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National Conference on Drug Abuse Prevention Research:
Presentations, Papers, and Recommendations

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Plenary Session

Risk and Protective Factor Models in Adolescent Drug Use: Putting Them to Work for Prevention

Robert J. Pandina, Ph.D.
Professor and Director
Center of Alcohol Studies
Rutgers University


National Conference on Drug Abuse Prevention Research

Introduction

The importance of applying findings from risk factor research in the public health prevention sphere became apparent as a result of the success of the groundbreaking and landmark Framingham Heart Study launched in the 1960s (Kannel and Schatzkin, 1983). That extensive program sought to aid understanding of what led some people to be more likely than others to suffer cardiovascular disease and to apply that understanding in the design of programs aimed at reducing susceptibility to various forms of cardiovascular disease. During the same timeframe, researchers in the mental health field also demonstrated the importance of factors that appeared to protect certain at-risk individuals from the development of predicted poor or negative outcomes. Those individuals were considered to be resistant or "resilient" (Rutter 1985; Garmezy and Masten 1994, pp. 191-208; Compas et al. 1995, pp. 265-293).

Risk factors are defined as ". . . those characteristics, variables, or hazards that, if present for a given individual, make it more likely that this individual, rather than someone selected at random from the general population, will develop a disorder" (Mrazek and Haggerty 1994, p. 127). Protective factors are those that, if present, make it less likely that such a disorder will develop. Resilience is based in the idea that some individuals who are exposed to risk factors (and hence should be more likely to develop a disorder) do not experience the disorder. Therefore, these otherwise susceptible individuals appear to be resistant to the effects of risk exposure; that is, they are resilient. Some investigators suggest that such resilience results from factors that buffer the at-risk individual from the adverse effects of exposure (Anthony and Cohler 1987).

Risk and protective factors encompass several meanings or levels of explanations ranging from simple statistical associations with a disorder (for example, heart disease, mental dysfunctions, drug dependence), to a predisposition for development of (or resistance to) the disorder, to the actual mechanisms responsible for causing or preventing a disorder. Hence, risk and protective factors can be markers (surface indicators), modifiers (augmenting or amplifying influences), or mediators (primary "causal" mechanisms) of drug use susceptibility and related outcomes and phenomena.

These categories of factors represent varying levels of scientific certainty or specificity about the nature of the influence that a given factor can have in directly producing a risk or protective effect on a particular drug use outcome or status. For example, knowing that an individual is a child of an alcoholic provides a surface indication (a marker) that a person is at heightened risk for negative alcohol use outcomes (for example, abuse and dependence). However, that marker designation does not specify how the risk is generated. For example, the risk could be generated through genetic loading resulting in increased receptor sensitivity to alcohol. Or the risk could be through a child's exposure to parental drinking models in the home environment. In this example, "familial history" can act as a marker, modifier, or mechanism. In fact, one of the important scientific challenges in the drug abuse field is sorting out the nature and strength of associations between factors known to be related to use statuses and outcomes and the manner in which factors exert their influence (Rothman 1986; Baron and Kenny 1986; Rogosch et al. 1990).


Risk and Protective Factors in Substance Abuse Research

Concepts related to risk and protective factors have been useful and effective in the design of programs to identify, characterize, and intervene in a number of serious health problems, including cardiovascular disease, cancer, and now drug abuse. Serious efforts at extending risk factor models to the drug abuse arena began in the early 1980s.

Bry and colleagues (Bry 1983; Bry and Krinsley 1990; Bry et al. 1982, 1988, p. 301) were among the first to demonstrate the importance and applicability of risk factor models in predicting drug use susceptibility. Their work was extended and refined by the work of Newcomb and colleagues (Newcomb 1995, pp. 7-37; Newcomb and Felix-Ortiz 1992; Scheier and Newcomb 1991; Newcomb et al. 1986). Among the important findings of these researchers was that the number of risk factors appears directly related to intensity of drug use, stage in drug use, likelihood of escalation to more serious forms of drug use, risk of negative consequences, and other fundamental drug use phenomena. Hence, it appeared that by identifying individuals with higher levels of exposure to greater numbers of risk factors, it was possible to identify susceptible individuals. Research to date seems to support these general conclusions irrespective of age, gender, or ethnic considerations (see, for example, Brook, Cohen, et al. 1992, pp. 359-389; Brook, Hamburg, et al. 1992; Brook, Whiteman, et al. 1992; Brook et al. 1994; Brook et al., in press).

Work by Newcomb illustrates the core principle of increasing the risk for use intensity (a basic drug use marker) for tobacco, alcohol, and cocaine. As the number of risk factors rises, the likelihood of heavier use increases. The rise in risk occurs in relationship to the number of factors, irrespective of their nature. In other words, different patterns of factors can lead to the same level of risk. A similar result has been demonstrated for protective factors; that is, the larger the number of protective factors, the less likely the individual is to engage in intensive drug use. Specific combinations of factors seem to be less important than total number of factors.

In early work, risk factors were drawn from a limited range of biological, psychological and behavioral, and social and environmental variables thought to be related to drug use. More recent efforts (for example, Newcomb 1995; Pandina et al. 1992; Hancock 1996) have dramatically increased the range of risk factors to be included and have begun an assessment of the interplay between risk and protective factors and their relative contribution to important variations in drug use patterns and outcomes. A number of other key concepts emerge consist-ently across a wide range of studies and relate to the general manner in which risk and protective factors behave in regulating drug abuse susceptibility.

The following summarizes the general characteristics of risk and protective factors:

  • They are cumulative or synergistic.

  • They differ qualitatively and quantitatively.

  • They vary in importance across individuals or groups.

  • They vary in influence at different times during the life cycle.

  • They vary in significance for the emergence of drug use stages and outcomes.

  • They are subject to change and can be significantly reduced or induced.

The central concept is that risk and protective factors are cumulative in impact. Thus, the greater the number of risk factors, the higher the susceptibility. Conversely, the accumulation of protective factors appears to reduce risk.

How risk and protective factors act to balance each other is yet to be determined. There is some preliminary information (Hancock 1996) that risk and protective factors may behave somewhat differently in influencing susceptibility. For example, protective factors appear to be more important for more long-term use patterns and cumulative outcomes, while risk factors are more important for short-term, more immediate use patterns and outcomes.

While some risk and protective factors appear to be at opposite ends of the same continuum (that is, high vs. low self-efficacy), therefore displaying an apparently simple bipolar factor structure, other constructs may operate only as risk or protective factors. Even those constructs that appear more straightforward (such as self-efficacy), may operate in different ways as risk or protective factors. Current research programs continue to enhance our understanding of the quantitative and qualitative characteristics of risk and protection (Labouvie et al. 1991; Scheier and Newcomb 1991; Newcomb and Felix-Ortiz 1992; Newcomb 1995).

No single factor from any domain - biological, behavioral, or environmental - appears to be clearly and consistently identified as the single key factor, either risk or protective, that regulates risk susceptibility. Varying factor patterns may be more influential for some individuals or groups displaying similar characteristics. In a similar vein, some clusters of factors may be more influential in producing or limiting susceptibility for different developmental phases of the life cycle. Further, various stages and phases in the continuum of drug use behaviors and outcomes may be influenced differentially by distinctive factor constellations. Thus, factors significant for earlier stages of use initiation (such as "trying" marijuana) may differ qualitatively and quantitatively from those related to the transition to dependence (for example, heroin addiction or alcoholism). However, research to date indicates that many of these risk factors, singly and in combination, are related also to other dysfunctional outcomes, such as delinquency, violence, or serious mental disorders. In fact, it is not uncommon for drug-abusing individuals to have overlapping problems (cf. Compas et al. 1995).

Most significantly, research has demonstrated that many factors, though not necessarily all, can and do change across time in many individuals. Thus, the fact that many risk and protective factors appear to be malleable suggests that these are sensitive to natural events and may be influenced by extraordinary events such as prevention interventions. It is this last important consideration that forms the basis of many of the prototypic prevention programs described by the prevention scientists in this volume and other publications (Botvin et al. 1995; Brook et al. 1989; Dishion et al., in press; Eggert et al. 1990; Kumpfer et al. 1996; Donaldson et al. 1994; Hawkins et al. 1992; Pentz et al. 1989).

The results of the work on the earliest models raised the possibility of developing a practical approach to identifying at-risk individuals (or populations of individuals at risk). The research also suggested that through inspection of the risk profiles, it might be possible to develop intervention programs aimed at decreasing levels of risk associated with drug use in much the same manner as those earlier programs aimed at cardiovascular disease. The most recent research continues to support those earliest findings and emphasizes the relationship, albeit complex, between risk and protective profiles, drug use phenomena, and prevention approaches (Tobler 1992).

Furthermore, the most recent work linking risk and protective factors to drug use phenomena suggests a higher level of complexity than the initial risk factor models anticipated. Yet, the basic principles of the models have been retained. The earliest models strongly suggested the appropriateness of linking prevention efforts to our understanding of the way risk and protective factors operated to influence susceptibility to drug use. The more refined models emphasize the need to base prevention programs on an understanding of risk and protective factors, including how they operate in different individuals at various stages in the life cycle, differential effects on drug use staging, and the extent to which they may be modified by specific intervention approaches. The research community is actively investiga-ting a series of fundamental issues that, when resolved, could have major significance for prevention efforts. These include the relative importance of differential factor profiles for use onset and progression to more serious stages and problematic outcomes; the differential impact of factors operating at varying life cycle phases (for example, childhood, adolescence, young adulthood, mature adulthood) (Kandel et al. 1992; Jessor 1993); and the degree to which factors (including genetic mechanisms) are sensitive to modification.


Use-Behavior Continuum

The types of use behaviors and related outcomes that drug abuse researchers are concerned with when attempting to determine degree of risk and protection, particularly for young people, form the ultimate targets for prevention science programming. Characterization and estimation of harm potential is a difficult and complex task. In fact, such determinations represent an important research effort in itself (Gable 1993). The scaling of "harm" blends together such concepts as risks resulting from the chemical composition of the substances; damage potential to biological targets; mechanisms of action, potency, toxicity, nature, and extent of consequences; and other such parameters. Consideration must be given also to balancing exposure rates, use levels, and outcomes for various substances. Shifts in the ranking may be argued on the basis of weight given to specific factors in the harm- potential algorithm. Programs for youth are aimed primarily at blocking, reducing, or limiting involvement or intensity of drug use.

The range of use outcomes, statuses, and conditions that prevention programs attempt to induce, prevent, or eliminate is summarized as follows:

  • Non-use

  • Use

  • Misuse

  • Abuse/abuser

  • Problem use/user

  • Dependence/dependent user

  • Addiction/addict

  • Recovery/recovering addict

  • First- and second-degree diseases.

The listing represents a rough qualitative continuum ranging from less to more problematic outcomes, which can be obtained for all substances (Clayton 1992). The majority of youth programs focus on earlier phases of the continuum targeting induction of non-use, delay of use initiation, and elimination of use, misuse, and abuse. This is not to say that viable prevention programs should ignore other outcomes or statuses; some effective campaigns focus on limited yet well-specified behaviors, such as driving under the influence. However, many of the more serious conditions, such as addiction, are often remote targets of youth-oriented programs.

Terms such as "use," "abuse," and "addiction," are global descriptors meant to capture quantitative and qualitative dimensions of the use- behavior spectrum. Use behaviors and states possess dynamic qualities that involve processes underlying various developmental sequencing of stages ("acquisition" or "maintenance") and within stage phases ("experimentation" or "dependence") of the use spectrum.

The following schema identifies fundamental developmental stages and their sequences:

  1. Acquisition

    • Priming
    • Initiation
    • Experimentation

  2. Maintenance

    • Habit formation
    • Dependence
    • Obsessive-compulsive use

  3. Control

    • Problem awareness
    • Interruption/suspension
    • Cessation.

The stages, phases, and sequencing are applicable to substances typically targeted in youth-oriented prevention programs. Many of these programs focus on the acquisition and early maintenance features of the developmental use cycle. While virtually all substances share similar developmental features, there are developmental features to sequencing of exposure to different substance classes. Kandel and colleagues (Kandel 1975, 1980; Yamaguchi and Kandel 1984; Kandel et al. 1992) were among the first to demonstrate sequential ordering of substance use onset. For example, onset of alcohol and cigarette use precedes onset of marijuana use, which in turn precedes initiation of other illicit drug use. One consequence of these developmental aspects is that risk of exposure to various drugs is likely to occur over a relatively lengthy timespan ranging from early adolescence through early adulthood.

Note that progression across substance classes is not inevitable. However, when it does occur, progression appears to occur in a stepwise fashion for many users. Entrance to a particular stage or phase of use and initiation of a particular substance does not mean that an individual cannot "regress" to an earlier stage within a particular drug class or to an earlier position in the sequence between substance classes (Labouvie et al., in press).

The target use behaviors forming the focus for prevention scientists are somewhat more complex than they might appear. Many youth- oriented prevention programs focus on a particular location in the "environmental space" of the substance-use spectrum bounded by the earliest phases of use development (such as priming and initiation), primary "position" in the substance-class spectrum (such as alcohol and tobacco), and more global qualitative states (such as use or abuse). Even within these limits, the targets for intervention are relatively complex.


Classes of Risk and Protective Factors

Risk and protective factors can be arranged in three domains or classes, which, in turn, can be divided into relevant subclasses as follows:

  1. Biological

    • Genetic
    • Constitutional

  2. Psychological and Behavioral

    • Internal processes
    • Behavioral action profiles and repertoire
    • Interpersonal interactional styles

  3. Social and Environmental

    • Familial interactions
    • Peer interactions
    • Institutional interactions
    • Social/institutional structures.

Biological factors can be characterized as genetic (related to a profile of inherited or gene- transcripted features) or constitutional (biological tissue changes induced by a variety of factors ranging from stress to drug exposure) (Wise 1996; Piazza and LeMoal 1996). Psychological and behavioral class variables include those indicative of internal processes (such as thoughts, feelings), behavior-action profiles and repertoires (drug-seeking, general deviance), and interpersonal interactional styles. Social and environmental subclasses include family, peer, and institutional relationships. Class and domain factors include both structural and dynamic (that is, process-oriented) properties. Factors within a given domain may be classified as simple surface markers or as factors playing a specific role in moderating or mediating use outcomes. One of the important challenges to the scientific community is unraveling the manner in which factors singly or in combination operate to influence use behavior and outcomes.

This general structure is consistent with a living systems view of human drug-using behavior that seeks to explain drug use in terms of the interaction of biological, psychobehavioral, and environmental processes (Miller 1978; Ford 1987). Major factors in each of the domains or compartments of the biopsychosocial model related to the substance-use continuum and related outcomes include the following:

  • Genetic profile

  • Sensory processing disturbances

  • Neurocognitive alterations

  • Personal history of affective disorders or impulse disorders

  • Family history of alcoholism or drug abuse

  • Family history of impulse disorders, such as conduct disorder or antisocial personality

  • Family history of affective disorders

  • Emotional disturbance such as depression or anxiety.

These factors do not represent an exhaustive list of all factors identified in the literature, nor do they represent a "consensus taxonomy" of all factors. Rather, they are a representative sample of the more accepted and documented factors in their most generic form. One of the most important and significant challenges that etiologists face is the development of a consensus taxonomy. The difficulty of the task is reflected in early and recent reviews of major theories of substance use etiology (Lettieri et al. 1980; Glantz and Pickens 1992; Hawkins et al. 1992; Petraitis et al. 1995).

Major biological risk and protective factors include the following variable domains: genetic profiles resulting in altered brain functioning and hence a predisposition to, or protection from, substance abuse propensity; sensory processing disturbances or stabilities; and neurocognitive alterations. The risk end of the continuum may be marked by family history of alcoholism, drug abuse, or related disorders, including affective disorders and emotional disturbances, presence of impulse disorders, and presence of neuropsychological dysfunction. The range spans more fixed or permanent, though more labile, characteristics of the individual.

The major behavioral/psychological risk and protective factors include the following:

  • Personality styles, such as sensation-seeking, novelty-seeking, harm avoidance, or reinforcement sensitivity

  • Emotional profile

  • Self-regulation style, such as coping repertoire

  • Behavioral competence

  • Self-efficacy/esteem

  • Positive and negative life events/experiences

  • Attitudes, values, beliefs regarding drug use.

These factors range from internal - more global and perhaps more stable and less malleable individual characteristics (such as personality profile) - to those more sensitive and reactive to external vectors (behavioral competence, values, beliefs). Factors more reactive to external forces may be viewed as more suitable potential targets for intervention.

Social/environmental risk and protection factors include these:

  • Structure/function of family supports

  • Parenting styles

  • Opportunities for development of basic competencies

  • Peer affiliations

  • Economic and social (including educational) opportunities

  • General social support structure

  • Availability of prosocial activities

  • Structures, including schools, communities, or workplaces

  • Strength and influence of the faith community

  • Social norms, attitudes, and beliefs related to drug use

  • Availability and projected attractiveness of drugs and drug use

  • Economic and social incentives of drug trafficking.

As in the case of the biogenic and psychobehavioral domains, factors span a range of complexity of organization. Factors may reflect the dynamic interactions of the individual with family and peer groups, with the more structured relationships between segments of the population variously characterized (for example, schoolchildren, dropouts, delinquents, underage drinkers), and with social institutions (for example, schools, law enforcement, regulatory agencies).


Summary and Conclusions

Risk and protective factors include biogenic, psychobehavioral, and socioenvironmental markers, modifiers, and mechanisms. These factors vary in importance as a reflection of individual or group differences. Further, risk and protective profiles may vary in significance for the emergence of different use stages or outcomes. Similarly, the magnitude of the impact of specific risk and protective profiles may fluctuate during the lifespan. It appears clear that individual factors may be cumulative or synergistic; that is, they may combine to magnify or offset the negative or positive influences on the development of drug use and related outcomes. Significant for the prevention scientist is the finding that many of the most salient factors are malleable and can be successfully reduced or induced through a variety of external interventions (Reiss and Price 1996). Equally important is the finding that some factors are relatively stable and may not yield readily to even intensive treatments.

A number of significant implications flow from the observations of etiological researchers working to understand the interplay of risk and protective factors. Intervention programs must [demonstrate understanding of] the nature of what they are attempting to prevent or promote. The design of intervention programs can profit substantially from consideration of the pattern of risk and protective factors within a given individual, target group, community, or social institution; and intervention strategies should be engineered on information derived from an understanding of the complex interaction and operation of these risk and protective factors.

Furthermore, intervention programs should seek to reduce immediate risks and promote more long-term protective factors in target groups or settings. The importance of particular risk and protective factors may change across groups, settings, and developmental periods of the lifespan. Hence, the general strategy for prevention efforts must encompass these facts. Research to date indicates the import of long-term commitment to intervention programs across childhood, adolescence, and adulthood. Consequently, "preventionists" need to integrate multicomponent, multistage programs at many different developmentally sensitive periods.

Research aimed at understanding risk and protective factors and their application to prevention efforts has to be intensified (Reiss and Price 1996; Coie et al. 1993; Muñoz et al. 1996). The better we are informed about more specific patterns of factors related to use stages and outcomes and the way they function separately and together, the more effectively and efficiently we can design and implement prevention programs. Information derived from research has provided a broad platform from which present prevention efforts have sprung. Intensifying our research efforts will provide an informed science upon which these pioneering and prototypic prevention efforts can advance.


References

Anthony, E.J., and Cohler, B.J., eds. The Invulnerable Child. New York: Guilford Press, 1987.

Baron, R.M., and Kenny, D.A. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J Pers Soc Psychol 51(6):1173-1182, 1986.

Botvin, G.J.; Baker, E.; Dusenbury, L.D.; Botvin, E.M.; and Díaz, T. Long-term followup results of a randomized drug abuse prevention trial in a white middle-class population. JAMA 273(14):1106-1112, 1995.

Brook, J.; Balka, E.B.; Abernathy, T.; and Hamburg, B.A. Sequences of sexual behavior in African-American and Puerto Rican adolescents. J Genet Psychol 155(1):5-13, 1994.

Brook, J.S.; Cohen, P.; Whiteman, M.; and Gordon, A.S. Psychosocial risk factors in the transition from moderate to heavy use or abuse of drugs. In: Glantz, M.D., and Pickens, R., eds. Vulnerability to Drug Abuse. Washington, DC: American Psychological Association, 1992.

Brook, J.S.; Hamburg, B.A.; Balka, E.B.; and Wynn, P.S. Sequences of drug involvement in African-American and Puerto Rican adolescents. Psychol Rep 71:179-182, 1992.

Brook, J.S.; Nomura, C.; and Cohen, P. A network of influences on adolescent drug involvement: Neighborhood, school, peer, and family. Genet Soc Gen Psychol Monogr 115: 125-145, 1989.

Brook, J.S.; Whiteman, M.; Balka, E.B.; Win, P.T.; and Gursen, M.D. African-American and Puerto Rican drug use: A longitudinal study. J Am Acad Child Adolesc Psychiatry, 36(9):1260- 1268, 1997.

Brook, J.S.; Whiteman, M.; Hamburg, B.A.; and Balka, E.B. African-American and Puerto Rican drug use: Personality, familial, and other environmental risk factors. Genet Soc Gen Psychol Monogr 118 (4):417-438, 1992.

Bry, B. Predicting drug abuse: Review and reformulation. Int J Addict 18:223-233, 1983.

Bry, B., and Krinsley, K. Adolescent substance abuse. In: Feindler, E., and Kalfus, G., eds. Adolescent Behavior Therapy Handbook. New York: Springer Publishing Company, 1990.

Bry, B.H.; McKeon, P.; and Pandina, R.J. Extent of drug use as a function of number of risk factors. J Abnorm Psychol 91:273-279, 1982.

Bry, B.; Pedraza, M.; and Pandina, R. Number of risk factors predicts 3-year probabilities of heavy drug and alcohol use in adolescents. In: Harris, L.S., ed. Problems of Drug Dependence 1987: Proceedings of the 49th Annual Scientific Meeting, The Committee on Problems of Drug Dependence, Inc. National Institute on Drug Abuse Research Monograph 81. DHHS Pub No. (ADM)88-1564. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1988.

Clayton, R. Transitions in drug use: Risk and protective factors. In: Glantz, M., and Pickens, R., eds. Vulnerability to Drug Abuse. Washington, DC: American Psychological Association, 1992.

Coie, J.D.; Watt, N.F.; West, S.G.; Hawkins, J.D.; Asarnow, J.R.; Markman, H.J.; Ramey, S.L.; Shure, M.B.; and Long, B. The science of prevention. A conceptual framework and some directions for a national research program. Am Psychol 48(10):1013-1022, 1993.

Compas, B.E.; Hinden, B.R.; and Gerhardt, C.A. Adolescent development: Pathways and processes of risk and resilience. In: Spence, J.T.; Darley, J.M.; and Foss, D.J., eds. Annual Review of Psychology, Volume 46. Palo Alto, CA: Annual Reviews Inc., 1995.

Dishion, T.J.; Kavanagh, K.; and Kiesner, J. Prevention of early substance use among high-risk youth: A multiple gating approach to parent intervention. In: Ashery, R.; Kumpfer, K.L.; and Robertson, E., eds. Drug Prevention Through Family Interventions. National Institute on Drug Abuse Research Mono-graph 177. U.S. Department of Health and Human Services, National Institutes of Health, National Insitute on Drug Abuse, in press.

Donaldson, S.I.; Graham, J.W.; and Hansen, W.B. Testing the generalizability of intervening mechanism theories: Understanding the effects of adolescent drug use prevention interventions. J Behav Med 17(2):195-216, 1994.

Eggert, L.L.; Seyl, C.D.; and Nicholas, L.J. Effects of a school-based prevention program for potential high school dropouts and drug abusers. Int J Addict 25(7):773-801, 1990.

Ford, D.H. Humans as Self-Constructing Living Systems: A Developmental Perspective on Behavior and Personality. Hillside, NJ: Lawrence Erlbaum Associates, 1987.

Gable, R.S. Toward a comparative overview of dependence potential and acute toxicity of psychoactive substances used nonmedically. Am J Drug Alcohol Abuse 19(3):263-281, 1993.

Garmezy, N., and Masten, A.S. Chronic adversities. In: Rutter, M.; Taylor, E; and Hersov, L., eds. Child and Adolescent Psychiatry. Boston: Blackwell Scientific Publications, 1994.

Glantz, M., and Pickens, R., eds. Vulnerability to Drug Abuse. Washington, DC: American Psychological Association, 1992.

Hancock, M. Prediction of Problem Behavior in Adolescence: The Impact of Stability and Change in the Number of Risk and Protective Factors. Doctoral dissertation, Department of Psychology. New Brunswick, NJ: Rutgers University, 1996.

Hawkins, J.D.; Catalano, R.F.; and Miller, J.Y. Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychol Bull 112(1):64-105, 1992.

Jessor, R. Successful adolescent development among youth in high-risk settings. Am Psychol 48(2):117-126, 1993.

Kandel, D. Stages in adolescent involvement in drug use. Science 190:912-914, 1975.

Kandel, D.B. Drug and drinking behavior among youth. Ann Rev Sociol 6:235-285, 1980.

Kandel, D.B.; Yamaguchi, K.; and Chen, K. Stages of progression in drug involvement from adolescence to adulthood: Further evidence for the gateway theory. J Stud Alcohol 53:447-457, 1992.

Kannel, W., and Schatzkin, A. Risk factor analysis. Prog Cardiovasc Dis 26:309-332, 1983.

Kumpfer, K.L.; Molgaard, V.; and Spoth, R. The "Strengthening Families Program" for the prevention of delinquency and drug use. In: Peters, R.D., and McMahon, R.J., eds. Preventing Childhood Disorders, Substance Abuse, and Delinquency. Newbury Park, CA: Sage Publications, 1996.

Labouvie, E.; Bates, M.E.; and Pandina, R.J. Age of first use: Its reliability and predictive utility. J Stud Alcohol 58(6):638-643, 1997.

Labouvie, E.; Pandina, R.J.; and Johnson, V. Developmental trajectories of substance use in adolescence: Differences and predictors. Int J Behav Dev 14(3):305-328, 1991.

Lettieri, D.J.; Sayers, M.; and Pearson, H.W., eds. Theories on Drug Abuse: Selected Contemporary Perspectives. National Institute on Drug Abuse Research Monograph 30. DHHS Pub. No. (ADM)83-967. Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1983. 488 pp.

Miller, J.G. Living Systems. New York: McGraw-Hill, 1978.

Mrazek, P.J., and Haggerty, R.J., eds. Reducing the Risk for Mental Disorders: Frontiers for Preventive Intervention Research. Washington, DC: National Academy Press for the Institute of Medicine, Committee on Prevention of Mental Disorders, 1994.

Muñoz, R.F.; Mrazek, P.J.; and Haggerty, R.J. Institute of Medicine report on prevention of mental disorders: Summary and commentary. Am Psychol 51(11):1116-1122, 1996.

Newcomb, M.D. Identifying high-risk youth: Prevalence and patterns of adolescent drug abuse. In: Rahdert, E., and Chzechowicz, D., eds. Adolescent Drug Abuse: Clinical Assessment and Therapeutic Interventions. National Institute on Drug Abuse Research Monograph 156. DHHS Pub. No. 95-3908. U.S. Department of Health and Human Services, National Institutes of Health, National Institute on Drug Abuse, 1995.

Newcomb, M.D., and Felix-Ortiz, M. Multiple protective and risk factors for drug use and abuse: Cross-sectional and prospective findings. J Pers Soc Psychol 63(2):280-296, 1992.

Newcomb, M.D.; Maddahian, E.; and Bentler, P.M. Risk factors for drug use among adolescents: Concurrent and longitudinal analyses. Am J Public Health 76:525-531, 1986.

Pandina, R.J.; Johnson, V.; and Labouvie, E.W. Affectivity: A central mechanism in the development of drug dependence. In: Glantz, M., and Pickens, R., eds. Vulnerability to Drug Abuse. Washington, DC: American Psychological Association, 1992.

Pentz, M.A.; Dwyer, J.H.; MacKinnon, D.P.; Flay, B.R.; Hansen, W.B.; Wang, E.Y.; and Johnson, C.A. A multicommunity trial for primary prevention of adolescent drug abuse: Effects on drug use prevalence. JAMA 261(22):3259-3266, 1989.

Petraitis, J.; Flay, B.R.; and Miller, T.Q. Reviewing theories of adolescent substance use: Organizing pieces in the puzzle. Psychol Bull 117(1):67-86, 1995.

Piazza, P.V., and LeMoal, M. Pathophysiological basis of vulnerability to drug abuse: Role of an interaction between stress, glucocorticoids, and dopaminergic neurons. Ann Rev Pharmacol Toxicol 36:359-378, 1996.

Reiss, D., and Price, R.H. National Research Agenda for Prevention Research: The National Institute of Mental Health Report. Am Psychol 51(11):1109-1115, 1996.

Rogosch, F.; Chassin, L.; and Sher, K.J. Personality variables as mediators and moderators of family history risk for alcoholism: Conceptual and methodological issues. J Stud Alcohol 51(4): 310-318, 1990.

Rothman, K.J. Modern Epidemiology. Boston: Little, Brown and Company, 1986.

Rutter, M. Resilience in the face of adversity: Protective factors in resistance to psychiatric disorders. Br J Psychiatry 147:598-611, 1985.

Scheier, L.M., and Newcomb, M.D. Psychosocial predictors of drug use initiation and escalation: An expansion of the multiple risk factors hypothesis using longitudinal data. Contemp Drug Prob, Special Reprint, 1991.

Tobler, N.S. Drug prevention programs can work: Research findings. J Addict Dis 11(3):1-28, 1992.

Wise, R.A. Addictive drugs and brain stimulation reward. Ann Rev Neurosci 19:319-340, 1996.

Yamaguchi, K., and Kandel, D.B. Patterns of drug use from adolescence to young adulthood: II. Sequences of progression. Am J Public Health 74:668-672, 1984.


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