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Longitudinal Patterns of Offending During the Transition to Adulthood in Youth From the Mental Health Systeln Maryann Davis, PhD Steven Banks, PhD William Fisher, PhD Albert Grudzinskas, JD

Abstract Arrest rates among the population of youth who have been served in child mental health systems

are known to be high during adolescence and young adulthood, but individual longitudinal patterns have not been examined. The present study used developmental trajectory modeling, a contemporary method used widely in criminology, to examine clusters of individual criminal justice involvement patterns at ages 8 through 25, from database records of 131 individuals in public adolescent mental health services. Three groups of particular concern emerged: one with increasingly high offense rates and two with moderate to high violent offense rates that did not desist. Offense patterns in these groups indicate that early intervention should occur before age 15. Some risk factors were identified. Peak offending for most groups occurred between ages 18 and 20. Implications of these findings for mental health services during the transition to adulthood are offered.

Studies that have followed youth with serious emotional disturbance (SED) from child mental

health (MH) population or special education settings into young adulthood have found alarmingly

poor functioning among these individuals. Fewer than half complete high school, and compared

to their peers, they are more likely to be unemployed and homeless and to hover around poverty

level. 1,2 One of the most striking findings in these studies is the frequency with which these youths

are involved with the criminal justice (CJ) system. 36'a Although age-related crime rates are known

Address correspondence to Maryann Davis, PhD, assistant professor, Department of Psychiatry, Center for Mental Health Services Research, University of Massachusetts Medical School, 55 Lake Ave, Worcester, MA 01655. E-mail: maryannAavis @umassmed,edu.

Steven Banks, PhD, is an associate professor in the Department of Psychiatry in the Center for Mental Health Services Research at the University of Massachusetts Medical School.

William Fisher, PhD, is a professor in the Department of Psychiatry in the Center for Mental Health Services Research at the University of Massachusetts Medical School.

Albert Grudzinskas, JD, is an assistant professor in the Department of Psychiatry in the Center for Mental Health Services Research at the University of Massachusetts Medical School.

Journal of Behavioral Health Services & Research, 2004, 31(4), 351-366. @ 2004 National Council for Community Behavioral Healthcare.

Longitudinal Patterns of Offending During Transition DAVIS et al. 351

to be high during adolescence and young adulthood in the general population (cf. references 7-10), findings from several studies suggest that arrest rates in the MH population are even higher during these ages. Vander Stoep and colleagues 11,12 compared juvenile justice system referrals between the MH population and the general population in the Seattle area and found a relative risk of 2.89 for the MH population. Vander Stoep and colleagues H also compared the CJ involvement of a community sample of youth with psychiatric disorders with youth without such disorders and found elevated arrest rates even when controlling for socioeconomic status. Finally, Wagner ~3 compared the arrest rates of special education students with SED with the arrest rates of special education students with other disabilities and found the SED group to have greatly elevated arrest rates. In addition to these differences between the MH and general populations, research indicates that adult and juvenile charges are distributed differently in the MH and general populations, 4,6 and there are some similarities to and differences from the general population in the narrow range of examined risk factors. 3,5,12J4,a Taken together, these studies suggest that the youthful MH population is at particularly increased risk of arrest during adolescence and adulthood, and that there may be important differences between offenders from the MH and general populations.

For administrators and policy-makers, the existing knowledge base about CJ involvement in the MH population is too superficial to guide efforts aimed at preventing or reducing its occurrence. Such knowledge should include data specifically on when, during childhood, adolescence, and young adulthood, this group is at the greatest risk for offending (onset, peak, and offset), and the extent of the diversity of these offending patterns.

There are no studies of longitudinal patterns of offending over time in the MH population. In addition to guiding planning and policy making, establishing a longitudinal framework for patterns of offending among the MH population provides an important conceptual linkage to the well-developed body of criminology research on criminal careers 15 or life-course studies. 16 Beginning with the landmark study "Delinquency in a Birth Cohort" by Wolfgang and colleagues, 17 the scrutiny of patterns of persistence and desistence of offending and the continuity between youthful and adult offending have occupied a central place in criminology research and theory.

Criminology research on careers of offending has also spawned a rich body of mathematical techniques 18 that have allowed modeling of these patterns. Most recently, researchers in this area have developed a new methodological and conceptual approach, termed "trajectory analysis," that describes temporal patterns and their associated individual-level risk factors) 8-2° "Developmental trajectory modeling," as this approach has been called, addresses longitudinal questions by identifying periods of greatest risk. A key feature of this analytic tool is its ability to identify and group individual trajectories into "clusters" of individuals who display similar patterns of offending over time. And, like ordinary cluster analyses, the characteristics of individuals within the trajectory clusters can be compared to identify person-level characteristics that might be associated with different trajectory patterns. As such, it allows the testing of a range of theoretical perspectives within developmental criminology.

Several studies have applied trajectory modeling to offending during adolescence and young adulthood in cohorts from the general population) 9-26 Each of these studies found between 2 and 4 different trajectory clusters among subjects with offenses, with most studies finding 3 or 4 clusters. There are some generalizable patterns. Most studies have found a pattern in which the peak probability of offending is during adolescence, with either complete or marked desistence by young adulthood. 19,21,23-25 Several studies have found a pattern of infrequent offending that shows little change across the youthful life course. 21'23'25 Some studies have also found alarming patterns of high-frequency offending that either escalate throughout the observation period, plateau in late adolescence at a high rate, or decline little after an adolescent high peak. 19'21'23,25,26

These findings support the notion that offenders are a heterogeneous, rather than homogeneous, group. However, the methodological diversity of the studies makes it difficult to explain differences in the identified number of clusters, cluster prevalence, or cluster risk factors. The sample sizes,

352 The Journal of Behavioral Health Services & Research 31:4 October~December 2004

likelihood of offending during the observed period, birth cohorts, and measures of offending vary tremendously across studies. Only one study has systematically varied one variable--sample size, and found that it did not affect the number of clusters. 25 Thus, at this time, there is no definitive answer to the question of how many clusters there are, how prevalent they are, and what the risk factors for them are in the general population. Nonetheless, the different trajectory patterns have helped test the criminological theory. These studies also demonstrate the value of examining trajectory models; different patterns reveal subgroups of offenders that appear to reflect different processes leading into and out of offending. Lastly, the studies demonstrate the need for direct comparison within study and specific methodology to draw comparative conclusions.

Despite the apparent utility of developmental trajectory modeling for examining patterns of offending in the high-risk adolescent MH population, this method has not been used in this population nor, in fact, with any MH population. The data shown here thus represent the first results of apply- ing developmental trajectory methods to research on this key population. Specifically, the present study explores trajectory patterns of CJ involvement among youth who utilized the child MH system in Massachusetts. The goal of this study is to determine whether there is evidence of meaningful subgroups of offenders among youth in this MH sample, and, if so, to characterize their patterns of offending, identify risk factors fbr and characteristics of individuals in the most concerning patterns, and explore whether the MH population may differ from the general population in the patterns of CJ involvement.

Methods

The present study examined the clinical records and automated CJ histories of 131 individuals who received intensive public MH services from one agency in the greater Boston area and had reached age 25 by December 31, 2000.

Human subjects review

Multiple levels of approval were obtained for this study. Approval and access to MH data was granted by the Central Office Research Review Committee of the Massachusetts Department of Mental Health. Approval for access to criminal records was obtained from the Criminal History Sys- tems Board of the Massachusetts Trial Court, which oversees the Massachusetts Criminal Offender Record Information system. Special permission was granted for examination of juvenile justice records. The Office of Human Subjects of the University of Massachusetts Medical School granted human subjects approval for the entire project.

Subjects

Subjects were all individuals with birth years 1968 through 1973 who were sequentially discharged between 1988 and 1994 from the agency's adolescent day, residential, or hospital treatment programs. Of these 131 subjects, 38 had clinical records that were not informative. These individuals came from one hospital unit, and they were likely to have had such brief stays that their charts were not prepared prior to discharge. There were no apparent differences in offending between those with and without informative clinical records. There were no group differences in the proportion of those arrested (x2(df= 1) = 1.53, P > . 10). Of those with a corrections record, there were no significant differences in the age of first arraignment or in the total number of charges (t(df= 81) = 0.09, 0.84, respectively, P > . 10). There were no group differences in the distributions across trajectory clusters for all charges (see descriptions later; x2(df= 4) = 3.44, P > .10), or for serious person charges (x2(df= 6) = 7.15, P > .10). Analyses that involve variables from clinical records are based on the remaining 93 subjects.


Over half of the subjects (56%) were male, a third were of minority race, and 47% were from single-parent households. Diagnostic information is based on the DSMIII-R classification system, which was in use during the observation period of 1988-1994. Discharge chart diagnoses were used. Examining all diagnoses for each subject revealed the distribution of the presence of at least one diagnosis in the following diagnostic categories: affective (50%); disruptive behavior (28%); anxiety (24%); personality (24%); substance abuse and dependence (20%); adjustment (15%); and psychotic (12%) disorders; and V codes (2%). In addition, 8% had a developmental disorder diagnosis or borderline intellectual functioning, Subjects averaged 3.1 (+3.2) psychiatric hospitalizations, and 26% had been in foster care. The average admission age was 17.4 (+1.3), and the average length of stay in the program was 69.3 (±97.5) days.

CJ data

The CJ database records the type and disposition of all charges that have been arraigned in all nonfederal courts in the state. Generally, arraignment follows rapidly after arrest (in most cases, on the next court day) and can be considered comparable to arrest. Records of all subjects were current as of December 31, 2000. Arraignments prior to individuals' 25th birthday were included.

Trajectory methodology

The data for the present analysis are at the person level and consist of a count of the number of charges each year between 8 and 25 years of age. These data are modeled using a zero-inflated Poisson model, as there are more years with a count of "0" than would be predicted using a simple Poisson model. It is also assumed that individuals in the current analysis do not all belong to a single group, but that, instead, multiple clusters of individuals exist within the current study population. To allow for this complexity (multiple clusters of individuals, each cluster with a potentially different zero-inflated Poisson model), trajectory models were used. t8 Trajectory modeling is based on a semiparametric, group-based modeling strategy that aids in the statistical analyses of patterns of offending over time when neither the pattern of the trajectory nor the cluster membership of the individual subjects is known. Technically, a trajectory model is a mixture of probability distributions that are suitably specified to describe the data to be analyzed,

Included in the present analyses was the number of charges per year of age for the period spanning 8 to 25 years of age, Previous trajectory studies that have used official indicators of CJ involvement have examined the number of charges,19 arrests,22 convictions,20,21,24,25 or police contacts. 24,25 The number of charges, arrests, and convictions were available from the automated CJ records in the present study. The number of charges was chosen as our analytic focus because it reflects the number of individual criminal acts the defendant is alleged to have committed and, therefore, more accurately reflects the individual's level of criminal involvement. This approach also allows closer consideration of the severity of the act for which subjects were arraigned than do arrests or convictions. Arrest data, for example, reflect only the fact of being taken into custody. Conviction data reflect the ultimate case disposition and may reflect plea bargains or dismissals resulting from trial issues not related to offending.

Trajectories were examined for 3 measures: the total number of all charges per year (referred to as Total CJ Involvement trajectories), the number of serious person crime charges per year (referred to as Serious Person Offense trajectories), and the total number of serious property crime charges per year (referred to as Serious Property Offense trajectories). Serious person charges consisted of felony charges involving direct physical violence toward another, including all assaults except simple assault. Simple assault in Massachusetts, in practice, reflects a threat of harm rather than an act of harm, and is not usually considered a serious crime. There were no murder or manslaughter charges lodged against the individuals in this sample. Serious property charges consisted of felony property charges involving the theft or damage of property valued more than $200. (A complete list of charges in each category can be obtained from the first author.)

354 The Journal of Behavioral Health Services & Research 31:4 October/December 2004

Statistical methods

The trajectory analysis employed the SAS procedure PROC TRAJ. 27 Univariate statistics (Pear- son's X 2 and 1-way analyses of variance [ANOVAs]) were used to analyze group differences between clusters of offenders (those with 1 or more charges). Nineteen variables from clinical records and 5 CJ variables were examined. The P for statistical significance in each group of analyses were Bonferroni corrected for repeated tests (P < .0026 for clinical variables, P < .01 for CJ variables). Clinical record variables included gender, minority status, single-parent household, birth year, diagnoses (8 groups), length of stay, admission age, restrictiveness of program (Restrictiveness of Living Environment Scale [ROLES]), 28 number of prior hospitalizations, number of prior out-of-home placements, and history of foster care. CJ variables included history of being adjudicated delinquent, total number of charges by age 25, age at first arrest, proportion of charges that were nuisance charges, and proportion of charges that were serious person charges. Trajectory modeling revealed 3 clusters of patterns for Total CJ Involvement (low, intermediate, and high; see "Results" section). The CJ variables for these 3 groups showed a consistent, ordinal relationship (later onset, infrequent, less serious charges with less serious dispositions versus earlier onset, frequent, more serious charges with more serious dispositions). Therefore, Total CJ Involvement cluster group risk factors were explored using multiple regression. The CJ involvement severity among Serious Person Offense trajectory groups was not ordinal; however, 2 groups were similar in being more violent, and 2 groups were similar in being less or not violent. Logistic regression was used to identify risk factors associated with membership in the "more violent" group.

Results

Trajectory groups

Sixty-four percent (n = 84) of the 131 subjects had juvenile or adult court records. One individual was an extreme outlier, with a total of 195 charges (more than 5 standard deviations from the mean) and was dropped from further analyses. The most common charge involved a serious person offense (23.3% of all charges), followed by less serious or "seriousness unknown" property charges (22.8%), serious property charges (20.5%), public nuisance charges (16.7%), other charges (11.0%), and less serious person charges (5.8%). Of those individuals with charges, 67% had a serious person offense and 67% had a serious property charge. A zero-inflated Poisson model with 2 curve changes was used to fit the data and the Bayesian Information Criterion was used to identify cluster groups. TM

Three Total CJ Involvement and 3 Serious Person Offense trajectories were identified (Figs 1 and 2), whereas only one Serious Property Offense trajectory was identified (Fig 3).

Total CJ Involvement trajectory groups

The largest Total CJ Involvement trajectory group (56%) had infrequent charges in young adolescence, peaking at age 19 and declining through age 25. The frequency of charges in this group was consistently intermexfiate to those seen in the other 2 groups; thus, this group was termed the intermediate group. Another group (32%), termed the low group, had infrequent charges throughout although it also displayed a relative peak at ages 19-20. The smallest group (12%), termed the high group, had the most concerning pattern. This group had frequent charges beginning at age 14, rising steadily to age 25. This group accounted for 48% of all charges.

Univariate group differences

The first set of analyses examined between-group differences across the Total CJ Involvement trajectory groups for variables that are commonly available in clinical records. Significant between- group differences were found only with regard to one variable, substance abuse/dependence. Having


Figure 1 Trajectories of charges per year from ages 8 to 25 for 84 individuals who received intensive public

adolescent mental health services and had been arraigned prior to age 25

t _

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High - - - Intermediate L o w

i i , i i i i i i i ~ i i i i I I

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

A g e , years

an identified substance abuse or dependence disorder diagnosis was more common in the high group than in the other 2 groups (X 2 = 12.8 (d f= 2), P = .002, Table 1). Using the more liberal criterion of P < .05, significant between-group differences were found for gender, level of restrictiveness of the clinical program, the presence of a personality disorder, and the presence of a disruptive behavior disorder (see Table 1). There were significant between-group differences for several CJ variables. The high group was younger when first charged, had more total and more serious person charges,

Figure 2 Trajectories of violent charges per year from ages 8 to 25 for 84 individuals who received intensive

public adolescent mental health services and had been arraigned prior to age 25

~. 2.5

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High Escalaters

8 9 10 11 12 13 14

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356 The Journal of Behavioral Health Services & Research 31.'4 October~December 2004

F i g u r e 3 Trajectories of serious property charges per year from ages 8 to 25 for 84 individuals who received

intensive public adolescent mental health services and had been arraigned prior to age 25

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Age, years

and had more people adjudicated delinquent. The low group was older when first charged, had fewer total and fewer serious person charges, and had fewer people adjudicated delinquent. Values for the intermediate group were intermediate between those of the low and high groups on these variables (see Table 1).

T a b l e 1 Differences between subjects in 3 Total CJ Involvement trajectory patterns *,t

Variable

Total CJ Involvement trajectory group

Low (n : 27) Intermediate (n = 46) High (n = 10) P

Clinical record variables Substance use disorder Personality disorder Restrictiveness Female gender Disruptive behavior disorder

Criminal justice variables Adjudicated delinquent Total number of charges Age at first arrest % Serious property crimes

0% 41.9% 66.7% .002 47.1% 10.0% 16.7% .013

3.2 + 1.7 4.3 4- 1.2 4.8 ± 0.4 .020 41.2% 15.6% 0.0% .024 23.5% 33.3% 83.3% .029

7,7% 31.9% 60.0% .004 3 .1±2 .2 13.1±11.3 64 .5±18.2 <.001 18.1 5:2.0 15.8±2.6 13.4±2.8 <.001 2.6 + 10.2 12.1 ~ 16.2 20.2 4- 13.0 .002

*Nonsignificantly different clinical record variables: minority status, single-parent household, birth year, length of stay, admission age, number of prior hospitalizations, number of prior out-of-home placements, history of foster care, presence of psychotic, affective, anxiety, adjustment, or developmental disorders; or V code conditions. Nonsignificantly different corrections variable: proportion of nuisance crimes. tCJ indicates criminal justice.

Longitudinal Patterns of Offending During Transition DAVIS et at. 357

Multivariate group differences

Multiple regression analysis was conducted using clinical record variables in an effort to identify potential risk factors that clinicians could use to identify individuals in the 3 Total CJ In- volvement trajectory groups within individuals with charges. As shown in Table 1, only substance abuse/dependence and personality disorder diagnoses differentiated the 3 groups (adjusted R 2 =

0.262, F2,4o = 8.1, P = .001, see Table 1). Adding the CJ variables to the analysis to provide an overall description of the 3 groups revealed

that the total number of charges, age at first arrest, and presence of substance abuse/dependence and personality disorder diagnoses differentiated the 3 groups (adjusted R 2 = 0.63,/74.39 = 17.6, P < .001, see Table 1).

Overall, then, those in the low group were rarely adjudicated delinquent, in part, because they tended to have their first arrest at the age of 18. The total number of charges by age 25 and the proportion of charges that were serious person offenses were both quite low. Most of the females who had an arrest were in this group. The low group did not receive substance use disorder diagnosis, were more likely to have received a personality disorder diagnosis, and were treated in less restrictive settings.

The high group consisted entirely of males, many of whom were seen as having substance abuse or dependence, rarely received a personality disorder diagnosis, and were treated in more restrictive settings. Their first offending occurred at a young age, most were adjudicated delinquent, they had proportionately more serious person charges, and they had accumulated a great number of charges.

The intermediate group fell between the low and high groups on each significant variable. It fell closer to the high group on clinical record variables (except for the proportion having a personality disorder diagnosis), while it primarily fell midway between the values for the high and low groups on the CJ variables.

Serious Person Offense trajectories

Sixty-seven percent of the 83 individuals with charges had been arraigned for a serious person offense (43% of all subjects). The largest percentage of those with serious person charges fell into the "Low Serious Person Offense" trajectory cluster (59%; see Fig 2). These individuals were infrequently charged with serious person offenses, which increased slightly to a low peak at age 18, then declined slowly to age 25. The second largest group (25%) showed a trajectory pattern of serious person charges rising rapidly to an intermediate frequency at age 18, then declining minimally through age 25. We refer to this group as intermediate persisters. In the smallest group (16%), charges rose sharply to a very high rate at age 18, then decreased until age 23, and increased markedly again. This group is referred to as high escalators. Intermediate persisters accounted for 44% of all serious person charges, and high escalators accounted for 38%.

Intermediate persisters and high escalators were distributed disproportionately among the 3 Total CJ Involvement trajectory groups (Fig 4). The low Total CJ Involvement trajectory group consisted solely of those in the none and low Serious Person Offense trajectory groups. The intermediate Total CJ Involvement group included some individuals from each of the Serious Person Offense trajectory groups, but mostly those from the low group. Most subjects in the high Total CJ Involvement group were intermediate persisters and high escalators.

Univariate group differences

Among arraigned subjects, group differences between the 4 Serious Person Offense trajectories were examined (none, low, intermediate persisters, and high escalators). The presence of a disruptive behavior disorder diagnosis was the only clinical variable differentiating the groups (Z 2 = 13.7

358 The Journal of Behavioral Health Services & Research 31:4 October/December 2004

Figure 4 Proportion of subjects from each charge trajectory group found in each violence trajectory group

among 84 youth from a mental health system with an arraignment before age 25

[] None m Low • Intermediate Persisters • High Escalators 70

60

50

~- 30 0

~ 20

10

0

Low Medium High

Charge trajectory group

(df= 3), P = .003, Table 2). Using a more liberal .05 a reveals that the proportion of females tends to be different in the groups (X 2 = 7.0 (df= 3), P = .036, see Table 2). There were significant between- group differences for all CJ variables. Having been adjudicated delinquent (X 2 = 21.4 (df= 3), P < .001) the age at first arrest, total number of charges, and the proportion of serious person and nuisance

Table 2 Differences between subjects in the 4 Serious Person Offense trajectory clusters and 2 levels of

dangerousness from among subjects with charges*

Serious Person Offense trajectory group

Intermediate High None Low persisters escalators

Variable (n = 27) (n = 33) (n = 14) (n = 9) P

Clinical record variable Disruptive behavior disorder Female gender Substance use disorder

Criminal justice variable Adjudicated delinquent Total number of charges Age at first arrest % Serious person crimes % Nuisance crimes

15.0% 30.0% 75.0% 80.0 .003 38.1% 19.0% 0.0% 0.0% .036 15.0% 38.1% 50.0% 40.0% .223

9.5% 28.6% 75.0% 100.0% <.001 3.1-t-2.8 12.5-4- 16.0 42,64-27.0 28.0-t- 19.9 <.001 17.5-4-2.5 16.34-3.0 14.64-2.1 14.74-2.9 .005 0.04-0.0 30.74-26.5 33.04- 14.5 56.24- 17.9 <.001

41.8 4- 42.6 26.5 4- 19.7 16.8 4- 10.3 7.8 :k 11.2 .006

*Nonsignificanfly different clinical record variables: minority status, single-parent household, birth year, length of stay, admission age, restrictiveness of program, number of prior hospitalizations, number of prior out-of- home placements, history of foster care, presence of psychotic, affective, anxiety, personality, adjustment, or developmental disorders; or V code conditions.


Table 3 Differences in clinical and CJ variables between subjects in the more and less violent groups *'t

Variable Less violent (n = 60) More violent (n = 23) P

Clinical record variable Disruptive behavior disorder Female gender Substance use disorder

Criminal justice variable Adjudicated delinquent Total number of charges Age at first arrest % Serious person crimes % Nuisance crimes

22.5% 76.9% <.001 28.6% 0.0% .015 26.8% 46.2% .191

19.0% 84.6% <.001 8.2 -4- 12.9 36.9 -4- 25.1 <.001

16.8 q- 2.8 14.7 -t- 2.3 .001 16.94-24.8 42.1 q- 19.4 <.001 33.4 -4- 32.7 13.3 4- 11.3 <.001

*Nonsignificantly different clinical record variables: minority status, single-parent household, birth year, length of stay, admission age, restrictiveness of program, number of prior hospitalizations, number of prior out-of- home placements, history of foster care, presence of psychotic, affective, anxiety, personality, adjustment, or developmental disorders; or V code conditions. tCJ indicates criminal justice.

charges were significantly different among the 4 groups (F3,82 = 4.7, 20.1, 26.1, 4.5, respectively, P < .01, see Table 2).

Multivariate group differences

The CJ variables did not show a consistent ordinal relationship among the 4 cluster groups. However, since the patterns of serious person charges were highly worrisome in both the intermediate persisters and high escalators, these 2 groups were combined to form the "more violent" group, whereas the none and low Serious Person Offense groups were combined to form the "less violent" group. Logistic regression was used to identify factors that differentiated these 2 groups. The 6 variables that differentiated the 4 groups in the univariate analyses were entered stepwise. A stepwise approach was chosen, as it is more appropriate than simultaneous entry of variables when the ratio of the number of cases to the number of variables is small. The total number of charges (OR = 1.09, 95% CI: 1.04-1.15) and the proportion of serious person charges (OR = 26.23, 95% CI: 1.07-642.83) were entered significantly. Since the proportion of serious person charges was so tightly entwined with belonging in the more violent group, this variable was removed from the equation to see what other variables emerged. The total number of charges remained (OR = 1.06, 95% CI: 1.01-1.11) while having been adjudicated delinquent became a more elevated risk factor (OR = 7.45, 95% CI: 1.0-55.20). These 2 factors correctly classified 88.5% of the arraigned sample.

Breakdown of the sample

Patterns of joint membership in the Total CJ Involvement and more/less violent groups create subgroups that vary in the level of concern they generate. The total sample was distributed across these groups as follows (arranged from least to most concerning): 36% of the sample had no charges, 21% were in the low Total CJ Involvement group, all of whom were in the less violent group, 24% were in the intermediate Total CJ Involvement group and the less violent group, 11% were in the


intermediate Total CJ Involvement group and the more violent group, and 8% were in the high Total CJ Involvement group, 80% of whom were also in the more violent group.

Discussion

This is the first study to apply developmental trajectory modeling methodology to a problem in MH services. This methodology identified important patterns of offending and subgroups of offenders in this population during adolescence and the transition to adulthood. It is noteworthy that more than half of this sample either had no charges or chronic, infrequent charges that rarely involved a serious person charge. Another quarter had a moderate number of charges that peaked during late adolescence and declined markedly by age 25, and had either few or no serious person charges. However, the remaining individuals (almost 20% of the sample) were members of subgroups of particular concern. There was a small group of individuals whose general offending started early, rapidly accelerated, and continued to increase, though more gradually, until age 25. These individuals were viewed as delinquents by courts and as substance abusers who needed the most restrictive care available in the MH system.

Two other groups of particular concern were the intermediate persisters and high escalators of the Serious Person Offense groups (the more violent group). Their frequency of serious person charges peaked during adolescence to a moderate to high level and then either declined minimally or declined and then peaked again in young adulthood. High escalators had a particularly intriguing pattern of charges, peaking at age 18, then declining sharply, and rising sharply again at age 23. It is possible that the decline in charges resulted from the fact that many of these youths were incarcerated or put on probation around the time when their offenses peaked, and the subsequent rise reflects release from these formal control mechanisms. This conjecture is supported by the findings of Piquero and colleagues 22 who observed higher arrest rates when they corrected their trajectories for "exposure time" by using only time when men were not incarcerated and were at risk for offending. Such adjustment with high escalators might reveal an even higher and sustained or escalating probable rate of serious person charges.

It appears that individuals in the more violent group were coming to be seen by systems as devel- oping antisocial traits during adolescence; courts were more likely to adjudicate them delinquent, and MH settings were more likely to label them as having disruptive behavior disorders. Those in the more violent group were also charged with more crimes in general.

Moffitt 29 observed that there were primarily 2 groups of antisocial individuals: those who express antisocial behavior primarily in adolescence and desist in early adulthood and those who begin antisocial behavior in early childhood, which continues through early adolescence and into and through adulthood. She labeled these 2 groups adolescent-limited and life-course persistent, respectively. She theorized that life-course persistent antisocial behavior results from a nexus of children's biological vulnerability (ie, difficult temperament, neuropsychological deficits that produce antisocial behavior), being raised in families with the same vulnerabilities that exacerbate or are unable to counter these behaviors, and living in impoverished circumstances where institutions such as schools are ill prepared to counter their antisocial behavior. These children are left with fewer social skills and less access to successful interaction with prosocial peers. There is a "constant process of reciprocal interactions between personal traits and environmental reactions to them ''29(p684) that turns a personal attribute into a consistent syndrome that can gain new components through development. Moffitt pro- poses that this kind of antisocial behavior is psychopathological, and notes that numerous comorbid conditions have been associated with it, including hyperactivity and learning disabilities.

Similarly, Patterson and colleagues 3° have theorized about early and late starters. In their theory, early starters result from a pattern of parenting that reinforces only negative social behavior, resulting in young children who enter school environments with behaviors that their peers reject. As a result, they gravitate toward other "peripheralized" peers who then begin a process of "training"


antisocial behavior that, in turn, leads to early offending that, in the absence of parental supervision, escalates during adolescence. There is little desistance in this group because by young adulthood the behaviors have become an automatic response, and there are few positive behaviors to reinforce.

In the current sample, the pattern of offending in the high Total CJ Involvement group, intermediate persisters, and high escalators fits the offending profile of life-course persistent or early onset individuals. The percentage of individuals in these 3 categories is significant (19% of the sample, 30% of those with charges). However, because of the methodological diversity in previous trajectory studies, described in the beginning of this article, it is virtually impossible to determine whether this rate is higher than that seen in the general population. Further, the archival records did not contain enough information to determine whether the causal processes proposed by Moffitt, 29 Patterson and colleagues, 3° or Laub and colleagues 19,31,32 are at work with the MH population. Clearly, a direct prospective comparison of offending and causal factors in the MH services population and the general population in a large sample would help clarify if offending in the MH population shows the same pattern and is caused by similar factors. Such a study would help determine when prevention efforts are needed, with whom, and whether prevention efforts found efficacious in the general population would be likely to succeed with the MH services population.

The pattern of offending among individuals in the more violent group who were in the intermediate Total CJ Involvement group is interesting. These individuals showed a decline in the number of total charges as they enter young adulthood, while serious person charges continued or even escalated, suggesting that they may become more specialized in serious person crimes. Specialization is a phenomenon seen in the general offending population. 15,33 In contrast, individuals in the more violent group who were in the high Total CJ Involvement group continued to have increasing numbers of all types of charges up to age 25. This finding demonstrates the utility of examining trajectories of different types of charges.

In fact, unlike serious person charges, serious property offending was a homogeneous pattern in this sample of youthful MH service recipients. It appears that, among these youth, being charged with serious property charges is uniformly an adolescent-limited phenomenon, showing a rise and peak during adolescence and a decline in young adulthood. This also suggests that the frequency is similar across individuals but different across ages; all individuals showed the same pattern at the same rate, regardless of the frequency of other offenses they were charged with. Thus, rather than there being a group of individuals whose overall offending is adolescent-limited in nature, as Moffitt posited and found, 21,29 being charged with serious property charges appears to be adolescent-limited in nature in this population. Perhaps, property offenses are considered a more socially acceptable form of rebellion during adolescence, but are considered immature or nonproductive after adolescence. In contrast, it is clear that for some individuals, violence continues to serve a purpose well after adolescence.

Limitations

This study has several limitations. The sample size was small compared to that in other trajectory studies of CJ involvement, and this sample would have great difficulty identifying statistically significant trajectory patterns occurring in less than 5% of youthful MH offenders. Even with this lim- itation, the study was able to identify 3 significantly different subgroups of youthful MH offenders, suggesting the study had sufficient power to find broad differences in offending patterns.

However, there may be other important trajectory patterns, embedded in small subpopulations, that this study would be unable to identify. For example, studies that have examined trajectory patterns of official crime in males and females have found it important to have a much larger sample of females and to conduct these analyses separately because the level of antisocial behavior in females is relatively low, obscuring important differences among females when combined with data


on males. 24 The one study that has examined sex differences in trajectories of official crime during adolescence and young adulthood found very different trajectory patterns in boys and girls. Only 15% of girls offended; 10% showed a very low-rate adolescent-peaked pattern and 5% showed a higher rate of offending, which was only a little higher than and paralleled the rate in the male low-rate chronic group. Thirty-nine percent of males offended, forming 4 trajectory clusters, 1 of which comprised only 1% of the total male sample. The findings from this large study (n = 3000 females and 1000 males) demonstrate the inability of smaller studies, such as the current one, to identify smaller subgroups of offenders. Thus, because of our limited sample size, we did not explore gender-specific trajectory models.

The available variables in the clinical records were also quite limited and did not address many of the social factors that have been found to predict antisocial behavior in the general population, such as affiliation with antisocial peers, 34 attachment to institutions of informal social control, 32 limited parental supervision, 35 or coercive and aggressive parent-child relations. 36 Clinical diagnoses were not research derived and so would best be interpreted as reflecting how the system viewed the individual, rather than a more factual reflection of their MH status. Further, it may be that levels of specific symptoms, such as levels of externalizing symptoms, are more important than diagnoses, as was found to predict incarceration in a national sample of youth in MH and special education settings (E. Brown and R Greenbaum, unpublished data, 1994),

Lastly, measurement of CJ involvement was limited to nonfederal court involvement that occurred within Massachusetts. Data on offenses committed in other states were not available. Also, official measures of crime are a conservative measure of actual offending behavior since much offending behavior does not come to officials' attention or result in specific charges. Because of these factors, the level of CJ involvement measured in this study is a conservative measure of actual criminal behavior. Yet, it is also likely that some youth with SED lack some of the skills that the general population has to conceal illegal behavior or to "talk their way out of" being charged; thus, this may be a less conservative measure of criminal behavior in this particular population. Nonetheless, it is a fairly accurate measure of official involvement in the CJ system.

Implications for Behavioral Health

Because of the above limitations, and the preliminary nature of this work, implications are offered with great caution. Overall, these findings highlight the need for MH and CJ systems to work together to prevent and reduce offending during adolescence and the transition to adulthood. Each system has expertise to offer the other. Males who are in late childhood or early adolescence (13 and younger), have already accessed both systems, particularly if they also have a substance use problem, would seem to be especially appropriate candidates for targeted efforts. If they are located in the juvenile justice system, addressing their MH issues may help reduce their offending. 37 If they are in the MH system, linking them to effective crime reduction interventions may be beneficial. These crime reduction interventions may include multisystemic therapy, 38 multidimensional treatment foster care, 39 or other evidence-based practices.

Another profitable direction might be the development of mechanisms for diverting these individuals from CJ processing to MH services. Such mechanisms would require that actors in the CJ system, including police, probation officers, and judges, be aware of the trajectories of offending these individuals are likely to display. Many jurisdictions are actively pursuing such mechanisms for adults. 4° Such formal MH courts or diversion programs are not yet up and running in juvenile court. The history of juvenile court as a treatment access point has been well documented. 41 Data on the outcome of such efforts aimed at juvenile interventions could be factored into the development of a range of diversionary programs and, where such intervention is not legally viable, into decisions regarding the disposition of youthful offenders' criminal charges.


The findings of this study and of similar lines of research have important implications for MH system policy and practice. The ages of the peak probability of being charged, 18 through 20 years of age, coincide with the ages at which systems often identify youth as no longer being "children?' Typically, child MH, child welfare, and special education services cannot be provided to individuals beyond ages 18 through 22, depending on each state's and agency's policy. Supportive services at those ages are offered by adult MH, vocational rehabilitation services, substance abuse services, and perhaps homeless services. However, there is evidence that many youth in the MH system cease receiving any supportive services once they "age out" of child systems. 42-44 There are adult MH eligibility criteria, often including a diagnosis of a severe adult mental illness, that make it less likely that youth from the child system will be eligible for adult MH services. 45 For the youths who comprise the most concerning of the trajectory groups we have identified here, the loss of services at these ages would seem most unfortunate. Lamentably, this study could not examine the relationship between service receipt and offense trajectories. It is thus unclear whether a loss of services contributed to the probability of offending. However, the timing of CJ involvement peaks suggests that barriers to the receipt of ongoing services as youth age out of the children's system could impede access to services that might help reduce the offending behavior.

This point is reinforced by the fact that, in general, desistence was nonexistent or slow after reaching the peaks at ages 18 through 20 for the majority of youth who became involved in the CJ system in this study. Criminology theorists have posited several reasons why offending adolescents desist (eg, references 19, 29, and 34). Generally, these theories relate desistence to changes in social status that occur when adolescents leave school and enter adult life. Such changes include a reduction in exposure to other antisocial adolescents, gaining access to the adult freedoms and privileges that youthful offending mimicked, or entering a new set of social circumstances, such as becoming a valued worker or a loved romantic partner or spouse, which imposes new informal social controls on antisocial behavior. The reduced desistance seen in this MH sample suggests that the social factors believed to draw young adults out of youthful offending may be less effective in, less available to, or may not have an impact until later in life among youth in MH systems. These findings again argue that rather than reducing the availability of services at these ages, making services more available to this population, particularly services that focus on helping to connect them to experiences and relationships that foster successful passage into adulthood, might foster more rapid desistence. In fact, general transition support programs for the MH population, such as the Jump on Board for Success program in Vermont, have shown a reduction in CJ involvement. 46 Nonetheless, studies that directly examine the relationship between service receipt and CJ involvement, and the impact of specific services on CJ involvement, are needed to confirm the value of services or service continuity in preventing or reducing CJ involvement.

The importance of fostering prevention and desistence is underscored by the fact that offending at ages 18 and older brings more serious consequences, since individuals are treated by the courts as adults rather than as juveniles. Jail diversion and other such programs seek to reintegrate offenders with mental illness into the MH system rather than continue their prosecution. However, those who age out and lose MH services around age 18 are unlikely to be referred to such programs. They will not appear on local MH systems' active client rosters and may seem less seriously ill than other adults, particularly those with major psychiatric disorders, who come to the attention of the police and courts. They may thus incur more serious dispositions.

Conclusions

Most youth receiving intensive public MH services are arrested at some point during their young lives. There are subgroups of offenders who display particularly concerning patterns of CJ involvement that suggest that MH and CJ systems need to work in concert to prevent and reduce offending in early adolescence and that particular attention should be applied to facilitating a successful transition


into adult roles. Nationally, transition support services are scarce in MH systems, and many youth are discharged from the MH system upon reaching the upper age limit for children's services. Ad- dressing this system issue may markedly improve arrest rates during the transition to adulthood by youth in the MH system.

A c k n o w l e d g m e n t s

The authors thank Rebecca Wolf, Andrew White, and David Greenidge for their careful data entry. Work on the manuscript was supported by a contract from the MA Department of Mental Health.

N o t e

a. Brown E, Greenbaum P. Recent findings from the National Adolescent and Child Treatment Study: Research related to juvenile justice and incarceration. Unpublished manuscript; 1994.

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