample yielded a power of .97 for the mediation. Given that a power of .80 is adequate (Cohen, 1992), the current study appears to have enough power to test the hypothesized model.

3. Results

All participants were male, with a mean age of 21.14 years at T2 (SD = 0.80), which corresponded to their discharge from service. On average, they had completed 12.01 years of education (SD = 0.10). The majority were Israeli-born (n = 325, 92.1%) and unmarried (n = 348, 98.3%). In terms of religiosity, 170 participants (45%) identified as secular, 78 (20%) as religiously traditional, 50 (13%) as religiously observant, and 76 (20%) did not report their religious affiliation; therefore, religiosity was included as a covariate in subsequent analyses. Most participants served as infantry soldiers (n = 260, 72.6%), while others were in the armoured corps (n = 68, 19.0%), special forces (n = 29, 7.8%), or combat engineering (n = 1, 0.3%) [Table 1].

Table 1.

Demographic and clinical information of the sample.

  Time N (%) Mean SD Range N
Cognitive Index 1   52.69 2.23 46–56 339
Performance prediction score 1   60.18 15.52 20–90 339
Age 2   21.14 0.81 20–24 358
Religiosity Religious 2 50 (13/4%)        
Religiosity Secular 2 170 (45.5%)        
Religiosity Traditional 2 78 (21%)        
Religiosity Non 2 75 (20%)        
Life events checklist 2   2.68 3.44 0–17 374
Branch of army – infantry 2 260 (69%)        
Branch of army – armoured corps 2 68 (18.2%)        
Branch of army – combat engineering 2 1 (0.3%)        
Branch of army – special forces 2 29 (7.8%)        
Branch of army (missing) 2 16 (4.3%)        
Combat exposure 2   3.47 2.71 0–14 372
PMIE self 2   7.17 4.44 3–24 372
PMIE other 2   5.07 3.01 2–12 372
PMIE Betrayal 2   6.02 3.66 3–18 372
PTSS 2   10.19 13.27 0–68 374
Moral injury outcomes 3   6.36 2.82 4–18 374
Intrusion symptoms 4   2.22 3.24 0–17 374
Avoidance symptoms 4   0.83 1.45 0–8 374
Arousal and reactivity symptoms 4   4.60 4.50 0–19 374
NACM symptoms 4   3.18 4.25 0–21 374
Depression symptoms 4   2.59 3.64 0–22 372
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Note. PMIE, potentially morally injurious event; PTSS, post traumatic stress symptoms; NACM, negative alterations in cognition and mood.

3.1. Prevalence of PMIEs, combat exposure, MI and PTSS

At discharge (T2), nearly half of the participants (48.7%, n = 181) endorsed at least one item on the Moral Injury Events Scale (MIES) at the level of ‘slightly agree’ or higher. Specifically, 23.7% (n = 88) endorsed at least one self-related item (MIES-Self), 41.7% (n = 155) endorsed at least one other-related item (MIES-Other), and 33.9% (n = 126) endorsed at least one betrayal-related item (MIES-Betrayal) [Table 2].

Table 2.

Frequencies of Yes/No answers of the life event checklist among Israeli combat veterans (N = 372).‏

Life event checklist items Frequencies
Yes (%) No (%)
Natural disaster (e.g. flood, hurricane, tornado, earthquake) 10 90
Fire or explosion 29 71
Transportation accident (e.g. car accident, boat accident, train wreck, plane crash) 29 71
Serious accident at work, home, or during recreational activity 23 87
Exposure to toxic substance (e.g. dangerous chemicals, radiation) 10 90
Physical assault (e.g. being attacked, hit, slapped, kicked, beaten up) 34 66
Assault with a weapon (e.g. being shot, stabbed, threatened with a knife, gun, bomb) 12 88
Sexual assault (e.g. rape, attempted rape, made to perform any type of sexual act through force or threat of harm) 8 92
Other unwanted or uncomfortable sexual experience 9 91
Combat or exposure to a war-zone (in the military or as a civilian) 29 71
Captivity (e.g. being kidnapped, abducted, held hostage, prisoner of war) 4 96
Life-threatening illness or injury 7 93
Severe human suffering 7 93
Sudden, violent death (e.g. homicide, suicide) 7 93
Sudden, unexpected death of someone close to you 25 75
Serious injury, harm, or death you caused to someone else 9 91
Other very stressful event or experience 31 69
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Regarding combat exposure, the most frequently reported experience was ‘Shooting or directing fire at the enemy’, endorsed by 57% of participants, followed by ‘Clearing or searching homes or buildings’ (53%). Other commonly endorsed experiences included ‘Being attacked or ambushed’ (35%), as shown in Table 3.

Table 3.

Frequencies of Yes/No answers of the combat exposure scale among Israeli combat veterans (N = 372).

Combat exposure scale items Frequencies
Yes (%) No (%)
Being attacked or ambushed 35 65
Receiving incoming artillery, rocket, or mortar fire 37 63
Being shot at or receiving small-arms fire 13 87
Shooting or directing fire at the enemy 57 43
Being responsible for the death of an enemy combatant 3 97
Being responsible for the death of a non-combatant 2 98
Seeing dead bodies or human remains 20 80
Handling or uncovering human remains 8 92
Seeing dead or seriously injured IDF soldiers 8 92
Knowing someone seriously injured or killed 29 71
Participating in demining operations 7 93
Seeing ill or injured women or children whom you were unable to help 14 86
Being wounded or injured 16 84
Had a close call, was shot or hit, but protective gear saved you 5 95
Had a buddy shot or hit who was near you 10 90
Clearing or searching homes or buildings 53 47
Engaging in hand-to-hand combat 11 89
Saved the life of a soldier or civilian 17 83
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At T4, 29 participants (7.8%) scored 31 or higher on the PTSD Checklist for DSM-5 (PCL-5), indicating probable PTSD based on the established clinical cut-off (Blevins et al., 2015).

3.2. Relationships between the study variables

The means, standard deviations, and correlations between the study variables are presented in Table 4, revealing no significant correlations between pre-enlistment data and any of the study variables. Furthermore, potentially traumatic life events (T2) correlated positively and significantly with PMIE-betrayal (T2) and PTSS (T4). Life events and combat exposure (T2) correlated positively and significantly with PTSS (T4). All PMIE dimensions (self, other, and betrayal) (T2) correlated significantly and positively with PTSS (T4). PMIE-other (T2) correlated significantly and positively with PTSS (T4). MI outcomes (T3) correlated significantly and positively with the three PMIE facets and combat exposure (T2) and PTSS (T4).

Table 4.

Descriptive statistics.

  Time n M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1. Performance prediction score 1 339 52.69 2.23 –                          
2. Cognitive index 1 339 60.18 15.52 .856** –                        
3. Life events 2 374 2.68 3.44 −0.053 −0.070 –                      
4. Combat exposure 2 374 3.47 2.71 0.003 −0.054 .287** –                    
5. PMIE 2 372 18.26 8.81 −0.039 0.028 0.094 .270** –                  
6. PMIE – self 2 372 7.17 4.44 −0.026 0.036 0.038 .213** .874** –                
7. PMIE-other 2 372 5.07 3.01 0.000 0.080 −0.019 .223** .757** .581** –              
8. PMIE-betrayal 2 372 6.02 3.66 −0.062 −0.041 .196** .208** .724** .411** .295** –            
9. MI outcomes 3 364 6.21 3.14 0.028 0.054 .107* .166** .414** .331** .372** .290** –          
10. PTSS 4 374 10.82 11.72 −0.016 −0.018 .122* .283** .293** .228** .220** .247** .396** –        
11. Intrusion 4 374 2.22 3.24 0.038 0.011 .110* .318** .231** .198** .214** .139** .359** .852** –      
12. Avoidance 4 374 0.83 1.45 0.012 −0.009 0.081 .149** .173** .161** .129* .114* .284** .765** .738** –    
13. Arousal and reactivity 4 374 4.60 4.50 −0.041 −0.059 0.097 .278** .262** .190** .176** .257** .299** .902** .658** .578** –  
14. NACM 4 374 3.18 4.25 −0.034 0.007 .122* .194** .296** .223** .214** .266** .409** .895** .642** .597** .733**  
15. Depression symptoms 4 372 2.59 3.64 −0.25 0.43 .150** .164** .300** .183** .199** .339** .374** .583** .417** .359** .556** .581**
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Note: *p < .05 (2-tailed), **p < .01. (2-tailed); PMIE, potentially morally injurious event; PTSS, posttraumatic stress symptoms; NACM, negative Alterations in cognition and mood. Significant correlations are in bold.

3.3. Mediation analysis

To assess the extent to which PMIE at T2 uniquely predicts PTSD symptom clusters at T4 via MI outcomes at T3, we modelled the three PMIE facets (betrayal, other, and self) as predictors of four PTSS clusters (arousal and reactivity, avoidance, intrusion, and NACM), with MI outcomes as the mediator. We also entered measures of combat exposure, negative life events, religiosity (T2), CI, and PPS (T1) into the model as control variables.

Given that the model was saturated, all fit indices were excellent, with χ2(0) = 0, p = 1.0, NFI = 1.0, CFI = 1.0, TLI = 1.0, and RMSEA = .0. The path analysis, summarized in Figure 1 and detailed in Table 5, revealed significant associations between the PMIE facets and MI outcomes, as well as between MI outcomes and the four PTSS clusters.

Figure 1.

Figure 1.

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PMIE facets as predictors of PTSS via MIO: Standardized path analysis coefficients. Note: To maintain a clear visualization of the model, covariances between the predictor variables and between the outcome variables, as well as the effects of the control variables, are not presented (a detailed description can be found in Table 2). Full lines represent significant paths, while broken lines represent non-significant paths. *p < .05; **p < .01; ***p < .001.

Table 5.

PMIE facets at T2 as predictors of PTSS at T4 via moral injury at T3: a path analysis model.

      Beta B S.E. t p
Predictors → Mediator              
PMIE-betrayal T2 → MIO T3 .16 0.14 0.05 2.95 .003
PMIE-other T2 → MIO T3 .23 0.24 0.06 3.79 <.001
PMIE-self T2 → MIO T3 .13 0.09 0.04 2.09 .037
Mediator → Outcomes              
MIO T3 → Arousal symptoms T4 .22 0.31 0.08 4.08 <.001
MIO T3 → Avoidance symptoms T4 .26 0.12 0.03 4.63 <.001
MIO T3 → Intrusion symptoms T4 .31 0.32 0.05 5.88 <.001
Moral injury outcomes T3 → NAMC symptoms T4 .35 0.47 0.07 6.69 <.001
Predictors → Outcomes              
PMIE-betrayal T2 → Arousal symptoms T4 .16 0.20 0.07 2.91 .004
PMIE-betrayal T2 → Avoidance symptoms T4 .01 0.00 0.02 0.12 .903
PMIE-betrayal T2 → Intrusion symptoms T4 −.01 −0.01 0.05 −0.25 .805
PMIE-betrayal T2 → NAMC symptoms T4 .14 0.16 0.06 2.56 .010
PMIE-other T2 → Arousal symptoms T4 −.02 −0.03 0.09 −0.34 .734
PM→IE-other T2 → Avoidance symptoms T4 −.05 −0.02 0.03 −0.69 .491
PMIE-other T2 → Intrusion Symptoms T4 .01 0.01 0.07 0.19 .852
PMIE-other T2 → NAMC symptoms T4 −.02 −0.03 0.09 −0.36 .721
PMIE-self T2 → Arousal symptoms T4 .02 0.02 0.06 0.38 .704
PMIE-self T2 → Avoidance symptoms T4 .08 0.03 0.02 1.29 .198
PMIE-self T2 → Intrusion symptoms T4 .04 0.03 0.04 0.71 .476
PMIE-self T2 → NAMC symptoms T4 .03 0.03 0.06 0.53 .594
Combat exposure T2 → Moral Injury Outcomes T3 .05 0.05 0.06 0.88 .381
Combat exposure T2 → Arousal symptoms T4 .20 0.34 0.09 3.90 <.001
Combat exposure T2 → Avoidance symptoms T4 .08 0.04 0.03 1.43 .154
Combat exposure T2 → Intrusion symptoms T4 .24 0.29 0.06 4.75 <.001
Combat exposure T2 → NAMC symptoms T4 .09 0.15 0.08 1.86 .063
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PMIE-betrayal at T2 was positively associated with MI outcomes at T3 (β = .16, p = .003), which, in turn, was associated with increased arousal and reactivity symptoms (β = .22, p < .001), avoidance symptoms (β = .26, p < .001), intrusion symptoms (β = .31, p < .001), and NACM (β = .35, p < .001) at T3. Tests of mediation were significant, indicating that PMIE-betrayal indirectly predicted arousal and reactivity symptoms (indirect effect = .040; 95% CI = .011, .088), avoidance symptoms (indirect effect = .016; 95% CI = .005, .033), intrusion symptoms (indirect effect = .041; 95% CI = .013, .083), and NACM (indirect effect = .061; 95% CI = .020, .119) at T4. Importantly, PMIE-betrayal also had a positive direct effect on arousal and reactivity symptoms (β = .16, p = .004) and NACM (β = .14, p = .010).

PMIE-self at T2 was positively associated with moral injury at T3 (β = .13, p = .037), which, in turn, was associated with increased arousal and reactivity symptoms, avoidance symptoms, intrusion symptoms, and NACM at T4. Tests of mediation were significant, indicating that PMIE-other at T2 indirectly predicted arousal and reactivity symptoms (indirect effect = .028; 95% CI = .004, .066), avoidance symptoms (indirect effect = .011; 95% CI = .001, .025), intrusion symptoms (indirect effect = .028; 95% CI = .003, .064), and NACM (indirect effect = .042; 95% CI = .003, .092).

PMIE-other at T2 was positively associated with MI outcomes at T3 (β = .23, p < .001), which, in turn, was associated with increased arousal and reactivity symptoms, avoidance symptoms, intrusion symptoms, and NACM at T4. Tests of mediation were significant, indicating that PMIE-other indirectly predicted arousal and reactivity symptoms (indirect effect = .079; 95% CI = .038, .143), avoidance symptoms (indirect effect = .031; 95% CI = .016, .051), intrusion symptoms (indirect effect = .081; 95% CI = .044, .138), and NACM (indirect effect = .120; 95% CI = .071, .196).

Interestingly, we found that combat exposure at T2 was significantly associated with increased arousal and reactivity symptoms (β = .20, p < .001) and intrusion symptoms (β = .24, p < .001) at T4. Sociodemographic control data implied significant differences in the participants' reported religiosity. Participants identifying as religious at T2 displayed significantly fewer intrusion symptoms (β = −.12, p = .030) and fewer NACM (β = −.11, p = .039) at T4 than those defining themselves as secular. Furthermore, individuals defining themselves as traditional at T2 displayed significantly lower MI outcomes at T3 than those defining themselves as secular (β = −.14, p = .013).

4. Discussion

Despite the increasing number of studies on moral injury, there is a scarcity of prospective studies that can clarify the developmental path of MI outcomes. To address this gap, our study aimed to deepen our understanding of PMIEs MI outcomes and its long-term effects on PTSS among recently discharged veterans. Our findings revealed slightly higher rates of PMIE exposure among older combat veterans and active-duty combatants in the IDF (Levi-Belz et al., 2020; Levi-Belz, Ben-Yehuda, et al., 2024). Furthermore, PMIE rates in our sample were significantly higher than those documented among Canadian Armed Forces veterans (Hansen et al., 2021) and US veterans (Nichter et al., 2021). It is important to note, however, that the participants in those studies primarily served in overseas deployment operations, such as Afghanistan and Iraq. In contrast, participants in the present study were active IDF combatants serving in a context of ongoing low-intensity conflict, frequent border operations, and repeated exposure to ambiguous combat environments within or near civilian populations.

The elevated PMIE rates observed in our sample may be attributed, in part, to participants' extended deployments in densely populated urban areas, where they were required to carry out operations in close proximity to civilians. Prior research among IDF veterans has linked engagement in acts of military violence and clashes in urban settings with increased PMIE exposure (Zerach & Levi-Belz, 2022). Ambiguous operational contexts – where distinguishing between combatants and non-combatants is particularly difficult – may increase the risk of moral dissonance and subsequent cognitive conflict (Jinkerson, 2016). Additionally, our data collection was purposefully scheduled at the point of discharge, a period likely to elicit more accurate and vivid recollections of morally injurious experiences. Notably, probable PTSD rates among our cohort were somewhat lower (8%) than those reported in US studies (9.5%–30%) among veterans, depending on exposure severity, era, area, and combat theater (Copeland et al., 2023; Fulton et al., 2015; Kok et al., 2012; Thomas et al., 2010; Wisco et al., 2022). The relatively lower probable PTSD rates of our sample could be explained by our cohort not being engaged in a full-scale war, as they were deployed mostly in peacekeeping missions. Furthermore, protective factors such as religiosity, sence of purpose and motivation of servince should be considerderd as they have been found in previous studies among IDF veterans (Israel-Cohen et al., 2016).

This research yielded numerous findings that related to the primary focus of our study. Our initial hypothesis suggested that encountering PMIEs during military service would predict the occurrence of MI outcomes six months after discharge, subsequently impacting PTSS a year later. The findings confirmed our expectations, aligning with prior cross-sectional studies (e.g. Battles et al., 2018) and consistent with MI models (Jinkerson, 2016; Litz et al., 2009). These results suggest that MI outcome play a developmental or maintenance role in PTSS. Notably, while all three facets of PMIEs supported the model, PMIE-betrayal and PMIE-others manifested stronger associations with MI outcomes and consequent increases in PTSS than PMIE-self. One possible explanation for the stronger association of PMIE-betrayal and PMIE-other with MI outcomes and PTSS, compared to PMIE-self, is that these types of events involve external agents or systems perceived as having violated moral expectations. This external attribution may exacerbate feelings of helplessness and loss of control, psychological responses that are strongly linked to both MI outcomes and PTSS. Furthermore, given that our sample comprised active-duty combatants at the time of PMIE assessment, attributional processes may have influenced the interpretation and salience of these events. Specifically, individuals may be more likely to externalize blame or responsibility during ongoing service, potentially diminishing the perceived impact of self-directed PMIEs. This attributional bias is addressed further in the study's limitations.

Furthermore, while extending our investigation, the study's second hypthesis and exploratory analysis suggested that distinctive mediating associations would be identified between facets of PMIEs and specific PTSS clusters. In this model, combat exposure, as expected, showed no significant association with MI outcomes; however, it did have a direct effect on all PTSS clusters, which is consistent with numerous studies of veterans (Hoge et al., 2004; Levi-Belz et al., 2020). Furthermore, MI outcomes fully mediated the relationships between all three PMIE facets as well as the intrusion and avoidance clusters. The latter findings align with the fact that MI itself implies re-experiencing painful memories and presenting avoidance symptoms (Jinkerson, 2016). Thus, it can be suggested that combatants' experiences of PMIEs and subsequent development of MI outcomes create a unique pathway to PTSS, demanding attention by mental health proffessionals, both during and after military service.

Parallel to the indirect effects through MI outcomes, PMIE-betrayal also demonstrated direct effects on the arousal and reactivity and NACM symptom clusters, suggesting partial mediation. A cross-sectional study of IDF veterans (Levi-Belz et al., 2020) reported significant positive correlations between PMIE-betrayal and the NACM cluster, which may suggest PMIE-betrayals' role as a link between PTSD and moral injury. While the link between betrayal and NACM is readily apparent, the connection to arousal and reactivity, a fear-based physiological symptom, is less evident. Arousal and reactivity symptoms arise from amplified normal stress responses due to hyperattention triggered by the hypothalamic–pituitary–adrenal axis (Jinkerson, 2016).

The current findings could be explained by considering PMIE-betrayal as related to an external factor that intensifies feelings of helplessness and lack of control. This view aligns with Shay’s (1995) speculation that betrayal by commanding authorities undermines the cohesion and effectiveness of military units, as well as the safety and security of combat personnel, thus increasing vulnerability to PTSS. Indeed, betrayal has been linked to feelings of anger and humiliation, emotions thought to have evolved to trigger adaptive behavioural responses, such as aggression and revenge, to threats or transgressions by others (Gilbert, 2019; Shay, 1995). Combatants encounter a multitude of combat stressors while fulfilling their duties and are often engaged in events that encompass both mortal and moral threats, such as those that may lead to both MI outcomes and PTSD (Maguen & Litz, 2012; Solomon, 2020).

Several limitations of this study warrant mention. First, we employed self-report questionnaires, potentially introducing biases, such as estimation bias, particularly in the assessment of PTSS and probable PTSD diagnosis. Second, regarding this study's sensitive subject of moral injury, we must assume an attribution effect (attributing positive events and outcomes to one's own agency but attributing negative events and outcomes to external forces). Third, participant attrition should be acknowledged, particularly the disparity in religiosity between those completing all three measurements and those who did not, perhaps impacting the study's internal validity and the generalizability of the findings. Fourth, military service characteristics were not explicitly examined as potential confounders in relation to other outcomes. Future research should consider these factors. Fourth, while depressive symptoms were not a central focus of this study, we reported their associations with PMIEs, MIO, and PTSS to reflect the substantial overlap among these forms of distress. Future research should systematically examine the distinct and shared pathways linking PMIEs, moral injury outcomes, PTSS, depression, and anxiety to better inform targeted interventions. Lastly, as our study involves an Israeli veteran cohort, we must acknowledge potential cultural and military context disparities with other countries, including variations in types of exposure and the role of the mandatory nature of military service. Thus, caution is advised when generalizing the findings beyond our study. Future research should aim for a more representative sample.

5. Conclusions and implications

In conclusion, we found significantly higher rates of PMIE exposure (48.7%) and lower rates of probable PTSD (8%) among our participants. combat exposure and experiencing PMIEs during military service significantly contributed to the emergence of PTSS during the first year after discharge. Our findings illustrate how these experiences may lead to such outcomes, highlighting two distinct paths through which PMIEs may lead to PTSS among veterans: experiencing acts of transgression and encountering betrayal.

Several important implications can be drawn from the study's findings. First, mental health professionals are encouraged to approach veterans seeking help with the utmost sensitivity and attentiveness to any expressions of MI outcomes. A recent review of cognitive–behavioural psychotherapies for individuals suffering from moral injury noted that contemporary clinical researchers have challenged the adequacy of existing evidence-based treatments for PTSD for addressing moral injury and its associated symptoms (Walker et al., 2024). Our findings illustrate how moral and mortal stressors may be intertwined in their contribution to the complex symptomatic outcomes. Individuals who express feelings of betrayal should be evaluated for tailored, evidence-based interventions such as adaptive disclosure (Litz et al., 2017) or cognitive processing therapy (CPT) (Resick et al., 2016), which address the patient's thoughts, feelings, and beliefs concerning the traumatic events as well as accompanying PTSD symptoms. In cases when experiences of transgression are evident, acceptance and commitment therapy (ACT) can assist individuals grappling with emotions such as shame, humiliation, guilt, and anger following morally injurious events (Hayes et al., 2011).

Funding Statement

This work was supported by the American Foundation for Suicide Prevention (AFSP) [grant number PRG-1-096-19].

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, [YL], upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, [YL], upon reasonable request.

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