The author(s) shown below used Federal funds provided by the U.S.

Department of Justice and prepared the following final report:

Document Title: Evaluation of the Los Angeles County Juvenile

Drug Treatment Boot Camp, Executive Summary

Author(s): Sheldon X. Zhang Ph.D.

Document No.: 187678

Date Received: April 5, 2001

Award Number: 96-SC-VX-0003

This report has not been published by the U.S. Department of Justice.

To provide better customer service, NCJRS has made this Federallyfunded grant final report available electronically in addition to

traditional paper copies.

Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect

the official position or policies of the U.S.

Department of Justice.
AN EVALUATION OF THE LOS ANGELES COUNTY 

JUVENILE DRUG TREATMENT BOOT CAMP 

--EXECUTIVE SUMMARY-- 

Principal 'Investigator: Sheldon Zhmg, P1i.D. 

California State University, San Marcos 

OVERVIEW 

This report presents findings from an evaluation of the Drug Treatment Boot 

Camp in Los Angeles County. To overcome common methodological problems of earlier 

studies, this project applied both cross-sectional and longitudinal strategies with a 

combination of official records and self-report measures to assess the effectiveness of the 

program with data gathered at different points in time. Multiple outcome measures were 

used to gauge program effectiveness in reducing recidivism, probation revocations, self- , 

report delinquency, drug use, participation in conventional activities, and changes in prosocial attitudes. 

The Los Angeles County Drug Treatment Boot Camp (DTBC) is mong the 

longest continuous-nmning boot camp programs in the nation since its inception in 

October 1990. Unlike most other boot camps found in published literature, the DTBC 

was created neither to alleviate institutional overcrowding, nor to attract state or federal 

funding. The program reflected the Los Angeles County Probation Department's belief in 

its potential as an effective method to treat drug-abusing.offenders in its juvenile 

facilities. The program has been a part of the regular county fbnding to the Probation 

FINAL.REPQRT 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
E Department and has been able to sustain its operation till today, long after many ‘r 

programs elsewhere folded after the federal or state funding had been exhausted. 

ML~I like boot camps elsewhere, the DTBC emphasized discipline and 

obedience. Routine activities included individual counseling, drilling, marching and 

physical training. In order to reduce fbttre offending, particularly on drug offenses, the 

program focused 011 building participants’ respect for authority, self-discipline, selfconlidence, life sltills, and fostering a sense of pride and accomplishment at graduation. 

The program eilrolled only male offenders between the ages of 16-1 8, who were either 

documented or alleged drug users with sustained petitions by the juvenile court for,nonviolent and non-sex offenses. 

PROJECT OBECTIVES AND METHODS 

This project had three main goals and three corresponding data collection 

components. First, to assess the long-term effect of the boot camp program on recidivism 

using official records only, a comparison was made between boot camp and traditional 

ccmp graduates. Because of the DTBC’s long operation histoiy, this study was able to 

gather both juvenile and adult records of the sampled subjects with an average post camp 

period of 4.25 years, the longest hong all known studies. A case matching method was 

used in the sampling process based on the stratification of several major variables (i.e., 

age, length of camp stay, prior arrests, and ethnicity); two additionaI variables were held 

e 

constant-subjects were first time on camp orders and all were male. Records of the 

selected subjects were obtained from the Los Angeles County Juvenile Automated Index 

(JAI) and the California Law Enforcement Tracking System (CLETS). 

2 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
-. Second, to augment almost exclusive reliance on the use of official records in 

most published boot camp studies, this project adopted a widely used self-report 

0 instrument to gather delinquent and criminal activity information from offenders’ self 

accounts. A comparison of post-camp delinquency involvement was made between 100 

boot camp and 100 traditional camp youngsters over 12 months. For the second 

component of the project (the 12-month seEf-report samples), the case matching method 

was attempted but abandoned because of the much smaller sampling frames and the 

difficulties in locating and interviewing camp graduates after they left camp. 

Third, this project included a longitudinal eornponent (the pre-and-post cohort), 

in which a group of participating youngsters (N=89) was interviewed twice, once at the 

camp entry and once six months after they left the camp. 

The self-report data were collected through telephone interviews at a central 

location under close supervision to ensure consistency in interview protocols. Subjects 

were paid a nominal fee for their participation. In addition to the self-report data, official 

records were gathered for all three components. 

e 

Data analysis consisted of three themes. First, the project’s goal of producing 

findings that can be shared with correctional agencies, program administrators and policy 

makers led to an emphasis on the production of descriptive statistics, such as simple 

frequency tables. Second, bivariate comparisons were used to establish the degree of 

similarities (or differences) between the boot camp and traditional camp systems in terms 

of their recidivism prevalence and fi-equency. Multivariate analysis was performed when 

appropriate to examine the extent to which demographic variables, life circumstances, 

and prior history of the subjects influenced the outcomes. 

3 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
t 

FINDINGS 

a The matched samples @e., the first component) included 427 boot camp 

graduates and 427 comparison camp youngsters. The re-offending patterns were almost 

identical in both gro~ips, The majority of the subjects in both groups (about 85%) were rearrested within five years after they left the cmps; and about two thirds of them had 

either sustained petitions (for juveniles) or convictions (for adults). The only major 

difference was that boot camp graduates were significantly more likely to have probation 

revocations than their comparison, which was most likely due to the intensive supervision 

afforded to boot camp youngsters upon their camp exit. 

An OLS regression analysis was conducted to examine what variables in official 

records could account for the patterns of arrests and sustained petitions for both samples 

and to determine whether participation in the boot camp would bear any impact on any of 

the outcomes. The most salient predictor for post-camp arrests was prior arrest history, 

which is in line with most criminology literature. The time being out of camp was also an 

important predictor. Predictably, the longer out-of-camp period the more re-arrests. The 

number of probation violations during the post-camp phase was also a significant 

predictor of arrests. African-Americans were significantly less likely to have sustained 

e 

' petitions than Whites or Hispanics. 

fn short, participation in the boot camp program had no appreciable effect on 

post-camp recidivism whatsoever. 

For the 12-month self-re~ort sample (the second component of the study), both . 

groups were very similar in their post-camp arrest rates, sustained petitions, and 

a 4 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
? probation violations. There was a general decline in self-reported delinquency 

involvement for both groups in terms of average number of o€fenses that were committed 

during the year after. However, tlie between-group patterns remained largely unchanged 

on non-drug related offenses. 

Because the DTBC was targeting drug abusing offenders, self-report measures of 

drug offenses were analyzed separately. Both groups experienced a general decline drug 

related offenses. Furthermore, the pre-camp differences between the groups, which were 

obvious and drastic, were visibly reduced during the follow-up period. 

On community integration measures, both groups were similar on employment 

and gang affiliations. On school enrollment, more comparison subjects were attending 

school than those of the boot camp graduates. The differences, although significant, coLtld 

be attributed to the age disparities, in which there were significantly more older subjects 

in tlie boot camp group. The comparison subjects were also more likely to participate in 

0 org&ized sports than the boot camp subjects. 

This study also gathered data on attitudinal changes. Psychometric scales were 

used to measure changes on four attitudinal dimensions: (1) self-esteem, (2) perceived 

hture prospect, (3) mastery of one’s own destiny, and (4) attitudes towards authority. A~I 

scales met ncceptabIe internal consistency tests. Despite the structural and programmatic 

di.fferences in these two types of camps, no significant differences were found between 

the two groups on any of the attitudinal measures. 

Although intensive aftercare and supervision were to follow these youngsters after 

they left the camp, boot camp subjects did not receive fmy more services than the 

comparison group, except in substance abuse educatiodcounseling. As expected, boot 

5 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
b camp subjects received far more drug and alcohol related couiiseling than the cornpslrison 

group. Despite the lack of any consistent improvement in behavioral and attitudinal 

measures, significantly more boot camp subjects reportedly enjoyed their camp 

experience than the comparison subjects. 

Multivariate analyses also failed to show that the treatment type (Le., boot camp 

vs. non-boot camp) had any significant influence on any of the outcomes. Post-camp selfreport clelinquency was influenced by such variables as post-camp drug offenses, precamp delinquency involvement and drug offenses, and exposure to substance abusing 

living environment. Confidence in one’s future prospect and in control of one’s destiny 

appeared to reduce delinquency involvement. However, stress and negative relationships 

at school appeared to increase post-camp delinquency involvement. 

Post-camp drug offenses appeared to be influenced by a minor’s pre-camp 

involvement in drug offenses and other post-camp delinquency activities. On the other 

@ hand, school enrollment and attachment to parents appeared to reduce a youngster’s postcamp involvement in drug related activities. 

For the Pre-and-Post Cohort, data were gathered from two observaftion periods- 

-six months prior to their camp entry and six months after they left the camp. 

Tremendous difficulties were encountered during the follow-up of the subjects who had 

been interviewed at the first wave (TI). The post-camp interviews were conducted in a 

. ltirne frame fa longer than planned. On average, there were 3 5 1 days in lapsed time 

between camp exit and the second interview. Therefore the second wave of interviews 

covered a much longer observation period. Case attrition was also substantial; cases 

dropped from 137 at TI to 89 at T2. Except for a small number of the subjects who were 

.. 

6 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
in the state penitentiary, the majority of the lost cases either declined to be interviewed 

for the second time or could not be found. An analysis of the pre-camp delinquency 

b 

involvement and drug offenses among the attiition cases did not reveal any statistically 

significant differences from those who completed the second wave interviews, 

When comparing the self-report delinquency involvement for the two observation 

periods, significant improvement was found on most outcome measures. On nearly all 

self-report delinquency indices (with the exception of drug use), these participants 

showed significant improvement during the two observation periods (Le., six months pior 

to their entry into the boot camp and the period since the left the cmp). These outcome 

measures included status offenses, vandalism, theft, violent offenses, and drug sale. 

However, there were no appreciable differences on the majority of community 

integration measures, including school enrollment, involvement in gangs, and 

employmeiit. Their participation in organized sports appeared to have significantly 

. decreased for the post camp period. 

Just as in the 12-month self-report component, psychometric scales were used to 

measure attitudinal changes on self-esteem, perceived hture prospect, control of one’s 

destiny, and attitudes towards authority. All scales met acceptable internal consistency 

tests. On the family relationship subscafe of the self-esteem measures, the youngsters on 

average held significantly more positive attitudes towards their parents (caretakers) at 

Time 2 than they did at Time 1. They also help significantly more positive attitudes 

towards their teachers. 

Multivariate analyses revealed few variables in the self-report measures as 

significant predictors on any of the outcome measures. Self-report delinquency 

7 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
ilivolveinent appeared to be significantly influenced by the level of pre-camp delinquency 

iiivolvement and perceived lack of s~ipport from parents when tlie respondent was in s. 

trouble. Post-camp involvement in drug offenses, however, was influenced significantly 

by the level of pre-carnp drug offenses and other post-camp delinquency, 

DISCUSSION 

The present study utilized both official and self-report methods to gather data at 

multiple points in time to assess from different angfes tlie effectiveness of the Drug 

Treatment Boot Camp program in Los Angeles County Probation Department. Based on 

various statistical' analyses and comparisons, the boot camp treatment approach was 

probably not any more effective than that of the traditional camps in reducing subsequent 

oEicial as well as self-report delinquency. Although there were many signs of 

improvement in post-camp deljnquency and substance abuses for the boot camp 

participants, it is diEicuIt to attribute any of the improvement directly to the boot camp 

treatment approach. Instead, much of the improvement were attributable to other 

exogenous variables such prior delinquency and drug involvement. 

The findings from this project support the conclusion from the existing literatme 

that juvenile boot camps as a treatment model are probably not any more effective than 

. most existing juvenile programs. Whether boot camp continues to remain a viable 

alternative for young adult and juvenile offenders depends mostly on what the program 

administrating agencies intend to accomplish. It is probably unrealistic to expect this me 

of short-term shock treatment, as implemented and administered in Los Angeles County 

8 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
or most other locales, to be any more effective than the existing traditional facilities h 

reducing recidivism. 

t 

Since. boot camps appeared more than 15 years ago, many studies have been 

conducted and the findings consistently point to the lack of their effectiveness in reducing 

recidivism or increasing pro-social activities. The present study argued for alternative 

data collection methods and analytical strategies to improve our understanding of boot 

camps as a treatment model through the use of self-report measures and the assessment of 

noli-programmatic factors. However, results from the self-report data in the present study 

have probably added additional confusion to the pool of findings that are already 

complex and difficult to interpret. 

The search for information to explicate the functions of different program 

components and explain why some offenders succeed while others fail requires 

researchers to resist the temptation to address the simple question: “Does a boot cap 

work?” Such a blanket qiiestion increases the chances of drawing misleading and 

simplistic conclusions, which will in turn lead either to srimmslrily dismissing or to 

unduly extolling boot camps as a correctional option. Although the present study built its 

rationale on methodological issues, it is unreasonable to believe that a change in research 

design will drastically change the findings. 

Based on site visits and conversations with the participants, staff and 

administrators, the Drug Treatment Boot Camp was indeed different in its operation from 

the other traditional camps in Los Angeles County, including such features as 

parmiiitary organization, rituals (i.e., salutations arid roll calls), ceremonies, uniforms, 

drills, and summary punishments. On the other hand, this study did not find the DTBC to 

9 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
rn be any different from other camps in traditional services such as counseling, parental 

involvement, and educational activities. The lack of differences in these therapeutic 

activities or in the combination of therapeutic and regimented activiti,es may account for 

the lack of differences in outcomes between boot camps and traditional carnps. 

At a policy level, the lack of positive effects in most studies begs all of those in a 

position to make programmatic decisions to think through the issue of why anyone 

should expect boot capps to be effective. The question for policymakers here is not wily 

boot camps have failed to produce successful outcomes, but why we should expect them 

to be effective in the first place. Lacking a clear conceptualization of what effects a 

treatment program is expected to produce and how it is supposed to produce them, most 

policymalters thus far have been relying on their political convictions or “common-sense” 

to promote treatment programs for youth as‘well as adult offenders. This “gut feeling” 

approach in designing and implementing correctional programs will inevitably collide 

e wid1 empirical verifications later on. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
AN EVALUATION OF THE LOS ANGELES COUNTY 

JUVENILE DRUG TREATMENT BOOT CAMP 

United States Department of Justice 

Office of Justice Programs 

National Institute of Justice 

Grant # 96-SC-VX-0003 

February 2000 

Principal Investigator: Sheldon X. Zhang, Ph.D. 

Associate Professor 

Department of Sociology 

California State University 

San Marcos, CA 92096-0001 

Tel: (760) 750-4162; Fa: (760) 750-3551 

Email: xzhang@csusm. edu 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
FOREWORD 

This project was conducted under Grant No. 96-SC-VX-0003 awarded by the National Institute 

of Justice, Office of Justice Programs, United States Department of Justice. Points of views in 

this docuinent are those of the author and do not necessarily represent the official position or 

policies of the United States government. 

0 

SUGGESTED CITATION 

Zhang, S. X. (2000). An Evaluation of the Los Angeles Cozrnly Probation Juvenile Drug 

Treatment Boot Cump. San Marcos, CA: California State University at San Marcos. 

ii 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
ACKNOWLEDGEMENT 

This study would not have been possible without the collaboration ofthe Los Angeles Probation 

Department where the evaluation took place. The author is gratefill to the following individuals 

for their participation and contribution to the design, implementation, analyses of the data, and 

the coinpilation of the final products: 

Los Angeles County Probation Department: 

Robert Polakow, Probation Director of Camp Munz (former) 

Paul Higa, Deputy Chief Probation Officer 

Celso De La Paz, Senior Research Analyst 

Soimy Gonzales, Supervisor of Juvenile Automated Index 

Consultants to the Proiect: 

Malcolm Klein, Professor Emeritus, University of Southern California 

Daniel Glaser, Professor Emeritus, University of Southern California 

Michael Newcomb, Professor, University of Southern California 

Proiect Manager: 

Voncile B. Gowdy, National Institute of Justice, U.S. Department of Justice 

Data Collection Team: 

Donnmwie Cruiclcshank, Research Assistant 

Julie Weathersby, Research Assistant 

Jacob Stowell, Research Assistant 

Richard Serpe, Director, Sbcial and Behavioral Research Institute 

Allen Risley, Associate Director, Social and Behavior Research Institute 

California State University, San Marcos 

iii 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
ABSTRACT . 

This report presents findings from an evaluation of a well-established juvenile drug e 

treatnient boot camp in Los Angeles County. In an effort to overcome common methodological 

probleins of earlier studies, this project used a combination of official and self-report measures to 

assess the effectiveness of the program with data gatliered at different points in time. While this 

study found some significant improvement in a few outcome meqsures based on self-report data, 

it is difficult to attribute any of the progress to the boot camp treatment program. Instead, most of 

the important outcomes could be explained by such non-programmatic variables as prior 

delinqueiicy involvement, substance abuse activities, positive family relationships and attitudes. 

The boot camp graduates in this study were almost identical to those of the comparison 

group iii re-arrests or convictions. The oiily significant difference on official measures was that 

boot camp participants were more likely to have probation revocations than the comparison, 

Implicatioiis for future research strategies and correctional policy were also discussed. 

1 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
STATEMENT OF THE PROBLEM 

Background and Current Knowledge of Juvenile Boot Cumps 0 

Since their iiiception in 1983 in Georgia and Oldahorna (MacKenzie, 1993), the idea of 

“shoclcing” criminal offenders into conformity with regimented activities resembling those of 

military basic training has been embraced by many politicians and practitioners Elcross the nation 

(Cronin, 1994; MacKenzie et al., 1995; Morash and Ruder, 1990; Hunter et al., 1992). Despite 

the paucity of empirical data supportive of their effectiveness, boot camps have spread across the 

nation. Most states, if not all, have some forms of regimented paramilitary tieatment programs 

designed to accommodate young adult or juvenile offenders (Granslcy et al. 1995; Souryal and 

MacKeiizie, 1995; Cronin, 1994; MacKenzie, 1993). 

Granslcy et d. (1995) attributed their popularity largely to the images created by the 

media. The public likes the image of rigid, military-style operations being applied to young adult 

offenders who are made to work hard, behave obediently, and display good manners and respect 

for authority (Polsky and Fast, 1993). For tlie first time in the lives of many of the participants, 

collective gods have to precede individual needs and desires. Boot camps not only appeal to 

conservatives who favor punishment and discipline, but also to liberals who are attracted to the 

many rehabilitative components that many program administrators touted (Anderson et al., 

e 

1999). 

i Most boot carnps are for young adults convicted of non-violent crimes (MacKeqie, 

1993). While in the camp, they are divided into platoons and follow the orders of the drill 

instructor. Those who complete the programs go through formal graduation ceremonies designed 

to give them a sense of accomplishment and confidence to start their lives anew. However, 

. beyond the military atmosphere characterized by its drills, physical training and work, boot ‘ 

2 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
camps differ considerably in their eligibility criteria, size, lengths of confinement terms, intensity 

of post-program supervision, and typ’e of aftercare. 

Nevertheless most boot camps appear to share similar system-level goals--rehabilitating 

a 

offenders, providing alternatives (&s an intermediate sanction) to long-term incarceration, and 

reducing piison/jail crowding. In a survey of boot camp administrators (MacKenzie and Souryal, 

I99 I), rehabilitation, recidivism reduction, and drug education were ranked the most highly as 

program gods, followed by reducing crowding, developing work skills and providing a safe 

prison environment, Deterrence, education and drug treatment were judged as somewhat less 

important, while the least important goals iizcluded punishment and vocational training. 

In a more recent survey of juvenile boot camps, MacKenzie mds her team also found that 

many cmps also shared similar external dimensions, such as structure and control (Gover et al., 

1998; Styve, et al., 1998; Mitchell et al., 1998). Based on interviews with administrators and data 

extracted from official documents, MacKenzie and her team found the juvenile boot camps to be 

more structured and with more military types of physical tiaining. While few differences were 

found in therapeutic resources, juveniles in boot camps participated in more physically oriented 

activities (Gover et al., 1998). Program participants reportedly perceived boot camp conditions as 

more structured, controlled, and safer than those of traditional juvenile camps. Boot camp 

juveniles also perceived their environment as providing more therapeutic programming and 

. 

a 

transitional programming (Styve, et d., 1998). 

While there was some regional variation, in comparison to traditional juvenile 

institutions, boot camp staff perceived the paramilitary environment as having more activity, 

control, structure, caring, treatment options, and a higher quality of life (Mitchell et al., 1998). 

FLirthemore, boot camp staff perceived their facilities as having less dmger for the youngsters 

3 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
a11d staff, as well as having less general environmental danger and risks to.residents. 

Additionally, boot camp staff perceived their work as more satisfying and supportive, with better 

conimunication between staff and administrators, and experienced less stress than staE from 

comparison facilities. In short, from the perceptions of staff, the conditions of confinement in 

a 

boot camps were more favorable than that of traditional facilities, 

Despite these structural and thematical differences between boot camps and traditional 

correctional programs, the findings 011 their treatment efficacy from the empirical studies (those 

available in published literature) have not been promising. Although boot camp graduates have 

been found to have favorable changes in their attitudes and generally describe their program 

experience as positive (MacKenzie and Shaw, 1990; Ransom and Mastrorilli, 1993; Htmter et al., 

1992), few programs have produced "hard" evidence of effectiveness on the variable that all 

correctional agencies are most concerned with, that is, reduction in re-offending. According to 

0 the most comprehensive study to date by MacICenzie et al. (1995), a comparative analysisof boot 

camps in eight states, the outcomes and their possible explanations are far more complex and 

muddled than my practitioner or policy rnalcer wo~ild want to know. In summary, boot camp 

graduates do not perform better or worse than their counterparts in the conventional facilities; 

and judgment of boot camp effectiveness has to be made by examining individual programs ad 

their components (MacKenzie et al., 1995). About the only summarizing statement one can make 

about boot camps is their lack of any clear consistent effect whatsoever. These findings are akin ' 

to those of many other intermediate sanctions (such as electronic monitoring or intensive 

probation supervision that were once popular in the 80s and early OS), which revealed no 

appreciable impact on recidivism (Zhang et al., 1994; PetersiIia and Turner, 1990). 

4 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Boot camps have drawn criticism from several fionts. Some contend that those who have 

bought into the idea of "shock" incarceration are more interested in the potential benefits of early 0 release and additional funds for treatment programs, the so-called "Machiavellian" point of view 

(MacKenzie and Souryal, 1995). As long as there are no obvious dangers, agency administrators 

will operate boot camps to accomplish two things: 1) early release to alleviate the overcrowding 

situation; 2) to attract government fimding for treatment, which would otherwise not be 

available. Whether the program is effective is secondary to their political pragmatism. Therefore 

few prograin administrators are concerned about if their program can reach the goals and 

objectives tliat they set out to accompIish. In fact, Gover et al. (1 998) found in their national 

survey that few institutions With boot camp programs had access to any outcome information, 

Other scholars suspect that the harsh and confrontational environment prevents the 

formation of any positive interpersonal relationships, thus reducing the likelihood of positive 

change (Moras11 and Rucker 1990). Many psychologists, experienced in both corrections and 

behavioral change believe that the paramilitary atmosphere may actually be detrimental to 

treatment (Styve et al., 1998). To them, positive interpersonal relationships, which are considered 

a necessary condition to any positive behavioral change, are not Iilcely to form in a 

confrontational environment (Andrew et al., 1990). 

a 

Issues of Eurlier Studies 

While much of the published literature debates the efficacy ofboot camps as'a treatment 

option from various philosophical as well as empirical orientations, few have raised questions on 

whether the methods employed in most evaluation studies can adequately assess boot camp 

effectiveness (Zhang, 1998). For instance, several studies were descriptive in nature and based on 

5 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
rattlier brief personal observations or inmate anecdotes (see Polsky and Fast, 1993; Ransom'and 

Mastrorilli, 1993). None thus far have employed a true experimental design, which allows 

randomized assignment of subjects to treatment and control groups. There was a failed attempt 

by the California Youth Authority (Bottcher, 1995), in which the original random assignment 

design was compromised by such factors as a lack of consensus on screening criteria, inadequate 

0 

' screening to generate cases for the control group, incomplete official records, and incomparable 

observation periods between treatment and control groups. Altl~ot~gh researchers have attempted 

to overcome the experimental design issue by using matching samples and multivariate statistics 

to compensate for the lack of random assignment, the results are always vulnerable to alternative 

interpretations. 

Several other issues are associated with early studies on boot camp programs that warrant 

further discussion, First, most boot camp studies were based on state-run programs funded by 

temporary legislative mechanisms or federal grants. Most of these programs were short lived and 

tended to fold soon after the funding was exhausted. Although there have been a few boot camps 

run by loca1 jurisdictions (MacICenzie, 1993), there is little empirical iiiformatioii on how countyoperated programs have fared. 

Second, most studies relied solely on official measures to assess program effectiveness 

(Le., arrests, convictions, and probatiodparole violations). It is commonly known that official 

statistics only reflect the activities of the police or other justice agencies, and do not fully 

measure the real level of crime, which is considerabIy higher than the official level. Few attempts 

have been made to gather recidivism information by using alternative methods, such as selfreports, which in comparison are more dif'ficdt and costly to c~ out. 

6 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Third, according to MacKenzie (1 993), dl programs operating in 1992 (30 states ad 10 

local jurisdictions and the Federal Bureau of Prisons) ,reported incorporating drug education or a 

combination of drug education and treatment iri their camp schedules. However, hardly any 

skidies addressed this aspect of boot camp activities and assessed its impact in reducing drug use 

_. 

a 

canioiig program participants. 

Fourth, although rehabilitation has been ranlted as a major goal in most programs, 

(MacKeiizie and Souryal, I991), efforts to help offenders adjust back to the community were 

rarely examined. While some reported positive attitudinal changes at graduation (MacKenzie 

and Shaw, 1990; Hunter et al., 1992), most studies failed to examine post-program reintegration 

in the comunity in terms of employment, education, vocational training, or other types of prosocial activities, thus leaving the impression that the success or failure of a boot camp program 

entirely hinges upon how many offenders are re-arrested. It is not clear, except for data on 

0 recidivism, how offenders who have not failed during the observation period have fared 

otherwise. 

Finally, few studies provided policy relevant or practical guidance to corrections agency 

administrators as to what types of offenders are likely to succeed in a boot camp--the 

characteristics associated with successful graduates. In other words, instead of just telling policy 

makers 'and practitioners whether their boot camps have worked as a whole, perhaps researchers 

should come up with more specific suggestions as to where improvements can be made or what 

type of offenders may benefit for the treatment. 

7 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Overview ofthe Los Angeles Juvenile Boot Camp 

The present study was an evaluation of the Los Angeles County Drug Treatment Boot 

Camp (DTBC). The selection of this boot camp in LOS Angeles County was based on several 

factors. First, as one of the earliest boot camps in the nation designed specifically for juvenile 

offenders, the DTBC has been in continuous operation since October 1990, with more than 2,000 

youngsters having graduated when this evaluation was commenced. Its long history helped 

minimize such possible interfering factors as program start-up inconsistencies, staff tLxnover 

' 

a 

(either due to over-zealous or demoralized staw, and unstable services often associated with 

short-term boot camps. 

Second, the Los Angeles DTBC was (and still is) an integral part of the Los Angeles 

County Probation Department's existing juvenile institutions. Its funding was tied to the overall 

budgetary concern of the Probation Department, therefore' it was designed and operated for the 

0 long ~iaul. 

Third, unlike the majority of the boot camps in the existing literature, the Los Angeles 

DTBC had a well-developed aftercare component combined with intensive supervision including 

drug education and individuallparental counseling. Services in the aftercare were provided based 

on the risk and needs assessment that every boot camp youngster received soon after their entry 

into the program. These features permitted research on the impact of the comprehensive aftercare 

. effort in curbbg the erosion of positive attitudes evidenced elsewhere by boot carhp participants 

at graduation. 

The Los Angeles DTBC consisted of two physically separate sites adjacent to one 

another, Camp John Munz and Camp William Mendenhall. The program was located in a rural 

setting of open, rolling foothills, approximately 60 miles north of downtown Los Angeles. Each 

8 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
site was a separate, self-contained facility with a 105-bed barracks, kitchen, mess hall, 

gymnasimn, school, administration building, nurse's office, staff quarters, basketball courts, 

athletic field, and obstacle course. 

0 

The DTBC emphasized discipline and obedience. Routine activities included individual 

co uizseling, drilling, marching and physical training. The paramilitary structure was intended tQ 

provide .M environment that would minimize negative peer pressure (in-camp gang cudture) and 

allow positive change. It was hoped that the camp experience would stimulate participants to 

redirect their physical, social and emotional energies into constructive channels, and that 

youngsters would return to the community with increased self-discipline, self-confidence, and a 

sense of pride and accomplishment for having met the boot camp challenges. 

A major difference between the Los Angeles juvenile boot camp and most other boot 

camps in the 1iterature.was that the DTBC was created neither to alleviate institutional 

overcrowding, nor to attract state or federal progrcun finding. The management of the Los 

Angeles County Probation Department was willing to institutionalize the paramilitary 

e 

eiivironnient to deal with its substance- abusing youngsters. The Department converted two 

adjacent senior camps (for youngsters ages 16 and older) into the boot camp program. In essence, 

these two caps were not any different physically fiom any other senior camps in the county, 

except for its paramilitary program. With donated military surplus clothing and camp staff with 

. .prior military experience plus additional training from former military personnel, the Probation 

'Department was able to lunch the program in October 1990 with much fanfare fiom the local 

media. 

The program enrolled only male offenders between the ages of 16-1 8;who were (either 

doctui.lented or alleged drug users with sustained petitions by the juvenile courts for non-violent 

9 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
and non-sex offenses.’ All potential recruits were medically cleared for work and rigorous 

physical exercise. Every other weekday, they attended a full academic high school program 

provided by the Los Angeles County Office of Education. On alternate weekdays, “cadets’’ 

participated in a work program with contracted agencies. Work projects included brush 

clearance, basic landscaping, road repair, and graffiti removal. Funds earned from the work were 

used to pay for court ordered fines and restitutions. 

a 

While iii camp, these youngsters attended a 15-week drug education program provided by 

the Inter-Agency Drug Abuse Recovery Program (I-ADARP), a non-profit agency that had been 

providing chemical dependency treatment services since 1973. Two full time counselors were 

assigned to each camp. The agency also conducted drug education training for the probation staff 

in the program to ensure their competence in working with drug using offenders. 

After completing the 24-week (six montlisj program, youngsters were released to 

intensive aftercare supervised by seven probation ofgcers who worked exclusively on DTBC 

cases. Small, specialized caseloads of 35-50 (compared to an average 150 cases per officer in the 

0 

department) were established to allow the aftercare staff to provide close supervision, personal 

counseling, and coordination of services from other community based organizations. The 

emphasis of the aftercare phase was on education, employment opportunities and vocational 

guidance. After six months of intensive supervision, those successfully adjusting to home and 

community, and.participating in treatment and academic or vocational plans, would have their 

probation terminated. 

Parental involvement was touted as a major feature of the program by the Probation 

Department since its inception. During boot camp, parents were invited to visit the camp and to 

talk to the staff about their concerns. They were also invited to attend the graduation ceremony. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
The aftercare component would begin while the ward was still in camp. Within the first six 

weeks upon camp entry, the aftercare probation officer would begin to review the participant’s 

file, to interview him, and to prepare the aftercare plan. The youngster would then be informed of 

his aftercae plan, and his parent(s)lgumdian(s) would also be invited to attend ten weeks of 

0 

classes conducted by the community based I-ADARP counselors. These parents would gain 

knowledge of street drugs and the drug cuIture, and acquire parenting skills in dealing with their 

delinquent cliildren. The drug counselors and the probation officers would work closely during 

the aftercare phase and continue to provide support to the parents. ’ 

Programmatic Changes over Time 

As time passed, the original boot camp went through several major changes, mostly due 

to DepartmeiitaI management decisions that affected the entire camp system in the county. 

Because the DTBC was part of the Bureau of Juvenile Institutions, my decision to overhaul or 

modify the existing camp system bore direct impact on the structure and programmatic integrity 

of the boot camp program. No departmental efforts were made to spare the boot camp program 

froin any clianges that affected the rest of the camp system. In other words, the boot camp 

program was treated much the same way as the other juvenile camps in the county. While some 

of tlie changes reflected the efforts of the management to improve the effectiveness of treatment 

on youth .offenders, most were in response to the demands of the juvenile court. The following 

0 

were the main changes that affected the boot camp progp~~ 

First, since its inception in 1990, the directorship at the DTBC changed many times, The 

change of the directorship, which happened about once every two years systemwide, also 

brought about changes to the regimented environment, as the management and operation of e& 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
juvenile camp more or less reflected the personal style of the director? One noticeable change 

was the gradual relaxation of the paramilitary atmosphere. With each succession, the new 

director became less and less “tough,” thus deviating farther and farther away from the original 

program design. There was noticeable decline in personal confrontation and in the drill-sergeantstyle marching coimnands. The original gung-ho directors, with high hopes of instilling respect 

for authority and discipline in these young souls through harsh military basic training, were 

replaced by moderate and perhaps more realistic managers who preferred to run the DTBC with 

lower decibels and more interpersonal skills. While camp youngsters were still grouped in 

“platoons,” housed in “barraclcs,” and clothed in donated fatigues, the military atmosphere was 

ostensibly lessened as years went by. 

a 

Second, since the inauguration of the DTBC in October 1990, LOS Angeles Probation 

Department had gone through several budget crises and structural rearrangement, which affected 

0 significantly the auxiliary services. Outside services were significantly reduced due to budgetary 

constraints. For instance, at the time of the data coIlection for the present study, drug counseling 

was provided by the camp staff, whose qualifications consisted of an eight-hour training course 

fiom a Probation Department internal substance abuse “expert,” who in turn provided an eightweek course (one-hour a week) for the boot camp youngsters. The boot camp program, which 

used to receive special counseling services fiom the outside contracted agency, I-ADAAW, was 

no longer able to receive any special treatment. 

Third, a major reorganization of the juvenile camp system, called regionalization, took 

place in the early 1996, which significantly affected the treatment population. Previously boot 

camp participants were recruited fiom the entire county, in which court orders were-first referred 

to the camp headquarters where the eligibility screening took place. However, the Probation 

12 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Department decided to adopt a regionalized model in I997 to assign camp orders according to 

their residential locations. Each juvenile camp was assigned to absorb all court-ordered 

a 

youngsters from ,a specific catchment.area. This realignment of camp referrals was said to combat 

' 

street gang culture with a head-on strategy, forcing camp-bound gang members to face their 

rivals in a correctional environment and to learn to live with each other in peace. For years, the 

traditioiial way of handling rival gang members or members of the same gang was to disperse 

them throughout the camp system to reduce their interactions while under camp supervision or to 

prevent the strengthening of any camaraderie among gang members during their stay in a camp. 

As a result of the regionalization, the ethnic composition of the original boot camp program 

shifted from representing more or less the population makeup of the entire county to that of its 

designated area, which significantly interfered with the present study to draw comparable 

subjects (as discussed later in the sampling section). 

. Finally, at the time of regionalization, the length of stay in all camps was also shortened 

to accommodate more youth offenders sentenced to camps. At the time of the data collection, the 

DTBC was shortened from the initial six months to 10 weeks. Later the 1 0-week program was 

e 

further shortened to eight weeks. In response to the increasing demand from the juvenile courts, 

the Probation Department overhauled the old camp structure and implemented a 3-phase camp 

program designed to move as many youngsters and as quickly through the system as possible. 

The 3-pliase program included a 2-week so-called stabilization phase, in which youngsters 

awaitkg their camp assignment in the juvenile halls would learn the basic des of a camp life 

and prepare for the new incarcerated environment. The second phase was 8-week long, during 

which youngsters were transferred to a secure camp designated for their geographical area. 

During the second phase, youngsters would continue to correct their negative behaviors and learn 

13 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
new skills to live with one mother in a closed cornmu&. For Phase Three, the youngsters 

would be transferred to the open camps (that include the two camps of the DTB C program), 

where youngsters supposedly would learn the sltills necessary to reintegrate into the home 

commuuity. After this phase, youngsters would be fiirloughed (i-e., conditional release) back into 

the community with a set of probation conditions and supervised by probation officers on smaller 

caseloads. Offenders on furlough could be sent back to the camp without a court order for any 

violation of the probation conditions. 

OBJECTIVES 

The.main goal of the present study was to use a combination of official and self-report 

ineasures to assess the effectiveness of the DTBC as a correctional model for juvenile offenders 

with a focus on their substance abusing behavior. 

Juvenile boot carnps have been relatively few (Austin et d., 1993; Cronh, 1994; Toby 

and Pearson, 1992). Even fewer studies have been published on the effectiveness of these 

programs in juvenile corrections. The few available publications are based either on fleeting 

personal observation and anecdotes (Polsky and Fast, 1993) or programs that were so poorly 

a 

implemented that results yielded little useful information (Bottcher, 1995). In addition to the 

general scarcity of research on juvenile boot camps, the behavioral impact of drug education and 

counseling in these boot camps have rarely been addressed in any evaluation studies. This is. 

mainly because such information is not readily available in official records. With the exception 

of mandatory urinalysis by court orders, there is no reliable official venue to collect information 

on offenders’ drug use. 

I4 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Therefore, program “effectiveness” in this study extended beyond traditional official 

recidivism (e.g., arrests, convictions, or probatiodparole violations) to include measures of 

@ involvement iii drug use and sale, attitudinal changes, and reintegration to the community. The 

main goal ofthe present study consisted of four specific objectives. 

First, this study examined official recidivism over a much longer period than most 

priblislied studies to increase our overall understanding of the long-term impact of juvenile boot 

camps on’recidivism. A particular issue was the extent to wlGch the various risk factors at iiit&e 

would influence program outcomes. Although all boot Cmp programs have screening 

procedures, they are often vague and loose enough to accommodate a wide variety of offenders 

who might meet some or all of the criteria, such as age, sex, and the nature of the sustained 

offense (drug offenses in the case of the DTBC). Beyond these characteristics, these youngsters 

may have little in common. Other background factors, such as the number of prior arrests or the 

age of onset, may put individuals at different risk levels, which become relevant once they return 

to the community. 

0 

Investigators frequently set the follow-up period at 12 months, such as the study by 

MacKenzie et al. (1 995). Some studies have used even shorter follow-up periods (Bottcher, 

1995). Longer observation periods for follow-up purposes are always desirable, but are often 

restricted by such factors as .finding, access to official records, and the length of the program in 

existence. Because of DTBC’s long history of continuous operation, this study was able to track 

graduates for up to five years after they left the program, an observation period much longer than 

most published studies. 

-? Second this study used the self-report method to examine the impact of the boot camp 

program on subsequent delinquency involvement, which few published studies have done. It is 

e 15 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
commonly accepted that few delinquent acts are ever detected or acted upon by anyone in 

authority .(see discussion in Empey and Stafford, 1992: 101). Even when serious crimes are 

involved (such as armed robbery, burglary, and auto theft) chances of ever being detected are still 

slim, about 2 out of every IO violations (Erickson and Empey, 1963:462; Williams and Gold, 

a 

1972: 219). 

The fraction of crimes ever recorded by authority might have contributed to the lack of 

significant findings thus fa. The purpose of this discussion is not to discredit the use of official 

data, hilt to point out the importance of including self-report measures to complement official 

statistics. Self-report data can provide additional information on the spread and frequency of 

criminal behavior among the offender population. The self-report method has also been shown to 

be robust and reliable (Zlmng et al.,'2000). A number of studies found a remarkable degree of 

uniformity between self-reported answers and official data (Erickson and Empey, 1963; Gibson 

et a]., 1970; Blaclunore, 1974). Another study of drug dealers that traced self-reports of arrests 

from interviews through criminal records found an 80% match between the two data sources 

(Reuter et al., 1990). 

a 

However, self-reports rely on offenders' memories, which fade over time. Therefore, it 

was not possible in this study to have as long an observation period as that for the official 

records. Since evaluation studies on recidivism are mostly concerned with the period 

immediately.&r treatment, this study proposed a 12-month post-camp observation period.for 

gathering self-report data. 

Third, this study examined, again using self-report measures, the effectiveness of boot 

camp in reducing participants' subsequent involvement in drug use and sale. Understandably, 

, such information is Lwm.lly not available in official files, which is probably why most evaluation 

a 

16 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
studies chose not to deal with this aspect of their boot camps. It is hard to ignore the importance 

of this issue since all boot camps seem to claim drug education and treatment to be a key 

component oftheir programmi& planning (MacKenzie, 1993). 

This study used two different ways to examine the effectiveness of the DTBC on 

substance abuse-( 1) a cross-sectional component (to compare boot camp participants against 

those from the traditional juvenile camps), and (2) a 1ongitudinaI approach (to follow a group of 

camp participants through a pre-and-post design to examine tlie change over time in their drug 

offenses). The pre-and-post design, while time consuming and’costly, was justified for 

methodological reasons. As MacKenzie (1993) reported, all programs operating in 1992 

emphasized drug education and counseling. For instance, participants in the New York program 

received drug counseling and education daily throughout the entire 180-day program 

(MacKenzie, 1993: 24). The heavy emphasis on drug counseling and education indicates a high 

concentration of drug using offenders in these boot camps, which makes it difficult to find e 

comparable subjects elsewhere. The same was tnie with the DTBC in Los Angeles County, 

which supposedly was recruiting drug-abusing offenders. Although elaborate case matching 

methods and statistical procedures can control for many variables including race, age, and prior 

. offenses, the unique nature of drug use and the lack of relevant official data can raise 

comparability problems in a quasi-experimental design by using so-called “legally eligible 

. subjects” (see MacKenzie et al., 1995). Therefore, to complement a cross-sectional comparison 

beiween the DTBC and the traditional camp in their effectiveness in reducing juvenile offenders’ 

involvement in drug use and sale, this study included a pre-and-post test component. 

Fourth, this study examined the level of participation of camp graduates in conventional 

activities (i.e., pro-social activities) and, in particular, the role of parental involvement in , 

17 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
fostering successful return of participants to the community. A distinct feature of the juvenile 

- boot cmp in Los Angeles County was its requirement for parental involvement during and after 

the program, which was supposedly not emphasized as much in the rest of the camp system. This 

feature would allow this study to examine the extent t0 which these parents may help improve 

the offenders’ subsequent behavior. 

PROJECT DESIGN 

This study consisted of thee independent data collection components, as shown in Fiaire 

1 , --( 1) a comparison of official recidivism rates between matched boot camp graduates and nonboot camp graduates over a five-year observation period (hereafter the matched samples); (2) 51 

cross-sectional comparison of self-reports between boot camp and non-boot camp graduates Over 

a 12-month observation period (hereafter the 12-month self-report samples); and (3) a pre-andpost test of a boot camp cohort over a 6-month observation period (hereafter the pre-and-post a 

cohort) + 

“Figure 1 about here” 

The Case Matching Method 

This study used the case matching technique to locate a group of comparable subjects 

from four other juvenile camps who were matched against the sampled boot camp participants on 

major descriptive variables (i.e., socio-demographic and criminal history characteristics). Prior 

to the implementation of the boot camp program, there were six so-called senior camps in Los 

Angeles County, enrolling youngsters who were at least 15 years of age. These camps were 

18 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
- equivalent to one another in terms of their levels of confinement and programmatic services. Two 

of the six senior carnps were converted to be the boot camp; the remaining four were thus 

0 selected to be the comparison camps. 

The case-matching technique has its limitations because a sample becomes exceedingly 

difficult to draw as the number of descriptive variables increases. Therefore, the number of 

descriptive variables selected for the case matching process was rather arbitrary and limited to 

the Ones that were thought to be conceptually important. This study used the following matching 

criteria: gender (all males), ethnicity (Wlite, Hispanic, and African American), age, and prior 

arrest history. To achieve a better understanding of the effectiveness of the boot camp and its 

aftercare component, this study also limited the sampling match to first-time camporder 

youngsters for both groups. Presumably, those With prior cap experience were likely to be more 

serious and chronic offenders, which may confound the results. 

This study did not use boot camp dropouts for comparison purposes. MacKenzie ,et al. 

(1995) used boot camp dropouts .to form comparison groups in five ofthe eight states they 

evaluated (see also MacKenzie and Shaw, 1993). These dropouts were enrolled but failed to 

complete the programs for various reasons (not reported in the study). While legally eligible, 

most wlio dropped out boot camps were due to disciplinary problems or uncooperativeness. 

Therefore, their very failure to complete the program made them a self-selected group and 

rendered the comparison problematic. 

’ It is important to point out that elaborate case matching and statistical manipulation can 

not make up for a true experimental design with random assignment because it is difficult to 

msess just how comparable the “matched” or “legally eligible” subjects are to the boot camp 

participants. Legally eligible subjects are indeed different fiom those who actually were assigned 

19 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
to boot camp, as any administrator can attest to the fact that the screeiling process at each camp 

enstires that the most eligible candidates are recruited. Intake officers usually have written 

selection criteria, which means those who do not get in the treatment program are somewhat less 

eligible. The same was true for the DTBC in Los Angeles. The initial screening protocol was 

designed to seek out documented or alleged drug users, thus making it hard to find comparable 

subjects in the larger camp system. 

Sampling and Data Collection 

For the matched samples, the sampling frame included youngsters who completed tlie 

boot camp between April 1992 and December 1993, to minimize possible treatment 

incoiisistencies aid programmatic/staff adjustment during the start-up phase. A complete roster 

of the boot camp graduates from this sampling period was obtained from the camp headquarters, 

from which 427 graduates with no prior camp experience were randomly selected. Frequency 

tables were compiled for the DTBC graduates to provide ethnic descriptions, which then served 

as guides to stratify for selecting the comparison gradkiates. SubseqLiently, a complete roster of 

the four comparison camps was also obtained and used to select 427 youngsters who matched on 

the predetermined descriptive variables. The sample size for either group was sufficient to 

achieve a 95% level of confidence in the results with a tolerated error margin of 5% (Backstrom 

and Hursh, 1963:33). 

0 

In fhe end, the two samples of subjects were matched on the following aspects: gender 

(all males), between the ages 16-1 8 at the time of camp entry, number of priorarrests, no prior 

cap experience, non-violent and non-sex offenses, and out of the camp during the same period 

as the boot camp graduates. In addition, these two samples were also matched on the ethnic 

20 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
. , composition (i.e., White, Hispanic, and African American). For pragmatic reasons, other ethnic 

minorities were excluded. 

a The access to official records (both juvenile and adult) was granted through the approval 

of a petition to the Los Angeles County Probation Department prior to the initiation of the project 

and of a motion to tlie Los Angeles County Juvenile Court. Complete records of arrests and 

dispositions were obtained for the matched samples, and keyed into an SPSS data file for 

analysis. 

For the 12-month self-report samdes, a complete list of all camp graduates who exited 

the boot camp program and the four comparison camps in 1996 was obtained from the Los 

Angeles County Probation Department camp headquarters. To ensure a sufficiently large pool of 

eligible candidates, the sampling time frame was extended to December of 19.95 and the first 

thee months of 1997. The original plan was to match the two samples on the same descriptive 

variables, however the effort was aborted after the selective interview process turned out to be 

prohibitively expensive and impractical. As a direct resdt of the regionalization in jivenile camp 

system (which affected the sampling period for this component, but not the matched samples), 

about 70% of the daily population at the two DTBC camps became Hispanic. It also drew slightly 

more Caucasians but far fewer African Americans than the rest ofthe camp system, 

It was originally planned that since the sampling frame for the comparison group was 

much larger than that of the boot camp subjects, interview activities on the comparison group 

would revolve .around the interviews of boot camp subjects for the matching purpose. In other 

words, age and ethnicity distributions of the boot camp interviews would be used to determine 

the interviews with the comparison subjects. As it turned out in the data collection process, 

significant human resources (hence expense) were spent to complete these matches between the 

21 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
- boot camp and comparison subjects on the descriptive variables. It soon became obvious that tlie 

resource iinplication of such a matching process was prohibitive. Furthermore, to avoid the time 

lag effect, interviews for both groups of subjects were to take place approximately at the same 

time to ensure equivalency in their exposure to the treatment environment and to risk (time out of 

0 

camp. The selective process was terminated and interview activities proceeded irrespective of 

tlieir matching criteria. As a result, there were significant differences between the two groups of 

subjects on two main descriptive variables--ethnicity and age (as shown later in the sample 

descriptions). 

All telephone interviews were conducted at the Social and Behavioral Research Institute \ 

(SBRI) at California State University San Marcos, which was equipped with a state-of-the-art 

computer-aided telephone interviewing (CATI) laboratory capable of conducting large-scale 

survey research regionally and nationally. The software of the CATI system tracked the 

scheduled call-baclcs and monitored progress on completing sanple related quotas. Interview 

questions appeared on the computer screen and the interviewer entered the data directly into the 

database. Supervisors were present during all ii-iterviewing activities and calls were monitored at 

random to ensure the consistency of the interview protocols and the accuracy of the recorded 

a 

data. All supervisors had worked as interviewers prior to becoming a supervisor, and received 

extensive training in telephone interviewing techniques and social science research methods. 

To locate potential subjects, probation records were obtained for the pool of eligible 

subjects, which contained their home addresses and phone numbers. Eliciting cooperation from 

these youngsters for interviews was aided by a nominal payment ($20 each for a completed 

interview). Additionally, subjects were assured of confidentiality of their identity, and by 

conducting interviews over the phone in the subject's choice of location (e.g., his bedroom or a 

22 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
friend’s place). However, because of the high residential mobility among the offender population, 

the majority of telephone numbers in the official files Wed out to be inaccurate by the time first 

phone contacts were attempted (approximately 12 months after their camp exit), Severd 

teclmiques were used to achieve the proposed sample size (Le., 100 completed interviews for 

each group), including directory assistance, cross street verification, repeated calls to unanswered 

calls, and reviewing hardcopy probation files to search for additional contact iiiforniation, such as 

(I) 

addresses and phone numbers of subjects’ relatives and employers. 

The Dre-and-post cohort component was designed to interview a group of subjects as soon 

as they entered the boot camp to obtain self-reportdata for the six months prior to their cukent 

entry into the justice system. The same group of subjects would then be interviewed for a second 

time six months after leaving the camp. The goal was to gauge changes over time as a result of 

participation in the boot camp. The first wave of interviews (Tl) were conducted over a threemor& period and included a cohort of 137 fresh recruits, which was estimated to be sufficient 

for 100 completed interviews at the second wave (T2). However, the sample attrition was far 

more severe than anticipated. Upon camp exit, contact information of all subjects interviewed at 

T1 was gathered, At approximately 5th month after the first few graduates leR the camp, the 

compIete list of T1 subjects was forwarded to the Probation Department for verification purposes 

and also to update any changes in participants’ addresses and phone numbers. After the first 

round of verification conducted by the DT3C st&, only 37 youngsters were located @e.? with no 

changes in either telephone number and residence). The rest either had disconnected their 

telephones or changed their addresses. An immediate request was made to the Probation 

Department to update on the whereabouts of the “missing” subjects, many of whom, according 

the program description, were still supposed to be either under intensive probation superv‘rsion or 

0 

23 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
just out of the aftercare program. A formal request from the boot camp director was sent out to 

all supervising area ofices for updated information on the “missing” subjects. The intensive 

aftercare (i.e., placed on small caseloads of 35 per probation officer) should last 90 days, and 

then the youngsters would be transferred to regular probation for an additional six months or 

terminated upon successfiil review of their probation performance. The process of the follow-ups 

became protracted; many area offices were simply non-responsive, which substantially increased 

the time lapse to T2 interviews far beyond the originally planned six months. 

’ 

a 

Three different strategies were attempted to obtain information about the “missing” 

subjects. First, boot camp director Robert Polakow issued a request to all area offices that 

supervised the T1 subjects to update on their most current contact information. A few area 

offices responded. Many did not, even after repeated requests. As soon as any updated 

information was forwarded to the research team, phone calls were made immediately to contact 

the youngsters. Many of the updated records from the supervising offices were again found to be 

inaccurate and returned for further verification. As this strategy became ineffective in generating 

accurate information in a timely manner, the research team requested and obtained the names and 

0 

phone nurOers of the supervising officers and directly requested the information. For various 

reasons, most officers were often away from their desks and reached only through repeated 

Uenipts. Messages left at their area offices were seldom returned. Additionally, because of the 

sensitive nature of the information requested, many officers were unwilling to release any 

information without written authorization. After all these hurtles, the information forwarded to 

the research team, which was supposed to be current, often turned out to be still inaccurate. As 

the search for T1 subjects snailed forward, the number of terminated cases was also rising. As a 

third strategy, members of the research team went to the Los Angeles County Hall of Records to 

24 

x 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
. search through closed supervision files in a last attempt to search for any clues on the 

whereabouts of tlie’youngster. Throughout the process in search of the T1 subjects, obtaining 

timely responses from field offices and especially from the responsible probation officers was 

a 

most difficult, probably due to their unfamiliarity with the project, unwillingness to release 

confidential information, or simply work overload. Finally, after the research team chased 

frustratingly for months after supervising officers, a directive from the bureau chief in charge of 

the field offices was issued, ordering cooperation to submit updated information on the 

“missing” cases. 

Because of the difficulty in locating the subjects, the elapsed time between the camp exit 

and. the second interview was significantly lengthened from the originally planned six months to 

anywhere between 204 days up to 5 17 days (with an average of 35 1 days; a standard deviation of 

67.7 days, and a median of 349 days). Therefore, the majority of T2 interviews took place 

approximately one year after their camp exit. Only 89 subjects were located and interviewed at 

the second wave (T2), a success rate of 65%. 

Measurements 

Official data: Recidivism can be defined in different ways, all of which have certain 

degree of content validity (Maltz, 1984; Schmidt and Witte, 1988). Instead of arguing over which 

’ measure is more appropriate, this study adopted multiple criteria: (1) any new arrests, (2) my . 

new sustained petition or conviction, (3) any filing of 477 petition for probation violation. . 

Probation officers at their discretion can file a 777 petition to request the court to revoke or 

,modify the terms of an offender’s probation. From an officer’s perspective, such petitions me an 

25 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
indication of probation failure. They usually result fiom serious probation condition violations or 

new arrests. 0 

The observation period began on the date a youngster was transferred from the boot camp 

to the aftercare unit, or a comparison subject from a camp facility to a regular probation unit. 

Temporal information was recorded on all legal actions. Duration (e.g., time between beginnillg 

probation and the first recidivism act) was calculated by taking the difference in days between the 

date on which post-camp supervision began and the date an incident occurred. 

The official data collection instiiunentation contained four general categories : (1) 

' . demographic iiiformatioii (e.g., age and race), (2) current offense and disposition type, (3) prior 

arrest history, and (4) post-camp recidivism information. Official data sources used in this study 

included (I) the Juvenile Automated Index (JAI) maiiitained by the Probation Department and 

(2) the California Law Enforcement Telecommunication System (CLETS) maintained by the 

0 state agency Bureau of Criminal Statistics. After positive identification of the selected puilgsters 

(through a combination of cross-referencing arrest records and matching vital demographic 

variables) in the automated system, computer records were printed and then manually codecl into 

the data form. 

Self-report data: This study adopted a well-established instrument, the International SelfReport Delinquency questionnaire (ISRD), to assess the youngsters' post-camp delinquent 

' ac~vities. This instrument, originalIy put together by criminologists fiom 15 Western countries, 

went through a series of empirical examinations and found to be reliable and methodologically 

sound (for a detailed discussion of this instrument, see Junger-Tas et al., 1994 and Zhang et al., 

2000). In addition, the ISRD was previously piloted on a sample of detained juvenile offenders in 

the Los Angeles Co~mty Pro bation Department, which supported its validity and applicability 

26 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
(see JLmger-Tas et al., 1992). The instrument contained measures on (1) the types of crimes 

comniitted during a specified time frame, (2) the frequency of these delinquent acts, (3) the onset 

of each admitted offense, (4) the circumstances of the incidents, and (5) a set of sociodemographic variables including attitudes to school aiid work, living arrangement, and circle of 

friends. 

a 

There are a total of 44 delinquency measures grouped in five categories. The first group 

contailis questions on problem behaviors (Le., status offenses and ininor infractions); the second 

group pertains to vandalism; the third contains various kinds of tliefl behaviors; the fomth aslcs 

questions about violent and aggressive behavior; and the fifth groLip contains qtlestions on 

alcohol and drug use. A set of filtering questions is put forth before the details of specific 

delinquent acts are probed, as shown in Figure 2. 

"Figure 2 about here" 

Following the filtering questions, more specific questions are prompted to gather 

iirfoimation on the fiequency of the acts, the most recent act, and its circumstances, as shown in 

Figure 3. 

"Figure 3 about here" 

. 

Modifications were made to adjust the time frame to suit this study. The following was an 

example: 

Item 290: You mentioned stealing a car (referring to the screening question). 

Item 292 ,(Original): Did you do it during tlGs last year? <interviewer: that is, since..,> 

Item 292 (Revised): Did you do it during this last year? <interviewer: that is, since yo^ 

graduated from the boot camv. > 

27 . 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Measures on drug offenses: The alcohol and drug related measures in the ISRD 

instniinent were designed to capture a youngster’s involvement iii both drug use and sale 

activities, which again were modified t.0 suit this study (Item 450 through Item 499). These 

measLires were designed to capture various aspects ofthe drug culture (i.e., circumstances of drug 

use and group activity) and the extent of the respondent’s involvement $e., frequency and types 

of drugs used or sold). The instrument also provided extensive measures 011 a respondent’s 

alcohol and tobacco use. Again, temporal elements were added to specify the time frame and 

help iiarrow down the time of first drug use/sale during the observation period. The following 

was an example: 

Item 450: You mentioned using marijuana, hashish or pot (referring to the screening 

question). 

Item 452 (Original): Did you do it during this last year? <Interviewer: that is, since. .. > 

(1) no (2) yes---> How often this fast year? times 

Item 452 (Revised): Did you do it during this last six months? (Interviewer: that is, since 

you graduated from the boot camp]? 

(1) no 

(3) When did YOLL do it the first time? (ask to identifi the month) (added) 

(4) Approximately what part of the month was it? (added) 

(2) yes---> How often this last six months? times 

. 

1 stm----5t11----- 1 Oth----- 1 5th-----2Oth-----25& 

To simply analysis and presentation, these 44 types of self-report offenses were grouped 

into five major offense categories: (1) status offenses, (2) vandalism offenses, (3) theft offenses, 

.(4) violent offenses, and (5) drug offenses. Index scores were computed for each of the five 

categories. The first four were Mer separated to form an index of all non-drug related offenses 

for analysis purposes. Drug offenses in this study were analyzed separately as a group to reflect 

the emphasis ofthe DTBC on substance abuse issues, 

28 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Measures on social integration: There were two sets of measures on social integration: (1) 

those 011 minors’ participation in conventional activities, and (2) those on parental involvement 

in tlie correctional process. Participation in conventional activities was measured by multiple 

indicators, including employment, education, organized sports, and other social activities. The 

ISRD instrument (in its socio-demographic section) contained a set of measures on these 

activities; 0111~ minor revision was made with reference to specified time frames (Le., since their 

e 

camp graduation). 

Information on parental involvement in the minor’s return to the community came from 

self-report measures that included such variables as camp visits, office visits, and cornmunichxy 

with probation officers, and support in the youngster’s efforts to engage in law abiding activities 

(such as school, sports, and paid jobs). The following was an example: 

I. Did YOLK garent(s)/guardian(s) ever visit you during your camp stay? 

(1) no 

2. Did your parent(s)/guardian(s) attend you ccarnp graduation ceremony? 

(1) no (2) Yes 

3. How often did your parent(s)/guardian(s) accompany you to your probation office 

visits? 

(1) always 

(2) most of the times 

(3) sometimes 

(4) occasionally 

(5) never 

(2) yes --->How many times? times 

Demograuhic variables and prior histow covered two broad categories: (1) sociodemographic background (e.g., age, race, education, living arrangement, education, general 

attitudes toward school and work, social network (friends), employment, hcome; and (2) 

information about the minor’s prior delinquent history including the number of arrests, and the 

nature of the incident offense. 

29 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
ANALYSES AND FINDINGS 

The project goal of producing findings that can be shared with correctional agencies, 

program administrators and policy makers led to an emphasis on descriptive ana lyse.^. Most of 

the statistics presented here focused on basic re-offending patterns (based on official as well as 

self-report data), the prevalence of recidivlsm and drug use among subjects. Bivariate 

cornparisoas were used to establish the degree of similarity (or differences) for these grotips of 

subjects in terms of their recidivism prevalence and frequency. Emphases were placed on the 

clarity of presentation and direct utility for service providers. More sophisticated analyses were 

also used when appropriate. For instance, stepwise inultivariate regression was used to explore 

the extent to which various individual and structural variables, life circumstances, and prior 

history of the subjects combine to affect the program outcomes. 

The Matched Samples 

Sample description: For the matched samples, 427 boot camp graduates were selected 

and another 427 subjects from the comparison camps. Both groups were matched on the 

descriptive variables as shown in Table I. Two other variables (i.e., male and first-time camp 

order) were constant as a result of the predetermined sampling frame. The ethnic brealcdowns 

* were asfollows: 66% Hispanics, 18% African American and 16% Whites. All subjects were at 

least 16 years of age. The vast majority of these youngsters (more than 90% for both groep) had 

at least one prior arrest; many of them had multiple contacts with the police prior to their camp 

entry (with 41% in each group having five or more prior arrests). 

30 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Both samples were exposed to the camp environment for approximately the same amount 

of time, averaging 159 days for the boot camp group (with a mecian of 155 days and a standard 

deviation of 29.96) and 155 days for the cornparison group (with a median of 145 days and a 

standard deviation of 46.98). The comparison group on average had been out of the camp system 

longer than the boot camp sample, 4.28 years compared to 4.21 years. 

a 

"Table 1 about here" 

Recidivism: 130th groups revealed very similar patterns in subsequent arrests and 

sustained petitions (as juveniles) or convictions (as adults), as shown in Table 2. During the 

follow-up period (more than four years on average), about 85% of the subjects in both groups 

were arrested at least once; 33% of the comparison group and 30% of the boot camp sample were 

arrested for five and more times. Two thirds of both groups had at least one sustained petition or 

coiiviction during this period, While the two samples were very similar in their post-camp arrests 

a 

and adjudications, boot camp graduates had significantly more probation violations (1 3%), 

compared to 6% among the comparison group. This was to be exp-ected because of the smaller 

caseloads and intensive supervision afforded to the boot camp youngsters during their aftercare 

phase. 

"Table 2 abput here'' 

An OLS regression analysis was conducted'to examine the effects of available variables 

in the official data on post-camp arrests and sustained petitions. AS shown in Table 3, the most 

31 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
salient predictor of post-camp arrests and adjudications was the number of prior arrests, which 

was consistent with most criminology literature. The number of probation violations also had a 

significant and positive impact on post-camp arrests, but not on adjudications. Those with a high 

number of post-camp arrests and adjudications (or convictions) were also Iikely to be arrested 

soon after they left the camp. Being African American appeared to decrease the likelihood of 

being convicted (or adjmlicated) on post-camp offenses, Furthermore, the length of camp stay 

also had a positive impact on the number of post-camp convictions (or adjudications), but not on 

arrests. 

a 

"Table 3 about here" 

Survival analysis (using the Kaplan-Meier method) was also conducted to compare the 

failure patterns as well as time to failure between the two groups: SurvivaI anaIysis specifies the 

proportion of offenders who survived by not recidivating (and, conversely, the proportion who fail) 

0 

across specified time intervals. The technique allows us to examine the process of failure within a 

fixed interval of time (such as every month, week, or even day) and provides more precision and 

specificity than does the fixed-comparison method. Those who did not fail during the observation 

period were treated as censored (meaning that they still could recidivate in the htwe). Boot camp 

, graduates andconventional camp graduates were almost identical in their survival (or failure) 

rates and time to fail. Since no new information was produced from the survival analysis, the 

findings were omitted here. 

32 

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of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
The 12-Month SslfReport Samples 

Because of the difficulties in locating and interviewing prospective subjects, these two 

a groups were not well matched, as shown in Table 4. There were Significantly more African 

Americans (33%), fewer Hispanic (58%) and White youngsters (9%) in the comparison group 

than those in the boot'camp sample (respectively 1 I%, 73%, and 16%). The boot camp subjects 

were slightly older (with an average age of 17 years old) than the comparison subjects (with an 

average ige of 16.54 years old). Both groups spent about the same length of time in camps. At ' 

the time of the interviews, both groups of the youngsters had been out of their camps for an 

average of 385 days, with a median of 366 days. 

"Table 4 about here" 

Despite the obvious differences in demographics, their patterns of pre-camp involvemellt 

in delinquency were similar. Both groups of subjects had about the same number of prior arrests 

and the number of self-reported non-drug related offenses. There were also similar in their selfa 

reported pre-camp delinquency involvement.'However, the boot camp subjects had a 

significantly higher number of s.elf-reported drug offenses than that of the comparison group, as 

was to be expected for the DTBC population. In sun, these two groups of subjects had 

significant 'differences in their ethnic and age compositions, but not in their levels of pre-camp 

delinquency involvement, as shown in Table 5, 

. "Table 5 about here" 

33 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
During the post-camp phase, the boot camp subjects reported to have engaged in more 

delinquent activities than the comparison group, particularly on theft related’offenses, as shown 

in Table 6. The differences on overall non-drug offenses between the two groups were 

significant, with ~1.95 and p<.05. Measures on drug related offenses consisted of (1) four items 

on usage (i,e., smoking cigarettes, drinking alcohol, smoking pot, .md use hard drugs) and (2) 

two on drug dealings (Le. selling pot and selling hard drugs). The differences between the grotips 

on drug related offenses became less pronounced, compared to their pre-camp comparison, In 

fact, the two groups were not different in their drug sale activities (with Fl.11 and p<.27), while 

tlie boot camp subjects still used significantly more dnigs in the post-camp period than the 

comparisoii group (with t=2.25 and p<.03). However, when their pre-camp differences were 

taken into consideration, tlie post-camp differences, based on the self-report data, between the 

two groups were probably due to the residual effects of their prior delinquency involvement in 

both non-drug as well as drug-related offenses. a 

“Table 6 about here” 

Official recidivism data were also collected for these two groups of subjects. Both groups 

exhibited very similar re-offending patterns with no significant differences on post-camp arrests, 

post-camp sustained petitions (or convictions), and post-camp probation violations, as shown in 

Table 7. As far as returning to the justice system was concerned, the two groups of subjects were 

not much different fiom one another. 

34 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
“Table 7 about here” 

The two groups were also much alike on most community integration measures, such as 

school attendance, involvement in gangs, employment, and participation in organized sports, as 

shown in Table 8. On the school measure, moreconiparison subjects (68%) were attending 

school at the time of the interviews, compared to 51 % of the boot camp youngsters, The 

difference was significant (with ,Y2= 6.00 and p<.03), which probably was caused by tlie age 

difference between the groups. There were more youngsters in the boot camp with 7 1 % aged 17 

aid older at tlie time of their camp entry, compared to only 52% among the coniparison group. 

Understandably, at the time of the interviews these older youngsters either were more likely to 

have completed high schools or were no longer required to attend school. 

“Table 8 about here” 

Besides behavioral measures, psychometric scales were incorporated in the instrument to 

measure changes in attitudes along four dimensions: self-esteem, perceived future prospect, 

mastery of one’s own destiny, and attitudes towards authority. All scales met acceptable internal 

consistency tests (Cronbach’s alpha), as shown in Table 9. Self-esteem measures consisted of 

’ threesubscales .with the higher score representing a more positive sense of self: (1) relations with 

peers (10 items,Cronbach’s alpha=.66), relationswith one’s parents (12 items, Cronbach’s 

aIpha=.89), and relations with school teachers (1 I items, Cronbach’s alpha=.80). Perceived 

fiiture prospect consisted of 12 items (Cronbach’s alpha=.76); the higher the score the more 

positive one felt about one’s future. Mastery of one’s own destiny consisted of seven items 

35 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
(Cro11bac1l’s alpha=.76); the higher the score the more one was in control of one’s destiny. 

Attihides towards authority were measured by 17 items (Cronbach’s alpha=.69); a higher score 

represented a higher tendency to respect a hierarchical order in life and agree with authority 

a 

figures. 

As shown in Table 9, despite the paramilitary drills and regimented camp life, boot cap 

youngsters did not score much differently from the comparison subjects on any of the attitudinal 

measures. These two groups of youngsters were essentially the same on these four sets of scales. 

“Table 9 about here” 

Based on the program design, boot camp youngsters were to receive individually planned 

aftercare plan and be placed on intensive supervision, in which the probation officer would tailor 

services according to each youngster’s needs. Such an elaborate aftercare compoiient was not 

available to youngsters fkom the comparison camps. In an attempt to assess the differences in the 

aniouiit of post-camp services received by the two groups of subjects, this study collected data on 

0 

five different activities: (1) tutoring, (2) recreation, (3) job training, (4) personal and family 

counseling, and (5) drug and alcohol counseling. 

This study found that the boot camp youngsters received signif&ntly more drug and 

dujhol counseling than the comparison, probably due to the emphasis of the DTBC on substance 

. abuse issues. Other than that, the boot camp subjects received no more services than their 

counterparts in the comparison group. Instead, significantly more comparison youngsters 

participated in organized recreation activities through community agencies, as shown in Table 

10. It appeared that despite the rhetoric, the elaborate aftercare plan and intensive sLlpervision did 

36 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
not materialize to provide more or different services to the boot camp youngsters (with ~e 

exception of drug and alcohol counseling), which was problematic to the integrity of the boot a 

ccmp program design. 

“Table 10 about here” 

Despite the lack of my consistent improvement in behavioral as well as attitudinal 

oiitcomes, this study found that significantly more boot camp snbjects reportedly enjoyed their 

ccmp experience than those of the comparison group, as shown in Table I 1. While about half of 

each group (49% each) did not feel strongly about the camp one way or the other, 34% of the 

boot camp youngsters found their camp experience to be pleasant, compared to 14% among the 

comparison group. While statistically non-significant, more boot camp subjects (84%) also 

coilsidered that the camp experience made them a better person, compared to 76% among the 

coniparison. Based on self-reports, both groups of subjects received about the same number of 

disciplinary actions for conduct problems while in cmp. However, when offkid data were 

compared, the boot camp subjects were significantly more likely to be sent to locked-down or 

more restricted facilities for disciplinary problems (26%), cornpared to zero among the 

comparison group. 

“Table 11 about here” 

Because of this study’s goal to search for profile characteristics’associated with 

recidivism, Pearson correlations analyses were conducted on conceptually relevant variables and 

37 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
foLir behavioral outcome measures-( 1) post-camp self-report delinquency (non-drug related), 

(2) post-camp self-report drug offenses, (3) post-camp arrests, and (4) post-camp sustained 

petitions (or convictions). To save space, only significantly correlated variables were presented 

here. 

(1) post-camp self-reDort delinquency: While a large number of variables were 

significantly correlated with the two indices of post-camp delinquency measures, only a few have 

sLibstantidly meaningful relations, as shown in TabIe 12. In line with the existing literature, a 

respondent’s post-camp delinquency involvement was most significantIy correlated with his precamp delinquency (r=..54 anclp<.OOO). This study also found a high correlation between postcamp non-drug related delinquency activities and post-camp drug offenses (r=, 53 andp<. 000). 

Other significant but moderate correlatioiis were fofound with prior exposure to substance abusing 

environment (r=. 31 andp<. OOO), school failure/fiustration (F. 30 andpc. OOl), and stress 

, (r=.38 andp<, 000). 

“Table 12 about here” 

(2) Post-camp self-report substance abuse: As discussed above, post-camp drug offfenses 

were significantly correlated with non-drug related delinquency activities, as shown in Table 13, 

More importantly, post-camp drug offenses were most significantly correlated with pre-cmp 

drug .offenses (r=, 62 andp<.000), which is in line with the existing literature. Other significant 

but moderate correlations were found with prior exposure to substance abusing environment 

(r=, 30 andp<. 000) and pre-carrip involvement in non-drug related delinquency offense (r=, 43 

and p<. 000). 

38 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
“Table 13 about here” 

(3) fost-camp arrests and (4) post-cbm sustained petitions for convictions) were found 

to have far fewer significant correlates compared to the self-report measures, as shown in Table 

14 and Table 15. FLirthermore, the correlation between prior arrests (pre-camp) and post-camp 

arrests was not only weak but also marginally significant (r=. 12 and p<. IO), which was 

somewhat inconsistent with the existing literature. Neither prior arrests nor prior sustained 

petitions were significantly correlated with post-camp sustained petitions. Subjects living with 

both of their mothers and fathers were less likely to be arrested after camp exit (r=-.23 and 

p<. 001). There was also a moderate and negative correlation between post-camp arrests and 

perceived parental support in times of trouble (r=-.25 andp<. 001). Being African-American was 

more likely to have post-camp sustained petitions (rz.25 arzdp<. 000). 

“Table 14 and Table 15 about here” 

Multiple regression analyses were carried out to further explore variables that weie 

influential on both self-report and official recidivism measures. With inference from the bivariate 

correlations, this study conducted stepwise regression to search for variables that could best 

predict tile outcomes. All significant correlates of individual outcome measures were included in 

their respective stepwise regression models. 

For post-camp self-report delinquency, seven variables were found to have significant 

predicting effects-pre-camp delinquency, prior exposure to substance abusing environment, 

39 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
perceptioii of hture opportunities, perception of control over one’s destiny, cumulative stress 

@ factors, pre-camp substance abuse, post-camp substance abuse, and perception of school failure 

and frustrations. These seven variables together combined to explain more th& 50% of fie 

variance in the dependent variables (adjusted R2=.52), as shown in Table 16. 

For post-camp self-report drug offenses, four variables were found to have significant 

predicting effects-pre-camp drug offenses, post-camp non-drug delinquency, enrollment in 

scllool, and parental knowledge of subjects’ friends and whereabouts. These v&iables combined 

to explain more than 50% of the variance in the dependent variable (adjusted R2=.56), as shorn 

in Table 16. 

“Table 16 about here“ 

\ 0 For post-camp arrests, four variables were found to have significant predicting effects- 

, perceived sLlpport from parents$ times of troubles, both parents living with the respondent, 

being a gang member, and having a job. However, these four variables, while significant in their 

beta values, could only explain a small amount of variance of the dependent variable (adjusted 

R2=. 16), as sliown in Table 17. Similar finding was also true of post-camp sustained Detitions. 

Being African American, perceived parental support in times of troubles, the number of times 

.. being disciplined while in the juvenile camp, and the number of days the respondent had to care 

for himself were found to be significant predictors. Again, these independent variables combined 

to explain only a small amount of the variance in the dependent variable (adjusted R2=. 101, as 

shown in Table 17. 

40 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
"Table 17 about here" 

It appeared that both official outcome measures (Le., post-camp arrests and post-camp 

sustained petitions) were not very explainable by the self-report measures iiicluded in this study, 

both in the bivariate correlation analyses as well as in the regressional analyses. Self-report 

outcome measures were far better explained by the variables in the instrument. However, being 

in the boot camp (coded as a dummy variable) did not appear to have any significant correlation 

or predicting effect with any of the four outcome measures. 

The Pre-and-Post Cohort 

Because of the significant reduction in sample size, an attrition analysis was conducted to 

compare the differences between the lost cases and the fmal sample. The ethnic composition was 

visibly different (although statistically the differences were marginally significant). There were 

also visible differences in the age categories, although at the group level both the filial sample 

and lost cases were similar. It appeared that attrition occurred mostly among Hispanic subjects ' 

and those who were I8 years of age or older at the time of the interviews. In terms of their length 

of stay in the boot camp, pre-camp self-report delinquency and pre-camp self-report drug 

offenses, there were no significant differences between the fmal sample and the lost cases, as 

shown in Table 18. 

"Table 18 about here" 

41 

P 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Because of the structural change as discussed earlier (i.e., regionalization), the pre-and0 post cohort spent far less time in the boot camp than the subjects in the other two components, 

with an average of about 78 days (with a median of 70 clays). Over the yews, there was a steady 

decline in the average length of camp stay in the entire juvenile camp system in Los Angeles 

Coui~ty due to various efforts to respond to the juvenile court pressure'to accommodate the 

increase of camp orders. For subjects of the matched samples (who were enrolled during the 

I prime time of the program and left the camps in 1992 and 1993)) the average length of camp stay 

was around 155 days, as shown in Table 1. For the 12-month self-report samples (who left their 

respective camps between 1995 and 1997), the average camp stay was around 130 days, 8s 

shown in Table 4. By the time the pre-and-post cohort entered the boot camp program, their time 

in camp was reduced by half. 

In comparing the changes over the two observation periods, significant improvement was 

foimd on almost all self-report measures, as shown in Table 19, despite the fact that the postcamp observation period was much longer than that of the pre-camp. On post-camp self-report 

delinquency (i.e., non-drug offenses), the average number of offenses was 3.67 during the post 

camp observation period, compared to 6.10 in the pre-camp period (1=3.84 andp<. 000). The 

improvement was significantly evident across all four categories that made up the index-status 

offenses, vandalism, theft, and violent offenses. For post-camp self-report drug offenses,' the 

improvementwas also remarkabIe with a mean score of3.90 compared to the pre-camp average 

of4.32 (t=1.88 andp<. 07). However, much of the significance was due to improvement over 

drug sale activities; there was no statistically significant improvement in drug use between the. 

two observation periods. 

42 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
“Table 19 about here” 

011 measures of social activities, no significant differences were found on school 

attendmce, employment and involvement in gangs, asshown in.Table 20. However, the subjects 

participated in organized sports more during the pre-camp period than in the post-camp period 

(X2=4.10 andpc.05). 

“Table 20 about here” 

Using the same psychometric scales as those for the 12-month self-report samples, this 

study also measured on the attitudinal changes over the two periods for this group of subjects. All 

scales met acceptable internal consistency tests (Cronbach’s alpha), as shown in Table 21, 

Overall, few differences were found over the two periods; the boot camp treatment did not 

appear to have any impact on their attitudes towards authority, on their perceptions of hture 

prospect, or on their perceived mastery of their own destiny. However, significant improvement 

was found on two sub-scales that made tip the self-esteem measures. The subjects’ perceptions of 

0 

their relationships with their parents (or caretakers) were improved significantly (t=2.16 and 

p<. 04) and the perceptions of their school relationships (with teachers and classmates) were also 

significantly improved (t=2.40 andpc. 02). 

“Table 21 about here” 

43 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Same as the 12-month self-report component, Pearson correlations were sought betweell 

conceptually relevant variables and the four behavioral outcome measures-(l) post-camp selfreport delinquency (non-drug related), (2) post-camp self-report dnig offenses, (3) post-camp 

0 

aiyests, and (4) post-camp sustained petitions (or convictions). Only significantly correlated 

variables were presented here. 

(1 1 Post-camp self-report delinquency: The most significant correlates were pre-camp 

delinquency (r=, 43 andpc. 000) and post-camp drug offenses (r=.41 anclpc. 000)’ as shown in 

Table 22. Interestingly, a subject’s intention to want his relationship with his girlfriend to last 

appeared to reduce his post-camp delinquency (r=-.31 andp<. 02). 

“Table 22 about here” 

(2) Post-camp self-report drug offenses were found to be most significktly correlated 

with pre-camp drug offenses (P=, 43 andp<. 000) and other post-camp delinquency involvement 

(r=. 41 czndp<. 000), as shown in Table 23, Other significant but moderate correlates included 

a 

pre-camp delinquency involvement (r=. 33 andpc. 002) and perceived support from parents in 

times of trouble (r=. 30 andp<. 004). 

“Table 23 about here” 

(3) Post-camp anests and (4) post-camp sustained petitions (or convictions) were also 

found to have far fewer significant correlates compared to those of the self-report measures, as 

shown in Table 24 and Table 25. The three leading variables significantly correlated with post44 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
camp arrests were post-camp self-report delinquency (non-drug related) (r=. 29 andp<. OQ5), pre0 camp arrests (r=.27 andp<.012), and the level of cultural assimilation (Le., Spanish spedcing 

families) (r=.27 andpc. 013). Even fewer variables were significantly correlated with post-cainp 

sustained petitions. The three leading correlates were the level of cu1tual assimilation (F. 45 and 

p<. 000), parental knowledge of the respondent’s friends and whereabouts (r=-.24 andp<. 0241, 

and the number of years the respondent lived in the neighborhood (r=-.24 andp<. 026). It 

appeared that respondents with limited level of cultural assimilation (who were born outside the 

US. and whose primary laiiguage at home was Spanish) were more likely to be associated with 

sustained petitioiis. 

“Table 24 and Table 25 about here” 

a Multiple regression analyses were also carried out to further explore variables that were 

influential on both self-report and official recidivism outcomes. With inference from tlie 

bivariate correlations, this study conducted stepwise regression and found few variables bearing 

significslnt impact on any of the four outcome measures, as shown in Table 26. All significant 

Pearson correlates of individual outcome measures were included in their respective stepwise 

regression models. 

: For post-camp delinquency, only two variabIes were found to have significant predicting 

effects-prwamp delinquency and perceived parental support in times of trouble. Higher precamp delinquency would predict higher post-camp delinquency involvement However, 

perceived parental support in times of trouble appeared to reduce post-camp delinquency. These 

two exogenous variables combined to explain 38% of the variance in the model. 

45 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
“Table 26 about here” 

For post-camp substance abuse, only two variables were found to have significant 

predicting effects-pre-camp substance abuse and post-camp delinquency. High levels of precamp substance abuse as well as post-camp delinquency involvement were predictive of high 

levels of post-camp substance abuse. Both independent variables combined to explain 30% ofthe 

variance in the dependent variable in the model, as shown in Table 26. 

For post-camp arrests, four variables were found to have significant predicting effectspost-cmp delinquency involvement, levels of cultural assimilation, pre-camp arrests, and 

eniployment. High levels of post-camp aeliiiquency involvement and the number of pre-camp 

arrests would more likely to bring about higher numbers of post-camp arrests. Participants who 

0 were foreign born and whose primary family language was Spanish were also likely to be 

arrested, Employment, on other hand, appeared to reduce subsequent re-arrests, These 

independelit variables combined to explain 26% of the variance in the dependent variable, as 

shown in Table 26. 

’ For post-camp sustained petitions, only one variable was found to have significant 

predicting power-levels of cultural assimilation, explaining 1 9% of the variance. Respondents 

.Who were born outside the US. and whose family primary language was Spanish were 

significantly more likely to receive sustained petitions, as shown in Table 26. Conversely, 

respondents who were born in the U.S. orland whose primary language at home was English 

were less likely to be adjudicated by the juvenile court after leaving the boot camp. 

46 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
DISCUSSION 

e This study utilized official and self-report measures in three separate components to 

gatlier data in an attempt to assess from different angles the effectiveness of the Drug Treatment 

Boot Cmp program in Los Angeles County Probation Department. The statistical. findings 

presented above were designed to provide a straightforward picture on the similarities (or 

differences) between youngsters who participated in tlie boot camp program and those who did 

not. More sophisticated multivariate analyses were also conducted to explore various protective 

as well as risk factors as they were related to treatment outcomes. For the most part, or at least 

among subjects of the inatched samples and those of the 12-month samples, about the only major 

finding was the lack of any clear and consistent improvement among boot camp participants over 

those of tlie traditional juvenile camps. This was particular true of official recidivism (Le., rearrests and adjudications). 

a Self-report measures, however, yielded more interesting findings. There was evidence to 

suggest that boot camp participants fared better than the comparison youngsters on drug related 

offenses, which was the main focus of the DTBC program. This improvement was evident 

among 12-month self-report samples and more pronounced in the pre-and-post cohort. In most 

other aspects of this evaluation, both boot cmp youngsters and their counterparts in the 

traditional camps were very similar. The following is a list of the main summary findings, 

First, despite the elaborative case matching procedure and the resulting comparable 

samples, the official data did not reveal any significant differences in arrests or adjudications 

between the boot camp participants and the youngsters from the traditional juvenile camp 

facilities. The only significant difference between the two groups was found on their post-camp 

probation violations. Because the boot cap participants were placed on smaller caseloads after 

47 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
camp exit, their technical violations were presumably more likely to be detected and acted upon, 

Overall, the boot camp program did not appear to have any effect on official recidivism in 

comparison to the traditional camp system. 

Second, for the 12-1nontli self-report samples, the case matching attempt for this 

component was aborted due to time constraints and difficulties in locating eligible and 

comparable subjects. The two samples, while comparable in their levels of pre-camp delinquency 

involvement (official as well as self-reported), were not as well matched on major demographic 

attributes (i.e., age and ethnicity). Despite their pre-camp comparability on non-drug related 

delinquency, the boot camp participants were significantly more involved in drug offenses; 

however, the significant differences were less pronounced in the post-camp period, an indication 

of the program effectiveness. In terms of post-camp arrests, adjudications (Le., sustained 

petitions), and probation violations, these two groups were very similar. Both groups were also 

very much alike on measures of self-esteem, perceptions of future prospect, mastery of one’s 

destiny, as well as attitudes towards authority. Even with more sophisticated statistical 

procedures, this study failed to liillc most post-camp chcanges to the DTBC program. 

Third, for the pre-and-post cohort, this study sustained heavy subject attritions; about one 

third of the T1 subjects were lost. The lost subjects tended to be older and Hispanic. It was in this 

sample that this study found the most positive signs of improvement. Despite the fact that the 

post-camp observation period was substantially longer than that of the pre-camp, a comparison of 

the subjects’ involvement in delinquency and drug offenses over these two time periods revealed 

consistent and across-the-board improvement. The only exception was drug usage, in which there 

was no difference over the pre-camp and post-camp periods. On attitudinal measures, the cohort 

appeared to have improved their relationships with their parents and school teachers. 

48 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Wliile the findings from the pre-md-post cohort revealed the most consistently positive 

a improvement after the youngsters left the boot camp, it would be difficult to draw a definitive 

connection between these changes and the DTBC program in light of the findings from the other 

two components. Because of the limited funding, this study was unable to obtain a comparison 

group from the traditional camps for the same longitudinal design. 

It ‘\vas speculated that some methodological issues might ,have contributed to the 

sigiiificant differences revealed in this longitudinal component of the stLldy. The T1 interviews 

were conducted while the juvenile offenders just entered the boot cmp. It was the impression of 

tile interviewers that many youngsters considered it a break from the demanding physical drills to 

talk to the interviewers on the phone. They did not seem to care much about the financial 

incentive so long as they could be away from everyone else in a quiet semi-private room for a 

while. These interviews lasted anywhere between 50 minutes to I .5 hours depending on the 

0 extensiveness of their pre-camp delinquency involvement, The implicit incentive in the 

avoidance of coilfrontations from the “drill sergeants” and the physical exercises could lead to 

increased reports of delinquent behaviors, The T2 interviews were conducted when the 

youngsters were at home or somewhere outside the cmp. By this time, the subjects had also 

been sensitized to the types of questions and structure of the interview. There could be a negative 

reaction based on their prior knowledge of the instrument on the p~ of the respondent who 

would deny having committed any offenses to cut short the interview. Additionally, there was the 

fatigue factor. The respondents could simply be tired of doing the interview again and chose an 

easy way out of the task based on their familiarity with the process. 

However when the average length of the interview was calculated for both waves of data 

collection, there was inadequate evidence to suggest my noise that had been introduced by the 

e 

49 

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has not been published by the Department. Opinions or points of view expressed are those

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Department of Justice.
fatigLne or the sensitization factor. Both waves of data collection were very similar in their medim 

length of interview (59.77 minutes for T1 interviews and 58.57 minutes for T2 interviews). The 

average length of interviews was actually longer for T2 (mear~69.43; std. deviation=49.43) than 

for T1 interviews (mea1~55.07; std. deviation=30.52). In other words, subjects at the T2 

interviews in general spent as much time as they did at T1. 

Besides methodological issues,'it may also be possible that juvenile offenders had indeed 

benefited from a period of incarceration and shock treatment in the juvenile canip. On the other 

hand, it may also be possible that the Los Angeles juvenile boot camp, now left alone by the 

news media and out of the public limelight, came to focus on the .substance rather than on the 

image, and the positive outcomes were products of R more sober-minded staff realistic about 

what they were able to accomplish. Furthermore, the organizational chmges, resulting iii a much 

shorter boot camp program, may have inadvertently produced positive results, by reducing their 

exposure to the labeling justice environment, Unfortunately the current design was not able to 

reconcile the different findings between the first two components with the last one. 

Obviously the role of boot camp in juvenile corrections is not likely to be swayed by this 

or other studies. Whether boot camps continue to remain a viable alternative for adult and 

juvenile offenders depends mostly on what the program administrator attempts to achieve. It is 

fair to say that the boot camp program, as implemented and administered in Los Angeles County, 

Was no more effective than its other juvenile facilities in reducing official recidivism. . 

Since boot camps appeared some 15 years ago, many studies have been conducted and the 

findings have consistently pointed to their ineffectiveness as a correctional model. Whether boot 

camps are used to alleviate jail/prison overcrowding, divert prison-bound offenders, .or to provide 

intermediate or alternative sanctions, one finding remains consistent from most studies-up to 

50 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
- date, that is, they are not effective in reducing official recidivism or increasing pro-social 

activities, 

In an attempt to identify what variables that appeared to bear significant impact on the 

program outcomes, this study was able to identify several, most important among which were 

pre-camp delinquency involvement or pre-camp drug offenses. While other variables such as the 

subjects’ perceptions of fiLt1u-e opportunities and general levels of stress were also found to be 

predictive of the.outcomes, none of the boot camp program measures were found to be related to 

any of the behaviord outcomes. 

Several factors may have affected the outcomes of this study. First, significant 

programmatic changes took place during the study. The most important one was the shortened 

program (from six months down to about IO weeks). The selection of program participants 

changed from a countywide pool screened by the central Camp Placement Unit to that of regional 

mandatory placement from the local juvenile court. Significant staff turnover occurred, mostly at 

the director’s level, making it difficult to maintain the same management style or program 

integrity over time, Although these meddling factors may have affected the integrity or 

consistency of the program, this study attempted to overcome these interfering factors by 

gathering data from multiple sources and at different points in time to gauge the effectiveness of 

the DTBC program. By and large, the findings from this study were consistent with the existing 

. 

literature. 

The present study made an argument on using alternative approaches and analytical 

strategies to improve our understanding of boot camps as a treatment modality, such as the use of 

self-report data and assessment of non-programmatic factors as related to offenders’ change. 

Needless to say, results from the self-report data in the present shtdy probably have added 

.. 

51 

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has not been published by the Department. Opinions or points of view expressed are those

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Department of Justice.
- . additioiial confiision to the pool of findings that are already complex and difficult to interpret. 

However, the self-report data appeared to have yielded rnore’interesting findings between the 

boot camp subjects and their counterparts in the traditional camps or before and after their 

participation in the program. Similar findings have not been reported elsewhere in the 1iteratLue. 

The search for information to explicate the functions of different program components 

and explain why some offenders succeed while others fail requires researchers to resist the . 

temptation to address the simple question: “Does boot camp work?y’ Such a blanket question 

increases the chances of drawing misleading and simplistic conclusions, which will in turn lead 

either to smminarily dismissing or to unduly extolling boot ccmps as a correctional option. 

Although the present study built its rationale on methodological issues, it would be unfair to 

suggest that the lack of consistent findings thus far was due to inadequate research designs. It 

may very well be true that boot camps as currently designed and implemented are indeed 

ineffective. 

Based on site visits and conversations with boot camp participants, staff and 

administrators, the Drug Treatment Boot Camp did appear very different fiom the traditional 

camps, such as the paramilitary organization, rituals (Le., salutations and roll calls), ceremonies, 

uniforms, drills, and summary punishments. However, these were superficial differences. The 

present study did not find the DTBC to be much different from the traditional camps in 

counse1ing;parental involvement, and educational activities. Similar results were also found in 

other studies, in which comparison was made on boot camp and traditional camp participants, 

their daily activities, structural and therapeutic environments (Gover et. al., 1998; Lutze, :1,998). 

These studies found differences h the &e of summary ptmishments, client screening, militaristic 

rituals, but not in therapeutic activities. 

a. 

52 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
The lack of therapeutic activities or the lack of a combination of therapeutic and 

regimented environment may account for the lack of differences in outcomes between boot 

camps and traditional camps. Future studies should examine non-programmatic factors and 

conditions, which are capable of influencing program outcomes irrespective of the particular 

treatment approach (Palmer 1995). For example, using the same self-report index developed by 

MacKenzie and Shaw (1 990), McCorkle (1 995) found that both boot participants and their 

prison comparison inmates became more pro-social, which raised doubts about the necessity of 

the military atmosphere to improve behavior and suggested that the attitudinal improvement was 

likely due to factors extraneous to the boot camp program (e.g., staff competence and 

commitment, program integrity, and the timing, of intervention). 

These non-progrcunrnatic factors may help expIah why some programs had a positive 

influence on certain offenders while others did not. Palmer (1 995) classified these factors into 

four categories: (1) staff characteristics (e.g., personal styles, volunteers/professionals, 

commitment, and competence), (2) quality of stafflclient interactions (e.g., surveillance, control, 

and self-expression), (3) individual differences among offenders (personalities and maturity 

levels), and (4) program settings (e.g., institutional, non-institutional, and direct parole). For 

instance, Jesness (1 975) found that positive changes occurred more often when the delinquents 

felt positive toward the staff, while Kelly and Baer (1971) found that delinquents reacting to 

situational stress associated with their developmental stage (e.g., identity crisis) were more 

responsive to a wilderness program than those who were immature andor emotionally disturbed. 

Boot camps are operated by staff of varying personalities md professional qualifications. 

The program’s goals and strategies as well as non-programmatic factors all interact with the 

characteristics of the delinquents to produce certain outcomes. The effectiveness of boot camp 

53 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
treatlnent is thus mediated by two sets of variables--individual differences and non-programmatic 

factors. On the one hand, a boot camp with a high level of program integrity (i-e., least disruption 

and higli consistence in treatment activities) is more likely to produce successfLi1 outcomes, wheiz 

the iiivolved staff are well trained and motivated, and when the staff-client interactions are 

positive. The non-programmatic factors can be further divided into two parts--in-camp and 

aftercare. The aftercare phase involves factors’ slightly different from the in-camp ones, in which 

family interactions, social s~ipport network, and community environment may play an important 

role in treatment effectiveness. On the other hand, offenders’ individual factors such as prior 

history, substance abuse, and the age of onset will combine to influence the effectiveness of boot 

camp treatment. Neither set of variables (individual and non-programmatic) can fimction 

independently of the otlier; instead they are expected to have interactive effects on program 

outcomes. 

a Most boot camp studies, including the present one, examined only programmatic . 

components and their connections with certain outcomes. To this end, Palmer’s review (1995) 

offered an excellent guide for fiiture studies on specific programmatic and non-programmatic 

factors to be included in a systematic manner. The task of identifying effective combinations of 

treatment components and non-programmatic factors is formidable. Aside from the many 

treatment strategies, the four areas of non-programmatic factors each consist of numerous 

features or variables. The complexities involved in the search for successful combinations 

require researchers to develop clear and precise conceptual frameworks on which systematic data 

items and assessment strategies can be plotted. As Palmer (1 995) pointed out, a holistic approach 

in an evaluation strategy would require long-term, multi-study research projects focusing on non54 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
yrogrcvnmatic as well as programmatic factors in an effort to determine the specific combinations 7 

of treatlnent modalities that lead to the most successfLi1 outcomes. 

At a policy level, the lack of positive effects in most studies begs all of those in the 

position to make programming decisions to think through the issue of why anyone should expect . 

boot camp to be effective. There is a significant gap (or clear linkage) between the 

conceptualization of a treatment model and its intended outcomes. The question for policym&ers 

here is not why boot camps have failed to produce suiccessfid outcomes, but why we should 

expect them to be effective in the first place. Lacking a clear conceptualization of what effects 

different components of boot camp programs are supposed to produce and how they are supposed 

to produce them, most policy makers thus far have relied on their political convictions or 

“common-sense” to plan treatment programs for youth as well as adult offenders. In an ideal 

world, decision makers in correctional agencies should converse with evaluators first before any 

0 significant financial and human resources are invested in a treatment program. Unfortunately, in 

reality political pragmatism usually takes precedence. 

Lessons learned from this project 

Several lessons can be drawn from this project. First and foremost, the integrity of a 

project depends on the agency commitment to the project, not only at the management level, but 

*also at the line officer level. In a sense, it is more important to secure commitment from the line 

officers who eventually supply the detailed information about the individual subjects in the study. 

When tracking and locating subjects must take place, these officers can either facilitate data 

collection in a timely manner, or insist on following the “proper” procedure to stall the progress 

of the project. In this study,’while the management of the Los Angeles Co,unty Department, from 

55 

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has not been published by the Department. Opinions or points of view expressed are those

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Department of Justice.
the boot camp director to the bureau chief, was more than helpful in answering the investigator’s 

0 inquiries and providing all necessary administrative assistance, the responses fiom the line 

officers were often slow, and the follow-up information was often incomplete or outdated. 

Second, the timing of project implementation is crucial. Often, researchers worlcing with 

justice agencies find it difficult to control or even anticipate changes to the program under 

evaluation. A portion of the present study was caught in the middle of restructuring, consequently 

the original design was compromised and the subjects included in this study did not receive the 

treatment as the program was originally designed. The subjects in the pre-and-post cohort in this 

study received far less expostire to the boot camp environment and there was also significant 

change in the ethnic composition as a result of the camp regionalization, thus malung findings 

from this component less comparable to those of the other two components. 

Third, alternative methods or contingency plans must integrated into any evaluation 

0 design as well as corresponding budgetary concerns. By the time the principal investigator of this 

study realized the scope and significance of the programmatic changes, there was no budget to 

support any salvaging strategies. While it may be unreasonable to add contingency budgetary 

items as a part of the evaluation proposal, in practice it may be imperative since few programs 

are ever carried out as they were originally designed. When a treatment program is drastically 

changed, the evaluator is often forced to compromise the original research design or to 

. compensate with statistical manipulation, both of which can only be considered handicaps from a 

methodological point of view. 

56 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
REFERENCES 

Anderson, J.F., Dyson, L. and Burns, J.C. (1 999> 

Boot Camps: An intermediate sanction. New York: University Press of America. 

Andrews, D. A., Zinger, I., Hoge, R. D., Bonta, J., Gendreu, P., and Cullen F. T. (1990) 

Does correctional treatment work? A clinically relevant and psychologically informed 

meta-analysis. Criminology 28(3): 369-404. 

Austin, J., Jones, M., and Bolyad, M. (1993) 

The Growing Use of Jail Boot Camps:‘ The Curmnt State of the Art. Research in Brief. 

Washington, D.C.: U.S. Department of Justice, National Institute of Justice. 

Backstrom, C, H. and Hursh, G. D. (1963) 

Survey Research. Evanston, Ill.: Northwestern University Press. 

0 Blackmore, J. (1 974) 

“The Relationship between Self-Reported Delinquency and Official Convictions amongst 

Adolescent Boys.” British Journal of Criminology 14: 172-1 76. 

Bottcher, J. (1995) 

LEAD: A Boot Camp and Intensive Parole Program-A Summary of Preliminary 

Evaluation Findings. Sacramento, CA: California Youth Authority. 

Cronin, R. C. (1994) 

Boot Camps for Adult and Juvenile Offeenders: Overview and Update. Washington, D.c.: 

National Institute of Justice. .: 

Empey, L. T. and Stafford, M. C. (1991) 

57 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
American Delinquency-Its Meaning nnd Construction. Belmont, CA: Wadswortli 

Publisliing. 

Ericltson, M. L. and Empey, L . T. (1963) 

“Court Records, Undetected Delinquency, and Decision-Making.” Journal of Criminal 

Lmv, Criminology and Police Science 54 (December): 456-469. 

Gibson, H. B., Morrison, S., and West D. J. (1970) 

“The Confession of I<nown Offenses in Response to a Self-Reported Delinquency 

Schedule.” British Journal ofCriminology 10:277-280. 

Gover, A, R., MacKenzie, D. L., and Styve, G. J. (1998) 

Boot Camps and Traditioanl Correctdional Facilities for Juveniles: A Comparison of the 

Participants, Daily Activities, and Environments. A paper presented at the 1998 annual 

meeting of the American Society of Criminology, Washington, D.C. 

@ Gransky, L. A., Castellano, T. C., and Cowes, E. L. (1995) 

“1s There a ‘Second Generation’ of Shock Incarceration Facilities?: The Evolving nabre 

of Goals, Program Elements and Drug Treatment Service in Boot Camp Programs.” In J. 

Smylcla and W. Selke, eds., Intermediate Sanctions: Sentencing in the 1 990s, Cincinnati, 

Ohio: Anderson Publishing Co., pp. 89-1 12. 

Hunter, R. J., Burton, V, S., Marquart, J. W., and Cuvelier, S. J. (1992) 

“Measuring Attitudinal Change of Boot Camp Participants.” JuurnaZ ofContemprary 

Criminal Justice 8(4): 283-298. 

Jesness, C. F. (1 975) 

“Comparative Effectiveness of Behavior Modification and Transactional Analysis 

Programs for Delinquents.” Journal of Consulting and Clinical Psychology 43 :75 8-79. 

58 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
- Junger-Tas, J. Klein, M. W., and Zhmg, X. (1992) 

‘‘Problems and Dilemmas in Comparative Self-Report Delinquency Research.’) In D. p. 

Farrington and S. Walklate, eds., Oflenders and Victims: Theory und Policy, London: 

British Society of Criminology and the Institute for the Study and Treatment of 

Delinquency. 

a 

Jwger-Tas, J. Terlouw, G. T., and Klein, M. W. (1994) 

Delinquent Behavior Among Youngsters in the Western World. ” Amsterdam: Kugler 

Publishing. 

Kelly, F. J. aid Baer, D. J. (1971) 

“Physical Challenge as a Treatment for Delinquency.” Crime and Delinquency 17:437- 

47 * 

Lutze, F. E. (1 998) 

0 “Are Shock Incarceration Programs More Rehabilitative than Traditional Prisons? A 

Survey of Inmates.” Justice Quurterly 15: 547-66. 

MacKenzie, D. L. (1993) 

“Boot Camp Prisons in 1993 .” National Institute of Justice Journal November: 2 1-28. 

MacKenzie, D. L. and Shaw, J. W. (1990) 

“Inmate Adjustment and Change During Shock Incarceration: the Impact of Correctional 

Boot Camp Programs.” Justice QuarterZy 7(1):125-149. 

MacKenzie, D. L., Brarne, R., McDowall, D., and Souryal, C, (1995) 

. 

“Boot Camp Prisons and Recidivism in Eight States.” Criminology 3(33): 327-357. 

MacKenzie, D. L, and Souryal, C. C. (1995) 

59 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
A ”Machiavellian” Perspective on the Development of Boot Camp Prisons: A Debate. 

a Uiiiversity of Chicago Roundtable. Chicago: University of Chicago Press. 

MacKenzie, D, L. md Sor~ryal, C. C. (1991) 

“Boot Camp Survey--Rehabilitation, Recidivism Reduction Outrank Punishment AS 

Main Goals.” Corrections Today October: 90-96. 

McCorlde, R. C. (1995). “Correctional Boot Camps and Change in Attitude: Is All This Shouting 

Necessary? A Research Note.” Justice Quarterly 12365-75. 

Maltz, M.D. (1984) 

Recidivism. New Yorlc: Academic Press. 

Mitchell, O., MacKenzie, D. L., Gover, A. R., and Sfyve, G. J. F. (1998) 

National Evaluation of Juvenile Correctional Facilities: Staff Perceptions of the 

Environment and Working Conditions. A paper presentation at the 1998 Annual meeting 

e of the American Society of Criminology, Washington, D.C. 

Morash, M. and Rwker, L. (1 990) 

“A Critical Look at the Idea of Boot Cmp as a Correctional Reform.” Crime and 

Delinquency 36(2):204-222. 

. Palmer, T. (1 995). “Programmatic and Nonprogrammatic Aspects of Successful Intervention: 

. New Directions for Research.” Crime and Delinquency 4 1 : 1 00-3 1. 

Petenilia, ,J. and Turner, S . (I 990) 

Intensive Supervision for High-Risk Probationers: Findings from Three California 

Bxperiments. Smta Monica, CA: The Rand Corporation. 

Polslcy, H. imd Fast J. (1993) 

60 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
“Boot Camps, Juvenile Offenders, and Culture Shock.” Child & Youth Care Forum, 

.@ 22(6): 403-415. 

Ransom, G. and Mastrorilli, M. E. (1 993) 

“The Massachusetts Boot Camp: Inmate Anecdotes.” The. Prison Journal 73(3/4): 307- 

318. 

Reuter, P.,’MacCoun, R., and Murphy, P. (1990) 

Moneyyfrom Crime: A Study of the Economics of Drug Dealing in Washington, D. C. 

Santa Monica, CA: RAND. 

Schmidt, P. and Witte, A. D. (1 988) 

Predicting Recidivism using Survival Models. New York: Springer-Verlag. 

Souryal, C. and MacKenzie, D. L. (1995) 

“Shock Incarceration and Recidivism: An Examination of Boot Camp Programs in Four 

a States.” In J. Smyltla and W. Selle, eds., Intermediate Sanctions: Sentencing in the 

199Os, Cincinnati, Ohio: Anderson Publishing Co., pp. 57-88. 

Stye, G. J., MacKenzie, D. L., Gover, A. R., and Mitchell 0. (1 998) 

“Perceived conditions of Confinement in Juvenile Correctional Institutions: A National 

Evaluation of Boot Camps and Traditional Facilities.” A paper presented at the annual 

meeting of American Society of Criminology, Washington, D.C. 

Toby, J. and Pearson, F S. (I 992) 

“Juvenile Boot Camps, 1992” in Boot Camps for Juvenile Offenders: ‘Constructive 

Intervention and Ear& Support-lmplemen~ation Evahation, a final ‘report to the National 

Institute of Justice. 

Williams, J. R. and Gold M. (1972) 

61 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
“From Delinquent Behavior to Official Delinquency’’ Social Problems 20(Fall): 209-229. 

Zhang, S. X. (1998) 

In Search of Hopeful Glimpses-A Critique of Research Strategies in Current Boot Camp 

Evaluations. Crime and Delinquency, 44(2): 3 14-334. ’ 

Zhang, S. X., Polakow, R., and Nidorf,:B. J. (1994) 

‘‘Varied Uses of Electronic Monitoring: The Los Angeles County Experience.” In J. 

Smykla and W. Sellte, eds., Intermediate Sanctions: Sentencing in the 1990~~ Cincinnati, 

Ohio: Anderson Publishing Co., pp. 3-20. 

Zhmg, S. X., Benson, T., andDeng, X. (2000) 

A Test and Re-test of the International Self-Report Delinquency Instrument. Journal of 

Criminal Justice, 28: 283-295. 

62 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Figure I. An Overview 0: 

Components: 

Sources of data: Official records from 

Los Angeles County and 

California State 

Criminal justice files 

Official arrest, petition, 

and disposition records 

prior and post camp; 

basic demographic 

Type of data 

Samples 

Telephone interview and 

oficial records from 

Los Angeles County and 

California State justice 

files 

Self-report delinquency, 

demographic, social and 

academic information; 

arrest and disposition 

Cohorts’ range of 

dates of release for 

inclusion 

Construction of 

comparison groups 

information 

4f92- 12/93 

Sample size 

Differences found 

between boot camp 

participants vs. 

comparison 

information 

12/95-3/97 

II Evaluation of the Los Angeles County Juvenile Dru 

Matched Samples 1 12-Month Self-Report 

Case matching on 

ethnicity, age, and prior 

arrests (with gender as a 

Unsuccessful match on 

ethnicity and age (with 

gender as a constant). 

constant). 

Boot camp: 427 

Comparison: 427 

None in re-arrests and 

Boot camp: 100 

Comparison: 100 

None in re-arrests. 

sustained petitions; 

more probation . violations 

sustained petitions, and 

probation violations; 

overall decline in selfreport delinquency but 

few differences between 

the groups. 

Treatment Boot Camp 

Pre-and-Post Cohort 

Telephone interviews 

and official records froin 

Los Angeles County and 

California State justice 

files 

Self-report delinquency, 

demographic, social and 

academic information; 

arrest and disposition 

information 

3/97 - lot97 

Panel design, with preand-post comparison of 

the same group of boot 

camp participants. 

Pre: 137 (at TI) 

Post: 89 (at nj 

Significant decline in 

self-report delinquency; 

more school enrolment; 

mixed in attitude 

measures. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
INTERVIEWER 

Many young people do things that are not ushlally permitted. We would like to know if 

you have done some of these things. Remember that all your answers are confidential 

and no one except the researchers will ever see them. Now I will read to you a number 

of activities and you can tell me then if you did these things, yes or no. 

(1)no (2)yes 010. Did you ever stay away f!rom school for at least a whole day 

without a legitimate excuse? 

(1)no (2)yes 020. Did you ever run away from home to stay somewhere else for 

one or more nights without your parents or guardian's 

permission? 

(1)no (2)yes 040. Did you ever travel on a bus without paying? 

(1)no (2)yes 060. Did you ever drive a car, a motorcycle or a moped without a 

license or insurance? 

(1)no (2)yes 070. Did you ever write or spray grafiiti on walls, buses, bus seats, 

shelters, etc.? 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Figure 3. An Example of ISRD Detailed Questions Following the Filtering. Questions 

INTERVIEWER: 

You mentioned staying away from school for at least a whole day, without a 

legitimate excuse. 

01 1. At what age did you do it for the first time? 

- years old 

012 Did the police ever find out that you did it? 

(1) no (2) yes (3) don't know 

0 13. Did you do it during this last year? 

(1) no ---> nextspecific subject (2) yes ---2 How often this last year? 

- times 

014, Speaking about the last time, how many days did you stay away? 

- days 

01 6. Where did you spend most of the time? 

(1) at home or the place you live, or witlh a 10 minute walk from 

your home or the place you live 

(2) at a shopping center/shopping mall 

(3) downtown or in the city center 

(4) somewhere else, namely: 

017. Did you do this alone or with others, then? 

(1) alone 

(2) with (approx.) - others 

01 8. Were you caught? 

(1) no > by whom? ( ) yes ------------- 

(2) parents (6) accidental witness(es) 

. (3) storestaff (7) police 

(4) teachers/school staff 

(5) public transport staff 

(8) other namely: 

019. what happened to you when you were caught? 

0 Does not apply (was never caught) 

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has not been published by the Department. Opinions or points of view expressed are those

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Department of Justice.
Table 1. Descriptive Statistics for Matched Samples 

Comparison Camps Boot Camps 

Frequency Percent' Frequency Percent 

Ethnicity 

African American 76 18 76 18 

Hispanic . 282 66 282 66 

White 69 16 69 16 

16-year-old 123 29 123 29 

17-year-old 195 46 I95 46 

1 8 -year-old 109 25 109 25 

0-1 arrests 72 17 72 17 

2-4 arrests 179 42 179 42 

5 or more 176 41 176 41 

Age 

Prior arrests 

(Total)b (427) (1 00) (427) (100) Length of camp stay (days) 

Mean 155.98 159.29 

Median 145.00 155.00 

Std. Dev. 46.98 29.96 

Max.-Min. 100-3 58 103-3 1 8 

Mean' 4.28 4.2 1 

Median 4.29 4.20 

Std. Dev. .43 .42 

Time out of camp (years) 

Max.-Min. 3.50-5.07 3.5 0-5.19 a Percentages were rounded in this and all subsequent tables. 

Gender was a constant in this study (males only). 

Significant differences were found between the two groups in the years since they left 

their respective camps; t= 2.32, dp852, p<.05 (two-tailed). 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 2. Outcomes of Matched Samples 

Comparison Camps Boot Camps 

Post Camp Arrests 

No arrest 

3-4 arrests 

5 or more arrests 

1-2 arrests 

Mean 

Std. Dev. 

Post Camp Sustained 

Petitions: 

No sus. petition 

1-2 sus. petitions 

3 or more sus. petitions 

Mean 

Std. Dev. 

Post Camp Probation 

Violations: 

No violation 

1 or more violations 

Meana 

Std. Dev. 

Frequency 

61 ’ 

120 

105 

141 

3.78 

3.47 

139 

197 

91 

1.53 

1.59 

40 1 

26 

.10 

.50 

Percent Frequency 

14 64 

28 127 

25 106 

33 130 

33 141 

46 209 

21 77 

93.9 370 

6.1 57 

3.54 

3.05 

1.41 

1.52 

.16 

-44 

Percent 

15 

30 

25 

30 

33 

49 

18 

86.7 

13.3 

(Total) (427) (1 00) (427) (1 00) 

~2.03, d’852,p<.05 (two-tailed). 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

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Department of Justice.
Table 3. OLS Regression Analysis of Matched Samples 

Dependent Variables: Postcamp Arrests Postcamp Sus. Petitions 

Independent Variables : Beta t-ratio Sig. Beta t-ratio Sig. 

(Constant) 2.62 .01 1.26 .21 

Number of probation violations .13 4.25 .OO -.01 -.43 .67 

African American (dummy var.) -.02 -.59 .55 -.11 -2.56 .01 

Type of Camp (dummy var.) -.04 -1.4 .15 -.04 -1.37 .17 

Hispanic (dummy var.) -.o 1 -.I1 .91' -.03 -.70 .48 

Length of camp stay (days) -.01 -.04 .96 .07 2.07 .04 

Prior arrests to camp instant .13 3.89 .OO .13 3.66 .OO 

Lapsed time from camp exit to 1' arrest -.47 -15.66 .OO -.41 -12.78 A0 

Age at camp exit -.02 49 .55 .01 .08 .93 

Age of first official arrest -.04 -1.16 .24 -.02 -.69 .49 

R'=.30; Adj. Rz=.29 RL=.21; Adj. R2=.20 

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Table 4. Descriptive Statistics of 12-Month Self-Report Samples e Comparison (N=100) Boot Camp (N=lOO) 

Percent 

Ethnicity:a 

African American 33 

Hispanic 58 

White 9 

15 or younger 15 

16 33 

17 27 

18 25 

Age (at camp entry): 

Mean 

Median 

Std. Dev. 

Length of camp stay: 

Mean 

Median 

Std. Dev. 

0-1 arrests 20 

2-4 arrests 47 

5 or more 33 

Prior arrests 

Mean 

Median 

16.54 

17.00 

1.18 

130.34 

121.00 

54.83 

3.57 

3 .OO 

Percent 

I1 

73 

16 

2 

27 

37 

34 

22 

48 

30 

17.03 

17.00 

.83 

125.90 

126.50 

44.80 

3.32 

3.00 

Std. Dev. 2.58 2.03 

Pre-camp self-report 

delinquency 

Non-drug offenses 9.65 10.72 

Mean 10.00 11 .oo 

Median 4.62 4.36 

Std. Dev: 

Drug offenses' 3.36 4.23 

Mean 3 .OO 4.00 ' 

Median 1.63 1.18 

Std. Dev. 

"X'=14.68; df-2; p<.OOl (two tailed). 

~3.38; d!198;p<.001 (two tailed). 

~4.32; dpl98;p<.001 (two tailed). 

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has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Status offenses Comparison 2.76 .91 

Boot camp 2.94 .95 

VandaIism Comparison 

Boot camp 

.99 .87 -2.02 .04 

1.23 .82 

Theft Comparison 3.97 2.61 -2.36 .02 

Boot camp 4.82 2.48 

Violent offenses Comparison 1.93 1.57 .88 .38 

Boot camp 1.74 1.46 

All non-drug offenses Comparison 9.65 4.62 -1.68 .09 

Boot camp 10.72 4.36 

Drug use 

Drug sale 

Comparison 

Boot camp 

Comparison 

Boot camp 

2.80 1.19 -4.49 .oo 

3.44 .78 

*56 .76 -2.07 .04 

.79 .81 

0 All drug offenses Comparison 3.36 1-63 -4.32 .oo 

Boot camp 4,23 1.18 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

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Department of Justice.
e Table 6. Descriptive Statistics of Post Camp Self-Report Delinquency among 12-Month Sample 

Offenses Camp Type Mean Std. Dev. t Sige (2-tailed) 

Status offenses Comparison 1.02 1-03 -1.32 .19 Boot camp 1.22 1.11 

Vandalism Comparison 

Boot camp 

.18 .50 -.84 , 

.24 .5 1 

.40 

Theft Comparison .6 1 1.15 -2.02 .05 

Boot camp 1.02 1.67 

Violent offenses Comparison 

Boot camp 

All non-drug offenses Comparison 

Boot camp 

Drug use comparison 

Bootcamp ' 

Drug sale Comparison 

Boot camp * All drug offenses Comparison 

boot cam^ 

SO 

.65 

*79 -1.13 .26 

1.07 

2.3 1 2-54 -1.95 

3.13 3.35 

1.35 

1.68 

1.05 . -2.25 

1.02 

.05 

.03 

.13 -42 -1.11 .27 

.20 .47 

1.48 

1.88 

1-23 -2.26 

1.27 

.03 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 7. Post Camp Official Delinquency Outcomes among 12-Month Sample e Comparison (N=dOO) Boot Camp @=loo) 

Post camp arrests Frequency Frequency 

No arrest 44 47 

1-2 arrests 35 25 

3 or more 21 18 

Mean 1.37 

Median 1 .oo 

Std. Dev. 1.68 

Post camp sustained petitions 

No sustained petition 70 

1-2 30 

77 

23 

1.05 

1 .oo 

1.31 

Mean .36 .26 

Std. Dev. .59 SO 

Median .oo .oo 

Probation Violations 

No Violations 88 88 

1-2 Violations 12 12 

Mean .18 .18 

Std. Dev. .59 .52 

Median .oo .oo 

Note: No significant differences were detected on any of the measures, 

e 

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Department of Justice.
Table 8. Post Camp Social Activity Measures (In Percent) 

Comparison Boot Camp 

(N=100) (N=lOO) 

1. Attending School at the Time of Interviewa 

a - 

(1) No 

(2) Yes 

2. Working 

(1) No 

(2) Yes 

(1) No 

(2) Yes 

(1) No 

3. Participation in Organized Sports 

4. Involvement in Gangs 

32 49 

68 51 

58 61 

42 39 

60 72 

40 28 

76 77 

(2) Yes 24 23 

a. 2 = 6.00; d’l;p<.03. 

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has not been published by the Department. Opinions or points of view expressed are those

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Department of Justice.
1. 

2. 

3. 

4. 

Table 9. Post Camp Attitudinal Measures among 12-Month Sample 

Comparison Boot Camp 

(N=lOO) @=loo) 

a 

Self-esteem Measures 

(1) Peer Related Measures 

(Cronbach's alp ha=O .66) 

(2) Family Related Measures 

(Cronbach's alpha =0.89) 

(3) School Related Measures 

(Cronbach's alpha = 0.80) 

Perceived Future Prospect 

(Cronbach's alpha = 0.76) 

Mastery of One's Future 

(Cronbach's alpha = 0.76) 

Attitudes towards Authority 

(Cronbach's alpha = 0.69) 

Mean 

Std. Dev. 

Mean 

Std. Dev. 

Mean 

Std. Dev. 

Mean 

Std. Dev. 

Mean 

Std. Dev. 

Mean 

28.19 

3.69 

34.71 

4.87 

24.44 

3.87 

33.91 

4.23 

14.67 

2.85 

44.97 

28.24 

3.44 

34.44 

6.29 

23 -92 

4.19 

34.20 

4.56 

14.24 

3.42 

44.86 

Std. Dev. 4.05 3.84 -. 

Note: No significant differences were detected on any of the measures. 

a 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 10. Post-Camp Services Received among 12-Month Sample 

Comparison Boot Camp 

1. Tutoring (Separate from Regular Sch, Classes) No 77 83 

2. 

3. 

4. 

5. 

Yes 23 

0 (98) 

Recreation /Sports through an Agency a No 82 

Yes 18 

@) (98) 

Job Training or Placement No 62 

Yes 38 

N) (100. 

Personal and Family Counseling No 78 

Yes 22 

0%) (1W) 

Drug and Alcohol Education /Counseling No 74 

Yes 26 

17 

(9 7) 

92 

8 

(99) 

60 . 

40 

(99) 

80 

20 

(100) 

41 

59 

W) (100) (9 7) 

a. x" = 4.55; dpl;p<.04. 

b. J? = 21.68; d'I;p<.OOl. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 1 1. Camp Experience among 12-Month Sample 

Comparison Boot Camp 

1. The camp experience was a 

a. Awful and I hated it 

b. Okay 

c. Pleasant and I enjoyed 

(N) 

2. The camp experience 

a. was a waste of time/made me a worse person 

b. made me a better person 

0 

a. 0 

b. 1-3 Times 

c. 4 or More 

3. Self-Report Camp Disciplinary Actions 

(N) 

4. Official Disciplinary Actions 

a. No 

b. 1-3 Times 

37.0 

49.0 

14.0 

(1 00) 

23.5 

76.5 

(98) 

33.7 ' 

36.7 

29.6 

(98) 

100 

0 

17.0 

49.0 

34.0 

(1 00) 

16;O 

84.0 

(100) 

37.4 

41.4 

21.2 

(99) 

74 

26 

b.2 = 29.89; dpl;p<.OOl. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 12. Significant Correlates of Post-Camp Delinquency among 12-Month Self-Report Samples* 

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 

1.INDXALL l.OOOn 

h 

200' 

.ooo 

2.POSDRUG .529 1.000 

200 200 

3.PlQ4 .177 .Ol8 1.000 

.012 .799 . 200 200 200 

4,'DUOPARNl -.150 -.loo .194 1.000 

,033 .159 .006 . 200 200 200 200 

,017 ,000 .354 .508 . 196 196 196 196 196 

,000 .OOO .150 .009 ,795 . 199 199 199 199 195 199 

.003 .006 .524 .OOO .8 10 .004 , 

199 199 199 I99 195 198 199 

,001 ,169 ,731 .498 .630 .060 .218 . 118 118 118 118 116 117 117 118 

.OOO .I12 .lo7 .090 .432 ,039 .661 .003 

200 200 200 200 196 199 199 118 200 

.006 .223 I 179 .07 1 .005 ,880 ,827 .OOO .OOO . 200 200 200 200 196 199 199 118 200 200 

.OOO .094 .164 ,867 .001 .202 ,562 .OOO .I94 .OOO . 199 199 199 399 195 198 198 118 199 199 199 

5.PRNICNOW -.170 m.272 -.066 -.048 1 .OOO 

6.SUBEXPO .313 .302 .lo2 -.I85 -.O19 1.000 

7.P 1Q 17 .208 ,195 .045 -.333 .017 202 1.000 

8.ESTEEM3 -303 .127 .-,032 -.063 -.045 .I75 .115 1.000 

9.P4Q6B .249 .I13 .I 14 -.120 m.056 .147 .031 .269 1.000 

10,FUTURE -.195 -.087 -.095 .128 .198 1.011 .016 -.475 -.249 1.000 

11.SELFESTl .252 .119 .099 -.012 -.242 .091 -.041 .565 .092 -.573 1.000 

I2.MASTERY .I86 ,075 .070 -.068 -.267 .082 .007 .58I ,130 m.578 -659 1.000 

-008 .293 .322 .339 .OOO ,252 .927 .OOO .067 .OOO .OOO . 200 200 200 200 196 199 199 118 200 200 199 200 

.OOO ,000 ,657 .091 .008 ,000 .002 .120 ,027 347 ,080 .409 . 200 200 200 200 196 199 199 118 200 200 199 200 200 

.OOO .OOO .316 .023 .030 .OOO .002 .004 ,004 .330 .001 .023 .OOO . 200 200 200 200 196 199 199 118 200 200 199 200 200 200 

-013 ,168 .158 .916 .210 -781 ,129 .078 ,104 .006 .075 .lo0 .713 .255 . 198 198 198 198 194 197 197 I18 198 198 197 198 198 198 198 

I3.PRIDRUGl .289 .619 .032 -.I20 -.I88 ,303 .217 .144 ,156 -.014 .125 .059 1.000 

L4.PRTSELF .542 .431 ,071 -.161 -.I55 .288 220 .266 .203 -.069 .244 ,161 .510 1.000 

I5 .P9Q4 -.177 -.098 -.lo1 .008 .090 m.020 -.lo8 -.I63 -.116 ,194 -.I27 m.117 -.026 -.081 1.000 

6.P9Q5A .188 .118 .110 -.Ob1 -.091 ,003 .210 -111 .150 -.039 .013 .060 .I29 .239 -.174 1.000 

-008 ,097 -122 .395 .209 .963 .003 ,236 .035 .589 354 .405 .071 .001 ,015 . 197 197 197 197 193 197 196 116 197 197 196 197 197 197 196 197 

.021 ,106 .006 .73 1 .077 .492 ,089 .002 .03 1 .004 .03 1 .008 .308 .O 19 ,000 .095 . 199 199 199 199 195 198 198 117 199 199 198 199 199 199 197 196 199 

7.NHOOD -.163 -.I15 -.I93 .025 -127 -.049 -.I21 -.284 -.153 .205 w.154 -.187 -.073 -.166 .268 -.I20 1.000 

8.STRESS .379 .276 .086 -.183 m.119 .323 244 .316 .I22 -.I32 .I48 .263 .275 .340 -.I16 .301 -.227 1.000 , 

.OOO .OOO 225 -009 .097 .OOO .001 ,001 .086 ,063 .037 .OOO .OOO .OOO -106 .OOO .001 . 199 199 199 199 195 198 I98 117 199 199 198 199 199 199 197 196 199 199 

.005 ,124 .008 .732 .099 .069 .374 ,000 .55 1 .OOO .OOO .OOO .086 .022 .177 .022 .002 .OOO . grs 198 198 198 198 194 197 197 117 198 198 197 198 198 198 197 196 198 198 198 

See Appendix A for variable names; a. Pearson Correlation Coefficient; b. Significance level (two-tailed); c. Effective sample size. 

.I99 .110 .189 .024 -.I19 .130 ,064 .394 .043 -.258 .423 .330 .I22 .I63 -.096 .164 -.221 .311 1.000 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
.. 

Table 13. Significant Correlates of Post-Camp Drug Offenses among 12-Month Self-Report Samples* 

12 3 4 5 6 7 8 910111213141516. 

20OC 

2.INDXALL ,529 1.000 

,000 

200 200 

3. WHITE .180 .046 1.000 

.011 .522 

200 200 200 

,048 .113 322 . 199 199 199 199 

.OOO ,017 .261 .004 

196 196 196 195 196 

.OOO .OOO .208 .734 ,795 

199 199 199 198 195 199 

.006 .003 .730 .575 310 ,004 . 199 199 199 198 195 198 199 

.012 .078 .98 1 .003 .OOO .387 .974 . 200 200 200 199 196 199 199 200 

,000 .298 .957 .446 ,137 .195 .563 .927 . 200 200 200 199 196 199 199 200 200 

,018 .540 .091 .900 .728 ,770 ,506 SO3 ,057 . 198 198 198 197 194 197 197 198 198 198 

.025 ,052 .136 303 ,099 ,029 .230 .735 .014 .300 . 200 200 200 199 196 199 199 200 200 198 200 

,000 .OOO .042 .I44 .008 .OOO .002 .295 .002 .035 .OOO . 200 200 200 199 196 199 199 200 200 198 200 200 

.OOO .OOO .050 .097 .030 .OOO .002 .I25 SO4 .15 1 .094 .OOO . 200 200 200 199 196 199 199 200 200 198 200 200 200 

.003 .110 .156 .649 .985 ,043 ,333 ,346 .035 .035 .OOO .OOO ,013 . 200 200 200 199 196 199 199 200 200 198 200 200 200 200 

.018 ,007 .654 .360 .876 ,857 .753 .940 .I35 A40 .OOO .018 ,570 ,042 . 200 200 200 199 196 199 199 200 200 198 200 200 200 200 200 

.OOO .OOO .489 .397 .097 .OOO .001 .015 ,615 .233 .380 .OOO .OOO ,591 .420 . 199 199 199 198 195 198 198 199 199 197 199 199 199 199 199 199 

4.PlQ9 -.141 m.113 ,016 1.000 

5.PRNKNOW -.272 -.170 .OS1 .203 1.000 

6.SUBEXPO ,302 .313 .090 m.024 -.019 1.000 

7.P 1 Q 17 .195 .208 .025 -.040 .O 17 .202 1.000 

8.ESTEEM2 -.177 -.125 .002 .212 .247 -.062 -.OO2 1.000 

3.P 1Q 19 -.266 m.074 .004 .054 .lo7 m.092 .04 1 .007 1 .OOO 

le0 .168 .044 -.120 -.009 .025 v.021 .048 .048 -.136 1.000 

1 1 .BOOT .159 .I37 .lo6 .018 -.118 .155 .086 -.024 -.173 -.074 1.000 

12,PRIDRUGI .619 .289 .144 -.lo4 -.l88 .303 .217 -.074 -.217 .150 .294 1.000 

l3.PRISELF .431 .542 .139 -.118 -.155 .288 .220 -.lo9 -.048 .lo2 .119 ,510 1,000 

14.P9Q3 .212 .113 .IO1 m.032 -.001 .143 .069 -.067 -.149 .I50 .280 .297 .175 1.000 

I5.DRS ,167 .I89 .032 m.065 -.011 .OI3 -022 -.005 -.I06 -.014 ,345 .167 .040 ,144 1.000 

L6.STRESS -276 .379 .049 -.060 m.119 .323 .244 m.172 -.036 -.OS5 .063 .275 .340 .038 .057 1,000 

' See Appendix A for variable names. 

1. Pearson Correlation Coefficient; 

L Significance level (two-tailed); 

:. Effective sample size. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 14. Significant Correlates of Post-Camp Arrests among 12-Month Self-Report Samples* 

1 2 3 4 5 6 7 8 9 

1.POSTARR 

2.POSTSUS 

3 .BLACK 

4.DUOeAREN 

5 .DUOPARN 1 

6.P1 Q38B 

7.P4Q6B 

8.PlQ29 

9.P8Q7 

1.0ooa 

200e 

.596 1.000 

.ooo 

200 200 

,183 ,249’ 

A10 .ooo 

200 200 

-.226 -.160 

,001 .024 

200 200 

-.170 -.140 

.016 .049 

200 200 

-.245 -. 167 

.001 ,019 

196 196 

.189 ,095. 

.007 .182 

200 200 

-.149 -.094 

.035 .184 

200 200 

.151 .165 

.037 ,022. 

b 

1 .ooo 

200 

-.217 

.002 

200 

-.233 

.001 

200 

-.063 

.379 

196 

-.010 

392 

200 

-. 168 

.018 

200 

.208 

.004 

1 .ooo 

200 

.612 

.ooo 

200 

-.03 1 

.671 

196 

-.045 

.525 

200 

.131 

.065 

200 

-.237 

.001 

1 .ooo 

200 

-.080 

.265 

196 

-.120 

,090 

200 

.169 

.017 

200 

-.198 

.006 

192 192 192 192 192 191 . 192 192 192 

* See Appendix A for variable names. 

a. Pearsin Correlation Coefficient; 

b. Significance level (two-tailed); 

c. Effective sample size. 

1 .ooo 

196 

.257 

196 200 

.205 ,006 

196 200 200 

.191 .087 .344 

-.081 1.000 

-.091 -.193 1,000 

e.095 -.124 -.069 1.000 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 15. Sigiiificant Correlates of Post-Camp Sustained Petitions among 12-Month Self-Report Samples* 

1 2 3 4 5 6 7 8 9 10 11 

l.oooa 

b lpg"Tsus 20OC 

2.POSTARR .596 

.ooo 

200 

3.HISPANIC 445 

.040 

200 

4.BLACK .249 

.ooo 

200 

5.DUOPAREN -.160 

,024 

200 

6.DUOPARNl -.140 

,049 

200 

-.158 

.026 

200 

-. 167 

.019 

7.PlQ10 

8.P 1 Q3 8B 

1 .ooo 

200 

-.115 

.lo4 

200 

.183 

,010 

200 

-.226 

.oo 1 

1.000 

200 

-.732 1.000 

.ooo 

200 200 

.286 -.217 1. 

,000 ,002 

200 

-.170 

.016 

200 

-.092 

.197 

200 

-.245. 

.001 

196 

-.014 

,840 

200 

.151 - 

.037 

192 

.137 

.055 

197 

200 

.232 

.001 

200 

.024 

.739 

200 

,105 

.144 

196 

.155 

.028 

200 

a.204 

.005 

192 

.oo 1 

.985 

197 

200 200 

-.233 .612 

.001 .ooo 

200 200 

-.lo1 -.048 

.154 .497 

200 200 

-.063 -.031 

.379 .671 

196 196 

-.293 -.114 

.OOO .lo7 

200 200 

.208 -.237 

.004 .001 

192 192 

.907 .523 

197 197 

-.008. -.046 

1 .ooo 

200 

,004 

.957 

200 

-.080 

.265 

196 

-.120 

.09 1 

200 

-. 198 

.006 

1 92 

-.061 

-395 

197 

1 .ooo 

200 

.939 

196 196 

.782 .469 

200 196 

.366 .193 

192 191 

.081 .002 

.255 ,977 

197 194 

-.005 . 1.000 

-.020 .052 

.066 -.095 

196 

DRUG1 -.143 1 .ooo 

,044 

200 

10.P8Q7 .165 

,022 

192 

11.P9Q5A ,146 

,041 

197 

200 

-.055 

.45 1 

I92 

.129 

.071 

197 

1.000 

192 

356 

190 197 

-.013 1.0010 

* See Appendix A for variable names. 

a. Pearson Correlation Coefficient; 

b. Significance level (two-tailed); 

c. Effective sample size. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 16. Stepwise Regression Analysis of Self-Report Outcomes among 12-Month Sample a Dependent Variable: Post Camp Non-Drug Offenses 

Best predictors* R Adj. R" Beta t-ratio Sig. 

(Constant) 2.38 .02 

PRlSELF .3 1 .3 1 .47 5.79 .oo 

SUBEXPO .36 .35 .19 2.52 .o 1 

FUTURE .39 .38 -.27 -3.07 .OO 

MASTERY .43 .4 1 -.38 -3.76 .OO 

STRESS .46 .44 .23 2.79 -00 

PRIDRUGl .49 .47 -.35 -3.87 .OO 

POSDRUG .53 SO .27 3.04 .OO 

ESTEEM3 .55 .52 .18 2.12 .04 

Best predictors R Adj. RL Beta t-ratio Sig. 

(Constant) 1.67 .09 

PRIDRUGl .39 .39 .46 8.77 .[Do 

INDXALL .53 .53 .37 7.30 .oo 

PlQ19 .55 .55 -.14 -2.78 .o 1 

PRNKNOW .57 .56 -. 13 -2.52 .0 1 

Dependent Variable: Post Camp Drug Offenses 

a. Variable Names: 

ESTEEM3-self-esteem on school related failure and frustrations 

FUTURE-perception of future opportunities 

HISPANIC-ethnicity (Hispanic 1, non-Hispanic 0) 

INDXALL-post-camp self-report delinquency (excluding drug offenses) 

MASTERY-perceived ability to control one's future destiny 

P 1 Q 19-Attending school 

POSDRUG-post-camp self-report drug offenses 

PRIDRUG1-self-report pre-camp drug offenses 

PRNKNOW-parental knowledge of respondents' fiends and whereabouts 

PRISELF-pre-camp delinquency (excluding drug offenses) 

STRESS-stress factors in the past year 

SUBEXPO-pre-camp exposure to substance abuse 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 17. Stepwise Regression Analysis on Official Outcomes among 12-Month Sample 0 Dependent Variable: Post Camp Arrests 

Best predictors R' Adj. R2 Beta t-ratio Sig." 

(Constant) 7.32 .OO 

PlQ38B .07 .07 -.28 -4.22 .OO 

DUOPAREN .13 .12 -.19 -2.87 .o 1 

GANGEVER .16 .15 .18 2.62 .0 1 

PlQ29 .18 .16 -. 14 -2.02 .05 

Best predictors RL Adj. R' Beta t-ratio sig. 

(Constant) 3.90 .00 

Dependent Variable: Post Camp Sustained Petitions 

BLACK 

PlQ38B 

P9Q5A 

.06 -05 .2 1 3 .OO .oo 

.08 .07 -.16 -2.22 .03 

.10 .09 .16 2.20 .03 

PlQlO .12 .10 -.15 -2.08 .04 

a. Variable Names: 

P 143 8B-perceived support from parents in times of troubles 

DUOPAREN-live with both parents at the the of interview 

GANGEVER-ever being a gang member (dummy variable) 

P 1 Q29-currently being employed 

BLACK-ethnicity (Black 1 and non-Black 0) 

P9Q5A-number of times being disciplined for conduct problems while in the camp 0 P 1 Q 1 0-number of days in a week respondent had to care for himself 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
,Table 18. Comparison of Attrition Cases and Final Sample of Pre-and-Post Cohort 

Attrition Cases (N=48) Final Sample (N=89) 

Etlvlicitya Percent Percent 

African American 13 18 

Hispanic 81 64 

White 6 18 

15 and younger 19 18 

16 8 25 

17 31 30 

18 42 27 

e 

Age (at interview) 

Mean 16.89 16.60 

Median 17.33 16.81 

Std. Dev. 1.24 1.21 

Length of camp stay 

Mean 84.57 77.21 

Median 70.00 70.00 

Std. Dev. 28.62 25.43 

Mean 5.42 6.10 

Median 4.50 5.00 

Std. Dev. 4.70 4.17 

MEUl 4.04 4.3 1 

Median 4.00 5.00 

Std. Dev. 1.66 1.47 

Self-report pre-camp delinquencyb 

Self-report pre-camp drug offenses 

0 

a. Marginal significant differences were found between groups, with J?=4.99; df-2; ~6.09 

b. Excluding drug offenses. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 19. Self-Report Outcome Measures for the Pre-and-Post Cohort 

Offenses Camp e Mean Std, Dev. t Sig. (2-tailed) 

Status offenses Pre-camp 2.02 1.03 5.52 ,000 

Post-camp 1.14 1.08 

Vandalism Pre-camp 

Post-camp 

,Theft Pre-camp 

Post-camp 

.64 .73 3.11 .002 

.33 ,62 

2 ;23 2.24 2.70 .008 

1.34 2.14 

Violent offenses Pre-camp 1.21 1.28 1.85 ,066 

Post-camp .87 1.24 

All non-drug offenses Pre-camp 

Post-camp 

Drug use Pre-camp 

Post-camp 

Drug sale Pre-camp 

6.10 4.17 3.84 .ooo 

3.67 4.25 

3.28 a90 .95 .342 

3.15 .98 

1.03 .85 2.20 

Post-camp .753 -86 

.029 

All drug offenses Pre-camp 4.32 1.47 1.88 .061 

Post-camp 3.90 . 1.46 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 20. Social Activity Measures among Pre-and-Post Cohort (In Percent) 

Pre Camp Post Camp 

(N=89) (N=89) 

1. Attending School 

(1) No 27 37 

(2) Yes 73 63 

(1) No 64 65 

2. Working 

(2) Yes 36 35 

3. Participation in Organized Sportsa 

(1) No 56 71 

(2) Yes 44 29 

(1) No 61 64 

4. Involvement in Gangs 

(2) Yes 39 36 

a. 2?=4.10; d!l;p<.O5. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 21. Attitudinal Changes in Pre-and-Post Cohort a Pre Camp Post Camp - - 

(N=89) (N=89) 

1. Self-esteem Measures: 

(1) Peer Related Measures Mean 28.62 28.97 

(Cronbach’s alpha=0.70) Std. Dev. 3.77 3.25 

(2) Family Related Measuresa Mean 36.27 34.66 

(Cronbach’s alpha =0.81) Std. Dev. 4.49 5.38 

(3) School Related Measuresb Mean 26.15 24.1 1 

(Cronbach’s alpha = 0.82) Std. Dev. 4.94 4.36 

2. Perceived Future Prospect Mean 34.10 34.21 

(Cronbach’s alpha = 0.80) Std. Dev 4.92 4.98 

3. Mastery of One’s Future Mean 14.79 14.49 

(Cronbach’s alpha = 0.73) Std. Dev. 3.20 3.21 

4. Attitudes towards Authority: Mean 37.89 3 8.47 

(Cronbach’s alpha = 0.72) Std. Dev. 4.39 5.07 

a. t-2.16; df-l76;p<.O4. 

b. F2.40; df-119; pC.02. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 22. Significant Correlates of Post-Camp Derinquency among Pre-Post Cohort* 

3 5 6 7 8 1 2 

1.WINDXALL l.OOoa 

b * 

8gC 

2. WPDRUGl ,410 

.ooo 

89 

3.WPOSTARR .293 

.005 

89 

4.PRNKNOW -.241 

A23 

89 

5.PlQ38B ,298 

.005 

88 

6.PlQ36 -.311 

,022 

54 

7.INDXALL .431 

,000 

1 .ooo 

89 

.051 1.000 

.637 

89 89 

,056 .081 

89 89 

.301 .075 

-004 .487 

88 88 

-.079 .OOO 

.571 1.000 

54 54 

.330 ,138 

,002 .198 

m.203 -.186 

4 

-121 

.268 

86 

.300 

86 

.169 

.23 1 

52 

,016 

,882 

-.113 

1 .ooo 

89 

-.180 

.094 

,302 

,027 

54 

-.194 

.069 

88 ' 

1 .ooo 

88 

.653 

.178 

.097 

-.063 

53 . 

1 .ooo 

54 

,174 

-.188 1.0100 

89 89 89 86 89 88 54 89 * See Appendix B for variable names; 0 a. Pearson Correlation Coefficient: 

b. Significance level (two-tailed); 

c. Effective sample size. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
' Table 23. Significant Correlates of Post-Camp Drug Offenses among Pre-and-Post Cohort" 

PDRUGl ' 

1 2 3 4 5 6 7 8 9 10 11 12 13 

2.WINDXALL 

3 .PURRST 

4.P 1 Ql8 

5.P1 Q38B 

6.PlQ38D 

7.ESTEEM2 

9.P4Q6B 

10.PlQ30 

1 1 .PDRUG 1 

12.INDXALL 

13 .NHOOD 

l.oooa 

89' 

b 

.41.0 1.000 

.ooo 

89 89 

,217 .036 

.041 ,736 

'89 89 

-.243 -.179 

.022 .093 

89 89 

.301 .298 

.004 .005 

88 88 

.255 .182 

,016 .087 

89 89 

-299 -.I37 

.004 .202 

89 89 

.007 .510 

89 89 

,278 .165 

.008 .121 

89 89 

.013 ,550 

89 89 

,437 ,203 

.OOO .056 

89 89 

.330 ,431 

.002 .ooo 

89 89 

-.254 -.143 

.016 .182 

-.286 -.07 1 

.264 :064 

1.000 

89 

-.367 

io00 

89 

.270 

.011 

88 

.074 

.489 

89 

.215 

89 

.422 

89 

.039 

.717 

89 

.199 

.062 

89 

.223 

.036 

89 

,030 

.780 

89 

-.269 

.011. 

-.133 

-.086 

1 .ooo 

89 

-003 

88 

.013 

89 

.23 1 

.030 

89 

.968 

89 

-.082 

.445 

89 

-.002 

-982 

89 

-.246 

.020 

89 

-.050 

.644 

89 

.273 

.010 

-.315 

-..264 

-.004 

1 .ooo 

88 

,411 

.ooo 

88 

-.365 

.ooo 

88 

-.067 

,536 

88 

-. 100 

.354 

88 

,041 

.704 

88 

.228 

.033 

88 

,178 

.097 

88 

.171 

-. 147 

1 .ooo 

89 

-.310 

.003 

89 

.026 

,809 

89 

.014 

,895 

89 

.017 

.873 

89 

,277 

.009 

.89 

,099 

,357 

89 

-.068 

.528 

1 .ooo 

89 

.230 

.030 

89 

.044 

89 

.806 

89 

.041 

89 

.461 

89 

.146 

.173 

-.2 14 

-.026 

-.2 17 

-.079 

1 .ooo .. 

89 

.083 

-.185 1.000 

89 89 

.009 .112 

-.274 .170 1.000 

89 89 89 

.011 ,0123 .056 

89 89 89 

.144 .057 .416 

89 89 89 

.169 .020 .220 

-.267 .314 .203. 

-.156 .202 .087 

.I47 -.246 -.131 

1 .ooo 

89 

.444 1.000 

.ooo 

89 89 

.021 .loo 

w.245 -.175 1.000 

89 89 89 89 88 89 89 89 89 89 89 89 89 

* See Appendix B for variable names; 

a. Pearson Correlation Coefficient; 

b. Significance level (two-tailed); 

c. Effective sample size. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 24. Significant Correlates of Post-Camp Arrests among Pre-and-Post Cohort* 

1 2 3 4 5 6 7 8 

1.WPOSTARR 

2.WINDxALL 

3.WPOSTSUS 

4 .PRIARRST 

S.LANGUAG1 

6.FUTURE 

7.P 1429 

8.PllQ1 

1.000* 

89' 

b 

. 

.293 

.005 

89 

.584 

.ooo 

89 

,265 

,012 

89 

.266 

.013 

87 

-.216 ' 

.042 

89 

-.217 

.041 

1 .ooo 

89 

.164 

.124 

89 

.036 

.73 6 

89 

,013 

.904 

87 

-.079 

.463 

89 

-.025 

.814 

1.000 

89 

.037 

.732 

89 

,446 

.ooo 

87 

-.132 

.216 

89 

-.156 

.143 

89 89 89 

-.212 -.129 -.235 

,046 .228 .026 

89 89 89 

* See Appendix B for variable names; 

a. Pearson Correlation Coefficient; 

b. Significance level (two-tailed); 

c. Effective sample size. 

1 .ooo 

89 

346 

-.lo2 1.000 

87 87 

.186 ,091 

-.142 -.182 1,000 

89 87 89 

311 .593 .585 

.Of2 ,058 -.OS9 1.000 

89 87 89 89 

.ti68 .003 .062 .848 

.046 -.317 .198 -.021 1,000 

89 87 89 89 89 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 25. Significant Correlates of Post-Camp Sustained Petitions amoiig Pre-andPost Cohort* 

1 2 3 4 5 6 

1.000" 

89' 

b 

1.WPOSTSUS 

2.WPOSTAR.R .584 

.ooo 

89 

3 .LANGUAGl .446 

.ooo 

87 

4.P1 Q7 -219 

.039 

89 

5 .PRNI(NO W -.239 

,024 

89 

.026 

6.PllQl -.235 

1 .ooo 

89 

.266 1.000 

.013 

87 87 

,662 .005 

89 87 

-08 1 ,106 

89 87 

.046 .003 

h.047 -.299 

-.186 -.174 

m.212 -.317 

1 .ooo 

89 

.623 

89 89 

.021 .173 1.000 

.845 .lo4 

-.053 1,000 

89 89 87 89 89 89 

* See Appendix B for variable names; 

a. Pearsoii Correlation Coefficient; 

b. Significance level (two-tailed); 

c. Effective sample size. 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Table 26. Stepwise Regression Analysis on Post Camp Measures (Pre-and-Post Cohort) 

Dependent Variable: Post Camp Self-Report Delinquency 

Best predictors a RL Adj. Rz Beta t-ratio Sig. 

(Constant) -1 -24 22 

INDXALL .34 .32 SO 4.45 .OO 

PlQ38B .4 1 .38 ,28 -2.46 .02 

Best predictors R' Adj. R' Beta t-ratio Sig. 

(Constant) 4.58 .oo 

PDRUGl .20 .19 .37 4.09 .80 

WINDXALL .32 .30 .36 3.89 .OO 

Dependent Variable: Post Camp Self-Report Drug Offenses 

Dependent Variable: Post Camp Arrests 

Best predictors RL Adj. RL Beta t-ratio sig. 

(Constant) .39 .70 

WINDXALL .09 .08 .29 3.12 .0 1 

LANGUAGl .16 .14 - .31 -3.26 .(I1 

PRIARRST .24 .2 1 .28 3.02 .o 1 

P 1429 .30 .26 - -24 -2.54 .o 1 

Best predictors R' Adj. RL Beta t-ratio sig. 

(Constant) 3 .18 .o 1 

LANGUAGl .20 .19 .45 4.59 .oo 

INDXALL- pre-camp self-report delinquency (excluding drug offenses) 

LANGUAGl- level of cultural assimilation 

P 143 8B- perceived support from parents in times of trouble 

P 1429- currently employed 

PDRUGl- pre-camp self-report drug offenses 

PRIARRST- prior arrests 

WINDXALL- post-camp self-report delinquency (excluding drug offenses) 

WPOSTARR- post-camp arrests 

Dependent Variable: Post Camp Sustained Petitions 

a a. Variable Names: 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
Appendix A. Correlation Variable Names for 12-Month Self-Report Samples 

Variable Name Label 

Outcome Measures: @ INDXAL,L, 

POSDRUG 

POSTARR 

POSTSUS 

Correlates: 

BLACK 

DEPRESS 

DUOPAREN 

DUOPARN1 

ESTEEM3 

FUTURE 

HISPANIC 

MASTERY 

NHOOD 

P1Q4 

PlQlO 

PlQ17 

P 1 Q29 

PlQ38B 

P4Q6B , 

P807 ~ 

P9Q4 

P9Q5A 

PRIDRUGl 

PRISELF 

PRNKNOW 

SELFESTl 

STRESS 

post. camp self-report delinquency (excluding drug offenses) 

post camp self-report drug offenses 

post-camp arrests 

post-camp sustained petitions 

binary ethnicity-black vs. non-black 

CDC depression scale index 

both mother and father currently live in the house 

both parents raised minor 

self esteem measures on school failure and frustrations 

perception of fkture opportunities 

binary ethnicity-Hispanic vs. non-Hispanic . 

perception of control over one's destiny 

neighborhood deterioration measures 

number of people lived in the same household 

Days per week minor has to care for himself 

Anyone in family go to jail? 

Do you have a job? 

perceived support from parents when in troubble? 

Are you a gang member? 

How often have parents called probation officer to tell how 

you're doing at home or school? 

positive camp experience 

number of times disciplined in camp for conduct problems 

prior drug use and sale 

prior delinquency (excluding drug offenses) 

parental knowledge of minor's friends and whereabouts 

self esteem (general positive feelings about oneself) 

cumulative stress factors 

SUBEXPO exposure to substance abuse 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.
11 

1). Outcome Measures: 

Appendix B. Correlation Variable Names for Pre-and-Post Cohort 

Variable Name Label 

WINDXALL 

WPDRUG1 

WPOSTARR 

WPOSTSUS 

Correlates: 

AGEARRST 

CARESELF 

ESTEEM1 

ESTEEM2 

FUTURE 

INDXALL 

LANGUAGI 

MASTERY 

NHOOD 

P1Q7 

PlQ17 

PlQ19 

P 1429 

PlQ30 

PIQ36 

PlQ38B 

PlQ38D 

P4Q6B 

PllQl 

PDRUGl 

PRIARRST 

PRNKNOW 

. PlQ18 

post camp self-report delinquency (excluding drug 

offenses) 

post camp self-report drug offenses 

post-camp arrests 

post-camp sustained petitions 

age of first arrest 

hours per week to care for oneself 

self-esteem measures on peer relations 

self-esteem measures on family relations 

perception of future prospect 

prior-to-camp self-report delinquency (excluding drug 

offenses) 

level of cultural assimilation 

perceived control of one's own future 

neighborhood deterioration measures 

lived with a lot of adults 

anyone in family go to jail? 

perception of family closeness 

do you go to school? 

do you have a job? 

spending money per week 

want the relationship with girlfriend to last 

perceived support fiom parents when in trouble 

perceived support from other relatives when in trouble 

are you a gang member? 

number of years lived in neighborhood 

prior-to-camp self-report drug offenses 

number of arrests prior to camp entry 

parents know respondent's friends and whereabouts . 

SUBEXPO exposure to substance abuse at home 

This document is a research report submitted to the U.S. Department of Justice. This report

has not been published by the Department. Opinions or points of view expressed are those

of the author(s) and do not necessarily reflect the official position or policies of the U.S.

Department of Justice.