Background: A small but significant proportion of military veterans become involved in the criminal justice system (CJS) after leaving service. Liaison and Diversion (L&D) services aim to identify vulnerable offenders in order to provide them with the health/welfare support they need, and (where possible) divert them away from custody. An administrative database of L&D service-users was utilised to compare the needs of veterans with those of non-veteran L&D service-users. Method: National data collected from 29 L&D services in 2015–2016 was utilised. Of the 62,397 cases, 1,067 (2%) reported previous service in the Armed Forces, and 48,578 had no previous service history. The associations between veteran status and socio-demographic characteristics, offending behaviour, health- and mental health-problems were explored. The associations between specific types of offending and mental health problems within the veterans in the sample were also investigated. Results: Veterans tended to be older, and less likely to be unemployed than non-veterans, but just as likely to have unstable living arrangements (including homelessness). Veteran status was associated with increased levels of interpersonal violence, motoring offences, anxiety disorders and hazardous drinking patterns. Veteran status was associated with decreased levels of acquisitive offending, schizophrenia, ADHD, and substance misuse. Among veterans, the presence of an anxiety disorder (umbrella term which included GAD, Phobias, PTSD etc.) was associated with increased interpersonal violence, alcohol misuse was associated with increased motoring offences, and substance use was associated with increased acquisitive offending. Conclusions: Our study indicates that among offenders in the CJS who have been identified as needing health or welfare support, veterans differ from non-veterans in terms of their health and welfare needs and offending behaviour. These differences may be influenced by the impact of military service and the transition into civilian life. Our findings support the identification of military personnel within the CJS to provide appropriate interventions and support to improve outcomes and reduce offending.
Keywords: Research Article; Social sciences; Political science; Governments; Armed forces; Military personnel; Veterans; Medicine and health sciences; Mental health and psychiatry; Health care; Veteran care; Biology and life sciences; Nutrition; Diet; Alcohol consumption; Neuropsychiatric disorders; Anxiety disorders; Neuroses; Epidemiology; Medical risk factors; Neuroscience; Developmental neuroscience; Neurodevelopmental disorders; ADHD; Neurology
The majority of service leavers make successful transitions back into civilian life [[
Government statistics show that veterans form the largest single occupational group within the prison and probation services, and that they are more likely to have committed a violent or sexual offence than offenders who have not served in the military [[
Existing research also suggests that socioeconomic needs, such as relationship problems, financial instability, unemployment and lack of stable accommodation, are strong risk factors for offending among veterans and that stability in these areas can be protective against the risk of offending in the presence of mental health problems [[
The purpose of Liaison and Diversion (L&D) services is to provide an assessment of individuals within the CJS who have been identified as having a psychosocial need (for example, mental health problems, learning difficulties, physical health problems, alcohol- and substance-use problems, welfare needs), to ensure that they receive the appropriate support, and to (where possible/appropriate) divert them out of the CJS and into health, social care or other services. Referral to L&D services usually occurs at the earliest opportunity, but may take place at any stage of the CJS. Furthermore, referrals can be made by a wide range of agencies, including: police, Crown Prosecution Service, youth offending teams, social workers, drugs/alcohol services, defence lawyers, and parents/guardians/family members. This broad referral process maximises the reach of the L&D service to the most vulnerable of individuals at the earliest opportunity. Individuals referred to L&D services are offered a screening appointment with a mental health practitioner, during which they are asked whether they have ever served in the UK Armed Forces. To date, there has been no formal comparison of L&D service offenders with offenders who have not been referred to these services. However, it is likely that those offenders referred to L&D services represent a particularly vulnerable group of offenders with a range of psychosocial vulnerabilities.
The research to date has focused either on aspects of military service that are risk factors for offending, or comparisons of offending between veterans and non-veterans within the CJS without considering other factors such as health, mental health and welfare needs. Our study aims to address this gap in the literature. We utilised the national L&D database of all offenders, both Armed Forces veterans and non-veterans, who were assessed by the 29 services across England during 2015–2016. Our primary aim was to identify differences between veterans and non-veterans within L&D services, in terms of: socioeconomic and welfare needs; offending behaviour; and health and mental health problems. In addition, we examined factors associated with specific types of offending (interpersonal violence, acquisitive and motoring offences) among veterans referred to L&D services.
This study employed routinely-collected data from 29 separate L&D services from April 2015 until April 2016. Data were gathered by L&D service practitioners, and included information pertaining to the individual's: military status; socio-demographics; current offence; mental health needs; alcohol/substance use; and other vulnerabilities (learning, physical, or social and communication difficulties). Data were entered onto the database on a case-by-case basis: each referral was treated as a separate case. Thus, in the absence of an individual identifier, the same individual may have multiple entries relating to different offences. As shown in Fig 1, a total of 62,397 referrals were made to the 29 L&D sites between April 2015 and April 2016. Of these, 49,793 (80%) cases included information regarding the individual's military status, 1,215 (2.4%) of which pertained to individuals who reported that they had served, or were currently serving, in the UK Armed Forces. Given that the majority of the military personnel in the database were veterans, we categorised the cases with a recorded military status as veterans (N = 1,067; includes individuals who left military service within the last 12 months, 1–5 years ago, or more than 5 years ago), or non-veterans (N = 48,578), and excluded those who reported that they were currently serving (N = 148; see Fig 1).
Permission to access the L&D database was sought from and approved by NHS Digital following ethical approval (reference: LRS15/162992) to ensure all information governance policies and procedures were met. The dataset was fully anonymised before it was accessed.
In accordance with the UK Government's criteria, a military veteran was classified by L&D services as anyone who had served for at least one day in the UK Armed Forces, and had left service at the time of contact with L&D services. All other non-military cases were classified as non-veterans. We note that our data are cross-sectional, thus our analyses reflect associations with veteran status, rather than its role as a risk factor for offending or physical/mental health problems.
Socio-demographic factors included: age, gender, ethnicity (white vs black and minority ethnic; BME), employment status (employed; unemployed; sickness/disability; retired; other), and accommodation status (homeless; in temporary accommodation; in owned/rented accommodation; living with parents/relatives; other). Age was recorded in 5-year increments, and reflected the age-group of the individual at their first meeting with the L&D service. For the purposes of the statistical analyses, age was recoded in to six categories: 25 years and under, 26–35 years, 36 to 45 years, 46 to 55 years, 56 to 65 years, and over 65 years.
This was recorded as the most serious offence that the individual was charged with, or suspected of having committed, at the time of their referral to the L&D service. Offences were classified as: violence against the person (including murder, manslaughter, violence against the person, harassment, robbery); sex offence; non-interpersonal violence (including criminal damage, arson, possession of an offensive weapon, possession of a firearm); acquisitive offence (including theft, burglary, fraud/forgery); drug offence; public order offence; motoring offence; breach of court order; and other. For the purposes of statistical analyses, this was recoded into nine separate binary variables, each indicating the presence or absence of each offence type, in line with previous research [[
Both alcohol and substance misuse were assessed using standardised instruments: the Alcohol Use Disorders Identification Test [[
The presence of learning difficulties (where suspected) was established using standard cut-off scores on the Learning Disability Screening Questionnaire [[
Individuals were screened for, or diagnosed with, the following: schizophrenia, bipolar affective disorder, depression, anxiety disorders (including generalised anxiety, PTSD, phobias, panic disorder, and obsessive-compulsive disorder), adjustment disorder, eating disorders, dementia, attention deficit/hyperactivity disorder (ADHD), and personality disorder. Up to three mental health problems could be recorded for each case. Whilst all mental disorders were assessed using standardised screening tools and information from medical records where available, the screening and diagnostic methods varied among the different sites. As a consequence, some recorded mental disorders reflect actual diagnoses, whereas others reflect elevated scores on screening questionnaires.
We conducted the analyses using a series of univariate and multivariate logistic regression models in Stata 14 [[
We then examined the factors associated with particular offence types in the veteran sample (N = 1,067). In these analyses, we only examined offences that were independently associated with veteran status in the preceding analyses: violence against the person (vs other non-violent and non-sexual offences); acquisitive offences (vs all other offence types); and motoring offences (vs all other offence types). As in the preceding analyses, we first identified any socio-demographic variables that were independently associated with each offence type using separate logistic regression analyses. We then conducted a series of logistic regressions to examine the univariate and adjusted associations between each offence type and each of the mental health variables. In these analyses we did not adjust the standard errors based on L&D site due to the small number of veterans per site [[
As we were unable to identify which cases belonged to separate individuals in the database, and thus unable to assess the extent of clustering in data, we performed a crude sensitivity analysis. We matched the cases on a series of "static" variables (L&D site, gender, age, ethnicity, veteran status, presence of physical disabilities, presence of learning difficulties, and presence of social and communication difficulties), removed the duplicates (by selecting the first case in a cluster), and repeated our analyses. Our main results remained unchanged, therefore we report the results of the analysis of the full dataset.
The veterans in the sample were predominantly male, aged 26–35, and of white ethnicity. These characteristics were significantly associated with veteran status (see Table 1). Veterans were more likely than non-veterans to be employed (OR = 2.63, 95% CI 2.25–3.07) or retired (OR = 8.77, 95% CI 6.54–11.75) than unemployed. Veterans were less likely than non-veterans to be living with relatives (vs. being in owned or rented accommodation; OR = 0.69, 95% CI 0.52–0.91). Veterans and non-veterans were equally likely to report being homeless (OR = 0.91, 95% CI 0.69–1.20). In the multivariate logistic regression model, gender, age, ethnicity, and employment status remained independently associated with veteran status (see Table 1), and were retained as covariates in the following multivariate analyses.
Table 1: Association of socio-demographic factors with veteran status.
Non-veterans (N = 48,578) Veterans (N = 1,067) N (%) N (%) OR [95% CI] p aOR [95% CI]† p Gender Female 11096 (22.84) 33 (3.09) 1 - 1 - Male 37112 (76.40) 1028 (96.34) 9.31 [6.69–12.97] <0.01 10.44 [7.84–13.91] <0.01 Age 25 & Under 13385 (27.55) 100 (9.37) 1 - 1 - 26–35 15813 (32.55) 328 (30.74) 2.78 [2.12–3.64] <0.01 2.80 [2.06–3.81] 0.01 36–45 10575 (21.77) 277 (25.96) 3.51 [2.65–4.63] <0.01 3.68 [2.64–5.12] 0.01 46–55 6276 (12.92) 214 (20.06) 4.56 [3.20–6.51] <0.01 4.68 [3.20–6.82] 0.01 56–65 1896 (3.90) 72 (6.75) 5.08 [3.39–7.61] <0.01 3.92 [2.40–6.39] 0.01 Over 65 423 (0.87) 71 (6.65) 22.47 [14.78–34.14] <0.01 9.70 [6.09–15.46] 0.01 Ethnicity BME 6625 (13.64) 65 (6.09) 1 - 1 - White 40981 (84.36) 974 (91.28) 2.42 [1.73–3.40] <0.01 2.48 [1.88–3.27] 0.01 Employment status Employed 8239 (16.96) 337 (31.58) 2.63 [2.25–3.07] <0.01 2.42 [2.03–2.89] 0.01 Unemployed 29104 (59.91) 453 (42.46) 1 - 1 - Sickness/disability 5497 (11.32) 117 (10.97) 1.37 [0.95–1.98] 0.10 1.20 [0.84–1.73] 0.32 Retired 601 (1.24) 82 (7.69) 8.77 [6.54–11.75] <0.01 3.62 [2.41–5.43] 0.01 Other 1659 (3.42) 24 (2.25) 0.93 [0.58–1.48] 0.76 1.51 [0.92–2.50] 0.10 Accommodation status Homeless 4481 (9.22) 98 (9.18) 0.91 [0.69–1.20] 0.51 1.07 [0.83–1.39] 0.59 Temporary 4234 (8.72) 73 (6.84) 0.72 [0.49–1.05] 0.08 0.95 [0.66–1.38] 0.79 Own/Rent 26603 (54.76) 638 (59.79) 1 - 1 - Parent/Family 7445 (15.33) 123 (11.53) 0.69 [0.52–0.91] <0.01 0.93 [0.68–1.27] 0.63 Other 1782 (3.67) 38 (3.56) 0.89 [0.58–1.37] 0.60 0.96 [0.66–1.40] 0.83
1
Offences classed as violence against the person were the most common type of offending among the whole sample (32%), followed by acquisitive (16%), public order (11%), and non-interpersonal violence offences (10%). The remaining offence types were relatively uncommon. As shown in Table 2, veterans were more likely to have committed violence against the person (OR = 1.28, 95% CI 1.10–1.49) or motoring offences (OR = 1.85, 95% CI 1.40–2.43), and less likely to have committed acquisitive offences (OR = 0.56, 95% CI 0.43–0.74) than non-veterans. These differences remained significant after adjusting for age, gender, ethnicity and employment status (see Table 2). Veterans were also more likely to have committed a sexual offence than non-veterans (OR = 1.54, 95% CI 1.10–2.14), but the multivariate model suggests that this association was driven by differences in socio-demographic characteristics (aOR = 0.77, 95% CI 0.54–1.10). The remaining offence types (drug, public order and breach offences) were not independently associated with veteran status.
Table 2: Association of offence type with veteran status.
Non-veterans (N = 48,578) Veterans (N = 1,067) N (%) N (%) OR [95% CI] p aOR [95% CI]† p Violence against the person No 32227 (66.34) 645 (60.45) 1 - 1 - Yes 15410 (31.72) 396 (37.11) 1.28 [1.10–1.49] <0.01 1.36 [0.94–1.99] 0.11 Sex No 45125 (92.89) 959 (89.88) 1 - 1 - Yes 2512 (5.17) 82 (7.69) 1.54 [1.10–2.14] 0.01 1.11 [0.58–2.15] 0.75 Acquisitive No 39844 (82.02) 938 (87.91) 1 - 1 - Yes 7793 (16.04) 103 (9.65) 0.56 [0.43–0.74] <0.01 1.42 [1.05–1.92] 0.02 Violence No 42662 (87.82) 953 (89.32) 1 - 1 - Yes 4975 (10.24) 88 (8.25) 0.79 [0.62–1.01] 0.06 1.03 [0.61–1.75] 0.91 Motoring No 45501 (93.67) 958 (89.78) 1 - 1 - Yes 2136 (4.40) 83 (7.78) 1.85 [1.40–2.43] <0.01 0.39 [0.16–0.94] 0.03 Drugs No 45834 (94.35) 1010 (94.66) 1 - 1 - Yes 1803 (3.71) 31 (2.91) 0.78 [0.55–1.11] 0.16 1.31 [0.96–1.78] 0.08 Public order No 42495 (87.48) 933 (87.44) 1 - 1 - Yes 5142 (10.59) 108 (10.12) 0.96 [0.78–1.18] 0.68 0.60 [0.15–2.43] 0.47 Breach No 44280 (91.15) 971 (91.00) 1 - 1 - Yes 3357 (6.91) 70 (6.56) 0.95 [0.73–1.25] 0.72 3.69 [0.36–37.29] 0.27
2
The health needs of veterans and non-veterans are shown in Table 3. Veterans were more likely than non-veterans to be recorded as having any mental health problem (OR = 1.47, 95% CI 1.18–1.82), harmful (OR = 1.28, 95% CI 1.08–1.51) or hazardous drinking (OR = 1.44, 95% CI 1.17–1.76), as well as being more likely to report physical health problems (OR = 2.03, 95% CI 1.52–2.72). Veterans were less likely than non-veterans to report substance misuse (OR = 0.49, 95% CI 0.40–0.60), learning difficulties (OR = 0.30, 95% CI 0.17–0.55), or social and communication difficulties (OR = 0.64, 95% CI 0.45–0.92). All of these health needs remained independently associated with veteran status in the multivariate models (see Table 3), except for alcohol misuse. Only hazardous drinking remained independently associated with veteran status (aOR = 1.37, 95% CI 1.09–1.71).
Table 3: Association of health needs with veteran status.
Non-veterans (N = 48,578) Veterans (N = 1,067) N (%) N (%) OR [95% CI] p aOR [95% CI]† p Mental Health need No 11711 (24.11) 203 (19.03) 1 - 1 - Yes 28820 (59.33) 733 (68.70) 1.47 [1.18–1.82] <0.01 1.70 [1.36–2.12] <0.01 Physical need No 34248 (70.50) 689 (64.57) 1 - 1 - Yes 4646 (9.56) 190 (17.81) 2.03 [1.52–2.72] <0.01 1.65 [1.27–2.13] <0.01 Learning Difficulties No 37971 (78.17) 922 (86.41) 1 - 1 - Yes 1903 (3.92) 14 (1.31) 0.30 [0.17–0.55] <0.01 0.37 [0.19–0.72] <0.01 Social & communication difficulties No 37905 (78.03) 897 (84.07) 1 - 1 - Yes 1846 (3.80) 28 (2.62) 0.64 [0.45–0.92] 0.02 0.64 [0.43–0.95] 0.03 Alcohol Use No 24165 (49.74) 516 (48.36) 1 - 1 - Harmful 6180 (12.72) 169 (15.84) 1.28 [1.08–1.51] <0.01 1.17 [0.98–1.39] 0.08 Hazardous 3818 (7.86) 117 (10.97) 1.44 [1.17–1.76] <0.01 1.39 [1.10–1.76] 0.01 Dependence 4317 (8.89) 116 (10.87) 1.26 [0.96–1.65] 0.09 1.08 [0.86–1.34] 0.51 Substance Use No 24603 (50.65) 709 (66.45) 1 - 1 - Yes 13635 (28.07) 193 (18.09) 0.49 [0.40–0.60] <0.01 0.62 [0.50–0.76] <0.01
3 † Adjusted odds ratios: adjusted for age, gender, ethnicity and employment status.
Veterans were more likely than non-veterans to be recorded as having an anxiety disorder (OR = 4.08, 95% CI 3.32–5.01), depression (OR = 1.22, 95% CI 1.04–1.44), and dementia (OR = 6.75, 95% CI 4.06–11.22). In addition, veterans were more likely to have multiple mental health problems (OR = 1.38, 95% CI 1.27–1.50). Veterans were less likely than non-veterans to be recorded as having personality disorder (OR = 0.59, 95% CI 0.46–0.78), schizophrenia (OR = 0.35, 95% CI 0.23–0.52), and ADHD (OR = 0.15, 95% CI 0.07–0.36). All of these mental health problems remained independently associated with veteran status, after adjusting for age, gender, ethnicity and employment status, except for personality disorder and depression (see Table 4).
Table 4: Association of mental health needs with veteran status.
Non-veterans (N = 48,578) Veterans (N = 1,067) N (%) N (%) OR [95% CI] p aOR [95% CI]† p Any disorder No 11711 (24.11) 203 (19.03) 1 - 1 - Yes 28820 (59.33) 733 (68.70) 1.47 [1.18–1.82] <0.01 1.70 [1.36–2.13] 0.01 Schizophrenia No 34604 (71.23) 883 (82.76) 1 - 1 - Yes 5927 (12.20) 53 (4.97) 0.35 [0.23–0.52] <0.01 0.37 [0.25–0.53] 0.01 Anxiety No 34491 (71.00) 546 (51.17) 1 - 1 - Yes 6040 (12.43) 390 (36.55) 4.08 [3.32–5.01] <0.01 4.34 [3.45–5.45] 0.01 Personality Disorder No 35093 (72.24) 857 (80.32) 1 - 1 - Yes 5438 (11.19) 79 (7.40) 0.59 [0.46–0.78] <0.01 0.80 [0.61–1.04] 0.10 Bipolar No 38889 (80.05) 903 (84.63) 1 - 1 - Yes 1642 (3.38) 33 (3.09) 0.87 [0.58–1.29] 0.48 0.79 [0.50–1.27] 0.33 Depression No 27403 (56.41) 590 (55.30) 1 - 1 - Yes 13128 (27.02) 346 (32.43) 1.22 [1.04–1.44] 0.02 1.18 [0.99–1.41] 0.06 Dementia No 40440 (83.25) 922 (86.41) 1 - 1 - Yes 91 (0.19) 14 (1.31) 6.75 [4.06–11.22] <0.01 1.77 [1.01–3.12] 0.05 ADHD No 39164 (80.62) 931 (87.25) 1 - 1 - Yes 1367 (2.81) 5 (0.47) 0.15 [0.07–0.36] <0.01 0.25 [0.10–0.61] 0.01 Adjustment Disorder No 37876 (77.97) 859 (80.51) 1 - 1 - Yes 2655 (5.47) 77 (7.22) 1.28 [0.98–1.68] 0.07 1.21 [0.93–1.57] 0.15 Brain Injury No 40273 (82.90) 925 (86.69) 1 - 1 - Yes 258 (0.53) 11 (1.03) 1.86 [0.96–3.59] 0.07 1.43 [0.66–3.08] 0.36 Organic Disorder No 40385 (83.13) 929 (87.07) 1 - 1 - Yes 146 (0.30) 7 (0.66) 2.08 [0.95–4.55] 0.07 1.20 [0.52–2.79] 0.67 Eating Disorder No 40402 (83.17) 932 (87.35) 1 - 1 - Yes 129 (0.27) 4 (0.37) 1.34 [0.41–4.41] 0.63 1.10 [0.13–9.09] 0.93 Number of MH needs 1 or fewer 33525 (69.01) 690 (64.67) 1 - 1 - More than 1 7049 (14.51) 246 (23.06) 1.38 [1.27–1.50] <0.01 1.48 [1.31–1.67] 0.01
4 † Adjusted odds ratios: adjusted for age, gender, ethnicity and employment status.
Results of the multivariate logistic regression analyses for factors associated with each offence type among veterans are presented in the supporting information (see S1–S6 Tables).
Age and employment status were both independently associated with violence against the person (compared to other non-violent and non-sexual offences; see S1 Table). Veterans aged 26–35 (vs. 25 and under: aOR = 0.61, 95% CI 0.37–1.00) and aged 56–65 (vs. 25 and under: aOR = 0.35, 95% CI 0.16–0.76) were less likely to have committed violence against the person than other non-violent and non-sexual offences. Veterans who were retired were more likely to have committed violence against the person than other non-violent and non-sexual offences (aOR = 2.30, 95% CI 1.05–5.04). With regard to mental health risk factors, veterans who were recorded as having an anxiety disorder (aOR = 1.42, 95% CI 1.05–1.92) were more likely to have committed violence against the person than other non-violent and non-sexual offences. Veterans who were recorded as having a problem with substance misuse (aOR = 0.51, 95% CI 0.35–0.75) were less likely to have committed violence against the person offences than other non-violent and non-sexual offences (see S2 Table). Bipolar disorder (aOR = 0.39, 95% CI 0.16–0.94) was also associated with reduced risk of violence against the person, however the low number of cases and wide confidence intervals suggest a less reliable finding (see S2 Table).
Employment status and accommodation status were independently associated with acquisitive offending (vs. all other offence types; see S3 Table). Veterans who were homeless (vs. owning/renting; aOR = 2.28, 95% CI 1.27–4.10) were more likely, and veterans who were employed (vs. unemployed; aOR = 0.50, 95% CI 0.29–0.88) were less likely to have committed acquisitive offences than any other offence type. Veterans who reported bipolar disorder (aOR = 3.99, 95% CI 1.73–9.21) or substance use (aOR = 3.49, 95% CI 2.17–5.63) were more likely to have committed acquisitive offences than any other offence type. Veterans reporting alcohol misuse were less likely to have committed acquisitive offences than other offence type (aOR = 0.59, 95% CI 0.37–0.94; see S4 Table).
Age and employment status were independently associated with motoring offences within the veteran sample (see S5 Table). Specifically, being employed (vs. unemployed; aOR = 3.70, 95% CI 2.12–6.58) was associated with motoring offences. Veterans aged 56–65 were more likely to have committed motoring offences than any other offence type (vs. 25 and under: aOR = 4.74, 95% CI 1.09–20.69), however the wide confidence intervals suggest a less reliable finding. Veterans reporting alcohol misuse were more likely to have committed motoring offences than any other offence type (aOR = 2.67, 95% CI 1.56–4.57; see S6 Table). Conversely, veterans reporting substance misuse were less likely to have committed motoring offences than veterans who had committed any other offence type (aOR = 0.32, 95% CI 0.12–0.83; see S6 Table).
We know that internationally a small, but significant, proportion of Armed Forces veterans become involved in the CJS after leaving service [[
There were differences in the socio-demographic characteristics of veterans compared to general population offenders: veterans were more likely to older, in employment or retired, but with just as unstable accommodation. The mean older age of veterans may be explained by military service, which delays the period during which an individual is at risk of offending in the community [[
An association was found between veteran status and interpersonal violence. This is consistent with previous UK and US research [[
An association between veteran status and motoring offences was also found. This is consistent with evidence that road-traffic accidents are prevalent among both UK and US military personnel, and that deployment increases the likelihood of risky driving [[
We observed a crude association between veteran status and sex offending. However, this association was no longer statistically significant after adjusting for socio-demographic differences. Previous studies found age-adjusted significant associations between veteran status and sex offending in UK prisons and probation services [[
Associations were shown between veteran status and anxiety disorders, dementia and multiple mental health problems. There is a wealth of evidence that links military service (in particular, combat exposure) with PTSD [[
Veteran status was associated with hazardous (but not dependent) drinking and physical health problems. Research shows that rates of hazardous and dependent drinking among UK Armed Forces personnel are higher than among those the general population, irrespective of gender [[
Within the veteran sample, factors associated with violence against the person, acquisitive, and motoring offending were also examined. Violence against the person offences were associated with a recording of anxiety disorders (compared to other non-violent and non-sexual offences). There is a well-established link between anxiety and violence/aggression [[
Acquisitive and motoring offences were associated with substance misuse and alcohol misuse, respectively (compared to all other types of offences). There is a well-established link between substance misuse and crime in general, and this is consistent across different types of substances and different types of offending [[
A major strength of our study was the large sample size, especially of the non-veteran group, which was likely to be representative of L&D service-users. This allowed us to account for the effects of potentially confounding socio-demographic factors, which would not have been possible using a smaller sample. We were also able to directly compare veterans and non-veterans that were members of the same population–i.e. vulnerable individuals in the CJS. This is a major advantage, as any differences between them are unlikely to be biased due to different sampling methods. Furthermore, given that individuals are referred to L&D services from a range of settings, our data include individuals who had committed (or were suspected of having committed) a range of offences: from summary offences to murder and manslaughter. This increases the generalisability of our findings.
Despite these strengths, the results of our study should be interpreted in the light of a number of limitations. First, there was a significant amount of missing data. For example, 20% of cases had no veteran status, suggesting that the question is not always asked by L&D service practitioners. However, this level of missingness is not unusual among administrative datasets [[
This study has highlighted the utility of using secondary routinely collected data from services engaged with offenders early in their CJS journey in order to identify those with specific needs and allow early intervention. We have identified that, among L&D service users, those who have served in the Armed Forces have offending, welfare, physical health, mental health and substance misuse needs that differ from general population offenders. In some jurisdictions in the United States of America such is the recognition of these differences in need that special veteran courts operate to divert some veterans into justice reform projects for veterans [[
In other jurisdictions and countries, such as the UK, where veteran courts are not viable, the differences observed between veterans and non-veterans highlight the need for workforce training across the CJS to improve the identification of veterans and understanding of their needs within the CJS. The different pattern of mental health needs among veterans, such as the higher rate of anxiety disorders, and the links between mental disorders and offending behaviour, especially the link between anxiety disorder and interpersonal violence, emphasises the need for improved availability of psychological therapies in general in prison and the need for staff with an understanding of the impact of military service and life after the military on mental health and risk of offending. This may be especially important, given research showing that veterans tend to improve less from standard PTSD treatment approaches than non-veterans [[
S1 Table. Association of socio-demographic variables with violence against the person offences within the veteran sample. (XLSX)
S2 Table. Association of mental health needs with violence against the person offences within the veteran sample. (XLSX)
S3 Table. Association of socio-demographics with acquisitive offences in the veteran sample. (XLSX)
S4 Table. Association of mental health needs with acquisitive offences in the veteran sample. (XLSX)
S5 Table. Association of socio-demographic variables with motoring offences within the veteran sample. (XLSX)
S6 Table. Association of mental health needs with motoring offences within the veteran sample. (XLSX)
DIAGRAM: Fig 1: Flow chart illustrating veteran status case selection.
We thank all of the L&D service practitioners who were involved in the data entry related to this research.
By Roxanna Short, Writing – review & editing; Hannah Dickson, Writing – review & editing; Neil Greenberg, Writing – review & editing and Deirdre MacManus, Writing – review & editing