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The life-course perspective on crime recognizes it is essential that we view the causes and consequences of criminal behavior throughout individuals’ developmental stages. In this research paper, we review the general conceptual foundation of the life-course perspective. We illustrate the use of this perspective by briefly reviewing four specific theories. Analytical tools to examine intraindividual trajectories are also reviewed. We conclude by suggesting future conceptual and methodological directions to advance the life-course perspective.
- The Conceptual Basis of the Life-Course Approach
- Life-Course Theories of Crime
- Moffitt’s Dual Taxonomy Theory
- Sampson and Laub’s Age-Graded Theory
- Thornberry and Krohn’s Interactional Theory
- Farrington’s Integrated Cognitive Antisocial Potential Theory
- Methodological Advances and the Life-Course Approach
- Historical Background
- Methodological Techniques Popular to the Life-Course Approach
- GBTM and Life-Course Theories
- Important Considerations for GBTM
- Future Directions
Theories of crime were primarily developed to explain the onset, prevalence, and frequency of adolescent delinquency. To an extent, this made pragmatic sense because official data revealed that, for the most part, the onset of arrests did not occur until the early adolescent years and reached the peak in prevalence at ages 15 through 17 years. However, the recognition that there was a small group of ‘career offenders’ who disproportionally contributed to the prevalence of serious crime and were likely to continue their offending into the adult years broadened our theoretical and research foci to incorporate what happened with these offenders as they transitioned from adolescence to young adulthood. Very quickly, we came to the conclusion that those who disproportionally contributed to the crime problem by committing frequent and serious criminal behaviors and had criminal careers of longer duration than less serious offenders were also precocious in their criminality, beginning their offending at younger ages. Hence, it became critical that we extend our focus to the childhood years. To do so would require a conceptual framework that addressed the full span of a person’s life. Such a vantage point would allow us to not only assess individuals’ criminal histories but also explore other aspects of individuals’ lives and assess how those aspects both impacted and were impacted by their criminal behavior. That conceptual framework has come to be known as the life-course approach.
The life-course approach provides a framework within which we can examine how people develop through the various stages of their lives. In doing so, the focus is on both stability and changes that occur in behavior and attitudes, the causes and consequences of that stability or change, and the interrelationships among different trajectories or pathways that characterize the life course. As such, rather than focusing on interindividual differences to discern patterns that may reflect the causes of behavior, the life-course approach emphasizes intraindividual stability and change to determine how both selection and socialization factors impact the life course. Within this broad conceptual approach, separate theoretical statements have been offered. While differing on some specifics of what they posit as important in describing and understanding human development, all of these theories are commonly concerned with the interweaving of trajectories representing different arenas of one’s life and the important changes or transitions that occur during the life course.
In this research paper, we examine the conceptual bases of a life course approach. We select four theoretical perspectives to review as illustrations of how life-course concepts have been used to account for the causes and consequences of crime. We also examine some of the unique analytical tools that have been developed and used to examine intraindividual change. This research paper concludes with suggestions for areas for future development.
The Conceptual Basis of the Life-Course Approach
The life-course approach to the study of human behavior conceptualizes the life course as a sequence of age-graded stages. The course through which a person traverses these stages within a domain of behavior is referred to as a trajectory (Elder, 1985). People traverse multiple trajectories such as educational, family, and work trajectories. In addition, behaviors such as criminal involvement can also be seen as trajectories. Importantly, the life-course perspective emphasizes the interconnectedness among trajectories. That is, the perspective is particularly interested in how the movement along one trajectory affects the path of another trajectory.
As people move along a particular trajectory, they will make transitions. A transition is a life event that is embedded within a trajectory and often results in “changes in state that are more or less abrupt” (Elder, 1985: pp. 31–32). For example, graduation from high school can be considered a transition in one’s educational trajectory that may not only influence the course of that trajectory but may also influence what happens in the person’s work life and family relationships. Related to the concept of transitions is the term ‘turning points.’ Turning points refer to particularly significant changes in the direction of one’s life course (Elder, 1985). Getting married is a transition that has been conceptualized as a potential turning point in the criminal behavior trajectory (Sampson and Laub, 1993). That is, marriage will often deflect a person who is on trajectory of continuing crime away from problematic behavior and more toward conforming behavior.
The timing and sequential order of transitions can be consequential. There are cultural expectations for the appropriate timing of transitions, which, when violated, may cause problems for the person. We are expected to stay in school at least through high school graduation. Quitting school prior to that time may have serious ramifications for the life course. Other off-time transitions such as having a child during one’s teenage years often impact one’s educational and work-related trajectories (Krohn et al., 1997).
The above review of key concepts in the life-course approach provides a foundation for further exploring the theoretical perspectives directed at explaining criminal behavior from a life-course perspective and the methodologies that have been developed to analyze these issues.
Life-Course Theories of Crime
The key concepts and general orientation of the life-course approach have been incorporated into several theories focusing specifically on the causes and consequences of criminal behavior (see Farrington, 2005). In this section, four theories that have had an important impact on the field are briefly described. Any explanation of what transpires across the life course is typically going to be complex; therefore, these theories cannot be presented fully in this brief research paper. Rather our emphasis is on what distinguishes one theory from the others.
Moffitt’s Dual Taxonomy Theory
Drawing from concepts in both developmental and neuropsychology, Terrie Moffitt introduced a dual taxonomic theory to explain the age–crime curve (Moffitt, 1993). This developmental theory asserted that indications of persistent antisocial behavior could be detected during childhood. What distinguishes this theory from other general or developmental models is that it proposed that not all offenders are the same and not all antisocial behaviors are caused by the same explanatory factors. More specifically, the theory identifies two unique ‘offending groups,’ or trajectories, that can be differentiated based on two factors: the age when conduct problems begin and the trajectories of those problems (Moffitt, 1993). The two offending groups are referred to as ‘early starters,’ or life-course persistent offenders (LCPs), and ‘late starters,’ or adolescence-limited offenders (ALs).
There are significant differences between LCPs and ALs. Within the late-starter group, antisocial behavior typically begins and ends during adolescence (hence the group name of ALs); thus, their delinquency career is brief (Moffitt, 2003). Moreover, adolescence-limited offending is said to be both situational and temporary. Moffitt suggests that a maturity gap – the time period after puberty when biological maturation has occurred, but youths do not yet have access to ‘adult’ privileges and resources – might contribute to the normalization of antisocial behavior. During this maturity gap, ALs may mimic the behaviors of LCPs in an attempt to show independence from parents or accelerate social maturity (Moffitt, 2003). But, because their early developmental years were prosocial and they do not have the neuropsychological deficits characteristic of LCPs, most ALs desist from crime and adopt a prosocial lifestyle upon entering young adulthood. By young adulthood, individuals typically have gained more independence from parents, leaving little reason for them to further mimic LCP behaviors.
Contrary to ALs who desist from delinquent behaviors as they gain independence, LCPs are characterized by continuity of antisocial behavior. That is, their delinquency careers begin in early childhood, persist into adulthood, and are stable over the life course. According to Moffitt, LCPs often have neuropsychological deficits that impede their verbal development. In addition, LCPs may have early emotional and behavioral problems such as bad temperament or hyperactivity (Moffitt, 1993). These early deficits may adversely influence parenting quality, as dealing with such children can often be difficult. Moreover, the inheritance of many of these antisocial qualities has been hypothesized, further suggesting that biological parents of LCPs may be poor candidates for effectively handling and coping with their children’s problem behaviors. Moffitt uses the term ‘cumulative continuity’ to suggest that early problems in the family can lead to continuing problems in school and other arenas in which LCPs interact. In addition, ‘contemporary continuity’ or the effects of deficits continue to be felt throughout different development stages. These high-risk neuropsychological and environmental interactions during the formative first two decades of life eventually develop into disordered personalities characterized by antisocial behaviors that carry on into midlife (Devers, 2011).
Sampson and Laub’s Age-Graded Theory
Growing out of Hirschi’s (1969) bonding theory, Sampson and Laub (1990) introduced the age-graded theory of informal social control to developmental criminology. This theory aimed to move away from what the authors believed were limitations of prior life-course research, including the adolescence focus and viewing desistance in a reductionist ‘criminal to noncriminal’ framework. Instead, Sampson and Laub viewed crime from childhood to adulthood, using individuals’ differences and social ties to explain their initiation and desistence from criminal behavior. Although they recognized continuity in deviant behavior, they theorized that high-quality social ties in adulthood could deflect criminal behavior trajectories toward conforming behaviors in adulthood (Sampson and Laub, 1990).
The age-graded model of informal social control predicts that individuals with more social capital, high-quality marital bonds, and secure employment are more likely to desist from criminal behavior. Thus, the basic premise of this model is that, in spite of the continuity of criminal behavior, turning points, such as getting married, can change an individual’s criminal trajectory and result in desistance from crime (Laub and Sampson, 1993). This age-graded model recognizes the influence of childhood behaviors while also highlighting the importance of major life transitions, or turning points, in explaining criminality over the life span.
Sampson and Laub (1992) delineated different stages of the life course that help provide context for their theory. From early childhood up to age of 18 years, structural problems such as low family socioeconomic status or parental divorce, in addition to individual differences in temperament, are predicted to influence whether juveniles become delinquent and how they form bonds in adulthood. During adolescence specifically, unhealthy relationships with parents, attachment to delinquent peers, and low levels of attachment to school are all expected to lead to juvenile delinquency. Ages 18 through 25 yeas represent the stage at which deviant activity can greatly threaten the development of informal social bonds, with possible incarceration and its subsequent stigma, making attachment to prosocial bonds even more difficult in adulthood. Therefore, career criminality may develop from ages 25–45 years due to individuals’ failure to reestablish prosocial attachments. In contrast, individuals who successfully develop prosocial attachments, whether through stable employment, family bonds, or high-quality marriages, will no longer commit crime because of these informal mechanisms of social control (Devers, 2011).
Thornberry and Krohn’s Interactional Theory
Terence Thornberry (1987) was one of the first criminologists to emphasize the importance of assessing how potential predictors of delinquency and crime might operate differently at different stages of the life course. He began by presenting three models depicting the causal processes of crime during early, middle, and late adolescence, respectfully. He elaborated on a basic social control model (Hirschi, 1969) by incorporating concepts from both social learning theory and social structural perspectives. In doing so, he emphasized three aspects of his theory: (1) the need to examine how the variables included in interactional theory may vary by stage of development, (2) the incorporation of the construct of structural disadvantage as antecedent to the elements of the social bond, and (3) the recognition that some of the variables may be reciprocally related to one another.
In part, because of his continuing work on the Rochester Youth Development Study (RYDS), a longitudinal panel analysis of high-risk adolescent youths, which eventually developed into both a follow-up into the adult years and a study of the children of the original target subjects, Thornberry further developed his theory (Thornberry and Krohn, 2001, 2005), transforming it into an explanation that covered the life course.
In addition to the three building blocks of interactional theory listed above, Thornberry and Krohn (2005) added the premise of proportionality of causal influences. In recognizing that delinquency and crime had multiple causes and that not all causes had to occur in order for a particular outcome to result, Thornberry and Krohn focused on the magnitude of a causal force as being critical for producing an outcome. The concept of proportionality would then suggest that “as the magnitude of the causal force increases, the person’s involvement in crime a) becomes more likely and b) increases in severity.” The concept of proportionality has implications for how their perspective differs from Moffitt’s dual taxonomy theory. According to Thornberry and Krohn (2005), there are not two types of offenders, but rather the range in the magnitude of causal influences results in some offenders beginning at an earlier age, committing more serious and frequent crime, and having a longer career than other offenders.
Taking into consideration how multiple causal factors play potentially different roles at different stages of development results in a somewhat complex theory that can account for the onset, duration, and seriousness of criminal behaviors. It is not possible to adequately describe the full range of the theory in this research paper, so we will concentrate on the onset of delinquency in order to illustrate some of the dimensions of the theory.
Thornberry and Krohn (2005) hypothesize that the early onset of antisocial factors is a result of individuals’ characteristics, problematic parenting, and positions in the social structure. The early manifestation of antisocial behaviors during toddlerhood and preschool years only results if the interaction of these three areas is of great magnitude (proportionality). The uncoupling of these three deficits weakens the causal mechanisms and is likely to delay the onset of problematic behavior until the social networks widen when the child goes to school. Now whatever deficits the child has are more likely to emerge, resulting in the onset of antisocial behavior. School and peer factors become increasingly important as the child ages. Early participation in antisocial behavior, of course, impacts performance in school and the choice of friends as well (bidirectional causality). Youths who have strong parental and school support will delay the onset of any delinquent behaviors until the adolescent years. Then the quest for independence, a necessary prerequisite for the successful transition into adulthood, may cause stress in the lives of some youths, creating more reliance on peers and, at least for some, engagement in delinquent behavior.
Thornberry and Krohn (2005) go on to account for both the continuity in delinquent behavior and the potential for change in those behaviors. The importance of the magnitude of deficits and the impact of prior behaviors on subsequent life chances and continuing criminal behavior are emphasized. For example, in describing continuity of criminal behavior among those who had an early onset, Thornberry and Krohn (2005: p. 198) state: “In brief, we hypothesize that individuals who initiate antisocial behavior at very young ages are more likely than average to persist because the causal factors are likely to remain in place and because early involvement in antisocial behavior generates cumulative and cascading consequences in the person’s life course.” For those whose deficits are uncoupled, change toward more conforming behaviors is more likely.
Farrington’s Integrated Cognitive Antisocial Potential Theory
David Farrington’s (2003) research using the Cambridge Study in Delinquent Development identified numerous risk factors of delinquent behavior and the consequences of such behavior throughout the life course of the study’s respondents. Based on the voluminous findings from that study, Farrington developed (1992) and then revised (2005) his integrated cognitive antisocial potential (ICAP) theory.
The key construct in his theory is antisocial potential (AP). AP is the potential individuals have to commit antisocial behaviors. Farrington further distinguishes between long-term AP and short-term AP. Long-term AP is due to some combination of impulsiveness, strain, socialization processes, and life events, while short-term AP depends on situational factors (Farrington, 2005: p. 76).
Farrington (2005) also identifies a set of risk factors that predicts the levels of both long-term and short-term AP. The factors suggested to predict long-term AP include those typically identified in developmental life-course theories related to social structural position, parenting, socialization, life events, and individual factors. Short-term AP is dependent on emotive states (bored, angry), the influence of male peers, and opportunities to commit crime.
The commission of a crime is dependent on the coming together of long-term and/or short-term AP with cognitive processes. Cognitive processes include a constellation of thoughts a person might have regarding the costs and rewards of behaviors and the probabilities of achieving desired outcomes. In turn, the benefits of committing a behavior are somewhat dependent on anticipated approval from parents, peers, and partners. Farrington recognizes that the different combinations of long-term AP, short-term AP, and various cognitive processes may differ for different types of people but does not speculate on those dynamics.
The ICAP theory is a compilation of Farrington’s research findings that focused primarily on establishing the risk factors for delinquent and criminal behavior. The causal processes that may explain why those factors present risk for criminal behavior have not been presented in his theory. Further development of those interconnections may provide a more thorough explanation of crime across the life course.
Methodological Advances and the Life-Course Approach
As outlined above, a main premise of the life-course approach is age-graded stages of development across various life domains. These stages can be further conceptualized as trajectories or long-term developmental patterns throughout the life course (Elder, 1975). A compendium of longitudinal data sets has emerged in recent years along with subsequent advances in methodological techniques. Researchers now have the enhanced ability to statistically ‘look back’ and simultaneously model respondents’ developmental trajectories while considering the impact of theoretically relevant covariates. The following section describes a few of these methodological advances, focusing especially on semiparametric group-based trajectory modeling (GBTM) (Nagin, 2005).
During the criminal–career–age–crime curve debates of the 1980s, Blumstein et al. (1988) contended that offenders’ patterns of criminal continuity and discontinuity were not static but, rather, were dynamic and varied over time. As such, these scholars posited that the classic, aggregate age– crime curve masked important differences in the prevalence and incidence of criminal involvement. This position was strongly debated by Gottfredson and Hirschi (1988), who argued in support of the static nature of offending behavior. Moreover, as proponents of the classic age–crime curve, Gottfredson and Hirschi (1986) posited that the pattern revealed at the aggregate level would be similar to patterns revealed from alternative individual-level analyses. Said differently, the authors argued that all individuals followed the rise, peak, and fall pattern seen in the aggregate. However, the significance of individuals’ different levels of crime participation and frequency of criminal involvement became increasingly recognized with groundbreaking longitudinal analyses using data from the Philadelphia birth cohort study (see Wolfgang et al., 1972). These findings revealed that, over time, a small group of offenders was responsible for the most serious offenses. More importantly, these longitudinal results revealed patterns and facets of criminal careers not previously apparent from cross-sectional analyses.
The life-course approach has generated an increasingly accessible database and methodological techniques with which to examine theoretical implications. We are no longer limited to identifying and interpreting correlations between behaviors and later outcomes. Rather, exploration into how behaviors are connected throughout the life course and their influence on the continuity or change of antisocial behaviors can now be more accurately assessed.
Methodological Techniques Popular to the Life-Course Approach
Increased use of longitudinal designs and analyses has resulted in more accurate estimation of individuals’ behavioral patterns (Sampson and Laub, 1992). Constrained to the statistical techniques available, early longitudinal researchers ran the risk of potentially ‘underfitting’ complex data sets and leaving certain developmental patterns undiscovered. However, recent advances in the methodological tools available allow researchers to better capture the connectedness of behaviors over time.
Three specific methods have been chosen for comparison in this research paper: hierarchical linear models (HLM), latent growth curve models (LGCM), and GBTM. All the three methods have been used to achieve a “common analytical objective” (Nagin and Odgers, 2010b: p. 114) of identifying shapes of developmental trajectories as functions of age or time and assessing the variability of identified trajectories within a population (Nagin, 1999; Nagin and Odgers, 2010b). Deciding which technique is best suited for analyses is typically guided by the theoretical framework, the research question at hand, and, especially, the assumptions made by each of the three methods (Curran and Bollen, 2001). This section gives an overview of important differences between these three models, ultimately providing a more thorough review of GBTM and its advantages for developing and modifying life-course theories.
Oft mentioned as alternatives to GBTM (Nagin and Tremblay, 2005b), HLM or LGCM offer multilevel approaches for modeling repeated measures to assess individuals’ change over time. The two methods allow models of individuals’ unobserved (latent) patterns, or trajectories, to be estimated using either manifest, observed measures in HLM (Raudenbush et al., 2004) or latent constructs, as is the case with LGCM (Loehlin, 2004). Likewise, both methods assess differences in within-person, or intraindividual change over time, with outcomes revealing mean developmental patterns within a population as well as individuals’ variability from these average patterns (Preacher et al., 2008).
HLM analyses assess variables across different levels. Initially, unconditional models are estimated to separate the fixed and random effects and provide both intra- and interindividual variance estimates. Level 1 variables address within-person measures that can vary over time, while Level 2 measures reflect independent variables that can be used to predict or explain variability in within-person changes between individuals (Raudenbush and Bryk, 2002). The unconditional model estimates are used to calculate intraclass correlations (ICCs). The ICCs are interpreted as differences attributable to the Level 2, inter(between)- individual measures. Further analyses include regression of Level 1 factors onto Level 2 variables. Such analyses result in cross-level interactions between the levels. These interaction terms are used to evaluate differences in individuals’ developmental trajectories as a function of their Level 2 covariates. In sum, HLM allow for assessing the influence of between-person differences on within-person change over time (Raudenbush and Bryk, 2002).
Despite many similarities to HLM, LGCM focus on latent, unobserved variables, or growth factors, that may shape and influence the population’s mean and variances for an outcome (Bollen and Curran, 2006). Like in HLM, initially estimated unconditional models provide the shape of developmental trajectories using the population mean growth and different rates of change. Instead of estimating variables by levels, LGCM measure growth factors at multiple times then relate those factors to other influential covariates (Bollen and Curran, 2006). Overall, LGCM have been touted as being more flexible than HLM, specifically better handling measurement error, reducing bias, and detecting main effects (Bollen and Curran, 2006; Muthen and Asparouhov, 2011). On the other hand, HLM have been found to provide more accurate estimates of cross-level interactions.
While basic HLM or LGCM share many similarities, more distinct differences exist between them and GBTM models. These differences are especially important when the empirical goal is identifying distinct, unique developmental patterns within a population. First, both HLM and LGCM assume that developmental patterns are distributed continuously. Such a distribution suggests that all individuals within a population move along the same, general development pathways, with their individual trajectories increasing or decreasing over time but following the same general shape or pattern (Nagin and Tremblay, 2005a). GBTM takes a very different approach, allowing for situations where estimated developmental pathways may not ‘fit’ or follow one common shape or growth pattern (Nagin and Tremblay, 2005a). GBTM’s different approach to modeling developmental patterns – assuming individuals within a population can be stratified into homogenous clusters that may follow differently shaped pathways – makes the method a prime technique for allowing unique, distinct developmental trajectories to emerge from a population (Nagin, 1999, 2005). Another strength of GBTM is the decreased subjectivity by which researchers identify clusters of individuals on similar developmental trajectories. While HLM and LGCM employ a more ad hoc style of classifying groups prior to estimating developmental trajectories, GBTM provides statistical output for further assessment after the identification of trajectory groups (Nagin, 1999, 2005). These posterior probability statistics can be used to guide more precise classifications of groups and are an important advantage to be aware of when considering the best technique to identify distinct intraindividual developmental trajectories.
GBTM and Life-Course Theories
With the continuity of human development central to lifecourse theories, it is important to use analytical techniques that can account for continuous unfolding of behaviors and within-person changes in criminal involvement over time (Bushway et al., 2003; Nagin, 2005; Thornberry and Matsuda, 2011). As such, the use of GBTM in life-course criminology is strengthened by its allowance for variations in rates at which individuals move along developmental trajectories as well as permitting individuals’ trajectories to differ by developmental stages, times, or ages (Krohn et al., 2013). Furthermore, by identifying rather than assuming patterns of antisocial development within a population, GBTM has been an invaluable tool in answering the types of questions asked by life-course criminologists (Nagin and Odgers, 2010a).
As an example, Moffitt’s (1993) dual taxonomy model suggests two clear, potential developmental offending paths, with individuals’ age of onset as the integral consideration for classifying them as ALs or LCPs. Alternatively, other life-course theories, such as Thornberry and Krohn’s (2005) interactional theory, do not model such strict classifications of offending groups. Using GBTM to address empirical questions stemming from these life-course theories, researchers have found support for some theoretical contentions but also revealed unexpected developmental patterns of antisocial behavior (i.e., offending groups beyond ALs and LCPs) (Farrington, 2005; Nagin and Tremblay, 2005a). These studies have certainly established variation of individuals’ offending patterns over time, showing differences by age of onset, severity of antisocial behavior (i.e., frequency, prevalence), and timing of desistence (Krohn et al., 2013; Piquero, 2008). A comprehensive review of research using different longitudinal data to estimate patterns of offending behavior over time reveals an average of four offending groups (Piquero, 2008).
For illustrative purposes, Figure 1 presents the results from one study that has estimated respondents’ (aged 13–22 years) offending trajectories. Using data from the RYDS, Bushway et al. (2003) find a best-fitting model of seven distinct trajectory groups. These trajectories reveal unexpected patterns, for example, one noteworthy group of ‘late bloomers’ (group P3). Distinguishing late bloomers from other offending trajectories is their unexpected age of onset when older, as well as their increasing severity of antisocial behaviors (Bushway et al., 2003; Krohn et al., 2013). For a certain period, late bloomers are even shown to surpass the offending patterns displayed by high-level chronics (Bushway et al., 2003; Krohn et al., 2013).
Figure 1. Rochester Youth Development Study offending trajectories estimated with GBTM (Bushway, S.D., Thornberry, T.P., Krohn, M.D., 2003. Desistance as a developmental process: a comparison of static and dynamic approaches. Journal of Quantitative Criminology 19, 129–153.).
The unearthing of this late-bloomer group using GBTM encourages theoretical explanation and advancement, with scholars already offering reasons for late-bloomer groups. Recent efforts include suggestions that the late-bloomer trajectory is a reflection of social changes – specifically the timing of certain developmental events (i.e., careers, marriage, parenthood) coming at a later age than they did in prior decades (Mata and van Duhlmen, 2012).
Important Considerations for GBTM
In sum, because no extant theory clearly or accurately outlines how many developmental trajectories should exist in a population, GBTM is an asset for scholars attempting to identify such patterns and further develop theoretical propositions. The following are key considerations when applying GBTM. First, groups are not to be considered as literal representations; they are estimates and are theory driven. Developmental trajectory groups are latent strata or clusters of individuals with similarities. These latent strata groups are sometimes referred to as ‘statistical fictions,’ suggesting the groups do exist in the best-fitting model of the data (i.e., there is an LCP group of offenders), but the best-fitting model is still an estimate of the true population parameters (Nagin and Tremblay, 2005c). Secondly, once trajectories are identified, posterior probabilities can also be used to assess precision of group membership. These posterior probabilities can also be used to classify groups and allow for better description of the characteristics, or profiles, of clusters following different developmental patterns. In addition to these key features, research focusing on GBTM or more general latent class models notes that such analyses are sensitive to the data being utilized, with longer follow-up lengths (i.e., more waves of data) and environmental exposure (i.e., incarcerated versus in the community) impacting trajectories’ shapes (Eggleston et al., 2004; Sampson and Laub, 1993). As such, GBTM and related techniques are increasingly combined with other statistical techniques such as propensity score matching (e.g., see Haviland et al., 2007; Ward et al., 2013) to better assess causal relationships or dual trajectory estimation to assess contemporaneous, or comorbid events over the life course.
The recognition that to fully understand the onset, duration, seriousness, continuity, and desistance of crime requires a full examination of what occurs throughout the life course is a relatively recent insight. The life-course approach to the study of crime is still in its early developmental stage. This brief overview of major concepts, theories, and analytical tools used in the life-course perspective touches on only some of the major themes of the approach and, frankly, fails to provide an appreciation for the complexity of examining crime across the life course. While there has been progress in beginning to explore issues related to the trajectory of criminal behavior, there is still much to be done before a true understanding of both the continuity and change in crime and the effects it has on other life-course trajectories can be accomplished. In the remaining paragraphs, we offer a few suggestions for future work on crime across the life course.
To date, much of the conceptual work on crime across the life course has focused on the degree to which there is continuity versus change in criminal behavior. For example, Moffitt’s dual taxonomy approach emphasizes continuity of crime for LCPs. Factors such as neurological deficits set in motion a sequence of consequences that result in child conduct disorders leading to juvenile delinquency and continuing crime into adulthood. Sampson and Laub’s age-graded theory emphasizes the role played by adult social bonds in changing the trajectory of crime. Oftentimes, the debate on the degree of overlap between continuity and change is couched in terms of whether selection factors (e.g., neuropsychological deficits) or socialization factors (e.g., marriage) are more important in determining individual trajectories of crime. Such debate has led to an overexaggeration of the differences between these positions. While this discussion may have been necessary for the emerging life-course perspective, it is now superseded by the recognition that there are both continuity and change in the patterns of crime and that both selection and socialization are important components of such patterns. To advance our understanding of the life-course perspective, the first step is to rephrase the conceptual question from ‘Whether there is more stability or change in crimes?’ to ‘Under what conditions do people continue on their criminal or noncriminal trajectory and under what conditions are there changes in the initial pattern?’
Relatedly, we need to identify similarities across approaches and the conceptualizations contained in different perspectives, as well as explore consistencies in findings across theoretically directed research. David Farrington (2005) has paved the way for these efforts by requesting scholars representing major life-course perspectives address how their theories answer his proposed set of 24 questions concerning issues such as the onset, duration, desistence, and the scope of the theory. Farrington further provides a summary chapter that could be considered a template for identifying the overlap in life-course theories. The next step is to examine the findings on the shared propositions.
Much of the examination of factors that affect changes in crime across the life course has focused on mediating processes. Essentially this approach considers the sequential causal processes that lead to continuity or change in criminal behavior. This, of course, is an essential approach if we are to understand the life course of criminal behavior. However, predicated on the risk and protective factor approach, we are increasingly beginning to see analyses that focus on moderating factors (Krohn et al., 2014; Lizotte et al., 2013). Moderating factors are those that interact with causal variables to either reduce or enhance covariates’ impact on criminal behaviors. One potentially valuable contribution of this approach is its focus on factors that could be manipulated to reduce the probability of continuing criminality for those most at risk.
Also, although many life-course theories recognize that genetic factors play a role in accounting for the trajectory of crime, the specifics of that role and relative importance have not been fully explored. In part, this is because criminologists have just begun to seriously consider the role of genetics in their theoretical models. One reason for this is the lack of longitudinal data sets that include molecular genetic data. Fortunately, this is changing as collection of these types of data is becoming more frequent. Shanahan and Hofer (2005) suggest that the gene–environment interaction may manifest in two distinct ways. The most common way this interaction is conceptualized is with the environment playing a moderating role in the relationship between genetic factors and crime. That is, a positive social environment will impact individuals’ propensity for crime. Such propensities for crime may be genetically coded. Alternatively, genetic factors may act as a trigger, enhancing the problematic effects of stressful life conditions. Krohn et al. (2013) discuss how contextual triggers may operate in the explanation of the late-bloomer group found in some studies (e.g., see Bushway et al., 2003). Future data collection efforts increasingly need to include collection of molecular genetic data, while theoretical perspectives need to provide insight into the role genetic factors may play in the crime over the life course.
Methodologically, we continue to see the development of analytical tools allowing for the examination of the intraindividual change. One advancement in trajectory modeling that shows promise for examining the relationship among different trajectories is dual trajectory modeling. Dual trajectory modeling allows for two separate outcomes to be modeled via repeated measures over time (Nagin, 2005; Nagin and Odgers, 2010b). Dual trajectory modeling has gained traction not only due to its ability to model co-occurring comorbid outcomes, but also due to the straightforwardness and explanatory power of resulting statistical output (Nagin and Odgers, 2010b). Such output relays information about the unique trajectory groups for both measures: probabilities of group memberships for each estimated trajectory group as well as probabilities connecting trajectory group memberships across outcomes (Nagin, 2005; Nagin and Odgers, 2010b). It is these probabilities relating group memberships across outcomes that have distinguished dual trajectory modeling from other longitudinal methods, with further analyses allowing for examination of variations according to individual-level factors (Nagin and Odgers, 2010b).
In his 2011 presidential address to the American Society of Criminology, Frank Cullen stated, “life-course criminology (LCC) now is criminology” (Cullen, 2011: p. 310). He further noted the current limited utility of what he characterized as adolescence-limited criminology. Indeed, he called for continuing emergence and further development of the life-course paradigm. This research paper provided an overview of the general life-course approach, reviewed four of the prominent life-course theories, and examined alternative analytical tools for examining crime, and its causes and consequences over the life course.
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