7
Preventing Drug Use

Prevention can be broadly defined to encompass an array of noncoercive activities intended to prevent, reduce, or delay the occurrence of drug-taking or associated complications, such as clinical syndromes of drug dependence and threats to public safety. This chapter emphasizes nonlegal, noncoercive approaches to reducing drug use in populations that are not yet seriously involved with drugs. They include efforts to educate people about the consequences of substance use, to change their beliefs about the acceptability or utility of substance use, and to increase or make more salient the costs of substance use. We address what is known, what is not known, and what data and research are needed to increase useable knowledge about the effectiveness of a wide range of approaches.

It is important to note at the outset that although this report concerns itself with illegal drug use, the notion that the use of tobacco, alcohol, and marijuana increases the probability of later illegal drug use, which is generally accepted in the prevention field, requires that these other substances be considered in this chapter. It is also the case that almost all of the available research in this area deals with what are called “gateway” substances, rather then cocaine, crack, heroin, and the other illegal drugs that are the focus of the other chapters of this report.

PREVENTION STRATEGIES

There are a number of possible factors that might be manipulated to reduce substance use, as suggested in Chapter 2. Many deliberate preven-



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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us 7 Preventing Drug Use Prevention can be broadly defined to encompass an array of noncoercive activities intended to prevent, reduce, or delay the occurrence of drug-taking or associated complications, such as clinical syndromes of drug dependence and threats to public safety. This chapter emphasizes nonlegal, noncoercive approaches to reducing drug use in populations that are not yet seriously involved with drugs. They include efforts to educate people about the consequences of substance use, to change their beliefs about the acceptability or utility of substance use, and to increase or make more salient the costs of substance use. We address what is known, what is not known, and what data and research are needed to increase useable knowledge about the effectiveness of a wide range of approaches. It is important to note at the outset that although this report concerns itself with illegal drug use, the notion that the use of tobacco, alcohol, and marijuana increases the probability of later illegal drug use, which is generally accepted in the prevention field, requires that these other substances be considered in this chapter. It is also the case that almost all of the available research in this area deals with what are called “gateway” substances, rather then cocaine, crack, heroin, and the other illegal drugs that are the focus of the other chapters of this report. PREVENTION STRATEGIES There are a number of possible factors that might be manipulated to reduce substance use, as suggested in Chapter 2. Many deliberate preven-

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us tion activities are based on the expectation that altering one or more of these factors will result in reduced substance use (Center for Substance Abuse Prevention, 1999; U.S. Department of Education, 1999). A wide assortment of modalities, delivery schedules, and targeting mechanisms are used to alter these factors. The following paragraphs describe some of the more common prevention modalities in use today. Based on a taxonomy for a recent national study of delinquency prevention in schools (Gottfredson et al., 2000), these modalities are neither exhaustive nor evaluative, but instead are intended to provide a sense for the variety of different activities that can be and are undertaken for the purpose of preventing subsequent substance use. Mass media campaigns. These efforts are most often aimed at changing norms regarding drug use by demonstrating negative consequences for use, positive consequences for nonuse, changing opinions about the prevalence of use or the types of people who use, and increasing skills for resisting drugs. Media avenues might include the use of billboards, newspapers, radio, and television, as well as collaborations with the entertainment industry, music videos, and interactive media. The ongoing National Youth Anti-Drug Campaign of the Office of National Drug Control Policy is an example of such a media campaign implemented at the national level. Reducing pro-drug media messages is also included in this category of prevention activity. Community organizing and coalitions. These efforts require collaboration among several community entities to develop community-wide strategies for reducing substance use. They generally involve representatives from community agencies working together to specify goals for reducing substance use, develop collaborative strategies for reaching those goals, and implement those strategies over a period of several years. Often, these community planning groups are more grassroots in nature, involving and empowering community residents in addition to professional staff. Well-known examples of this type of strategy include Project STAR (Pentz et al., 1989) and Project Northland (Perry et al., 1996). Family training, counseling, and case management. This category includes efforts to alter family management practices or to build parenting skills in general through instruction or training. These activities often teach parents skills for monitoring or supervising their children, increasing emotional attachments, helping their children succeed in school, or otherwise assisting their children in the development of skills and competencies that will be needed to avoid substance use. An example is the Strengthening Families Program (Kumpfer et al., 1996). Family therapy often focuses on building the same skills, but it is generally more intensive than parent training activities and usually involves high-risk adolescents and their

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us families. Family case management includes a variety of monitoring and intervention activities to assist families who are in need of services. Drug-involved families may be encouraged to seek treatment, and conditions that might facilitate relapse are addressed. Classroom instruction. This is the most common strategy used in schools. The content of these interventions varies, but they can be grouped into three main classes: Information-only interventions teach students factual information about drugs and the consequences of use. Skill-building interventions increase students’ awareness of social influences to engage in misbehavior and expand their repertoires for recognizing and appropriately responding to risky or potentially harmful situations. Normative education interventions change perceptions of the norms related to substance use. Many instructional programs contain different mixes of these three types. Two well-known examples are the Drug Abuse Resistance Education (D.A.R.E.) program and Life Skills Training. The most effective of these instructional programs use what are called cognitive-behavioral or behavioral instructional methods, which rely on modeling, providing rehearsal, and coaching in the display of new skills (Gottfredson, 2001). Cognitive behavioral, behavioral modeling, and behavior modification strategies. Behavior modification strategies focus directly on changing behaviors. They involve timely tracking of specific behaviors over time and behavioral goals, using feedback and positive or negative reinforcement to change behavior. These strategies rely on reinforcers external to the student to shape behavior; an example of their use is the Good Behavior Game (Dolan et al., 1993; Kellam et al., 1994; Kellam and Anthony, 1998). Larger or more robust effects on behavior are obtained by teaching students to modify their own behavior using a range of cognitive strategies. Efforts to teach students cognitive-behavioral strategies involve modeling or demonstrating behaviors and providing rehearsal and coaching in the display of new skills. Students are taught, for example, to recognize the physiological cues experienced in risky situations. They rehearse this skill and practice stopping rather than acting impulsively in such situations. Students are taught and rehearsed in such skills as suggesting alternative activities when friends propose engaging in a risky activity. And they are taught to use prompts or cues to remember to engage in behavior. Lochman’s (1992) Anger Coping Training is an example of this type of preventive intervention. Other counseling, social work, psychological, and therapeutic strategies. Family prevention and cognitive-behavioral approaches often involve counseling specifically targeted at certain behaviors or cognitions. Prevention can also consist of more generic individual counseling, case man-

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us agement, or similar group-based interventions other than those described above. Student assistance and peer counseling programs, popular in many schools, are included in this category. Mentoring, tutoring, and work study strategies. These efforts primar-ily aim to increase the stakes in conformity and reduce individuals’ predispositions to use drugs. Mentoring is distinguished from counseling because it is generally provided by a lay person rather than a trained counselor and is not necessarily guided by a structured approach. Tutoring includes individualized assistance with academic tasks. Recreational, community service, enrichment, and leisure activities. These are activities intended to provide constructive and fun alternatives to drug use. Drop-in recreation centers, after-school and weekend programs, dances, community service activities, and other events are offered in these programs as alternatives to more dangerous activities. The popular Mid-night Basketball is included in this category. School and discipline management. This category includes interventions to change the decision-making processes or authority structures to enhance the general capacity of the school. These activities parallel those described under community organizing above, but they are contained within a school building or a school system. These interventions often involve teams of staff and (sometimes) parents, students, and community members engaged in planning and carrying out activities to improve the school. They often diagnose school problems, formulate school goals and objectives, design potential solutions, monitor progress, and evaluate their efforts. Activities aimed at enhancing the administrative capability of the school by increasing communication and cooperation among members of the school community are also included. Examples include Project PATHE (Gottfredson, 1986) and Comer’s School Development Process (Comer, 1985; Cook et al., 1998). Often these interventions also include efforts to establish or clarify school rules or discipline codes and mechanisms for the enforcement of school rules—strategies discussed in more detail in Chapter 6. Establishment of norms and expectations for behavior. These activities include school-wide or community-wide efforts to redefine norms for behavior and signal appropriate behavior. Activities include newsletters, posters, ceremonies during which students declare their intention to remain drug-free, and displaying symbols of appropriate behavior. Some well-known interventions in this category are Red Ribbon Week, sponsored through the Department of Education’s Safe and Drug-Free Schools and Communities program. Classroom and instructional management. Aside from teaching specific content intended to reduce the probability that students will use drugs, teachers can also use instructional methods designed to increase student

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us engagement in the learning process and hence increase their academic performance and bonding to the school (e.g., cooperative learning techniques and “experiential learning” strategies) and classroom organization and management strategies. The latter include activities to establish and enforce classroom rules, uses of rewards and punishments, time management to reduce down-time, strategies for grouping students within the class, and the use of external resources, such as parent volunteers, police officers, and professional consultants as instructors or aides. The Seattle Social Development Project (Hawkins et al., 1992) relied in large part on such classroom and instructional management strategies. Regrouping students. Schools can reorganize classes or grades to create smaller units, continuing interaction, or different mixes of students or to provide greater flexibility in instruction. This category includes changes in the school schedule (e.g., block scheduling, scheduling more periods in the day, changes in the lengths of instructional periods); adoption of schools-within-schools or similar arrangements; tracking into classes by ability, achievement, effort, or conduct; formation of grade-level “houses” or “teams”; and decreasing class size. These changes are often intended to increase sources of social control for students. Exclusion of intruders and contraband. These interventions are designed to prevent intruders (who might be drug dealers) from entering the school. They include the use of identification badges, visitor’s passes, security personnel posted at school entrances, locks, cameras, and other surveillance methods. They also include efforts to prevent contraband from entering the school, such as locker searches and drug-sniffing dogs. These strategies are discussed in greater detail in Chapter 6. Manipulation of school composition. These interventions determine who will be enrolled in the school and include such strategies as the use of selective admissions practices, assignment of students with problem behavior to “alternative schools,” and other exclusionary or inclusionary practices. Zero-tolerance policies, which automatically expel students who bring drugs to school, are an example of such a strategy. These sanction-related policies are discussed at greater length in Chapter 6. Although little is known about the extent to which these different prevention strategies are used in local communities, a recent national study of school-based prevention attempted to describe the prevalence of prevention strategies used in schools (Gottfredson et al., 2000). The investigators asked school principals to report which of 14 types of discretionary prevention activities—instruction, counseling, norm change, recreation, etc. —were currently in place in their schools, and to name each specific activity currently under way in each of the 14 categories. On average, principals reported 9 of the 14 types of prevention activities under way in their schools. The median number of different specific pre-

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us vention activities named was 14—and this underestimates the total number of activities because principals were asked to name only their discretionary activities rather than all activities. Prevention curricula were the most popular modality, used in 76 percent of the nation’s schools. Every type of prevention activity included in the survey was used in at least 40 percent of the schools. Clearly, a wide variety of prevention strategies is currently in use in U.S. schools. LIMITED EVIDENCE OF EFFECTIVENESS What is known about the effectiveness of prevention is limited by the types of prevention that have been studied. Although a wide variety of prevention strategies are in use, most studies of effectiveness are of classroom instructional strategies. For example, in a recent meta-analysis of school-based programs (Gottfredson et al., forthcoming), 78 percent of the treatment-control comparisons of program effectiveness involve instructional programs, such as ALERT (Ellikson and Bell, 1990; Ellickson et al., 1993) and Life Skills Training (Botvin et al., 1984a, 1984b). It comes as no surprise, then, that most reviews of substance abuse prevention have focused on distinctions among types of instructional programs rather than on the broader array of strategies which have not been well studied. At least 20 reviews and meta-analyses of drug prevention programs were published during the 1980s and 1990s. The most recent of these generally conclude that substance abuse prevention efforts are “effective” for preventing substance use, in the sense that the studies reviewed report statistically significant differences between subjects receiving and not receiving the preventive intervention on some measure of substance use, at least immediately following the termination of the prevention activity, and in rare cases months or years beyond that point (Botvin, 1990; Botvin et al., 1995; Dryfoos, 1990; Durlak, 1995; Ennett et al., 1994a, 1994b; Gerstein and Green, 1993; Gorman, 1995; Gottfredson, 1997; Gottfredson et al., forthcoming; Hansen, 1992; Hansen and O’Malley, 1996; Hawkins et al., 1995; Institute of Medicine, 1993, 1994; Norman and Turner, 1993; Tobler, 1992; Tobler and Stratton, 1997). (One study—Gorman, 1995—a review limited to the effects of one type of program on one specific substance, is the only exception.) However, certain practices in the reporting of original research and in the summaries of these findings have tended to overstate the effectiveness of prevention activities. For example, there is an “availability” bias in the published literature. Studies showing limited effectiveness often are difficult to publish and may remain unpublished technical reports available only in the original investigator’s office. Lipsey and Wilson (1993) summarized the results of 302 reviews of psychological, behavioral, and educational interventions

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us and found that effect sizes in published studies were 0.14 standard deviations larger than in unpublished studies. They also noted, however, that this bias could not completely account for the positive findings found in the studies. Effects are also sometimes exaggerated when either the original research or subsequent summaries highlight only the few statistically significant findings among the many nonsignificant ones, a subsample for which results are significant, or results for a “high-fidelity” sample. These are all examples of selective attention to positive findings that operate similarly to the availability bias mentioned above. Often studies measure substance use or a related outcome using multiple measures, and only one of the several measures may show a statistically significant positive effect. Summaries of this research will almost always omit the information about the null findings. Of course, this practice increases the likelihood of false positives because each test involves a 5 percent chance of a false positive, and this probability cumulates over multiple tests. This same type of bias is evident in some federal activities to identify effective programs. Criteria for effectiveness require only a single positive finding, rather than a preponderance of positive findings (e.g., U.S. Department of Education, 1999). More careful research identifies the primary outcome of interest at the outset and limits the hypothesis testing to that outcome, or uses one composite of multiple outcomes of interest to avoid increasing the risk of false positives. The practice of reporting results for high-fidelity samples is also often misleading because it confounds other factors with the success of the program. For example, a study that randomly assigns schools to treatment and control conditions may find that only half of the schools assigned to the treatment condition faithfully implemented the program. Yet outcomes for only this high-fidelity sample often are presented instead of, or in addition to, the comparisons of the treatment and control schools as they were actually assigned. Investigators argue that the comparison of the original groups underestimates the actual program effect, because it includes schools that did not actually carry out the program. What they fail to point out is that in selecting the high-fidelity sample, they are also likely to be selecting on unmeasured extraneous factors that may also be related to the outcome of interest, including high teacher morale, effective school leadership, and favorable school-community relations. This selection renders the groups nonequivalent in ways that have not been measured and cannot be controlled. Most reviews of drug prevention programs have also focused on statistical significance rather than the magnitude of effects as the sole criterion for determining effectiveness. Because significance levels depend in part on the number of cases included in the study, and because statistical

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us significance does not necessarily map into practical significance, the policy relevance of this information is questionable. A handful of reviews go a step farther by providing a measure of the magnitude of the effect of different types of prevention strategies, irrespective of statistical significance. The magnitude of the program effect is often expressed as a standardized mean difference effect size (ES), a measure of the difference between the program and comparison groups relative to the standard deviation of each measure employed. The use of the ES allows for the direct comparison of effects across studies and outcomes. ESs typically range from –1.0, indicating that the treatment group performed one standard deviation lower than the comparison group, to +1.0, indicating that the treatment group performed one standard deviation higher than the comparison group (although larger absolute values do occur). Rosenthal and Rubin (1982) showed that the ES can be translated into differentials in success rates between the program and comparison groups, greatly facilitating the interpretation of the ES. For example, assuming an overall success rate of 50 percent, an ES of 0.50 translates into a success rate of 62.5 percent for the program group and 37.5 percent for the comparison group—a success rate differential of 25.1 The practical significance of an effect size depends largely on the seriousness of the outcome for the population and the effort needed to produce the effect. Lipsey (1992) argues that even a small effect (e.g., an ES of 0.10) for serious criminal behavior has practical significance. A small percentage difference between treated and untreated subjects on a prevalence measure in a high-frequency offending population could represent a large volume of crime. Likewise, small effect sizes on measures of very serious crimes are worthy of note because preventing even a small number of such crimes is important. Only a handful of reviews of prevention programs have reported ESs. One of the earliest was Tobler (1986), who reported ESs derived from 98 research studies. These studies yielded 159 different measures of program effectiveness on some measure of substance use (including cigarette use). 1   To see the algebra for this translation, let y indicate success so that y=1 if successful and 0 otherwise, and let z=1 if a respondent is assigned to the program and 0 to the comparison. In this example, we observe P[y=1]=0.5 and that ES={P[y=1|z=1]–P[y=1| Thus, P[y=1|z=1]–P[y=1|z=0]=0.25 (1) and, assuming that half of subjects are assigned to the program, P[y=1|z=1]+P[y=1|z=0]=1. (2) Solving these two equations implies P[y=1|z=1]=0.625 and P[y=1|z=0]=0.375.

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us The mean effect size across all of these measures was 0.24. Tobler’s most recent analysis examined 120 programs of school-based drug prevention programs between 1978 and 1990 (Tobler and Stratton, 1997). This study showed median effect size of 0.14 on measures of tobacco, alcohol, and other drug use across all programs. Results from the most recent meta-analysis of school-based drug prevention programs (Gottfredson et al., forthcoming) documents effect sizes slightly smaller than those from previous meta-analyses.2 This study found that across 88 relevant published treatment-control comparisons, the mean effect size for school-based prevention activities on measures of alcohol and other drug use (but not tobacco use) is statistically significantly different from zero. The mean effect size was 0.054, which (assuming a control group prevalence rate of 50 percent) translates into about a 2.7 point difference between the prevention and control groups in the percentage of students who report using a substance. Although the average effect size across all studies is small, the range of average effect sizes observed from study to study is broad (–.44 to .54) and varies by type of prevention program. In contrast to these small effects of substance abuse prevention programs are the larger effects found on a wider array of outcomes of psychological, behavioral, and educational interventions. Lipsey and Wilson (1993), summarizing effect sizes from 302 reviews of such studies, reported an average of the average effect sizes across these reviews of 0.50 with a standard deviation of 0.29. Thus, relative to a much broader set of social and behavioral outcomes, substance use is more difficult to alter, at least through the types of prevention strategies that have been studied. GAPS IN THE EXISTING KNOWLEDGE BASE The limited evidence available suggests that some forms of prevention activities are effective for reducing some measures of substance use. Some studies produce a substantial effect, and others no effect or negative effects. This section takes a closer look at the available evidence in order to highlight its limitations as a basis for policy decisions. 2   Gottfredson et al. (forthcoming) recalculated effect sizes based on the entire population that received any of the program whenever possible. Also, if multiple effect sizes were available for different measures of substance use, these multiple measures were averaged to obtain one effect size per study. These practices, as well as the exclusion of effects on tobacco use, may explain the slightly lower estimates of the magnitude of effects found in this study.

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us For Whom Does Prevention Work? Universal Programs Most of what we know about the effectiveness of prevention comes from studies of “universal” programs, which target the general population. These universal approaches, which often focus on incipient or “gateway” drug use, are based on the assumption that early experimentation with tobacco, alcohol, and marijuana can lead to more frequent use of these substances and progression into the use of other more dangerous substances. This gateway notion is rooted in early conceptions of marijuana as a stepping-stone to more serious drug involvement (Wagner and Anthony, 1999) as well as research evidence of a statistical link between age at first use of drugs and later more frequent or problematic use (Brunswick and Boyle, 1979; O’Donnell and Clayton, 1979; Robins and Przybeck, 1985; Anthony and Petronis, 1991) Findings such as these and subsequent analyses of sequences of drug use patterns over time led to a developmental stage theory of adolescent involvement in legal and illegal drugs (Kandel, 1975; Kandel and Faust, 1975). According to this perspective, use of alcohol and tobacco precedes the use of illegal drugs, and the use of marijuana precedes the use of other illegal drugs. Early descriptions of this developmental process (e.g., Kandel, 1982) were careful to point out that most individuals who reach a given stage of substance use discontinue it for one reason or another, and that only a small subgroup of users at earlier stages actually progress to the next stage of use. Although sophisticated research demonstrated that the use of legal drugs is associated with increased probability of marijuana use, and the use of marijuana is associated with increased probability of other illegal drug use (Yamaguchi and Kandel, 1984), the authors stress the limitations on the inferences about the link between use of one drug and use of another. They point out (p. 679) that personality and lifestyle variables, as well as environmental factors such as availability and supply, also explain the transition from one drug to another and from one level of use to another. In particular, they pointed out the need to control for individual propensity variables prior to the time of initiation into legal drug use. These effects due to heterogeneity in population characteristics are confounded with the early use of gateway substances. The models do not rule out the alternative interpretation that some individuals are more likely to use more drugs, to use more dangerous drugs, to persist in their use for a longer period of time, and to begin their use earlier than others. This idea is consistent with the well-established findings in the criminological literature (Moffitt, 1993) that the offending

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us population consists of two distinct groups: a large group of individuals who experiment with illegal activities for a relatively short time during adolescence and then desist, and a small group of offenders who begin their criminal careers earlier, end them later, and offend at higher rates during their criminal careers. The latter group is responsible for the majority of the crime that occurs. MacCoun (1998) also notes that there are several plausible causal interpretations of the basic findings that tobacco, alcohol, marijuana, and hard drug use are associated and tend to occur in a particular sequence. One interpretation suggests that the association is spurious or noncausal— specifically, the notion (discussed earlier) that the use of the early and late drugs in the sequence reflects some common risk factors, with timing determined by price and availability. Other interpretations are causal— for example, experiences with the early substances in the sequence might: (a) stimulate one’s interest or appetite for the later substances, (b) change one’s beliefs about the severity of health, legal, or social risks of drug use, (c) bring one into contact with a subculture of hard drug users, or (d) bring one into contact with hard drug sellers. Interestingly, the first causal interpretation is widely cited in the United States as a basis for stringent sanctions against marijuana; the latter three interpretations were influential in the development of Dutch drug policy, which seeks to separate “soft” and “hard” drug markets and cultures (see MacCoun and Reuter, 1997). Few actual data are available to direct policy decisions about the targeting of prevention activities, but debates over appropriate targeting have appeared at the margins of the prevention literature. Although the field continues to be predominated by the gateway ideas, a few commentators have questioned this approach (Brown and Kreft, 1998; Gilham et al., 1997; Gilchrist, 1991). Brown and Kreft (1998) argue that the “no use” messages typically conveyed in universal prevention programs actually increase use among those most at risk for using. These youths are more knowledgeable about drugs and their effects than prevention curricula assume, and the naive messages conveyed in the programs serve to create cognitive dissonance in the minds of these youths. Gilham et al. (1997) argue that the results of research on these universal prevention programs is misleading because the programs have no effect on the large proportion of the population that is not likely to use drugs even without benefit of prevention programming, but they may have large effects on the smaller population that is at risk. They argue that the more substantial effects on potential users are diluted in studies that report findings for the entire population. For example, suppose that 98 percent of a population targeted for universal prevention programming will never use heroin, and that the

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us better (e.g., Durlak, 1995; Gottfredson, 1997). Programs that provide booster sessions after the initial activity produce more lasting effects than those that do not. These conclusions are based largely on a handful of studies that have compared effects of an instructional program with and without a booster. Botvin et al. (1984b), for example, show that the effects of Life Skills Training (the peer-led version) on self-reports of marijuana use in the past month taken 16 months after the initial pretest are not statistically significantly different from zero for those students in the condition without the booster, but when additional lessons are provided in the following school year to reinforce the initial lessons, effects at 16 months after the pretest are statistically significant and more than doubled in magnitude. However, others have demonstrated both short-term (Eggert et al., 1994) and long-term (e.g., Lochman, 1992) positive effects of one-shot interventions of approximately the same duration as Botvin’s initial program. Clearly, booster sessions are not a necessary ingredient of successful prevention, but their timing appears to be important. For example, research may discover that the total dosage of prevention messages can be traded off against the timing of the messages. Brief messages delivered closer in time to the situation in which an opportunity to use drugs is likely to arise, or small doses delivered continually over the life span, may be more effective than long messages delivered within a short time frame, as is most often the case in drug prevention classes as they are offered today. Mass media campaigns—television and radio advertisements, billboards, and posters—offer this potential advantage over classroom-based messages. More research is needed to sort out these potential trade-offs between timing and dose. Reviews have also concluded that the role of the deliverer is important. Hansen (1992) suggested that the training and background of the leader and the fidelity of presentation may be more important than the content of the message. Tobler compared programs delivered by different types of leaders: mental health professionals and counselors produced the largest effects, followed by peers; teachers produced the smallest effects. Tobler (1992:20–21) concluded that the leader must be someone who is “competent in group process, who can enhance the interactional process and simultaneously focus and direct the group. Successful leaders have the ability to act as guides, as opposed to being dominant. They are able to tolerate ambivalence, and know when to remain silent to facilitate true dialogue. They are able to empower adolescents to make conscientious decisions and to encourage freedom of choice and individual self determination.” Undoubtedly, the content of the message and the characteristics of the leader interact to produce more or less effective programs. Perhaps the provision of accurate information about the consequences of use by a

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us capable leader with the characteristics described by Tobler would be just as or more effective as a resistance skills training course taught by a teacher. Timing, duration, and the characteristics of the deliverer are potentially important moderator variables that could explain the wide range of effects observed across studies of prevention activities that are otherwise similar. But at present, we can only guess about which activities and what about each activity is critical to its success. The knowledge base for choosing among the multitude of prevention options is severely limited. Each of the potential moderator variables must be systematically varied in rigorous prevention trials. Needed Research Much remains to be learned about the potential of prevention activities for reducing illegal drug use. The committee identified five major areas in which answers from additional research would bridge this knowledge gap. Research is needed to examine Which of the noninstructional modalities are effective for reducing drug use. Whether prevention activities affect the subsequent drug use of different user groups differently. To what extent do prevention messages spread to individuals and groups not initially targeted, and can this “diffusion effect” be harnessed to reduce drug use in high risk peer groupings? Whether prevention activities affect the quantity, frequency or problems associated with use of nongateway substances. What prevention content is most effective, with which groups. How the timing, duration, and characteristics of the deliverer condition the effects of prevention programs. Does the effectiveness of prevention effects vary relative to the timing of drug epidemics? Are there important trade-offs between total dosage delivered and timing of delivery of prevention messages? Table 7.2 shows the areas that must be studied for each prevention modality in order to fill in gaps in understanding of the potential of prevention. Most is known about the ideal content of instructional programs, but in the committee’s judgment, more research is needed even in that cell. Once these gaps are filled, the next step will be to explore how effects can be enhanced through combinations of the most effective modalities. A number of studies have combined several modalities (e.g., Battistich et al.,

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us TABLE 7.2 Gaps in Knowledge about Prevention Effectiveness Modality Target Population Outcomes Affected Content Characteristics of Deliverer Duration Timing Mass Media Campaigns X X X X X X Community Organizing/Coalitions X X X X X X Family Training, Counseling, or Case Management X X X X X X Instruction X X X X X X Behavior Modification and Cognitive/Behavioral Strategies X X X X X X Other Counseling, Social Work, Psychological, or Therapeutic Strategies X X X X X X Tutoring, Mentoring, and other Individual-Attention Strategies X X X X X X Recreational, Enrichment, and Leisure Activities X X X X X X School/Discipline Management   X       X Establishment of Norms for Behavior X X X X X X Classroom Management   X       X Regrouping Students X X     X X Exclusion of Intruders and Contraband   X       X Manipulation of School Composition X X     X X Note—“X” indicates areas in which additional research is needed.

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us 1996; Gottfredson, 1986; Johnson et al., 1990; MacKinnon et al., 1991; Pentz et al., 1990; Pentz et al., 1989; Gottfredson et al., 1996; Skroban et al., 1999). Some of these attempts have been successful, and some have not. The less successful ones have suffered from implementation problems that may have been related to the multimodal nature of the program (e.g., Skroban et al., 1999). These individual studies have not resulted in an accumulation of knowledge about the conditions under which multimodal programs can work and the modes that can and cannot easily be combined. This line of inquiry will have to be carefully designed to control for conditions that may bear on the effectiveness of the activity. Research should also test the interactive effects of the different elements. That is, combinations may increase the magnitude of effects through the additive effects of each component, but they may also have a multiplicative effect, so that certain strategies are more or less effective in combination with another than they are by themselves. For example, a drug prevention curriculum with a “no use” message may be counterproductive when delivered in a school environment in which norms favor use, or one in which the rules related to the possession of substances are lax or inconsistently applied. Only through research on the additive and multiplicative effects of different strategies can knowledge accumulate that will allow communities to develop portfolios of effective prevention strategies. CONCLUSIONS AND RECOMMENDATIONS A wide spectrum of plausible approaches to the prevention of substance use exist in both theory and practice. The effectiveness of most of these approaches for reducing substance use is unknown because the research evidence is nonexistent or inconclusive. Some of the approaches for which we have no evidence of effectiveness include many popular control strategies, such as zero-tolerance policies, the use of security measures such as locker searches, and the presence of police in schools, as well as more innovative approaches that draw on advances in toxicology, molecular biology, genetics, and clinical medicine (e.g., parents’ attempts to protect their children via increased use of home test kits to detect drug use, or active immunization of high-risk children with vaccine analogues). Research is needed on a wider array of prevention activities than has been studied to date. With respect to the prevention approaches that have been studied, the committee makes the following observations: Some prevention approaches are effective at delaying the initiation or reducing the frequency of tobacco, alcohol, and marijuana use. The

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us magnitude of these effects are generally small, but the efforts that are generally more effective than other programs are implemented with high fidelity, focus on improving the capability of social organizations such as schools for managing themselves more effectively and communicating clear messages about expected behavior, and use cognitive-behavioral methods to teach skills that youths need to make competent decisions in social situations. Considerable heterogeneity in effectiveness is found from study to study in each broad category of prevention activity. Although hints can be gleaned from the literature about factors that might differentiate the more effective from the less effective activities—such as duration, timing, and characteristics of the deliverer—existing research is not capable of isolating these moderating factors. Some of the most widely promulgated classroom-based drug prevention programs—such as D.A.R.E. in the 1980s and early 1990s—have been found to have little impact on student drug use. Large amounts of public funds have been and continue to be allocated to prevention activities whose effectiveness is unknown or known to be limited. It is not clear that preventing or reducing the use of gateway substances translates into reduced risk of use of cocaine or other illegal drugs. With only a few exceptions, the long-term effects of prevention programs are unknown. Some evidence suggests that universal approaches to prevention of drug use have differential effects on different groups, so that students who have already initiated drug use before exposure to the program may escalate it following the program. In light of these observations, the committee recommends a major increase in current efforts to evaluate drug prevention efforts. Further research is needed to better understand (1) effects of the entire spectrum of plausible approaches to prevention proposed or in use, rather than those that are most easily evaluated; (2) effects of drug prevention programs implemented under conditions of normal practice, outside the boundaries of the initial tightly controlled experimental tests of program efficacy under optimal conditions; (3) effects of different combinations of prevention programs, for example, how they complement each other or detract from one another when used in combination, as they most often are; and (4) the extent to which experimentally induced delays in tobacco, alcohol, and marijuana use yield reductions in later involvement with cocaine and other illegal drugs specifically, and long-term effects of prevention programming more generally. Until the results of such research are available, policy makers have only a weak information base on which to base policy decisions and are

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Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us likely to continue to fund and operate ineffective prevention programs and programs of unknown effectiveness. REFERENCES Anthony, J.C., and K.R.Petronis 1991 Epidemiologic Evidence on Suspected Associations Between Cocaine Use and Psychiatric Disturbances. NIDA Research Monograph 110:71–94. Battistich, V., E.Schaps, M.Watson, and D.Solomon 1996 Prevention effects of the child development project: Early findings from ongoing multisite demonstration trial. Journal of Adolescent Research 11(1):12–35. Beck, J. 1998 100 years of “just say no” versus “just say know” Reevaluating drug education goals for the coming century. Evaluation Review 22:15–45. Bell, R.M., P.L.Ellickson, and E.R.Harrison 1993 Do drug prevention effects persist into high school? How project ALERT did with ninth graders. Preventive Medicine 22:463–483. Botvin, G.J., S.Schinke, and M.A.Orlandi 1995 School-based health promotion: Substance abuse and sexual behavior. Applied and Preventive Psychology 4:167–184. Botvin, G.J. 1990 Substance abuse prevention: Theory, practice, and effectiveness. Pp. 461–519 in M.Tonry and J.Q.Wilson, eds., Drugs and Crime. Chicago: University of Chicago Press. Botvin, G.J., E.Baker, E.M.Botvin, A.D.Filazzola, and R.B.Millman 1984a Prevention of alcohol misuse through the development of personal and social competence: A pilot study. Journal of Studies on Alcohol 45:550–552. Botvin, G.J., E.Baker, N.L.Renick, A.D.Filazzola, and E.M.Botvin 1984b A cognitive-behavioral approach to substance abuse prevention. Addictive Behaviors 9:137–147. Brown, J.H., and I.G.G.Kreft 1998 Zero effects of drug prevention programs: Issues and solutions. Evaluation Review 22(1):3–14. Brunswick, A.F., and J.M.Boyle 1979 Patterns of drug involvement: Developmental and secular influences on age at initiation. Youth and Society 2:139–162. Caulkins, J.P., C.P.Rydell, S.S.Everingham, J.Chiesa, and S.Bushway 1999 An Ounce of Prevention, A Pound of Uncertainty: The Cost Effectiveness of School-Based Drug Prevention Programs. Santa Monica, CA: RAND. Center for Substance Abuse Prevention 1999 Here’s Proof Prevention Works. DHHS Publication No. (SMA)99–3300. Rockville, MD: U.S. Department of Health and Human Services. Comer, J.P. 1985 The Yale-New Haven primary prevention project: A follow-up study. Journal of the American Academy of Child Psychiatry 24(2):54–160.

OCR for page 208
Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us Cook, T.D., H.D.Hunt, and R.F.Murphy 1998 Comer’s School Development Program in Chicago: A Theory-Based Evaluation. Chicago: Institute for Policy Research, Northwestern University. Cook, T.D., and D.T.Campbell 1979 Quasi-Experimentation: Design and Analysis Issues for Field Settings. Chicago: Rand McNally. Dishion, T.J., and D.W.Andrews 1994 Preventing escalation in problem behaviors with high risk young adolescents: Immediate and one year outcomes. Journal of Consulting and Clinical Psychology 63(4):538–548. Dolan, L.J., S.G.Kellam, C.H.Brown, L.Werthamer-Larsson, G.W.Rebok, L.S.Mayer, J. Laudolff , J.S.Turkkan, C.Ford, and L.Wheeler 1993 The short-term impact of two classroom-based preventive interventions on aggressive and shy behaviors and poor achievement. Journal of Applied Developmental Psychology 14:317–345. Dryfoos, J.G. 1990 Adolescents at Risk: Prevalence and Prevention. New York: Oxford University Press. Durlak, J.A. 1995 School-Based Prevention Programs for Children and Adolescents. Thousand Oaks, CA: Sage. Eggert, L.L., E.A.Thompson, J.R.Herting, L.J.Nicholas, and B.G.Dicker 1994 Preventing adolescent drug abuse and high school dropout through an intensive school-based social network development program. American Journal of Health Promotion 8(3):202–215. Ellickson, P.L., R.M.Bell, and K.McGuigan 1993 Preventing adolescent drug use: Long-term results of a junior high program. American Journal of Public Health 83(6):856–861. Ellickson, P.L., and R.M.Bell 1990 Drug prevention in junior high: A multi-site longitudinal test. Science 247:1 299–1305. Ennett, S.T., D.P.Rosenbaum, R.L.Flewelling, G.S.Bieler, C.L.Ringwalt, and S.L.Bailey 1994a Long-term evaluation of drug abuse resistance education. Addictive Behaviors 19(2):113–125. Ennett, S.T., N.S.Tobler, C.L.Ringwalt, and R.L.Flewelling 1994b How effective is drug abuse resistance education? A meta-analysis of project D.A.R.E. outcome evaluations. American Journal of Public Health 84:1394–1401. Gilchrist, L.D. 1991 Defining the intervention and the target population. In C.G.Leukefeld and W.J. Bukoski, eds. Drug Abuse Prevention Intervention Research: Methodological Issues. National Institute on Drug Abuse Research Monograph No. 107. DHHS Publication No. (ADM) 91–1761. Washington, DC: U.S. Department of Health and Human Services. Gilham, S.A., W.L.Lucas, and D.Sivewright 1997 The impact of drug education and prevention programs: Disparity between impressionistic and empirical assessments. Evaluation Review 21(5):589–613. Gorman, D.M. 1996 The irrelevance of evidence in the development of school-based drug prevention policy, 1986–1996. Evaluation Review 22(1):118–146.

OCR for page 208
Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us 1995 Are school-based resistance skills training programs effective in preventing alcohol misuse? Journal of Alcohol and Drug Education 41:74–98. Gottfredson, D.C. 2001 Schooling and Delinquency. New York: Cambridge University Press. 1997 School-based crime prevention. In L.W.Sherman, D.C.Gottfredson, D. MacKenzie, J.Eck, P.Reuter, and S.Bushway, eds., Preventing Crime: What Works, What Doesn’t, What’s Promising: A Report to the United States Congress. Washington, DC: U.S. Department of Justice, Office of Justice Programs. 1986 An empirical test of school-based environmental and individual interventions to reduce the risk of delinquent behavior. Criminology 24(4):705–731. Gottfredson, D.C., G.D.Gottfredson, and S.Skroban 1996 A multimodel school-based prevention demonstration. Journal of Adolescent Research 11(1):97–115. Gottfredson, D.C., D.B.Wilson, and S.S.Najaka forthcoming School-based crime prevention. In D.P.Farrington, L.W.Sherman, and B.Welsh, eds., Evidence-Based Crime Prevention. United Kingdom: Harwood Academic Publishers. Gottfredson, G.D., D.C.Gottfredson, ? Czeh, D.Cantor, S.Crosse, and I.Hantman 2000 A National Study of Delinquency Prevention in Schools. Ellicott City, MD.: Gottfredson Associates, Inc. Hansen, W.B., and P.M.O’Malley 1996 Drug use. Pp. 161–192 in R.J.DiClemente, W.B.Hansen, and L.E.Ponton, eds., Handbook of Adolescent Health Risk Behavior. New York: Plenum Press. Hansen, W.B. 1992 School-based substance abuse prevention: A review of the state of the art in curriculum: 1980–1990. Health Education Research 7:403–430. Hansen, W.B., and J.W.Graham 1991 Preventing alcohol, marijuana, and cigarette use among adolescents: Peer pressure resistance training versus establishing conservative norms. Preventive Medicine 20:414–430. Hansen, W.B., C.A.Johnson, B.R.Flay, J.W.Graham, and J.Sobel 1988 Affective and social influences approaches to the prevention of multiple substance abuse among seventh grade students: Results from Project SMART. Preventive Medicine 17:135–154. Hawkins, J.D., M.W.Arthur, and R.F.Catalano 1995 Preventing substance abuse. Pp. 343–427 in M.Tonry and D.Farrington, eds., Building a Safer Society: Strategic Approaches to Crime Prevention. Chicago: University of Chicago Press. Hawkins, J.D., R.F.Catalano, D.M.Morrison, J.O’Donnell, R.D.Abbott, and L.E.Day 1992 The Seattle Social Developmental Project: Effects of the first four years on protective factors and problem behaviors. Pp. 141–161 in J.McCord and R.E.Tremblay, eds., Preventing Antisocial Behavior: Interventions from Birth Through Adolescence. New York: Guilford Press. Institute of Medicine 1994 Reducing Risks for Mental Disorders: Frontiers for Preventive Intervention Research. Washington, DC: National Academy Press.

OCR for page 208
Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us Johnson, C.A., M.A.Pentz, M.D.Weber, J.H.Dwyer, N.Baer, D.P.MacKinnon, W.B.Hansen, and B.R.Flay 1990 Relative effectiveness of comprehensive community programming for drug abuse prevention with high-risk and low-risk adolescents. Journal of Consulting and Clinical Psychology 58(4):447–456. Kandel, D.B. 1982 Epidemiological and psychosocial perspectives on adolescent drug use. Journal of the American Academy of Child Psychiatry 21(4):328–347. 1975 Stages in adolescent involvement in drug use. Science 190:912–914. Kandel, D., and R.Faust 1975 Sequences and stages in patterns of adolescent drug use. Archives of General Psychiatry 32:923–932. Kellam, S.G., and J.C.Anthony 1998 Targeting early antecedents to prevent tobacco smoking: Findings from an epidemiologically based randomized field trial. American Journal of Public Health 88: 1490–1495. Kellam, S.G., G.W.Rebok, N.Ialongo, and L.S.Mayer 1994 The course and malleability of aggressive behavior from early first grade into middle school: Results of a developmental epidemiologically-based preventive trial. Journal of Child Psychology and Psychiatry 35:259–281. Kumpfer, K.L., V.Molraard, and R.Spoth 1996 The “Strengthening Families Program” for the prevention of delinquency and drug use. In R.Peters and R.McMahon, eds., Preventing Childhood Disorders, Substance Abuse, and Delinquency. Thousand Oaks, CA: Sage Publications. Lipsey, M.W., and D.B.Wilson 1993 The efficacy of psychological, educational, and behavioral treatment: Confirmation from meta-analysis. American Psychologist 48(2):1181–1209. Lipsey, M.W. 1992 Juvenile delinquency treatment: A meta-analytic inquiry into the variability of effects. Pp. 83–127 in T.D.Cook, H.Cooper, D.S.Cordray, H.Hartmann, L.V. Hedges, R.J.Light, T.A.Louis, and F.Mosteller, eds., Meta-Analysis for Explanation. New York: Russell Sage Foundation. Lochman, J.E. 1992 Cognitive-behavioral intervention with aggressive boys: Three-year follow-up and preventive effects. Journal of Consulting and Clinical Psychology 60(3):426–432. MacCoun, R. 1998 In what sense (if any) is marijuana a gateway drug? Drug Policy Analysis Bulletin 4:5–8. MacCoun, R., and P.Reuter 1997 Interpreting Dutch cannabis policy: Reasoning by analogy in the legalization debate. Science 278:47–52. MacKinnon, D.P., C.A.Johnson, M.A.Pentz, J.H.Dwyer, W.B.Hansen, B.R.Flay, and E.Y. Wang 1991 Mediating mechanisms in a school-based drug prevention program: First-year effects of the Midwestern prevention project. Health Psychology 10(3):164–172. Moffitt, T.E. 1993 Adolescence-limited and life-course persistent antisocial behavior: A developmental taxonomy. Psychological Review 100:674–701.

OCR for page 208
Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us National Research Council 1993 Preventing Drug Abuse: What Do We Know? Committee on Substance Abuse Prevention. D.R.Gerstein and L.W.Green, eds. Washington, DC.: National Academy Press. Norman, E., and S.Turner 1993 Adolescent substance abuse prevention programs: Theories, models, and research in the encouraging 80’s. Journal of Primary Prevention 14:3–20. O’Donnell, J.A., and R.R.Clayton 1979 Determinants of early marijuana use. Pp. 63–110 in G.M.Beschner and A.S.Friedman, eds., Youth Drug Abuse: Problems, Issues, and Treatment. Lexington, MA: Lexington Books. Pentz, M.A., E.A.Trebow, W.B.Hansen, D.P.MacKinnon, J.H.Dwyer, C.A.Johnson, B.R. Flay, S.Daniels, and C.Cormack 1990 Effects of program implementation on adolescent drug use behavior: The Midwestern prevention project (MPP). Evaluation Review 14(3):264–289. Pentz, M.A., J.H.Dwyer, D.P.MacKinnon, B.R.Flay, W.B.Hansen, E.Y.I.Wang, and C.A. Johnson 1989 A multicommunity trial for primary prevention of adolescent drug abuse: Effects on drug use prevalence . Journal of the American Medical Association 261(22): 3259–3266. Perry, C.L., C.L.Williams, S.Veblen-Mortenson, T.L.Toomey, K.A.Komro, P.S.Anstine, P.G.McGovern, J.R.Finnegan, J.L.Forster, A.C.Wagenaar, and M.Wolfson 1996 Project northland: Outcomes of a communitywide alcohol use prevention program during early adolescence. American Journal of Public Health 86(7):956–965. Robins, L.N., and T.R.Przybeck 1985 Age of onset of drug use as a factor in drug and other disorders. In C.L.Jones and R.J.Battjes, eds., Etiology of Drug Abuse: Implications for Prevention. National Institute on Drug Abuse Research Monograph No. 56. Washington, DC: U.S. Department of Health and Human Services. Rosenthal, R., and D.B.Rubin 1982 A simple, general purpose display of magnitude of experimental effect. Journal of Educational Psychology 74(2):166–169. Skroban, S.B., D.C.Gottfredson, and G.D.Gottfredson 1999 A school-based social competency promotion demonstration. Evaluation Review 23(1):3–27. Tobler, N.S., and H.H.Stratton 1997 Effectiveness of school-based drug prevention programs: A meta-analysis of the research. Journal of Primary Prevention 18(1):71–128. Tobler, N.S. 1992 Drug prevention programs can work: Research findings. Journal of Addictive Diseases 11(3):1–28. 1986 Meta-analysis of 143 adolescent drug prevention programs: Quantitative outcome results of program participants compared to a control or comparison group. Journal of Drug Issues 16(4):537–567. U.S. Department of Education 1999 Guidelines and Materials for Submitting Safe, Disciplined, and Drug-Free Schools Programs for Review. Washington, DC: U.S. Department of Education.

OCR for page 208
Informing America’s Policy on Illegal Drugs: What We Don’t Know Keeps Hurting Us Westat, Inc. 1999 Evaluation of the National Youth Anti-Drug Media Campaign: Historical Trends in Drug Use and Design of the Phase III Evaluation. Report prepared for the National Institute on Drug Abuse, http:/www.Whitehousedrugpolic.ov/pdf/nida/pdf. Yamaguchi, K., and D.B.Kandel 1984 Patterns of drug use from adolescence to young adulthood: III. Predictors of progression. American Journal of Public Health 74(7):673–681.