This article reviews 14 multivariate theories of experimental substance use (e.g., alcohol and marijuana use) among adolescents, including those theories that emphasize (a) substance-specific cognitions, (b) social learning processes, (c) commitment to conventional values and attachment to families, and (d) intrapersonal processes. Important similarities and differences among these theories are addressed, as are the conceptual boundaries of each theory. In an attempt to integrate existing theories, a framework is proposed that organizes their central constructs into 3 distinct types of influence (viz., social, attitudinal, and intrapersonal) and 3 distinct levels of influence (viz., proximal, distal, and ultimate). Implications for future theory development are discussed.

peer smoking on adolescents' own smoking is still a matter of debate. In addition, little research has examined the role of sign8cant others' behavior on different stages of smoking onset. In particular, not much information is available regarding gender and ethnic differences in social influences on smoking behavior. We use structural equation modeling to address these issues. Different theoretical perspectives from cognitive-affective theories (Ajzen 1985; Ajzen and Fishbein 1980) and social learning theories (Akers et al. 1979; Bandura 1969, 1982, 1986) have been integrated into a structural model of smoking influence. The results show that friends' smoking affects adolescent initiation into smoking both directly and indirectly, whereas parental smoking influences smoking initiation only indirectly. The data also show that friends' and parents' smoking affect smoking escalation only indirectly. In general, friends' smoking has a stronger effect on adolescents' smoking behavior, particularly on initiation. Multiple group comparisons of the structural models predicting smoking initiation among males and females reveal that parental approval of smoking plays a sign8cant mediating role for females, but not for males. Comparisons of Whites, Blacks, Hispanics, and other ethnic groups reveal that there are some signiJicant differences in the pathways of friends' influences among the four groups.

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Knowledge of risk and protective factors for adolescent tobacco use will lead to the development of improved intervention strategies to reduce/prevent tobacco use. Theory and empirical findings demonstrate the multivariate complexity of the etiology of tobacco use. Sociocultural, social/interpersonal, and intrapersonal factors act through mediated chains of ultimate, distal, and proximal influences. Some influences moderate the effects of others. Once tobacco is used, feedback mechanisms modify prior causes that in turn alter subsequent tobacco use behavior. Most theories and cross-sectional, prospective, and causal process studies have contained major limitations: (a) most addressed only small portions of the total picture; (b) most mediational studies did not test for interactions and most moderation studies are based on limited theory (if any); and (c) most theories do not discuss how the causal processes might be different for males and females or for different ethnic groups (special cases of moderation). Furthermore, few studies focused on more distal or ultimate influences or examined multi-stream patterns, and few theories or causal process studies have specified or tested feedback loops. Determining psychosocial risk factors and how they influence tobacco use faces several major challenges, including discovering complex mediating processes, moderating variables, and overcoming limitations of surveys and theory. We offer six recommendations to advance transdisciplinary tobacco-prevention research: (a) base future studies on strong theory and aim to test one or more theories or theoretically derived hypotheses; (b) collect four or more waves of data and adopt dynamic strategies of prediction and analysis, including interactions, indirect effects, feedback loops, and transitions from one level of tobacco use to another; (c) provide evidence of generalizability to sub-populations within the study sample, such as by gender, ethnic group, and socioeconomic status; (d) use high-quality measures and multiple methodologies, including non-panel longitudinal studies, intensive interview, ethnography, experimental intervention, and small exploratory studies as well as further prospective studies; (e) include variables from multiple streams of influence to investigate interrelationships among cultural, social, and intrapersonal factors; and (f) collect data from multiple nested units (e.g., children within families, within schools, within neighborhoods) and employ multi-level analysis methods to investigate interrelationships among ultimate, distal, and proximal variables.

This paper reviews findings from 58 prospective studies of illicit substance use (ISU) among adolescents. It arranges 384 findings according to three types of influence (viz., social, attitudinal, and intrapersonal) and four levels of influence (viz., ultimate, distal, proximal, and immediate). The bulk of evidence reconfirms the importance of several predictors of ISU (e.g., intentions and prior substance-related behavior, friendship patterns and peer behaviors, absence of supportive parents, psychological temperament), reveals that a few variables thought to be well-established predictors may not be (e.g., parental behaviors, parental permissiveness, depression, low self-esteem), and uncovers several variables where findings were either sparse or inconsistent (e.g., the role of public policies concerning ISU, mass media depictions of ISU, certain parenting styles, affective states, perceptions of parental disapproval for ISU, and substance-specific refusal skills). Directions for future research are discussed.

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This article examines correlates of desire and plans to quit smoking among 248 young, low-socioeconomic status African American women, using variables derived from the health belief model (HBM) and the theory of reasoned action. Consistent with these theoretical models, stronger concern about the effect of smoking on one's health and having close others who want the smoker to quit increased motivation to quit smoking. However, motivation was not associated with specific HBM components regarding lung cancer. Heavier smoking and stronger perceptions regarding the functional utility of smoking decreased motivation to quit, but not as much as expected in this study population. Consistent with a process of change approach to smoking cessation, the factors that moved smokers from not planning to planning to ever quit were different from factors associated with further motivation level among the smokers who did plan to ever quit.

Methods are proposed and described for estimating the degree to which relations among variables vary at the individual level. As an example of the methods, M. Fishbein and I. Ajzen's (1975; I. Ajzen & M. Fishbein, 1980) theory of reasoned action is examined, which posits first that an individual's behavioral intentions are a function of 2 components: the individual's attitudes toward the behavior and the subjective norms as perceived by the individual. A second component of their theory is that individuals may weight these 2 components differently in assessing their behavioral intentions. This article illustrates the use of empirical Bayes methods based on a random-effects regression model to estimate these individual influences, estimating an individual's weighting of both of these components (attitudes toward the behavior and subjective norms) in relation to their behavioral intentions. This method can be used when an individual's behavioral intentions, subjective norms, and attitudes toward the behavior are all repeatedly measured. In this case, the empirical Bayes estimates are derived as a function of the data from the individual, strengthened by the overall sample data. Psychological theories often posit relations among variables that can vary depending on the individual. Thus, it may be stated that on average, a given variable X influences another variable Tto a certain degree, but that the degree of this relationship is not a constant but varies to some degree in the population of individuals. In other words, a relationship between two variables may be quite strong in some individuals, whereas for others it may be weak or nonexistent. In clinical research, for example, the effect of a given therapeutic agent for treating, say, depression is thought to vary to some degree from individual to individual; in some individuals, the therapeutic agent, given at the same dose and under the same conditions, is effective whereas for others it is not. Most traditional statistical methods, on the other hand, provide estimation of relations among variables on a group and not on an individual level. A