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Personality risk and alcohol consumption: A latent variable analysis
Addictive Behaviors, Vol. 15, pp. 183-187, Primed in the USA. All rights reserved.
1990 Copyright
0306-4603/90 $3.00 + .OO Q 1990 Pergamon Press plc
BRIEF REPORT PERSONALITY RISK AND ALCOHOL CONSUMPTION: A LATENT VARIABLE ANALYSIS MITCHELL
EARLEYWINE,
PETER R. FINN, and CHRISTOPHER Indiana University
S. MARTIN
at Bloomington
between measures of personality and Abstract - Several studies report modest correlations measures of alcohol consumption. These results have led many to conclude that the relation between personality characteristics and drinking is weak, and that studying such a relation may not be fruitful. Nevertheless, the magnitude of the correlations between measures of certain personality characteristics and drinking may be attenuated due to the imperfect reliability of the measures. By viewing specific measures of personality and alcohol consumption as fallible indicators of underlying constructs, and using confirmatory factor analysis to estimate the relation between them, a correlation of .80 was found, implying that the relation between personality and drinking may be stronger than correlational analyses suggest.
Given the numerous situation-specific determinants of alcohol use, simple explanations linking personality and drinking have often been viewed as myopic (Sutker & Allain, 1988). Although data have failed to support the notion of a single alcoholic personality (Gaines & Connors, 1982), modest relations between personality measures and the use of alcohol have been established (Rohsenow, 1982; Stein, Newcomb, & Bentler, 1987). Current data that reveal only a modest link between certain personality measures and measures of consumption may not reflect the actual relation between these underlying constructs of personality and drinking partly because of problems with the reliability of the measures. The correlation between two theoretical constructs is underestimated when measures contain error (Lord & Novik, 1968; Nunnally , 1978). Measures that are not perfectly reliable may fail to reveal a relation between two constructs when one actually exists, increasing the chances of a Type II error (failing to reject a false null hypothesis). Because the hypotheses concern the constructs rather than their imperfect measures, latent variable analyses, such as confirmatory factor analysis, may correct this problem by optimally weighing multiple indicators of each construct and correcting for measurement error. The use of confirmatory factor analysis to estimate the relation between estimates of true scores unaffected by measurement error has already revealed strong links between personality measures and job satisfaction (Reuman, Alwin, & Veroff, 1984), and social skills (Cole, Howard, & Maxwell, 1981). This study was designed to use these methods to investigate the relation between personality and drinking. The MacAndrew (MacAndrew, 1965) and Socialization (Gough, 1969) scales, two measures of personality that have been related to drinking, tend to reflect outgoing, impulsive, and aggressive tendencies. The MacAndrew scale, which was designed to discriminate between alcoholic patients and psychiatric controls, has also predicted subse-
We thank David Kessler and Laura Stith for their adept data collection. Special thanks to Rick Viken and Cara Wellman. This research was supported in part by NIMH Clinical Training Grant PHS T32 MH 17146-05 to the fmt author. Requests for reprints should be sent to Mitchell Earleywine, Ph.D., Psychology Building, Indiana University, Bloomington, IN 47405. 183
184
M. EARLEYWINE,
Table 1. Correlations,
P.R. FINN, and C.S. MARTIN
means, and standard deviations 1
1. 2. 3. 4.
Quantity Frequency MacAndrew Socialization
2
.45* .30* - .33*
.28* - .24*
for measures
3
M
SD
- .29*
3.05 1.75 19.27 35.62
2.96 1.22 3.58 5.64
M = mean. SD = standard deviation. p < .ool.
quent alcoholism in non-alcoholic males (Hoffman, Loper, & Kammeier, 1974). Individuals with high scores on this scale were rated as immature and assaultive (Lachar, Berman, Grissell, & Schoof, 1976), and have been described as bold, uninhibited, self-confident, and sociable (Finney, Smith, Skeeters, & Auvenshine, 1971). The Socialization scale has not been linked to alcoholism or consumption directly, but studies reveal that individuals with low scores on this scale are more likely to show stress-response-dampening after consuming alcohol. (Levenson, Oyama, & Meek, 1987; Sher & Levenson, 1982). This stressresponse-dampening, a decreased cardiovascular reactivity to stress, has also been found in individuals considered at elevated risk for alcoholism because of extensive family histories of alcoholism (Finn & Pihl, 1987). The Socialization scale was designed to measure degree of social maturity, and low scorers tend to be seen as rebellious, ostentatious, and defensive (Gough, 1969). These two scales can be viewed as measures of behavioral inhibition, and the attitudes and behaviors they survey may be associated with increased risk for excessive alcohol use. METHOD
Two hundred and two undergraduate men completed the MacAndrew (MacAndrew , 1965) and Socialization (Gough, 1969) scales, as well as a measure of quantity and frequency of alcohol use adapted from Cahalan and Cisin (1968), to partially fulfill a course requirement. Overlapping items from the two personality scales were counted toward the score of only one scale (Socialization), in order to avoid an artificially inflated correlation between the measures. In addition, any items that specifically referred to alcohol were omitted. After these two conditions were satisfied, the Socialization scale had 52 items; the MacAndrew had 44. Quantity was measured as the average number of drinks per drinking episode. Frequency was the number of times per week alcohol was consumed. RESULTS
The correlations, means, and standard deviations of the four measures are presented in Table 1. Note that although these correlations are statistically significant, they account for only a small percentage of the variance (r2 from 6 to 8%). In order to examine the relation between the latent variables we analyzed the correlation matrix using Joreskog and Sorbom’s (1986) LISREL program. The specified model restricted the solution to two factors, labeled here as behavioral inhibition and drinking. The model specified two measures for each construct. Quantity and frequency of alcohol use were used as separate measures of drinking. This arrangement is preferable to multiplying the two to serve as a single index. Combining quantity and frequency could mask a relation should behavioral inhibition relate to one or the other but not both (Apao & Damon, 1982). This
Personality
185
and alcohol consumption
QUANTITY
DRINKING
FREQUENCY
-.796
PERSONALITY
SOCIALIZATION
Fig. 1, Parameter
estimates and model specifications
relating behavioral
inhibition
and drinking.
arrangement also allows assessment of differences between individuals who consume the same amount of alcohol in a given week, but who have a different number of drinking occasions. MacAndrew scale and Socialization scale scores served as the measures of behavioral inhibition. The two factors were allowed to correlate in order to estimate the true relation between them. The analysis generates goodness of fit indices that test the degree to which the data fit the specified model. The model produced a nonsignificant chi-square of .63, p > .4, meaning that the correlation matrix did not differ significantly from a matrix that is consistent with the specified model. The goodness-of-fit index of .99, the adjusted goodness-of-fit index of .98, and a root mean square of residuals of .Ol 1 all suggest that the model provided a good fit to the data. The estimate of the correlation between the latent variables (drinking and behavioral 62% of the variance. Parameter inhibition) was - .796, accounting for approximately estimates and an illustration of the model appear in Figure 1. The possibility exists that all four of these measures (MacAndrew, Socialization, Quantity, and Frequency) actually reflect a single construct of self-report tendencies. An alternative model, using a single latent variable labeled here as self-report, used all four questionnaires as measures of this construct. This model produced a marginally significant chi-square of 3.14, p < .076, implying that the correlation matrix differed from one that
186
M. EARLEYWINE,
P.R. FINN, and C.S. MARTIN
would be consistent with a model using a single latent variable. The goodness-of-fit index equalled that of the two factor model (.99), but the adjusted goodness-of-fit index was smaller (.92) and the root mean square residuals was larger (.029) relative to the previous model. This analysis suggests that the data are more consistent with a two factor model of behavioral inhibition and drinking, than a one factor model of self-report tendencies. DISCUSSION
Standard correlations between personality measures of behavioral inhibition and quantity and frequency measures of alcohol consumption are statistically significant (p < .OOl) but do not account for a large percentage of variance. In this study, correlations between personality variables and measures of drinking ranged from magnitudes of .24 to .33. By using an alternative analysis, we discovered that when the relation is not attenuated by error in the measurement of the latent variables, the correlation between these two constructs increases to - .796. We obtained these data from college students, and the correlations of the measures as well as the relation between the two underlying constructs may differ for samples from other populations, such as problem drinkers or alcoholics. Nevertheless, this finding supports the notion that although situational factors may be important determinants of alcohol use, personality variables relate strongly to drinking as well. Although these data do not address the mechanism behind this relation between behavioral inhibition and alcohol consumption, the possibility exists that personality may help determine an individual’s situational as well as drinking factors, as certain individuals may prefer particular social environments that are frequently associated with drinking. Regardless of the mechanism behind this relation, the characteristics of an individual are stronger predictors of drinking behavior than was once believed, and deserve further investigation.
REFERENCES Apao, W.K., & Damon, A.M. (1982). Locus of control and the quantity-frequency index of alcohol use.. Journal of Studies on Alcohol, 43, 233-239. Cahalan, D., & Cisin, I.H. (1968). American drinking practices; summary of findings from a national probability sample. I. Extent of drinking by population subgroups. Quarterly Journal of Studies on Alcohol, 29, 13&151. Cole, D.A., Howard, G.S., & Maxwell, S.E. (1981). Effects of mono- versus multiple-operationalization in construct validation efforts. Journal of Consulting and Clinical Psychology, 49, 395-404. Finn, P.R., & Pihl, R.O. (1987). Men at high risk for alcoholism: The effect of alcohol on cardiovascular response to unavoidable shock. Journal of Abnormal Psychology, 96, 230-236. Finney, J., Smith, D., Skeeters, D., & Auvenshine, C. (1971). MMPI alcoholism scales: Factor structure and content analysis. Quarterly Journal of Studies on Alcohol, 32, 1055-1060. Gaines, L.S., & Connors, G.J. (1982). Drinking and personality: present knowledge and future. trends. In Alcohol consumption and related problems (pp. 331-346). Washington, DC: National Institute on Alcohol Abuse and Alcoholism. Gough. H.G. (1969). Manualfor rhe California Psychological Invenrory. Palo Alto, CA: Consulting Psychologists Press. Hoffman, H., Loper, R., & K-eier, M.L. (1974). Identifying future alcoholics with MMPI alcoholism scales. Quarterly Journal of Studies on Alcohol, 35, 490-498. Joreskog, K., & Sorbom, D. (1986). LISREL VI: User’s guide. Mooresville, IN: Scientific Software, Inc. Lachar, D., Berman, W., Grissell, J., & Schoof, K. (1976). The MacAndrew alcoholsm scale as a general measure of substance abuse. Journal of Studies on Alcohol, 37, 1609-1615. Levenson, R.W., Oyama, O.N., & Meek, P.S. (1987). Greater reinforcement from alcohol for those at risk: Parental risk, personality risk, and sex. Journal of Abnormal Psychology, 96, 242-253. Lord. F.M.. & Novik, M.R. (1968). Srarisrical theories of mental test scores. Reading, MA: Addison-Wesley. MacAndrew, C. (1965). The differentiation of male alcoholic outpatients from nonalcoholic psychiatric outpatients by means of the MMPI. Quarterly Journal of Studies on Alcohol, 26, 238-246. Nunnally, J.C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill. Reuman, D., Alwin. D., & Veroff, J. (1984). Assessing the validity of the achievement motive in the presence of random measurement error. Journal of Personality and Social Psychology, 47, 1347-1362. Rohsenow, D.J. (1982). Social anxiety, daily moods, and alcohol use over time among heavy social drinking men. Addictive Behaviors, 7, 311-315.
Personality
and alcohol consumption
187
Sher, K.J., & Levenson, R.W. (1982). Risk for alcoholism and individual differences in the stress-responsedampening effect of alcohol. Journal of Abnormal Psychology, 91, 350-367. Stein, J.A., Newcomb, M.D., dc Bentler, P.M. (1987). Personality and drug use: Reciprocal effects across four years. Personality and Individual Diaerences, 8, 419430. Sutker, P.B., & Allain, A.N. (1988). Issues in personality conceptualizations of addictive behaviors. Journal of Consulting and Clincial Psychology, 56, 172-182.
1990 Copyright
0306-4603/90 $3.00 + .OO Q 1990 Pergamon Press plc
BRIEF REPORT PERSONALITY RISK AND ALCOHOL CONSUMPTION: A LATENT VARIABLE ANALYSIS MITCHELL
EARLEYWINE,
PETER R. FINN, and CHRISTOPHER Indiana University
S. MARTIN
at Bloomington
between measures of personality and Abstract - Several studies report modest correlations measures of alcohol consumption. These results have led many to conclude that the relation between personality characteristics and drinking is weak, and that studying such a relation may not be fruitful. Nevertheless, the magnitude of the correlations between measures of certain personality characteristics and drinking may be attenuated due to the imperfect reliability of the measures. By viewing specific measures of personality and alcohol consumption as fallible indicators of underlying constructs, and using confirmatory factor analysis to estimate the relation between them, a correlation of .80 was found, implying that the relation between personality and drinking may be stronger than correlational analyses suggest.
Given the numerous situation-specific determinants of alcohol use, simple explanations linking personality and drinking have often been viewed as myopic (Sutker & Allain, 1988). Although data have failed to support the notion of a single alcoholic personality (Gaines & Connors, 1982), modest relations between personality measures and the use of alcohol have been established (Rohsenow, 1982; Stein, Newcomb, & Bentler, 1987). Current data that reveal only a modest link between certain personality measures and measures of consumption may not reflect the actual relation between these underlying constructs of personality and drinking partly because of problems with the reliability of the measures. The correlation between two theoretical constructs is underestimated when measures contain error (Lord & Novik, 1968; Nunnally , 1978). Measures that are not perfectly reliable may fail to reveal a relation between two constructs when one actually exists, increasing the chances of a Type II error (failing to reject a false null hypothesis). Because the hypotheses concern the constructs rather than their imperfect measures, latent variable analyses, such as confirmatory factor analysis, may correct this problem by optimally weighing multiple indicators of each construct and correcting for measurement error. The use of confirmatory factor analysis to estimate the relation between estimates of true scores unaffected by measurement error has already revealed strong links between personality measures and job satisfaction (Reuman, Alwin, & Veroff, 1984), and social skills (Cole, Howard, & Maxwell, 1981). This study was designed to use these methods to investigate the relation between personality and drinking. The MacAndrew (MacAndrew, 1965) and Socialization (Gough, 1969) scales, two measures of personality that have been related to drinking, tend to reflect outgoing, impulsive, and aggressive tendencies. The MacAndrew scale, which was designed to discriminate between alcoholic patients and psychiatric controls, has also predicted subse-
We thank David Kessler and Laura Stith for their adept data collection. Special thanks to Rick Viken and Cara Wellman. This research was supported in part by NIMH Clinical Training Grant PHS T32 MH 17146-05 to the fmt author. Requests for reprints should be sent to Mitchell Earleywine, Ph.D., Psychology Building, Indiana University, Bloomington, IN 47405. 183
184
M. EARLEYWINE,
Table 1. Correlations,
P.R. FINN, and C.S. MARTIN
means, and standard deviations 1
1. 2. 3. 4.
Quantity Frequency MacAndrew Socialization
2
.45* .30* - .33*
.28* - .24*
for measures
3
M
SD
- .29*
3.05 1.75 19.27 35.62
2.96 1.22 3.58 5.64
M = mean. SD = standard deviation. p < .ool.
quent alcoholism in non-alcoholic males (Hoffman, Loper, & Kammeier, 1974). Individuals with high scores on this scale were rated as immature and assaultive (Lachar, Berman, Grissell, & Schoof, 1976), and have been described as bold, uninhibited, self-confident, and sociable (Finney, Smith, Skeeters, & Auvenshine, 1971). The Socialization scale has not been linked to alcoholism or consumption directly, but studies reveal that individuals with low scores on this scale are more likely to show stress-response-dampening after consuming alcohol. (Levenson, Oyama, & Meek, 1987; Sher & Levenson, 1982). This stressresponse-dampening, a decreased cardiovascular reactivity to stress, has also been found in individuals considered at elevated risk for alcoholism because of extensive family histories of alcoholism (Finn & Pihl, 1987). The Socialization scale was designed to measure degree of social maturity, and low scorers tend to be seen as rebellious, ostentatious, and defensive (Gough, 1969). These two scales can be viewed as measures of behavioral inhibition, and the attitudes and behaviors they survey may be associated with increased risk for excessive alcohol use. METHOD
Two hundred and two undergraduate men completed the MacAndrew (MacAndrew , 1965) and Socialization (Gough, 1969) scales, as well as a measure of quantity and frequency of alcohol use adapted from Cahalan and Cisin (1968), to partially fulfill a course requirement. Overlapping items from the two personality scales were counted toward the score of only one scale (Socialization), in order to avoid an artificially inflated correlation between the measures. In addition, any items that specifically referred to alcohol were omitted. After these two conditions were satisfied, the Socialization scale had 52 items; the MacAndrew had 44. Quantity was measured as the average number of drinks per drinking episode. Frequency was the number of times per week alcohol was consumed. RESULTS
The correlations, means, and standard deviations of the four measures are presented in Table 1. Note that although these correlations are statistically significant, they account for only a small percentage of the variance (r2 from 6 to 8%). In order to examine the relation between the latent variables we analyzed the correlation matrix using Joreskog and Sorbom’s (1986) LISREL program. The specified model restricted the solution to two factors, labeled here as behavioral inhibition and drinking. The model specified two measures for each construct. Quantity and frequency of alcohol use were used as separate measures of drinking. This arrangement is preferable to multiplying the two to serve as a single index. Combining quantity and frequency could mask a relation should behavioral inhibition relate to one or the other but not both (Apao & Damon, 1982). This
Personality
185
and alcohol consumption
QUANTITY
DRINKING
FREQUENCY
-.796
PERSONALITY
SOCIALIZATION
Fig. 1, Parameter
estimates and model specifications
relating behavioral
inhibition
and drinking.
arrangement also allows assessment of differences between individuals who consume the same amount of alcohol in a given week, but who have a different number of drinking occasions. MacAndrew scale and Socialization scale scores served as the measures of behavioral inhibition. The two factors were allowed to correlate in order to estimate the true relation between them. The analysis generates goodness of fit indices that test the degree to which the data fit the specified model. The model produced a nonsignificant chi-square of .63, p > .4, meaning that the correlation matrix did not differ significantly from a matrix that is consistent with the specified model. The goodness-of-fit index of .99, the adjusted goodness-of-fit index of .98, and a root mean square of residuals of .Ol 1 all suggest that the model provided a good fit to the data. The estimate of the correlation between the latent variables (drinking and behavioral 62% of the variance. Parameter inhibition) was - .796, accounting for approximately estimates and an illustration of the model appear in Figure 1. The possibility exists that all four of these measures (MacAndrew, Socialization, Quantity, and Frequency) actually reflect a single construct of self-report tendencies. An alternative model, using a single latent variable labeled here as self-report, used all four questionnaires as measures of this construct. This model produced a marginally significant chi-square of 3.14, p < .076, implying that the correlation matrix differed from one that
186
M. EARLEYWINE,
P.R. FINN, and C.S. MARTIN
would be consistent with a model using a single latent variable. The goodness-of-fit index equalled that of the two factor model (.99), but the adjusted goodness-of-fit index was smaller (.92) and the root mean square residuals was larger (.029) relative to the previous model. This analysis suggests that the data are more consistent with a two factor model of behavioral inhibition and drinking, than a one factor model of self-report tendencies. DISCUSSION
Standard correlations between personality measures of behavioral inhibition and quantity and frequency measures of alcohol consumption are statistically significant (p < .OOl) but do not account for a large percentage of variance. In this study, correlations between personality variables and measures of drinking ranged from magnitudes of .24 to .33. By using an alternative analysis, we discovered that when the relation is not attenuated by error in the measurement of the latent variables, the correlation between these two constructs increases to - .796. We obtained these data from college students, and the correlations of the measures as well as the relation between the two underlying constructs may differ for samples from other populations, such as problem drinkers or alcoholics. Nevertheless, this finding supports the notion that although situational factors may be important determinants of alcohol use, personality variables relate strongly to drinking as well. Although these data do not address the mechanism behind this relation between behavioral inhibition and alcohol consumption, the possibility exists that personality may help determine an individual’s situational as well as drinking factors, as certain individuals may prefer particular social environments that are frequently associated with drinking. Regardless of the mechanism behind this relation, the characteristics of an individual are stronger predictors of drinking behavior than was once believed, and deserve further investigation.
REFERENCES Apao, W.K., & Damon, A.M. (1982). Locus of control and the quantity-frequency index of alcohol use.. Journal of Studies on Alcohol, 43, 233-239. Cahalan, D., & Cisin, I.H. (1968). American drinking practices; summary of findings from a national probability sample. I. Extent of drinking by population subgroups. Quarterly Journal of Studies on Alcohol, 29, 13&151. Cole, D.A., Howard, G.S., & Maxwell, S.E. (1981). Effects of mono- versus multiple-operationalization in construct validation efforts. Journal of Consulting and Clinical Psychology, 49, 395-404. Finn, P.R., & Pihl, R.O. (1987). Men at high risk for alcoholism: The effect of alcohol on cardiovascular response to unavoidable shock. Journal of Abnormal Psychology, 96, 230-236. Finney, J., Smith, D., Skeeters, D., & Auvenshine, C. (1971). MMPI alcoholism scales: Factor structure and content analysis. Quarterly Journal of Studies on Alcohol, 32, 1055-1060. Gaines, L.S., & Connors, G.J. (1982). Drinking and personality: present knowledge and future. trends. In Alcohol consumption and related problems (pp. 331-346). Washington, DC: National Institute on Alcohol Abuse and Alcoholism. Gough. H.G. (1969). Manualfor rhe California Psychological Invenrory. Palo Alto, CA: Consulting Psychologists Press. Hoffman, H., Loper, R., & K-eier, M.L. (1974). Identifying future alcoholics with MMPI alcoholism scales. Quarterly Journal of Studies on Alcohol, 35, 490-498. Joreskog, K., & Sorbom, D. (1986). LISREL VI: User’s guide. Mooresville, IN: Scientific Software, Inc. Lachar, D., Berman, W., Grissell, J., & Schoof, K. (1976). The MacAndrew alcoholsm scale as a general measure of substance abuse. Journal of Studies on Alcohol, 37, 1609-1615. Levenson, R.W., Oyama, O.N., & Meek, P.S. (1987). Greater reinforcement from alcohol for those at risk: Parental risk, personality risk, and sex. Journal of Abnormal Psychology, 96, 242-253. Lord. F.M.. & Novik, M.R. (1968). Srarisrical theories of mental test scores. Reading, MA: Addison-Wesley. MacAndrew, C. (1965). The differentiation of male alcoholic outpatients from nonalcoholic psychiatric outpatients by means of the MMPI. Quarterly Journal of Studies on Alcohol, 26, 238-246. Nunnally, J.C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill. Reuman, D., Alwin. D., & Veroff, J. (1984). Assessing the validity of the achievement motive in the presence of random measurement error. Journal of Personality and Social Psychology, 47, 1347-1362. Rohsenow, D.J. (1982). Social anxiety, daily moods, and alcohol use over time among heavy social drinking men. Addictive Behaviors, 7, 311-315.
Personality
and alcohol consumption
187
Sher, K.J., & Levenson, R.W. (1982). Risk for alcoholism and individual differences in the stress-responsedampening effect of alcohol. Journal of Abnormal Psychology, 91, 350-367. Stein, J.A., Newcomb, M.D., dc Bentler, P.M. (1987). Personality and drug use: Reciprocal effects across four years. Personality and Individual Diaerences, 8, 419430. Sutker, P.B., & Allain, A.N. (1988). Issues in personality conceptualizations of addictive behaviors. Journal of Consulting and Clincial Psychology, 56, 172-182.