Chapter 12: Family Background and Psychopathy
Biopsychosocial Interactions & Protective Factors I: multiplicative effects – biological & psychosocial variables
Risk factors have many different kinds of interaction effects – for example, between biological and psychosocial variables (see Farrington, 1997). However, the main distinction is between multiplicative effects, where the people with both types of risk factors have the worst outcomes, and protective effects, where in some way the “protective” end of one variable counteracts or nullifies the “risk” end of the other variable.
Biopsychosocial Interactions & Protective Factors II: psychopathy increases w/risk factor numbers
Multiplicative or additive effects are the most common. In general, the likelihood of an undesirable outcome such as psychopathy increases with the number of risk factors that a person possesses. For example, in the Cambridge Study, Farrington (2000) found that the percentage of boys who were antisocial at age 32 increased from 13% of those with no risk factors at ages 8-10 to 61% of those with 3-or-4 risk factors at ages 8-10.
Biopsychosocial Interactions & Protective Factors III: predictors of offending:= chronic offenders & psychopaths
Magnusson & Bergman (1988) found that many of the significant relationships between early risk factors and adult criminality and psychiatric illness disappeared when a small group of multiple-problem, multiple-risk factor individuals were taken out of the analysis. Many of the findings regarding predictors of offending in general may be largely attributable to this small group of individuals, who are likely to be disproportionally chronic offenders and psychopaths.
Biopsychosocial Interactions & Protective Factors IV: hard to socialize temperament X poor childrearing
Biosocial interactions have not been studied specifically in relation to psychopathy, although they migh be expected. For example, Lykken (1995) argued that people with a “a hard to socialize temperament would be high risk for developing AB in all child-rearing environments, whereas people w/out this predisposing temperament would only develop AB when exposed to poor childrearing.
Biopsychosocial Interactions & Protective Factors IX: child protective factors
In the Newcastle Thousand-Family Study, Kolvin, Miller, Fleeting & Kolvin (1988a) investigated high-risk boys from deprived backgrounds who did not become delinquents. Major protective factors: under age 5 were good mothering, good maternal health, an employed head of household, and being an oldest child.
Biopsychosocial Interactions & Protective Factors V: degree of dysfunctional parenting
Wootton, Frick, Shelton and Silverthorn (1995) tested this hypothesized interaction, using “callous-unemotional” (CU) as a measure of a “hard-to-socialize temperament” and poor supervision, inconsistent and harsh discipline and low praise as measures of poor childrearing. They found that the prevalence of conduct disorder (CD), oppositional deficit disorder (ODD) at all levels of childrearing, whereas for other children it increased with the degree of dysfunctional parenting. This interaction effect was termed “suppressing-protective” by Farrington (1997) because the probability of a poor outcome is high except when both variables are favorable (with the combination of good childrearing and not callous-unemotional).
Biopsychosocial Interactions & Protective Factors VI: low resting heart rate – intact v broken homes
An early biopsychosocial interactions was reported by Wadsworth (1976) in the British National Survey of Health and Development. He found that a low pulse rate (resting heart rate) predicted violent and sexual offenses only among boys who had not experienced broken homes by age 4. Pulse rate was not predictive among boys from broken homes. This is a “suppressing-protective” effect.
Biopsychosocial Interactions & Protective Factors VII: birth complications & parental dysfunction
In a study of biopsychosocial interactions in a Copenhagen longitudinal survey, Raine, Brennan & Mednick (1994) found that children who had experienced both birth complications and early maternal rejection at age 12 months were particularly likely to be convicted of violent crimes by age 19. Using the same sample, Brennan et al. (1993) showed that children who experienced both parental psychopathology (including psychopathy) and delivery complications were particularly likely to become violent offenders. These are multiplicative interaction effects.
Biopsychosocial Interactions & Protective Factors VIII: major protective factors for children
In Hawaii, Werner & Smith (1982) studied children who possessed 4+ risk factors for offending before age 2 but that did not develop problems during childhood or adolescence. They found that the major protective factors included being first-born, being active and affectionate during infancy, small family size, and receiving a large amount of attention from caretakers.
Cambridge Study I: test & scoring parameters
Cambridge Study in Delinquent Development: a 40-year prospective longitudinal survey of development of offending and AB; 411 London boys were followed from age 8-to-48 (Farrington, 2003; Farrington et al., in press). Individual, family & socioeconomic risk factors were measured at ages 8-10 prior to convictions. At age-45, 365 of the 394 men who were still alive were interviewed (93%). Of the 365 who completed a social interview, 304 (83%) also completed a medical interview & the Structured Clinical Interview for DSM-IV (SCID-II) & the PCL:SV (Hare; Psychopathy Checklist: Screening Version). The DSM-IV (SCID-II) assessed Axis II personality disorders: avoidant, dependent, obsessive-compulsive, paranoid, schizoid, histrionic, narcisstic, borderline, and antisocial. The PCL:SV was originally scored by Dr. Crystal Romilly & checked by Dr. Simone Ulrich. Conviction records were taken into account in scoring the PCL:SV. Scores ranged from 0-to-17 (of a possible maximum of 24), with a mean if 3.5 & a standard deviation of 3.8.
Cambridge Study II: seven-% chronic offenders = 53% convictions
Up to age 48, 165 men (40%) were convicted out of 404 at risk (that is, excluding men who emigrated permanently before age 21 and therefore could not be searched for convictions). Of the convicted men, 29 were defined as chronic offenders because they had 10+ convictions. These chronic offenders (7% of the sample) accounted for 53% of all convictions.
Cambridge Study III: PCL:SV 10+ scores & high convictions
When PCL:SV scores were compared w/numbers of convictions, it was clear that there were qualitative differences between those scoring 10+ on the PCL-SV. 97% of the 33-men scoring 10+ (11% of the sample) were convicted, compared w/55% of those scoring 3-9 & only 17% of those scoring 0-2. Nearly half (48%) of the men scoring + were chronic offenders, compared w/1% of the rest. The vast majority of chronic offenders who completed the medical interview (16-of-20) scored 10+ on the PCL:SV. The average number of convictions and average number of AB personality disorder criteria fulfilled on the SCID-II were also high for those scoring 10+ on the PCL:SV.
Cambridge Study IV: PCL:SV Factors 1 & 2 differentially related to SCID-II & convictions
The affective-interpersonal (Factor 1) and antisocial lifestyle (Factor 2) components of the PCL:SV were differentially related to convictions & APD (antisocial personality disorder) criteria on the SCID-II (Axis II personality disorders: avoidant, dependent, obsessive-compulsive, paranoid, schizoid, histrionic, narcisstic, borderline, and antisocial.). Factor 1 correlates .53 w/the #-of-convictions, compared w/ .72 for the antisocial component (Factor 2) and .71 with total APD score.
Child Abuse & Neglect I: physically abused-neglected children = offenders
Children who are physically abused or neglected tend to become offenders later in life. The most famous study of this phenomenon was carried out by Widom (1989) in Indianapolis. Widom used court records to identify over 900-children who had been abused or neglected before age-11 and compared then w/control group matched on age, race, gender, elementary school class, and place of residence. A 20-yr. follow-up study showed that the children who were abused or neglected were more likely to arrested as juveniles and as adults than were controls, and they were more likely to be arrested for juvenile violence (Maxfield & Widom, 1996).
Child Abuse & Neglect II: child sexual & physical abuse = high AB & psychopathy scores
Child sexual & physical abuse & neglect also predict adult arrests for sex crimes (Widom & Ames, 1994). Most important -> Luntz & Widom (1994) showed that child abuse predicted adult antisocial personality disorder, and Weiler & Widom (1996) found that child abuse predicted high PCL-R scores in adulthood, for males & females and African Males & white children.
Child Abuse & Neglect III: physically abused child = crimes, mental illness, death by 35
An extensive review by Malinosky-Rummell & Hansen (1993) confirmed that being physically abused as a child predicted later violent and nonviolent offending. In the Cambridge-Somerville study in Boston, McCord (1983) found that about half of the abused or neglected boys were convicted for serious crimes, became alcoholic or mentally ill, or died before age 35.
Child Abuse & Neglect IV: early child abuse & high PCL-R scores & violent scores
In Stockholm, Lang, af Klinteberg & Alm (2002) reported that boys who were abused or neglected at ages 11-14 tended to become violent and to have high PC scores at age 36. Retrospective studies of offenders by Koivisto & Haapasalo (1996) in Finland and by Patrick, Zempolic & Levenston (1997) in Florida found correlations between early child abuse and high PCL-R scores; but Marshall & Coke (1999) in Scotland reported no difference in physical abuse history between psychopathic and nonpsychopathic prisoners.
Child Abuse & Neglect V: early family predictors = psychopathy at age-48
In the Cambridge Study, predicted his high psychopathy scores 40-years later and also predicted high affective and antisocial component scores: poor supervision, harsh discipline, father uninvolved, physical neglect, disrupted family, large family size, convicted father, convicted mother, delinquent sibling, young mother, depressed mother, low SES, low family income, poor housing, unpopular, delinquent school, low nonverbal IQ, low verbal IQ, low school track, high daring, lacks concentration, high impulsivity, dishonest, troublesome.
Child Abuse & Neglect VI: environmental effects linking child victimization & later AB
Possible environmental causal mechanisms linking childhood victimization and later antisocial behavior were reviewed for Wisdom (1994): 1) childhood victimization may have immediate but long-lasting consequences (e.g., shaking may cause brain injury); 2) childhood victimization may cause bodily changes (e.g., desensitization to pain) that encourage later violence; 3) child abuse may lead to impulsive or dissociative coping styles hat, in urn, lead to poor problem-solving skills or poor school performance; 4) victimization may cause changes in self-esteem or in social information-processing patterns that encourage later violence; 5) child abuse may lead to changed family environments (being placed in foster care) that have deleterious effects; and 6) juvenile justice practices ay label victims, isolate them from prosocial peers, and encourage them to associate w/delinquent peers.
Childrearing Problems I: hard to measure dimensions that predict chronic offending
Many different types of childrearing problems predict offending, as well as chronic offending (Farrington & West, 1993) and high antisocial personality scores (Farrington, 2000). The most important dimensions of childrearing are supervision or monitoring of children, discipline or parental reinforcement, warmth or coldness of emotional relationships, and parental involvement w/children. Unlike family size, these constructs are difficult to measure with high reliability and validity, and there is some evidence that results differ according to methods of measurement. Rothbaum & Weisz (1994) concluded measures of parent-child relations best measured by observation or interview v using questionnaires.
Childrearing Problems II: poor parental supervision best predictor of offending
Parental supervision refers to the degree of monitoring by parents of the child’s activities, and their degree of watchfulness or vigilance, and their degree of watchfulness or vigilance. Of all these childrearing methods, poor parental supervision is usually the strongest and most reliable predictor of offending (Farrington & Loeber, 1999; Smith & Stern, 1997), as well as chronic offending (Farrington & West, 1993) and high antisocial personality scores (Farrington, 2000).
Childrearing Problems III: poor supervision best predictor of crime to age-45
Many studies show that parents who do not know where their children are when they are out, and parents who let their children roam the streets unsupervised from an early age, tend to have delinquent children. In the classic Cambridge-Somerville study in Boston, poor parental supervision in childhood was the best predictor of both violent & property crimes up to age-45 (McCord, 1979).
Childrearing Problems IV: physical punishment predictes later convictions
Parental discipline refers to how parents react to a child’s behavior. It is clear that harsh or punitive discipline (physical punishment) predicts offending, as the review by Haapasalo & Pokela (1999) showed. In a follow-up study of nearly 700 Nottingham children, John & Elizabeth Newson (1989) found that physical punishment at ages 7-and-11 predicted later convictions; 40% of offenders had been smacked or beaten at age-11, compared with 14% of nonoffenders.
Childrearing Problems IX: poor parental-child communication & family cohesiveness poor
Poor parental-child communication predicted offending in the Pittsburgh Youth Study (Farrington & Loeber, 1999), and low family cohesiveness was the most important predictor of violence in the Chicago Youth Development Study (Gorman-Smith, Tolan, Zelli & Huesmann, 1996).
Childrearing Problems V: erratic & inconsistent discipline predicts delinquency
Erratic or inconsistent discipline also predicts delinquency (West & Farrington, 1973). This involves either erratic discipline by one parent (tolerant v harsh), or inconsistency between parents (tolerant/indulgent v harsh). And, low parental reinforcement (not praising) of good behavior is also a predictor (Farrington & Loeber, 1999).
Childrearing Problems VI: Cold, rejecting parents = delinquent children
Cold, rejecting parents tend to have delinquent children, as McCord (1979) found in the Cambridge-Somerville study in Boston.
Childrearing Problems VII: parental warmth = protective factor
McCord also concluded that parental warmth could act as a protective factor against the effects of physical punishment (McCord, 1997). 51% of the boys w/cold physically punishing mothers were convicted in the study, only 21% of the boys w/warm physically punishing mothers were convicted – like the 23% of boys w/warm nonpunitive mothers who were convicted. The father’s warmth was also a protective factor against the father’s physical punishment.
Childrearing Problems VIII: Low parental involvement in child’s activities
Low parental involvement in the child’s activities predicts subsequent offending, as found in the Nottingham survey (Lewis, Newson & Newson, 1982). In the Cambridge Study, having a father who never joined in the boy’s leisure activities doubled his risk of conviction (West & Farrington, 1973), and this was the most important predictor of persistence in offending after age 21 as opposed to desistance (Farrington & Hawkins, 1991).
Childrearing Problems X: psychopathic prisoners = parental neglect
Marshall & Cooke (1999) compared psychopathic & nonpsychopathic prisoners in Scotland using the PCL-R and found that significantly more of the psychopathic prisoners had experienced parental indifference or neglect, poor parental supervision, and poor parental discipline.
Childrearing Problems XI: poor parental supervision age 8 = high psychopathy – AB scores
In the Cambridge Study, poor parental supervision, measured at age-8, significantly predicted high psychopathy scores at age 48 (based on info. between ages 18-48: 24% of boys who were poorly supervised at age-8 (because the parents did not know here they were when they went out) had high psychopathy scores at age-48 V 8% of the remainder (odds ratio [OR] = 3.6, confidence interval: 1.9-7.0, 2 = 3.22, p = .0006) Generally an OR of 2.0 or greater indicates a strong relationship (Cohen, 1996). Interestingly, poor parental supervision predicted high AB (Factor 2) scores (OR = 3.9) but not high affective (Factor 1) scores (OR = 1.9).
SEE: Z-score article.
Childrearing Problems XII: harsh or erratic/low parental discipline at age-8 = high affective scores
Harsh or erratic parental discipline at age-8 predicted both high affective component scores and high antisocial component scores; 19% of boys suffering harsh discipline at age-8 had high total scores at age-48, compared w/8% of the remainder (OR = 2.6, CI [confidence interval ] = 1.4-4.8, z = 2.47, p = .007). Low parental involvement w/the son (dad not joining in the son’s activities) was a strong predictor of high psychopathy scores (OR = 6.5) and it predicted high affective scores most.
Childrearing Problems XIII: attachment theory
Attachment theory was inspired by Bowlby (1951) and suggests that children who are not emotionally attached to warm, loving and prosocial parents tend to become antisocial (Carlson & Sroufe, 1995).
Childrearing Problems XIV: Social learning theories: child behavior = parental response prosocial
Social learning theories (Patterson, 1982, 1995) suggest that children’s behavior depends on parental rewards and punishments and on the models of behavior that parents provide. Children tend to become antisocial if parents do not respond consistently and contingently to their bad behavior and if parents themselves behave in an antisocial manner.
Crime Runs in Families I: family crime history & father arrests = boy’s delinquency
In the Pittsburgh Youth Study, a prospective longitudinal survey of Pittsburgh males ages 7-25. Arrests of fathers, mothers, brothers, sisters, uncles, aunts, grandfathers and grandmothers all predicted the boy’s own delinquency (Farrington, Jolliffe, Loeber, Stouthamer-Loeber & Kalb, 2001). The most important relative was the father; arrests of the father predicted the boy’s delinquency independently of all other arrested relatives. Only 8% of the families accounted for 43% of arrested family members.
Crime Runs in Families II: parental psychopathology = higher psychopathy-violent offenders
In Copenhagen, Brennan, Mednick & Mednick (1993) found that parental psychopathology (including psychopathy) significantly predicted violence by sons up to age-22. Harris, Rice & Lalumiere (2001) showed that antisociality in parents (incorporating parental criminality and alcoholism along w/child abuse and neglect) was related to higher psychopathy in a sample of violent offenders drawn from a Canadian maximum security psychiatric hospital.
Crime Runs in Families III: parent conviction/delinquent older sibling = juvenile convictions
In the Cambridge Study, having a convicted parent or a delinquent older sibling by the 10th birthday were consistently among the best ages 8-10 predictors of the boy’s latent offending and antisocial behavior. Apart from behavioral measures such as troublesomeness and daring, they were the strongest predictors of juvenile convictions (Farrington, 1992a) and chronic offending (Farrington & West, 1993).
Crime Runs in Families IV: parent conviction predictor of high AB & psychopathy
Having a convicted parent was the best predictor of high antisocial personality scores at age-32 (Farrington, 2000). Having a convicted father was a strong predictor of the most psychopathic males: 25% of males w/convicted father scored 10+ on the PCL:SV, compared w/6% of the remainder (OR = 5.1), CI 2.7-9.7, z = 4.23, p Handbook of Psychopathy).
Parental Conflict & Disrupted Families IX: broken families = AB 3-classes
Explanations of the relationship between disrupted families and later AB fall into 3-classes: 1) Trauma Theories suggest that the loss of a parent has a damaging effect on a child, most commonly because of the effect on attachment to the parent; 2) Life-Course Theories: focus on separation as a sequence of stressful experiences, and on the effects of multiple stressors such as parental conflict, parental loss, low SES, changes in parental figures, and poor childrearing methods; 3) Selection Theories: argue that disrupted families produce delinquent children because of pre-existing differences from other families in risk factors such as parental conflict, criminal or AB parents, low family income, or poor childrearing methods.
Parental Conflict & Disrupted Families V: disrupted family = AB NOT affective component
Coming from a disrupted family predicted the antisocial component of psychopathy but not the affective component. The retrospective study by Koivisto & Haapasalo (1996) in Finland found a correlation between broken homes and high PCL-R scores, Patrick et al. (1997) in Florida reported that psychopathic prisoners were less likely than nonpsychopathic prisoners to come from single-parent homes.
Parental Conflict & Disrupted Families VI:. violence between parents = crime
Many studies have shown that parental conflict & inter-parental violence predict later antisocial behavior (Buehler et al., 1997; Kolbo, Blakely & Engleman, 1996). In the Christchurch Health & Development Study in New Zealand, children who witnessed violence between their parents were more likely to commit both violence & property offences according to their self reports (Fergusson & Horwood, 1998).
Parental Conflict & Disrupted Families VII:. witnessing father-initiated violence
The predictability of witnessing father-initiated violence held up after controlling for other risk factors as parental physical abuse punishment, a young mother, and low family SES. Parental conflict also predicted offending in both the Cambridge and Pittsburgh studies (Farrington & Loeber, 1999).
Parental Conflict & Disrupted Families VIII: parental conflict age-8 NOT= high psychopathc scores age-48
But, parental conflict at age-8 did not significantly predict later psychopathy scores at age-48 (Cambridge Study) & Marshall & Cooke in Scotland (1999) found that psychopathic & nonpsychopathic prisoners were not quite significantly different on early parental discord.
Parental Conflict & Disrupted Families X: broken homes = intact high-conflict families
Hypotheses derived from the 3-classes of AB (SEE: Parental Conflict & Disrupted Families IX: broken families = AB 3-classes article) were tested in the Cambridge Study (Juby & Farrington, 2001). While boys from broken homes (permanently disrupted families) were more delinquent than boys from intact homes; they were not more delinquent than boys from intact high-conflict families.
Parental Conflict & Disrupted Families XI: predisposition factor = most important factor
Overall, the most important factor was the predisposition factor. Boys who remained w/their mother after the separation had the same delinquency rate as boys from intact low-conflict families. Boys who remained w/their father, w/relatives or others (foster parents) had high offending rates. It was favored that life-course theories v trauma or selection theories.
Parental features predicting AB I: teenage pregnancy a risk factor
Early childbearing or teenage pregnancy is a risk factor. Morash & Rucker (1989) analyzed results from four surveys in the US and England (including the Cambridge Study) and found that teenage mothers tended to coincide w/low-income families and tended to have welfare support and absent biological fathers. In addition, they tended to use poor childrearing methods, and their children were often characterized by low school attainment and delinquency. However, the presence of the biological father mitigated many of these adverse factors and generally seemed to have a protective effect.
Parental features predicting AB II: unmarried mothers 17-or-less = chronic offending predictor
A large scale study in Washington State showed that children of teenage or unmarried mothers had a significantly increased risk of offending ((Conseur, Rivera, Barnoski & Emanuel, 1997). Boys born to unmarried mothers 17-or-less showed an 11-fold increase in the risk of chronic offending compared w/boys born to married mothers aged 20+.
Parental features predicting AB III: adolescent mothers = crime-prone offspring
In the Cambridge & Pittsburgh studies, the age of the mother at her first birth was only a moderate predictor of the boy’s later delinquency (Farrington & Loeber, 1999). In the Cambridge Study, 27% of sons of teenage mothers were convicted as juveniles, compared w/18% of the remainder. More detailed analyses in this study showed that teenage mothers who went on to have large numbers of children were especially likely to have convicted children (Nagin, Pogarsky & Farrington, 1997). It was concluded that the results were concordant with the diminished resource theory: The offspring of adolescent mothers were more crime-prone because they lacked not only economic resources but also personal resources such as attention and supervision.
Parental features predicting AB IV: teenage parents & child delinquency link
Because juvenile delinquency is a predictor of causing an early pregnancy (Smith et al., 2000),the link between teenage parents and child delinquency may be a consequence of the link between teenage and criminal parents. Boys born to teenage mothers were significantly likely to have high PCL:SV scores at age 48. Teenage mothers also predicted high antisocial personality scores at age 32 (Farrington,2000).
Parental features predicting AB V: mom stress-anxiety-depression = AB-psychopathy
High parental stress and parental anxiety or depression also predicted delinquency in the Pittsburgh Youth Study (Loeber, Farrington, Stouthamer-Loeber & van Kammen, 1998). In the Cambridge Study, having a mother who was anxious or depressed (according to psychiatric social worker ratings, a health questionnaire, or psychiatric records) predicted high antisocial personality scores at age-18 but not at age-32 (Farrington, 2000). But, having an anxious or depressed mother predicted high psychopathy scores at age 48.
Parental features predicting AB VI: parental substance abuse = persistent offending by male offspring
Substance abuse by parents predicts AB in children, finds the Pittsburgh Youth Study (Loeber,Farrington,Stouthamer-Loeber & van Kammen, 1998). Smoking by the mother during pregnancy is a significant risk factor. A large-scale follow-up of a general cohort study in Finland showed that maternal smoking during pregnancy doubled the risk of violent or persistent offending by male offspring, after control for other biopsychosocial risk factors (Rasanen et al., 1999). When maternal smoking was combined w/teenage mother, a single-parent family, and an unwanted pregnancy, the risk of offending increased 10-fold.
Peer, School, Neighborhood Factors I: delinquent friends = predictor of offending
It is well established that having delinquent friends is an important predictor of offending (Lipsey & Derzon, 1998). What is less clear is whether antisocial peers encourage and facilitate adolescent antisocial behavior, or whether it is merely the case that “birds of a feather flock together.” Delinquents may have delinquent friends because of co-offending, which is particularly common under age-21 (Reiss & Farrington, 1991).
Peer, School, Neighborhood Factors II: delinquent friends = chronic offenders
Elliot & Menard (1996) in the U.S. National Youth Survey concluded that delinquent friends influenced an adolescent’s own delinquency and that the reverse was also true: More delinquent adolescents were more likely to have delinquent friends. Delinquent friends were not measured until age 12 in the Cambridge Study, but chronic offenders significantly tended to have them (Farrington & West, 1993).
Peer, School, Neighborhood Factors III: peer rejection of highly aggressiuve children = ASP
There is no doubt that highly aggressive children tend to be rejected by most of their peers (Coie, Dodge & Kupersmidt, 1990). In the Oregon Youth Study, peer rejection at ages 9-10 significantly predicted adult antisocial behavior at ages 23-24 (Nelson & Dishion, 2004). p. 239.
Peer, School, Neighborhood Factors IV: PCL scores high in hyperactive boys
In Stockholm, Freidenfelt & af Klinteberg (2003) found that unpopularity predicted high PCL scores among hyperactive boys but not among nonhyperactive boys.
Peer, School, Neighborhood Factors IX: school’s variations in delinquency rates
In the Cambridge Study, most of the variation between schools in their delinquency rates could be explained by differences in their intakes of troublesome boys at age 11 (Farrington, 1972). However, reviews of American research show that schools with clear, fair and consistently enforced rules tend to have low rates of student misbehavior (Gottfredson, 2001; Herrenkohl, Hawkins, Chung, Hill & Battin-Pearson, 2001).
Peer, School, Neighborhood Factors V: low popularity = predictor of psychopathy age 48
Low popularity at ages 8-10 was only a marginal predictor of adolescent aggression and teenage violence in the Cambridge Study (Farrington, 1989). It significantly predicted chronic offending (Farrington & West, 1993) but not high antisocial personality disorder scores at age-32 (Farrington, 2000). Low popularity significantly predicted high affective at high total scores at age 48 (Early Predictors Psychopathy at age 48; Table 12.2, p 234, this volume).
Coie & Miller-Johnson (2001) found that it was the boys who were both aggressive and rejected by their classmates who became the self-reported and official offenders.
Peer, School, Neighborhood Factors VII: Continuation Schools have high delinquency-rates
It is well established that delinquents disproportionately attend high delinquency-rate schools, which have high levels of distrust between teachers and students, low commitment to the school by students, low commitment to the school by students, and unclear and inconsistently enforced rules or Continuation Schools) (Graham, 1988).
Peer, School, Neighborhood Factors VIII: boys delinqency age 11 = high psychopahy scores age 48x
In the Cambridge Study, age-11 significantly predicted a boy’s own delinquency (Farrington, 1992a), as well as his chronic offending (Farrington & West, 1993) and high antisocial personality scores at age 32 ) Farrington, 2000). Table 12. 2 (p. 243, this volume) shows that attending a high delinquency-rate school also significantly predicted high psychopahy scores at age 48.
Peer, School, Neighborhood Factors X: boys in urban areas more violent
In the U.S. National Youth Survey, the prevalence of self-reported assault and robbery was considerably higher among urban youth (Elliot et al., 1989). Within Urban youth, boys living in high-crime neighborhoods are more violent than those living in low-crime neighborhoods. In the Rochester Youth Development Study, living in a high crime neighborhood significantly predicted self-reported violence (Thornberry, Huizinga & Loeber, 1995). In the Pittsburgh Youth Study, living in a bad neighborhood (either as rated by the mother, or based on censes measures of poverty, unemployment, and female-headed households) significantly predicted official and reported violence (Farrington, 1998).
Peer, School, Neighborhood Factors XI: Offenders live in inner-city areas
Offenders disproportionately live in inner-city areas characterized by physical deterioration, and high residential mobility (Shaw & McKay, 1968). Sampson, Raudenbush and Earls (1997) argued that a low degree of “collective efficacy” in a neighborhood (a low degree of social control) caused high crime rates.
A study designed to determine the relationship between a condition and a characteristic shared by some members of a group. The population selected is healthy at the beginning of the study. Some of the members share a particular characteristic, such as cigarette smoking, whereas others do not. The study follows the population groups over a long period, noting the rate at which a condition, such as lung cancer, occurs in the smokers and in the nonsmokers
FROM: Mosby’s Dental Dictionary, 2nd edition. © 2008 Elsevier
Socioeconomic Factors I: low SES family predicts later violence
In general, coming from a low SES family predicts later violence. In the U.S. National Youth Survey, prevalence rates for self-reported assault and robbery were about twice as high among lower-class youth as among middle-class youth (Elliott, Huizinga & Menard, 1989). In Project Metropolitan in Stockholm (Wikstrom, 1885) an the Dunedin study in New Zealand (Henry, Caspi, Moffitt & Silva, 1996), the socioeconomic status of the boy’s family – based on the father’s occupation – predicted his later violent crimes.
Socioeconomic Factors II: Low SES as a predictor of offending less inconsistent
Low SES is a less consistent predictor of offending. Variability relates to whether it is measured by income and housing or by occupational prestige. In the Cambridge Study, low family income and poor housing predicted official and self-reported, juvenile and adult offending, but low parental occupational prestige predicted only self-reported offending (Farrington, 1992a, 1992b).
Socioeconomic Factors III: strongest predictor is low family income & low SES = high AB
Low family income and low SES status (but not poor housing) significantly predicted chronic offending (Farrington & West, 1993) and high antisocial personality scores at age 32 (Farrington, 2000). Table 12.2 (p. 234, this volume) shows that low family income at age-8,low social class at ages 8-10 (based on occupational prestige), and poor housing at ages 8-10 all predicted high psychopathy scores at age-48. The strongest predictor was low family income.
Socioeconomic Factors IV: no SES link w/PCL-R prisoners scores
In statistics, a z-score (or standard score) is used to compare means from different normally distributed sets of data. The actual score indicates how many standard deviations an observation is above or below the mean. The z-score is useful in research utilizing statistical analysis because it allows for the comparison of observations from different normal distributions. In effect, when items from different data sets are transformed into z-scores, then they may then all be compared.