Journal of Consulting and Clinical Psychology 1976, Vol. 44, No. 2, 224-228
Alcoholism, Alpha Production, and Biofeedback Frances W. Jones and David S. Holmes University of Kansas Electroencephalograms of 20 alcoholics and 20 nonalcoholics were obtained during a 20-minutc baseline period. Data indicated that alcoholics produced less alpha (8-13 cps) than nonalcoholics, a finding that supports previous speculations that alcoholics have a higher level of arousal. Biofeedback training designed to increase alpha production and thereby reduce arousal was given during three subsequent daily sessions of 20 minutes each. Tn one condition subjects were given accurate biofeedback, whereas in the other condition subjects were given random (noncontingcnt) feedback. Data indicated that accurate biofeedback did not result in greater increases in alpha than did random biofeedback. This finding is discussed in terms of the problem of generalizing from the younger, more sophisticated, and belter motivated populations on which the biofeedback techniques were developed to the clinical populations to which the biofeedback techniques arc applied as treatment.
Considerable attention has been devoted to the possible differences between alcoholics and nonalcoholics in terms of their electrophysiological brain activity as measured by the electroencephalogram (EEG). Several investigators have reported that alcoholics appear to produce lower proportions of alpha (8-13 cps) than nonalcoholics (e.g., Davis, Gibbs, Davis, Jetter, & Trowbridge, 1941; Little & McAvoy, 1952), but there are also data suggesting that this may not be the case (e.g., Murphree, Shultz, & Jusko, 1970). Unfortunately, it is often difficult to draw conclusions from many of the reports in this area because investigators have either (a) overlooked the effects of medication on EEGs, (b) overlooked the fact that the EEGs obtained during detoxification may be influenced by the related anxiety and agitation, (c) used inadequate classification of subjects, (cl) used an inadequate number of subjects, (e) based results on potentially unreliable EEG interpretations, or (f) based conclusions on statistically nonsignificant differences. (See Begleiter & Flatz, 1972, for a review of some of the problems.) The authors would like to thank the staff of the Topeka Veterans Administration Hospital for their cooperation and help in conducting this experiment. The research was supported in part by Research Grant MH 20819 to David S. Holmes. Requests for reprints should be sent to David S. Holmes, University of Kansas, Department of Psychology, Lawrence, Kansas 66045.
Despite the equivocal nature of the reported results and the methodological shortcomings of many of the investigations, several writers (e.g., Conger, 1956; Doctor, Naitoh, & Smith, 1966; Kingham, 1958; Little & McAvoy, 1952; Varga & Nagy, 1960) have based etiological hypotheses of alcoholism on the speculation that alcoholics have alphapoor EEGs. Although stated differently by different authors, the basic idea is that relative to nonalcoholics the low level of alpha in alcoholics reflects a high level of arousal and that alcoholics consume alcohol to reduce or "normalize" this arousal. Consistent with this hypothesis, a considerable body of literature indicates that alcohol does slow the EEG (e.g., Bach-Y-Rita, Lion, & Ervin, 1970; Docter et al., 1966; Murphree et al., 1970; Varga & Nagy, 1960). Although it has not been firmly established that alcoholics have alpha-poor EEGs, nor has the causal relationship between low alpha production and alcoholism been advanced beyond speculation, treatment programs for alcoholics have been developed in which the goal is to teach the alcoholic to produce more alpha through techniques other than the ingestion of alcohol. It has been hypothesized that the availability of an alternate technique for increasing alpha (and thereby decreasing arousal) would reduce the person's need for alcohol. The technique for increasing alpha that has received most attention recently is biofeedback. 224
ALCOHOLISM, ALPHA PRODUCTION, AND BIOFKEDBACK
Biofeedback is generally viewed as a type of instrumental conditioning in which the subject is given feedback concerning the occurrence of the desired physiological response, and there are now many reports that document the effectiveness of biofeedback for altering EEC patterns (e.g., Beatty, 1971; Kamiya, 1968; Nowlis & Kamiya, 1970; Peper & Mulholland, 1970; Schwartz, Shaw, & Shapiro, 1972). Because the EEC response per se is usually considered to be an involuntary response, control of the response is probably achieved through the use of a mediating response. More specifically, control of the EEC is probably achieved through the learned avoidance or inhibition of external or internal cues that, if attended to, would inhibit alpha and cause arousal (Lynch & Paskewitz, 1971; Paskewitz & Orne, 1973). The learned avoidance of the arousing cues and the accompanying increase in alpha reportedly results in feelings of "relaxation," "letting go," "sensual warmth," "not focusing," "pleasure," and "security" (Nowlis & Kamiya, 1970, p. 482). The high-alpha state appears to have the positive experiential aspects associated with the initial ingestion of alcohol but does not have the negative effects associated with continued ingestion. Therefore, proponents of biofeedback treatment have suggested that teaching alcoholics how to increase their alpha production may provide the alcoholics with a technique they could use to achieve a more rewarding experiential state than that produced by alcohol. Hopefully, this option would reduce the alcoholic's consumption of alcohol. The present experiment was conducted to obtain data on two questions basic to the biofeedback treatment of alcoholics. First, we asked whether alcoholics do produce lower levels of alpha than nonalcoholics. Adequate data concerning the relative levels of alpha production in alcoholics and nonalcoholics are necessary because the above theories of alcoholism and treatment are based on the suggested disparity in alpha production. To answer this question, the base rates of alpha production of alcoholic and similar but nonalcoholic subjects were compared. Second, we asked whether biofeedback is effective in increasing the production of alpha in alcoholics.
225
Although there arc numerous reports indicating that alpha production can be altered with biofeedback techniques, almost all of the investigations used young, well-educated, rather sophisticated, and highly motivated subjects. As a consequence, it may be that the same benefit would not accrue with the typical alcoholic population. To determine whether alpha production could be increased in the patient and relevant control population, rates of alpha production during an initial 20-minute period were compared to rates of alpha production on the third of three 20-minute training sessions. In assessing changes in alpha production, it seemed important to determine whether any observed increase was due to biofeedback per se or to the associated opportunity and instructions to relax. Therefore, half of the subjects were given accurate (or true) biofeedback reflecting their alpha production and half were given irrelevant (or fake) biofeedback that they were led to believe reflected their actual alpha production. In summary, the experiment was a 2 X 2 factorial design in which alcoholic and nonalcoholic subjects were given either true or fake biofeedback. METHOD Subjects The alcoholic subjects (n = 20) were male ambulatory patients recently admitted to the Alcoholism Treatment Unit of the Topcka Veterans Administration Hospital. The mean age of alcoholic subjects was 44.S years, and most had long-term histories of alcohol abuse. None of the alcoholic subjects had diagnosed organic brain syndromes, nor did they carry other relevant medical or psychiatric diagnoses. All of the alcoholic subjects were sober and were not suffering from any of the syndromes associated with acute alcohol intoxication. Testing took place approximately 1 week after admission, and subjects had been removed from sedatives or other relevant medication before their participation in the experiment. The nonalcoholic subjects (n ~ 20) were male employees at the Topeka Veterans Administration Hospital. The mean age of the nonalcoholic subjects was 45.S years, and they represented a wide variety of job positions in the hospital but were roughly comparable to the alcoholic subjects in socioeconomic status. None of the nonalcoholic subjects had ever received any relevant medical or psychiatric diagnoses and none were taking any relevant medication. Although some of the nonalcoholic subjects consumed alcohol, their intake had never been great enough to require their liospitalization.
226
I'-RANCES W. JONKS AND DAVID S. HOLMES
AH of the alcoholic and nonalcoholic subjects voluntarily participated in the experiment, and no subject of either group had had previous experience in either biofeedback or meditation. Within the alcoholic and nonalcoholic groups, subjects were randomly assigned in equal numbers to the true and fake biofeedback conditions.
Procedure Each subject participated in four sessions over 4 successive days. The first session was used to assess initial levels of EEC activity and the latter three sessions were used for alpha biofeedback training. At, the beginning of the first session, the subject was informed that he was participating "in a study of brain wave activity during relaxation," and an attempt was made to reduce any apprehension ho might have concerning the procedures and their implications. He was then seated in a large comfortable reclining chair and three silver/silver chloride electrodes were applied. The main electrode was placed on the left occipital area (01), the reference electrode was placed on the left car lobe, and the ground electrode was placed on the right ear lobe. The resistance of each circuit was checked, and if it did not meet the minimum standard the electrodes wore rcapplied. The subject's chair was then placed in a semireclining position, and the subject was asked to relax (eyes closed) as much as possible without falling asleep for a 20-minutc period. Although no feedback was given during this first session, a set of Telex earphones was placed over the subject's cars in order to increase the comparability between (his and the (raining sessions that were to follow. With the subject prepared, the experimenter reduced the illumination of the experimental room and then went to the adjoining control room where she could both monitor (he physiological recording apparatus (see description later) and observe the, subject through a window. After a 20-minute period during which the subject relaxed and his EEG activity was recorded, the experimenter recntered the experimental room, detached the electrodes, and excused the subject. During each of the three biofeedback training sessions, the subject was prepared as he had been in the initial session, but the experimenter went on to explain to the subject that while he relaxed he might hear a tone through the headphones that would reflect his brain activity picked up by the electrodes. The experimenter told the subject, If you hear any tones, try to keep them on as much as possible. Since each person does this differently, I can't tell you how to do it, but just try to relax, and if you hear any tones try to make them stay on as much as you can. After the experimenter had demonstrated the tone and was convinced that the subject understood the procedure and his task, she reduced the room illumination and went to the control room. During the next 20 minutes, a subject in the true biofeedback condition received tones that accurately reflected his production of EEGs in the alpha range while a sub • ject in the fake biofeedback condition heard randomly presented tones (see description later). At the end of each session, and after the subject's EEG
activity had been recorded, the experimenter reentcred the room, detached the electrodes, and excused the subject,
Apparatus and Feedback The gross EEG activity generated by the subject was fed into a Scott Alpha-Theta trainer, Model 300C, on which the amplitude sensitivity was set at IS /J.V and the band-pass filters were preset at 8-13 cps (alpha) and 4-7 cps (theta). EEGs with an amplitude of 15 /iV or more that were within the two frequency bands triggered elapsed time clocks on a Scott Alpha-Theta event counter, while a total elapsed time clock ran continuously throughout the session. Using the three clocks, it was possible to determine the proportions of time during which the subject generated EEGs in the alpha and theta ranges for any given period (initial or training). In addition to being filtered and recorded by the equipment just described, the gross EEG signal was fed into a Bcckman-Offner Type RP two-channel dynograph where it was recorded on a chart moving at 10 mm/sec. This second recording unit enabled the experimenter to monitor both the clock operation and the subject's activity, the latter to ensure that he did not fall asleep or suffer from any gross EEG disturbances. For the subjects in the true biofeedback condition, the Scott unit provided feedback in the form of a tone whenever EEG activity of the appropriate amplitude occurred within the alpha range. No feedback was provided for EEG activity in the theta range, although activity of this type was recorded. 1 Rather than being exposed to tones contingent on their EEG alpha activity, subjects in the fake biofeedback condition heard a tape recording of noncontingent feedback tones that they believed reflected their brain activity. The tape was made from signals produced by a Grason-Stadler while noise generator, Model 901A, which was filtered to output signals from 8-13 cps. When received by the trainer, these signals produced alpha tones similar to a typical alpha record in both amount (26% alpha) and duration (e.g., short and long "alpha bursts"), with the important exception that the tones occurred at random intervals. The amount and nature of the fake feedback were designed to approximate the records of pilot subjects. The apparent authenticity of the fake feedback procedure was attested to by the fact that after the last training session, subjects in the fake biofeedback condition were as likely to report that they believer] they learned to control the tone as were subjects in the true biofeedback condition.
RKSULTS AND DISCUSSION Base Rate Production of Alpha by Alcoholics and Nonalcoholic.'; To determine whether the alcoholic subjects produced less alpha than the nonalco1
Because the contribution of theta as a dependent variable by itself or in combination with alpha was negligable, the following analyses deal only with alpha scores.
ALCOHOLISM, ALPHA PRODUCTION, AND BIOFEEDBACK
holic subjects during the base period, a 2 (alcoholic, nonalcoholic) X 2 (true biofeedback, fake biofeedback) factorial analysis of variance was performed on the log transformed alpha scores obtained during the base period. This analysis indicated that alcoholic subjects produced less alpha than did the nonalcoholic subjects, ^(1,36) =3.44, p — .0,69. In considering this finding with reference to the development of alcoholism, two points deserve mention. First, although there was a statistically significant overall difference in the means of the two groups, it is important to note that there was considerable overlap in the two distributions; in fact, 70% of the alcoholic and 80% of the nonalcoholic subjects shared a common range of the distribution. Obviously, production of alpha does not clearly separate alcoholics from nonalcoholics, and additional factors will therefore have to be incorporated with any thorough explanation of alcoholism. Second, it must be recognized that in this as in other investigations, alpha production was assessed after the patients were diagnosed as alcoholic, and thus the possibility that the alcoholism influenced the alpha production rather than vice versa cannot yet be definitely ruled out. The true-fake biofeedback effect and the interaction effect generated by the 2 (alcoholic, nonalcoholic) X 2 (true biofeedback, fake biofeedback) analysis provided data concerning the effectiveness of the random assignment of subjects to treatment conditions. Neither of these effects approached statistical significance, 7 / 's(l,36) = .59 and .17, respectively, thus indicating that the random assignment had been effective in producing equivalent groups in terms of initial alpha levels. Effect of True and Fake Biojeedback on the Production of Alpha by Alcoholics and Nonalcoholics To determine whether true biofeedback was generally more effective in helping subjects to increase their alpha production than was fake biofeedback and to determine whether the feedback was differentially effective for alcoholic and nonalcoholic subjects, change scores were computed that reflected the difference in alpha production between the baseline period and the third training period. To control for the possible effects of the law of initial values (Wilder, 1962) on these change scores, the
227
change scores were adjusted for initial values through a covariance technique (McNemar, 1962). 2 The log transformed and adjusted change scores were then subjected to a 2 (alcoholic, nonalcoholic) X 2 (true biofeedback, fake biofeedback) factorial analysis of variance. This analysis revealed three interesting findings. First, the analysis indicated that the true biofeedback did not result in a generally greater increase in alpha production than did the fake biofeedback ^(t, 36) = .02. In view of the previous reports indicating the effectiveness of biofeedback, this finding was somewhat surprising and may be of considerable importance. With regard to this discrepancy in results, we might suggest that the three 20minute training sessions did not provide enough time for the subjects to benefit from the true biofeedback. This seems unlikely, however, in view of the research indicating that biofeedback can be effective in altering alpha production within one 20-minute training period (e.g., Beatty, 1971; Honorton, Davidson, & Bindler, 1972; Nowlis & Kamiya, 1970; Peper & Mulholland, 1970). Alternatively, it may be that the difference in results between this and previous research stems from the differences in subject populations employed. The type of subjects used in this investigation differed markedly in important ways from the subjects of previous investigations: They were older, less well educated, less sophisticated, and less motivated with regard to biofeedback. Given the subtleties of biofeedback training, this may be a case in which generalization across disparate populations is not appropriate. This may be an exceptionally important point to recognize in terms of our attempts to apply biofeedback techniques in general clinical settings with other than very highly selected and nonrepresentative patients. Because of the questions raised concerning the generalizability of the findings, it appears that systematic work needs to be done on the subject parameters that may influence the effectiveness of biofeedback. The second interesting finding generated by ! This procedure produced dualized" scores suggested by (1970) that provide base-free (Benjamin, 1907; Tucker ct al.,
scores like the "restCronbach and Furby measures of change I960).
228
FRANCES W. JONES AND DAVID S. HOLMKS
the 2 x 2 analysis was thai the alcoholic subjects did not show a generally greater or lesser change in alpha production over time than did nonalcoholic subjects, F(l, 36) — .78; that is, although alcoholics were found to produce initially less alpha (see previous section), their rate of change in alpha production between the base period and the last training period did not differ from that of nonalcoholics. Finally, the analysis did not reveal an interaction between alcoholics/nonalcoholics and true/fake biofeedback, F(l, 36) = .64, thus indicating that true and fake biofeedback had the same effect on alcoholic and nonalcoholic subjects. This is important because it indicates that a possible influence of biofeedback was not being obscured by a selective effect on only one type of subject; rather, in this case it appears that biofeedback was uniformly ineffective in altering alpha production. CONCLUSIONS AND IMPLICATIONS First, this investigation provided evidence for the contention that in a resting state alcoholics produce less alpha than nonalcoholics. This finding is consistent with the speculation that alcoholics drink to reduce arousal, but the overlap of alcoholics and nonalcoholics in the distribution of alpha production clearly indicates that additional factors must be incorporated with any explanation of alcoholism. Second, this investigation provided no evidence that biofeedback was an effective means of teaching alcoholics (or comparable nonalcoholics) to increase their alpha production. The failure of the biofeedback to be effective probably stemmed from the nature of the subject population used, a point that is important in our attempts to generalize the use of biofeedback from the laboratory to the clinical setting. REFERENCES Bach-Y-Rita, G., Lion, J., & Ervin, F. Pathological intoxication: Clinical and elcctrocncephalographic studies. American Journal of Psychiatry, 1970, 127, 698-703. Bealty, J. Effects of initial alpha wave abundance and operant training procedures on occipital alpha and beta wave activity. Psychonom/c Science, 1971, 23, 197-199. Buglcitcr, H., & Platz, A. The effects of alcohol on the central nervous system in humans. In B. Kissin & H. Bcglciter (Eds.), The biology of alcoholism (Vol. 2). Physiology and behavior. New York: Plenum Press, 1972.
Benjamin, L. Fads and artifacts in using analysis of covariancc to "undo" the law of initial values. Psychophysiology, 1967, 4, 187-206. Conger, J. Reinforcement, theory and the dynamics of alcoholism. Quarterly Journal oj Studies in Alcoholism, 1956,17, 296-305. Cronbach, L., & Furby, L. How we should measure change—or should we? Psychological Bulletin, 1970, 74, 68-80. Davis, P., Gibbs, F., Davis. H., Jetter, W., & Trowbridge, L. The effects of alcohol upon the electroencephalogram (brain waves). Quarterly Journal of Studies in Alcoholism, 1941, 1, 626-637. Docler, R., Naitoh, R., & Smith, J. Elcctrocncephalographic changes and vigilance behavior during experimentally induced intoxication with alcoholic subjects. Psychosomatic Medicine, 1966, 28, 311315. Tlonorlon, C., Davidson, R., & Bindler, P. Shifts in subjective state associated with feedback-augmented EEC! alpha. Psychophysiology, 1972, 9, 296. (Abstract) Kamiya, J. Conscious control of brain waves. Psychology Today, 1968, 1, 57-60. Kingham, R. Alcoholism and the reinforcement theory of learning. Quarterly Journal oj Studies in Alcoholism, 1958, 19, 320-330. Little, S., & McAvoy, M. Eleclroencephalograph sludies in alcoholism. Quarterly Journal oj Studies in Alcoholism, 1952,13, 9-15. Lynch, J., & Paskcwilz, D. On the mechanism of the feedback control of human brain wave activity. Journal oj Nervous and Mental Disease, 1971, 153, 205-2J7. McNcmar, Q. Psychological statistics (3rd ed.). New York: Wiley, 1962. Murphrce, H., Schultz, R., & Jusko, A. Effects of high congener intake by human subjects on the EEC. Quarterly Journal of Studies in Alcoholism: Stitdies oj congeners in alcoholic beverages, 1970, S, 50-61. (Supplement). Nowlis, D., & Kamiya, J. The control of electroencephalographic alpha rhythms through auditory feedback and the associated mental activity. Psychophysiology, 1970, 6, 476-484. Paskcwitz, D., & Orne, M. Visual effects on alpha feedback training. Science, 1973, 181, 360-363. Peper, E., & Mulholland, T. Methodological and theoretical problems in the voluntary control of electroencephalographic occipital alpha by the subject. Kybernetik, 1970, 7, 10-13. Schwartz, G., Shaw, G., & Shapiro, D. Specificity of alpha and heart rale control through feedback. Psychophysiology, 1972, 9, 269. (Abstract) Tucker, L., Damarin, F., & Messick, S. A base-free measure of change. Psychometrika, 1966, 31, 457473. Varga, B., & Nagy, T. Analysis of the alpha rhythm in the clcctroencephalograph of alcoholics. Electroencephalography and Clinical Neurophysiology, I960, 12, 933. (Abstract) Wilder, J. Basimetric approach (law of initial values) to biological rhythms. Annals oj the New York Academy oj Science, 1962, 98, 1211-1220. (Received July 14,1975)
Alcoholism, Alpha Production, and Biofeedback Frances W. Jones and David S. Holmes University of Kansas Electroencephalograms of 20 alcoholics and 20 nonalcoholics were obtained during a 20-minutc baseline period. Data indicated that alcoholics produced less alpha (8-13 cps) than nonalcoholics, a finding that supports previous speculations that alcoholics have a higher level of arousal. Biofeedback training designed to increase alpha production and thereby reduce arousal was given during three subsequent daily sessions of 20 minutes each. Tn one condition subjects were given accurate biofeedback, whereas in the other condition subjects were given random (noncontingcnt) feedback. Data indicated that accurate biofeedback did not result in greater increases in alpha than did random biofeedback. This finding is discussed in terms of the problem of generalizing from the younger, more sophisticated, and belter motivated populations on which the biofeedback techniques were developed to the clinical populations to which the biofeedback techniques arc applied as treatment.
Considerable attention has been devoted to the possible differences between alcoholics and nonalcoholics in terms of their electrophysiological brain activity as measured by the electroencephalogram (EEG). Several investigators have reported that alcoholics appear to produce lower proportions of alpha (8-13 cps) than nonalcoholics (e.g., Davis, Gibbs, Davis, Jetter, & Trowbridge, 1941; Little & McAvoy, 1952), but there are also data suggesting that this may not be the case (e.g., Murphree, Shultz, & Jusko, 1970). Unfortunately, it is often difficult to draw conclusions from many of the reports in this area because investigators have either (a) overlooked the effects of medication on EEGs, (b) overlooked the fact that the EEGs obtained during detoxification may be influenced by the related anxiety and agitation, (c) used inadequate classification of subjects, (cl) used an inadequate number of subjects, (e) based results on potentially unreliable EEG interpretations, or (f) based conclusions on statistically nonsignificant differences. (See Begleiter & Flatz, 1972, for a review of some of the problems.) The authors would like to thank the staff of the Topeka Veterans Administration Hospital for their cooperation and help in conducting this experiment. The research was supported in part by Research Grant MH 20819 to David S. Holmes. Requests for reprints should be sent to David S. Holmes, University of Kansas, Department of Psychology, Lawrence, Kansas 66045.
Despite the equivocal nature of the reported results and the methodological shortcomings of many of the investigations, several writers (e.g., Conger, 1956; Doctor, Naitoh, & Smith, 1966; Kingham, 1958; Little & McAvoy, 1952; Varga & Nagy, 1960) have based etiological hypotheses of alcoholism on the speculation that alcoholics have alphapoor EEGs. Although stated differently by different authors, the basic idea is that relative to nonalcoholics the low level of alpha in alcoholics reflects a high level of arousal and that alcoholics consume alcohol to reduce or "normalize" this arousal. Consistent with this hypothesis, a considerable body of literature indicates that alcohol does slow the EEG (e.g., Bach-Y-Rita, Lion, & Ervin, 1970; Docter et al., 1966; Murphree et al., 1970; Varga & Nagy, 1960). Although it has not been firmly established that alcoholics have alpha-poor EEGs, nor has the causal relationship between low alpha production and alcoholism been advanced beyond speculation, treatment programs for alcoholics have been developed in which the goal is to teach the alcoholic to produce more alpha through techniques other than the ingestion of alcohol. It has been hypothesized that the availability of an alternate technique for increasing alpha (and thereby decreasing arousal) would reduce the person's need for alcohol. The technique for increasing alpha that has received most attention recently is biofeedback. 224
ALCOHOLISM, ALPHA PRODUCTION, AND BIOFKEDBACK
Biofeedback is generally viewed as a type of instrumental conditioning in which the subject is given feedback concerning the occurrence of the desired physiological response, and there are now many reports that document the effectiveness of biofeedback for altering EEC patterns (e.g., Beatty, 1971; Kamiya, 1968; Nowlis & Kamiya, 1970; Peper & Mulholland, 1970; Schwartz, Shaw, & Shapiro, 1972). Because the EEC response per se is usually considered to be an involuntary response, control of the response is probably achieved through the use of a mediating response. More specifically, control of the EEC is probably achieved through the learned avoidance or inhibition of external or internal cues that, if attended to, would inhibit alpha and cause arousal (Lynch & Paskewitz, 1971; Paskewitz & Orne, 1973). The learned avoidance of the arousing cues and the accompanying increase in alpha reportedly results in feelings of "relaxation," "letting go," "sensual warmth," "not focusing," "pleasure," and "security" (Nowlis & Kamiya, 1970, p. 482). The high-alpha state appears to have the positive experiential aspects associated with the initial ingestion of alcohol but does not have the negative effects associated with continued ingestion. Therefore, proponents of biofeedback treatment have suggested that teaching alcoholics how to increase their alpha production may provide the alcoholics with a technique they could use to achieve a more rewarding experiential state than that produced by alcohol. Hopefully, this option would reduce the alcoholic's consumption of alcohol. The present experiment was conducted to obtain data on two questions basic to the biofeedback treatment of alcoholics. First, we asked whether alcoholics do produce lower levels of alpha than nonalcoholics. Adequate data concerning the relative levels of alpha production in alcoholics and nonalcoholics are necessary because the above theories of alcoholism and treatment are based on the suggested disparity in alpha production. To answer this question, the base rates of alpha production of alcoholic and similar but nonalcoholic subjects were compared. Second, we asked whether biofeedback is effective in increasing the production of alpha in alcoholics.
225
Although there arc numerous reports indicating that alpha production can be altered with biofeedback techniques, almost all of the investigations used young, well-educated, rather sophisticated, and highly motivated subjects. As a consequence, it may be that the same benefit would not accrue with the typical alcoholic population. To determine whether alpha production could be increased in the patient and relevant control population, rates of alpha production during an initial 20-minute period were compared to rates of alpha production on the third of three 20-minute training sessions. In assessing changes in alpha production, it seemed important to determine whether any observed increase was due to biofeedback per se or to the associated opportunity and instructions to relax. Therefore, half of the subjects were given accurate (or true) biofeedback reflecting their alpha production and half were given irrelevant (or fake) biofeedback that they were led to believe reflected their actual alpha production. In summary, the experiment was a 2 X 2 factorial design in which alcoholic and nonalcoholic subjects were given either true or fake biofeedback. METHOD Subjects The alcoholic subjects (n = 20) were male ambulatory patients recently admitted to the Alcoholism Treatment Unit of the Topcka Veterans Administration Hospital. The mean age of alcoholic subjects was 44.S years, and most had long-term histories of alcohol abuse. None of the alcoholic subjects had diagnosed organic brain syndromes, nor did they carry other relevant medical or psychiatric diagnoses. All of the alcoholic subjects were sober and were not suffering from any of the syndromes associated with acute alcohol intoxication. Testing took place approximately 1 week after admission, and subjects had been removed from sedatives or other relevant medication before their participation in the experiment. The nonalcoholic subjects (n ~ 20) were male employees at the Topeka Veterans Administration Hospital. The mean age of the nonalcoholic subjects was 45.S years, and they represented a wide variety of job positions in the hospital but were roughly comparable to the alcoholic subjects in socioeconomic status. None of the nonalcoholic subjects had ever received any relevant medical or psychiatric diagnoses and none were taking any relevant medication. Although some of the nonalcoholic subjects consumed alcohol, their intake had never been great enough to require their liospitalization.
226
I'-RANCES W. JONKS AND DAVID S. HOLMES
AH of the alcoholic and nonalcoholic subjects voluntarily participated in the experiment, and no subject of either group had had previous experience in either biofeedback or meditation. Within the alcoholic and nonalcoholic groups, subjects were randomly assigned in equal numbers to the true and fake biofeedback conditions.
Procedure Each subject participated in four sessions over 4 successive days. The first session was used to assess initial levels of EEC activity and the latter three sessions were used for alpha biofeedback training. At, the beginning of the first session, the subject was informed that he was participating "in a study of brain wave activity during relaxation," and an attempt was made to reduce any apprehension ho might have concerning the procedures and their implications. He was then seated in a large comfortable reclining chair and three silver/silver chloride electrodes were applied. The main electrode was placed on the left occipital area (01), the reference electrode was placed on the left car lobe, and the ground electrode was placed on the right ear lobe. The resistance of each circuit was checked, and if it did not meet the minimum standard the electrodes wore rcapplied. The subject's chair was then placed in a semireclining position, and the subject was asked to relax (eyes closed) as much as possible without falling asleep for a 20-minutc period. Although no feedback was given during this first session, a set of Telex earphones was placed over the subject's cars in order to increase the comparability between (his and the (raining sessions that were to follow. With the subject prepared, the experimenter reduced the illumination of the experimental room and then went to the adjoining control room where she could both monitor (he physiological recording apparatus (see description later) and observe the, subject through a window. After a 20-minute period during which the subject relaxed and his EEG activity was recorded, the experimenter recntered the experimental room, detached the electrodes, and excused the subject. During each of the three biofeedback training sessions, the subject was prepared as he had been in the initial session, but the experimenter went on to explain to the subject that while he relaxed he might hear a tone through the headphones that would reflect his brain activity picked up by the electrodes. The experimenter told the subject, If you hear any tones, try to keep them on as much as possible. Since each person does this differently, I can't tell you how to do it, but just try to relax, and if you hear any tones try to make them stay on as much as you can. After the experimenter had demonstrated the tone and was convinced that the subject understood the procedure and his task, she reduced the room illumination and went to the control room. During the next 20 minutes, a subject in the true biofeedback condition received tones that accurately reflected his production of EEGs in the alpha range while a sub • ject in the fake biofeedback condition heard randomly presented tones (see description later). At the end of each session, and after the subject's EEG
activity had been recorded, the experimenter reentcred the room, detached the electrodes, and excused the subject,
Apparatus and Feedback The gross EEG activity generated by the subject was fed into a Scott Alpha-Theta trainer, Model 300C, on which the amplitude sensitivity was set at IS /J.V and the band-pass filters were preset at 8-13 cps (alpha) and 4-7 cps (theta). EEGs with an amplitude of 15 /iV or more that were within the two frequency bands triggered elapsed time clocks on a Scott Alpha-Theta event counter, while a total elapsed time clock ran continuously throughout the session. Using the three clocks, it was possible to determine the proportions of time during which the subject generated EEGs in the alpha and theta ranges for any given period (initial or training). In addition to being filtered and recorded by the equipment just described, the gross EEG signal was fed into a Bcckman-Offner Type RP two-channel dynograph where it was recorded on a chart moving at 10 mm/sec. This second recording unit enabled the experimenter to monitor both the clock operation and the subject's activity, the latter to ensure that he did not fall asleep or suffer from any gross EEG disturbances. For the subjects in the true biofeedback condition, the Scott unit provided feedback in the form of a tone whenever EEG activity of the appropriate amplitude occurred within the alpha range. No feedback was provided for EEG activity in the theta range, although activity of this type was recorded. 1 Rather than being exposed to tones contingent on their EEG alpha activity, subjects in the fake biofeedback condition heard a tape recording of noncontingent feedback tones that they believed reflected their brain activity. The tape was made from signals produced by a Grason-Stadler while noise generator, Model 901A, which was filtered to output signals from 8-13 cps. When received by the trainer, these signals produced alpha tones similar to a typical alpha record in both amount (26% alpha) and duration (e.g., short and long "alpha bursts"), with the important exception that the tones occurred at random intervals. The amount and nature of the fake feedback were designed to approximate the records of pilot subjects. The apparent authenticity of the fake feedback procedure was attested to by the fact that after the last training session, subjects in the fake biofeedback condition were as likely to report that they believer] they learned to control the tone as were subjects in the true biofeedback condition.
RKSULTS AND DISCUSSION Base Rate Production of Alpha by Alcoholics and Nonalcoholic.'; To determine whether the alcoholic subjects produced less alpha than the nonalco1
Because the contribution of theta as a dependent variable by itself or in combination with alpha was negligable, the following analyses deal only with alpha scores.
ALCOHOLISM, ALPHA PRODUCTION, AND BIOFEEDBACK
holic subjects during the base period, a 2 (alcoholic, nonalcoholic) X 2 (true biofeedback, fake biofeedback) factorial analysis of variance was performed on the log transformed alpha scores obtained during the base period. This analysis indicated that alcoholic subjects produced less alpha than did the nonalcoholic subjects, ^(1,36) =3.44, p — .0,69. In considering this finding with reference to the development of alcoholism, two points deserve mention. First, although there was a statistically significant overall difference in the means of the two groups, it is important to note that there was considerable overlap in the two distributions; in fact, 70% of the alcoholic and 80% of the nonalcoholic subjects shared a common range of the distribution. Obviously, production of alpha does not clearly separate alcoholics from nonalcoholics, and additional factors will therefore have to be incorporated with any thorough explanation of alcoholism. Second, it must be recognized that in this as in other investigations, alpha production was assessed after the patients were diagnosed as alcoholic, and thus the possibility that the alcoholism influenced the alpha production rather than vice versa cannot yet be definitely ruled out. The true-fake biofeedback effect and the interaction effect generated by the 2 (alcoholic, nonalcoholic) X 2 (true biofeedback, fake biofeedback) analysis provided data concerning the effectiveness of the random assignment of subjects to treatment conditions. Neither of these effects approached statistical significance, 7 / 's(l,36) = .59 and .17, respectively, thus indicating that the random assignment had been effective in producing equivalent groups in terms of initial alpha levels. Effect of True and Fake Biojeedback on the Production of Alpha by Alcoholics and Nonalcoholics To determine whether true biofeedback was generally more effective in helping subjects to increase their alpha production than was fake biofeedback and to determine whether the feedback was differentially effective for alcoholic and nonalcoholic subjects, change scores were computed that reflected the difference in alpha production between the baseline period and the third training period. To control for the possible effects of the law of initial values (Wilder, 1962) on these change scores, the
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change scores were adjusted for initial values through a covariance technique (McNemar, 1962). 2 The log transformed and adjusted change scores were then subjected to a 2 (alcoholic, nonalcoholic) X 2 (true biofeedback, fake biofeedback) factorial analysis of variance. This analysis revealed three interesting findings. First, the analysis indicated that the true biofeedback did not result in a generally greater increase in alpha production than did the fake biofeedback ^(t, 36) = .02. In view of the previous reports indicating the effectiveness of biofeedback, this finding was somewhat surprising and may be of considerable importance. With regard to this discrepancy in results, we might suggest that the three 20minute training sessions did not provide enough time for the subjects to benefit from the true biofeedback. This seems unlikely, however, in view of the research indicating that biofeedback can be effective in altering alpha production within one 20-minute training period (e.g., Beatty, 1971; Honorton, Davidson, & Bindler, 1972; Nowlis & Kamiya, 1970; Peper & Mulholland, 1970). Alternatively, it may be that the difference in results between this and previous research stems from the differences in subject populations employed. The type of subjects used in this investigation differed markedly in important ways from the subjects of previous investigations: They were older, less well educated, less sophisticated, and less motivated with regard to biofeedback. Given the subtleties of biofeedback training, this may be a case in which generalization across disparate populations is not appropriate. This may be an exceptionally important point to recognize in terms of our attempts to apply biofeedback techniques in general clinical settings with other than very highly selected and nonrepresentative patients. Because of the questions raised concerning the generalizability of the findings, it appears that systematic work needs to be done on the subject parameters that may influence the effectiveness of biofeedback. The second interesting finding generated by ! This procedure produced dualized" scores suggested by (1970) that provide base-free (Benjamin, 1907; Tucker ct al.,
scores like the "restCronbach and Furby measures of change I960).
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FRANCES W. JONES AND DAVID S. HOLMKS
the 2 x 2 analysis was thai the alcoholic subjects did not show a generally greater or lesser change in alpha production over time than did nonalcoholic subjects, F(l, 36) — .78; that is, although alcoholics were found to produce initially less alpha (see previous section), their rate of change in alpha production between the base period and the last training period did not differ from that of nonalcoholics. Finally, the analysis did not reveal an interaction between alcoholics/nonalcoholics and true/fake biofeedback, F(l, 36) = .64, thus indicating that true and fake biofeedback had the same effect on alcoholic and nonalcoholic subjects. This is important because it indicates that a possible influence of biofeedback was not being obscured by a selective effect on only one type of subject; rather, in this case it appears that biofeedback was uniformly ineffective in altering alpha production. CONCLUSIONS AND IMPLICATIONS First, this investigation provided evidence for the contention that in a resting state alcoholics produce less alpha than nonalcoholics. This finding is consistent with the speculation that alcoholics drink to reduce arousal, but the overlap of alcoholics and nonalcoholics in the distribution of alpha production clearly indicates that additional factors must be incorporated with any explanation of alcoholism. Second, this investigation provided no evidence that biofeedback was an effective means of teaching alcoholics (or comparable nonalcoholics) to increase their alpha production. The failure of the biofeedback to be effective probably stemmed from the nature of the subject population used, a point that is important in our attempts to generalize the use of biofeedback from the laboratory to the clinical setting. REFERENCES Bach-Y-Rita, G., Lion, J., & Ervin, F. Pathological intoxication: Clinical and elcctrocncephalographic studies. American Journal of Psychiatry, 1970, 127, 698-703. Bealty, J. Effects of initial alpha wave abundance and operant training procedures on occipital alpha and beta wave activity. Psychonom/c Science, 1971, 23, 197-199. Buglcitcr, H., & Platz, A. The effects of alcohol on the central nervous system in humans. In B. Kissin & H. Bcglciter (Eds.), The biology of alcoholism (Vol. 2). Physiology and behavior. New York: Plenum Press, 1972.
Benjamin, L. Fads and artifacts in using analysis of covariancc to "undo" the law of initial values. Psychophysiology, 1967, 4, 187-206. Conger, J. Reinforcement, theory and the dynamics of alcoholism. Quarterly Journal oj Studies in Alcoholism, 1956,17, 296-305. Cronbach, L., & Furby, L. How we should measure change—or should we? Psychological Bulletin, 1970, 74, 68-80. Davis, P., Gibbs, F., Davis. H., Jetter, W., & Trowbridge, L. The effects of alcohol upon the electroencephalogram (brain waves). Quarterly Journal of Studies in Alcoholism, 1941, 1, 626-637. Docler, R., Naitoh, R., & Smith, J. Elcctrocncephalographic changes and vigilance behavior during experimentally induced intoxication with alcoholic subjects. Psychosomatic Medicine, 1966, 28, 311315. Tlonorlon, C., Davidson, R., & Bindler, P. Shifts in subjective state associated with feedback-augmented EEC! alpha. Psychophysiology, 1972, 9, 296. (Abstract) Kamiya, J. Conscious control of brain waves. Psychology Today, 1968, 1, 57-60. Kingham, R. Alcoholism and the reinforcement theory of learning. Quarterly Journal oj Studies in Alcoholism, 1958, 19, 320-330. Little, S., & McAvoy, M. Eleclroencephalograph sludies in alcoholism. Quarterly Journal oj Studies in Alcoholism, 1952,13, 9-15. Lynch, J., & Paskcwilz, D. On the mechanism of the feedback control of human brain wave activity. Journal oj Nervous and Mental Disease, 1971, 153, 205-2J7. McNcmar, Q. Psychological statistics (3rd ed.). New York: Wiley, 1962. Murphrce, H., Schultz, R., & Jusko, A. Effects of high congener intake by human subjects on the EEC. Quarterly Journal of Studies in Alcoholism: Stitdies oj congeners in alcoholic beverages, 1970, S, 50-61. (Supplement). Nowlis, D., & Kamiya, J. The control of electroencephalographic alpha rhythms through auditory feedback and the associated mental activity. Psychophysiology, 1970, 6, 476-484. Paskcwitz, D., & Orne, M. Visual effects on alpha feedback training. Science, 1973, 181, 360-363. Peper, E., & Mulholland, T. Methodological and theoretical problems in the voluntary control of electroencephalographic occipital alpha by the subject. Kybernetik, 1970, 7, 10-13. Schwartz, G., Shaw, G., & Shapiro, D. Specificity of alpha and heart rale control through feedback. Psychophysiology, 1972, 9, 269. (Abstract) Tucker, L., Damarin, F., & Messick, S. A base-free measure of change. Psychometrika, 1966, 31, 457473. Varga, B., & Nagy, T. Analysis of the alpha rhythm in the clcctroencephalograph of alcoholics. Electroencephalography and Clinical Neurophysiology, I960, 12, 933. (Abstract) Wilder, J. Basimetric approach (law of initial values) to biological rhythms. Annals oj the New York Academy oj Science, 1962, 98, 1211-1220. (Received July 14,1975)
