Overview of a Metaanalytic Review of Risk Markers for Ipv Stith
Interpersonal violence is among the most important preventable causes of premature mortality and morbidity. Excluding state of war, it leads to effectually 410 000 deaths per year and is the 19th almost common cause of death globally.Reference Wang, Naghavi, Allen, Barber, Bhutta and Carter i Morbidity is too substantial, although there are big variations, it is in the top five causes of disability-adapted living years in central and tropical Latin America, and southern Sub-Saharan Africa.Reference Murray, Hairdresser, Foreman, Ozgoren, Abd-Allah and Abera ii Trends in violence vary depending on the outcome used: decreases in violence-related mortality have been reported from 2000 to 2015,Reference Wang, Naghavi, Allen, Hairdresser, Bhutta and Carter one whereas morbidity has remained unchanged.Reference Wang, Naghavi, Allen, Hairdresser, Bhutta and Carter one , Reference Murray, Barber, Foreman, Ozgoren, Abd-Allah and Abera two
Public wellness has moved toward a prevention model for violence,Reference Krug, Mercy, Dahlberg and Zwi 3 and influential Globe Health Organisation reports have focused on delineating risk factors.iv Identifying modifiable risk factors could potentially reduce risks and assist in developing interventions. Nonetheless, these reports are limited by existence narrative reviews of the prove without quantitative methods to evaluate the strength, quality and consistency of risk factors.
To address limitations in previous piece of work and provide an overview, we conducted an umbrella review of the bear witness from existing systematic reviews and meta-analyses on chance factors for violence.
Methods
No specific ethical blessing was required for this research as it was a synthesis of secondary data from published sources.
Search strategy
The systematic search strategy was prospectively registered on PROSPERO5 (registration number CRD42014010400). The original search incorporated both hazard factors for violence and suicide, and this paper reports the violence search. 3 databases were searched from their first dates until January 2018: PsycINFO (1 January 1806 to 5 January 2018), Medline (ane Jan 1946 to 5 January 2018) and Global Wellness (i January 1973 to five January 2018), supplemented by targeted searches on Google Scholar (i January 2004 to 5 January 2018) and PubMed (1 January 1996 to 5 January 2018).
Keywords for violence (violen*, crim*, offen*, hating and delinq*) were combined with search terms for risk factors (run a risk, predict*') and publications (meta*, systematic review). Citations and reference lists of relevant reviews were mitt-searched. Targeted searches were used to place boosted studies past offset author names and specific gamble factors that were not identified in our initial search (including developmental disorders).
Report eligibility
Eligible studies were meta-analyses or systematic reviews that examined risk factors for violence in the general population, and provided effect sizes and data to calculate 95% confidence intervals. We aimed to measure interpersonal violence and included a wide range of violence outcomes, such as assault, violent crime and sexual violence. Although this is a wide scope, we aimed to include only those reviews that used some mensurate of interpersonal violence as outcome (so that verbal aggression, minor misdeed and antisocial behaviour were excluded). Published and unpublished reviews in any language were considered.
Excluded studies were those with methodologies other than a meta-analysis or systematic review, such as private case–control or cohort studies. As the primary research question was hazard factors in the general population, reviews that investigated selected populations, such as prisoners or those with a specific diagnosis, were excluded. Reviews that focused on reoffending risks or those examined interventions for violence were besides excluded.Reference Asscher, van Vaugt, Stams, Eichelsheim, Deković and Yousfi 6 – Reference Lipsey 8 If more than one eligible review was establish on the same risk factor, the well-nigh recent 1 was included.
Data extraction
Data were extracted with a standardised form. Reported effect sizes with 95% confidence intervals were recorded with other key data. Separate upshot sizes for gender, the consequence size of the largest written report included in each meta-analysis and the effect size for the dissimilar study designs were extracted. When these data were non recorded, we corresponded straight with authors. Extracted data were independently cross-checked past a post-doctoral researcher (Z.C.), and any queries were resolved past give-and-take with the project supervisor (S.F.).
Statistical analyses
Every bit the reporting of result sizes varied betwixt studies (including odds ratios, Cohen's d, correlation coefficients, relative risks and standardised mortality ratios), they were converted to comparable measures. For the primary event, all issue sizes were converted to odds ratios (for selected formulae, see Supplementary Appendix i available at https://doi.org/ten.1192/bjp.2018.145). For those reported equally Cohen's d, log-transformed odds ratios were calculated.Reference Douglas, Guy and Hart nine – Reference Borenstein, Hedges, Higgins and Rothstein 11 Issue sizes reported every bit correlation coefficients were converted outset to Cohen's d and so to log-transformed odds ratios. Odds ratios were categorised as follows: weak, 1.0–ane.5; moderate, 1.vi–two.five; strong, 2.6–nine.9 and very stiff, ≥10.0.Reference Chesney, Goodwin and Fazel 12
Categorisation of run a risk factors and outcome measures
Risk factors and event measures were qualitatively analysed after the search, and common categories were identified. We identified singled-out categories of outcome measures (any interpersonal violence, intimate partner violence, sexual violence and homicide) that were reported separately. Meta-analyses with other related issue measures, such as assailment and hostility, were reported equally secondary outcomes in Supplementary Appendix ii.
Population attributable risk fractions
Population attributable risk fractions (PAFs) indicate the proportion of an outcome that would theoretically not occur in a population if a given risk factor was eliminated, assuming causality between risk cistron and outcome. We estimated the proportion of cases that could be attributed to each run a risk factor in the general population (meet Supplementary Appendix 1 for formulae). Although causal inferences were not possible for some take a chance factors, PAFs provide a measure of the maximum possible event that each risk factor has at a population level by taking into account the risk factor's prevalence.Reference Li, Page, Martin and Taylor 13 Thus, if a chance gene has a large effect size but low prevalence, its effect at a population level volition exist lower than a risk gene with low or moderate effect but a high prevalence.
Tests of quality of prove
Reviews were assessed for quality by various approaches. First, we scored the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) tool.Reference Shea, Grimshaw, Wells, Boers, Andersson and Hamel 14 Scores of 0–3 are considered depression, iv–7 are medium and eight–11 are high.Reference Chesney, Goodwin and Fazel 12 Second, we compared the effect size for the largest included study in each meta-assay with the overall quoted meta-analysis effect size. Results where the largest included study effect size (assumed to be the about accurate) was shut to the overall meta-assay event size were deemed to exist more precise.Reference Kirkwood and Sterne 15 Third, we calculated ratios between overall meta-assay effect size and that of the largest included study in each meta-analysis. A meta-analysis overall effect size/largest included report effect size ratio of more than than one indicates a larger effect size in the meta-analyses compared with its largest included study, and is an indication of bias.Reference Kavvoura, McQueen, Khoury, Tanzi, Bertram and Ioannidis 16 Fourth, a comparison was made betwixt meta-analyses' overall consequence size and the number of cases included in each meta-assay (meta-analyses with large sample sizes were deemed to be more preciseReference Kirkwood and Sterne 15), when sufficient data were available. Fifth, we assessed the relationship between written report design and issue size. Where sufficient data were available, results were extracted for pooled overall effect sizes of prospective studies lonely and compared with overall meta-analysis' event sizes. Finally, we presented prediction interval calculations for risk factors. Prediction intervals provide an estimate of the ranges in which future observations will autumn. Gamble factors with prediction intervals that did non cross the null value were deemed to be of higher quality. Those that cantankerous the null value propose that they may not be significant if tested in a new population.Reference Riley, Higgins and Deeks 17 To summarise these quality tests, a scoring system was developed, which also included between-study heterogeneity (with I ii <fifty% categorised as depression heterogeneity) and whether adequate adjustments for confounders was conducted (see Table 1 for details on the scoring system). All analyses were performed with STATA-IC version xiii.
Table 1 Meridian five risk factors for interpersonal violence ranked by quality of evidence
Results
Xx-two meta-analyses on take chances factors for violence (Supplementary Appendix iii) were identified.Reference Fazel, Lichtenstein, Grann, Goodwin and Långström xviii – Reference Whitaker, Le, Hanson, Baker, McMahon and Ryan 39 This included data from over 120 000 individuals from 1139 individual studies beyond 14 dissimilar countries. Risk factors were grouped into broad categories or domains of neuropsychiatric, historic and other. Considering of high heterogeneity and non-comparability, results were non further pooled. The largest effect sizes for violence were constitute in the neuropsychiatric category (Fig. 1), with substance misuse ranking most highly. Antisocial personality disorder had the strongest link to violence within the category of personality disorders.
Fig. 1 Effect sizes of hazard factors (identified in meta-analyses) for interpersonal violence, ranked by strength of association and subcategory. Adjusted odds ratios were used when possible.
Some childhood and boyish factors were important (particularly youth antisocial behaviour). Four meta-analyses examined parental factors that were associated with violenceReference Derzon twenty , Reference Murray, Farrington and Sekol 26 , Reference Hoeve, Dubas, Eichelsheim, van der Laan, Smeenk and Gerris 31 , Reference Pratt, Cullen, Sellers, Winfree, Madensen and Daigle 35 (Supplementary Appendix 4). These factors included poor attachment to parents, parental incarceration, antisocial attitudes in parents and more general problems within the family.
Intimate partner violence
Half dozen meta-analyses focused on intimate partner violence.Reference Stith, Smith, Penn, Ward and Tritt 32 – Reference Stith, Rosen, Middleton, Busch, Lunderberg and Carlton 37 Ii take chances factors overlapped with adventure factors for whatever interpersonal violence, namely substance misuse and exposure to violence. Other run a risk factors for intimate partner violence appeared to be specific to relationships, such as marital dissatisfaction and previous abuse by i partner toward the other (Supplementary Appendix 5).
Sexual violence and homicide
Two reviews provided data for take a chance factors for sexual violence alone,Reference Jespersen, Lalumière and Seto 38 , Reference Whitaker, Le, Hanson, Baker, McMahon and Ryan 39 and but 1 review provided separate risk estimates for homicideReference Fazel, Gulati, Linsell, Geddes and Grann 21 (Supplementary Appendix 6). Risk factors for sexual violence broadly overlapped with chance factors for any interpersonal violence. Data were more limited for the homicide review although two neuropsychiatric run a risk factors (schizophrenia and substance misuse) overlapped with interpersonal violence.
Risk factors stratified by gender
Where possible, results were stratified by gender (Supplementary Appendix 7). Event sizes for women appeared to be larger than for men for all neuropsychiatric violence risk factors.
PAFs
Although PAFs assume causality, they provide an guess of the maximum possible effect that removing a risk cistron could have, and PAFs for private take chances factors may overlap and add upward to more 100%.Reference Rockhill, Newman and Weinberg xl The highest PAFs for violence were substance misuse, witnessing or beingness a victim of violence in childhood, and personality disorder (Fig. 2).
Fig. 2 Population attributable fractions (PAFs) of risk factors (identified in meta-analyses) for interpersonal violence.
Other reviews
We identified a further 13 systematic reviews and meta-analyses that provided additional information. For violence, these were for the secondary outcomes of assailment and hostility rather than interpersonal violence (Supplementary Appendix 2). Risk factors for assailment included two main themes: biological factors (serotonin and testosterone levels, middle rate, genetic influences and electrodermal activity) and witnessing violence (e.one thousand. being exposed to television set violence and violent videogames). Negative findings included the lack of evidence for candidate genes associated with assailment in a meta-analysis and field synopsis of 185 studies of the field.Reference Vassos, Collier and Fazel 41
Quality assessments
Despite mostly loftier scores on AMSTAR, other analyses found indications of poorer quality. There were pocket-size study furnishings and effectually 60% of reviews had overall effect sizes larger than the effect size quoted in each meta-assay' largest included study (Fig. 3; ratios in Supplementary Appendix 8). There was no statistically significant correlation between meta-analyses' overall effect size and the number of cases included in each meta-analysis, when sufficient data were available. Of the 12 included chance factors, seven were found to exclude the null value using prediction intervals (Supplementary Appendix 9).
Fig. iii A comparison of pooled result size of included meta-analyses and the upshot size of the largest included study in these private meta-analyses.
Three meta-analyses enabled investigation of study design.Reference Fazel, Gulati, Linsell, Geddes and Grann 21 , Reference Ttofi, Farrington and Lösel 24 , Reference Wilson, Stover and Berkowitz 25 One review, which examined beingness bullied as a take a chance factor, reported a lower pooled result size for prospective studies (odds ratio 1.8, 95% CI 1.three–2.iii versus overall odds ratio iv.ix, 95% CI 2.i–eleven.2).Reference Ttofi, Farrington and Lösel 24 Two other reviews did non observe statistically meaning differences by study blueprint (one of which examined prospective studies versus case–control designs in schizophrenia,Reference Fazel, Gulati, Linsell, Geddes and Grann 21 and the other examined nested case–command versus others in childhood witnessing of violenceReference Wilson, Stover and Berkowitz 25).
Overall, using a scoring arrangement (with a maximum of six) based on quality indicators and a threshold of four or higher up for high-quality studies, seven gamble factors for violence met these criteria. None of the risk factors for intimate partner violence or sexual offending met this quality threshold (see Table 1 for peak five risk factors based on quality scores; see Supplementary Appendix 10 for a full list and caption of the scoring organisation).
Discussion
We have presented an overview of chance factors for interpersonal violence from 22 meta-analyses based on over 120 000 individuals. Nosotros have presented associations, PAFs and measures of prove quality, and investigated gamble factors for related outcomes of homicide, intimate partner violence and sexual offending. To our knowledge, this is the first quantitative meta-review of the field. In addition, novel features include bringing together relative risks and estimates of population event, using tests of methodological quality to determine the strength of the underlying testify, and the breadth of the outcomes and the ability to compare effect sizes between them.
There were iii principal findings. Commencement, based on relative risk, the strongest risk factors were typically in the neuropsychiatric domain. Second, in terms of population result, there was some overlap with factors that had the strongest relative effects, with substance utilise disorders, schizophrenia and personality disorders having loftier PAFs and relative risks. Third, the overall quality of the underlying evidence was not strong, with the majority of reviews demonstrating small study effects and big heterogeneity. By focusing on risk factors, this umbrella review has identified individual-level determinants. Socioeconomic causes of violence will rely on ecological studies that were not included.
A number of implications arise from this work. Offset, it suggests that many important risk factors for violence are modifiable, and public wellness can realistically include substantial reductions globally if these factors are confirmed in treatment trials as causal.Reference Norheim, Jha, Admasu, Godal, Hum and Kruk 42 2d, violence prevention strategies should incorporate guidelines and targets for the identification, assessment and treatment of psychiatric disorders. Nonetheless, diagnostic categories themselves are not sole treatment goals, and active symptoms and comorbidities, which mediate the above-reported associations with violence, should also be targeted. Our findings challenge the current view of criminology as a field that appears to nether-recognise mental health in the aetiology of violent crime.Reference Farrington, MacKenzie, Sherman and Welsh 43 In dissimilarity, this umbrella review found no relevant meta-analyses that were amongst the peak five risk factors in terms of quality for socioeconomic variables, and only one for a psychosocial factor (moral judgement). I possible caption is that the focus of many included reviews were neuropsychiatric conditions rather than socioeconomic factors. In add-on, within the former, the variation in socioeconomic factors is express, and thus studying their effects volition crave more full general population samples.
At the same fourth dimension, information technology should be noted that criminal history variables are among the strongest for individuals with psychiatric disorders, underscoring the need to strengthen the relationship between criminal justice and mental health services to manage future risks. Third, on a population level, antisocial personality disorder is an of import chance factor for violence, and more research on links between such disorders and these outcomes is warranted. Although footling evidence exists to advise that the underlying personality disorders are treatable, some common symptoms arising from them are modifiable.44 Another run a risk factor identified, which has been less widely discussed, is witnessing or existence a victim of violence in babyhood. The machinery for how this contributes to adult violence perpetration needs exam, and may provide targets for intervention. Yet, it suggests that interventions in childhood and adolescence for hating behaviour should consider whatever such history and broaden treatments for victims to include children who have witnessed violence. Finally, enquiry should focus on longitudinal studies, investigate sources of heterogeneity and improve aligning for confounding. Sibling controls are one powerful arroyo to do then,Reference D'Onofrio, Lahey, Turkheimer and Lichtenstein 45 and tin can provide important bear witness every bit they business relationship for familial confounding (early environmental and genetic factors). Ultimately, potent evidence of causal inference for identified risk factors volition need to exist tested in trials. However, many trials in this surface area may non be feasible for practical and upstanding reasons, and quasi-experimental designs (such as observational studies using family designs and natural experiments) volition play an important role in developing the evidence base.
Limitations of the current meta-review include the possibility that the included meta-analyses have been superseded by more recent, high-quality individual studies. For example, the reviews on traumatic brain injury and schizophrenia are from 2009.Reference Fazel, Gulati, Linsell, Geddes and Grann 21 , Reference Fazel, Philipson, Gardiner, Merritt and Grann 22 However, both of these have been confirmed by more recent, big population-based studies.Reference Sariaslan, Larsson and Fazel 46 In relation to traumatic brain injury, a big Swedish population and sibling comparison investigation plant robust links with vehement law-breaking subsequently adjustment for sociodemographic confounders,Reference Fazel, Lichtenstein, Grann and Långström 47 and an Australian study likewise establish a link when tearing crime (equally opposed to any crime) was used equally an event (with additional aligning for previous misdeed).Reference Schofield, Malacova, Preen, D'Este, Tate and Reekie 48 In addition, how violence was operationalised was necessarily heterogeneous, reflecting the lack of a consensus in the field for the all-time outcome.Reference Chambers, Yiend, Barrett, Burns, Helen and Fazel 49 Chiefly, although these will change prevalence of outcomes, they does not appear to touch on adventure estimates as the prevalence of outcomes is consistently reported in the cases (subgroups defined by exposure to a item risk factor) and general population controls.
How might treatment reduce violence? One approach is just to target and treat underlying psychiatric disorders too as symptoms and other mediators of run a risk. Randomised controlled trials provide lilliputian testify for this approach as they are not usually powered or designed to investigate rare outcomes. Observational data provide stronger back up for antipsychotic medication reducing violence risk,Reference Chang, Lichtenstein, Långström, Larsson and Fazel 50 and are important sources of evidence when randomised controlled trials are not feasible. For example, clozapine may take specific violence-reducing effectsReference Frogley, Taylor, Dickens and Picchioni 51 and psychological therapies that specifically target aggression could likewise be considered. There is some testify for structured grouping therapy in drug-using offenders to prevent reoffending.Reference Perry, Neilson, Martyn-St James, Glanville, Woodhouse and Godfrey 52 Screening for violence risk in selected populationsReference Fazel, Chang, Fanshawe, Långström and Lichtenstein 53 needs further research to clarify its potential role, including use of trial methodology. Targeting high-chance groups, such equally released prisoners and individuals with hating personality disorder, should be prioritised for hereafter intervention research. Treatments in childhood and boyhood require improvement.Reference Farrington, Gaffney and Ttofi 54 In addition, preventative approaches should be developed to address the potential importance of the two childhood risk factors that nosotros accept identified: existence bullied and witnessing or experiencing violence.
Funding
S.F. is funded by the Wellcome Trust (grant #202836/Z/16/Z). The funding source had no involvement in whatsoever attribute of the written report.
Acknowledgements
We are grateful to Dr Rongqin Yu for assistance with updating our systematic search to January 2018 and to Mr Alex Horn for technical support.
References
1 Wang, H , Naghavi, M , Allen, C , Barber, RM , Bhutta, Z , Carter, A , et al. Global, regional, and national life expectancy, all-cause bloodshed, and crusade-specific mortality for 249 causes of decease, 1980–2015: a systematic analysis for the Global Brunt of Disease Report. Lancet 2015; 388: 1459–544.CrossRefGoogle Scholar
2 Murray, CJ , Barber, RM , Foreman, KJ , Ozgoren, AA , Abd-Allah, F , Abera, SF , et al. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and salubrious life expectancy (HALE) for 188 countries, 1990–2013: quantifying the epidemiological transition. Lancet 2015; 386: 2145–91.CrossRefGoogle ScholarPubMed
6 Asscher, JJ , van Vaugt, ES , Stams, GJ , Eichelsheim, V , Deković, M , Yousfi, S. The human relationship between juvenile psychopathic traits, delinquency and (vehement) recidivism: a meta-analysis. J Child Psychol Psychiatry 2011; 52: 1134–43.CrossRefGoogle ScholarPubMed
seven Gutierrez, L , Wilson, HA , Rugge, T , Bonta, J. The prediction of recidivism with ancient offenders: a theoretically informed meta-analysis. Can J Criminol Criminal Justice 2013; 55: 55–99.CrossRefGoogle Scholar
viii Lipsey, MW. The primary factors that characterize constructive interventions with juvenile offenders: a meta-analytic overview. Vict Offenders 2009; four: 124–47.CrossRefGoogle Scholar
9 Douglas, KS , Guy, LS , Hart, SD. Psychosis as a risk cistron for violence to others: a meta-assay. Psychol Balderdash 2009; 135: 679–706.CrossRefGoogle ScholarPubMed
10 Zhang, J , Yu, KF. What'due south the relative risk? A method of correcting the odds ratio in accomplice studies of common outcomes. JAMA 1998; 18: 1690–ane.CrossRefGoogle Scholar
11 Borenstein, M , Hedges, LV , Higgins, JP , Rothstein, HR. Introduction to Meta-Assay: Converting among Upshot Sizes. Wiley, 2009.CrossRefGoogle Scholar
12 Chesney, E , Goodwin, GM , Fazel, Due south. Risks of all-cause and suicide mortality in mental disorders: a meta-review. World Psychiatry 2014; thirteen: 153–60.CrossRefGoogle ScholarPubMed
13 Li, Z , Page, A , Martin, G , Taylor, R. Attributable take chances of psychiatric and socio-economic factors for suicide from individual-level, population-based studies: a systematic review. Soc Sci Med 2011; 72: 608–16.CrossRefGoogle ScholarPubMed
14 Shea, BJ , Grimshaw, JM , Wells, GA , Boers, One thousand , Andersson, N , Hamel, C , et al. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol 2007; 7: 1.CrossRefGoogle ScholarPubMed
15 Kirkwood, BR , Sterne, JA. Essential Medical Statistics (2nd edn). Blackwell Publishing, 2000.Google Scholar
sixteen Kavvoura, FK , McQueen, MB , Khoury, MJ , Tanzi, RE , Bertram, L , Ioannidis, JP. Evaluation of the potential excess of statistically significant findings in published genetic clan studies: application to Alzheimer'south disease. Am J Epidemiol 2008; 168: 855–65.CrossRefGoogle ScholarPubMed
18 Fazel, Due south , Lichtenstein, P , Grann, Yard , Goodwin, GM , Långström, N. Bipolar disorder and violent crime: new evidence from population-based longitudinal studies and systematic review. Curvation Gen Psychiatry 2010; 67: 931–eight.CrossRefGoogle ScholarPubMed
19 Yu, R , Geddes, JR , Fazel, S. Personality disorders, violence, and hating behaviour: a systematic review and meta-regression analysis. J Pers Disord 2012; 26: 775–92.CrossRefGoogle ScholarPubMed
20 Derzon, JH. The correspondence of family features with trouble, aggressive, criminal, and fierce behaviour: a meta-analysis. J Exp Criminol 2010; 6: 263–92.CrossRefGoogle Scholar
21 Fazel, S , Gulati, G , Linsell, 50 , Geddes, JR , Grann, M. Schizophrenia and violence: systematic review and meta-analysis. PLoS Med 2009; 6: eight.CrossRefGoogle ScholarPubMed
22 Fazel, S , Philipson, J , Gardiner, L , Merritt, R , Grann, Grand. Neurological disorders and violence: a systematic review and meta-assay with a focus on epilepsy and traumatic brain injury. J Neurol 2009; 256: 1591–602.CrossRefGoogle ScholarPubMed
23 Pratt, TC , Cullen, FT , Blevins, KR , Daigle, L , Unnever, FD. The human relationship of attention deficit hyperactivity disorder to crime and delinquency: a meta-analysis. Int J Law Sci Manage 2002; 4: 344–60.CrossRefGoogle Scholar
24 Ttofi, MM , Farrington, DP , Lösel, F. School bullying as a predictor of violence afterward in life: a systematic review and meta-analysis of prospective longitudinal studies. Aggress Tearing Behav 2012; 17: 405–xviii.CrossRefGoogle Scholar
25 Wilson, HW , Stover, CS , Berkowitz, SJ. Research review: the human relationship betwixt childhood violence exposure and juvenile hating behaviour: a meta-analytic review. J Child Psychol Psychiatry 2009; 50: 769–79.CrossRefGoogle ScholarPubMed
26 Murray, J , Farrington, DP , Sekol, I. Children's hating behavior, mental health, drug use, and educational performance after parental incarceration: a systematic review and meta-assay. Psychol Bull 2012; 138: 175.CrossRefGoogle ScholarPubMed
27 Derzon, JH. Antisocial behaviour and the prediction of violence: a meta-assay. Psychol Schools 2001; 38: 93–106.CrossRefGoogle Scholar
28 Stams, GJ. The moral judgment of juvenile delinquents: a meta-assay. J Abnorm Child Psychol 2006; 34: 692–708.CrossRefGoogle ScholarPubMed
29 Morgan, AB , Lilienfeld, Then. A meta-analytic review of the relation betwixt antisocial behavior and neuropsychological measures of executive function. Clin Psychol Rev 2000; 20: 113–36.CrossRefGoogle ScholarPubMed
xxx Jolliffe, D , Farrington, DP. Empathy and offending: a systematic review and meta-analysis. Aggress Violent Behav 2004; 9: 441–76.CrossRefGoogle Scholar
31 Hoeve, G , Dubas, JS , Eichelsheim, 6 , van der Laan, PH , Smeenk, West , Gerris, JR. The relationship betwixt parenting and delinquency: a meta-analysis. J Abnorm Child Psychol 2009; 37: 749–75.CrossRefGoogle ScholarPubMed
32 Stith, SM , Smith, DB , Penn, CE , Ward, DB , Tritt, D. Intimate partner physical abuse perpetration and victimization risk factors: a meta-analytic review. Beset Violent Behav 2004; ten: 65–98.CrossRefGoogle Scholar
33 Stith, SM , Green, NM , Smith, DB , Ward, DB. Marital satisfaction and marital discord equally risk markers for intimate partner violence: a meta-analytic review. J Fam Violence 2008; 23: 149–60.CrossRefGoogle Scholar
34 Gil-Gonzalez, D , Vives-Cases, C , Alvarez-Dardet, C , Latour-Pérez, J. Alcohol and intimate partner violence: practice we have plenty information to act? Eur J Pub Wellness 2006; xvi: 278–84.CrossRefGoogle Scholar
35 Pratt, TC , Cullen, FT , Sellers, CS , Winfree, LT , Madensen, TD , Daigle, LE. The empirical condition of social learning theory: a meta-assay. Justice Quarterly 2010; 27: 765–802.CrossRefGoogle Scholar
36 Moore, TM , Stuart, GL , Meehan, JC , Rhatigan, DL , Hellmuth, JC , Keen, SM. Drug abuse and aggression between intimate partners: a meta-analytic review. Clin Psychol Rev 2008; 28: 247–74.CrossRefGoogle ScholarPubMed
37 Stith, S , Rosen, SM , Middleton, KH , Busch, KA , Lunderberg, AL , Carlton, K. The intergenerational manual of spouse corruption: a meta-analysis. J Matrimony Fam 2000; 62: 640–54.CrossRefGoogle Scholar
38 Jespersen, AF , Lalumière, ML , Seto, MC. Sexual abuse history among adult sex offenders and non-sex offenders: a meta-analysis. Child Abuse Negl 2009; 33: 179–92.CrossRefGoogle ScholarPubMed
39 Whitaker, DJ , Le, B , Hanson, R , Bakery, CK , McMahon, PM , Ryan, One thousand , et al. Gamble factors for the perpetration of child sexual abuse: a review and meta-analysis. Child Abuse Negl 2008; 32: 529–48.CrossRefGoogle ScholarPubMed
40 Rockhill, B , Newman, B , Weinberg, C. Utilize and misuse of population attributable fractions. Am J Public Health 1998; 88: 15–9.CrossRefGoogle ScholarPubMed
41 Vassos, E , Collier, DA , Fazel, S. Systematic meta-analyses and field synopsis of genetic association studies of violence and aggression. Mol Psychiatry 2014; 19: 471–7.CrossRefGoogle ScholarPubMed
42 Norheim, OF , Jha, P , Admasu, K , Godal, T , Hum, RJ , Kruk, ME , et al. Avoiding 40% of the premature deaths in each country, 2010–30: review of national bloodshed trends to help quantify the United nations sustainable development goal for health. Lancet 2015; 23: 239–52.CrossRefGoogle Scholar
43 Farrington, DP , MacKenzie, DL , Sherman, LW , Welsh, BC. Evidence-Based Offense Prevention. Routledge, 2003.CrossRefGoogle Scholar
45 D'Onofrio, BM , Lahey, BB , Turkheimer, E , Lichtenstein, P. Critical need for family-based, quasi-experimental designs in integrating genetic and social science research. Am J Public Health 2013; 103: 46–55.CrossRefGoogle ScholarPubMed
46 Sariaslan, A , Larsson, H , Fazel, S . Genetic and environmental determinants of violence run a risk in psychotic disorders: a multivariate quantitative genetic study of 1.viii million Swedish twins and siblings. Mol Psychiatry 2016; 21: 1251–1256.CrossRefGoogle ScholarPubMed
47 Fazel, S , Lichtenstein, P , Grann, Thousand , Långström, N. Risk of violent crime in individuals with epilepsy and traumatic brain injury: a 35-year Swedish population study. PLoS Med 2011; viii: 12.CrossRefGoogle ScholarPubMed
48 Schofield, PW , Malacova, Eastward , Preen, DB , D'Este, C , Tate, R , Reekie, J , et al. Does traumatic brain injury lead to criminality? A whole-population retrospective cohort study using linked data. PLoS Ane 2015; 10: 7.CrossRefGoogle ScholarPubMed
49 Chambers, JC , Yiend, J , Barrett, B , Burns, T , Helen, D , Fazel, South , et al. Outcome measures used in forensic mental health research: a structured review. Crim Behav Ment Health 2009; xix: 9–27.CrossRefGoogle ScholarPubMed
50 Chang, Z , Lichtenstein, P , Långström, North , Larsson, H , Fazel, S. Association between prescription of major psychotropic medications and fierce reoffending after prison house release. JAMA 2016; 316: 1798–807.CrossRefGoogle ScholarPubMed
51 Frogley, C , Taylor, D , Dickens, G , Picchioni, MA. Systematic review of the evidence of clozapine's anti-aggressive effects. Int J Neuropsychopharmacol 2012; 15: 1–21.CrossRefGoogle ScholarPubMed
52 Perry, AE , Neilson, M , Martyn-St James, Thou , Glanville, JM , Woodhouse, R , Godfrey, C , et al. Interventions for drug-using offenders with co-occurring mental illness. Cochrane Database Syst Rev 2015; (half-dozen): CD010901.Google Scholar
53 Fazel, S , Chang, Z , Fanshawe, T , Långström, Due north , Lichtenstein, P. Prediction of tearing reoffending on release from prison house: derivation and external validation of a scalable tool. Lancet Psychiatry 2016; 3: 535–43.CrossRefGoogle ScholarPubMed
54 Farrington, DP , Gaffney, H , Ttofi, MM. Systematic reviews of explanatory hazard factors for violence offending and delinquency. Beset Viol Behav 2016; 33: 24–36.CrossRefGoogle Scholar
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