Positive and Negative Alcohol Expectancies. John Mc Mahon, Barry T Jones and Patrick O'Donnell. Department of Psychology. University of Glasgow. Glasgow ...
COMPARING POSITIVE AND NEGATIVE ALCOHOL EXPECTANCIES IN MALE AND FEMALE SOCIAL DRINKERS. Positive and Negative Alcohol Expectancies.
John Mc Mahon, Barry T Jones and Patrick O’Donnell
Department of Psychology University of Glasgow Glasgow G12 8QQ Scotland UK
Proofs and correspondence to: John Mc Mahon Barry T Jones at the above address
Submitted toAddiction Research May 1993 Resubmitted to Addiction Research August 1993 Accepted for publication in Addiction Research September 1993 Published 1994 1(4), 349-365. page 1.
COMPARING POSITIVE AND NEGATIVE ALCOHOL EXPECTANCIES IN MALE AND FEMALE SOCIAL DRINKERS. John Mc Mahon, Barry T Jones and Patrick O’Donnell ABSTRACT Negative alcohol expectancy has been poorly represented in empirical studies of alcohol consumption because (i) conceptions of negative expectancy have been limited and, as a result, (ii) tools to measure it have been crude.
In developing the Negative Alcohol
Expectancy Questionnaire (NAEQ), Mc Mahon and Jones have addressed this neglect. This paper demonstrates that when measured appropriately, negative expectancy rather than positive expectancy (as measured by the Alcohol Expectancy Questionnaire, AEQ) appears to be associated with consumption in social drinkers. Multiple stepwise regression analyses showed that for 163 subjects (81 males, 82 females): gender and proximal negative expectancies (those surrounding consumption) were associated with the consumption measure, units/session; gender and distal negative expectancies (those relating to the ‘next day’) were associated with sessions/week; gender and both proximal and distal negative expectancies were associated with units/week. For males: associations with units/session and sessions/week remained but only distal expectancies were associated with units/week. For females: distal negative expectancies and positive expectancies (sexual enhancement) were associated with units/session; age with sessions/week; age, proximal negative expectancies and positive expectancies (physical and social pleasure) with units/week. Although the results are discussed in terms of different drinking patterns and gender in a cultural context, the main goal of the paper is to report the largely unrecognised role that negative expectancy appears to have in social drinking when it is measured more extensively that has been the normal practice. keywords negative alcohol expectancy positive alcohol expectancy social drinking motivation gender page 2.
COMPARING POSITIVE AND NEGATIVE ALCOHOL EXPECTANCIES IN MALE AND FEMALE SOCIAL DRINKERS. INTRODUCTION During the 1980s the burgeoning literature on quantitative and qualitative aspects of alcohol expectancy firmly established it as both a predictor of drinking behaviour and a treatment focus.
Although the important role of alcohol expectancy in our understanding of
consumption decisions has been consistently demonstrated, the literature represents two notable neglects. Firstly, both clinical and non-clinical research has almost exclusively concentrated upon positive alcohol expectancy at the expense of negative. Secondly, with respect to expectancy, researchers have tended to make little of whatever gender differences have been found to exist. This study is principally designed (i) to explore and compare the explanatory utility of both positive and negative expectancy in drinking behaviour and, subsequently, (ii) to more fully examine the extent to which it might be different for males and females. The explanatory role of positive alcohol expectancy Research during the 1980s has defined both the content of positive alcohol expectancy and its relationship with consumption. Although it has attracted some criticism (for example, Leigh 1989ab, Collins et al 1990), the Alcohol Expectancy Questionnaire (AEQ, Brown et al 1980) best specifies the content of positive alcohol expectancy and remains the most widely-used instrument for measuring it. With the AEQ (and other similar instruments), two important relationships between positive expectancy and consumption have been established and have become part of the subculture of alcohol research.
For drinkers in general, higher levels of expectancy have been
associated higher levels of consumption (Brown et al 1985,
Leigh 1989b) and for
post-treatment problem drinkers, higher levels of expectancy have been associated with higher probabilities of relapse (Brown 1985, Connors et al 1988). Because of these two relationships, it has been frequently argued that an assessment of an individual problem drinker’s positive expectancy should provide a focus for interventions through which alternative and less harmful ways could be advanced of achieving the desired effects that alcohol consumption would otherwise be expected to bring (Mooney et al 1988, Brown et al 1988, Cox and Klinger 1988, Cox 1993, Brown 1993). page 3.
The status of negative alcohol expectancy In stark contrast to the extensive research literature on positive alcohol expectancies, negative expectancies have been relatively unresearched. As Mc Mahon and Jones (1993a) have argued, such research neglect is surprising for a number of reasons: First it has been well-recognised for some time that, within a cognitive framework, negative alcohol expectancies ought to have important potential explanatory utility with respect to alcohol decisions and there has been no shortage of reasoned calls for its study (Conners et al 1986, Mooney et al 1988, Leigh 1989b, Collins et al 1990, Adams and McNeil 1990, Fromme and Dunn 1992, Jones and Mc Mahon 1992, Mc Mahon and Jones 1992a). Second, negative alcohol expectancies have been shown to be involved in at least some alcohol decisions, for surveys of so-called spontaneous remitters’ reasons for stopping chronic over-consumption have shown that it is the expected negative consequences of continued drinking (negative expectancies) that did, in fact, cause them to stop (Tuchfield 1981, Ludwig 1985, Amodeo and Kurtz 1990, Tucker and Sobell 1992, Mc Mahon and Jones 1993b). Third, (in one of the earliest studies of negative expectancies we know and one that extends the likelihood of their involvement in recovery from alcohol problems from spontaneous remitters to those in treatment), Eastman and Norris (1982) reported a remarkable finding in which they used a repertory grid technique to assess alcohol outcome expectancies of subjects in a treatment program. They discovered that 77% of subjects holding positive alcohol expectancies subsequently relapsed whereas only 7% did of those holding negative expectancies! However, studies with non-problem drinkers have told a much less persuasive story and this has somewhat diluted the impact of the problem drinking studies referred to above and, in particular, Eastman and Norris’ otherwise instructive finding.
Although some of the
non-problem drinking studies have demonstrated an association between negative alcohol expectancy and consumption (Leigh 1987, Young and Knight 1989, Williams and Wortley 1991) others have found only a weak association (Stacey et al 1990) and still others have found no association at all (Southwick et al 1981, Rohsenow 1983) . Of course, one reason for this ambiguity might be that negative alcohol expectancies only surround problem drinking and that at much lighter levels of consumption, negative expectancies are either (i) absent - although this is unlikely since they have been previously measured in young adults (Williams and Wortley 1991), early teenagers (Christiansen et al 1982) and children (Casswell et al 1988) - or (ii) inoperative. There is a more compelling page 4.
reason, however, that suggests that these studies are not testing appropriately the relationship between negative expectancy and consumption because the range of negative expectancies that they sample is substantially incomplete. Consequently, Mc Mahon and Jones argue, the relationships that might otherwise be found, remain indeterminate. In developing their use of the concept of negative alcohol expectancy as a measure of motivation to restrain or stop drinking as opposed to positive expectancy as a measure of motivation to drink (Mc Mahon and Jones 1993a), Mc Mahon and Jones argue that negative expectancy should rise with consumption because as consumption rises (presumably under the control of positive expectancy) so, inevitably, will rise the frequency and intensity of negative consequences and these will normally translate to expectancies through learning. Subsequently, at some point, they claim, negative expectancy will reach levels at which it will begin to influence drinking decisions and drinking behaviour (although the mechanisms by which negative expectancy might be processed against positive has remained, largely, unresearched). Proximal and distal negative alcohol expectancies Mc Mahon and Jones (1993b) have distinguished between two types of negative expectancy - proximal and distal. Proximal negative expectancies are those that surround the activities of consumption, itself, and generally refer to the direct cognitive and behavioural consequences of the pharmacology of alcohol. Mc Mahon and Jones call these ‘same-day’ expectancies.
Distal negative expectancies, however, derive from the longer-term
consequences of alcohol use and refer to the expected consequences ‘next-day’ and, if drinking were to continue at the current rate, the expected consequences that come from ‘prolonged-use’. For example, a same-day negative expectancy might be unruly behaviour in public or difficulty in stopping drinking once a particular episode has started; a next-day negative expectancy might be missing work or having the ‘shakes or sweats’ on waking and a prolonged-use negative expectancy might be losing a partner or job, ending up sleeping rough or becoming profoundly ill. Proximal negative expectancies are likely to have much less effect in terms of motivating drinking restraint than are distal negative expectancies, Mc Mahon and Jones claim. Many have either shown or speculated that the subsequent judgements that individuals make about the negative consequences that surround consumption, itself, are flawed for the information is not processed properly on input and is the basis of a whole range of misperceptions that considerably underestimate the negative nature of the accompanying consequences of page 5.
overconsumption (Tamerin et al 1970, Rohsenow 1983, Critchlow 1986, Oei and Jones 1986, Leigh 1987). This is not simply a feature of alcohol consumption for others have extended this observation to social judgements, in general (Sarason et al 1991). For these reasons, the lack of association or weak association found between negative alcohol expectancy, is unsurprising because the measures of negative expectancy that they describe were principally proximal. The relative contributions to consumption decisions of proximal and distal negative expectancies, however, is best put as an empirical question and this is what Mc Mahon and Jones have done in a series of discrete experiments (Jones and Mc Mahon 1992, Mc Mahon and Jones 1993bc). Using light, moderate, heavy and problem drinkers, they have shown positive expectancy to be a much less reliable predictor of consumption than negative expectancy when negative expectancy is measured in the wider and more appropriate fashion that they advocate and which was briefly described above. Mc Mahon and Jones have concluded that the, hitherto, inadequately-sampled negative expectancies and the consequent poor relationship found with drinking behaviour when put in explanatory competition with positive expectancy (particularly the frequently-quoted result of Rohsenow 1983) has, in all probability, led to the neglect of what should otherwise have been a fruitful line of enquiry for both theory and practice. In response to this, the following study is designed to more appropriately and realistically compare the relative contributions of positive and negative alcohol expectancies in non-problem or ‘social’ drinkers. METHOD Subjects 81 males (mean age 31, range 18-62 years) and 82 females (mean age 30, range 18-60 years), recruited from public places where there was seating, served as subjects. There were approximately 30% refusers.
18% of subjects were undergraduates.
The frequency
distribution across the age decade intervals for males and females was almost identical. 25% of males and 45% of females were light drinkers males (0-10, females 0-7 units of alcohol/week), 55% of males and 50% of females were moderate drinkers (11-35, 8-25 units/week) and 20% of males and 5% of females were heavy drinkers (>35, >25 units/week). A unit of alcohol is equivalent to one half pint of normal-strength beer/lager, a single pub measure of spirits (1/6 gill) or a glass of wine - imperial measures. page 6.
Measurements Three instruments of measurement were used: (i) a local Demographic and Drinking Details Questionnaire (3D), (ii) the Alcohol Expectancy Questionnaire (AEQ, Brown et al 1987) and (iii) the Negative Alcohol Expectancy Questionnaire (NAEQ: Mc Mahon and Jones 1993d, Jones and Mc Mahon 1993a, NIAAA 1993). Subjects were given the questionnaire pack to fill in themselves with the experimenter in attendance to deal with questions.
The order of presentation of the two expectancy
questionnaires was alternated within gender. Demographic and Drinking Details Questionnaire (3D): The 3D comprises a series of forty questions designed for non-problem drinkers and from which the following was collected for the current analysis: gender; age; average number of drinking episodes per week (frequency, F); average number of units per session (quantity, Q) and average number of units per week (consumption, QF). There are good reasons for using the F, Q and QF measures of drinking behaviour and for subsequently using each as a dependant variable in separate analyses. Knupfer (1966), Mäkelä (1978), Greenfield (1986), Fromme et al (1986) and Mooney et al (1987) have pointed to the fact that the frequently-used QF measure of consumption poorly represents drinking lives (it can be ambiguous for it does not capture ‘pattern’). For example, a particular QF measure of 21 beers could represent a frequent drinker who drinks little at each session (daily: a beer at lunch, a beer leaving work, a beer at supper) or represent an infrequent drinker who drinks only once a week, but verily heavily (Friday night: 21 beers). Moreover, Vogel-Sprott (1983) has shown that the F and Q measures of consumption are, in fact, orthogonal and if this is the case then they will have different causes. A QF measure used alone might, at best, muddy the true causal structure of drinking decisions or, at worst, create an artefactual one.
Consequently, investigations that attempt to statistically or
causally relate alcohol beliefs to alcohol behaviour (as does this study) should pay attention to not only the coarse-grain measures (QF) but also the finer-grain measures of consumption (F and Q). Alcohol Expectancy Questionnaire (AEQ): The AEQ comprises 90 items which relate to expected positive consequences of alcohol consumption. Only 68 of the items are scored. Subjects are asked whether they agree or otherwise with each item. Responses are scored 1 for ‘agree’ 0 for ‘disagree’. Scores from page 7.
items on each of six subscales (global positive change; physical and social pleasure; sexual enhancement; social assertiveness; relaxation and tension reduction; arousal and aggression) are aggregated to produce subscale scores and the subscale scores, themselves, are aggregates to produce a total positive expectancy score (maximum 68). Negative Alcohol Expectancy Questionnaire (NAEQ): The NAEQ comprises 60 items relating to expected negative consequences of alcohol consumption. Subjects are asked to respond on a five-point Likert scale whether they expect the content of each of the items to happen to them. Responses are scored 1 for ‘highly unlikey’ and 5 for ‘highly likely’. The items, themselves, are grouped onto three subscales (same-day, next-day and continued-drinking expectations as described in the introduction) and subscale totals produced by aggregating item scores appropriately.
The next-day and
continued-drinking subscales together form the distal expectancy subscale and the same-day, the proximal. A total negative expectancy score is produced by aggregating the three subscale totals (maximum 300). RESULTS In the pooled analysis, the relationship between the four independent variables gender, age, positive expectancy and negative expectancy and the dependent variable, consumption, was explored using stepwise multiple-regression analyses. The three measures of consumption (F, Q and QF) were used as dependent variables in three parallel analyses. Each of the three parallel analyses was conducted at the four levels described below in an effort to systematically examine the relative contributions of the expectancies.
The four levels
represent the inclusion of increasingly finer-grain measures of both negative and positive expectancy along with the ‘static’ variables, gender and age: Level I, positive and negative expectancy total scores; Level II, positive expectancy total scores and two scores representing the two negative expectancy subscales (proximal and distal); Level III, the conventional six positive expectancy subscale scores and the two scores representing the two negative expectancy subscales (proximal and distal) and Level IV, the conventional six positive expectancy subscale scores and the three scores representing the three negative expectancy subscales (same-day, next-day and continued-drinking). In the by-gender analysis, the analysis described above was repeated separately for men and women. The F-to-enter to build the regression models was set at 1, throughout (the default value of the statistical package, Statistica/Mac) . page 8.
The correlation matrix for the variables contained in these two analyses is shown in Table 1. In common with previous findings, consumption measures Q and F are correlated with the composite measure, QF, but not with each other indicating the need for separate analyses with Q and F as dependent variables. ______________________________________________ Insert Table 1 about here ______________________________________________ The correlations between total positive expectancy and consumption were smaller than negative and this also applied to the expectancy subscales in general. Pooled analysis Table 2 contains the variables that, from stepwise multiple-regression analyses, had reliable beta values at any of the four levels of analysis and for each of the three parallel consumption measures. Level I Variables: gender, age, positive (total) and negative (total) expectancy. The two variables gender and total negative expectancy were reliably associated with the number of sessions per week (frequency) and between them account for 9% of the variance (derived from the adjusted multiple R2). Neither age nor total positive expectancy were reliably associated with frequency. The same reliable (but stronger) associations were found with the consumption measure of units/session (quantity) in which 26% of the variance was explained and also for units/week in which 29% of the variance was explained. Again, neither age nor total positive expectancy formed reliable associations with quantity or units/week. Level II Variables: gender, age, positive (total) and negative (2 subscales) expectancy. When the negative expectancy totals are cast onto the two subscales of proximal and distal expectancy, the association between gender and consumption remained reliable. Consistent with the Level I analysis, the association was considerably stronger for quantity and units/week than for frequency. ______________________________________________ Insert Table 2 about here ______________________________________________ Neither age nor positive expectancy made a reliable contribution to the regression equation for any of the measures of consumption. page 9.
Table 1 Correlation matrix upon which the analysis is based.
Gender Gender Age P-global P-sexual P-pleasure P-assert P-relax P-arousal P-total N-same N-next N-cont N-distal N-total Q F QF
Age -0.086
-0.170 -0.041 -0.238 -0.132 -0.172 -0.425 -0.226 -0.441
-0.214 -0.236 -0.080 -0.206 -0.217 -0.098 -0.042 -0.060
P-global P-sexl P-please P-assert P-relax P-arousal P-total -0.059 -0.148
0.134 0.029 0.436
0.342 0.131 0.283 -0.009 0.211 0.053 0.297 0.016 0.347 0.090 0.214 0.088 0.101 -0.039 0.214 0.008
-0.035 0.014 0.497 0.454
0.282 0.106 0.071 0.107 0.205 0.172 0.097 0.1126
N-same N-next N-cont N-distal N-total Gender Age P-global P-sexual P-pleasure P-assert P-relax P-arousal P-total N-same N-next N-cont N-distal N-total Q F QF
-0.170 -0.214 0.342 0.131 0.281 0.337 0.096 0.299 0.331
-0.041 -0.236 0.282 -0.009 0.101 0.162 0.010 0.151 0.172 0.606
-0.238 -0.132 -0.080 -0.207 0.210 0.347 0.053 0.016 0.071 0.107 0.150 0.182 0.061 0.033 0.169 0.184 0.170 0.203 0.487 0.650 0.457 0.925 0.761
-0.172 -0.217 0.297 0.089 0.205 0.264 0.076 0.262 0.288 0.864 0.862 0.709 0.932
-0.094 -0.224 0.570 0.417 0.574
0.039 0.118 0.602 0.597 0.601 0.529
0.024 -0.239 0.509 0.406 0.466 0.525 0.469
0.032 -0.111 0.850 0.684 0.730 0.791 0.821 0.700
0.339 0.162 0.150 0.182 0.264 0.199 0.016 0.126
0.096 0.010 0.061 0.033 0.076 0.067 -0.013 0.008
0.299 0.153 0.169 0.184 0.263 0.123 0.048 0.060
0.331 0.179 0.170 0.203 0.287 0.196 0.050 0.136
Q
F
QF
-0.425 -0.098 0.214 0.088 0.172 0.200 0.067 0.123 0.196 0.415 0.283 0.313 0.340 0.406
-0.226 -0.042 0.100 -0.039 0.097 0.01 -0.013 0.048 0.050 0.264 0.293 0.242 0.317 0.327 0.077
-0.441 -0.060 0.214 0.008 0.126 0.126 0.008 0.060 0.136 0.410 0.399 0.354 0.442 0.465 0.721 0.639
Note the negative expectancy subscales ‘same-day’ and ‘proximal’ are the same subscales.
page 10.
Table 2 Pooled subjects analysis: reliable beta values and multiple/adjusted R2s from stepwise regressing a systematically-increasing range of subject variables upon consumption, males and females combined (n=163)
I 4 variables: gender, age, pos (total) , neg (total) Variable sess/wk F units/sess Q units/wk QF Gender Neg (total) Multiple R2 Adjusted R2
-0.189* 0.230** 0.106*** 0.093
-0.364*** 0.314***
-0.370*** 0.338***
0.273*** 0.263
0.296*** 0.287
II 5 variables: gender, age, pos (total), neg (2 subs) Variable sess/wk units/sess units/wk Gender Neg (proximal) Neg (distal) Multiple R2 Adjusted R2
0.213**
-0.360*** 0.350*** _
-0.375*** 0.319*** 0.199*
0.098*** 0.086
0.295*** 0.286
0.285*** 0.276
-0.199*** _
III 10 variables: gender, age, pos (6 subs), neg (2 subs) Variable
sess/wk
units/sess
units/wk
Gender Neg (proximal) Neg (distal)
-0.199** _ 0.213**
-0.360*** 0.348*** _
-0.375*** 0.319*** 0.199*
0.098*** 0.086
0.295*** 0.286
0.285*** 0.276
Multiple R2 Adjusted R2
IV 11 variables: gender, age, pos (6 subs), neg (3 subs) Variable
sess/wk
Gender -0.215** _ Neg (same-day) Neg (next-day) 0.223** Multiple R2 Adjusted R2
0.103*** 0.092
units/sess
units/wk
-0.360*** 0.348*** _
-0.348*** 0.184* 0.207*
0.295*** 0.286
0.310*** 0.297
Note: * for 0.05 ≥ p > 0.01; ** for 0.01 ≥ p > 0.0001; *** for p ≤ 0.0001 page 11.
This level of analysis was designed to help established where the reliable contribution demonstrated at Level I by total negative expectancy was located: proximal or distal. The analysis showed that distal (not proximal) negative expectancy was reliably associated with frequency of consumption whereas proximal (not distal) negative expectancy was associated with quantity consumed per session. Both proximal and distal negative expectancy were reliably associated with the consumption measure, units/week. Gender and proximal/distal expectancy, together, accounted for 9%, 29% and 28%, respectively, of the variance in the consumption measures of frequency, quanity and units/week. Level III
Variables:
gender, age, positive (6 subscales) and negative (2 subscales)
expectancy. Casting total positive expectancy onto the six conventionally-used positive expectancy subscales of the AEQ did not reliably bring either age or any subscale of positive expectancy into the regression equation. The outcome of the analysis at this level for gender and proximal/distal negative expectancy was identical to Level II. Level IV
Variables:
gender, age, positive (6 subscales) and negative (3 subscales)
expectancy. In this analysis, the two negative expectancy subscales (proximal and distal) were replaced by the three negative expectancy subscales same-day (equivalent to proximal), next-day and continued-drinking (when combined, equivalent to distal) to better identify where the negative expectancy effects were located. In common with the other analyses, gender was reliably associated with each of the three measures of consumption but more strongly with the measures quantity and units/week than frequency. Age and positive expectancy did not reliably contribute. Also in common with earlier analyses, distal negative expectancy was reliably associated with frequency of consumption; proximal negative expectancy was reliably associated with quantity consumed per session and both proximal and distal negative expectancy was reliably associated with units/week. What the Level IV analysis shows is that whenever distal negative expectancy makes a reliable contribution to the regression equation, the contribution comes from next-day and not continued-drinking negative expectancy. page 12.
Together, gender and same-day/next-day negative expectancy, accounted for 9%, 29% and 30%, respectively, of the variance in the consumption measures of frequency, quanity and units/week. In brief summary, these results show gender and negative expectancy to be related to alcohol consumption whereas age and positive expectancy are not. The results also show where the origin of the negative expectancy is (temporally) located. By-gender analysis Males The outcome of the stepwise multiple-regression analyses carried out with the 81 male subjects corresponded in very close detail to the outcome of the analyses with the combined subject pool of 163 (see Table 3). In summary: neither age nor any scale or subscale of positive expectancy formed reliable associations with the three dependent variables; frequency formed weaker and less reliable associations with negative expectancy than did consumption; the anomalous proximal/consumption-distal/frequency associations were present and reliable and distal negative expectancy was reliably confined to the next-day subscale. Although the reliablility of the multiple-R2s was generally reduced as compared with the pooled analyses, the beta-values of the reliable negative expectancy variables were increased. Indeed, for the negative expectancy subscales reliably associated with consumption, values as high as 0.381 and 0.429 were obtained. ______________________________________________ Insert Table 3 about here ______________________________________________ There was one notable and important difference, however: even though the anomalous proximal/consumption-distal/frequency associations were present and reliable in males, no reliable association between proximal negative expectancy and the combined measure (frequency x consumption) was found. Females The outcome of the stepwise multiple-regression analyses carried out with the 82 female subjects showed a number of differences from both the outcome of the analyses with the combined subject pool of 163 and also from the 81 males (see Table 3). Unlike males (and the combined pool), age appeared to be reliably and negatively associated with frequency. Indeed, it appeared to be the only variable associated with frequency for females. Whilst there was no association between age and consumption for females, there page 13.
Table 3 By-gender analysis: reliable beta values and multiple/adjusted R2s from stepwise regressing a systematically-increasing range of subject variables upon consumption for males (n=81) and females (n=82).
Variables
Males (n=81)
Females (n=82)
I 3 variables: I 3 variables: age, pos (total) , neg (total) Variable sess/wk F units/sess Q units/wk QF sess/wk F units/sess Q units/wk QF _
_
Age Neg (total)
0.252*
0.381**
Multiple R2 Adjusted R2
0.063* 0.051
0.146** 0.137
_ 0.386**
0.293**
-0.239* 0.366***
0.147** 0.136
0.059* 0.046
0.086** 0.075
0.226*** 0.206
II 4 variables: age, pos (total), neg (2 subs) Variable sess/wk units/sess units/wk Age Neg (proximal) Neg (distal) Multiple R2 Adjusted R2
_ _
_
_ _
Multiple R2 Adjusted R2
0.263*
0.429*** _
0.366**
0.069* 0.057
0.185*** 0.174
0.135** 0.123
0.059* 0.046
_ _ _
_ _
_ _ _
0.263*
0.429*** _
0.366**
0.069* 0.057
0.184*** 0.174
0.134** 0.123
0.059* 0.046
Multiple R2 Adjusted R2
_ _ _ _
_ _ _
_ _ _ _
0.276*
0.429*** _
0.389**
0.076* 0.064
0.184*** 0.174
0.150** 0.139
_ _ 0.281* 0.079* 0.068
III 10 variables: sess/wk units/sess -0.240* _ _ _
IV 11 variables: age, pos (6 subs), neg (3 subs) Variable sess/wk units/sess units/wk Age Pos (sex) Pos (pleasure) Neg (same-day) Neg (next-day)
II 4 variables: sess/wk units/sess -0.240* _ _
III 10 variables: age, pos (6 subs), neg (2 subs) Variable sess/wk units/sess units/wk Age Pos (sex) Neg (proximal) Neg (distal)
_
-0.240* _
_ 0.270* _ 0.281** 0.153** 0.131
IV 11 variables: sess/wk units/sess -0.240** _ _ _ _ 0.058* 0.046
_ 0.265* _ _ 0.333** 0.185** 0.163
units/wk -0.223* 0.368** _ 0.225*** 0.205
units/wk -0.223* _ 0.368** _ 0.225*** 0.205
units/wk -0.271** _ 0.203* 0.342** _ 0.281*** 0.253 page 14.
was a reliable association between age and the combined measure. Again, unlike males (and the combined pool), distal negative expectancy was reliably associated with consumption and proximal was associated with neither. With the combined measure, however, the reliable association was only with proximal. Finally, for females, when the six subscales of positive expectancy were included in the analysis (Level III), the subscale, sex enhancement, was found to be reliably associated with consumption (but not frequency). However, when the dependent variable was the combined measure and the analysis was extended to include the three subscales of negative expectancy (Level IV), it was the positive expectancy subscale, pleasure, that was found to form a reliable association. DISCUSSION . Pooled analysis Unsurprisingly, the robust finding that male drinkers consume more than females (Dawson and Archer 1992) is replicated here. What is surprising in light of the research reported during the last decade, however, is that positive alcohol expectancy does not appear to feature in the equation when it is assessed against (or in conjunction with) negative alcohol expectancy. The only difference between this study and those few earlier ones in which positive and negative expectancies have been put ‘head to head’ and in which the relative explanatory utility of positive expectancy has been demonstrated, is that a more extensive and representative range of negative expectancies has been employed. Once attention is paid to this neglect the relative explanatory utility of the two types of expectancy used in this study appears to be reversed and the potential importance of negative expectancy is revealed. Of the two direct measures of drinking most frequently used in alcohol research (frequency of session, F, and consumption per session, Q), stronger associations between variables entered into the regression equation (gender and negative expectancy) and Q were found than with F. This is consistent with an earlier study by Fromme et al (1986) who found a similar asymmetrical association between these measures of consumption and positive expectancy. In common with many (maybe most) studies that have explored alcohol beliefs, Fromme et al used college/university students as subjects and speculated that, with such a group, F is largely governed by opportunity (a factor outside their control) and, consequently, the relatively weak association between positive expectancy and F might be expected. However, once an opportunity to drink had arisen and been taken, they argued, Q would be more under cognitive control and a much stronger association between positive page 15.
expectancy and Q might be expected. This is also consistent with earlier speculation by Vogel-Sprott (1974). It now seems there is no reason why an explanation that includes ‘opportunity’ cannot be extended to consumers, in general, because in the current study only 18% of subjects were students. While the general association between negative expectancy and consumption has been demonstrated in the current study, the results display a curious anomaly. How can the fact that proximal negative expectancy has been shown to be reliably implicated in consumption in the current study be reconciled with Mc Mahon and Jones’ claim that during the last decade it is through mistakenly paying attention to only proximal expectancies at the expense of distal that the relative importance of negative expectancy has been missed? In answer to this, it is important to note that not only have Mc Mahon and Jones extended the horizons of negative expectancy distally (next-day and continued-drinking), they have also extended them proximally. For whereas earlier studies appear to have concentrated their measures simply upon a relatively small number of cognitive/behavioural features (which are proximal), Mc Mahon and Jones (1993b) have extended these to include other important negative expectancies that their survey has shown accompany consumption (and are therefore proximal, too). For example, they have included a range of items that relate to affective states (anxiety, depression); to the direct and indirect control that individuals expect to have (or not have) over their consumption and to individuals’ expected ability (or inability) to avoid or deal with a number of situations that would otherwise, if alcohol were not involved, cause no problem. Consequently, Mc Mahon and Jones’ own measure of proximal negative expectancy is a more extensive and realistic measure of the expected negative consequences that surround consumption. It is not inevitable, therefore, that the (proximal) measure of negative expectancy used by others in earlier studies demonstrates the same associations as does the proximal measure used by Mc Mahon and Jones. Indeed, given the much more extensive range of proximal expectancies used within Mc Mahon and Jones’ NAEQ, it might be surprising, perhaps, if it did. This explanation of the anomaly begs a second question. Why is proximal expectancy only associated with Q and distal (next-day) with F? In principle, at least, this should not surprise, for Mooney et al (1987) and Williams and Wortley (1991) have shown that different types of positive expectancy (AEQ subscales) associate with measures of F and Q and there is no reason why it should be any different for different types of negative expectancy (NAEQ subscales). In practice it should not surprise, either. Greefield (1986), for example, provides a priori, theoretical and empirical grounds for the speculation that page 16.
“the consequences of frequently drinking small amounts (vs imbibing less often but copiously) could be very different” (the current authors’ emphasis). Consequently, if there were, indeed, two types of individual with different patterns of consumption, as Greenfield suggests, then there should be two different types of individual with commensurately different negative expectancy profiles, too. Infrequently heavy consumers would almost certainly be surrounded by more proximal negative consequences than would frequent light consumers even though both might have the same overall consumption (QF) and, consequently, they would devlop more proximal negative expectancies. For this reason, in such drinkers, proximal negative expectancy might be more associated with Q than F and this is just what the analyses in Table 2 show. However, this raises the difficult question of why there is no relationship between consumption per session and distal (next-day) negative expectancy. For if there is inebriation (or even subinebriation), should there not also be negative consequences next day? One can only speculate that under normal circumstances only one source of (‘concurrent’) negative consequence is capable of affecting cognition and, if this were the case, the results suggest it is the same-day rather than next-day consequences that ‘win out’. Support for this view is derived from within the animal learning field where evidence of the ‘blocking’ of one association by another is not uncommon and this framework has been successfully extended towards animal addiction (Dafters et al 1983). Although the association between proximal negative expectancy and Q fits fairly comfortably into Greenfield’s drinking typology, it is difficult to see how this typology can account for the association between distal (next-day) expectancy and F. Unfortunately, the fact that only 65 of the subjects in the current study displayed drinking patterns that unambiguously match Greenfield’s has made it difficult to determine whether the reliable associations formed with Q and F represent the drinking patterns and alcohol beliefs of the two different groups of individuals described above or whether they are represented within the cognitive life of them all. By-gender analysis When gender is removed from the regression analyses, there is a strong and reliable association between weekly consumption, QF, and proximal negative expectancy for females but between QF and distal negative expectancy for males. What this suggests is that the earlier explanation in terms of drinking patterns, per se, of the dual association of proximal and distal negative expectancy with QF found in the pooled analyses, might have been premature. For, through the by-gender analyses, it appears that the origins of the page 17.
proximal and distal negative expectancies found in the pooled analyses might be through gender, itself.
(Of course, this might well entail different drinking patterns, but not
necessarily so.) How might these gender-different assocations with negative expectancy originate? If, as they most surely do, negative expectancies of alcohol use partly derive through learning from repeated negative consequences, then an individual’s own perception of the consequences becomes an important factor in the learning equation (and, thereby, an important factor in the development of negative expectancy, itself - Bauman and Bauman 1980, Bauman et al 1985, Leigh 1989b, Jones and Mc Mahon 1992, Mc Mahon and Jones 1993b). In most cultures and societies, one of the most secure observations is that the negative consequences surrounding consumption (proximal consequences) are tolerated more in males than in females. This would mean that a particular negative consequence of consumption that an individual might experience would generally be judged more ‘negative’ by the individual if they were female than if they were male. The development of proximal negative expectancies in females would, therefore, occur more readily than in males. Indeed, in empirical support of this explanation, it has been shown with respect to behavioural impairment that as a result of drinking alcohol, females have considerably more negative expectancies than do males (Leigh 1987).
These negative expectancies of
behavioural impairment (which is what they primarily were in Leigh’s study) form a component of Mc Mahon and Jones’ assessment of proximal negative expectancy using the NAEQ. Moreover, if, as is the case in most cultures and societies, males drink more than females nomatter what measure is used, then the aftermath of consumption (the next-day negative consequences) should be more ‘negative’ in males than in females. The development of distal (next-day) negative expectancies in males would, therefore, occur more readily than in females. It is suggested, here, that these ‘by-gender’ reasons account for the appearance of the associations between QF and proximal and distal negative expectancy identified earlier in the pooled data. It is difficult to know whether an account of these associations based upon infrequent heavy and frequent light drinking patterns is confounded with gender, derived from gender or quite independent of it. Unfortunately, the results of the by-gender anaylses are much less orderly when F and Q measures are used as dependent variables in place of the composite measure, QF. (Of course, this might simply be due to the fact that the by-gender analyses have sample size reductions of 50%.) For males, the profile obtained in the current analysis mirrors the page 18.
profile obtained with the earlier pooled analyses. For females, though, it is quite different: there are no associations between F and negative expectancy, only between Q and distal negative expectancy. However, the by-gender analysis shows that age is associated with F and QF for females but not for males and this would be expected in females (particularly the association with frequency which was also found by Mooney et al) and most probably represents a cohort effect. But if age is, indeed, a strong predictor of drinking frequency in females (as compared with males), then its presence in the by-gender analyses might easily overshadow other (weaker) associations for females that it is not doing for males. This might account for the difference in orderliness in males and females for the other associations that the by-gender analyses clearly reveal. Finally, for women, there appears to be an association between one of the subscales of positive expectancy, sexual enhancement, and Q. This association disappears when QF is used and is replaced by an association with the positive expectancy subscale, physical/social pleasure. It is not difficult to imagine either of these subscales forming valid associations. Perhaps what is surprising, though, is that the associations are not found in males and, even more surprising still (based upon a wealth of findings published during the last decade), is that for both males and females more positive expectancy subscales are not implicated. Conclusion Mc Mahon and Jones have argued that just as positive alcohol expectancy represents a component of motivation to drink, so does negative alcohol expectancy represent a component of motivation to restrain drinking. Whilst the former has enjoyed more than a decade of being at the core of expectancy research, surprisingly, the latter has not. In a different study, Jones and Mc Mahon (1993b) have demonstrated the importance of both negative and positive expectancies in predicting post-treatment consumption in problem drinkers and in doing so have supported and augmented the finding of Brown et al (1988), the only other study that has investigated alcohol beliefs in relation to post-treatment problem drinking and in which evidence of a role for only positive expectancy was sought. In the current study, Mc Mahon and Jones extend the same motivational argument to non-problem drinking and have found negative expectancy to be more closely associated with drinking decisions than is positive. Of course, with respect to drinking decisions, there remain the vexed problems of whether these different motivations or expectancies represent truly discrete entities or different page 19.
aspects (or ways of measuring) the same unitary whole (Leigh 1989, Mc Mahon and Jones 1993c); whether personality variables and more extended aspects of the individual’s cognitive life are involved (Cox and Klinger 1988, Cox 1993) and whether the investigative procedures used to help discover the structures used within decision making and the processes of decision making, itself, are capable of providing valid information (Davies 1993). This range of problems, however intriguing and important it might be, should not divert attention away from the more fundamental problem in researching drinking decisions: that the tendency to drink has been vigorously investigated whereas the tendency not to, has not. The major purpose of this paper has been to report on the apparant involvement of negative alcohol expectancy in drinking decisions, for this observation is poorly represented in the subculture of alcohol research. ACKNOWLEDGEMENTS This work was supported by Scottish Office Home and Health Department Research Training Fellowship K/OPR/2/3/82 held by the first author supervised by the second and Alcohol Education and Research Council Grant R6/92 held by the first two authors.
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