Alcoholism and memory: broadening the scope of alcohol-expectancy research.

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Psychological Bulletin 1991, Vol. 110, No. 1,137-146

Copyright 1991 by the American Psychological Association. Inc. 0033-2909/91/fe.OO

Alcoholism and Memory: Broadening the Scope of Alcohol-Expectancy Research Mark S. Goldman University of South Florida

Sandra A. Brown University of California, San Diego

Bruce A. Christiansen

Gregory T. Smith University of Kentucky

University of Wisconsin Medical School Milwaukee Clinical Campus

Current biopsychosocial research on the etiology of alcoholism has begun to focus on memory processes as a possible common pathway for drinking decisions. The alcohol-expectancy construct is rooted both in cognitive psychology and alcohol research and can serve as a vehicle for this study. Reexamination of one recent review of issues in alcohol-expectancy research provides an opportunity to broaden the scope of this research with theoretical and methodological alternatives to those suggested in that review. Most importantly, this article shows that expectancy findings, discussed by Leigh (1989a) as reflecting "psychometric" limitations, are instead quite consistent with recent network models of memory structure. Such models can provide an informative guide to future research activities. It is also recommended that alcohol-expectancy research remain open to inputs from expectancy theories already developed in several psychological domains, as well as to theories of social cognition and attitude structure in addition to those advanced by Leigh.

Although research on the causes of alcohol use and alcoholism has traditionally been heavily influenced by pharmacological and genetic explanations, recent findings have drawn attention to cognitive processes as a potentially critical element in the etiological matrix. Work in this area, much of which conies under the rubric of alcohol expectancies, has accelerated in recent years as evidenced by the increasing availability of review articles that include this topic (eg, Abrams & Niaura, 1987; Cappell & Greeley, 1987; Connors & Maisto, 1988; Cox, 1987; Cox & Klinger, 1988; Critchlow, 1986; Goldman, 1989a; Goldman, Brown, & Christiansen, 1987; Lang & Michalec, in press; Leigh, 1989a; Maisto, Connors, & Sachs, 1981; Marlatt, 1987; Marlatt, Baer, Donovan, & Kivlahan, 1988; Oei & Jones, 1986; G. T. Wilson, 1987). In one recent review of alcohol-expectancy research in Psychological Bulletin (Leigh, 1989a), a number of methodological and theoretical issues were highlighted, and directions for future research were offered. This article reexamines the most central of these issues for two reasons. First, the planning of future expectancy research is best undertaken with simultaneous consideration of both the recent

literature on the cause of alcoholism and current theories of cognitive processing. This additional perspective has been insufficiently articulated in the existing literature and can augment aspects of Leigh's (1989a) presentation. Second, embedded in what may appear to be a largely methodological discussion by Leigh (1989a) were implicit assumptions about psychological theory and research strategy that warrant explicit examination and consideration of alternatives. We begin with a brief overview of the potential role of expectancies in the etiology of alcoholism and follow with alternative perspectives on five key issues raised in the Leigh article: the psychometrics of expectancy measurement instruments, expectancy content, the capacity of expectancies to predict drinking, their possible role as a mediator, and the application of attitude theory to this arena. No attempt will be made to exhaustively review each point raised in the earlier article; in some cases we agree with Leigh (1989a), and other points are less critical. The Potential Role of Alcohol-Expectancy Research Intensive research over the past two decades has shown that the development of alcohol use and alcoholism is influenced by a wide range of antecedent factors associated with an individual's environment during childhood and adolescence and their genetically determined biological characteristics, including temperament (Cloninger, 1987; Donovan, Jessor, & Costa, 1988; Marlatt et al., 1988; National Institute of Alcohol Abuse and Alcoholism, 1990; Tarter, 1988; Zucker& Gomberg, 1986). Although controversy has existed over the relative importance of these two sets of variables (see Peele, 1986; Searles, 1988), most researchers now support a multifactor model that includes both domains, possibly arranged in differing combina-

Portions of this work were supported by National Institute on Alcohol, Alcoholism, and Abuse (N1AAA) Grants 1R01AA05946 and 1R01AA06123 to Mark S. Goldman, Bruce A. Christiansen, and Gregory T. Smith and by a Veterans Administration Research Service Award and NIAAA Grant 1R01AA07033 to Sandra A. Brown. After Mark S. Goldman, the order of authorship is alphabetical. Appreciation is expressed to Edward Levine, Louis Penner, Robert Heaton, and Robert Kaplan for comments on earlier drafts of this article. Correspondence concerning this article should be addressed to Mark S. Goldman, Department of Psychology, University of South Florida, Tampa, Florida 33620.

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GOLDMAN, BROWN, CHRISTIANSEN, SMITH

tions that result in multiple pathways to alcoholism (Cloninger, 1987; Zucker, 1987). As important as the identification of these variables has been, however, most merely reflect descriptive characteristics of an individual's physical and social environment, behavioral patterns, or neurophysiology. No biological

study. From this vantage point, we turn now to the issues raised by Leigh (1989a).

Psychometric Issues

researcher has yet demonstrated that any factor automatically

By first reexamining Leigh's presentation of psychometric

"commandeers" drinking activity, and psychosocial researchers

issues, a number of theoretical choices that researchers must

continue to search for controlling mechanisms that connect

make in future investigations can be highlighted. Her discus-

early experiences and dispositions with later drinking patterns. Because of their potential for tying together a host of psycho-

sion centered on three scales for expectancy measurement: the Alcohol Expectancy Questionnaire (AEQ; Brown, Christian-

social and biological/genetic variables, and carrying forward the influence of these variables over extended time periods,

sen, & Goldman, 1987), the Alcohol Effects Scale (AES; Southwick, Steele, Marlatt, & Lindell, 1981), and her own Effects of

memory processes (information storage) are now being consid-

Drinking Alcohol Scale (EDA; Critchlow, 1987), all of which are

ered by researchers of all types as one possible "final common pathway" for drinking decisions. For example, psychobiologi-

accepted by Leigh (1989a, p. 368) as "valid measures of general

cal researchers noted that "memory may be the real biological

addressed the structure and "discriminative ability" (p. 367) of

basis of drug dependence" (Jaffe, cited in Barnes, 1988, p. 417), and that "significant craving results from the memory of past positive reinforcement" (Wise, 1988, pp. 124-125).

these instruments' subscales. Guiding this discussion is the as-

Although psychopharmacological researchers have traditionally eschewed the study of memory processes, cognitive research over the past 20 years has demonstrated that intervening variables may be productively used for enhancing prediction and control of complex behavior (Kihlstrom, 1987), and psychology has become more comfortable with these approaches (Kimble, 1989). Research during the past decade on alcohol-reinforcement expectancies has been consistent with cognitive approaches to the study of memory processes, and has provided a new research "window" from which the emer-

alcohol expectancies." Instead of overall validity, Leigh (1989a)

sumption that instruments that measure a central construct (e.g., expectancies) and subsections of its domain (expectancy scales) must have scales (factors) that are completely independent of each other. In keeping with this assumption, Leigh (1989a) reported that confirmatory factor analyses, using a model in which items were constrained to load on only one factor, reveals discrepancies between what is referred to as "perfect simple structure" and each questionnaire's subscale structure. These analyses are then used to place in doubt the psychometric characteristics of the questionnaires. What is not explained is why subscales measuring a construct

gence of the incentive patterns that influence lifelong alcohol

such as expectancy should be "distinct and independent" or why a "perfect simple structure" criterion "best represents the

decision making may be studied. The use of the expectancy

presumed [italics added] distinctiveness of the subscales" (p.

concept in relation to alcohol also derives from a rich theoretical base in general psychology and has parallels in several applied realms. Modern expectancy formulations date back to

368). There is little psychological basis for such a model. Expec-

Tolman (1932), MacCorquodale and Meehl (1954), and Rotter (1954), and have received a burst of attention in recent years as

tancies are apparently acquired even before alcohol use, probably by observational learning (Goldman et al, 1987; P. G. Miller, Smith, & Goldman, 1990). It is difficult to conceive of a situation in which only one alcohol effect is demonstrated for

it has become understood how postulating that an organism acquires information about "if-then" contingencies can help

the child or adolescent observer at a time. Similarly, when adolescents actually begin use of alcohol, more than one behavioral

explain all varieties of decision making. Expectancy formula-

or pharmacological consequence occurs, especially when drinking in a group. Even if only one effect could somehow

tions have been offered even for such paradigms as operant and classic conditioning (Anderson, 1983; Bolles, 1972; Rescorla, 1988), and success has been achieved in producing computer

occur with each instance of use, these effects would all be conceptually linked to the general theme of "effects that derive

programs that mimic human behavior based on hypothesized

from alcohol use." Leigh (1989a) argued for a rational, a priori

constructs much like expectancies (Newell, cited in Waldrop,

taxonomy for future scales, but did not make it clear why such a taxonomy should be preferable. Would such factors better represent the way in which real individuals encode their alcohol ex-

1988). Psychopathology has been usefully studied by means of expectancy analysis (Alloy & Tabachnick, 1984), as have hypnosis (Kirsch, 1985), interpersonal processes (Jones, 1986; D. T. Miller & Turnbull, 1986), and even affect (Carver & Scheier, 1990; Jones & McGillis, 1976; Wilson, Lisle, Kraft, & Wetzel, 1989). Closer to the present topic, expectancies have been used to explain conditioned tolerance (Siegel, Krank, & Hinson, 1988) and placebo effects (Shapiro & Morris, 1978). In sum, current knowledge in the alcohol field suggests that memory processes should be examined as a possible mediational mechanism, and recent work in cognitive psychology offers a theoretical base for these investigations. The alcoholexpectancy construct, which is rooted in both cognitive psychology and alcohol research, provides an obvious vehicle for this

pectancies, or is there a reason to believe, in advance of empirical tests, that a priori factors would serve as better predictors and theoretical mediators than data-driven factors (see Prediction)? It is also not made evident why confirmatory factor analysis is inherently superior to exploratory analysis for expectancy scale development (Leigh, 1989a, p. 370); this position is not universally shared by authorities in this area (Comrey, 1988). Confirmatory analysis is customarily used to test a preconceived theoretical structure. On what basis does Leigh (1989a) propose a structure for alcohol expectancies in the absence of preliminary exploratory work? When pursuing this structure, it is important that alcohol-ex-


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ALCOHOL EXPECTANCIES

pectancy researchers clearly distinguish between their subject matter and that of other research areas in which the confirmatory model used by Leigh (1989a) may be considered an ideal to be sought (although rarely, if ever, achieved). For example, it might be optimal to strive for total scale independence (items that load on only one scale) when developing tests of personality or psychopathology in which scales are intended to measure systematic syndromes of behaviors, from which are inferred underlying trait constructs. As a specific instance, items measuring introversion should not also fall on an aggressiveness scale if confusion about the constructs is to be avoided. However, in the case of expectancy research, the intent is not to measure a cluster of classic traits, but instead information stored in memory that is associated with the reinforcing effects of alcohol. Recent work on semantic memory and concept formation appears, therefore, to provide a more appropriate model (Goldman, 1989a). Alcohol expectancies are essentially concepts of if-then relationships between events or objects in the world and their consequences, including self-generated behavioral consequences (Goldman et al, 1987). Research on semantic (concept) memory encountered very early the fact that in the real world categories are inherently "fuzzy" (concepts have elements that overlap). For this reason, more recently accepted views of concept formation (Rosch, 1975; Rosch & Mervis, 1975) hold that concept elements may be shared. Furthermore, concepts are understood to be defined by the observer based on an individualized accumulation of information elements related to that concept. Concepts cannot therefore be determined in an a priori manner across all individuals. This now widely held view is known as the prototype (or probabilistic) approach. Consider the element wings of the concepts airplane and bird. Wings are components of both and may even be an essential (defining) characteristic of both. Could a psychological instrument aimed at measuring the overall concept of flying objects, with subscales for airplane and bird, appropriately exclude wings from either subscaie? In recognition of this characteristic of concepts stored in memory, cognitive psychologists have used a number of models of memory structure (e.g, Anderson, 1983; Glass & Holyoak, 1974/1975; Humphreys, Bain, & Pike, 1989; Roediger, 1980; see also Chang, 1986) that include some means by which concept elements can be associated with multiple concepts. In one of the best known of these models—the spreading activation approach (Collins & Loftus, 1975)—concepts are schematically represented as spatial relationships between semantic elements, with elements more centrally related to a concept located closer to other central elements. Hence, although elements are perhaps more closely related to one concept than another, they can be related to more than one concept. Decisions are made in this model by activation spreading from concept node to concept node based on associational strength (probability). Semantic network theory has also been extended to include emotions (Bower, 1981). The factor model that appears to fit prevailing memory models is one in which factors (and corresponding scales) are related to each other but also have unique components that establish their separate semantic identity. The unique portion of each factor's variance reflects that individuals' can discern special

characteristics of a concept, even though this concept may also share components with other concepts and, in routine usage, may be most frequently activated with other concepts. Leigh (1989a) seemed to recognize this characteristic of expectancies (p. 369) when she noted that alcohol's tension reduction and social lubricant functions must be related, but then suggested that the only viable alternative is "to think of these scales as measuring a general belief about desirable alcohol effects" (p. 369). It is not necessary to understand semantic structures as either completely discrete or completely undiflerentiated. Factor models that have included both unique and common variance have been used routinely to model psychological phenomena since the inception of factor analysis. Furthermore, existing models of concept memory hold that concepts are organized hierarchically; that is, that wing is an element of bird, which is in turn an element of flying objects. Hence, hierarchical factor analyses should demonstrate that expectancies are meaningfully interpretable at different levels of aggregation, from the specific and molecular to the general. Contrast this view to Leigh's (1989a, p. 368) implication that this characteristic of an instrument such as the AEQ is somehow a limitation.1 Of course, approaches other than paper-and-pencil survey instruments could (and should) be used to measure expectancies, and it can be argued that factor analysis of any kind has limitations for the study of a cognitive network. Most current procedures developed specifically for measuring cognitive networks are, however, difficult to apply to large groups of subjects. Multimethod measurement is an obvious path for future work. Specific Scales Since Leigh (1989a) characterized the AEQ as the most widely used instrument in the field and discussed it at length, the AEQ provides an obvious specific case for reviewing the previous conceptualization. First, however, it must be noted that the correlated nature of the AEQ items and scales did not need to be discovered by confirmatory factor analysis. In several original reports on the AEQ (Brown, 1985a; Brown, Goldman, & Christiansen, 1985; Brown, Goldman, Inn, & Anderson, 1980), the fact that items loaded on more than one scale was reported. An explicit decision was made when establishing a unit-weighting system (rather than scoring by factor loadings) to place items on the scales on which they loaded most highly rather than discarding items with modest factor loadings on other scales. In fact, because of the loading of items on more than one factor, a unit-weighting system inevitably produces correlated scales. In 1985, Brown and colleagues indicated that "given the item selection procedure and the probable relation among alcohol expectancies in the 'real world,' it was not surprising that the six alcohol expectancy scales were intercorrelated . . . [with an] average interscale correlation of .25" (p. 514). Thus, the implication that the AEQ subscales were ever

1 In fact, the adolescent AEQ was first developed using hierarchical factor analysis.


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conceived or presented as completely "distinct and independent" (Leigh, 1989a, p. 367) is inaccurate and misleading. R-om the outset, the development of the AEQ for both adults and adolescents (see Brown, Christiansen, & Goldman, 1987; Goldman et al, 1987) reflected both a research strategy for mapping alcohol expectancies as they exist in the subjects' cognitive structure and the refinement of an instrument that could be used repeatedly for investigating the nomothetic network of relationships between expectancies and related cognitions and behaviors. To this end, items used subjects' own words about alcohol effects based on hundreds of interviews with both alcoholics and nonalcoholics, and exploratory factor analysis was deliberately used to do just that: explore the relationships among expectancy elements. Subjects were systematically selected to represent all levels of alcohol use. The factors derived using this strategy were offered as the beginning step of an ongoing research effort to demonstrate expectancy operation and to refine knowledge of expectancy structure. Even the first report on the AEQ in 1980 by Brown and colleagues stated that "additional expectancies exist beyond those tapped in the present study" and "expectancies may be differently applied by drinkers as a function of the amount of alcohol consumed and the context or setting in which the drinking occurs" (p. 425). Nevertheless, the AEQ factors so derived have uniquely contributed to prediction of different drinking patterns, and the profile of scales that afford the best prediction is more consistent across studies than Leigh (1989a) suggested. For example, the expectancy of social enhancement is consistently predictive of more frequent drinking in adolescents and adult samples, whereas scales measuring more specific and pharmacologically linked effects (e.g., tension reduction, relaxation) are associated with problem drinking and alcohol dependency.2 The AEQ factors also fit the memory model noted previously in which each scale consists of both common and unique variance. This fit is readily demonstrated by partitioning factor variance on the AEQ using our adult cumulative data base and our longitudinal adolescent sample. Partitioning is accomplished by first estimating each factor's common variance using simultaneous multiple regression to predict that factor from all remaining factors in the instrument (five for the AEQ and six for the AEQ-adolescent) and squaring the resulting multiple R. Total systematic variance for that factor is then computed using the formula for coefficient alpha. Finally, the total (reliable) unique variance of that factor is computed as the difference between total systematic variance and common variance. Table 1 shows that for large representative samples (1,742 adults, including nonalcoholics and alcoholics and 841 junior high and high school students), every factor on both the AEQ and AEQadolescent version consists of both a unique and a common portion of variance. As might be anticipated, the scales having the highest predictive power in prior research are those with the most unique variance. This factor-structure pattern is also quite stable; in an annual data collection over 5 years in an adolescent sample, the average common and unique variance pattern for all 5 years was quite similar to the data for each separate year.3 An additional difference between a spreading activation memory model and the model applied by Leigh (1989a) is highlighted by Leigh's (1989a, p. 368) suggestion that the AEQ scales

Table 1 Reliable AEQ Factor Variance (Estimated by Coefficient Partitioned Into Common and Unique Portions

AEQ(;V= 1,742) Factor

R2

a

,-R2

1 2 3 4 5 6 7

0.62 0.39 0.46 0.56 0.52 0.56

0.87 0.81 0.69 0.86 0.73 0.67

0.25 0.42 0.23 0.30 0.21 0.11

AEQ-A-R2 0.64 0.42 0.34 0.56 0.41 0.54 0.65

0.19 0.41 0.37 0.25 0.43 0.22 0.20

Note. AEQ = Alcohol Expectancy Questionnaire. The AEQ subscales are coded as follows: 1 = global positive changes; 2 = sexual enhancement; 3 = social and physical pleasure; 4 = social assertiveness; 5 = relaxation; 6 = arousal/aggression. The AEQ for adolescents (AEQ-A) are coded as follows: 1 = global positive changes; 2 = social enhancement or impairment; 3 = improved cognitive and motor functioning; 4 = sexual enhancement; 5 = deteriorated cognitive and motor functioning; 6 = increased arousal; 7 = relaxation.

do not measure expectancy strength. From a spreading activation perspective, strength refers to the availability of concept elements. Hence, individuals who more readily associate (and quickly retrieve) more elements with any concept (scale) are revealing a stronger, and perhaps more elaborately defined, conceptual network. In fact, from this perspective, it is these very associational processes that, in part, govern an individual's decision about whether to endorse a particular item. When arguing that the AEQ scales do not measure strength, Leigh (1989a, p. 368) apparently applied the term strength to an individual's separate estimation of the likelihood of particular expectancies operating in particular situations rather than to the cognitive processes that influence the probability of item endorsement. The contribution of a separate strength rating to prediction of drinking is a legitimate, but different, question. As to the other two scales reviewed by Leigh (1989a), neither has the extensive validation network currently enjoyed by the AEQ, but the AES has demonstrated sensitivity to dose effects (although, as Leigh indicated, it has not fared well in prediction studies), and the EDA emphasizes negative expectancies and has been shown to have concurrent validity. That they do not match Leigh's (1989a) confirmatory model is not a psychometric weakness and does not mean they have insubstantial utility in the areas in which they have been found sensitive. The crossvalidation of these instruments is, however, still limited, and further work is necessary. Interestingly, though, if the expec2 The primary source of some early inconsistency was noted in our 1985 article (Brown etal, p. 517) as being due to inclusion of abstainers in the 1980 study (Brown et al.). Since the recognition of this early source of confusion, findings have been generally consistent. 3 As also can be seen from Table 1, Leigh's (1989a, p. 367) reference to "several" AEQ subscales showing "very poor reliability" is incorrect; most scales on both versions of the instrument have always had moderate to high coefficient alphas, and the power/agression subscale was modified from the original in 1985 to bring it to acceptable levels.


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tancy factors discerned with these disparate methods are compared, the overlap is actually quite remarkable and contributes to the emerging picture of expectancy structure. For example, the AEQ social and physical pleasure scale readily compares with the AES pleasurable disinhibition scale, and the AEQ social assertiveness and relaxation scales overlap with the gregariousness and depressant scales on the EDA.

Hence, the operation of an element within the expectancy conceptual network may inherently reflect aspects of valence and utility in the form of associational proximity (Goldman, 1989a). Recent investigations using multidimensional scaling techniques have, in fact, highlighted the associative strength of positive expectancies for high drinkers relative to negative expectancies (Rather, Levine, & Goldman, 1990).

Content

Prediction of Drinking Patterns

Rather than viewing endorsement of expectancy items as a reflection of each individual's associational network of expectancies, Leigh (1989a) appeared to regard each expectancy as one of a set of independent intervening variables that act additively to influence drinking choices in a kind of "mental algebra." In this algebra, a subject deliberates desirability and utility separately from expectancy outcome, which may itself be positive or negative. The result of this calculation determines questionnaire responses and behavior. Models of this kind certainly deserve consideration as an explanation of expectancy phenomena, and, at a purely mathematical level, may provide some predictive power (e.g., Bauman. Fisher, Bryan, & Chenoweth, 1985). Such models (e.g, Ajzen & Fishbein, 1973; Fishbein & Ajzen, 1975) have been recognized before in our writing (Goldman etal., 1987). Algebraic models are not, however, some ultimate standard against which other work must be judged, but merely one of several possible theoretical formulations. Do individuals actually consider positive and negative outcomes of alcohol use and their valuation and utility in steps or stages? This process is more likely to happen in a novel situation, or if time permits a response to be carefully considered in advance (as it might be by a researcher contemplating the mechanism). The ongoing stream of most human behavior is, however, more automatic and rapid. Cognitive theorists have noted this characteristic of decision behavior by distinguishing controlled (or effortful) from automatic processing (Hasher & Zacks, 1979,1984). It is likely that, except in the early phases of alcohol use, decision making is very often automatic. It is also likely that different processes operate in early and later phases, but without a discrete demarcation between phases. Emotional reactivity, which Zajonc (1980) pointed out happens far too quickly to be a consequence of a separate cognitive evaluation stage, must also be integrated within the decision process. Whether a "mental algebra" (stage) model, or some other model such as spreading activation, holds best in relation to expectancy operation is an empirical question. For example, Leigh (1989a, p. 363) herself noted that the preponderance of available evidence supports neither negative expectancies (of aversive outcomes) nor separate ratings of value (utility) as noteworthy contributors to prediction beyond that offered by measuring positive expectancies (for another instance, see Stacy, Widaman, & Marlatt, 1990). It is not that individuals lack negative expectancies or cannot provide utility ratings, or even that these characteristics cannot enter into expectancy-driven decisions." However, in usual (more automatic) operation, more retrievable (high-association) expectancy elements are those with significance for reinforcement, and these elements more readily influence ongoing behavior.

Although Leigh (1989a) reviewed some of the relationships found between measured expectancies and drinking behavior, the nomothetic network (Cronbach & Meehl, 1955) of these relationships merits further emphasis. For example, expectancies measured by the AEQ and its variants have been found to relate to drinking levels in adolescents and adults, from low-level social drinkers to alcoholics (regardless of their treatment history; Brown, 1985a; Brown, Goldman, & Christiansen, 1985; Christiansen & Goldman, 1983; Christiansen, Goldman, & Inn, 1982; Connors, OTarrell, Cutter, & Thompson, 1986; Cooper, Russell, & George, 1988; Mann, Chassin, & Sher, 1987; Mooney, Fromme, KMahan, & Marlatt, 1987). That is, expectancy strength increases with drinking level independent of the possibly confounding effects of other life experiences associated with alcohol use (placement in an alcohol-treatment facility). They have been found in children (Miller et al., 1990) and adolescents before direct experience with alcohol consumption (Christiansen & Goldman, 1983; Christiansen, Smith, Roehling, & Goldman, 1989), showing that they derive initially from sources other than direct pharmacological experiences. These sources are most likely of a social learning nature. They longitudinally predict drinking onset and onset of problem drinking (Christiansen et al, 1989; Smith, Roehling, Christiansen, & Goldman, 1986; Roehling, Smith, Goldman, & Christiansen, 1987) in adolescents. As would be anticipated from both social learning and genetic origins, adolescent expectancies relate to parental drinking (Brown, Creamer, & Stetson, 1987), to highrisk status based on family history of alcoholism (Mann et al., 1987), and to personality characteristics that predispose individuals to early abuse (Brown & Munson, 1987). In connection with the actual percents of variance accounted for by expectancies in predicting quantity/frequency indexes of drinking, the Leigh (1989a) article reported only those percents of variance found in one study Leigh carried out with a sample of college students (Leigh, 1989b). Other findings are available. For example, whereas Leigh (1989a) reported that the adult AEQ and her own scale (Leigh, 1987) explain between 10% and 19% of the variance in quantity and frequency of drinking, a series of reports from our laboratory using the adolescent version of the AEQ (AEQ-A; Christiansen etal, 1989; Roehling et al, 1987; Smith et al, 1986) showed that in adolescents concurrently measured expectancies may account for as much as 45% of the variance in drinking (quantity and frequency), and expectancies measured even 1 and 2 years in advance of drinking may

4 It should also be mentioned that Leigh (1989a) disregarded our work on the adolescent AEQ (Christiansen et al., 1982) when critiquing the absence of negative expectancies in the AEQ.


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account for up to 26% of the variance. The AEQ-A even accounted for 13% of the variance in predicting the likelihood of adolescents converting from nonproblem to problem-drinking status over a year-long period. As Leigh (1989a) suggested, the relationship between expectancies and drinking may be higher in beginning drinkers for a variety of theoretical and psychometric reasons, but the robustness of this association cannot be appreciated unless all obtained predictive relationships across expectancy-assessment instruments and studies are reported. If prediction of empirically derived drinking styles is included for consideration (as it should be for a comprehensive understanding of expectancy operation), then variance accounted for has reached as high as 22% even in experienced adult drinking populations (Brown, 1985a).

Longitudinal Studies Although Leigh (1989a) acknowledged the importance of longitudinal research, she questioned the significance of existing longitudinal studies (e.g. Smith et al, 1986) based on methodological concerns (p. 366). It is suggested that because expectancies are correlated with drinking longitudinally from Time 1 to Time 2, and concurrently at Time 2, then the longitudinal relation is potentially an artifact of the concurrent relation. This situation will, of course, obtain with any relatively stable predictor. For example, measured intelligence will predict school performance in advance, and will correlate with it concurrently, because nonpsychological variables such as muscle strength will relate at both time points to performance in weightlifting. No statistical technique can (or should) eliminate this characteristic of a stable predictor. In the case of alcohol expectancies, this relationship obtains because early measurement of learned expectancies anticipates the operation of these same expectancies at a later point proximal to a drinking opportunity (and decision). Cross-lagged panel correlation, which Leigh (1989a, p. 366) recommended for teasing apart these relationships, has been severely criticized for just this reason; that is, it may spuriously indicate directional influence (Rogosa. 1980). Rogosa (1980) strenuously recommended against its use and the technique has been largely abandoned. To overcome the limitations inherent to purely statistical determination of directionality, existing longitudinal expectancy research was deliberately designed to capitalize on the natural "experiment," which occurs in adolescents who change from nondrinking to drinking status. Using this quasiexperimental control, Christiansen and co-workers (1989) showed that expectancies measured before drinking begins predict later drinking. This finding replicates the results of earlier work using an agestratified design (Christiansen & Goldman, 1983), and is consistent with the recent finding of expectancies in children (P. G. Miller et al, 1990). Hence, although expectancies may be refined by drinking experience, the evidence that they antedate drinking is strong.

Mediation Leigh (1989a) discussed causality in connection with the directionality of effects in the longitudinal studies noted previously, but the inference of causality is more directly asso-

ciated with the mediational role of expectancies. While investigating this role, however, it is important for researchers to remember that a variable can serve as a mediator without explaining the entire relationship between independent and dependent variables (Baron & Kenny, 1986). That is, multiple mediational mechanisms may conjointly operate to influence a dependent variable. To use a common example, alcohol abusers may decrease drinking by suppressing existing incentive systems (by anticipatory avoidance of negative consequences) or by increasing the incentive value of behaviors that compete with expectancies. Hence, Leigh's (1989a, p. 370) implication that observation of decreased drinking without concurrent decrease in measured expectancies brings into question the power of expectancies as a mediator is not warranted. In fact, higher expectancies do relate to higher risk for return to problematic drinking in alcohol-dependent individuals (Brown, 1985b). It is not necessary that expectancies change over the observed time period; stable higher expectancies may more effectively compete with (resist) the therapeutic influences of other mediators of treatment effects. Also the Fromme, Mooney, Kivahan, and Marlatt (1986) study, which Leigh (1989a, p. 370) cited as an example of decreased drinking without decreases in expectancy, used the AES for measuring expectancy change, a scale that Leigh (1989a, p. 365) herself criticized for insufficient sensitivity to parameters other than dosage. Evidence supporting alcohol expectancies as a partial mediator of known antecedents of alcohol risk (family history of alcoholism, sensation seeking/antisocial personality), using variants of the correlational design recommended by Baron and Kenny (1986), has recently been obtained (Henderson, cited in Goldman, 1989b; Sher & Walftzer, 1989; Smith & Goldman, 1990). However, the strongest support for a causal inference comes only from true experiments in which the focus variable is manipulated, with a consequent change in a dependent variable. One of the difficulties with the postulation of any intervening (hypothetical) mechanism is that such mechanisms can only be indirectly (implicitly) manipulated, by manipulating some tangible variable that is inferred to affect the intervening variable (e.g, food deprivation to increase hunger). In the case of alcohol expectancies, this process is especially difficult because these expectancies are not conceived as readily subject to shortterm fluctuations, as hunger might be. Furthermore, we now have evidence that expectancy formation dates back to early childhood, with notable strengthening about ages 9 to 10 (P. G. Miller et al, 1990). As Leigh (1989a) noted, it is perhaps unrealistic to bring adult subjects into a laboratory and expect a brief manipulation to have a measurable effect on such a long-lasting system, particularly because laboratory subjects are often inherently suspicious of being deceived in psychological laboratories. In a recent study, we fared somewhat better by challenging expectancies in a more extensive manner in college-student drinkers and showing a subsequent decrease in drinking levels in those individuals who at the outset were higher level drinkers (Massey & Goldman, 1988). After a baseline period during which subjects monitored their own drinking behavior, subjects attended a session at which they knew they would be administered alcohol or placebo. Their task was to determine, based on behavioral observations of party behavior, those subjects


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among them that had actually received alcohol. To make this intervention session applicable to adolescents and college students who were below the legal drinking age, younger subjects in attendance knew they would not consume any alcohol, but would only get an opportunity to judge the presence of alcoholrelated behavior in older subjects. As anticipated, neither drinkers nor observers were able to accurately discriminate those individuals who had actually received alcohol. After this intervention, experimental subjects were given a 2-week intervention program that included extensive training about expectancy effects and self-monitoring of exposure to everyday situations that encourage expectancies (e.g., advertising). Onemonth follow-up showed that, for the subjects who drank least initially, both the expectancy and a traditional program had equal effect in reducing drinking. However, among the moderate to high drinkers, the expectancy program was more effective in reducing drinking. A pre-post assessment group showed no change in drinking behavior. Demand characteristics were evaluated and discounted as the source of this effect. The limited range of drinking monitored makes us regard these results as preliminary. In addition, unfortunately for simplicity of interpretation, subjects in all groups slightly lowered their AEQ scores from premanipulation to postmanipulation, probably because of repeated exposure over a limited time span (three times) to the same instrument, which, as noted earlier, was constructed to be related to global drinking levels and not short-term changes. Drinking behavior, however, did respond to an intervention that could only have been designed based on the expectancy literature. Obviously, further work must be done using expectancy measures more sensitive to phasic expectancy levels.

Attitudes At a variety of points, Leigh (1989a) referred to research on attitudes and social cognition as appropriate resources for expectancy research. We support the use of other research bases, along with the use of the cognitive models of memory and learning models noted earlier. However, do attitudes "have an edge" over expectancies as an explanatory construct (Leigh, 1989a, p. 366)? Traditional attitude research has a spotty record for predicting behavior (Chaiken & Stangor, 1987). Furthermore, when such prediction is improved by assessing attitudes with reference to very specific targets, the choice of the term attitude or expectancy may merely reflect differing points of emphasis in various social/cognitive models of behavior. A more fundamental question is why expectancy and attitude approaches must be placed in competition. The recent attitude literature shows many parallel developments with expectancy research and many points of convergence (see Fazio, 1989). Consider Tesser and Shaffer in their chapter on attitude research in the most recent Annual Review of Psychology (1990, p. 482): "A number of workers have suggested that attitudes are representations in memory. This perspective . . . draws heavily on ... work on associative networks. . .[and postulates a] processor spreading activation.'" If Leigh's advocacy of attitude concepts is intended to argue for a muhicomponent model of attitude, our earlier discussion of algebraic or associational network models becomes again

relevant.5 One additional point in this connection needs to be made, however. In traditional attitude research, separate informational and evaluative components are sometimes hypothesized because the informational characteristic (e.g, political party) may have no inherent valuation apart from an observer. The alcohol expectancies found so far to be most predictive of drinking contain information about subjective effects (reinforcement). Such expectancies are never formed without reference to the observer (i.e, individuals' accumulate information about how alcohol is likely to affect them),6 and, therefore, the evaluative and the informational component may be inherently linked. It must also be said, however, that many attitude researchers have come to a similar unidimensional view, although complexities still remain (Tesser & Shaffer, 1990, p. 481).

Conclusion As the identification of biological and psychosocial variables that serve as predictors of alcohol use and alcoholism accelerates, the need increases for mediatorial mechanisms that explain how these largely descriptive variables actually influence drinking. Memory processes have been proposed as one such mechanism, with the alcohol expectancy construct as a central memory element. A substantial network of findings is now available linking this construct to alcohol consumption and abuse and to relevant antecedent variables that relate to later drinking patterns. The refinement of measurement procedures and identification of specific operational mechanisms are now receiving increasing attention. A recent article in this journal (Leigh, 1989a) recommended directions for this developmental process. Consideration of alcohol-expectancy research in the context of alcoholism etiology and cognitive psychology does suggest, however, important theoretical and methodological alternatives to some of the most central positions indicated by Leigh (1989a). First, alcohol-expectancy research has not been atheoretical as Leigh (1989a) suggested, but has always been tied to funda-

5 Leigh's (1989a) view of the competition between attitudes and expectancies should be placed in the context of her own finding (Leigh, 1989b) that even when the attitude measure was constructed with reference to a specific target (having a drink, getting drunk), expectancies outpredicted attitudes. Actually, close examination of the attitude items used in that study (e.g., interesting/boring; rewarding/punishing; pleasant/unpleasant) supports the contention that there is little difference between attitudes measured to a specific target and expectancies of reinforcement. The advantage of the expectancy instrument was likely due to the fewer items and lesser development of the attitude scale. The fact that expectancies only added a moderate amount of unique prediction above demographics (Leigh, 1989b) is also consistent with the contention in the present article that expectancies are the proximal representation (memory) of experiences acquired in connection with demographic characteristics (e.g., gender-specific learning or age-related accumulation of experience with alcohol), and therefore there is an overlap in variance accounted for. 6 Individuals also hold expectancies about the drinking behavior of others (Rohsenow, 1983), but these expectancies are less central to the motivation for one's own drinking, as are other tangential expectancies such as the physical characteristics of alcohol (e.g., color, container shape, alcohol chemistry).


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mental psychological processes such as motivation and reinforcement. Expectancy theory itself has a rich history across many disciplines within psychology, and has enjoyed significant recent development as an explanatory tool for many basic psychological phenomena, including classic and operant conditioning, and social processes. Versions of expectancy theory tailored to the alcohol realm are needed, but it is customary in science to first move through a descriptive phase to provide a foundation for formal theory. To date, alcohol-expectancy researchers (see review articles referenced early in this article) have provided useful description, have begun to use experimental and quasiexperimental designs to answer specific questions, and have articulated working heuristics. Second, many current models of memory hypothesize an interconnected representational system as exemplified by the spreading activation model. Although Leigh (1989a) recommended cognitive models of expectancy, arguments central to her thesis hinge on the use of a confirmatory factor analytic model, which does not appear applicable to current memory models. Other models that treat expectancy factors as distinguishable but interrelated parts of an information network offer a better fit to existing theory and data. Similarly, traditional attitude and utility models that treat expectancies, attitudes, perceived social norms, subjective utility, and behavioral intentions as separate intervening variables were advanced by Leigh (1989a), although these models are only a subset of current models in memory research and social cognition. In fact, attitude theorists have themselves begun to rely heavily on associational network models, which are difficult to distinguish from expectancy of reinforcement models. At this point, a variety of theoretical approaches are viable and should be explored empirically No model is inherently a standard against which others should be measured at a purely conceptual level. Potentially much more productive areas for future investigation may be when (under what conditions) and how much alcohol-related decision making is automatic versus controlled (planful) and the consequent degree to which spreading activation or stage (algebraic) models are applicable. Third, Leigh's (1989a) psychometric critique of expectancy instruments primarily reflected implicit conceptual (and not methodological) considerations, because the application of confirmatory analysis is predicated on the initial choice of a theoretical model. Although each of the instruments reviewed does have certain limitations and boundary conditions, each may be used in realms for which validity data are currently available and, experimentally to explore novel relationships. It is certainly appropriate to continue use of the most extensively validated instrument, the AEQ, although improvements of this instrument are continuing, and other instruments should be developed to accomplish different tasks in the process of discerning expectancy operation. Exploratory factor analysis remains a viable technique for use in development of such scales. Finally, as Leigh (1989a) averred, further longitudinal studies are warranted, as are studies of mediation (which lend themselves to inferences of causality). Directionality of effects should be determined using experimental and quasi-experimental control of variables, and not cross-lagged panel correlation, which has been abandoned by most researchers. Covariance structure modeling techniques also offer promise in this realm.

References Abrams, D. B, & Niaura, R. S. (1987). Social learning theory. In H. T. Blane&K. E. Leonard (Eds), Psychological theories of drinking and alcoholism (pp. 131-178). New York: Guilfoid Press. Ajzen, I., & Fishbein, M. (1973). Attitudinal and normative variables as predictorsof specific behavior. Journal of Personality and Social Psychology, 27, 41-57. Alloy, L. B., &. Tabachnik, N. (1984). Assessment of covariation by humans and animals: The joint influence of prior expectations and current situational information. Psychological Review, 91,112-149. Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning and Verbal Behavior, 22, 261-295. Barnes, D. M. (1988). The biological tangle of drug addiction. Science, 241, 415-417. Baron, R. M., & Kenny, D.D. (1986). The moderator-mediator distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, SI, 1173-1182. Bauman, K. E, Fisher, L. A., Bryan, E. S., &Chenoweth, R. L. (1985). Relationship between subjective expected utility and behavior: A longitudinal study of adolescent drinking behavior. Journal of Studies on Alcohol, 46, 32-38. Bolles, R. C. (1972). Reinforcement, expectancy, and learning. Psychological Review, 79, 394-409. Bower, G. H. (1981). Mood and memory. American Psychologist, 36, 129-148. Brown, S. A. (1985a). Expectancies versus background in the prediction of college drinking patterns. Journal of Consulting and Clinical Psychology, S3,123-130. Brown, S. A. (1985b). Reinforcement expectancies and alcoholism treatment outcome after a one-year follow-up. Journal of Studies on Alcohol, 46, 304-308. Brown, S. A., Christiansen, B. A., & Goldman, M. S. (1987). The alcohol expectancy questionnaire: An instrument for the assessment of adolescent and adult expectancies. Journal of Studies on Alcohol, 48, 483-491. Brown, S. A., Creamer, V A, & Stetson, B. A. (1987). Adolescent alcohol expectancies in relation to personal and parental drinking practices. Journal of Abnormal Psychology, 96,117-121. Brown, S. A, Goldman, M. S., & Christiansen, B. A. (1985). Do alcohol expectancies mediate drinking patterns of adults? Journal of Consulting and Clinical Psychology, 53, 512-519. Brown, S. A, Goldman, M. S., Inn, A, & Anderson, L. (1980). Expectations of reinforcement from alcohol: Their domain and relation to drinking patterns. Journal of Consulting and Clinical Psychology, 48, 419-426. Brown, S. A, & Munson, E. (1987). Extroversion, anxiety and the perceived effects of alcohol. Journal of Studies on Alcohol, 48(3), 272276. Cappell, H., & Greelej; !. (1987). Alcohol and tension reduction: An update on research and theory. In H. T. Blane & K. E Leonard (Eds), Psychological theories of drinking and alcoholism (pp. 15-54). New York: Guilfoid Press. Carver, C. S., & Scheier, M. F. (1990). Origins and functions of positive and negative affect: A control process view. Psychological Review, 97, 19-35. Chaiken, S., & Stangor, C. (1987). Attitudes and attitude change. Annual Review of Psychology, 38, 575-630. Chang, T. M. (1986). Semantic memory: Facts and models. Psychological Bulletin, 99,199-220. Christiansen, B. A, & Goldman, M. S. (1983). Alcohol-related expectancies versus demographic/background variables in the prediction of adolescent drinking. Journal of Consulting and Clinical Psychology, 51, 249-258.


ALCOHOL EXPECTANCIES Christiansen, B. A., Goldman, M. S., & Inn, A. (1982). Development of alcohol-related expectancies in adolescents: Separating pharmacological from social learning influences. Journal of Consulting and Clinical Psychology. 50, 336-344. Christiansen, B. A, Smith, G. T, Roehling, P. V, & Goldman, M. S. (1989). Using alcohol expectancies to predict adolescent drinking behavior after one year. Journal of Consulting and Clinical Psychology, 57, 93-99. Cloninger, C. R. (1987). Neurogenetic adaptive mechanisms in alcoholism. Science, 236,410-416. Collins, A. M., & Loftus, E. F. (1975). A spreading activation theory of semantic processing. Psychological Review, 82,407-428. Comrey, A. L. (1988). Factor analytic methods of scale development in personality and clinical psychology. Journal of Consulting and Clinical Psychology, 56, 764-761. Connors, G. J., & Maisto, S. A. (1988). The alcohol expectancy construct: Overview and clinical applications. Cognitive Therapy and Research, 12, 487-504. Connors, G. J., OTarrell, T. J, Cutter, H. S. G, & Thompson, D. C. (1986). Alcohol expectancies among male alcoholics, problem drinkers, and nonproblem drinkers. Alcoholism: Clinical and Experimental Research, 10, 667-671. Cooper, M. L., Russell, M, & George, W H. (1988). Coping, expectancies and alcohol abuse: A test of social learning formulations. Journal of Abnormal Psychology, 97, 218-230. Cox, W M. (1987). Personality theory and research. In H. T. Blane & K. E. Leonard (Eds), Psychological theories of drinking and drinking and alcoholism (pp. 55-89). New York: Guilford Press. Cox, W M., & Kh'nger, E. (1988). A motivational model of alcohol use. Journal of Abnormal Psychology, 97,168-180. Critchlow, B. (1986). The powers of John Barleycorn: Beliefs about the effects of alcohol on social behavior. American Psychologist, 41, 751-764. Critchlow, B. (1987). A utility analysis of drinking. Addictive Behaviors, 12, 269-273. Cronbach, L. J, &Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52, 281-302. Donovan, J. E., lessor, R, & Costa, F. M. (1988). Syndrome of problem behavior in adolescence: A replication. Journal of Consulting and Clinical Psychology, 56, 762-765. Fazio, R. H. (1989). On the power and functionality of attitudes: The role of attitude accessibility. In A. R. Pratkanis, S. J., Breckler, & A. G. Greenwald (Eds.), Attitudes structure and function (pp. 153179). Hillsdale, NJ: Erlbaum. Fishbein, M., & Ajzen, I. (1975). Belief attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. Fromme, K., Mooney, D. K.., Kivlahan, D. R., & Marian, G. A. (1986). Expectancies, risk identification, and secondary prevention with problem drinkers. Advances in Behavior Research and Therapy, 8, 237-251. Glass, A. L.,& Holyoak, K. J. (1974/1975). Alternative conceptions of semantic theory. Cognition, 3(4), 313-339. Goldman, M. S. (1989a). Alcohol expectancies as cognitive-behavioral psychology: Theory and practice. In T. Loberg, G. A. Marlatt, P. E. Nathan, & W Miller (Eds), Treatment of addictive behaviors (pp. 11-30). Amsterdam: Swets. Goldman, M. S. (1989b, November). Expectancies and alcoholism risk in adolescence. Paper presented at the 23rd Annual Association for Advancement of Behavior Therapy Convention, Washington, DC. Goldman, M. S., Brown, S. A., & Christiansen, B. A. (1987). Expectancy theory: Thinking about drinking. In H. T. Blane & K. E. Leonard (Eds.), Psychological theories of drinking and alcoholism (pp. 181226). New York: Guilford Press.

145

Hasher, L., & Zacks, R. T. (1979). Automatic and effortful processes in memory. Journal of Experimental Psychology: General, 108, 356388. Hasher, L., & Zacks, R. T. (1984). Automatic processing of fundamental information: The case of frequency of occurrence. American Psychologist, 39,1372-1388. Humphreys, M. S, Bain, J. D, & Pike, R. (1989). Different ways to cue a coherent memory system: A theory for episodic, semantic, and procedural tasks. Psychological Review, 96, 208-233. Jones, E. E. (1986). Interpreting interpersonal behavior: The effects of expectancies. Science, 234, 41-46. Jones, E. E., & McGillis, A. (1976). Correspondent inferences and the attribution cube: A comparative reappraisal. In J. H. Harvey, W J. Ickes, & R. R. Kidd (Eds.), New directions in attribution research (Vol. 1, pp. 389-420). Hillsdale, NJ: Erlbaum. Kihlstrom, J. E (1987). The cognitive unconscious. Science, 237,14431452. Kimble, G. A. (1989). Psychology from the standpoint of a generalist. American Psychologist, 44, 491-499. Kirsch, I. (1985). Response expectancy as a determinant of experience and behavior. American Psychologist, 40,1189-1202. Lang, A. R., & Michalec, E. M. (in press). Expectancy effects in reinforcement from alcohol. In W M. Cox (Ed.), Why people drink: Parameters of alcohol as a reinforcer. New York: Gardner. Leigh, B. C. (1987). Beliefs about the effects of alcohol in self and others. Journal of Studies on Alcohol, 48, 467-475. Leigh, B, C. (1989a). In search of the seven dwarves: Issues of measurement and meaning in alcohol expectancy research. Psychological Bulletin, 705,361-373. Leigh, B. C. (1989b). Attitudes and expectancies as predictors of drinking habits: A comparison of three scales. Journal of Studies on Alcohol, 50, 432-440. MacCorquodale, K. M, & Meehl, P. E. (1954). Preliminary suggestions as to a formalization of expectancy theory. Psychological Review, 60, 53-60,125-129. Maisto, S. A, Conners, G. I, & Sachs, P R. (1981). Expectation as a mediator in alcohol intoxication: A reference level model. Cognitive Therapy and Research, 5,1-18. Mann, L. M., Chassin, L, & Sher, K. J. (1987). Alcohol expectancies and the risk for alcoholism. Journal of Consulting and Clinical Psychology, 55, 411-417. Marlatt, G. A. (1987). Alcohol, the magic elixir: Stress, expectancy, and the transformation of emotional states. In E. Gottheil, K. A. Druley, S. Pashko, & S. P. Weinstein (Eds.), Stress and addiction (pp. 302322). New York: Brunner/Mazel. Marlatt, G. A., Baer, J. S, Donovan, D. M., & Kivlahan, D R. (1988). Addictive behaviors: Etiology and treatment. Annual Review of Psychology, 38, 575-630. Massey, R., & Goldman, M. S. (1988, August). Manipulating expectancies as a means of altering alcohol consumption. Paper presented at the 96th Annual Convention of the American Psychological Association, Atlanta, GA. Miller, D. T, & Turnbull, W (1986). Expectancies and interpersonal processes. Annual Review of Psychology, 37, 233-256. Miller, P. G, Smith, G. T, & Goldman, M. S. (1990). Emergence of alcohol expectancies in childhood: A possible critical period. Journal of Studies on Alcohol, 51,343-349. Mooney, D. K., Fromme, K, Kivlahan, D. R, & Marlatt, G. A. (1987). Correlates of alcohol consumption: Sex, age, and expectancies relate differentially to quantity and frequency Addictive Behaviors, 12, 235-240. National Institute of Alcohol Abuse and Alcoholism. (1990) Seventh special report to the US. Congress on alcohol and health. Washington, DC: U.S. Government Printing Office.


146


Oei, T. P. S., & Jones, R. (1986). Alcohol-related expectancies: Have they a role in the understanding and treatment of problem drinking? Advances in Alcohol and Substance Abuse, 6,89-105. Peele, S. (1986). The implications and limitations of genetic models of alcoholism and other addictions. Journal of Studies on Alcohol, 4 7(1), 63-73. Rather, B, Levine, R, & Goldman, M. S. (1990, August). Multidimensional scaling for measuring alcohol expectancies. Paper presented at the 98th Annual Convention of the American Psychological Association, Boston, MA. Rescorla, R. A. (1988). Pavlovian conditioning. American Psychologist, «, 151-160. Roediger, H. L., III. (1980). Memory metaphors in cognitive psychology. Memory and Cognition, S, 231-246. Roehling, P. Y, Smith, G. T, Goldman, M. S., & Christiansen, B. A. (1987, August-September). Alcohol expectancies predict adolescent drinking: A three year longitudinal study. Paper presented at the 95th Annual Convention of the American Psychological Association, New York, NY Rogosa, D. (1980). A critique of cross-lagged correlation. Psychological Bulletin, 88. 245-258. Rohsenow, D. J. (1983). Drinking habits and expectancies about alcohol's effects for self versus others. Journal of Consulting and Clinical Psychology, 51, 752-756. Rosch, E, & Mervis, C. B. (1975). Family resemblances: Studies in the internal structure of categories. Cognitive Psychology, 7, 573-605. Rosch, E. H. (1975). Cognitive representations of semantic categories. Journal of Experimental Psychology: General. 104,192-233. Rotter, J. B. (1954). Social learning and clinical psychology. New York: Prentice-Hall. Searles, J. S. (1988). The role of genetics in the pathogenesis of alcoholism. Journal of Abnormal Psychology, 97(2), 153-167. Shapiro, A. K., & Morris, L. A. (1978). The placebo effect in medical and psychological therapies. In S. L. Garfield & A. E. Bergin (Eds.), Handbook of psychotherapy and behavior change: An empirical analysis (2nd ed., pp. 369-410). New York: Wiley. Sher, K. J., & Walitzer, K. S. (1989, November). Children of alcoholics and the search for mediators of risk. Paper presented at the 23rd Annual Convention of the Association for Advancement of Behavior Therapy, Washington, DC. Siegel, S., Krank, M. D., & Hinson, R. (1988). Anticipation of pharmacological and nonpharmacological events: Classical conditioning and addictive behavior. In S. Peele (Ed.), Visions of addiction (pp. 85-116). Lexington, MA: D. C. Health. Smith, G. T, & Goldman, M. S. (1990, August). Toward a mediational

model of alcohol expectancy. Paper presented at the 98th Annual Convention of the American Psychological Association, Boston, MA. Smith, G. T, Roehling, P. V, Christiansen, B. A, & Goldman, M. S. (1986, August). Alcohol expectancies predict early adolescent drinking: A longitudinal study. Paper presented at the 94th Annual Convention of the American Psychological Association, Washington, DC. Southwick, L, Steele, C, Marlatt, A, & Lindell, M. (1981). Alcohol-related expectancies: Denned by phase of intoxication and drinking experience. Journal of Consulting and Clinical Psychology, 49, 713721. Stacy, A. W, Widaman, K. E, & Marlatt, G. A. (1990). Expectancy models of alcohol use. Journal of Personality and Social Psychology, Attitudes and Cognition, 58,918-928. Tarter, R. E. (1988). Are there inherited behavioral traits that predispose to substance abuse? Journal ofConsulting and Clinical Psychology, 56(2), 189-196. Tesser, A., & Shaffer, D. (1990). Attitudes and attitude change. Annual Review of Psychology, 41, 479-523. Tolman, E. G. (1932). Purposive behavior in animals and man. New York: Appleton-Century-Crafts. Waldrop, M. M. (1988). Soar: A unified theory of cognition? Science, 241, 296-298. Wilson, G. T. (1987). Cognitive studies in alcoholism. Journal ofConsulting and Clinical Psychology, 55(3), 325-331. Wilson, T. D., Lisle, D. J, Kraft, D., & Wetzel, C. G (1989). Preferences as expectation-drive inferences: Effects of affective expectations on affective experience. Journal of Personality and Social Psychology, 56. 519-530. Wise, R. A. (1988). The neurobiology of craving: Implications for the understanding and treatment of addiction. Journal of Abnormal Psychology, 97,1 \S-132. Zajonc, R. B. (1980). Feeling and thinking: Preferences need no influences. American Psychologist, 35,151-175. Zucker, R. A. (1987). The four alcoholisms: A developmental account of the etiologic process. In P. Clayton Rivers (Ed.), Alcohol and addictive behavior, Nebraska Symposium on Motivation. 1986 Lincoln: University of Nebraska Press. Zucker, R. A, & Gomberg, E. S. L. (1986). Etiology of alcoholism reconsidered: The case for a biopsychosocial process. American Psychologist, 41, 783-793. Received September 19,1989 Revision received July 20,1990 Accepted September 9,1990 •

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