Traumatology
The Occupational Moral Injury Scale: Development and Validation in
Frontline Health and First Responder Workers
Victoria Thomas, Boris Bizumic, and Sara Quinn
Online First Publication, October 26, 2023. https://dx.doi.org/10.1037/trm0000482

CITATION
Thomas, V., Bizumic, B., & Quinn, S. (2023, October 26). The Occupational Moral Injury Scale: Development and Validationin Frontline Health and First Responder Workers. Traumatology. Advance online publication.
https://dx.doi.org/10.1037/trm0000482

Traumatology© 2023 American Psychological Association
ISSN: 1085-9373

https://doi.org/10.1037/trm0000482

The Occupational Moral Injury Scale: Development and Validation in
Frontline Health and First Responder Workers
Victoria Thomas, Boris Bizumic, and Sara Quinn

This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

School of Medicine and Psychology, The Australian National University
Moral injury is an emerging construct that has been primarily examined in military groups but is increasingly
expanding to a broader range of nonmilitary occupational settings. A key barrier to this research on moral
injury in broader occupational groups has been the lack of valid and reliable measures speciﬁcally developed
for nonmilitary settings. The current article addresses this gap by developing the Occupational Moral Injury
Scale (OMIS), a measure designed to capture both morally injurious events (MIEs) and primary markers ofmoral injury (guilt, shame, anger, loss of trust, existential conﬂict) in any occupational setting, without theneed for modiﬁcation. A combination of conﬁrmatory factor analyses and item response theory analyses wasused in scale development and reﬁnement. Drawing upon a sample of 1,454 primarily frontline health andﬁrst responder workers across two studies, factor analytic results revealed an expected bifactor structure ofﬁve primary factors capturing exposure to MIEs (commission with agency, commission under duress, act ofomission, witnessing, betrayal) and a general factor of moral injury. Subscales demonstrated excellent internal consistency, and when compared to theoretically relevant constructs OMIS scores demonstrated strong
convergent and divergent validity. Differential validity was also observed among the OMIS subscales. The
OMIS provides a psychometrically validated tool for assessing moral injury risk in any occupational setting.
The OMIS will help facilitate further research and understanding of how moral injury presents in high-risk
occupational settings beyond the military and allow for direct comparison between these groups for the ﬁrst
time.
Keywords: moral injury, psychometrics, frontline health, ﬁrst responders, civilian
Supplemental materials: https://doi.org/10.1037/trm0000482.supp

Moral injury is an emerging construct that originally arose fromresearch into military trauma but is increasingly expanding beyond
this in recent years. Deﬁned as symptoms that result from involvementin either perpetrating or witnessing actions that violate one’s core
beliefs in high stakes situations (Grifﬁn et al., 2019; Litz et al.,2009) or betrayal by a leader or trusted authority (Shay, 2014), moral
injury captures the profound suffering that may be caused by involvement in moral violations.

Conceptual Understanding of Moral Injury
Moral injury frequently overlaps with mental health diagnoses, inparticular major depressive disorder (MDD) and posttraumatic stressdisorder (PTSD). Nevertheless, although there is shared symptomology, it is also distinct from PTSD in both presentation and etiology(Barnes et al., 2019; Bryan et al., 2018; Currier et al., 2019). Unlike
PTSD, moral injury does not typically display an exaggerated startle
reﬂex, memory loss, nightmares, ﬂashbacks, and insomnia (Bryan
et al., 2018). Moral injury instead tends to manifest primarily as
guilt, shame, anger, existential conﬂict, and loss of trust (Jinkerson,
2016; Yeterian et al., 2019), with secondary symptoms often including depression, anxiety, self-harm, suicidal ideation, substance use,and social problems (Currier et al., 2019; Frankfurt & Frazier,
2016; Grifﬁn et al., 2019; Jinkerson, 2016). Although moral injury
is contingent on a precipitating morally injurious event (MIE) in thesame way PTSD development is contingent on exposure toCriterion A trauma, the nature of the event may also differ. The experience of mortal danger is central to the experience of PTSD, with
Criterion A trauma exposure deﬁned within the Diagnostic andStatistical Manual of Mental Disorders (DSM-5 TR; American
Psychiatric Association, 2022) as exposure to actual or threatened
death, serious injury, or sexual violence. MIEs differ in that mortal
danger is not a key precipitating factor. MIEs are instead deﬁned as
situations in which one’s core beliefs of what is right are violated insome way. Speciﬁcally, MIEs can be perpetration events in which
the individual has acted in a way that goes against their values (orfailed to act when they believe it was the right thing to do), situations

Victoria Thomas
https://orcid.org/0000-0002-6038-6641
This work was supported by Mental Health Australia (Grace Groom
Memorial Scholarship).
We would like to express our sincere gratitude to the individuals and organizations that have contributed to this research. We would like to thank ourcolleagues at the Australian National University, Dr. Conal Monaghan and
Dr. Danushika Sivanathan, for their time and generous statistical support.
We would also like to thank Lisa Oxman and Tim Grenfell for their valuable
feedback throughout the research process. We are also grateful to Mental
Health Australia for providing ﬁnancial support for this research in theform of the Grace Groom Memorial Scholarship. Without this support, it
would not have been possible for us to complete this project.
We have no known conﬂict of interest to disclose.
Correspondence concerning this article should be addressed to Victoria
Thomas, School of Medicine and Psychology, The Australian National
University, Building 39 Science Road, Canberra, ACT 2601, Australia.
Email: victoria.thomas@anu.edu.au1

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THOMAS, BIZUMIC AND QUINN

in which the individual witnesses morally violating acts committed byothers, or betrayal events in which the individual is treated in a waythat violates what’s right (typically by a trusted leader or authority).
There is an almost inﬁnite possibility of variations in the speciﬁc circumstances of such situations, according to the context (Held et al.,2021), but the common themes of MIEs remain consistent.

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Moral Injury Beyond the Military
Our understanding of moral injury was borne from military literature, and most research to date has explored it within this context(Grifﬁn et al., 2019). However, an increasingly broad range of occupational settings are experiencing moral injury. The most common occupations are those in which the requirements of the job are frequently atodds with more widely held moral norms, often in high-stakes situations, resulting in more frequent or intense exposure to MIEs and subsequent risk of moral injury (Held et al., 2019; Williamson et al.,2018). Research also suggests that risk is greater when the above conditions are met, along with a lack of psychosocial safety or institutional
support (Simmons-Beauchamp & Sharpe, 2022), which aligns withthe “betrayal” form of MIE. The literature has begun to expand to capture this broadening of the construct, with research exploring moral
injury in a range of high-risk occupations—particularly frontline healthand ﬁrst responder workers, including doctors, nurses, paramedics, andpolice, in addition to other occupations (Williamson et al., 2018).
However, one of the consistent barriers to research on moral injury
in nonmilitary occupations has been the lack of valid, reliable measures
speciﬁcally developed for civilian groups.

Assessment of Civilian Moral Injury
Most extant psychometric measures designed to capture moral
injury (MI) have also been tailored for military groups (Currier etal., 2015, 2018; Koenig et al., 2018; Litz et al., 2022; Nash et al.,2013). The dominant military-speciﬁc measure, the Moral Injury
Events Scale (MIES; Nash et al., 2013) also assesses both MI exposure and symptomology separately, but pools responses into a total
score—not discriminating between exposure to events that may
lead to moral injury, and the symptoms of it. As previously noted,
the conﬂation of exposure events and symptomatic outcomes inthis way has contributed to conceptual confusion in the ﬁeld.
Although some of these military-speciﬁc measures have been
adapted and validated for generalized civilian use (Morriss &Berle, 2023; Thomas et al., 2023), there are limited measures available developed intentionally for civilian settings. More recently,
measures designed for nonmilitary contexts have begun to emerge;
however, this vein of research is in its infancy. Three measuresthat we are aware of have been published—one adaptation of an
existing military measure tailored for health professionals (Mantri
et al., 2020), a measure of MIEs developed for youth populations(Chaplo et al., 2019), and a preliminary measure of moral injury perpetration and betrayal events with a subscale exploring emotionalsequelae, designed for public safety personnel (Roth et al., 2023).
As yet, there are no existing measures that are (a) generalized enoughfor use across different occupational settings, allowing for effective
comparison across groups, and (b) able to link the moral injury symptoms asked about to precipitating MIEs. The measures referenced
above tend to either focus on one occupational group (meaning themeasure is not transferable across other settings; Mantri et al., 2020),

or ask about MIEs or symptoms only, without linking the two ina meaningful way (Chaplo et al., 2019; Roth et al., 2023).
Assessment of MI symptoms without also assessing MI exposure
impairs the ability to tie MI symptoms which are often transdiagnostic to MIEs speciﬁcally, contributing to “concept creep” (N. Haslam,2016) and reducing the utility of the assessment tool. The Moral
Injury Assessment for Public Safety Personnel (Roth et al., 2023)
proposes subscales of “exposure” and “symptoms” of MI, but thishas not yet been subject to conﬁrmatory factor analyses, limiting
empiric conﬁdence in whether it is meaningful to calculate scoreson this measure in this way.
Furthermore, existing civilian measures of MI do not use advanced
techniques such as item response theory (IRT) in their development.
A new measure is required to facilitate the expansion of moral injury
research across occupational settings, address inconsistencies in measurement, and address the frequent conﬂation of MIEs and moral
injury outcomes whilst also limiting “concept creep” of moral injury(N. Haslam, 2016) by ensuring symptoms are linked to a precipitating
MIE.

The Occupational Moral Injury Scale (OMIS)
We are introducing here the OMIS to ﬁll the needs outlined above.
Our aim was to develop a measure that effectively captures the fullrange of the moral injury construct, whilst also remaining generalized enough in its wording to allow it to be used across any occupational setting without ad hoc adaptation. We also aimed to addressconcerns with measures not adequately linking moral injury outcomes to precipitating MIEs, by ensuring each moral injury symptom explored was directly linked to a precipitating MIE type at theitem level. We aimed to do this using advanced techniques in theform of a combination of IRT analysis and conﬁrmatory factor analysis (CFA).
Construction of OMIS items was informed by empirical, clinicaland theoretical sources. An a priori ﬁve-factor model of MIEs waschosen. In specifying this ﬁve-factor structure, we drew upon
research (Chaplo et al., 2019; Nash et al., 2013) and mapped onto
existing deﬁnitions of moral injury. In doing so, we built on the
more common three-factor structure often seen in measures ofMIEs (commission, witnessing and betrayal events) to add greater
nuance around the forms MIEs may take. By adding greater theoretically informed a priori speciﬁcation and clarity to the forms MIEs
may take within the OMIS rather than relying on post hoc interpretation of the factor structure, we aimed to reduce conceptual confusion around the moral injury construct and advance the ﬁeld of
understanding by pinpointing which types of MIEs may (a) be
most relevant to different occupational settings; (b) elicit the most
distress and impairment; and (c) differentially relate to each other,and to moral injury outcomes. The ﬁve MIE factors chosen were:commission with agency, commission under duress, acts of omission, witnessing, and betrayal (see the online supplemental materials
for operational deﬁnitions of each).
Initially delineated by Chaplo et al. (2019), this ﬁve-factor structure breaks down the usual perpetration factor often utilized into two
different but related factors: commission with agency and commission under duress. These different but related factors are distinguished by the intrinsic motivation behind an individual’s moral
violation—either of their own volition without external pressure(commission with agency), or perhaps more commonly, due to an

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OCCUPATIONAL MORAL INJURY SCALE

experience of duress or external pressure to act in a way one believes
to be wrong (commission under duress). The usual witnessing factor
seen in moral injury research is also broken down further, into witnessing and acts of omission—to differentiate between the experience of simply witnessing a moral violation without a sense of
personal culpability, versus witnessing a violation and feeling a
sense of personal culpability through a failure to step up and intervene even if the individual has agency to do so. These two related
but different aspects of moral injury are often referred to in deﬁnitions of the construct, but rarely distinctly speciﬁed within scale construction efforts.
Within each factor, ﬁve primary markers of moral injury were also
explored: guilt, shame, anger, loss of trust, and existential conﬂict(see the online supplemental materials for operational deﬁnitionsof each). These primary markers were informed by clinical expertiseand existing literature (Jinkerson, 2016; Yeterian et al., 2019), andaimed to capture the most pertinent manifestations of moral injury
as an outcome. A range of secondary behavioral outcomes are also
linked to moral injury (Jinkerson, 2016). Nevertheless, given thegreater variability in how these may manifest according to individual
difference and circumstance, we instead chose to focus on the primary markers of moral injury which capture the key emotional
symptoms (guilt, shame, anger) and alterations in beliefs (loss oftrust, existential crisis) that are hallmarks of the condition.
When writing items, it was a priority to ensure each symptom
explored was also linked to a precipitating moral injury event at
the item level. Without symptoms being linked to precipitating
MIEs in this way, there is a risk of “concept creep” (N. Haslam,2016) due to the strong overlap of moral injury with many othermental health conditions such as PTSD, depression, and anxiety(Hall et al., 2022). We anticipated higher levels of interfactor correlation due to this overlap of shared symptomology among factors,
and therefore planned to conﬁrm the a priori factor structure of themodel with a bifactor conﬁrmatory factor analysis (BCFA). A bifactor model hypothesizes a general (G) factor onto which all items
load, and a series of factors orthogonal to the G factor (Reise,2012). In the case of the OMIS, our general factor accounted forthe shared variance of the common moral injury symptoms in theform of a general moral injury factor (G factor), and our orthogonal
factors were speciﬁed by the ﬁve dimensions of different MIEs.

Overview of OMIS Development
The OMIS was developed via two sequential investigations that
followed rigorous scale development guidelines (DeVellis, 2012).
Study 1 focused on the initial construction of the OMIS and wastested on a pool of 744 workers primarily from frontline healthand ﬁrst responder occupations, supported as high risk by the literature. IRT analyses in addition to BCFA were used to identify thesuperior-performing items that should be retained, examine the factor structure of the shortlist and assess individual item performance,
before additional analyses were performed to assess internal consistency, convergent and divergent validity. We hypothesized that the
OMIS would correlate strongly with other theoretically supported
constructs, anticipating positive associations with PTSD symptoms(reexperiencing, avoidance, negative cognition and mood, hyperarousal), MIE exposure (perpetration, witnessing, and betrayal),
burnout, and secondary traumatic stress. We also anticipated signiﬁcant negative correlations with well-being, compassion satisfaction,

and aspects of workplace psychosocial safety including organizationand management commitment, management priority, and organization participation, offering support for divergent validity.

Study 1—Method
Participants and Procedure
The initial sample consisted of 748 frontline health and ﬁrst
responders. Data from four participants were excluded due to requesting to withdraw their data. The ﬁnal sample therefore consisted of 744
participants, who were primarily health and ﬁrst responder occupations. All participants were preselected on Proliﬁc because they indicated they worked in frontline health and ﬁrst responder ﬁelds.
Nonetheless, when completing the survey, a subset of 73 participants
left their occupations unspeciﬁed or stated they did not ﬁt these occupational categories. Primary analyses were run both with and without
these participants included (see the online supplemental materials for
a comparison of results). Given that excluding these participants did
not alter the results in any meaningful way, their data was retained.
A total of 479 participants identiﬁed as women, 260 as men, four
as nonbinary, and one identiﬁed as a transgender man. The mean ageof the sample was 33.48 (SD = 10.61, 18–72). In the sample, 321(43.14%) identiﬁed their country of origin as the United
Kingdom; 180 (24.19%) as the United States; 143 (19.22%) froma range of other European countries; 43 (5.77%) as South Africa;
24 (3.22%) as South American countries; 23 (3.09%) as Canada;
and eight (1.07%) from Australia and New Zealand.
Of the occupations, 199 participants (26.74%) worked in law enforcement (55.77% sworn police, 33.66% unsworn police, 8.54% unspeciﬁed police, 1% prison ofﬁcers); 171 participants (22.98%) were
frontline health workers (62.94% nurses, 32.94% doctors, 2.94% dentists); 90 participants (12.09%) were additional ﬁrst responders separate
from law enforcement (53.33% emergency medical services, 31.11%
paramedics, 15.55% ﬁre and other emergency services); and 114 participants were allied health professionals (15.32%). Additional health professionals who did not fall into any primary category accounted for 64
participants (8.60%), and 33 (4.43%) participants were medical administrative and hospital support staff. A total of 73 participants (9.81%) had
unspeciﬁed or other occupations. Participants’ years of service ranged
from 1 to 44, with an average of 8.59 years.
Participants were recruited via the online recruitment platform
Proliﬁc. Participants were remunerated 6 GBP p/h (£2.30 for an estimated 23-min study). Participants were prescreened/selected as thoseindicating they worked within health and ﬁrst responder ﬁelds, withmore speciﬁc occupational information being sought within the survey. After reading a participant information sheet and providing consent, participants were redirected to the Qualtrics platform where they
completed a battery of measures, comprising the OMIS item pool andadditional related constructs. Participants also answered demographic
questions and were given the option to request their data be deleted
after submission. All ethical aspects of this study were approved by
the relevant human research ethics committee and were in line with
the Helsinki Declaration on Human Research.

Generation of Candidate Items
The initial item pool of the OMIS included 146 candidate items,
developed over a rational, iterative process and informed by theliterature and expert feedback. Each symptom (guilt, shame, anger,

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4

THOMAS, BIZUMIC AND QUINN

loss of trust, existential conﬂict) was also linked to a precipitating MIE(commission with agency, commission under duress, act of omission,
witnessing, betrayal) at the item level. Items were written to be comprehensible at a ﬁfth-grade reading level, according to the Flesch–Kincaid
Grade Level Formula. Items were pilot tested in a small group (18) ofﬁrst responder and frontline health workers, with feedback used to further reﬁne items. This item pool then underwent a rigorous expert-rater
process (DeVellis, 2012). With the assistance of these experts critiquing,suggesting alternate wording, and providing ratings on each item(“excellent”/“good”/“poor”), the item pool was narrowed down to 73
items. Items were retained if all raters selected a “good” or “excellent”
rating, while also paying attention to ensure even coverage of factor
structure and symptom content domains. The ﬁnal pool of 73 items
was then evaluated and further reﬁned within the study, utilizing psychometric data to inform development of the ﬁnal 25-item shortlist.

Measures Used in Construct Validity Analyses
Demographic Questions
Participants were asked to indicate their age, gender, country ofresidence, occupation, years of service, and, if police, whether
they are sworn or unsworn members of their policing organization.

Posttraumatic Stress
The PTSD Checklist for DSM-5 (PCL-5) is a 20-item self-reportmeasure that captures PTSD symptoms experienced during the pastmonth in accordance with DSM-5 criteria (Blevins et al., 2015;
Wortmann et al., 2016). Respondents indicate on a 5-point scaleranging from 0 (not at all) to 4 (extremely) how much they havebeen bothered in the past month by each item. Examples of someof the items are: “feeling very upset when something reminded
you of the stressful experience”; “trouble remembering importantparts of the stressful experience”; and “being superalert or watchfulor on guard.” Cronbach’s alpha of the PCL-5 was .95 in this sample.

communication, and organizational participation (Hall et al., 2010).
Participants indicate how strongly they agree or disagree with howeach item reﬂects the psychological health and safety of their workplace on a 5-point Likert scale (ranging from strongly disagree tostrongly agree). Example items include: “Psychological well-beingof staff is a priority for this organization”; “there is good communication here about psychological safety issues which affect me”; and “inmy workplace senior management acts quickly to correct problems/issues that affect employee’s psychological health.” Cronbach’s
alpha of the PSC-12 was .96 in this sample.

Moral Injury Events Scale (MIES)The MIES (Nash et al., 2013) is a nine-item self-report measure ofpotentially morally injurious events, exploring exposure to perceived transgressions committed by the respondent and/or others,
and perceived betrayals by other military and nonmilitary individuals. Respondents indicate how much they agree with each statement
on a scale ranging from 1 (strongly agree) to 6 (strongly disagree),with higher scores indicating greater moral injury. Examples of
items are: “I am troubled by having witnessed others immoral
acts,” “I violated my own morals by failing to do something I felt
I should have done,” and “I feel betrayed by leaders who I once
trusted.” Cronbach’s alpha of the MIES was .92 in this sample.

Well-being
The Warwick Edinburgh Mental Well-being Scale (WEMWBS;
Tennant et al., 2007) is a 14-item scale designed to capture abroad conception of well-being, including affective–emotional
aspects, cognitive–evaluative dimensions and psychological functioning. Items are scored on a 5-point Likert scale ranging from1 (none of the time) to 5 (all of the time). Examples of some of
the items are: “I’ve been feeling optimistic about the future” and“I’ve been feeling close to other people.” Cronbach’s alpha of the
WEMWBS was .94 in this sample.

Professional Quality of LifeOMIS Initial Item Pool
The Professional Quality of Life Scale (ProQOL-5) is a 30-item
self-report measure of the positive and negative effects of working
in helping professions (Stamm, 2010). It differentiates between compassion satisfaction (the pleasure you derive from being able to doyour work well) and two elements of compassion fatigue: burnout(feelings of hopelessness and difﬁculties in dealing with work or
in doing your job effectively) and secondary traumatic stress(work-related, secondary exposure to stressful events). Participants
rate how frequently they experienced each item on a 5-point Likert
scale (ranging from 1 = never to 5 = very often) in the past 30
days. Example items include: “I am not as productive at work as I
am losing sleep over traumatic experiences of a person I [help]”;“I feel invigorated after working with those I [help]”; and “I feeloverwhelmed because my case [work] load seems endless.”
Cronbach’s alpha of the ProQOL was .83 in this sample.

Psychosocial Safety
The Psychosocial Safety Climate Scale (PSC-12) is a 12-item selfreport measure of the PSC of a workplace, comprising four subscales:
management commitment, management priority, organizational

The pool of 73 test items developed to form a new measure of occupational moral injury were also included in the study. Participants
rated how much they agree with each item on a 7-point Likert-type
scale ranging from 1 (strongly disagree) to 7 (strongly agree).
Examples of some items are: “I feel guilty over things I’ve had to
do at work that I don’t morally agree with,” “Ignoring my consciencein order to do my job has made it hard for me to trust myself,” and“I’m ashamed of the unethical behavior I’ve seen from others in myworkplace.”

Analytic Plan
The initial design of the item pool was undertaken with a bifactor
model in mind, with items including both MIE exposure and an
associated primary marker within the one item. We anticipatedhigher levels of interfactor correlation due to this overlap of shared
symptomology among factors, and therefore intended to run a
BCFA to account for this shared variance in the form of a generalmoral injury factor (G factor), in addition to the ﬁve separate MIE
dimensions (Figure 1).

OCCUPATIONAL MORAL INJURY SCALE

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Figure 1
Five-, Four-, and Three-Factor OMIS Models Compared in Study 1

Note. OMIS = Occupational Moral Injury Scale.

In the case where there is sufﬁcient empirical and theoreticalevidence for an a priori/anticipated factor structure, proceeding
directly to CFA rather than running exploratory factor analysis(EFA) is recommended (Hurley et al., 1997). A recent example
is the new Nationalism Scale (Sheppard et al., 2023), which wasdeveloped based on theory and CFA. This approach produced ascale of nationalism that had better incremental validity thananother widely used measure of nationalism, developed on thebasis of EFA (Kosterman & Feshbach, 1989). Our decision to proceed directly to BCFA was based on the theoretically informed, apriori structure of our model. Our goal was to reduce conceptual
confusion around the moral injury construct and advance theﬁeld of understanding. Speciﬁcally, we intended to pinpoint
which types of MIEs may (a) be most relevant to different occupational settings; (b) elicit the most distress and impairment; and (c)differentially relate to each other and to moral injury outcomes.
Utilizing BCFA in this way rather than relying on post hoc interpretation to establish the factor structure provides a more robust
test of our theory, allowing us to conﬁrm the construct validityof our proposed scale. Although EFA is useful when the structureof the constructs is not well known, it may also capitalize on
chance and characteristics unique to a particular sample, leading
to identiﬁed factors that may not be theoretically meaningful or
replicable.
Therefore, we ran an initial BCFA based on the hypothesized ﬁvefactor structure to assess the item loadings using lavaan package in R
(Rosseel, 2012), using a maximum likelihood estimator robust to nonnormality. Based on initial BCFA results, we chose ﬁve of the bestperforming items for each subscale—one item tapping each of theﬁve primary markers of MI within each subscale, thus ensuring
even content coverage. We then reran factor analyses to compareand conﬁrm the hypothesized factor structure, before running IRT
analyses to assess the item performance of the shortlisted scale. IRT
analyses were run using the R package mirt (Chalmers, 2012),
to determine individual item functioning using a graded responsemodel (GRM) due to polytomous items. Analyses for each subscale
were run separately due to assumption of unidimensionality (Reise& Revicki, 2015). Lastly, correlational analyses were run to assess
construct validity by determining the correlations between the ﬁnal
scale and our external validity constructs. When interpreting correlation coefﬁcients, interpretation guidelines by Dancey and Reidy(2007) were observed (.01–.03 indicating a weak relationship;.04–.06 indicating a moderate relationship; .07–.09 indicating a strong
relationship). Internal consistency was assessed using Cronbach’s
alpha and McDonalds omega. Although Cronbach’s alpha is themore widely reported measure of reliability, it has more restrictive
assumptions. McDonalds omega relies on fewer assumptions and istherefore the more robust measure of reliability. For ease of interpretation, both are reported here.
The general moral injury (G) factor of the BCFA was speciﬁed as
being orthogonal to the MIE factors, as is required in a bifactor
model (Reise, 2012). Fit indices were assessed using the recommended cutoff (Kline, 2016): Comparative Fit Index (CFI) andTucker–Lewis Index (TLI; values close to .95 indicate a good ﬁt
for both CFI and TLI); and root-mean-square error of approximation(RMSEA) with 90% conﬁdence intervals (values of .06 or less indicate a good ﬁt), and standardized root-mean-square residual (SRMR;
values of .08 or less indicate a good ﬁt). The chi-square test statistic
was also reported (a nonsigniﬁcant value indicates good ﬁt to thedata); however, it was interpreted with caution due to large sample
size and sensitivity to nonnormal data (Kline, 2016). We also
reported the χ2/df value, which is robust to sample size (althoughstill sensitive to normality of data). In the case of χ2/df, lower values
indicate a better ﬁt, with values of less than three indicating good ﬁt(Schermelleh-Engel et al., 2003). After assessing model ﬁt, we calculated ancillary bifactor indices of model reliability and dimensionality recommended by Rodriguez et al. (2016) using an Excel tool
developed by Dueber (2017): explained common variance (ECV),
individual ECV, omega (ω), omega hierarchical (ωH), and omega
hierarchical subscale (ωHS).

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THOMAS, BIZUMIC AND QUINN

Study 1—Results

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CFAs
We examined the factor structure of the OMIS shortlist using a
BCFA. Speciﬁcally, we tested differences in model ﬁt between the
hypothesized ﬁve-factor structure and two alternative models: athree- and four-factor bifactor speciﬁcation. In each model, allitems loaded simultaneously on a general MI factor for bifactor speciﬁcation along with MIE group factors (see Figure 1 for a graphicalrepresentation of each model). Alternate models were tested due tothe anticipated higher than usual correlation between certain pairsof associated latent factors (see Table 3). Additional statistical
approaches of regular CFA and hierarchical CFA were also compared for each model (see the online supplemental materials), withthe bifactor approach providing the best ﬁt to the data. Bifactor ﬁtstatistics for each model tested are provided in Table 1.
The ﬁve-factor model displayed superior model ﬁt when compared to the four- and three-factor models. The ﬁve-factor solution
was ultimately retained due to superior ﬁt and the a priori development of items designed with the ﬁve-factor structure in mind.
The ﬁve-factor chi square was signiﬁcant, χ2(241) = 699.30,
p , .001; however, all alternative ﬁt indices (CFI, TLI, SRMR,
and RMSEA) showed that the model ﬁtted the data well, andthe χ2/df value was below three (2.90) indicating good modelﬁt. We used the ﬁve-factor bifactor model to calculate several
diagnostic indices to analyze the dimensionality and reliabilityof the OMIS in more detail (Rodriguez et al., 2016). These indices suggested that the general MI factor explained 37% of thecommon variance overall (ECV = .37; see the online supplemental materials for individual ECV values for each item).
Furthermore, the model-based omega reliability (interpreted
similar to a Cronbach’s α; Rodriguez et al., 2016) was excellent
for the general factor (ω = .97), betrayal (ω = .90), commission
under duress (ω = .94), commission with agency (ω = .94), actof omission (ω = .92) and witnessing (ω = .91). The percent of
reliable total score variance attributable to the general factor(ωH/ω = .72), suggested that 72% of reliable (systematic) variance in the multidimensional OMIS model was explained by
the general factor. Likewise, the ωHS values suggested that thepercent of reliable subscale score variance attributable to the speciﬁc factors was 61% for betrayal, 52% for commission underduress, 56% commission with agency, 60% for act of omission
and 63% witnessing.
The factor loadings for each of the ﬁve MIE factors were higher
than the recommended level of .32 (Tabachnick & Fidell, 2013; see
the online supplemental materials for a full table of standardized factor
loadings for the model). All items also loaded onto the generalized MI

factor, with all but two items (Btr_7 and Wit_7) exceeding this cutoff.
The two items that fell short did so due to loading very strongly on
their own MIE factor, and less strongly on the G factor, and areassessed not to be of concern.

IRT: Shortlisted Model Characteristics
We conducted IRT analyses, with a GRM on each subscale of theshortlisted OMIS model to assess individual item performance. There
were no violations to unidimensionality based on principal component
analyses. While a number of items were locally dependent based on
Yen’s Q3 index . |0.3| (Yen, 1984), this is to be expected in shorter
scales—with Type I error rates occurring signiﬁcantly more in scaleswith 10 items or less (Houts & Edwards, 2013). All items (Figure 2)
and factors (Figure 3) had peaked information curves in the −1 to +2
logit range, indicating that the OMIS provides higher measurement
precision from 1 SD below the mean up to 2.5 SD above averagescores of the latent trait. Full parameter estimates for the GRM ofeach subscale may be viewed in the online supplemental materials.

Descriptive Statistics, Reliability, and Validity
Descriptive statistics for the shortlisted OMIS are presented inTable 2. Mean scores for each factor of the OMIS trended higher
in women over men, and also tended to increase with years of service(see the online supplemental materials for mean scores according togender, each occupational group, and years of service). Total scores
ranged from 5 to 35 for each subscale, with the full range utilized.
Reliability indices for each subscale and the total measure were allin the excellent range.
Correlations among the latent factors were estimated for the ﬁvefactor model and may be seen in Table 3. Correlations among the
OMIS factors ranged from .32 to .85. The weakest correlations
were between the betrayal subscale and other four subscales, suggesting that the betrayal factor is the most distinct of the moral injury
construct. The strongest correlations were observed between related
factors—commission with agency and commission under duress(.85), and witnessing and act of omission (.78), indicating thatthese represent unique but highly associated elements of MI. It
was anticipated that there would be high correlations between
these pairs due to highly related operational deﬁnitions and shared
symptoms; however, the correlation values between these twopairs were still higher than is optimal.
As expected, the overall OMIS scale and its subscales illustrated
signiﬁcant positive correlations with additional measures of MIEs
(capturing witnessing-based, perpetration-based and betrayal-based
events), PTSD symptoms, burnout and secondary traumatic stress(see Table 4). There was a consistent pattern of signiﬁcant negative

Table 1
Bifactor Fit Indices for the Five-, Four- and Three-Factor Models of the OMIS in Study 1
Model

df

χ2

χ2/df

p-Value

RMSEA

95% CI

CFI

TLI

SRMR

AIC

BIC

Five-factor
Four-factor
Three-factor

241
294
297

699.301,444.07
1,682.90

2.90
4.91
5.66

,.001
,.001
,.001

.05
.07
.08

[.046–.055][.069–.073][.076–.083]

.97
.94
.93

.97
.93
.91

.03
.04
.04

60,125.85
65,079.18
65,312.01

60,513.53
65,466.59
65,685.58

Note. OMIS = Occupational Moral Injury Scale; RMSEA = root-mean-square error of approximation; CI = conﬁdence interval; CFI = Comparative Fit
Index; TLI = Tucker–Lewis Index; SRMR = standardized root-mean-square residual; AIC = Akaike information criterion; BIC = Bayesian information
criterion.

OCCUPATIONAL MORAL INJURY SCALE

7This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Figure 2
Item Information Curves for Items Within Each OMIS Factor in Study 1

Note. The graphs are truncated along θ (−3, +3). OMIS = Occupational Moral Injury Scale. See the online article for the color version of this ﬁgure.

correlation of the OMIS with compassion satisfaction, well-being,
and all aspects of psychosocial safety, including management commitment and priority, and organization commitment and participation. The betrayal subscale of the OMIS displayed signiﬁcantly
stronger correlations with burnout and all aspects of psychosocial
safety, compared to any other OMIS subscale (see Table 4 for significance comparisons).

Study 1—Discussion
Results from Study 1 indicate that the factor structure of the shortlisted model performed well. Correlations with external validity criteria

Figure 3
Test Information and SE Curves for Each OMIS Factor in Study 1

Note. The SE is illustrated by the dotted line.

occurred in predicted ways, offering strong convergent and divergent
validity support for the OMIS shortlist. Some interesting differential
relationships between OMIS factors and external criteria were also
noted, particularly with the betrayal factor, which showed a signiﬁcantly stronger negative relationship with compassion satisfaction,
burnout and secondary traumatic stress compared with any other factor.
The commission under duress and commission with agency factors
both showed the strongest relationships with PTSD symptomology,
including reexperiencing, avoidance, negative cognition and mood,and hyperarousal—although these relationships did not tend to be signiﬁcantly stronger than those of the other factors. As mentioned, twolatent factor correlations of the OMIS were higher than optimal,

8

THOMAS, BIZUMIC AND QUINN

Table 2
Descriptive Statistics for the Occupational Moral Injury Scale—Study 1
Study 1

M

SD

Range

Cronbach’s α

McDonald’s ω

Total score
Betrayal
Commission under duress
Commission with agency
Act of omission
Witnessing

3.25
3.41
3.18
2.99
3.28
3.41

1.49
1.64
1.52
1.45
1.58
1.63

1–7
1–7
1–7
1–7
1–7
1–7

.97
.89
.94
.94
.91
.90

.97
.89
.94
.94
.91
.90

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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Note. N = 744.

suggesting further reﬁnement of the OMIS measure in the form of a second study is required. As can be seen in the results, we examined threedifferent models to explore whether collapsing factors provided a better
ﬁt. The three- and four-factor models demonstrated a poorer ﬁt—suggesting that although the latent variables of the OMIS are highly related,
they are still distinct enough to support a ﬁve-factor model. However,given the high nature of these latent intercorrelations, further reﬁnementof the measure is recommended—in particular, adjustments of the operational deﬁnitions and item content to emphasize the conceptual andtheoretical distinctiveness of the ﬁve dimensions and minimize any
unnecessary overlap between these dimensions.

Study 2—Introduction
Correlations between latent factors in Study 1 were much higher
than is optimal. Upon reﬂection, it was noted this may be caused
by a lack of speciﬁcity on the differences between each of theseﬁve related factors. In response, we slightly reconceptualized theﬁve MIE factors. Minor revisions were made to operational deﬁnitions and associated test items to ﬁt this reconceptualization in
response to ﬁndings from Study 1, with the goal of reducing correlational values between latent factors. An independent group of 710
high-risk frontline health and ﬁrst-responder workers then completed this revised shortlist of OMIS items in Study 2, along withassessments of MI symptomology, psychopathology and several
theoretically relevant constructs that were not included in Study
1. The main goal of Study 2 was to assess the effectiveness ofTable 3
Correlations Between the OMIS Latent Factors in Study 1 and Study 2
Latent factor
Study 1OMIS commission
OMIS duress
OMIS omission
OMIS witnessing
Study 2OMIS commission
OMIS duress
OMIS omission
OMIS witnessing

OMIS
betrayal

OMIS
commission

OMIS
duress

.32*
.45*
.38*
.44*

—
.85*
.78*
.69*

—
.71*
.65*

—
.81*

.16**
.15**
.11
.32*

—
.69*
.61*
.47*

—
.70*
.37*

—
.42*

modiﬁcations made in response to Study 1 in reducing latent factor
correlations; utilize BCFA and IRT analyses to cull any remaining
poorer performing items; conﬁrm the factor structure of the ﬁnalizedversion of the OMIS; and assess construct validity and internal consistency of the ﬁnal measure.
We anticipated that the item revisions applied would reduce latent
factor correlations to acceptable levels, while retaining excellent
model ﬁt. We hypothesized that the ﬁnalized OMIS would correlate
positively with external measures of primary symptoms (guilt,
shame, anger, loss of trust, existential conﬂict), in addition to related
psychopathology (depression and PTSD symptoms). In extending
the nomological network of MI, we also anticipated some differential relationships among the factors of the OMIS and associated outcomes of MI, predicting stronger relationships of externallyattributed factors (betrayal and witnessing) with anger, and weaker
relationships with guilt and shame. The inverse was anticipatedwith internally attributed subscales (commission with agency,
under duress, and act of omission)—weaker relationships withanger, and stronger relationships with guilt and shame. To further
extend the nomological network of the MI construct, we also examined some personality traits and their relationship to MI outcomes.
We chose to measure neuroticism, and subclinical levels of thethree dark triad personality traits (Machiavellianism, narcissism,and psychopathy). While little is known regarding the relationshipof these traits with experiences of MI, based on existing literatureand understanding we anticipated a positive relationship of MIwith neuroticism due to known increased vulnerability to PTSD
(Jakšić et al., 2012; Litz et al., 2009; Voecks, 2018), and a negative
relationship with subclinical dark triad personality traits due to the
reduced empathy and indifference to morality often associatedwith these characteristics (Heym et al., 2019; ter Heide, 2020)—
offering support for discriminant validity.

OMIS
omission

Study 2—Method

Note. Study 1 N = 744. Study 2 N = 710. OMIS = Occupational Moral
Injury Scale; commission = commission with agency; duress = commission
under duress; omission = act of omission.
* p , .001. ** p , .05.

Participants and Procedure
Study 2 focused on a second sample of 713 primarily frontline
health, ﬁrst responder and emergency services workers. As in
Study 1, although all participants were preselected on Proliﬁc as
indicating they worked in frontline health and ﬁrst responder ﬁelds,
a subset of 71 participants stated they did not ﬁt the speciﬁed occupational categories when completing the survey. Primary analyses
were run both with and without these participants included (seethe online supplemental materials for a comparison of results).
Given that excluding these participants did not alter the results in

9

OCCUPATIONAL MORAL INJURY SCALE

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Table 4
Correlations Between OMIS Subscales and Validity Criteria Subscales in Study 1
SubscaleOMIS total

OMIS betrayal

OMIS duress

OMIS commission

OMIS omission

OMIS witnessing

OMIS betrayal
OMIS duress
OMIS commission
OMIS omission
OMIS witnessing
MIES total
MIES other
MIES self
MIES betrayal
PCL-5 total
PCL-5 reexperiencing
PCL-5 avoidancePCL-5 negative cog/mood
PCL-5 hyperarousal
ProQOL total
ProQOL compas. satisfact
ProQOL burnout
ProQOL second. traum strs
PSC-12 total
PSC-12 mgmt commitment
PSC-12 mgmt Priority
PSC-12 org commitment
PSC-12 org participation
Well-being

.74*
.91*
.91*
.90*
.88*
.81*
.67*
.73*
.68*
.38*
.35*
.29*
.35*
.35*
.33*
−.28*
.45*
.40*
−.42*
−.41*
−.41*
−.38*
−.35*
−.32*

—
.59*
.52*
.52*
.56*
.56*
.44*
.41*
.61*
.28*
.23*1
.18*
.28*
.27*
.29*
− .37* 2,3,4.53* 5,6,7.36*− .67* 8,9,10− .64* 11,12,13,14− .65* 15,16,17− .63* 18,19,20− .55* 21,22,23,24− .38* 25,26,27

—
.86*
.77*
.72*
.72*
.59*
.69*
.56*
.35*
.33* 1
.27*
.32*
.32*
.29*
−.27*4.40*7.38*−.32*10−.31*14−.31*17−.28*20−.28*24−.27*27

—
.81*
.74*
.73*
.60*
.71*
.56*
.35*
.32*
.28*
.32*
.32*
.28*
−.22*3.35*6−.34*−.26*8−.26*11−.26*15−.23*18−.22*22−.25*26

—
.80*
.73*
.61*
.70*
.57*
.34*
.32*
.25*
.31*
.31*
.26*
−.22*3.35*6.31*−.28*9−.27*12−.28*16−.25*19−.24*23−.25*26

—
.76*
.68*
.65*
.65*
.33*
.31*
.25*
.29*
.29*
.31*
−.14*2.32*5.34*−.28*9−.28*13−.28*16−.25*19−.21*21−.24*25

Note. N = 744. The values in bold represent the largest correlation of a variable with a subscale of the OMIS. OMIS = Occupational Moral
Injury Scale; MIES = Moral Injury Events Scale; PCL-5 = PTSD Checklist for DSM-5; ProQOL = Professional Quality of Life Scale; PSC12 = Psychosocial Safety Climate-12.
Signiﬁcant differences in correlation values between OMIS factors are marked with superscript—p values as follows: 1 = .04; 2 = ,.001;
3 = .002; 4 = .04; 5 = ,.001; 6 = ,.001; 7 = .002; 8 = ,.001; 9 = ,.001; 10 = ,.001; 11 = ,.001; 12 = ,.001; 13 = ,.001;
14 = ,.001; 15 = ,.001; 16 = ,.001; 17 = ,.001; 18 = ,.001; 19 = ,.001; 20 , .001; 21 = ,.001; 22 = ,.001; 23 = ,.001;
24 = ,.001; 25 = .003; 26 = .007; 27 = .02.
* Signiﬁcant at Bonferroni-corrected p , .0003.

any meaningful way, their data was retained. All other recruitment
platform, remuneration and ethical approval details remained thesame as described in Study 1. Data from three participants were
excluded due to requesting to withdraw their data. The ﬁnal sample,
therefore, consisted of 710 participants. A total of 456 identiﬁed as
women, 245 as men, two as nonbinary and three identiﬁed as transgender men, three as transgender women and one preferred not todisclose gender. The mean age of the sample was 36.23 (SD =10.93, range = 18–68). The sample focused primarily on the
United Kingdom and United States, with 563 (79.30%) identifying
their country of citizenship as the United Kingdom and 86 (12.11%)
as the United States. An additional 53 (7.46%) participants held citizenship in a range of different countries. Most participants resided
within the United Kingdom and United States.
Occupational demographics mirrored those seen in Study 1. Of
the occupations, 148 (20.84%) were police (86 sworn, 33 unsworn,
29 unspeciﬁed); 147 (20.70%) frontline health (107 nurses, 40 doctors, 21 other frontline health professionals); 109 (15.35%) wereother ﬁrst responders (17 emergency medical services, 26 paramedics, 16 ﬁre ﬁghters, 24 Emergency 911 dispatchers, 26 other emergency services); and allied health comprised 145 (20.42%).
Additional health professionals who did not fall into any primarycategory made up 44 (6.20%). Medical administrative and hospital
support staff numbered 25 (3.52%). 71 (10.00%) were unspeciﬁed
or other occupations. Years of occupational service ranged from
,1 to 48, with an average of 9.72 years. Participants werepredominantly White (83.52%; 593), followed by Asian (8.16%;58), Black/African (4.36%; 31), multiracial (1.69%; 12), Hispanic(0.98%; seven), and other (0.98%; seven). The majority were of
average socioeconomic status (SES; 60.84%; 432), with 167(23.52%) indicating higher than average SES, 91 (12.81%) lower
than average SES, and 16 (2.25%) much lower than average SES.
The majority of participants were college/university graduates(44.64%; 317), followed by higher degree graduates (24.22%;172), some college/university (17.46%; 124), high school graduates(9.29%; 66), vocational/technical school (3.80%; 27), and grammar/
primary school only (0.42%; three).

Revision of OMIS Items
In response to the higher than optimal correlation values between
latent factors noted in Study 1, operational deﬁnitions of each factor
underwent minor revisions to clarify conceptual distinctiveness, anditems of each factor were also adjusted accordingly. To further contribute to factor distinctiveness, six new items were also drafted to be
included in the ﬁnal item pool (see the online supplemental materials
for full changes made). One ﬁnal question assessing functional
impairment was also included at the conclusion of the scale (“Dothe feelings you indicated above cause you signiﬁcant distress, ormake it hard for you to function in relationships, at work, at home,or other areas of your life important to you?”). This functional
impairment assessment question was adapted from prior researchThis document is copyrighted by the American Psychological Association or one of its allied publishers.
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10

THOMAS, BIZUMIC AND QUINN(Mantri et al., 2020). It was ancillary to the primary OMIS scale anddid not contribute to the overall score, but rather provided supplemental information to assess the level of functional impairment
caused by primary moral injury markers. The inclusion of this functional impairment assessment was in response to recent research suggesting the deﬁning characteristic distinguishing moral distressversus injury is the level of functional impairment caused by thesymptoms (Litz et al., 2022; Litz & Kerig, 2019). It was therefore
important to capture functional impairment in order to distinguishbetween moral injury risk and moral distress. The revised operational deﬁnitions for each factor and ﬁnal pool of 31 items thenunderwent a second expert rater process, utilizing the same method
and expert raters employed within Study 1. In response to feedback,one item with a “poor” rating was deleted, resulting in a ﬁnal shortlistof 30 items which underwent data collection.

Measures
In addition to the 30 items of the revised OMIS shortlist, participants completed a range of additional measures designed to capture
relevant aspects of MI and provide support for convergent and divergent validity.

Demographic Questions
Participants were asked to indicate their age, gender, occupation,
years of service, education level, ethnicity, country of citizenshipand residence, economic situation, and, if police, whether they are
sworn or unsworn members of their policing organization.

(completely disagree) to 5 (completely agree). Cronbach’s alphaof the GTS was .85 in this sample.

Existential Conﬂict
The Meaning in Life Questionnaire (MLQ) is a 10-item self-reportinventory (Steger et al., 2006), which captures subjective presence of
meaning in life and search for meaning in life. Items are rated on a
7-point Likert scale (ranging from 1 = absolutely untrue to 10 =absolutely true). Examples of some of the items are: “My life hasa clear sense of purpose,” “I am searching for meaning in mylife,” and “I am seeking a purpose or mission for my life.”
Cronbach’s alpha of the MLQ was .87 in this sample.

Depression
The Patient Health Questionnaire (Spitzer et al., 1999) is a nineitem measure of depression symptom severity. Participants endorse
items on a 4-point frequency scale (ranging from 0 = not at all to
3 = nearly every day) about their depressive symptoms in the last
14 days. Item responses were summed, with higher scores reﬂecting
greater severity of depression symptoms. Examples of some of theitems are: “little interest or pleasure in doing things,” “trouble falling
asleep or staying asleep, or sleeping too much,” and “feeling down,
depressed or hopeless.” Cronbach’s alpha of the PHQ was .90 in thissample.

Moral Injury

The Dimensions of Anger Reactions Scale 5 (DAR-5; Forbes
et al., 2014) is a ﬁve-item self-report measure that assesses anger
experiences over the prior 4 weeks. Items are rated on a 5-point
Likert scale (ranging from 1 = none or almost none of the time to
5 = all or almost all of the time). Examples of some of the items
include: “When I got angry, I stayed angry,” “I found myself getting
angry at people or situations,” and “When I got angry, I got reallymad.” Cronbach’s alpha of the DAR-5 was .88 in this sample.

The Moral Injury Outcome Scale (MIOS; Litz et al., 2022) is a
14-item measure of military moral injury which captures the shameand trust violation-related outcomes of moral injury. The MIOS comprises two pages—the ﬁrst page entails an assessment of exposure to
three types of MIEs, deﬁned as events that went against the person’s
moral code or values (doing something or failing to do something,observing someone else acting or failing to act, or being directly
impacted by someone else [or people] acting or failing to act).
Following this, DSM-5 PTSD Criterion A trauma exposure and symptoms of PTSD are assessed via the Primary Care PTSD Screener(Prins et al., 2016), which comprises ﬁve items which ask about
DSM-5 PTSD symptomology. The second page of the MIOS comprises a 14-item measure of moral injury outcomes, all indexed to
the MIE that is the participant rated as the worst and most currently
distressing. The time frame for ratings is the last month. At the endof the MIOS, the Brief Inventory of Psychosocial Functioning(Kleiman et al., 2020) is included to assess the functional impact of
the MIOS symptoms endorsed across seven domains (romantic relationships, relationships with children, family relationships, friendships, work, training/education, and day-to-day activities).
Participants are asked to rate the degree they are impacted on a
7-point Likert scale (ranging from 0 = not at all to 6 = extremely).
Cronbach’s alpha of the MIOS was .89 in this sample.

Loss of Trust

Neuroticism

The General Trust Scale (GTS; Yamagishi & Yamagishi, 1994)
measures general level of trust in the form of expectation of trustworthiness of others. It consists of six items, which assess belief about
people’s trustworthiness, such as “Most people are basically honest.” Participants responded using 5-point Likert scale from 1

The Mini International Personal Item Pool (Mini-IPIP; Donnellan
et al., 2006) is a 20-item measure that captures the Big Five personality traits, namely extraversion, neuroticism, agreeableness, openness to experience, and conscientiousness. These items are scoredon a 5-point scale ranging from 1 (strongly agree) to 5 (strongly

Guilt and ShameThe State Guilt and Shame Scale (SGSS-8; Cavalera et al., 2017)is an eight-item measure of state guilt and shame. Participants
endorse items on a 5-point scale (1 = not feeling this way at all to
5 = feeling this way very strongly). Item responses were summed
to create a total score for state guilt and shame. Examples of someof the items are: “I feel like I am a bad person,” “I feel like apologizing, confessing,” and “I want to sink into the ﬂoor and disappear.”
Cronbach’s alpha of the SGSS-8 was .95 in this sample.s

Anger

OCCUPATIONAL MORAL INJURY SCALE

disagree). We used only the ﬁve-item neuroticism scale for the purposes of predictive validity in our study, anticipating that neuroticism would correlate positively with the OMIS. Examples of someof the items are: “I have frequent mood swings,” and “I seldom
feel blue.” Cronbach’s alpha of the Mini-IPIP neuroticism subscale
was .92 in this sample.

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Dark Triad Personality Traits
The Short Dark Triad (SD3; Jones & Paulhus, 2014) is a 27-item
measure which measure three dark personality traits—psychopathy,
Machiavellianism and narcissism. The measure was utilized fordivergent validity purposes as a negative predictor of the OMIS tofurther support construct validity. In the SD3, participants are
asked to rate how much they agree with a series of statements on a
5-point Likert scale (from 1 = strongly disagree to 5 = strongly
agree). Examples of test items include: “It’s not wise to tell yoursecrets,” “people see me as a natural leader,” and “I insist on getting
the respect I deserve.” Cronbach’s alpha of the SD3 was .86 in thissample.

Analytic Plan

11

OMIS model. The factor loadings of all items on both the generalmoral injury factor and each of the ﬁve MIE factors were higher
than the recommended level of .32 (Tabachnick & Fidell, 2013).

IRT: Final Model Characteristics
GRM IRT analyses were run on each factor of the ﬁnalized OMIS
model. There were no violations to unidimensionality based on principal component analysis. While a number of items were locallydependent based on Yen’s Q3 index . |0.3| (Yen, 1984), this is to
be expected in shorter scales—with type I error rates occurring signiﬁcantly more in scales with 10 items or less (Houts & Edwards,
2013). All items (Figure 4) and factors (Figure 5) had peaked information curves in the −2 to +2 logit range, indicating that the ﬁnal
OMIS provides higher measurement precision from 2 SD below
up to 2 SD above average scores of the latent trait. Each factor demonstrated a good range of item difﬁculty, suggesting test items provide information at different levels of the latent trait. Full parameter
estimates for the GRM of each subscale may be viewed in the online
supplemental materials.

Descriptive Statistics, Reliability, and Validity

Analyses from Study 1 were repeated on the new sample andrevised OMIS shortlist. Based on the BCFA results, we eliminated
10 of the poorest-performing items, and arrived at a ﬁnalized
OMIS measure of 20 items. Analyses described below assess thisﬁnalized item pool. We then reran the BCFA to conﬁrm the hypothesized factor structure, and ran IRT analyses to assess individual
item performance of the items within the ﬁnal scale. Reliability,
validity, and internal consistency of the ﬁnal model were also
assessed using analyses described in Study 1.

Study 2—Results
BCFAs
The ﬁve-factor chi square was signiﬁcant, χ2(141) = 421.411,
p , .001; however, all alternative ﬁt indices showed that the model ﬁtted the data well: CFI = .98, TLI = .97, SRMS = .06, RMSEA = .05(95% conﬁdence interval [.047–.059]), Akaike information criterion= 45,263.51, BIC = 45,578.51. The χ2/df value was below 3 (2.99)
indicating good model ﬁt. Importantly, in response to alterations
made in the service of increasing the conceptual distinction between
the dimensions of moral injury, correlations between latent factors
were reduced to acceptable levels (Table 3). Diagnostic indices(Rodriguez et al., 2016) suggested that the general MI factor explained
39% of the common variance overall (ECV = .39; see Table 5 forindividual ECV values for each item). Furthermore, the model-basedomega reliability was excellent for the general factor (ω = .97),
betrayal (ω = .91), commission under duress (ω = .92), commission
with agency (ω = .91), act of omission (ω = .92), and witnessing(ω = .89). The percent of reliable total score variance attributable to
the general factor (ωH/ω = .73), suggested that 73% of reliable (systematic) variance in the multidimensional OMIS model was explainedby the general factor. Likewise, the ωHS values suggested that the percent of reliable subscale score variance attributable to the speciﬁc factors was 55% for betrayal, 46% for commission under duress, 57%
commission with agency, 63% for act of omission, and 63% witnessing. Table 5 shows the standardized factor loadings of the ﬁnalized

Descriptive statistics for the ﬁnal OMIS are presented in Table 6.
As with Study 1, mean scores for each factor of the OMIS trended
higher in women over men (see the online supplemental materials
for mean scores according to gender, each occupational group andyears of service). The full range of possible scores for each subscale
were utilized. Reliability indices for each subscale and the total measure were all in the excellent range.
Correlations among the latent factors were estimated for the ﬁvefactor model and may be seen in Table 3. Correlations among the
OMIS factors were all reduced to acceptable levels and ranged
from .11 to .70. As in Study 1, the weakest correlations were again
between the betrayal subscale and other four subscales, suggestingthat the betrayal factor is the most distinct of the moral injury construct (although it did share a slightly stronger relationship withthe other externally attributed factor, witnessing). The three strongest
correlations were between the internally attributed factors—
commission with agency, commission under duress, and act of omission, suggesting that although these factors are still distinct enoughto support the ﬁve-factor model, they do cluster together. As
expected, the overall scale and its subscales illustrated signiﬁcant
positive correlations with external validity criteria—guilt, shame,anger, depression, and PTSD symptoms (see Table 7 for all comparisons). Existential conﬂict, as measured by meaning in life, showed amore differential relationship—speciﬁcally, presence of meaning
had a negative trend of correlation with all OMIS subscales (thestrongest relationship being with betrayal), whereas search for meaning had a trending positive relationship with all OMIS subscales (thestrongest correlation being with act of omission). The moral injury
outcomes of shame and trust violation as measured by the MIOS
showed some of the strongest correlations with OMIS subscales,
supporting construct validity. The betrayal subscale of the OMIS
displayed the strongest positive correlations with anger, depression
and PTSD symptoms, and the strongest negative correlations witha general sense of trust and presence of meaning. Commission
under duress showed the strongest positive correlations with guilt,
shame, anger, and MIOS shame and trust violation.

12

THOMAS, BIZUMIC AND QUINN

Table 5Results From the Bifactor Conﬁrmatory Factor Analysis Showing Standardized Item Loadings in Study 2
Factor loading
Item label
Factor 1: betrayal
Btr_3
Btr_4
Btr_5

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Factor 2: Commission with agency
Agn_1
Agn_2
Agn_3
Agn_4
Agn_6
Factor 3: commission under duress
Dur_1
Dur_2
Dur_3
Dur_5
Factor 4: act of omission
Omi_1
Omi_2
Omi_3
Omi_4
Factor 5: witnessing
Wit_2
Wit_3
Wit_4
Wit_5

Item content

Gen F1F2F3F4F5 IECVI’m angry because my workplace expects a lot from employees but does
not look after us in return
Experience has shown me that I cannot rely on my workplace to look after me
The way my workplace has failed to look after me makes me question mycareer

.52

.69

.37

.52
.62

.74
.63

.34
.49

I feel guilty for choosing to do things at work that go against my conscience
I’m ashamed of choices I’ve made in my job that go against my beliefs
about right and wrong
I feel anger when I think about things I’ve decided to do at work that
don’t align with my moral values
I question whether I can trust others because of workplace decisions I’ve
made that go against my conscience
Choosing to act against my own moral values in my job has made it hardfor me to ﬁnd meaning in my work

.35
.41

.65
.76

.22
.22

.49

.76

.29

.60

.58

.52

.70

.49

.67

I feel guilty over things I’ve been made to do at work that I don’t morally
agree with
I’m ashamed of myself because of things I’m pressured to do at work thatgo against my conscience
I’m angry because I’ve been forced to do things in the workplace that go
against my beliefs about right and wrong
It’s difﬁcult for me to ﬁnd meaning in the morally questionable things
I’ve been made to do at work

.50

.73

.32

.64

.65

.49

.68

.58

.58

.72

.51

.67

I feel guilty about times I stood back and allowed bad things to continue
happening in my workplace
I’ve let myself down at work by allowing things I knew were not right tocontinue happening
I’m angry that I haven’t chosen to stand up against the things that go
against my beliefs about right and wrong at work
Ignoring my conscience in order to do my job has made it hard for me totrust myself
Even though it’s outside my control, the unethical behavior I’ve seenfrom others in my workplace makes me ashamed
It makes me angry that I cannot stop others from doing things at work thatgo against my values
Being unable to stop people from doing things I don’t morally agree within the workplace has made me less trusting of others
Witnessing unethical behavior at work without being able to change it has
broken the sense of purpose I used to have

.36

.77

.18

.46

.78

.26

.51

.73

.33

.62

.55

.56

.34

.65

.22

.35

.82

.15

.48

.68

.33

.58

.56

.52

Note. N = 710. Gen = general moral injury factor; IECV = individual explained common variance.

Study 2—Discussion
Study 2 provided important information about the factor structure,reliability, and construct validity of the revised and ﬁnalized OMIS.
BCFA results afﬁrmed that the OMIS is best conceptualized as ﬁve
distinct but related MIE factors, with an overarching general moral
injury factor. All items loaded above the minimum threshold on
both their own MIE factor and the general MI factor. Items tapping
guilt and shame were dropped from the betrayal factor entirely, due
to consistent poor loading, suggesting they are not directly relevantto the presentation. Furthermore, correlations among the latent MIE
factors were reduced to acceptable levels due to the amendments
made in response to Study 1. IRT analyses suggested the OMIS measure as a whole captures the MI construct well from 2 SD below to 2
SD above the mean of the latent construct, with a good range of item

information and item difﬁculty within each factor. Cronbach’s
alphas were in the excellent range for each factor, and remaining
analyses supported the construct validity of the instrument.
Speciﬁcally, OMIS scores were positively correlated with guilt,
shame, anger, search for meaning, depression, PTSD symptoms,
and MI-related shame and trust violation symptoms, and negatively
associated with general trust and presence of meaning. No signiﬁcant relationship was observed with narcissism or neuroticism. As
hypothesized, betrayal was more strongly associated with anger,
whereas internally attributed factors were more strongly associatedwith guilt and shame—although differences between the subscalestended not to be signiﬁcant. Contrary to expectations, personality
traits tended to show no signiﬁcant relationship with the OMIS ora relationship opposite to that predicted. Speciﬁcally, neuroticism
and narcissism were not signiﬁcantly associated with any OMISOCCUPATIONAL MORAL INJURY SCALE

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Figure 4
Item Information Curves for Items Within Each OMIS Factor in Study 2

Note. The graphs are truncated along θ (−3, +3). OMIS = Occupational Moral Injury Scale. See the online article for the color version of this ﬁgure.

subscale. Contrary to expectations, Machiavellianism was signiﬁcantly positively correlated with all subscales except for witnessing,and psychopathy was signiﬁcantly correlated with commission
under duress, commission with agency, and acts of omission. We
will discuss the implications of these ﬁndings in the general
discussion.

General Discussion
The moral injury construct captures the profound psychosocial suffering that can arise from the violation of deeply held moral values andbeliefs, beyond which can be captured by related diagnoses such as
PTSD and MDD. It is increasingly recognized that many frontline
health and ﬁrst responder workers are suffering from moral injury,

particularly in the wake of the global COVID-19 pandemic. Lack ofvalid, reliable measurement tools developed for nonmilitary occupations has limited the advancement of knowledge. At present, researchers may utilize one of three measures developed speciﬁcally for civiliangroups (Chaplo et al., 2019; Mantri et al., 2020; Roth et al., 2023);
however, none of these measures are appropriate for use across a
range of diverse occupational settings. They also do not link moral
injury symptomology to precipitating MIEs in a meaningful way,
and do not utilize more advanced scale construction techniques suchas IRT. To our knowledge, this is the ﬁrst attempt to develop and evaluate a measure of occupational moral injury, precise enough to capture
the construct well whilst generalized enough in wording to allow use
across any occupational setting in which moral injury might be a concern, without ad hoc adaptation. Addressing previous measurement

Figure 5
Test Information and SE Curves for Each OMIS Factor in Study 2

Note. The SE is illustrated by the dotted line. OMIS = Occupational Moral Injury Scale.

14

THOMAS, BIZUMIC AND QUINN

Table 6
Descriptive Statistics for the Occupational Moral Injury Scale—Study 2
Study 2

M

SD

Range

Cronbach’s α

McDonald’s ω

Total score
Betrayal
Commission under duress
Commission with agency
Act of omission
Witnessing

4.20
4.81
3.84
3.92
3.91
4.54

1.24
1.67
1.65
1.48
1.60
1.42

1–7
1–7
1–7
1–7
1–7
1–7

.95
.90
.93
.91
.91
.87

.95
.89
.93
.91
.91
.87

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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Note. N = 710.

problems in the ﬁeld, we also unite MIEs and moral injury symptoms
at the item level, limiting “concept creep” (N. Haslam, 2016) and facilitating conﬁdence in construct validity, in addition to utilizing a combination of CFA and IRT statistical approaches. Overall, the results ofthis article suggest the OMIS is a structurally sound, psychometricallyvalid, and reliable instrument for assessing the presentation of moral
injury in occupational settings.

Review of Key Psychometric Findings
BCFA results conﬁrmed that the OMIS is best conceptualized as abifactor model, with a general factor of moral injury, in addition to ﬁve
distinct but related dimensions of MIEs. This was evidenced by excellent model ﬁt, and items loading effectively on their individual MIE
factor as well as the general moral injury factor. The ﬁve-factor MIE
model is consistent with the psychometric properties of most existingmeasures of moral injury (Chaplo et al., 2019; Currier et al., 2018; Litz
et al., 2022; Nash et al., 2013) that ﬁnd unique factors related towhether the individual is the direct perpetrator of a moral transgression(i.e., commission), a witness of a moral transgression, or has experienced a betrayal of what’s morally right by another trusted party.
IRT analyses on OMIS items suggested all items performed well,
capturing a high level of information on the moral injury constructfrom two standard deviations below to two standard deviations above
average. Cronbach’s alpha and McDonald’s omega values of the
OMIS were all within the excellent range, and all remaining analyses
supported the construct validity of the instrument. Speciﬁcally, OMIS
scores in Study 1 were positively correlated with all aspects of PTSD
symptomology, including reexperiencing, avoidance, negative alterations in cognition, mood, and hyperarousal. The OMIS also positively
correlated with an alternate measure of MIEs—self, other, and betrayal
events—and negative aspects of psychosocial safety, including burnout
and secondary traumatic stress. Strong divergent validity was observedin signiﬁcant negative correlations of the OMIS with well-being, compassion satisfaction, and all aspects of psychosocial safety, including
management commitment and priority, as well as organization commitment and participation. Study 2 demonstrated further support for construct validity, with scores of the ﬁnalized OMIS scale showing

Table 7
Correlations Between OMIS Subscales and Validity Criteria Subscales in Study 2
SubscaleOMIS total

OMIS betrayal

OMIS duress

OMIS commission

OMIS omission

OMIS witnessing

OMIS betrayal
OMIS duress
OMIS commission
OMIS omission
OMIS witnessing
SD3 narcissism
SD3 Machiavellianism
SD3 psychopathy
MINI IPIP neuroticism
SSGS-8 guilt
SSGS-8 shame
DAR-5 anger
GTS trust
MILQ presence of meaning
MILQ search for meaning
PHQ-9 depression
MIOS shame
MIOS trust violation
MIOS PTSD

.62*
.88*
.88*
.84*
.76*
−.02
.23*
.16*
.10
.31*
.34*
.31*
−.13
−.15*
.16*
.38*
.45*
.43*
.30*

—
.44*
.40*
.34*
.47*
− .08
.18*
.10
.07
.21*2
.28*
.27*
− .21* 3,4,5− .22* 6,7,8.12.34*.28*10
.37*
.28*

—
.76*
.75*
.53*
.02
.23*
.20*
.09
.32* 1,2
.32*
.27*
−.105
−.118
.14
.33*
.43* 9,10
.38*
.27*

—
.69*
.58*
−.00
.21*
.15*
.05
.28*
.28*
.26*
−.084
−.107
.12
.29*
.41*
.32*
.22*

—
.52*
−.01
.17*
.14*
.10
.27*
.28*
.22*
−.053
−.118
.15*
.31*
.39*
.31*
.24*

—
−.02
.13
.06
.09
.16*1
.22*
.24*
−.12
−.086
.14
.28*
.27*9
.38*
.23*

Note. N = 710. The values in bold represent the largest correlation of a variable with a subscale of the OMIS. OMIS = Occupational
Moral Injury Scale; MINI IPIP = Mini International Personal Item Pool; SSGS-8 = State Shame and Guilt Scale; DAR-5 =Dimensions of Anger Reactions Scale 5; GTS = General Trust Scale; MILQ = Meaning in Life Questionnaire; PHQ = Patient Health
Questionnaire; MIOS = Moral Injury Outcome Scale; PTSD = posttraumatic stress disorder.
Signiﬁcant differences in correlation values between OMIS factors are marked with superscript—p values as follows: 1 = .002; 2 = .03;
3 = .002; 4 = .02; 5 = .03; 6 = .007; 7 = .02; 8 = .03; 9 = .0008; 10 = .002.
* Signiﬁcant at Bonferroni-corrected p , .0005.

OCCUPATIONAL MORAL INJURY SCALE

signiﬁcant positive correlations with measures of guilt, shame, anger,
search for meaning, depression, PTSD symptoms, and moral
injury-related shame and trust violation outcomes. Signiﬁcant negative
relationships were noted with presence of meaning and general trust.

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Contribution to Conceptual Understanding of MI
Building on prior research (Chaplo et al., 2019), the OMIS adds
greater nuance to the factors mentioned above by reﬁning whether the
moral violation was committed of the individual’s own volition (i.e.,commission with agency), or they were coerced or pressured to do so
in some way (i.e., commission under duress). In assessing occupational
moral injury, this is an important difference because much of the sourceof moral distress in occupational acts of commission comes from individuals being obligated to act in a certain way due to institutional constraints
or requirements of their position, even if the action “feels” morally wrong(Held et al., 2019; Williamson et al., 2018). Likewise, differentiating
between whether an individual simply witnesses a moral violation (witnessing) or witnesses a violation with an added sense of personal culpability for failing to step in and intervene in what was observed (act ofomission) is a subtle but important distinction to make. This is particularly true when assessing moral injury in occupational settings where
the shared sense of social identity (Brown, 2000) is likely to increase feelings of personal culpability when witnessing another perpetrate a moral
violation without choosing to or being able to intervene. It is also possiblethat the more meaningful source of moral injury is from the sense of personal culpability in an act of omission, rather than simply witnessing a
violation—but without differentiating the two, research has previously
been unable to pinpoint this. The greater nuance of the OMIS factor
structure will help advance our understanding of the way we deﬁne themoral injury construct in future research.

Differential Relationships and Theoretical
Considerations
Some differential relationships in validity were observed, particularly with the OMIS betrayal factor, which demonstrated a signiﬁcantly stronger negative association with all aspects of psychosocial
safety, compared to any other OMIS factor and the OMIS total
score. Betrayal also demonstrated a signiﬁcantly stronger positive relationship with burnout and a negative relationship with compassion
satisfaction, compared to any other OMIS factor. In Study 2, betrayal
also correlated most strongly with anger, depression, and PTSD symptoms, and had the strongest negative correlation with a general senseof trust and presence of meaning. Conceptually, the betrayal aspect ofmoral injury and negative psychosocial safety climate are very similar,
and research suggests that poor psychosocial safety climate may be a
predictor of developing moral injury in occupational settings (GilbertOuimet et al., 2022). Psychometrically, our study supported the distinctiveness of the betrayal factor through its lower correlation withother factors and differential relationship to external variables. The
guilt and shame symptoms of moral injury also did not load asstrongly with the betrayal factor, which instead showed a strengthened
relationship with anger, loss of trust and existential conﬂict. The consistent poor loading of the guilt and shame-related OMIS items on the
betrayal factor led to the dropping of these items entirely in Study 2, as
results twice suggested the items did not ﬁt well with the factor.
Given the pertinence of the betrayal factor to occupational settings, where much moral injury is precipitated by poor treatment

15

and support from the organization in the context of high-stakes
work (McKendy & Ricciardelli, 2022; Simmons-Beauchamp &Sharpe, 2022), and where betrayal may manifest operationally as
poor psychosocial safety climate, this is an important avenue for
future exploration. A strong shared social identity is a powerful protective factor for a range of psychosocial health outcomes (Ellemers
et al., 2013; C. Haslam et al., 2018). When this breaks down due toperceived institutional betrayal, it may leave the individual without
the psychosocial safety climate buffer to protect from moral
injury—meaning they are more vulnerable to long-term sufferingand impairment caused by perpetration or witnessing-based MIEs
(Dollard et al., 2012; Hall et al., 2013; Law et al., 2011). Future studies may wish to explore whether institutional betrayal plays a mediating or moderating role between exposure to commission andwitnessing-based MIEs and the development of moral injury as an
outcome.
As predicted, commission with agency, commission under duress
and act of omission tended to correlate most strongly with measuresof guilt and shame in Study 2, suggesting these symptoms are most
relevant to internally attributed factors of moral injury. There wasalso a trend for meaning in life to correlate with OMIS subscales
in a differential way—speciﬁcally, presence of meaning was negatively associated with all subscales, whereas search for meaning
was positively associated with all subscales. This suggests thatwhile the experience of moral injury does indeed damage an individual’s sense of life as meaningful and contributes to a sense of existential conﬂict, it may also increase the person’s search for life
meaning—suggesting that while our current sense of meaning isdamaged, we intrinsically attempt to seek out meaning in our lives
to repair from this in an act of posttraumatic growth(Jayawickreme & Blackie, 2014).
Lastly, the personality-related variables that were included as predictors of moral injury tended to show either no signiﬁcant relationship to the construct, or the opposite relationship to what was
anticipated. Neuroticism did show a weak positive relationship toeach factor of the OMIS, and subclinical narcissism also demonstrated
a weak negative relationship, which was consistent with predictions.
However, subclinical levels of Machiavellianism and psychopathy
both demonstrated signiﬁcant positive relationships with MI as measured by the OMIS. While antithesis to our hypothesis, this may beunderstood in the context of policing literature, which suggests thatthose with higher dark triad personality traits do experience higher
instances of moral injury—perhaps due to poorer emotional regulation
within such individuals, and the experience of MIEs being interpreted
as a betrayal of their self-concept and ego (Papazoglou et al., 2019).
Further examination of the role of personality traits in moral injury
experience is beyond the scope of this article, but an important avenue
for future research. We recommend these ﬁndings be further extended
and replicated in other groups to better understand the relationshipbetween Machiavellianism, psychopathy, and MI.

Limitations and Future Directions
There are some limitations within the current study to note. One of
the key limitations is the use of a predominantly White, Western,
educated sample (83.52% white, 84.36% average or above average
SES, 68.87% tertiary educated). Although a range of relevant occupations and balance of gender demographics were captured, thenature of the recruitment platform used meant that participants

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16

THOMAS, BIZUMIC AND QUINN

were primarily White, English-speaking, and educated at a tertiarylevel. This is signiﬁcant because recent research suggests that
moral injury may present differently according to ethnicity and gender, and measures of moral injury likewise may not be appropriate
for use with other ethnicities if developed using primarily White,
Western samples (Morris et al., 2022). Healthcare systems may
also differ between cultures, meaning the OMIS may not be valid
for use with Eastern healthcare workers unless validated for use inthis way. Future research, therefore, should aim to apply measurement invariance analyses to validate the OMIS for use across different ethnic, occupational, and gendered groups.
There were also further limitations. The goal of the OMIS was to create a MI measure generalized enough for use across occupational settings without the requirement for ad hoc adaptation. While weachieved this aim, it is possible that some sensitivity of measurement
may have been lost due to the nonspeciﬁc language used. While thisis a necessary cost to creating a measure that facilitates generalized
use and cross-group comparison in this way, it is also a limitation nonetheless. The study was cross-sectional in nature, without longitudinal
analyses, so no temporal inferences about ﬁndings can be made.
Validity analyses were also correlational in nature, and although thesewere mostly moderate in magnitude, regression analyses may allow
greater predictive utility in the future. The OMIS sample also focusedon speciﬁc high-risk occupations but did not screen out those who
did not meet a minimum threshold of trauma or MIE exposure. Theremay be utility for future studies to prescreen participants with greater
precision to ensure a mostly clinical population is captured rather
than a large proportion who do not report any experience of moral
injury. Doing so may also offer more insight into the rates at which different subtypes of MIEs occur across different occupational settings.
Lastly, we were able to implement a limited number of variables within
the study to allow for evaluation of construct validity. Theoretical models of moral injury (Farnsworth et al., 2017; Jinkerson, 2016; Litz et al.,2009; Shay, 2014) suggest a greater range of variables with potential
relevance to moral injury that may be explored in future studies to further support the construct validity of the OMIS.

Conclusion
The OMIS offers one of the ﬁrst reliable, psychometrically validated tools for capturing the experience of moral injury in occupational settings. One of the strongest contributions of the OMIS is its
ability to be used in any occupational setting, without the necessity
for ad hoc amendment, which is currently seen in most other measuresof MI. Our research suggests the OMIS is both reliable and valid (factorial, convergent, and divergent) instrument, precise enough to capture key aspects of the moral injury construct whilst generalized
enough in wording to allow its use across any occupational setting
without requiring amendment. With consideration of limitations, the
OMIS offers a valuable tool for clinicians and researchers seeking
to explore moral injury presentation in occupational settings outside
the military. The OMIS will help facilitate further research into andgreater understanding of the moral injury construct as a whole.

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Received May 11, 2023
Revision received August 5, 2023
Accepted August 10, 2023 ▪