Intelligence and criminal behavior in a total birth cohort: An examination of functional form, dimensions of intelligence, and the nature of offending
Introduction
Along with sex and age, intelligence stands out as one of the most consistent predictors of criminal and antisocial behaviors. Decades of studies from multiple disciplines have shown that, on average, individuals with lower IQ scores are more likely to engage in antisocial behavior relative to individuals with higher IQ scores (Beaver et al., 2013, Herrnstein and Murray, 1994, Jolliffe and Farrington, 2004, Kratzer and Hodgins, 1999, Neisser et al., 1996). Lower overall levels of intelligence have also been found to be associated with a wide range of criminal offending including violent offenses such as sexual assault (Cantor, Blanchard, Robichaud, & Christensen, 2005), murder (Dwyer & Frierson, 2006), and other forms of interpersonal violence (Kearns & O'Connor, 1988). Additional studies have demonstrated a negative association between intelligence and offending versatility, wherein offenders with lower levels of intelligence are more likely to engage in a greater variety of criminal acts (Frisell et al., 2012, Nevin, 2000, Walsh, 1987, Walsh and Beyer, 1986).
In addition to studies examining the association between intelligence and criminal behaviors, a related body of literature has documented negative associations between intelligence and contact with the criminal justice system (Beaver et al., 2013, Diamond et al., 2012, Fergusson et al., 2005, Hirschi and Hindelang, 1977, Loeber et al., 2012, Yun and Lee, 2013). These patterns have also been replicated at higher levels of aggregation, such as neighborhoods (Beaver & Wright, 2011), states (Bartels et al., 2010, McDaniel, 2006), and even nations (Rushton & Templer, 2009). In perhaps the most comprehensive study examining the IQ-offending association at the macro-level, Rushton and Templer (2009) utilized previously estimated national IQ scores (Lynn & Vanhanen, 2006) and crime statistics from 116 countries. Even after controlling for a host of covariates, the results revealed a significant and negative association between intelligence and criminal offending, providing evidence of a robust pattern that persists across geographic regions and cultural contexts.
Despite the large number of studies identifying a significant negative association between intelligence and offending, important aspects of the association remain relatively unknown. One aspect that has received recent attention is the functional form of the association. On the one hand, several studies have found evidence of a linear association between intelligence and offending; showing highest rates of offending among individuals with the lowest intelligence scores, followed by gradual decreases in offending at increasing levels of intelligence (Denno, 1990, Moffitt et al., 1981, West and Farrington, 1973, Welte and Wieczorek, 1998). On the other hand, at least two important studies have found evidence of non-linear patterns. Hirschi and Hindelang (1977) found individuals in the second to lowest category of their IQ measure to have the greatest involvement in criminal offending. This finding documents a slightly nonlinear association, as a purely linear association would have shown the greatest proportion of offenders to reside within the lowest IQ category. A more recent analysis by Mears and Cochran (2013) revealed a clearly curvilinear association in which offending rates were the lowest among individuals within the highest and lowest IQ categories, and individuals in the 30th to 40th percentiles were the most likely to offend.
One potential explanation for this lack of consensus in the existing literature may have to do with data limitations. We wish to draw attention to four specific limitations. First, previous research has primarily relied upon data collected several decades ago, most notably the National Longitudinal Survey of Youth (NLSY), which was initially collected in 1979 (e.g., Herrnstein and Murray, 1994, Mears, 2013). Second, most studies have examined criminal offending using vague or overly general measures of criminal behavior. For example, a substantial number of studies have relied on a single comprehensive measure of crime or delinquency without considering more specific types of offending (e.g., Diamond et al., 2012). This approach may limit the conclusions that can be drawn from the results. For example, it is possible that the IQ-crime association varies depending on the seriousness and the type of crime (e.g., property vs. violent crime).
Third, even in cases where a wider range of offending measures was examined (e.g., Mears & Cochran, 2013), such studies rely exclusively on self-reported data. While the limitations of both self-report and official records measures of offending have been documented, the strengths of each measurement strategy seem to complement the other's limitations (Thornberry & Krohn, 2000). In light of these observations, a further examination of the functional form of the IQ-offending association based on individual-level data from official records would address a significant gap in the literature.
Finally, the vast majority of previous studies examining the IQ-offending association rely either on a single, comprehensive measure of intelligence (Herrnstein and Murray, 1994, Mears, 2013) or a single subscale (Beaver et al., 2013). While previous studies have indicated that virtually all standardized measures of intelligence tend to tap the same underlying construct (typically referred to as general intelligence or g; Nisbett et al., 2012), the results of a recent meta-analysis suggest that verbal intelligence may be a better predictor of offending and delinquency relative to other subscales (e.g., performance intelligence; Isen, 2010). Based on these findings, a more nuanced approach that involves examining separate subscales along with a composite intelligence measure would constitute an important contribution to the literature.
The current study explores the IQ-offending association with specific attention devoted to functional form, while also addressing additional limitations present in the literature. A total birth cohort of Finnish males born in 1987 will be used to examine the IQ-offending association in a contemporary sample. In addition, a wide range of criminal offenses – nine different measures in total – will be examined in an effort to gain a more detailed picture of the association. The measures of criminal offending employed in the current study were collected from official records (the Central Register for Criminal Records) rather than a survey of self-reported offending. Finally, in an effort to examine whether different subscales of intelligence alter the IQ-offending association, this research employs three subscales – verbal reasoning, mathematical reasoning, and spatial reasoning – along with a composite intelligence measure.
Section snippets
Data
This study analyzes data from the 1987 Finnish Birth Cohort (FBC), which consists of 60,069 children born in Finland in 1987 (Paananen & Gissler, 2012). Individuals were selected using the 1987 Medical Birth Registry. All children weighing greater than 500 g or a gestation age of greater than or equal to 22 weeks were included. Additional information was gathered for children born abroad during the study period (n = 185) from the Central Population Register. A total of 73 (0.1%) children born
Descriptive statistics
Due to its comprehensiveness, the FBC offers the rare opportunity to more closely examine average intelligence scores and the prevalence of criminal behavior within a male birth cohort. The first set of descriptive calculations focused on the intelligence measures. The mean scores for the verbal reasoning, mathematical reasoning, spatial reasoning, and the composite reasoning measures are presented in Table 1 and were 4.62 (SD = 2.15), 4.72 (SD = 2.17), 5.05 (SD = 4.00), and 4.76 (SD = 2.18),
Discussion
Few psychological concepts have received more empirical attention than intelligence. The number of individual outcomes that have been linked to intelligence is quite extensive, covering such subjects as academic achievement (Caspi et al., 1998, Colom and Flores-Mendoza, 2007, Deary et al., 2007), health and mortality (Deary & Batty, 2006), job performance (Gottfredson, 1997), and political affiliation (Deary et al., 2008a, Deary et al., 2008b). Intelligence has maintained a somewhat
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