انگیزش، استفاده از مواد مخدر و دیگر عوامل مرتبط میان اموال و بزهکاران خشونت بار که به طور منظم مواد مخدر تزریق می کنند

Abstract Objective To examine the prevalence, correlates and motivations for the commission of property and violent crime amongst a sample of people who inject drugs (PWID). Method Data were obtained from the 2013 Illicit Drug Reporting System (IDRS), which includes a cross-sectional sample of 887 PWID.

The relationship between substance use and criminal activity has been studied extensively over the past few decades, with both international and Australian studies showing that people who use drugs are more likely to engage in crime than those who do not (AIHW, 2014 and Bennett et al., 2008). Previous studies report the odds of offending to be three to four times greater for drug users than non-drug users, with the odds of offending varying across drug classes (Bennett et al., 2008). Property crime has traditionally been associated with heavier and more frequent use of illicit opioids, namely heroin, often as a means to purchase more drugs (Bennett and Holloway, 2005b, Blumstein et al., 1986 and Bradford and Payne, 2012). There is, however, growing literature to suggest that methamphetamine use is also associated with property offending (Crime and Misconduct Commission, 2005, Gizzi and Gerkin, 2010, Klee and Morris, 1994, McKetin et al., 2005 and Wilkins and Sweetsur, 2010). A large Australian sample of police detainees found that heavy users (i.e. 16–30 days of use in the preceding 30 days) of illicit opioids and amphetamines had significantly more property charges than less frequent (i.e. 1–15 days of use in the past month) and non-drug using individuals (Bradford & Payne, 2012). Furthermore, the number of drugs used by an individual influences crime, with polydrug users at increased risk of committing a property offence compared to those using a single drug (Bennett and Holloway, 2005a and Makkai, 2001). As noted above, motivations for property crime have been linked with income-raising to support drug addiction (Bennett and Holloway, 2005a, Goldstein, 1985, Klee and Morris, 1994 and Weatherburn et al., 2000) and are highly correlated with the severity of use and cost of the drug (Blumstein et al., 1986). To date, however, these outcomes have predominantly been explored in the context of heroin use (Ball et al., 1983, Bennett and Holloway, 2005b and Klee and Morris, 1994). Indeed, it has been reported that heroin users are the most likely to attribute their offending to economic reasons (i.e. needed money to buy drugs), followed by cocaine and other illegal opiate users (Payne & Gaffney, 2012). Similarly, substance use has consistently been shown to be associated with an increased risk of violent crime (Hoaken & Stewart, 2003). Studies have shown that individuals with substance use disorders contribute more to the public health burden of violent behaviour than all other psychiatric disorders combined (Pulay et al., 2008). Three popular theories surrounding the link between substance use and violent behaviour were proposed by Goldstein (1985) including: psychopharmacological violence, whereby it is argued the violence committed is a direct physiological effect of the substances used (Kuhns & Clodfelter, 2009); systemic violence, which is associated with the aggressive patterns of interaction involved with dealing and trafficking substances; and economic-compulsive violence, the perpetration of economically oriented violent crime to support the costs of their substance use. Violence occurs in this instance due to unanticipated circumstances such as the presence of a weapon or the reaction of the victim (Goldstein, Brownstein, Ryan, & Bellucci, 1989). Drugs most associated with economic-compulsive violence are heroin and cocaine due to their compulsive pattern of use and financial cost (Goldstein, 1985, Hunt, 1991 and Nurco et al., 1991). Other environmental factors that have been found to be correlated with substance use and violence include lower education, unemployment, a history of imprisonment, as well as a higher number of psychiatric diagnoses. Indeed, the drug–crime nexus can vary considerably across drug classes and crime types. The importance of examining different types of crime separately was recognised by Horyniak et al. (2014), who examined the correlates of property and violent crime amongst a sample of people who inject drugs (PWID) over a ten year period. It was found that property crime was significantly associated with age, recent heroin injection, employment status, recent benzodiazepine use and recent arrest; whist violent crime was associated with age, Indigenous status, daily alcohol consumption, recent arrest and lifetime prison history (Horyniak et al., 2014). However, the study did not account for a number of important variables that have been shown to lead to an increased risk of offending, including severity of substance use, polydrug use, drug expenditure and mental health. This paper will build upon the work done by Horyniak and colleagues by including such variables. Whilst a number of studies have examined the relationship between substance use and crime, very few studies directly ask the individuals about their criminal motivations. In addition, little is known about how particular drugs influence motivations to commit property and violent crime. Subsequently, this paper will examine the prevalence, correlates and motivations for the commission of property and violent crime amongst a sample of PWID. Identification of self-reported motivations for offending will improve our understanding of the complex relationship between substance use and crime, and assist with targeting both prevention and intervention efforts.

3. Results 3.1. Demographics Eight hundred and eighty-seven IDRS participants were interviewed in 2013 (Sydney n = 151, Melbourne n = 150, Hobart n = 107, Canberra n = 100, Adelaide n = 100, Brisbane n = 100, Darwin n = 91, Perth n = 88), reflecting predetermined quotas. Briefly, 64.20% of PWID were male with a mean age of 40.28 years (SD 9); 95.90% were of English speaking background, 49.04% were tertiary qualified, 83.50% were unemployed and 47.13% were currently in drug treatment. Over half (56.20%) had a prison history and one-third (33.60%) had been arrested in the 12 months preceding interview (Stafford & Burns, 2013). 3.2. Prevalence of property and violent crime Eighteen percent (17.50%) of IDRS participants reported past month involvement in a property offence and 3.40% reported past month involvement in a violent offence. Twenty percent of the sample (19.62%; n = 174) had committed a property or violent offence in the month preceding interview. Eleven participants reported that they had recently committed both a property and violent offence. The sample was divided into those who had committed a property offence in the past month (n = 150) and those who had committed a violent offence in the past month (n = 30). These figures include participants who had committed both a property and violent offence. 3.3. Property crime correlates At a bivariate level, those who had committed a recent property offence were younger at the time of interview (36.83 years vs. 41.01 years, t883 = − 5.40, p < 0.001) and had initiated injecting at a younger age (17.00 years vs. 18.00 years, U = 49100, p < 0.01). They were also more likely to self-report a recent mental health problem (57.90% vs. 44.00%, [OR 1.75 95% CI 1.22–2.51]), were twice as likely to score in the K10 ‘high’ or ‘very high distress’ category (i.e. score between 22 and 50) (70.50% vs. 51.70%, [OR 2.24 95% CI 1.52–3.29]), were more likely to have been arrested in the twelve months preceding interview (45.80% vs. 30.90%, [OR 1.89 95% CI 1.32–2.69]) and had also spent more money on drugs on the day preceding interview ($50.00 vs. $20.00, U = 48312, p < 0.01). In relation to substance use, those who had recently committed a property crime were twice as likely to report methamphetamine use (78.10% vs. 63.30%, [OR 2.07 95% CI 1.37–3.11]), illicit pharmaceutical stimulant use (17.40% vs. 9.60%, [OR 2.0 95% CI 1.23–3.23]) and illicit benzodiazepine use (63.20% vs. 43.90%, [OR 2.20 95% CI 1.54–3.15]) in the six month period preceding interview. They were also significantly more likely to report polydrug use, with property offenders reporting that they had used a higher number of drug classes over the last six months (7.01 vs. 5.87, t883 = 4.64, p < 0.001) than non-property offenders. Those in the property crime group were also significantly more likely to qualify for opioid dependence (84.70% vs. 71.70%, [OR 2.18 95% CI 1.33–3.57]) and stimulant dependence (51.70% vs. 36.20%, [OR 1.88 95% CI 1.25–2.82]) as measured by the SDS. When these significant factors were entered into a logistic regression model, controlling for sex, the following factors remained significant: being younger as well as being categorised opioid dependent. (See Table 1). Table 1. Correlates amongst IDRS participants that had committed a property or violent offence in the past month. Property crime past month Violent crime past month Yes (n = 155) No (n = 732) OR/t 95% CI Multivariate Yes (n = 30) No (n = 857) OR/t 95% CI Multivariate % % AOR 95% CI p-Value % % AOR 95% CI p-Value Mean age (SD) 36.83 (8.52) 41.01 (8.77) t883 = − 5.403 p < 0.001 ⁎ 0.96 0.93–0.99 p < 0.01 35.67 (8.60) 40.45 (8.83) t883 = − 2.915 p < 0.01 ⁎ 0.97 0.92–1.03 p > 0.05 Sex (male) 59.40 65.20 0.78 0.55–1.11 1.12 0.65–1.93 p > 0.05 73.30 63.90 1.56 0.69–3.54 1.36 0.49–3.73 p > 0.05 Median age first injected (range) 17.00 (12–60) 18.00 (9–47) U = 1.68 p < 0.01 ⁎ 1.01 0.97–1.06 p > 0.05 16.00 (10–40) 18.00 (9–60) U = 9672.50 p < 0.05 Median years at school (range) 10.00 (6–12) 10.00 (0–12) U = 0.05 p > 0.05 9.00 (6–12) 10.00 (0–12) U = 10276.50 p > 0.05 In a relationship 41.30 39.80 1.06 0.75–1.51 46.70 39.80 1.32 0.64–2.74 Unemployed 85.80 83.10 1.23 0.76–2.01 96.70 83.10 5.91 0.79–43.70 Unstable housinga 27.30 21.00 1.42 0.95–2.12 43.30 21.30 2.82 1.35–5.93⁎ 2.29 0.93–5.66 p > 0.05 Self-reported mental health problemb 57.90 44.00 1.75 1.22–2.51⁎ 1.39 0.82–2.37 p > 0.05 50.00 46.30 1.16 0.56–2.41 K10 score ≥ 22 70.50 51.70 2.24 1.52–3.29⁎ 0.98 0.56–1.71 p > 0.05 69.00 54.50 1.86 0.84–4.13 Heroin useb 60.60 59.40 1.05 0.74–1.50 73.30 59.20 1.90 0.84–4.31 Methamphetaminec useb 78.10 63.30 2.07 1.37–3.11⁎ 1.54 0.53–4.48 p > 0.05 73.30 65.60 1.44 0.64–3.28 Alcohol useb 61.30 59.00 1.10 0.77–1.57 63.30 59.30 1.19 0.56–2.53 Cannabis useb 77.40 70.40 1.45 0.96–2.17 83.30 71.20 2.03 0.77–5.35 Cocaine useb 18.70 14.90 1.32 0.84–2.07 36.70 14.80 3.33 1.55–7.16⁎ 1.75 0.70–4.43 p > 0.05 Illicit benzodiazepine useb 63.20 43.90 2.20 1.54–3.15⁎ 1.57 0.88–2.78 p > 0.05 50.00 47.10 1.12 0.54–2.32 Illicit morphine useb 36.80 34.80 1.09 0.76–1.56 23.30 35.60 0.55 0.23–1.30 Illicit oxycodone useb 39.40 30.30 1.49 1.04–2.13 46.70 31.40 1.91 0.92–3.98 Illicit pharmaceutical stimulant useb 17.40 9.60 2.0 1.23–3.23⁎ 1.46 0.74–2.90 p > 0.05 10.00 11.00 FET = 1.0 Illicit methadone useb 22.80 31.00 1.52 1.04–2.22 23.70 40.00 2.15 1.02–4.53 Poly drug use classes (mean; SD) 7.01 (2.69) 5.87 (2.82) t883 = 4.64 p < 0.001 ⁎ 0.97 0.87–1.09 p > 0.05 7.27 (2.70) 6.02 (2.83) t883 = 2.370 p < 0.05 Median drug expenditured $20.00 $50.00 U = 48312 p < 0.01 ⁎ 1.00 1.00–1.00 p > 0.05 $25.00 $60.00 U = 10076.50 p < 0.05 SDS (opioids) ≥ 5 84.70 71.70 2.18 1.33–3.57⁎ 2.57 1.29–5.10 p < 0.01 77.80 73.90 1.24 0.49–3.11 SDS (stimulants) ≥ 4 51.70 36.20 1.88 1.25–2.82⁎ 1.59 0.96–2.63 p > 0.05 78.30 37.80 5.91 2.16–16.17⁎ 5.34 1.91–14.93 p < 0.01 Prison history 54.20 56.70 0.91 0.64–1.28 70.00 55.70 1.85 0.84–4.10 Recent arrest (past year) 45.80 30.90 1.89 1.32–2.69⁎ 1.52 0.90–2.54 p > 0.05 70.00 32.30 4.89 2.21–10.82⁎ 2.42 0.96–6.12 p > 0.05 ⁎ Denotes significance using the Benjamini–Hochberg procedure. a Unstable housing includes those who were living in a boarding house/hostel, shelter/refuge, or who had no fixed address. b In the six months preceding interview. c Methamphetamine includes: speed powder, base and ice/crystal. d On the day prior to interview. Controlling for sex. Table options 3.4. Substance use and motivations for property crime offences The majority of participants who disclosed having committed a property offence in the past month reported being under the influence of drugs and/or alcohol at the time of their last property offence (70.67%). The substances that were reported at the time of the offence included benzodiazepines (28.30%), methamphetamine (23.60%), alcohol (20.80%), methadone (15.50%), cannabis (14.20%) and morphine (8.50%). Over half of drug-affected property offenders (56.44%) reported being under the influence of only one substance the last time they committed an offence; one-third (31.68%) were under the influence of two substances; and 11.88% reported being under the influence of more than two substances at the time of last offence. All participants who had committed a property crime in the past month were asked their main motivation for committing that offence. The majority reported that the reason was financial (74.70%), with smaller proportions reporting that the main motivation for their last property offence was opportunistic (16.70%) or psychopharmacological (4.00%). Five percent of property offenders reported some ‘other’ reason which did not categorise into the above motivations. Interestingly, participants who reported being under the influence of drugs and/or alcohol the last time they committed an offence were significantly less likely to nominate financial reasons as the main motivation for their last property offence (69.80% vs. 86.40%, [OR 0.37 95% CI 0.14–0.95]). Furthermore, participants who reported being under the influence of benzodiazepines at the time of their last property offence were significantly less likely to attribute their offending to financial reasons (14.80% vs. 31.70%, [OR 0.38 95% CI 0.16–0.87]) and proportionately more likely to attribute it to opportunistic reasons, although this did not reach statistical significance (28.00% vs. 17.70%, [OR 1.81 95% CI 0.68–4.83], p > 0.05). There were no other significant differences in regard to substance use and criminal motivations. (See Table 2). Table 2. Motivations amongst IDRS participants that had committed a property or violent offence in the past month. Under the influence of drugs and/or alcohol during last property crime Under the influence of drugs and/or alcohol during last violent crime Yes (n = 106) No (n = 44) Total (N = 150) OR 95% CI Yes (n = 22) No (n = 8) Total (N = 30) OR 95% CI Motivations for last property offence % Financiala 69.80 86.40 74.70 0.37 0.14–0.95⁎ 13.60 0.00 10.00 – – Opportunisticb 18.90 11.40 16.70 1.81 0.63–5.19 50.00 37.50 46.70 1.16 0.32–8.74 Psychopharmacologicalc 5.70 0.00 4.00 – – 18.20 0.00 13.30 – – Self-defence 0.00 0.00 0.00 – – 13.60 37.50 20.00 0.26 0.04–1.72 Committed last property offence for financial reasons Committed last property offence for opportunistic reasons Yes (n = 114) No (n = 41) p value OR 95% CI Yes (n = 25) No (n = 130) p value OR 95% CI Drug under the influence of at time of last offence % Methamphetamine 18.40 9.80 p > 0.05 2.09 0.67–6.50 12.00 16.90 p > 0.05 0.67 0.18–2.43 Heroin 15.80 14.60 p > 0.05 1.09 0.40–2.98 24.00 13.80 p > 0.05 1.97 0.69–5.58 Cannabis 11.40 4.90 p > 0.05 2.51 0.54–11.64 8.00 10.00 p > 0.05 0.78 0.17–3.70 Alcohol 14.90 12.20 p > 0.05 1.26 0.43–3.67 12.00 14.60 p > 0.05 0.80 0.22–2.93 Benzodiazepines 14.90 31.70 p < 0.05 ⁎ 0.38 0.16–0.87 28.00 17.70 p > 0.05 1.81 0.68–4.83 Methadone 16.90 12.50 p > 0.05 1.42 0.42–4.81 10.00 16.90 p > 0.05 0.55 0.11–2.63 Morphine 5.30 7.30 p > 0.05 0.70 0.17–2.95 12.00 4.60 p > 0.05 2.82 0.66–12.11 ⁎ p < 0.05. a Financial includes: needed money to buy drugs, needed money to support myself/family, needed money to repay debts, other financial reasons (e.g. needed money for food, savings, needed to buy something). b Opportunistic includes: enjoy the rush, lost your temper, looking for revenge, urged on by your friends, acting on spur of moment, opportunity arose, helping a friend out. c Psychopharmacological includes: under the influence of drugs, coming down and hanging out. Table options 3.5. Violent crime correlates At a bivariate level, those who committed a recent (past month) violent offence were younger (35.67 years vs. 40.45 years, t883 = − 2.92, p < 0.01), almost three times as likely to have unstable accommodation (43.30% vs. 21.30%, [OR 2.82 95% CI 1.35–5.93]) and almost five times as likely to have been arrested in the twelve months preceding interview (70.00% vs. 32.30%, [OR 4.89 95% CI 2.21–10.82]) than those who had not recently committed a violent offence. In relation to substance use, violent offenders were more than three times as likely to have used cocaine in the six months preceding interview (36.70% vs. 14.80%, [OR 3.33 95% CI 1.55–7.16]) and almost six times more likely to have scored in the dependence category for the stimulant SDS (78.30% vs. 37.80%, [OR 5.91 95% CI 2.16–16.17]). When these significant factors were entered into a logistic regression model, controlling for sex, only stimulant dependence remained significant. 3.6. Substance use and motivations for violent crime offences It was found that the majority of participants who reported having committed a violent offence in the past month were under the influence of drugs and/or alcohol at the time of their last violent offence (73.30%). The substances reported at the time of the offence included heroin (31.80%), alcohol (31.80%), methamphetamine (22.70%), cannabis (13.60%), methadone (9.10%) and benzodiazepines (9.10%). Almost two-thirds (63.60%) of drug-affected participants reported being under the influence of only one substance the last time they committed a violent offence, whilst over one-third (36.40%) reported being under the influence of two substances. All participants who had committed a violent offence in the past month were asked their main motivation for committing that offence, to which the highest proportion reported that the reason was opportunistic (46.70%). Within this category, reasons such as ‘the opportunity arose’ and ‘acting on the spur of the moment’ were included. This was followed by an action of self-defence (20.00%), with smaller proportions reporting that the offence was psychopharmacological (13.30%) or financial (10.00%). Due to small numbers, it was not possible to determine whether there were any significant differences in regard to substance use and the self-reported motivations of violent offenders.