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Prevalence and correlates of destructive behaviors in the US Naval Surface Forces from 2010–2020



To estimate the prevalence of domestic violence, sexual assault, and suicide for United States Navy (USN) personnel between 2010 and 2020 and identify potential associated factors.


Official report data were used to calculate prevalence rates and odds ratios, accounting for sample and general USN population demographic data to assess differences in over- or underrepresentation of destructive behaviors.


Domestic violence and sexual assault offenders tended to be younger lower-ranked males. For sexual assaults, offenders were three times more likely to be senior to the victim, which was not the case for domestic violence. Females were overrepresented in terms of suicidal ideation and attempts relative to the USN population, while males accounted for more actual suicides. The relative rates of suicidal ideation and attempts for females exceeded those for males (i.e., comparing the sample rate against the USN male and female populations), but the sample proportion for completed suicides (compared to the USN population) were greater for males than for females. Those in the junior enlisted (E1–E3) paygrades exhibited greater odds of suicide attempts versus suicidal ideations relative to those in the Petty Officers (E4–E6) paygrades, although E4–E6s completed more suicides.


The descriptive profile of destructive behaviors in a representative sample of USN personnel provides an overview of the possible factors associated with destructive behaviors and includes an exploration of the relational dynamics and nature of the incidents. The results suggest that sexual assault and domestic violence are characterized by unique relational dynamics and that these destructive behaviors should not necessarily be classified together as male-oriented aggressions (i.e., mainly perpetrated by males against female victims). Those in the E1–E3 and E4–E6 paygrades displayed different patterns in suicidal ideation, attempts, and actual suicides. The results highlight individual characteristics to help inform the development of targeted policies, practices, and interventions for military and other hierarchical organizations (e.g., police).

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Destructive behaviors have been broadly defined as conduct that results in or presents imminent danger to the person exhibiting the behavior to others (e.g., co-workers, friends, and family members) or to property [1, 2]. In the commercial sector, destructive behaviors can have negative externalities such as reduced productivity, declines in customer service, and lost profits [3]. In a military context, however, destructive behaviors also have national security implications as they undermine unit cohesion, combat readiness, and ultimately warfighting capabilities [4].

Military personnel face a number of environmental (e.g., austere work settings) and occupational (e.g., combat) stressors that can result in a multitude of negative mental health outcomes, which have increased in frequency over the last two decades [5]. Over the same period of time, the US military has experienced an increase in the incidence rates of destructive behaviors, especially suicide-related behaviors [6], which suggests a relationship between mental health and destructive behaviors [7]. The impact of destructive behaviors extends beyond the individual to the group, potentially undermining military team cohesion [8]. For instance, the prevalence of destructive behaviors has increased in military units that experienced a suicide [9, 10].

Despite a growing interest in destructive behaviors in military populations, there is a dearth of research in this domain, especially in relation to naval personnel. In response, the US Navy (USN) instituted an initiative called the Culture of Excellence, which aims to address destructive behaviors, among other things, “by fostering psychological, physical and emotional toughness; promoting organizational trust and transparency; and ensuring inclusion and connectedness among every sailor, family member and civilian throughout their Navy journey” [11]. A key facet of fostering Culture of Excellence is understanding the general scope and contributing factors driving destructive behaviors. To that end, this research examines destructive behavior data from USN personnel between 2010 and 2020. The goal is to establish prevalence rates and explore possible factors associated with destructive behaviors. These findings will help assess the long-term effects of sustained military operations on an all-volunteer force and help inform the development of prevention/intervention efforts to enhance the health and well-being of servicemembers.

Reported destructive behaviors

Domestic violence

The US Department of Defense (DoD) defines domestic violence as “an offense that involves the use, attempted use, or threatened use of force or violence against a person, or a violation of a lawful order issued for the protection of a: (1) person who is a current or former spouse, (2) person with whom the abuser shares a child in common, or (3) current or former intimate partner with whom the abuser shares or has shared a common domicile” [12]. For civilians, the prevalence rates for those who have experienced some form of domestic violence in their lifetime can reach upwards of 25% for females and 14% for males [13], compared to up to 33% for females and 17% for males in the military [14].

Some risk factors, such as previous violence perpetration and substance abuse, are common to both the general and military populations [15], but there is evidence that military-specific experiences contribute to the higher rates of domestic violence [4]. For instance, combat deployment experiences (e.g., having killed/wounded others) may increase a servicemember’s likelihood to exhibit domestic violence behaviors [14].

The military has a hypermasculine mystique and previous research has focused on male as perpetrators and female as victims, which may present a limited view on otherwise complex relational dynamics [14, 16]. Data availability has also limited previous efforts to understand the prevalence and causes of domestic violence in military populations [17, 18].

Sexual assault

The DoD defines sexual assault as “intentional sexual contact characterized by use of force, threats, intimidation, or abuse of authority or when the victim does not or cannot consent” [19]. In the general population, estimates indicate that 28–33% of females and 12–18% of males experience sexual abuse during their lifetime [20]. Within the US military, depending on the sample, estimates range from 15–49% for females to 2–23% for males [21, 22]. A study with a more recent sample estimated that 6% of female and 0.7% of male US servicemembers have experienced a sexual assault [23]. Although sexual assault is an issue for all servicemembers, there is a greater percentage of cases involving female victims [24]. Some have theorized that this can be due to several factors, including lower sociocultural and organizational power possessed by females, which can be amplified in a military setting given its often hypermasculine leaning [16, 21].

In the context of sexual assault, substance use (i.e., namely alcohol) is often a contributing factor and associated with both offender and victim consumption [25,26,27,28]; for example, one DoD report noted that alcohol was involved in over 50% of sexual assault cases at military academies [29]. Alcohol use is also especially prevalent in military populations due to various factors, including peer pressure, a drinking culture, easy access to alcohol, and operational/environmental stressors that compel use as coping mechanism [30, 31].

Sexual assault among servicemembers and veterans, especially females, can lead to numerous negative outcomes, such as post-traumatic stress disorder [32, 33], poor servicemember retention [34], degraded unit cohesion [35], and degraded combat readiness [36]. Although the DoD has enacted far-reaching policies and practices to reduce sexual assaults, the issues persist for reasons still not fully understood [23, 37]. As such, military-salient research is needed to: (1) identify where problems exist and who is affected by them; (2) characterize the magnitude of those problems; (3) identify factors associated with those problems; and (4) identify military-relevant prevention/intervention strategies [38]. This research seeks to contribute to these topics within the context of a relatively understudied, relative to US Army and Marine Corps frontline personnel, yet at-risk military population: the USN’s Surface Force.

Suicide behaviors

Suicide is a global concern, with approximately one million people in the world taking their own lives per year [39]. In the US, suicide is the tenth leading cause of death in the general population, but the second leading cause of death for those aged 10–34 [40], and the second leading cause in the military [41]. To provide more context, the global suicide rate is 13.3 per 100,000 compared to 17.4 for the general US population, but 21.9 for the US military’s Active Component, 25.7 for the Reserve Component (i.e., Federally-controlled reserves), and 29.1 for the National Guard (i.e., State-controlled reserves) per 100,000 [42]. Furthermore, since 2001, military suicides have occurred at a rate four times greater than combat-related deaths [6].

Suicide-related behaviors are the product of a complex system of interacting causes some of which include demographic characteristics [43, 44]. In 2019, males in the US were three times more likely to die by suicide than females, although females were more likely to exhibit suicidal ideations and attempts. There are a number of possible explanations for such differences. For instance, females may benefit from greater levels of social support compared to males [45]. Males may also be more comfortable with, and have greater access to, weapons [46]. Within the military, studies focused on US Army soldiers found primary demographic risk factors to include being a white male aged 17–19 [47]. Race may also be a contributing factor due to associated cultural and socioeconomic factors that impact resource availability (e.g., access to care) and social support (e.g., via religious affiliations) [44, 46, 47]. For instance, African Americans may more readily engage personal support systems (e.g., attend religious activities) which may act as a protective factor against suicide-related behaviors [47].

Taken together, the large body of suicide research signals a complex interplay among risk and protective factors associated with suicidal behaviors. As with domestic violence and sexual assaults, the DoD has undertaken a number of efforts to stem suicide-related behaviors, yet the problem persists. As such, problems persist at different rates across military groups (e.g., infantrymen vs. medical personnel and Navy vs. Army), it is important to surveil military sub-groups as to better monitor and understand the factors relevant to each group in order to best shape policies, allocate resources and develop support programs [48]. To that end, this paper seeks to provide a deeper understanding of destructive behavior outcomes in naval context by leveraging a unique longitudinal dataset.


Data source

The data for this study were obtained from USN Operational Reports (OPREP-3). These reports are submitted by subordinate units to provide timely awareness to higher-level commands when special destructive behavior related events occur (e.g., a suicide, domestic violence, harassment, an assault, and suicide-related behavior) [49]. These reports contain no personally identifiable information and capture only the basic facts about an incident, which include: incident date/time, reporting command name, brief text synopsis of the incident, offender’s details (e.g., gender, age, paygrade, and race/ethnicity), victim’s details (e.g., gender, age, paygrade, and race/ethnicity), incident type (e.g., legal/illicit substance-related), description of any weapons involved, whether a law enforcement arrest was made, and geographic location. All the available OPREP-3 data from 2010 to 2020 were included in the study. There were no inclusion or exclusion criteria.

Statistical analysis

To assess the sample’s representativeness, the demographics (paygrade, gender, age, and race) reported in the OPREP-3 data were compared to the USN’s annual populations between 2010 and 2020 [50]. Chi-square tests were used to determine the magnitude and statistical significance of differences across key demographic characteristics from the OPREP-3 data as compared to the entire USN’s population demographics for each year.

Racial categories comprised white, black, and other as the cases of non-white, non-black were smaller [48]. Paygrades were categorized as E1–E3 (Junior Enlisted), E4–E6 (Petty Officers), E7–E9 (Chiefs), and Officers. Following the precedent of USN population reporting [50], age groups were categorized as: < 25, 26–30, 31–35, 36–40, and > 41. Values that did not correspond to the above categories were categorized as Other, which also includes missing data. Chi-square tests comparing the OPREP-3 data to the available demographics data only included data in the defined categories (not including Other).

Logistic regression models were used to calculate odds ratios (OR). Specifically, for the suicide data, the categorizations of suicide attempts and ideation allowed for the relationship assessment between servicemembers’ suicide attempts as compared to ideation across the four main demographic categories (i.e., gender, race, age, and paygrade). ORs and 95% confidence intervals were calculated for each of the above dimensions. Data were prepared and analyzed with R 4.1.1 and the dplyr, ggplot2, ggparallel packages [51,52,53,54]


Domestic violence

Table 1 provides an overview of the domestic violence incident data by year. The results show that in general, across the years, the number of female and male offenders reflect the observed proportions in the overall USN. With respect to age, there were more offenders aged 25 and under (48.41%) relative to the Navy’s general population of those aged 25 and under (42.07%), X2(4, N = 4674) = 258.01, p < 0.001. Regarding race, there was a consistently higher proportion of black (46.80%) than white (53.20%) offenders when taking into account the overall demographics, which was reliably different from the expected proportion based on the overall demographic breakdown (21.94% white versus 78.06% black), X2(1, N = 3960) = 1440.17, p < 0.001. Regarding paygrades, more cases were reported for those in the paygrades of E4–E6 than in any other paygrade group, X2(3, N = 3896) = 608.15, p < 0.001. For victims of domestic violence, there was generally a higher rate of being black, female, under age 25, and in the E4–E6 paygrades.

Table 1 Domestic violence: distribution of selected characteristics for the total sample and by demographics across the years

Sexual assaults

Table 2 provides an overview of sexual assault incidents by year. There were significantly more male offenders than females (96.72% of the offenders were male), X2(1, N = 5310) = 800.39, p < 0.001. For age, those aged 25 and under constituted the majority of offenders (58.87%), which was higher in proportion to USN demographics, X2(4, N = 5310) = 518.46, p < 0.001. With respect to race, white sailors constituted the majority of offenders (64.56%), but the proportion was lower than what would be expected for the overall population, X2(1, N = 3533) = 375.96, p < 0.001. Regarding paygrades, most offenders were E1–E3 (33.27%) and E4–E6 (56.18%), X2(3, N = 3156) = 326.14, p < 0.001.

Table 2 Sexual assault: distribution of selected characteristics for the total sample and by demographics across the years

Females represented the majority (85.12%) of the sexual assault victims, significantly higher in proportion to the Navy demographics (18.26%), X2(1, N = 5648) = 16,314.03, p < 0.001. The majority (81.46%) of victims were aged 25 and under, which is also disproportionately high relative to the USN’s overall population, X2(4, N = 5049) = 3309.34, p < 0.001. Between 2010 and 2020, the white and black proportion for victims reflected the Navy demographics except in recent years (after 2016). Sailors in the E1–E3 paygrades constituted the majority (50.74%) of sexual assault victims, which was much higher in proportion to the overall demographics, X2(3, N = 4744) = 2618.12, p < 0.001.

Relational dynamics

Figures 1 and 2 are parallel charts of the non-missing domestic violence and sexual assault incident data in relation to paygrade level. The relationship between the offender and victim was categorized as senior if the offender’s paygrade category was higher than the victim’s (e.g., E4–E6 vs. E1–E3), and as junior if the paygrade category was lower. For domestic violence the majority of offenders and victims were from the same paygrade category (67.36%). Of the remaining cases, 19.06% of cases were senior and 13.58% were junior (X2(1, N = 250) = 7.06, p < 0.01). For offender and victim relations in sexual assault cases, most of the incidents (58.31%) involved sailors in the same paygrade category. However, offenders were three times more likely to be senior to the victim than junior (31.74% versus 9.95% respectively, X2(1, N = 1081) = 295.31, p < 0.001).

Fig. 1
figure 1

Domestics violence parallel plot

Fig. 2
figure 2

Sexual assault parallel plot

Alcohol involvement

Alcohol was associated with 38% of the domestic violence incidents. Of these, more incidents were reported of an offender with alcohol (33.81%) than of the victim with alcohol (25.18%) (X2(1, N = 7377) = 65.19, p < 0.001). Overall, in 21.58% reported incidents, there was alcohol use in both parties. Regarding age, 4% of the offenders using alcohol were 21 or younger while 16% of the victims who used alcohol were 21 or younger.

Regarding alcohol involvement in sexual assault, there were more reports of perpetrators consuming alcohol than of victims consuming alcohol (54.99% vs. 51.48%, X2(1, N = 8848) = 10.81, p = 0.001); the probability that one or the other had used alcohol was 59.92%. Regarding age, 12% of the sexual assault offenders using alcohol were 21 or younger while 27% of the victims who used alcohol were aged 21 or under.

Suicide behaviors

Suicidal ideation

Table 3 provides an overview of the suicide-related incident data by year; of note, the Atlantic Fleet only began capturing suicidal ideation related data comparable to that of the Pacific Fleet’s 2010–2020 data. There was a higher proportion of female suicidal ideations as compared to males, in proportion to the USN population demographics, X2(1, N = 6291) = 305.41, p < 0.001. For age, more servicemembers aged 25 and under displayed suicidal ideation compared to other groups, which constitutes 70.58% of the total reported incidents from 2011 to 2020, X2(4, N = 6247) = 2272.55, p < 0.001. Regarding paygrades, there were significantly higher reported suicidal ideations in the paygrades of E1–E3, X2(3, N = 6175) = 1741.88, p < 0.001. For years 2011–2018 with the Pacific Fleet data, there was no statistically significant difference between white and black sailors in proportion to the overall demographics. However, for years 2019 and 2020 with the merged Pacific Fleet and Atlantic Fleet data, there was a significantly higher proportion of suicidal ideations reported for black sailors.

Table 3 Suicide risk behaviors: distribution of selected characteristics for the total sample and by demographics across the years

Suicide attempts

There were a total of 282 female suicide attempts (33.41%) as compared to 562 attempts for males (66.59%) across all years, which was significantly higher in proportion to the demographics (18.26% and 81.74%), X2(1, N = 844) = 129.29, p < 0.001. With respect to age, there were many more attempted suicides for those aged 25 and under (73.62%), in proportion to the USN’s population demographics (42.07%), X2(4, N = 834) = 359.43, p < 0.001. For each individual year, in general, suicide attempts across white and black sailors were consistent to the population, but when aggregated, there were more suicide attempts among black sailors, X2(1, N = 686) = 13.97, p < 0.001. Regarding rank, once again, suicide attempts occurred more frequently amongst those in the E1–E3 paygrades in proportion to the USN’s demographics, X2(3, N = 837) = 275.43, p < 0.001.


When assessing suicides by year in proportion to the USN’s overall demographics, no statistically significant differences were observed between females and males. However, when aggregated across 2010–2020, there were more male than female suicides, X2(1, N = 178) = 14.36, p < 0.001. Regarding age, there was no evidence of a robust difference in the proportions of reported incidents and the proportions expected from the overall USN population, X2(4, N = 178) = 6.22, p > 0.05. For by year assessments, no statistically significant differences between white and black sailors were observed, but aggregating the data longitudinally resulted in a reliably greater suicide number in white than in black sailors, X2(1, N = 148) = 8.25, p < 0.01. Regarding paygrade, there was no statistically significant difference across paygrades, but when aggregated from 2010 to 2020, there were slightly more suicides in E4–E6 and fewer among Officers, X2(3, N = 178) = 9.40, p < 0.05.

Suicide odds-ratio

Logistic regression models were constructed to determine the relationships between suicidal attempts and suicide ideations based on key demographics (i.e., gender, age, race, and paygrade). Gender was significant at the 0.05 level with an OR of 0.80 (95% CI 0.66–0.98). Males were 20% less likely than females to attempt suicide versus exhibit suicidal ideation. For age, the ORs by age category in reference to the age under 25 group: 26–30 (OR 0.82; 95% CI 0.64–1.05), 31–35 (OR 0.82; 95% CI 0.55–1.20), 36–40 (OR 1; 95% CI 0.58–1.72), and > 41 (OR 1.12; 95% CI 0.54–2.32), and there was no significant difference by age. Regarding race, white sailors exhibited an OR of 0.87 (95% CI 0.69–1.10) to attempt suicide, but it was not significantly different from black sailors. For paygrade, those E4–E6 had an OR of 0.78 (95% CI 0.64–0.94), E7–E9 had an OR of 0.61 (0.33–1.11), and Officers had an OR of 0.70 (95% CI 0.4–1.19). E4–E6 had a significantly lower OR (p < 0.05) as compared to the reference group E1–E3, in terms of attempting suicides versus suicidal ideations.


Consistent with previous research [13], males committed the majority of domestic violence incidents in the USN population understudy. However, the relative proportion in the sample did not differ from the expected relative proportions of males and females in the overall USN population, which supports findings from previous studies of mixed gender military populations [24]. This study’s findings suggest that generically assuming that males are de facto perpetrators should thus not be the modus operandi; instead, a more comprehensive taxonomy of acts of aggression in the military context should be developed to better inform prevention and intervention efforts.

Concerning sexual assaults, males were overwhelmingly reported as being offenders in the majority of incidents. It is noteworthy that the proportion of males and females is quite different in sexual assault incidents compared to domestic violence incidents. As such, these destructive behaviors should not necessarily be classed together as male aggressions. Each behavior likely requires unique research attention in order to better understand them.

Regarding the relational dynamics associated with sexual assaults, the finding that offenders were three times more likely to outrank the victim sheds light on a facet of the social constructs underlying such incidents. This is also in contrast to the relational dynamics in domestic partners, which occurred more in the same ranks. This could be because of the definition of domestic partners as being an intimate partner or adult family member, but it could also shed light into the nature of sexual assaults, such as these aggressions manifesting when there is a difference in power or social position [21]. Indeed, differences in power may explain why younger, junior servicemembers may be at greater risk for sexual assault (in addition to factors such as living on base in close quarters [30]). These results suggest that prevention efforts could be targeted towards specific ranks to offset potential perpetrators, while other prevention efforts could be designed for lower ranks to enhance potential victim awareness. Additional research is needed to tease apart the contributions of these different factors.

Alcohol was often cited in domestic violence reports and its use was frequently associated with the offender and the victim, which conforms to previous substance use research [29, 55]. In particular, underage drinking poses an important problem, especially as seen in the sexual assault and domestic violence cases.

In terms of suicide behaviors, in proportion to the USN population demographics, females were more likely to exhibit suicidal ideation and suicide attempts, which is consistent with previous findings [56]. Various theories account for such gender differences, whether it is because it is more acceptable for females to express a perceived vulnerability or because they are more likely to use a suicide attempt as a means of communicating distress [57]. In terms of actual suicides, males represented the majority of completed suicides, which is also in line with previous research that has found that men are more adept with fatal weapon use [58].

In terms of age, suicidal ideations and attempts were higher for sailors aged 25 and younger, which aligns with previous results of people at a younger age being more at-risk [59]. However, there was no statistically reliable difference in the actual suicides carried out by the age groups in proportion to the Navy demographics. This suggests that military suicide intervention efforts should continue to target young servicemembers.

Regarding race, for the 2011–2018 Pacific Surface Fleet data, suicidal ideations and attempts for white and black sailors were roughly in proportion to USN population demographics (78.06% and 21.94%). For the larger 2019–2020 dataset (Pacific and Atlantic Surface Fleets), there was a significantly greater number of ideations and attempts amongst black sailors. However, for completed suicides, there was a significantly greater number of suicides by white sailors aggregated across the years. The greater number of suicides by white sailors is aligned with previous results, both in military and general population studies, but the high number of ideations and attempts in black sailors in recent years warrants further research to explore the interplay between race and suicidal ideation, suicide attempts, and actual suicides.

Regarding rank and suicide, sailors in the paygrades E1–E3 exhibited more suicidal ideations and attempts relative to other ranks. However, there were significantly more completed suicides in the E4–E6 paygrades than would be expected in the general USN population demographics. As there is little extant research that explores relationship between rank and suicide behaviors, more research in this area is warranted.

In conclusion, this study presents the findings from unique longitudinal destructive behavior dataset from 2010 to 2020. The study provides an overview of the possible factors associated with these behaviors and explores the relational dynamics and nature of the incidents. The results help inform the development of prevention and mitigation efforts. A noteworthy finding is the relationship between paygrade differences and sexual assaulters and victims; although it warrants additional research, this finding suggests a two-pronged intervention strategy whereby prevention efforts should target higher paygrades to offset potential perpetrators and interventions designed to enhance potential victim awareness might be directed at more junior paygrades.

In all, this study leverages a decade’s worth of unique data to document the prevalence rates of maladaptive behaviors in at-risk naval force populations and provides a contextual understanding of the underlying factors. To supplement these quantitative insights, analysis should be conducted on the qualitative nature of such incidents to better illuminate more specific candidate causes of destructive behaviors within military populations. In particular, interviews can uncover the challenges faced by servicemembers across the various ages, gender, race, and ranks, and further inform the development of policies, practices, and targeted interventions.

Strengths and limitations

This study’s strength lies in leveraging a unique longitudinal destructive behavior dataset. The study also compares the incident reporting data to the USN’s overall demographics data for the past decade to identify trends and also help interpret the findings.

The data are focused specifically on the USN’s Surface Force; as such, it does not reflect destructive behavior incidents across the entire USN. Another limitation is that given the nature of the incident reports, the data are subject to incomplete data (e.g., a victim’s information might not be available at the time the report is submitted) and inaccurate or inconsistent data categorization given that multiple people file the reports. Also, OPREP-3 derived data only reflect events that matriculate to a command’s attention; thus, these findings might not fully reflect all events.

There were also many unknown and missing values, due to the complex and sensitive nature of the incidents, thus the actual number of cases could perhaps be underreported. However, these are challenges and limitations faced by most applied research. Despite the limitations, this study provides an overview of incident report data spanning a decade which illuminates domestic violence, sexual assault, and suicide risk destructive behaviors in a unique military population.

Availability of data and materials

Access to the data may be provided by submitting a Freedom of Information Act request via



Department of Defense


Odds ratio


Operational Reports


United States


United States Navy


  1. Centers for Disease Control and Prevention, National Center for Injury Prevention and Control. Costs of intimate partner violence against women in the United States. Atlanta: Centers for Disease Control and Prevention; 2003.

    Book  Google Scholar 

  2. National Institutes of Health, Consensus Development Panel on Destructive Behaviors in Persons with Developmental Disabilities. Treatment of destructive behaviors in persons with developmental disabilities (NIH Publication No. 91–2410). Bethesda: U.S. Department of Health and Human Services; 1989.

    Google Scholar 

  3. Willness C, Steel P, Lee K. A Meta-analysis of the antecedents and consequences of workplace sexual harassment. Pers Psychol. 2007;60(1):127–62.

    Article  Google Scholar 

  4. Castro CA, Kintzle S, Schuyler AC, Lucas CL, Warner CH. Sexual assault in the military. Curr Psychiatry Rep. 2015;17(7):54.

    Article  PubMed  Google Scholar 

  5. Inoue C, Shawler E, Jordan CH, Jackson CA. Veteran and military mental health issues. Treasure Island: StatPearls Publishing; 2021.

    Google Scholar 

  6. Suitt III TH. High suicide rates among United States service members and veterans of the post 9/11 Wars. 2021.

  7. James LM, Strom TQ, Leskela J. Risk-taking behaviors and impulsivity among veterans with and without PTSD and mild TBI. Mil Med. 2014;179:357–63.

    Article  PubMed  Google Scholar 

  8. Kanesarajah J, Waller M, Zheng WY, Dobson AJ. Unit cohesion, traumatic exposure and mental health of military personnel. Occup Med. 2016;66:308–15.

    Article  Google Scholar 

  9. Hom MA, Stanley IH, Gutierrez PM, Joiner TJ. Exploring the association between exposure to suicide and suicide risk among military service members and veterans. J Affect Disord. 2017;207:327–35.

    Article  PubMed  Google Scholar 

  10. Ursano RJ, Kessler RC, Naifeh JA, Mash HH, Fullerton CS, Bliese PD, Zaslavsky AM, Ng TH, Aliaga PA, Wynn GH, Dinh HM. Risk of suicide attempt among soldiers in army units with a history of suicide attempts. JAMA Psychiat. 2017;74:924–31.

    Article  Google Scholar 

  11. MyNavy HR (n.d.) Culture of excellence overview. Retrieved 22 June 2022.

  12. Department of Defense. Domestic abuse involving DoD military and certain affiliated personnel. Dep of Def Instr, 6400.06, Chapter 4. 2007.

  13. Breiding MJ, Smith SG, Basile KC, Walters ML, Chen J, Merrick MT. Prevalence and characteristics of sexual violence stalking, and intimate partner violence victimization- national intimate partner and sexual violence survey. Atlanta: National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2014.

    Book  Google Scholar 

  14. Kwan J, Sparrow K, Facer-Irwin E, Thandi G, Fear NT, MacManus D. Prevalence of intimate partner violence perpetration among military populations: a systematic review and meta-analysis. Aggress Violent Behav. 2020;53(April):101419.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Taft CT, Pless AP, Stalans LJ, Koenen KC, King LA, King DW. Risk factors for partner violence among a national sample of combat veterans. J Consult Clin Psychol. 2005;73(1):151–9.

    Article  PubMed  Google Scholar 

  16. Schaefer HS, Cotting DI, Proctor ES, Ryan DM, Lerner RM. The military hypermasculine mystique: sex, status, and emotional control at the United States Military Academy. Psychol Men Masculinities. 2021;22(4):611.

    Article  Google Scholar 

  17. Trevillion K, Williamson E, Thandi G, Borschmann R, Oram S, Howard LM. A systematic review of mental disorders and perpetration of domestic violence among military populations. Soc Psychiatry Psychiatr Epidemiol. 2015;50(9):1329–46.

    Article  PubMed  Google Scholar 

  18. Williamson E. Domestic abuse and military families: the problem of reintegration and control. Br J Soc Work. 2011;42(7):1371–87.

    Article  Google Scholar 

  19. Department of Defense. Sexual assault prevention and response (SAPR) program procedures (Instruction No. 6495.02). Washington: Department of Defense; 2013.

    Google Scholar 

  20. Hall M, Hall J. The long-term effects of childhood sexual abuse: counselling implications. 2011.

  21. Turchik JA, Wilson SM. Sexual assault in the military: a review of the literature and recommendations for the future. Aggress Violent Behav. 2010;15:267–77.

    Article  Google Scholar 

  22. Defense Manpower Data Center. Workplace and gender relations survey of active duty members. Washington: Department of Defense; 2012.

  23. Acosta JD, Chinman M, Shearer AL. Countering sexual assault and sexual harassment in the US military. Santa Monica: RAND; 2021.

    Google Scholar 

  24. Kimerling R, Gima K, Smith MW, Street A, Frayne S. The Veterans Health Administration and military sexual trauma. Am J Public Health. 2007;97:2160–6.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Abbey A. Alcohol-related sexual assault: a common problem among college students. J Stud Alcohol Suppl. 2002;14:118–28.

    Article  Google Scholar 

  26. Campbell R, Greeson M, Bybee D, Raja S. The co-occurrence of childhood sexual abuse, adult sexual assault, intimate partner violence, and sexual harassment: a mediational model of posttraumatic stress disorder and physical health outcomes. J Consult Clin Psychol. 2008;76(2):194–207.

    Article  PubMed  Google Scholar 

  27. Gidycz CA, Wyatt J, Galbreath NW, Axelrad SH, McCone DR. Sexual assault prevention in the military: key issues and recommendations. Mil Psychol. 2018;30(3):240–51.

    Article  Google Scholar 

  28. Hankin CS, Skinner KM, Sullivan LM, Miller DR, Frayne S, Tripp TJ. Prevalence of depressive and alcohol abuse symptoms among women VA outpatients who report experiencing sexual assault while in the military. J Trauma Stress. 1999;12(4):601–12.

    Article  PubMed  Google Scholar 

  29. Department of Defense. Report of the defense task force on sexual harassment and violence at the military service academies; 2005.

  30. Department of Defense. Task force report on care for victims of sexual assault; 2004.

  31. Schumm JA, Chard KM. Alcohol and stress in the military. Alcohol Res Curr Rev. 2021;34(4):401.

    Google Scholar 

  32. Kang H, Dalager N, Mahan C, Ishii E. The role of sexual assault on the risk of PTSD among Gulf War veterans. Ann Epidemiol. 2005;15(3):191–5.

    Article  PubMed  Google Scholar 

  33. Vogt DS, Pless AP, King LA, King DW. Deployment stressors, gender, and mental health outcomes among Gulf War I veterans. J Trauma Stress. 2005;18(2):115–27.

    Article  PubMed  Google Scholar 

  34. Dichter ME, True G. This is the story of why my military career ended before it should have. Premature separation from military service among U.S. women veterans. Affilia. 2014;30(2):187–99.

    Article  Google Scholar 

  35. Morral AR, Gore KL, Schell TL. Sexual assault and sexual harassment in the US military: volume 3. Estimates for coast guard service members from the 2014 RAND military workplace study. Santa Monica: Rand Corp; 2015.

    Google Scholar 

  36. Sadler AG, Lindsay DR, Hunter ST, Day DV. The impact of leadership on sexual harassment and sexual assault in the military. Mil Psychol. 2018;30(3):252–63.

    Article  Google Scholar 

  37. Wood EJ, Toppelberg N. The persistence of sexual assault within the US military. J Peace Res. 2017;54(5):620–33.

    Article  Google Scholar 

  38. Laurence JH, Matthews MD, editors. The Oxford handbook of military psychology. New York: OUP USA; 2012.

    Google Scholar 

  39. Gvion Y, Apter A. Suicide and suicidal behavior. Public Health Rev. 2012;34:1–20.

    Article  Google Scholar 

  40. Kochanek KD, Xu JQ, Arias E. Mortality in the United States, 2019. NCHS Data Brief, no 395. Hyattsville: National Center for Health Statistics; 2020.

    Google Scholar 

  41. Mann, CT, Fischer H. Trends in active-duty military deaths since 2006. Congressional Research Services; 2021.

  42. DoDSER: Department of Defense Suicide Event Report. Calendar year 2017 annual report. Washington, D.C.: U.S. Department of Defense; 2018.

  43. Black SA, Gallaway MS, Bell MR, Ritchie EC. Prevalence and risk factors associated with suicides of army soldiers 2001–2009. Mil Psychol. 2011;23(4):433–51.

    Article  Google Scholar 

  44. Cohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol Bull. 1985;98(2):310.

    Article  PubMed  Google Scholar 

  45. Cohen S. Social relationships and health. Am Psychol. 2004;59(8):676–668.

    Article  PubMed  Google Scholar 

  46. Kubrin C, Wadsworth T. Explaining suicide among Blacks and Whites: how socioeconomic factors and gun availability affect race-specific suicide rates. Soc Sci Q. 2009;90(5):1203–27.

    Article  Google Scholar 

  47. Griffith J. Suicide in the Army National Guard: an empirical inquiry. Suicide Life Threat J. 2011;42(1):104–19.

    Article  Google Scholar 

  48. Russell DW, Cohen GH, Gifford R, Fullerton CS, Ursano RJ, Galea S. Mental health among a nationally representative sample of United States Military Reserve Component Personnel. Soc Psychiatry Psychiatr Epidemiol. 2015;50(4):639–51.

    Article  PubMed  Google Scholar 

  49. Department of Navy. Special incident report. OPNAVINST 3100.6K. 2021.

  50. US Department of Defense. 2020.

  51. R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2021.

  52. Wickham H, François R, Henry L, Müller K. dplyr: a grammar of data manipulation. R package version 1.0.7. 2021.

  53. Wickham H. ggplot2: Elegant graphics for data analysis. New York: Springer; 2016.

    Book  Google Scholar 

  54. Hofmann H, Vendettuoli M. Common angle plots as perception-true visualizations of categorical associations. IEEE Trans Visual Comput Graph. 2013;19(12):2297–305.

    Article  Google Scholar 

  55. Foran HM, Heyman RE, Slep AMS, Snarr JD, United States Air Force Family Advocacy Research Program. Hazardous alcohol use and intimate partner violence in the military: understanding protective factors. Psychol of Addict Behav. 2012;26(3):471–83.

    Article  Google Scholar 

  56. Crosby AE, Han B, Ortega LAG, Parks SE, Gfroerer J. Suicidal thoughts and behaviors among adults aged ≥18 years: United States, 2008–2009. Morb Mortal Wkly Rep: MMWR. 2011;60(SS13):1–22.

    Google Scholar 

  57. Sudhir Kumar CT, Mohan R, Ranjith G, Chandrasekaran R. Gender differences in medically serious suicide attempts: a study from south India. Psychiatry Res. 2006;144(1):79–86.

    Article  PubMed  Google Scholar 

  58. Vijayakumar L. Suicide in women. Indian J Psychiatry. 2015;57(2):233–8.

    Article  Google Scholar 

  59. Griffith J. Correlates of suicide among army national guard soldiers. Mil Psychol. 2012;24(6):568–91.

    Article  Google Scholar 

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Authors and Affiliations



DWR conceived of the study and initiated the study design in conjunction with KL and JTJ. KL conducted the analyses, created the tables and figures, and drafted the first version of the manuscript. JTJ provided analytic direction and coding support. DWR supervised the statistical analyses plan and critically reviewed, edited, and approved the final manuscript. All authors read and approved the final manuscript.

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Dale W. Russell: I am an employee of the U.S. Government. This work was prepared as part of my official duties. Title 17, U.S.C §105 provides that copyright protection under this title is not available for any work of the U.S. Government. Title 17, U.S.C §101 defines a U.S. Government work as work prepared by an employee of the U.S. Government as part of that person’s official duties. This work was funded by Commander, Naval Surface Forces. Neither the authors nor their family members have a financial interest in any commercial product, service, or organization providing financial support for this research. The views expressed herein are those of the authors and do not necessarily reflect the official policy or position of the Department of Defense, Department of the Navy, Uniformed Services University nor the U.S. Government.

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Correspondence to Dale W. Russell.

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Lai, K., Jameson, J.T. & Russell, D.W. Prevalence and correlates of destructive behaviors in the US Naval Surface Forces from 2010–2020. BMC Psychol 11, 103 (2023).

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