Gender Differences in the Effectiveness of Delinquency Prevention Programs

Abstract

Empirical research indicates that males are more likely than females to be delinquent, yet it is unclear why this gender gap exists. This uncertainty can impede gender-responsive prevention efforts to implement programs that target the criminogenic factors most salient for each sex. However, information from experimental evaluations of gender differences in the effectiveness of prevention services can guide gender-responsive approaches. This article provides a systematic review of such literature. The results demonstrated some evidence of gender differences in the ability of community-based preventive interventions to reduce substance use, delinquency, and/or violence, although no clear patterns emerged regarding the types of programs that are most effective for each sex. In addition, some programs had similar effects on females and males and others evidenced harmful effects for one sex or the other. These findings suggest that practitioners should carefully review evaluation evidence prior to targeting females, males, or both sexes for prevention services.

Keywords

delinquency prevention gender experimental research risk and protective factors gender-responsive programming

The gender¹ gap in offending, indicating that males are much more likely than females to engage in law-breaking activities, is one of the most stable findings in criminology (Daly & Chesney-Lind, 1988; Fagan, 2014; Steffensmeier & Allen, 1996). In 2009, females accounted for 18% of all juvenile arrests for serious violent offenses and 38% of all juvenile arrests for serious property offenses (Puzzanchera & Adams, 2011). Information from self-report surveys also indicate that boys are more likely than girls to break the law and are especially more likely to engage in acts of aggression and violence (Elliott, 1994; Moffitt, Caspi, Rutter, & Silva, 2001). For example, among high school students participating in the 2009 Youth Risk Behavioral Survey (YRBS), 27% of males reported carrying a weapon in the month prior to the survey compared with 7% of females, and 39% reported getting into fights in the past year compared with 23% of females (Centers for Disease Control and Prevention, 2010). There are few offenses in which females are overrepresented as perpetrators and few forms of deviance in which their rates are comparable with males. One of these exceptions is minor forms of substance use, as national studies suggest that females and males engage in similar rates of smoking and drinking during adolescence (Centers for Disease Control and Prevention, 2010; Johnston, O’Malley, Bachman, & Schulenberg, 2011).

Gender Differences in Offending

Numerous theories have been created or revised and empirical studies have been conducted to help explain the overrepresentation of males as perpetrators (Belknap & Holsinger, 2006; Blum, Ireland, & Blum, 2003; Daly & Chesney-Lind, 1988; Smith & Paternoster, 1987). Likewise, a growing body of research has investigated the degree to which factors or experiences thought to increase (i.e., risk factors) or decrease (i.e., protective factors) the likelihood of offending are generalizable across the sexes (Baxendale, Cross, & Johnston, 2012; Fagan, 2014; Lanctot & Le Blanc, 2002; Steffensmeier & Allen, 1996).² Taken as a whole, this research has tended to show support for gender similarity more than for gender difference in the individual, peer, school, family, and neighborhood factors affecting delinquency (Blum et al., 2003; Daigle, Cullen, & Wright, 2007; Fagan, Van Horn, Hawkins, & Arthur, 2007; Lanctot & Le Blanc, 2002; Moffitt et al., 2001; Rowe, Vazsonyi, & Flannery, 1995). For example, several meta-analyses have failed to show evidence of sex differences in key predictors of offending, including antisocial beliefs and attitudes (Pratt et al., 2010); exposure to delinquent peers (Pratt et al., 2010); parental supervision, monitoring, and reinforcement (Hoeve et al., 2009); and exposure to family violence (Sternberg, Baradaran, Abbott, Lamb, & Guterman, 2006).

Some studies have identified gender differences in the impact of particular experiences on delinquency, but attempts to replicate such findings have often failed. For example, there is mixed evidence regarding whether the impact on delinquency of early childhood adversities and behavioral problems (Zahn-Wexler, Shirtcliff, & Marceau, 2008), school experiences (Payne, Gottfredson, & Kruttschnitt, 2009), and neighborhood conditions (Kroneman, Loeber, & Hipwell, 2004; Zahn & Browne, 2009) is stronger for males or for females. Some studies have shown that these factors have a greater impact on delinquency among males, some indicate a stronger influence for females, and still others demonstrate similar effects for both sexes. Furthermore, many of these studies have methodological or statistical limitations that hinder the ability to identify gender differences in causal predictors of offending (Fagan, 2014). For example, some studies fail to control for other possible influences on delinquency, rely on small numbers of participants, or utilize cross-sectional data.

The absence of clear etiological information regarding the risk and protective factors that are most influential for males and females impedes our ability to reduce involvement in crime. It also makes “gender-responsive” (Bloom, Owen, Deschenes, & Rosenbaum, 2002; Hubbard & Matthews, 2008; Kempf-Leonard & Sample, 2000) prevention approaches difficult, given their goal of ensuring that services address the risk and protective factors that are most salient for each gender group. We suggest that experimental research that tests for gender differences in the impact of preventive interventions has great potential for guiding gender-responsive service provision. This article provides a systematic review of such literature as it pertains to evidence-based prevention programs implemented in community settings as opposed to the juvenile justice setting. Our goals are to (a) assess the degree to which an array of community-based preventive interventions have shown evidence of gender differences in reducing delinquency, (b) identify types of interventions that are more or less effective for females and males, and (c) provide recommendations for delivering these interventions in community settings in a gender-responsive manner.

The Benefits of Experimental Research

Criminologists have increasingly advocated for the use of evidence-based interventions to reduce offending (Andrews et al., 1990; Farrington & Welsh, 2007; Sherman et al., 1998). Such programs seek to manipulate the underlying causes of crime: the individual, peer, school, family, and community risk and protective factors that have been shown to precede and affect the likelihood of youth offending (Hawkins, Catalano, & Miller, 1992; Herrenkohl et al., 2000; Lipsey & Derzon, 1998). Many such interventions have been successful in doing so, as evidenced by the growing number of programs and practices that high-quality research trials have shown to lower rates of substance use, delinquency, and violence across diverse youth participants (Farrington & Welsh, 2005; O’Connell, Boat, & Warner, 2009; Sherman et al., 1998; U.S. Department of Health and Human Services, 2001).

As such evidence has accumulated, there has been a corresponding emphasis on the need to implement gender-responsive and/or sex-specific treatments that target the factors that are most likely to lead to male offending and female offending (Bloom et al., 2002; Kempf-Leonard & Sample, 2000). This call to action represents an important shift from “one size fits all” treatments that use the same approach with all individuals to implementing programs that are responsive to the needs of particular individuals (or groups of individuals). However, given the lack of clarity in empirical research regarding the risk and protective factors that are most salient for males and females, it is difficult to know which types of services should be delivered to each sex group or if some services should be implemented with both sexes. We contend that evidence from well-conducted evaluations of programs implemented with females and males can advance our theoretical understanding of sex differences in the causes of delinquency and our efforts to reduce offending of both sexes.

Related to the first issue, even the best empirical study faces difficulties ascertaining causal influences of crime. Research has shown that multiple factors affect adolescent offending, and it is very challenging for observational research to fully account for and rule out rival explanations of offending. Although experimental research also has limitations (Mears, 2007; Sampson, 2010; Sherman & Strang, 2004), experiments are arguably the most scientifically rigorous approach to identifying the root causes of crime (Farrington & Welsh, 2005). First, experiments seek to manipulate one or more independent variables (e.g., risk or protective factors), then assess subsequent changes in dependent variables (e.g., delinquency), thus helping to establish temporal ordering of cause(s) and effect(s). Experiments, particularly randomized controlled studies, can also minimize contamination by other potential influences, which should be equally distributed across individuals in treatment and control groups, assuming successful randomization to conditions (Sherman, 2003; Weisburd, 2010). Observed changes in behaviors among those participating in the experimental versus control condition can then be attributed with much more certainty to the intervention, rather than to pre-existing or intervening biological, individual, social, or contextual factors (Fagan, 2013).

Evaluations that compare the effectiveness of interventions for male and female participants can help to illuminate factors predicting offending for each sex and, importantly, suggest appropriate strategies for reducing delinquency for each group. For example, a primary goal of mentoring programs is to create strong bonds between youth and prosocial adults, with the expectation that these attachments will inhibit the delinquency of the mentored child (Hirschi, 1969). If mentoring programs were shown to be more effective, or only effective, in reducing offending for female participants, then social bonds would be viewed as a key determinant of female offending, which in turn would suggest that mentoring programs target female participants. In contrast, if an intervention designed to increase individuals’ self-control was shown to be equally effective in reducing offending for males and females, then self-control would be viewed as a salient risk factor for both sexes and programs emphasizing this type of content would be recommended for girls and boys.

Evaluations of prevention programs can thus be a useful tool for identifying salient and gender-specific predictors of crime and for guiding gender-responsive approaches to prevention. Fortunately, many impact evaluations have begun to investigate gender differences (e.g., Eckenrode et al., 2010; Oesterle, Hawkins, Fagan, Abbott, & Catalano, 2010; Reynolds, Temple, Ou, Arteaga, & White, 2011). However, this information has yet to be systematically reviewed, which is particularly important when considering gender differences in the effectiveness of community-based programs which are seeking to prevent or reduce delinquency among youth not yet involved in the juvenile justice system. We are aware of one study that assessed gender differences in the effects of treatment programs intended to reduce delinquency for youth already involved in the juvenile justice system (Zahn, Day, Mihalic, & Tichavsky, 2009). However, to our knowledge, no prior reviews have assessed gender differences in the effectiveness of community-based prevention programs.³

This article aims to fill this gap in the literature by reviewing evidence of gender differences in the effects of community-based delinquency prevention programs that have been evaluated in rigorous research trials. Based on this evidence, we also provide recommendations to community practitioners interested in gender-responsive approaches to delinquency prevention. We hope the review and recommendations will have significant practical value to communities, given the potential for early preventive interventions to prevent and reduce the likelihood of future offending (Welsh & Farrington, 2006), and the increasing number of such programs now available for implementation.

Method

Our review of the literature focused on evaluations of programs and practices listed on the Blueprints for Healthy Youth Development (http://www.colorado.edu/cspv/blueprints/), Campbell Collaboration (http://www.campbellcollaboration.org/), and Crime Solutions (http://www.crimesolutions.gov/) websites, as well as interventions described in Crime Trends publications describing programs that are effective for male (Bandy, 2012) and female (Bell, Terzian, & Moore, 2012) participants. We restricted the review to these sources given that they all have rigorous criteria regarding the research design and analysis strategies that must be met for an intervention to be deemed effective. Such guidelines are important given the wide range of methodological rigor characterizing evaluation research and the fact that some lists of best practices do not have particularly high standards for determining program effectiveness (Hallfors, Pankratz, & Hartman, 2007; Wright, Zhang, & Farabee, 2012). Following Massetti et al. (2011), we prioritized and listed separately findings from programs listed on the Blueprints website (in Tables 1 and 3), as this organization arguably has stricter criteria for determining program effectiveness compared with the other sources.⁴

Table 1:

Preventive Interventions From the Blueprints for Healthy Youth Development Website^a With Significant Gender Differences in Effects

Program NameCitation	Length/Dosage	Sample Size and Characteristics (at Baseline)	Differential Effects	More Effective for Females or Males?	Significant Gender Difference in Effects?^b
HOME VISITATION PROGRAMS
Nurse-Family Partnership Eckenrode et al. (2010)	2.5 years of nurse visits every 2 weeks	N = 400 pregnant mothers, 85% unmarried, low SES, or teenaged N = 400 youths aged 0-2, 50% male, mostly White	At age 19 Reduced arrests and convictions for female but not male children	Females	Yes
EARLY CHILDHOOD EDUCATION
HighScope/Perry Preschool Project Schweinhart and Weikart (1997)	2 years of half-day preschool classes	N = 68 youths aged 3-4 with low intelligence 46% male 65% Black All low income	By age 23 Reduced adult felony arrest rates more for males than females	Males	Yes
PARENT TRAINING
SFP 10-14 Trudeau, Spoth, Randall, and Azevedo (2007)	7 weekly sessions of 2 hr each for parents and children	N = 446 youths in Grade 6 48% male All White	At Grade 12 Reduced growth in poly-substance use (tobacco, alcohol, and other drugs) more for females than males	Females	Yes
SCHOOL-BASED CURRICULA
Good Behavior Game Kellam and Anthony (1998); Kellam et al. (2008; Kellam, Rebok, Ialongo, and Mayer (1994)	2 years of ongoing classroom activities	N = 1,196 students in Grade 1 49% male 65% Black, 31% White	At Grade 6 (Kellam et al., 1994)
			Reduced aggression for males who were aggressive at baseline but not females	Males	n/a
			At age 14 (Kellam and Anthony, 1998)
			Reduced smoking for males but not females	Males	n/a
			At ages 19-21 (Kellam et al., 2008)
			Reduced smoking for males but not females	Males	n/a
Fast Track/PATHS Conduct Problems Prevention Research Group (2010)	3 years of weekly classroom lessons	N = 2,937 students in Grade 1	At Grade 3Reduced peer reports of aggression for males but not females	Males	Yes
Life Skills Training Vicary et al. (2006); Botvin, Baker, Filazzola, and Botvin (1990)	3 years of 5-15 classroom lessons each year	Vicary et al., 2006N = 732 students in Grade 754% male97% WhiteBotvin et al., 1990N = 372 students in Grade 750% male69% White, 29% Black	At Grade 7 (Vicary et al., 2006)
			Reduced smoking, drinking, binge drinking, and marijuana use for females but not males	Females	Yes
			At Grade 8 (Botvin et al., 1990)
			Reduced smoking more for females than males	Females	Yes
			Reduced marijuana use more for females than males	Females	Yes
Project Towards No DrugAbuse Sussman, Dent, and Stacy (2002); Sussman, Sun, McCuller, and Dent (2003)	3-week program with 12 classroom lessons	Sussman et al., 2002N = 1,208 students in Grades 9-1147% male38% Hispanic, 34% White, 26% BlackSussman et al., 2003N = 1,037 students aged 14-1954% male45% White, 42% Hispanic	1-year follow-up (Sussman et al., 2002)Reduced weapon carrying for males but not females2-year follow-up (Sussman et al., 2003)Reduced marijuana use among baseline nonusers for males but not females	Males Males	n/a Yes
COMMUNITY-BASED, MULTI-COMPONENT PROGRAMS
Communities That Care Oesterle, Hawkins, Fagan, Abbott, and Catalano (2010)	Community-wide system with various school, family, and afterschool activities	N = 4,407 students in Grade 550% male68% White	At Grade 8Reduced smokeless tobacco use, alcohol use, and binge drinking for males but not females	Males	Yes
Project Northland—Croatia West, Abatemarco, Ohman-Strickland, Zec, and Russo (2008)	3- to 6-year program with school curricula and community-wide alcohol prevention activities	N = 1,981 students in Grade 650% male90% Croatian	At Grade 8Reduced past month and past year drinking for females but not males	Females	n/a

Note. SES = socioeconomic status; SFP = Strengthening Families Program.

http://www.blueprintsprograms.com/

Indicates whether the differences in effects between males and females were statistically significant (at least p < .10); “n/a” indicates that the evaluation assessed program results separately for males and females but did not statistically test for differences in effects across these two groups.

Table 2:

Preventive Interventions Identified by the Campbell Collaboration,^a Crime Solutions,^b and Child Trends^c With Significant Gender Differences in Effects

Program NameCitation	Length/Dosage	Sample Sizes and Characteristics (at Baseline)	Differential Effects	More Effective for Females or Males?	Significant Gender Difference in Effects?^d
EARLY CHILDHOOD EDUCATION
Chicago Parent Child Center Reynolds, Temple, Ou, Arteaga, and White (2011)	1-2 years of half-day preschool services	N = 1,539 youths aged 3-450% male93% BlackAll low income	At age 28Reduced felony arrests for females but not males	Females	Yes
FAMILY-FOCUSED PROGRAMS
Moving to Opportunity Kling, Liebman, and Katz (2007); Kling, Ludwig, and Katz (2005)	Housing voucher program providing monetary incentives to relocate families from highly disadvantaged neighborhoods to higher income and safer areas	Kling et al., 2007N = 1,807All low incomeKling et al., 2005N = 4,47550% male62% Black, 32% Hispanic	5-year follow-up (ages 15-20; Kling et al., 2007)Reduced alcohol and marijuana use for females and increased smoking for males6-year follow-up (ages 15-25; Kling et al., 2005)Reduced arrests for any crimes, violent crimes, and property crimes for females and increased arrests for property crimes for males	FemalesFemales	n/a n/a
SCHOOL-BASED CURRICULA
Tribes Hanson, Izu, Petrosino, Delong-Cotty, and Zheng (2012)	1 year of violence prevention activities taught 2-5 times per week	N = 2,309 students in Grades 1-452% male23% Asian, 22% Hispanic,20% White, 14% Black60% low income	1-year follow-upIncreased aggression for males but not females in Grades 1-2Reduced aggression for males but not females in Grades 3-4	Males	n/a
European Drug Abuse Prevention/Unplugged Vigna-Taglianti et al. (2009)	1-year program with 12 classroom lessons	N = 7,079 students aged 11-1852% maleFrom 7 European countries	At ages 11-18Decreased smoking, drinking, marijuana use, and hard drug use for males but not femalesIncreased smoking for females but not males	MalesFemales	n/an/a
Responding in Peaceful and Positive Ways Farrell, Meyer, and White (2001)	1-year program with 25 classroom lessons	N = 626 students in Grade 650% male96% Black	At Grade 7Reduced violence for females but not males	Females	Yes
Keepin’ it REAL Kulis, Yabiku, Marsiglia, Nieri, and Crossman (2007)	1-year program with 10 classroom sessions	N = 3,605 students in Grade 773% Hispanic	At Grade 7Only among less acculturated Hispanics, reduced smoking and drinking more for males than females	Males	Yes
Project ALERT Plus Longshore, Ellickson, McCaffrey, and St. Clair (2007)	3-year program with 19 classroom lessons	N = 1,772 students in Grade 756% male80% White	At Grade 9Reduced alcohol and marijuana use for females who used at baseline but not males	Females	n/a
TCYL Sloboda et al. (2009)	2-year program with 17 lessons taught in Grades 7 and 9 by police	N = 17,320 students in Grade 744% male35% White, 22% Hispanic, 14% Black	At Grade 11Increased smoking for females but not malesIncreased drinking and drunkenness for males but not females	Mixed	n/a
CLIMATE Alcohol Program Vogl et al. (2009)	1-year program with 6 classroom lessons	N = 1,434 students in Grade 859% maleAustralian	1-year follow-upReduced weekly drinking and binge drinking for females but not males	Females	n/a
AFTERSCHOOL PROGRAMS
Children’s Aid Society—Carrera Program Philliber, Kaye, and Herrling (2001)	3 years of academic, vocational, health and sports activities, and mental and physical health services	N = 1,163 youths aged 13-1545% male32% Black, 29% Hispanic, 15% multi-ethnic, 5% White	At ages 16-18Reduced initiation of marijuana use for males but not females	Males	n/a
COMMUNITY-BASED, MULTIPLE-COMPONENT PROGRAMS
Aban Aya Flay, Graumlich, Segawa, Burns, and Holliday (2004)	4-year program with 16-21 classroom lessons each year, parent support, and community mobilization	N = 1,153 students in Grade 550% maleAll BlackMostly low income	At Grade 8
			Reduced violence (7 items) for males but not females	Males	n/a
			Reduced substance use (cigarettes, alcohol, and marijuana) for males but not females	Males	n/a
CASASTART Mihalic, Huizinga, Ladika, Knight, and Dyer (2011)	2 years of individual case management including family support services, tutoring, mentoring, afterschool activities, and community policing	N = 364 high-risk youths aged 11-1360% male40% Black, 31% Hispanic, 12% White	At ages 13-15Reduced self-reported delinquency, violence, serious property offenses, and number of arrests for males, but increased self-reported delinquency, serious violence, hard drug use, and number of arrests for females	Males	Yes
DARE Plus Perry et al. (2003)	2-year program with 10 lessons taught by police, afterschool activities, and community mobilization	N = 6,237 students in Grade 752% male67% White	At Grade 8Reduced growth in smoking, drinking, and other drug use for males but not females	Males	Yes
LIFT DeGarmo, Eddy, Reid, and Fetrow (2009)	1-year program with 20 classroom sessions for students and 6 weekly sessions for parents	N = 351 students in Grade 549% male85% White	At Grade 12Reduced growth in smoking and other drug use more for females than males	Females	Yes
Resolve It, Solve It Swaim and Kelly (2008)	2-year program with 5-10 peer-led classroom sessions, media ads, and school and community events each year	N = 1,492 students in Grades 7-848% male67% White47% low income	2-year follow-upReduced growth in violent assaults (4 items) more for females than males	Females	n/a

Note. TCYL = Taking Charge of Your Life; LIFT = Linking the Interests of Families and Teachers.

http://www.campbellcollaboration.org/

http://www.crimesolutions.gov/about_otherlibraries.aspx

See Bandy (2012) and Bell, Terzian, and Moore (2012).

Table 3:

Preventive Interventions From the Blueprints for Healthy Youth Development Website^a With No Significant Gender Differences in Effects

Program NameCitation	Length/Dosage	Sample Size and Characteristics (at Baseline)	Outcomes That Did Not Show Gender Differences
HOME VISITATION PROGRAMS
Nurse-Family Partnership Olds, Henderson, and Cole (1998)	2.5 years of nurse visits every 2 weeks	N = 400 pregnant mothers, 85% unmarried, low SES, or teenagedN = 400 youths aged 0-2, 50% male, mostly White	At age 15Self-reported arrests and convictions
EARLY CHILDHOOD EDUCATION
HighScope/Perry Preschool Project Heckman, Moon, Pinto, Savelyev, and Yavitz (2010); Schweinhart (2013)	2 years of half-day preschool classes	N = 123 youths aged 3-458% maleAll BlackAll low income and low intelligence	By age 27 (Heckman et al., 2010)Lifetime arrests for any crimeBy age 40 (Schweinhart, 2013)Lifetime arrests for any crimeLifetime arrests for property crime
PARENT TRAINING
Effekt Koutakis, Stattin, and Kerr (2008)	5 parent meetings with project workers over 3 years	N = 811 students in Grade 7All Swedish	At Grade 9DrunkennessDelinquency (20 property and violent offenses)
SCHOOL-BASED CURRICULA
Good Behavior Game Furr-Holden, Ialongo, Anthony, Petras, and Kellam (2004)	2 years of ongoing classroom activities	N = 653 students in Grade 153% male86% Black62% low income	At Grade 8Initiation of smokingInitiation of illegal drug use
Positive Action Beets et al. (2009); Lewis et al. (2013)	Multi-year program with 20-min sessions 2-4 times per week	Beets et al., 2009N = 2,994 students in Grades 1-250% male26% Hawaiian, 23% multi-ethnic, 9% WhiteLewis et al., 2013N = 590 students in Grade 353% male53% Black, 30% Hispanic, 10% White84% low income	At Grade 5 (Beets et al., 2009)Drug use (tobacco, alcohol, and hard drugs)Violence (5 items)At Grade 8 (Lewis et al., 2013)Violence (6 items)
Project Towards No Drug Abuse Sussman, Sun, McCuller, and Dent (2003)	3-week, 12-session program	N = 1,037 students aged 14-1954% male45% White and 42% Hispanic	2-year follow-upUse tobacco and hard drugs
Safe Dates Foshee et al. (2004); Foshee et al. (2005)	1-year program with 10 classroom lessons	N = 1,886 students in Grades 8-949% male73% White, 19% Black	At Grades 11-12Physical dating violence perpetrationSexual dating violence perpetration
AFTERSCHOOL PROGRAMS
BBBS Tierney, Grossman, and Resch (1995)	At least 1 year of meetings 2-4 times per month	BBBS agencies in 8 citiesN = 1,138 low-income youths aged 10-16 (mean 12 years)62% male71% Black, 18% Hispanic	1-year follow-upInitiation of alcohol useInitiation of drug useSimple assault (hitting someone)
COMMUNITY-BASED, MULTI-COMPONENT PROGRAMS
Communities That Care Oesterle, Hawkins, Fagan, Abbott, and Catalano (2010)	Community-wide system with various school, family, and afterschool activities	N = 4,407 students in Grade 550% male68% White	At Grade 8SmokingDelinquency (9 property and violent offenses)
Project Northland Perry et al. (1996)	3- to 6-year program with school curricula and community-wide alcohol prevention activities	N = 2,351 students in Grade 653% male94% White	At Grade 8Alcohol use
Raising Healthy Children Catalano et al. (2003)	Multi-year program with school and family activities	N = 1,239 students in Grades 1-253% male82% White	At Grades 2-3Delinquency (10 aggressive acts or vandalism)

Note. SES = socioeconomic status; BBBS = Big Brothers Big Sisters.

http://www.blueprintsprograms.com/

Additional inclusion/exclusion criteria that guided our selection of interventions are as follows. Program evaluations had to assess outcomes for both male and female youth aged 0 to 18. Services had to be implemented by community-based agencies rather than juvenile justice institutions and could include programming for youth and/or parents, as long as effects on the youth were examined. Evaluations had to assess behavioral outcomes indicating actual involvement in substance use, delinquency, and/or aggression or violence by youth. Programs that evaluated only attitudes related to these behaviors (e.g., support for violence or beliefs that using drugs is harmful), intentions to commit deviant acts in the future, or behaviors that are not illegal for youth were excluded. Although offenses such as smoking or minor forms of assault may be considered somewhat trivial, evaluations that included such acts were eligible for review given that these acts are illegal. However, we did exclude interventions that focused only on smoking as many of these programs were older and not evaluated in high-quality research trials and/or relied on content that differed significantly from other program types. Interventions that assessed “externalizing” or “bullying” behaviors were eligible for inclusion only when the behaviors assessed were illegal (such as aggressive acts directed toward others). All evaluations of substance use prevention programs relied on self-reported information from youth. For programs seeking to reduce other types of illegal behaviors, outcomes were assessed using reports from youth, parents, or teachers and/or official reports of delinquency (e.g., arrest rates); all of these sources were considered valid and reliable and thus were eligible for inclusion in this review. The particular measures varied widely across studies and sometimes evaluated behavioral changes using a summary score indicating participation in multiple delinquent acts or use of more than one substance (e.g., tobacco, alcohol, and marijuana use). When describing results, we take care to note the actual behaviors measured and the types of acts included in summary measures.

Only programs that demonstrated effects that were at least marginally significant (at p < .10, using two-tailed tests) on one or more outcomes for at least one sex were eligible for inclusion. Evaluations could be based on either quasi-experimental or randomized experimental studies, so long as the study was well conducted and threats to internal validity were minimal. Studies were reviewed to ensure appropriate assignment of participants to conditions, baseline comparability, minimal and non-differential attrition, an intent-to-treat approach, use of valid and reliable instruments to assess outcomes, and appropriate statistical techniques. Finally, evaluations had to examine program effectiveness either in separate analyses of female and male participants or analyze and find at least marginally significant (p < .10) gender differences using interaction terms and/or group difference tests. Although we would have preferred to limit our review to evaluations meeting the second criterion (i.e., those that actually tested for gender differences), doing so would have reduced the number of studies by about half.

Results

Prevention programs listed on the Blueprints for Healthy Youth Development website that evidenced gender differences in outcomes are listed in Table 1. In addition to providing information on the program type (e.g., home visitation), length or “dosage” (e.g., number of sessions and/or duration of programming), and sample characteristics, Table 1 identifies significant effects on delinquency-related outcomes that were specific to one sex or the other or which evidenced a stronger impact on one sex compared with the other. In total, nine programs (with 14 evaluation studies) on the Blueprints site had outcomes that varied for male and female participants.

The programs listed in Table 1 are diverse in terms of their content, scope or duration, and intended audiences. They include very early intervention strategies such as home visitation and early childhood education programs, as well as family-, school-, and community-based interventions for middle and high school youth and/or their families. Both home visitation and early childhood education programs are usually classified as selective programs intended for higher risk individuals. As seen in Table 1, the Nurse-Family Partnership program (Eckenrode et al., 2010) is intended for low-income, teenage mothers having their first child. The mothers receive regular visits from nurses to help them care for themselves during pregnancy and to learn how to nurture and care for their newborn child. The HighScope/Perry Preschool Project (Schweinhart & Weikart, 1997) provides low-income youth from minority racial/ethnic groups (mostly African American) with high-quality education services. Both of these interventions are intensive, offering regular service provision for at least 2 years. The family, school, and community programs are universal prevention strategies, intended to be delivered to a diverse audience. Typically, parent training programs allow caregivers to come together to learn and discuss strategies for effectively monitoring and supporting their children, whereas school-based programs aim to strengthen students’ decision-making, communication, and other personal and social skills by relying on teachers to provide structured information and opportunities for discussion and role playing. Community-based interventions often offer a combination of these types of services. All of these types can range in their duration, from a minimum of 3 weeks (e.g., Project Towards No Drug Abuse) to 3 to 6 years (e.g., Project Northland).

As shown in Table 1, mixed results were found regarding gender differences in the effectiveness of these nine interventions, with about half evidencing stronger effects for males and the other half evidencing stronger effects for females. Of the seven programs that actually tested for and found gender differences in outcomes, four demonstrated more positive effects for males and three for females (see the last column in Table 1). There are no discernible patterns regarding these effects. That is, the findings do not clearly indicate that particular types of programs were more effective for females than males or vice versa, as based on their delivery setting, content, dosage, age of participants, or behavioral outcome(s). Moreover, some of the interventions were shown to have positive effects for both sexes, but one sex benefitted more than the other, while others produced significant changes in behaviors for only males or only females. Importantly, no harmful effects were found for any program for either sex.

Table 2 lists the programs identified by sources other than Blueprints that showed evidence of gender differences in outcomes. Similar to those listed in Table 1, these are a diverse group of interventions focused on reducing substance use, delinquency, and/or violence via family-focused interventions, school- or classroom-based curricula, afterschool activities, and community-based practices. The school-based programs included in this table tended to be shorter in duration (a year or less) than the other types and targeted more universal audiences, while many of the other intervention types were designed for selective populations considered at higher risk for delinquency, such as those from low-income families or neighborhoods and youth from non-White racial/ethnic groups. As with the interventions listed in Table 1, the community-based strategies tended to provide an integrated set of components, such as classroom-based curricula for students, parent training sessions, and/or community mobilization activities such as community forums to highlight problems associated with adolescent substance use or violence or the passing of local ordinances to make access to alcohol more difficult.

Although these programs were not equally effective for female and male participants, no clear pattern emerged regarding gender differences in effects. Seven of the 15 programs showed significant and/or stronger effects for females compared with males, whereas six showed the opposite relationship, and two had mixed effects. Nine of the programs did not actually test whether gender differences in effects were statistically significant, and of the six that did, three showed stronger positive effects for females and three for males. Given these results, it is difficult to identify any program characteristics that predicted better outcomes for one sex or the other. For example, some school-based programs were more effective in reducing substance use or delinquency for females but others showed more positive results for males. Similarly, neither the length of programming nor the characteristics of program participants appeared to be related to sex differences in effectiveness. More intensive programs and those for higher risk youth sometimes affected females more positively, but, in other cases, males experienced more beneficial outcomes from these types of interventions.

Importantly, five of the 15 programs demonstrated harmful effects for participants. Two evaluations (of the Unplugged and CASASTART programs) indicated increases in problem behaviors for girls who participated in the program (but reductions for boys), compared with those in a control group; one (Moving to Opportunities) evidenced harmful effects for males; and one evaluation (of the Tribes program) indicated increases in aggression for males who received the program in Grades 1 to 2 but lower rates of aggression for males who received the program in Grades 3 to 4. The Taking Charge of Your Life curriculum (Sloboda et al., 2009) showed iatrogenic outcomes for both sexes. Boys who received the program were more likely to report drinking and getting drunk compared with those in the control group, while girls who received the program were more likely than those in the control group to report smoking 2 years following the 3-year intervention. The studies showing iatrogenic effects represent a diverse group of programs making it difficult to pinpoint characteristics of programs that are associated with harmful outcomes for either male or female participants.

While this review identified 24 interventions that demonstrated gender differences in some outcomes, it is important to consider the larger context in which these results were evidenced. On average, are interventions likely to show similar effects for females and males or different effects? To explore this issue, we provide in Table 3 a list of programs from the Blueprints website that tested for but did not demonstrate gender differences in effects on substance use, delinquency, and violence.⁵

Eleven of the Blueprints-nominated programs demonstrated similarity in intervention effectiveness for female and male participants. These findings suggest that gender similarity may be at least as common, if not more common, than gender differences in effects, at least when considering delinquency prevention programs evaluated in high-quality experimental trials. It is also clear from the findings in Table 3 that some of the same programs, and the same program types, can show evidence of gender similarity and gender differences in effects, depending on the outcome assessed and/or the follow-up period at which effects were analyzed. For example, the Nurse-Family Partnership program demonstrated similar positive effects in reducing male and female adolescents’ reports of being arrested or convicted through age 15 (Olds, Henderson, & Cole, 1998), but at age 19, the program had greater reductions in arrests and convictions for girls compared with boys (Eckenrode et al., 2010). As another example, an evaluation of Project Towards No Drug Abuse (Sussman, Sun, McCuller, & Dent, 2003) showed stronger reductions in marijuana use for male compared with female participants, but reductions in smoking and use of hard drugs were of a similar magnitude for both sexes. As we will discuss in more detail in the next section, these findings emphasize the need for community implementers to carefully review all evidence of program effects prior to making decisions about which sex to target for services.

Discussion

This study likely represents the first comprehensive review of the potential for community-based preventive interventions to have differential effects on male and female substance use, delinquency, and violence during adolescence. This research is important given the increasing focus on using evidence-based interventions to reduce delinquency and crime (Andrews et al., 1990; Farrington & Welsh, 2007; Sherman et al., 1998), and on using a gender-responsive approach (Bloom et al., 2002; Hubbard & Matthews, 2008; Kempf-Leonard & Sample, 2000) to ensure that boys and girls receive interventions that target the criminogenic factors that are most salient for them. The goals of the current article were to help integrate these lines of research by identifying preventive interventions that have shown evidence of gender differences in well-conducted evaluation trials, identifying types of programs that may be more or less effective for females and males, and using this information to guide gender-responsive delivery of such interventions.

In terms of the first goal, the review indicated that many evidence-based preventive interventions have differing effects for male and female participants, which is important given the often prevailing assumption that preventive interventions will have generalizable outcomes across individuals and do not need to be tailored to or delivered only to particular groups of individuals (Elliott & Mihalic, 2004). Nine of the 47 interventions listed on one of the most rigorous databases of effective programs, Blueprints for Healthy Youth Development, showed evidence of gender differences in outcomes when implemented with male and female participants. That is, some of the interventions impacted girls’ substance use, delinquency, and/or violent behavior more than boys’, whereas other programs were more effective for boys. Fifteen additional interventions classified as effective according to other sources also had a differential impact on females and males.

Importantly, five programs were shown to have iatrogenic effects for one sex or the other. Two interventions were found to increase the likelihood of delinquency for girls but not boys, two showed the opposite finding, and the Taking Charge of Your Life program (Sloboda et al., 2009) showed harmful effects in increasing substance use for both sexes. Our discovery that 24 evidence-based delinquency prevention programs showed gender differences in outcomes emphasizes the need for program evaluations to routinely investigate variations in intervention effectiveness by sex. The fact that interventions can have harmful effects for one sex but not the other, and the potential for failing to uncover such iatrogenic effects when only analyzing program impacts for the entire sample, makes this recommendation even more critical. For example, the evaluation of CASASTART (Mihalic, Huizinga, Ladika, Knight, & Dyer, 2011) indicated reductions in delinquency, violence, and arrests for males but increases in these outcomes for females. Had the authors of this study not examined effects by gender, they may have reported that the program had no impact at all, a false conclusion masking the benefits for male participants and the harmful effects for girls.

We are encouraged by the growing awareness of the need to examine differential effectiveness in interventions according to gender as well as other participant characteristics (e.g., age, race/ethnicity, etc.; Flay et al., 2005). However, much progress needs to be made in this area. We found numerous other evaluations in our review of the literature that did not consider (or publish) gender differences in program outcomes. In addition, only 13 of the 24 programs listed in Tables 1 and 2 actually used statistical tests to compare the size of the impact across male and female participants, whereas the other evaluations limited their analyses to determining effects within gender groups. Although both methods increase our understanding of program effectiveness for male and female participants, the first strategy provides much stronger evidence of gender differences in effects and, as a result, will be more useful for guiding gender-responsive service delivery.

To expand on the practical implications of this review (the third goal of the article), the findings suggest that program implementers can and should take gender into account when replicating evidence-based programs. If a program demonstrates significant reductions in substance use for both sexes, but stronger effects for females than males (which can only be demonstrated via a gender difference test), then it would be “safe” to provide the intervention to both sexes. However, given limited budgets, a community might try to recruit more (or only) girls to the intervention than boys. In addition, practitioners need to know if an intervention has harmful effects for one or both sexes so that they can avoid delivering the program to that group. Because implementers are unlikely to have access to the scientific literature in which such evidence is described, we recommend that internet-based lists of evidence-based programs clearly identify the populations for whom programs have been shown to be effective, ineffective, or harmful. The Blueprints for Healthy Youth Development website makes this information accessible to users, but such information is not as easy to find on other websites.

Although our review indicated that many community-based preventive interventions have differential effects for males and females, these findings should not be over-stated. As shown in Table 3, many programs also showed no evidence of gender differences. Moreover, in many cases, the same program produced similar benefits for girls and boys for some outcomes and gender differences in other outcomes. Such findings suggest that relatively few interventions will show gender differences in all outcomes evaluated, across all follow-up periods, or every time a program is replicated. In light of this information, we repeat the recommendation that practitioners base their implementation choices on a careful review of evidence of program effectiveness. If evaluations indicate that programs are effective for both sexes, then both boys and girls could safely be targeted for services. If gender differences in effects are found, then service providers should be strategic in their implementation approach and target those whose behavior can most positively be impacted.

We had limited success in achieving the second goal of the article, which was to identify particular program types showing greater program effectiveness for one sex or the other. The systematic review indicated that some programs were more effective for females and others were more effective for males, but no clear patterns of relationships emerged. For example, about half the school-based programs evidenced stronger effects for girls and about half showed stronger effects for boys, and similar findings were shown for family-focused, afterschool, and community-based programs. This mixed pattern mirrors and does not resolve the inconsistent results produced by empirical studies that have investigated the degree to which risk and protective factors vary by sex. Similar to the empirical literature, there was much variation in how particular measures were assessed across evaluation studies (e.g., some relied on self-reports and others on official crime records; some studies evaluated only a few delinquent behaviors whereas others included a broader array of offenses), which may have hindered our ability to detect patterns. Nonetheless, the findings do not preclude gender-responsive approaches to delinquency prevention. Practitioners can and should still use evaluation information to guide their implementation choices, but these decisions will have to be made for each and every program they wish to replicate. However, we do not have adequate information at this point to recommend that particular types of programs be replicated only for girls or only for boys.

Our review also suggests the need for evaluators and practitioners to avoid making assumptions regarding how boys and girls will respond to the content or delivery style of a particular program (or program type). For example, some of the evaluations reviewed had hypothesized that because girls have lower rates of offending, they would be less amenable to prevention programming (Kellam & Anthony, 1998; Perry et al., 2003). Nonetheless, some programs seeking to reduce aggression and violence, behaviors more likely to be displayed by boys, were more effective for girls. Interestingly, other evaluations suggested an opposing hypothesis: that because males engage in more delinquency than girls, they will require more intensive change efforts and will be less affected by shorter and/or more universal interventions (Vogl et al., 2009). However, our review indicated that some low-intensity programs demonstrated stronger effects for males, whereas some of the longer term and more intensive interventions were more effective for females, though the opposite pattern of effects was also shown. Likewise, some universal programs were more effective for boys, but others were more effective for girls. Because we did not find any consistent pattern of gender differences in terms of the program type, length/dosage, or characteristics of participants, we cannot say with any certainty that particular programs should be restricted to one sex or the other. Instead, we would recommend that these decisions be made on a case-by-case basis, taking into account the evaluation evidence for each intervention being considered for replication.

In conclusion, our review of the literature identified a varied set of interventions that showed some evidence of differential effects for male and female participants, including some harmful effects for each sex, and also many which had no evidence of gender differences in impact. Based on these findings, it is premature to make general conclusions regarding the types of programs that are “ready” to be disseminated to all sexes or which should be restricted to one sex or the other. Additional investigation of gender differences is required to arrive at such conclusions. In the meantime, we advocate that practitioners be aware that gender differences may exist, and that they consider this information when preparing to implement interventions aimed at reducing delinquency.

Footnotes

Notes

Abigail A. Fagan is an associate professor in the Department of Sociology and Criminology & Law at the University of Florida. Her research focuses on the causes and prevention of juvenile delinquency, particularly family and community influences on youth offending; the relationship between victimization and offending; and gender differences in delinquency. She also studies issues related to the identification, implementation, and dissemination of effective delinquency and crime prevention strategies.

Andrea M. Lindsey is a doctoral student in the College of Criminology and Criminal Justice at Florida State University. Prior to attending Florida State for her master’s degree, Andrea completed her bachelor’s degree in criminology and criminal justice at Arizona State University. Her research interests are in neighborhoods and crime, prisoner sentencing and reentry, juvenile justice, and public policy.

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