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The validity of smoking self-reports by adolescents: A reexamination of the bogus pipeline procedure
Vol. 12, pp. 7-15, 1987 Printed in the USA. All rights reserved.
AddictiveBehaviors,
0306-4603/87 $3.00 + .OO Copyright o 1987 Pergamon Journals Ltd
THE VALIDITY OF SMOKING SELF-REPORTS BY ADOLESCENTS: A REEXAMINATION OF THE BOGUS PIPELINE PROCEDURE DAVID M. MURRAY, CATHERINE M. O’CONNELL, CHERYL L. PERRY
LINDA A. SCHMID, and
Division of Epidemiology, School of Public Health, University of Minnesota smoking was measured in a naive tenth grade population under conditions expected to influence the student’s willingness to admit smoking. All students were tested for smoking both by questionnaire and by expired-air carbon monoxide assessment. The carbon monoxide data were used to test the equivalence of the study groups and to partition the sample into smokers and nonsmokers. Of the smokers those who were advised in advance of the biological test were twice as likeiy to admit cigarette use in the past week compared to those who were advised of the testing procedure only after they had completed their questionnaire. A live explanation and demonstration of the biological testing procedure proved as effective as a videotaped message. These data support earlier reports of the ‘bogus pipeline’ effect. Several methodological issues are discussed which may explain previous failures to replicate this finding. Abstract-Cigarette
Adolescent smoking behavior is generally measured by self-reports of frequency and intensity. Though such methods are simple, efficient and inexpensive, a number of factors often render them invalid (Pechacek, Fox, Murray, & Luepker, 1984). For example, adolescents often smoke infrequently and episodically; as a result, it may be difficult for them to characterize their “usual” pattern of smoking. They may not accurately recall the number of cigarettes smoked in recent days or weeks. Neither adolescents nor adults can accurately describe their puff rate, depth of inhalation and other factors related to physiological exposure. Adolescents may also try to mislead the investigator and underreport smoking behavior out of embarrassment or in a desire to please. Finally, they may exaggerate smoking levels to appear older or to be uncooperative. The weaknesses of the self-report have prompted extensive research on objective measures of smoking. Numerous investigations document the relationship between carbon monoxide, thiocyanate, nicotine and cotinine and tobacco use among adolescents and adults (Pechacek, Fox, Murray, & Luepker, 1984). These biological measures are helpful but imperfect because adolescent smoking remains relatively rare and develops gradually. Among young adolescents, smoking is often more appropriately characterized as a social display rather than as drug self-administration. As a result, biological measures are weakly correlated with self-reports of smoking among young adolescents (Biglan, Gallison, Ary, & Thompson, 1985; Pechacek, Murray, Luepker, Mittelmark, Johnson, & Shultz, 1984). Other researchers have developed methods to increase the validity of smoking selfThis research was supported through grants from the National Institute on Drug Abuse (ROl DA03205 and ROl DA03044) and the National Cancer Institute (ROl CA38275). The authors wish to thank Minnesota Independent School District 11 for its cooperation in this research. We also thank Jan Whitbeck who directed the school survey; Lisa Roche who assisted with the data analyses; Terry Pechacek and Susan Blake who commented on an earlier draft; and Laurie Zurbey who prepared the manuscript. Requests for reprints should be sent to David M. Murray, PhD, Division of Epidemiology, School of Public Health, University of Minnesota, Stadium Gate 20, 611 Beacon Street S.E., Minneapolis, MN 55455.
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D.M. MURRAY
et al.
reports. One of the best known is the “bogus pipeline” method. This approach assumes that adolescents will be more likely to disclose socially undesirable behavior if they believe the investigator has an independent and objective measure of that behavior. Evans, Hansen, and Mittelmark (1977) first applied this method to smoking, borrowing from the work of Jones and Sigall(l971). Jones and Sigall(l971) used a false physiological test and attached the “bogus” label to this “pipeline to the truth.” Valid physiological measures have been used in the smoking applications, but the misnomer “bogus pipeline” is still used to describe the method. The study of Evans et al. (1977) went unchallenged for several years. Five other reports seemed to support Evans et al.‘s early findings (Bauman & Dent, 1982; Bray, Hill, & Henderson, 1979; Gillies, Wilcox, Coates, Kristmundsdottir, & Reid, 1982; Hill, Henderson, Bray, & Evans, 1981; Luepker, Pechacek, Murray, Johnson, Hurd, & Jacobs, 1981). More recently however, the pipeline effect has come into question. Bauman, Koch and Bryan (1982) reported no difference in self-reported smoking rates between students assessed under pipeline and non-pipeline conditions. Others also failed to replicate the pipeline effect (Akers, Massey, Clarke, & Lauer, 1983; Botvin, Botvin, Renick, & Filazzola, 1984; Hansen, 1983; Hansen, Malotte, & Fielding, 1985; Lauer, Akers, Massey, & Clarke, 1982). A careful review of the eleven previous papers indicates that five reported a pipeline effect while six did not. The current debate is thus understandable. These studies are summarized in Table 1. A close examination of these reports suggests several possible explanations for their findings: Nonequivalence of Groups. The equivalence of study groups is important to the interpretation of findings from any experimental or quasi-experimental design (Cook & Campbell, 1979). Randomization of individual subjects provides such assurance where sufficient numbers are randomized to each group (e.g., Bauman & Dent, 1982; Gillies et al., 1982). However, the small sample sizes of Bauman, Koch, and Bryan (1982), Evans et al. (1977) and Hansen (1983) may have been inadequate to assure comparability, especially given the low prevalence of adolescent smoking. Six other studies randomized classrooms to each condition (Akers et al., 1983, Botvin et al., 1984; Bray et al., 1979; Hansen et al., 1985; Hill et al., 1981; Lauer et al., 1982; Luepker et al., 1981). Only Hansen et al. (1985) verified the comparability of study groups formed in this way. While students are sometimes assigned to classes in a random fashion, this is often not by design and should not be assumed. As an example, randomization of ten classes to each condition did not result in equivalent groups in the study we report here. One way to test for comparability is to gather biological data from all subjects and test for differences in group smoking levels. Though biological measures are weakly correlated with individual self-reported smoking among young adolescents, such measures provide a relatively good measure of population behavior (Luepker et al., 1981; Pechacek, Murray, Luepker, Mittelmark, Johnson, & Shultz, 1984). As Akers et al. (1983) noted, “. . . simply increasing the number of ‘yes’ responses does not by itself demonstrate the validity of those responses. The two groups may have been responding with equal validity, and the non-pipeline group, in fact, had fewer smokers; or the knowledge that deception could be detected might have introduced a systematic bias toward overreporting into the self-reports of the bogus pipeline group. The issue then is whether the level of smoking self-reported in each group, whether higher or lower, can be independently confirmed as valid” (p. 238). Unfortunately, only two studies (Bauman & Dent, 1982; Bauman et al., 1982) reported biological data for all subjects.
No No Yes No No
No No ? No ?
No No No No No
? Yes ? 7 7
No No No No No
Student Class Class Class Class
Verbal Verbal Film Verbal Film
38
143-387
213-476
75-718
84-338
Hansen et al., 1985
Hill et al., 1981
Lauer et al., 1982 Akers et al., 1983
Luepker et al., 1981
Hansen, 1983
Yes ? No
Yes
No
Student
Verbal
138-142
Gillies et al., 1981
Yes ? Yes
?
No
Student
Film
29-55
Evans et al., 1977
Yes ?
No
?
No
Class
Film
145-230
Bray et al., 1979
No ?
No
?
No
Yes
Support Pipeline Hypothesis
No
Class
Verbal, Video, Cartoon
112-126
Botvin et al., 1984
?
Yes
7
Yes
Student
Verbal
39-43
Bauman, 1982
Yes
No
Bauman & Dent, 1982
Yes
Yes
Student
Verbal
319-1178
Study
Pressure to Underreport
Equivalent Groups
Report Biological Data For All Subjects
Unit of Assignment
Bogus Pipeline Method
Sample Size Per Condition
Highly Selected Sample
Table 1. Summary of eleven previous studies of the effect of the ‘bogus pipeline’ procedure on the validity of adolescent smoking self-reports.
10
D.M. MURRAY
et
al.
Sciecfion. Comparing the results of several studies is often difficult, but particularly ‘>o when one of the studies is based on an unusual sample. Bauman et al. (1982) were forced to study only students who agreed with their parents to participate, less than 40% of those originally invited. Severson and Ary (1983) have shown that active consent procedures eliminate many smokers from participation; this restriction could make it difficult to detect a pipeline effect. Evans et al. (1977) reported data based in part on a sample of adolescents attending a summer camp. Here again, it is difficult to determine how representative such a sample was of any population.
Low Pressure to Underreport. Jones and Sigall (1971) identified a necessary condition for the pipeline effect as the perception by the subjects of some “pressure” to underreport. In the absence of this pressure, one should not expect to see a difference in disclosure attributable to the pipeline procedure. Four of the studies which did not replicate the pipeline effect appear to fail this test of “social undesirability.” Hansen (1983) tested only students assigned to detention hall after being caught smoking at school; such students probably felt little pressure to underreport. Hansen et al. (1985) tested only students who had participated in similar testing on two to four previous occasions; prior experience also may reduce pressure to underreport. Similarly, half of the data reported by Akers et al. (1983) and Lauer et al. (1982) came from students who had been surveyed previously. Botvin et al. (1984) acknowledged that their subjects may have felt little pressure to underreport: in their sample, smoking was very common, perhaps reducing its social undesirability. Finally, both Hansen et al. (1985) and Akers et al. (1983) saw no effect among high school students; it is possible that older students, among whom smoking is quite common, feel relatively little pressure to underreport. On the other side of this issue, Bauman and Dent (1982) interviewed their subjects face-to-face and at home and the pipeline procedure led to a substantial increase in reported smoking. Kandel (1975) reported that face-to-face interviews in the home were associated with reduced disclosure of drug use; she speculated that this effect may be due to the strong pressure to underreport created by such unusual survey conditions. Credibility of the Pipeline Message. On the surface, the pipeline procedure appears simple. Convincing several hundred adolescents that the measure is valid may not be simple. Most studies delivered the pipeline message through a verbal presentation; none provided evidence that the students believed them. Five studies used other delivery channels. Evans et al. (1977) used a film presentation and reported a positive pipeline effect. Bray et al. (1979) and Hill et al. (1981) replicated Evans et al.? (1977) study in older populations and also reported strong pipeline effects. Botvin et al. (1984) and Luepker et al. (1981) reported non-significant trends favoring the pipeline hypothesis. In the only direct evaluation of a verbal delivery, Botvin et al. (1984) observed the lowest disclosure rate among those assigned to that condition. On the other hand, Bauman and Dent (1982) observed a strong pipeline effect using a verbal presentation. These findings suggest that the method and quality of the presentation may influence the disclosure rate. This review suggests that optimal conditions for testing the hypothesized pipeline effect include: 1) equivalent groups, 2) enough smokers to provide adequate power to detect a reasonable difference, 3) students who otherwise would perceive some pressure to underreport, 4) a credible pipeline message, and 5) a biological measure to separate smokers from nonsmokers. The study which appears to have come closest to meeting these requirements was that of Bauman and Dent (1982) who reported a strong pipeline effect.
Validity of smoking self-reports
11
This study was designed to provide a test of the pipeline hypothesis where all five of these conditions could be assured. We hypothesized that students would underreport smoking if they had no prior experience with the survey methods, were tested at school and if the prevalence of smoking was low. We also hypothesized that students exposed to the pipeline message through television would be more likely to disclose smoking than those given a verbal presentation. Finally, we made direct tests for group equivalence and underreporting. METHODS
Subjects The sample consisted of 770 tenth-grade students from one of the largest suburban high schools in the Twin Cities metropolitan area. None had participated in any prior smoking survey. Ninety-six percent of the sample was Caucasian, and 51% was female. The parents of each student were contacted prior to the survey using a passive consent procedure; none withheld their child from the study. Procedures In April, 1984, thirty-one tenth grade required English classes were randomly assigned to one of three conditions: control (11 classes), live pipeline (10 classes), or liveplus-video pipeline (10 classes). All students were told they would receive a questionnaire to assess their attitudes and beliefs about cigarette smoking; students were advised of the biological testing at a time determined by their group assignment. Confidentiality of the data and free choice of participation were emphasized in all three groups. When the biological testing was introduced at the end of the class (control group), students were given a second opportunity to refuse to participate in that part of the study. The participants represented 94% of the 10th grade enrollment. The study groups were equivalent in the number of absent students (5Oro)and in the number of refusals (1Cro). The groups were also equivalent in the number of air samples inadequate for analysis (1%) and in the number with incomplete data on their questionnaires (3%). Usable data were obtained for greater than 95% of the students present on the day of the survey. Control group. Students in the control group (n = 262) completed the questionnaire prior to receiving a verbal explanation and live demonstration of the carbon monoxide (CO) measurement procedures. Pencils were withdrawn prior to the CO testing to prevent alteration of the self-reports. Live pipeline. Students in the live pipeline group (n = 254) received the explanation and demonstration of the CO measurement procedures prior to completing the questionnaire. Live-plus-video pipeline. Students in the live-plus-video group (n = 254) also received the explanation and demonstration of carbon monoxide testing prior to completing the questionnaire; following the live demonstration, a videotaped version also was presented to emphasize the pipeline message. Measures Self-report. Self-report data were collected from all students via computer-scored questionnaires. The questionnaire included items on demographics; smoking, alcohol, and marijuana use; and on a number of psychosocial factors associated with drug use.
12
D.M. MURRAY
et al.
Three smoking self-report items were used to form a summary INDEX scaled to reflect the number of cigarettes smoked in the week prior to the survey. This INDEX is well correlated to both expired air carbon monoxide (CO) and salivary thiocyanate (SCN) (Pechacek, Murray, Luepker, Mittelmark, Johnson, & Shultz, 1984). The correlation between the INDEX and CO in this sample was 0.58 (p < .OOl). Carbon Monoxide. CO was measured immediately following the self-report survey in the control group and during the survey in the two pipeline groups. Students were tested individually: they exhaled fully, inhaled, held their breath for 15 seconds, exhaled half their volume, and then exhaled as much remaining air as possible into a balloon attached to a MiniCO device (Catalyst Research Corp, Owens Mills, Maryland). Each sample was filtered through activated charcoal and analyzed for CO, read in parts per million. Students were not shown their CO value to avoid any effect on their selfreports (Hansen & Evans, 1982). Analysis methods Subjects were classified as current smokers separately by CO level ( I 8 ppm) (Pechacek, Murray, Luepker, Mittelmark, Johnson, & Shultz, 1984) and by the composite self-report INDEX (at least one cigarette in the past week). The smoking prevalence rates in the three study groups were compared separately using the two classification methods and again based on the cross-classification of the two methods. Chi-square and log-linear modeling techniques were used to analyze the two- and three-way tables (Feinberg, 1980). All analyses were conducted using BMDP (Dixon & Brown, 1979). RESULTS
Comparability of Groups Since noncomparability of the three groups could inadvertently mask or exaggerate the effects of the pipeline manipulations, we examined the prevalence of CO levels above 8 ppm. The differences between groups were highly significant: the rate in the control group was 19% while it was only 6% and 8% in the live and live-plus-video pipeline groups respectively (X’ = 24.36, df = 2, p < .OOl). In spite of the random assignment of at least 10 classes to each condition, the groups were not equivalent in the prevalence of elevated CO levels, suggesting differences in recent smoking. Self-Reported Smoking Levels The self-report data were first analyzed without consideration for the CO levels. This type of analysis was the only one presented in nine of the previous studies and it may have contributed to the current confusion surrounding the pipeline procedure. By ignoring the CO levels, one is forced to assume that the study groups have equivalent true smoking rates. When the data were analyzed without regard for CO levels, the smoking prevalence rate in the control group was estimated as 18070,while the rates in the two pipeline groups were estimated at 21% and 18% respectively; these differences were nonsignificant and suggested that the pipeline procedure had no effect. The self-report data then were analyzed after partitioning the study groups by CO level. The frequency distribution of self-reported weekly smoking by study group and CO level is presented in Table 2. The log-linear analysis identified a highly significant three-way interaction (LR xz = 17.43, df = 2, p < .OOl). Among students having a low CO level, there were no differences based on treatment condition in the proportion
13
Validity of smoking self-reports
Table 2.
Prevalence of Self-Reported Weekly Smoking by Study Group and CO Level.
Treatment Group
<8 ppm CO n Rate
rl3 ppm CO n Rate
Control Live Pipeline Live and Video Pipeline
199 11.1% 233 15.5% 227 12.3%
46 45.7% 15 100.0% 19 89.5%
who reported smoking. Among students with elevated CO levels, twice as many students in the two pipeline groups admitted smoking compared to the control group. There was no difference between the two pipeline conditions. DISCUSSION
Previous research on the bogus pipeline effect in adolescent populations has produced inconsistent results. Most studies contained design weaknesses which make it difficult to interpret their findings. These weaknesses relate to the equivalence of the study groups, the power of the analyses, the credibility of the pipeline message, the selection of the study sample or the level of social pressure to underreport, Though the majority of the studies failed to support the pipeline hypothesis, their unique and common problems left doubt as to whether the originally postulated pipeline effect was real and about the conditions necessary for achieving such an effect. The present study differs from previous reports in several ways. It was based on a nearly complete sample from a representative high school population in the Twin Cities area. Efforts were made to assure adequate power by including at least 250 subjects per condition. We tested the comparability of the study groups and made adjustments when the groups were not equivalent. Finally, two pipeline messages, believed to differ in credibility, were tested. The data from this experiment support the hypothesis that adolescent smokers are more willing to disclose cigarette use under pipeline conditions. This effect was properly limited to the smokers in the sample; within Jones and Sigall’s (1971) conceptualization, the nonsmokers had not engaged in an undesirable behavior and had no reason to underreport. The pipeline effect also was apparent only when the smokers were partitioned from the total sample. None of the studies which failed to replicate the pipeline effect reported partitioning their samples in this way. Even in this study, where there was strong evidence for the pipeline effect, the effect was masked by collapsing across CO levels. While it is unlikely that this pattern also occurred in each of the previous studies, it demonstrates the danger inherent in assuming study group equivalence when it may not exist. While these data suggest that the pipeline procedure can increase disclosure, they do not support the argument that this will always be the case. To understand this point it is important to recall the original description of the pipeline. Jones and Sigall (1971) argued that persons would be more likely to disclose a socially undesirable behavior if they believed the investigator had an independent and valid method to measure that behavior. There are two necessary conditions: the behavior must be socially undesirable and the subjects must believe the investigator has such a method. As Botvin et al. (1984) have suggested, smoking may not always be a socially undesirable behavior. This is probably the case where smoking is quite common or where
14
D.M. MURRAY et al.
there are few social sanctions against smoking. There may also be less pressure to underreport when students feel assured their responses will be kept confidential. In other situations, there may be considerable social pressure to underreport. The other necessary condition requires that subjects believe the investigators have an independent and valid method to assess the undesirable behavior. When credibility is missing, the pipeline procedure should have no effect. There is evidence from this study, and from the work of Evans et al. (1977), Botvin et al. (1984), Bray et al. (1979), Hill et al. (1981) and Luepker et al. (1981) that the use of a videotape presentation may help to produce a pipeline effect. Botvin et al. (1984) reported results favoring a cartoon presentation. These methods may carry greater credibility through more powerful communication channels. This study suggests that a live presentation and demonstration can be an adequate stimulus. The protocol stated that carbon monoxide would be measured as a “way to more accurately assess your smoking behavior.” This message was followed by a demonstration of the technique by members of the survey staff; thus the live presentation was more graphic than simply reading a prepared statement. The credibility of the message may also depend on the type of independent measure used. Evans et al. (1977) used saliva nicotine assays. These may have high face validity to adolescents since it is widely known that tobacco contains nicotine. Other studies have used saliva thiocyanate or expired air CO, or both. The difference between a saliva test and a breath test has not been tested, but the data from Bauman and Dent (1982) and the current study suggest that a breath test is adequate to produce an effect. Obviously, the more accurate the measure is, and the more familiar it is, the more persuasive is the message. If the students do not recognize the test, they also may not believe the pipeline message. The results from this study suggest that the pipeline effect is replicable, given the appropriate mix of conditions. Previous failures to replicate the pipeline effect may have resulted from the absence of one or both of those conditions or from weaknesses in research design. Future research may help refine the procedures to increase the validity of the smoking assessments. Other research may eventually permit identification of characteristics of populations which reduce the need for a pipeline procedure. Now, it would appear both prudent and conservative to employ as credible a pipeline procedure as possible. Until we can identify in advance those samples for whom the pipeline is not necessary, use of this procedure offers the best assurance of a valid assessment. REFERENCES Akers, R.L., Massey, J., Clarke, W., & Lauer, R.M. (1983). Are self-reports of adolescent deviance valid? Biochemical measures, randomized response, and the bogus pipeline in smoking behavior. Social Forces, 62, 234-251. Bauman, K.E., &Dent, C.W. (1982). Influence of an objective measure on self-reports of behavior. Journal of Applied Psychology, 67, 623428. Bauman, K.E., Koch, G.G., & Bryan, E.S. (1982). Validity of self-reports of adolescent cigarette smoking. The International Journal of the Addictions, 17, 1131-l 136. Biglan, A., Gallison, C., Ary, D., & Thompson, R. (1985). Expired air carbon monoxide and saliva thiocyanate: Relationships to self-reports to marijuana smoking and cigarette smoking. Addiction Behavior, 10, 137-144. Botvin, E.M., Botvin, G.L., Renick, A.D., & Filazzola, J.P. (1984). Adolescents’ self-reports of tobacco, alcohol, and marijuana use: Examining the comparability of videotape, cartoon, and verbal bogus pipeline procedures. Psychological Reports, 55, 379-386. Bray, J.H., Hill, P.C., & Henderson, A.H. (1979). Increasing the validity of self-reports of drug use: Generalizability of a bogus pipeline procedure used a study cigarette smoking. Paper presented at the annual convention of the Southwestern Psychological Association, San Antonio, Texas. Cook, T.D., & Campbell, D.T. (1979). Design and analysis issuesforfield settings. Chicago: Rand McNally Publishing Company.
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15
Dixon, W.J., & Brown, M.B. (1979). BMDP biomedical computer programs P-series. University of California Press, Berkeley, California. Evans, RI., Hansen, W.B., & Mittelmark, M.B. (1977). Increasing the validity of self-reports of smoking behavior in children. Journal of Applied Psychology, 62, 521-523. Fienberg, S.E. (1980). The analysis of cross classified categorical data. Cambridge, MA: The MIT Press. Gillies, P.A., Wilcox, B., Coates, C., Kristmundsdottir, F., & Reid, D.J. (1982). Use of objective measurement in the validation of self-reported smoking in children aged 10 and 11 years: Saliva thiocyanate. Journal of Epidemiology
and Community Health, 36, 205-208.
Hansen, W.B., & Evans, RI. (1982). Feedback versus information concerning carbon monoxide as an early intervention strategy in adolescent smoking. Adolescence, 17, 89-98. Hansen, W.B. (1983). Behavioral predictors of abstinence: Early indicators of a dependence on tobacco among adolescents. The International Journal of the Addictions, 18, 913-920. Hansen, W.B., Malotte, C.K., & Fielding, J.E. (1985). The bogus pipeline revisited: The use of the threat of detection as a means of increasing self-reports of tobacco use. Journal of Applied Psychology. Hill, P.C., Henderson, A.H., Bray, J.H., & Evans, R.I. (1981). Generalizing a self-report validator of cigarette smoking to older adolescents. Replications of Social Psychology, 1, 38-40. Jones, E.E., & Sigall, H. (1971). The bogus pipeline: A new paradigm for measuring affect and attitude. Psychological Bulletin, 76, 349-364.
Kandel, D. (1975). Reaching the hard-to-reach: Illicit drug use among high school absentees. Addictive Diseases, 1, 465-480. Lauer, R.M., Akers, R.L., Massey, J., & Clarke, W.R. (1982). Evaluation of cigarette smoking amongst adolescents: The Muscatine study. Preventive Medicine, 11, 417-428. Luepker, R.V., Pechacek, T.F., Murray, D.M., Johnson, C.A., Hurd, P., & Jacobs, D.R. (1981). Saliva thiocyanate: A chemical indicator of cigarette smoking in adolescents. American Journal of Public Health, 12, 1320-1324. Pechacek, T.F., Fox, B., Murray, D.M., & Luepker, R.V. (1984). Review of techniques for measurement of smoking. In J.D. Matarazzo, S.M. Weiss, J.A. Herd, N.E. Miller, S.M. Weiss (Eds.), Behavioral health: A handbook of health enhancement and disease prevention. New York: John Wiley and Sons, Inc. Pechacek, T.F., Murray, D.M., Luepker, R.V., Mittelmark, M.B., Johnson, CA., & Shultz, J.M. (1984). Measurement of adolescent smoking behavior: Rationale and methods. Journal of BehavioralMedicine, 7, 123-140.
Severson, H.H., & Ary, D. (1983). Sampling bias due to consent procedures with adolescents. Addictive Behaviors, 3, 433-437.
AddictiveBehaviors,
0306-4603/87 $3.00 + .OO Copyright o 1987 Pergamon Journals Ltd
THE VALIDITY OF SMOKING SELF-REPORTS BY ADOLESCENTS: A REEXAMINATION OF THE BOGUS PIPELINE PROCEDURE DAVID M. MURRAY, CATHERINE M. O’CONNELL, CHERYL L. PERRY
LINDA A. SCHMID, and
Division of Epidemiology, School of Public Health, University of Minnesota smoking was measured in a naive tenth grade population under conditions expected to influence the student’s willingness to admit smoking. All students were tested for smoking both by questionnaire and by expired-air carbon monoxide assessment. The carbon monoxide data were used to test the equivalence of the study groups and to partition the sample into smokers and nonsmokers. Of the smokers those who were advised in advance of the biological test were twice as likeiy to admit cigarette use in the past week compared to those who were advised of the testing procedure only after they had completed their questionnaire. A live explanation and demonstration of the biological testing procedure proved as effective as a videotaped message. These data support earlier reports of the ‘bogus pipeline’ effect. Several methodological issues are discussed which may explain previous failures to replicate this finding. Abstract-Cigarette
Adolescent smoking behavior is generally measured by self-reports of frequency and intensity. Though such methods are simple, efficient and inexpensive, a number of factors often render them invalid (Pechacek, Fox, Murray, & Luepker, 1984). For example, adolescents often smoke infrequently and episodically; as a result, it may be difficult for them to characterize their “usual” pattern of smoking. They may not accurately recall the number of cigarettes smoked in recent days or weeks. Neither adolescents nor adults can accurately describe their puff rate, depth of inhalation and other factors related to physiological exposure. Adolescents may also try to mislead the investigator and underreport smoking behavior out of embarrassment or in a desire to please. Finally, they may exaggerate smoking levels to appear older or to be uncooperative. The weaknesses of the self-report have prompted extensive research on objective measures of smoking. Numerous investigations document the relationship between carbon monoxide, thiocyanate, nicotine and cotinine and tobacco use among adolescents and adults (Pechacek, Fox, Murray, & Luepker, 1984). These biological measures are helpful but imperfect because adolescent smoking remains relatively rare and develops gradually. Among young adolescents, smoking is often more appropriately characterized as a social display rather than as drug self-administration. As a result, biological measures are weakly correlated with self-reports of smoking among young adolescents (Biglan, Gallison, Ary, & Thompson, 1985; Pechacek, Murray, Luepker, Mittelmark, Johnson, & Shultz, 1984). Other researchers have developed methods to increase the validity of smoking selfThis research was supported through grants from the National Institute on Drug Abuse (ROl DA03205 and ROl DA03044) and the National Cancer Institute (ROl CA38275). The authors wish to thank Minnesota Independent School District 11 for its cooperation in this research. We also thank Jan Whitbeck who directed the school survey; Lisa Roche who assisted with the data analyses; Terry Pechacek and Susan Blake who commented on an earlier draft; and Laurie Zurbey who prepared the manuscript. Requests for reprints should be sent to David M. Murray, PhD, Division of Epidemiology, School of Public Health, University of Minnesota, Stadium Gate 20, 611 Beacon Street S.E., Minneapolis, MN 55455.
8
D.M. MURRAY
et al.
reports. One of the best known is the “bogus pipeline” method. This approach assumes that adolescents will be more likely to disclose socially undesirable behavior if they believe the investigator has an independent and objective measure of that behavior. Evans, Hansen, and Mittelmark (1977) first applied this method to smoking, borrowing from the work of Jones and Sigall(l971). Jones and Sigall(l971) used a false physiological test and attached the “bogus” label to this “pipeline to the truth.” Valid physiological measures have been used in the smoking applications, but the misnomer “bogus pipeline” is still used to describe the method. The study of Evans et al. (1977) went unchallenged for several years. Five other reports seemed to support Evans et al.‘s early findings (Bauman & Dent, 1982; Bray, Hill, & Henderson, 1979; Gillies, Wilcox, Coates, Kristmundsdottir, & Reid, 1982; Hill, Henderson, Bray, & Evans, 1981; Luepker, Pechacek, Murray, Johnson, Hurd, & Jacobs, 1981). More recently however, the pipeline effect has come into question. Bauman, Koch and Bryan (1982) reported no difference in self-reported smoking rates between students assessed under pipeline and non-pipeline conditions. Others also failed to replicate the pipeline effect (Akers, Massey, Clarke, & Lauer, 1983; Botvin, Botvin, Renick, & Filazzola, 1984; Hansen, 1983; Hansen, Malotte, & Fielding, 1985; Lauer, Akers, Massey, & Clarke, 1982). A careful review of the eleven previous papers indicates that five reported a pipeline effect while six did not. The current debate is thus understandable. These studies are summarized in Table 1. A close examination of these reports suggests several possible explanations for their findings: Nonequivalence of Groups. The equivalence of study groups is important to the interpretation of findings from any experimental or quasi-experimental design (Cook & Campbell, 1979). Randomization of individual subjects provides such assurance where sufficient numbers are randomized to each group (e.g., Bauman & Dent, 1982; Gillies et al., 1982). However, the small sample sizes of Bauman, Koch, and Bryan (1982), Evans et al. (1977) and Hansen (1983) may have been inadequate to assure comparability, especially given the low prevalence of adolescent smoking. Six other studies randomized classrooms to each condition (Akers et al., 1983, Botvin et al., 1984; Bray et al., 1979; Hansen et al., 1985; Hill et al., 1981; Lauer et al., 1982; Luepker et al., 1981). Only Hansen et al. (1985) verified the comparability of study groups formed in this way. While students are sometimes assigned to classes in a random fashion, this is often not by design and should not be assumed. As an example, randomization of ten classes to each condition did not result in equivalent groups in the study we report here. One way to test for comparability is to gather biological data from all subjects and test for differences in group smoking levels. Though biological measures are weakly correlated with individual self-reported smoking among young adolescents, such measures provide a relatively good measure of population behavior (Luepker et al., 1981; Pechacek, Murray, Luepker, Mittelmark, Johnson, & Shultz, 1984). As Akers et al. (1983) noted, “. . . simply increasing the number of ‘yes’ responses does not by itself demonstrate the validity of those responses. The two groups may have been responding with equal validity, and the non-pipeline group, in fact, had fewer smokers; or the knowledge that deception could be detected might have introduced a systematic bias toward overreporting into the self-reports of the bogus pipeline group. The issue then is whether the level of smoking self-reported in each group, whether higher or lower, can be independently confirmed as valid” (p. 238). Unfortunately, only two studies (Bauman & Dent, 1982; Bauman et al., 1982) reported biological data for all subjects.
No No Yes No No
No No ? No ?
No No No No No
? Yes ? 7 7
No No No No No
Student Class Class Class Class
Verbal Verbal Film Verbal Film
38
143-387
213-476
75-718
84-338
Hansen et al., 1985
Hill et al., 1981
Lauer et al., 1982 Akers et al., 1983
Luepker et al., 1981
Hansen, 1983
Yes ? No
Yes
No
Student
Verbal
138-142
Gillies et al., 1981
Yes ? Yes
?
No
Student
Film
29-55
Evans et al., 1977
Yes ?
No
?
No
Class
Film
145-230
Bray et al., 1979
No ?
No
?
No
Yes
Support Pipeline Hypothesis
No
Class
Verbal, Video, Cartoon
112-126
Botvin et al., 1984
?
Yes
7
Yes
Student
Verbal
39-43
Bauman, 1982
Yes
No
Bauman & Dent, 1982
Yes
Yes
Student
Verbal
319-1178
Study
Pressure to Underreport
Equivalent Groups
Report Biological Data For All Subjects
Unit of Assignment
Bogus Pipeline Method
Sample Size Per Condition
Highly Selected Sample
Table 1. Summary of eleven previous studies of the effect of the ‘bogus pipeline’ procedure on the validity of adolescent smoking self-reports.
10
D.M. MURRAY
et
al.
Sciecfion. Comparing the results of several studies is often difficult, but particularly ‘>o when one of the studies is based on an unusual sample. Bauman et al. (1982) were forced to study only students who agreed with their parents to participate, less than 40% of those originally invited. Severson and Ary (1983) have shown that active consent procedures eliminate many smokers from participation; this restriction could make it difficult to detect a pipeline effect. Evans et al. (1977) reported data based in part on a sample of adolescents attending a summer camp. Here again, it is difficult to determine how representative such a sample was of any population.
Low Pressure to Underreport. Jones and Sigall (1971) identified a necessary condition for the pipeline effect as the perception by the subjects of some “pressure” to underreport. In the absence of this pressure, one should not expect to see a difference in disclosure attributable to the pipeline procedure. Four of the studies which did not replicate the pipeline effect appear to fail this test of “social undesirability.” Hansen (1983) tested only students assigned to detention hall after being caught smoking at school; such students probably felt little pressure to underreport. Hansen et al. (1985) tested only students who had participated in similar testing on two to four previous occasions; prior experience also may reduce pressure to underreport. Similarly, half of the data reported by Akers et al. (1983) and Lauer et al. (1982) came from students who had been surveyed previously. Botvin et al. (1984) acknowledged that their subjects may have felt little pressure to underreport: in their sample, smoking was very common, perhaps reducing its social undesirability. Finally, both Hansen et al. (1985) and Akers et al. (1983) saw no effect among high school students; it is possible that older students, among whom smoking is quite common, feel relatively little pressure to underreport. On the other side of this issue, Bauman and Dent (1982) interviewed their subjects face-to-face and at home and the pipeline procedure led to a substantial increase in reported smoking. Kandel (1975) reported that face-to-face interviews in the home were associated with reduced disclosure of drug use; she speculated that this effect may be due to the strong pressure to underreport created by such unusual survey conditions. Credibility of the Pipeline Message. On the surface, the pipeline procedure appears simple. Convincing several hundred adolescents that the measure is valid may not be simple. Most studies delivered the pipeline message through a verbal presentation; none provided evidence that the students believed them. Five studies used other delivery channels. Evans et al. (1977) used a film presentation and reported a positive pipeline effect. Bray et al. (1979) and Hill et al. (1981) replicated Evans et al.? (1977) study in older populations and also reported strong pipeline effects. Botvin et al. (1984) and Luepker et al. (1981) reported non-significant trends favoring the pipeline hypothesis. In the only direct evaluation of a verbal delivery, Botvin et al. (1984) observed the lowest disclosure rate among those assigned to that condition. On the other hand, Bauman and Dent (1982) observed a strong pipeline effect using a verbal presentation. These findings suggest that the method and quality of the presentation may influence the disclosure rate. This review suggests that optimal conditions for testing the hypothesized pipeline effect include: 1) equivalent groups, 2) enough smokers to provide adequate power to detect a reasonable difference, 3) students who otherwise would perceive some pressure to underreport, 4) a credible pipeline message, and 5) a biological measure to separate smokers from nonsmokers. The study which appears to have come closest to meeting these requirements was that of Bauman and Dent (1982) who reported a strong pipeline effect.
Validity of smoking self-reports
11
This study was designed to provide a test of the pipeline hypothesis where all five of these conditions could be assured. We hypothesized that students would underreport smoking if they had no prior experience with the survey methods, were tested at school and if the prevalence of smoking was low. We also hypothesized that students exposed to the pipeline message through television would be more likely to disclose smoking than those given a verbal presentation. Finally, we made direct tests for group equivalence and underreporting. METHODS
Subjects The sample consisted of 770 tenth-grade students from one of the largest suburban high schools in the Twin Cities metropolitan area. None had participated in any prior smoking survey. Ninety-six percent of the sample was Caucasian, and 51% was female. The parents of each student were contacted prior to the survey using a passive consent procedure; none withheld their child from the study. Procedures In April, 1984, thirty-one tenth grade required English classes were randomly assigned to one of three conditions: control (11 classes), live pipeline (10 classes), or liveplus-video pipeline (10 classes). All students were told they would receive a questionnaire to assess their attitudes and beliefs about cigarette smoking; students were advised of the biological testing at a time determined by their group assignment. Confidentiality of the data and free choice of participation were emphasized in all three groups. When the biological testing was introduced at the end of the class (control group), students were given a second opportunity to refuse to participate in that part of the study. The participants represented 94% of the 10th grade enrollment. The study groups were equivalent in the number of absent students (5Oro)and in the number of refusals (1Cro). The groups were also equivalent in the number of air samples inadequate for analysis (1%) and in the number with incomplete data on their questionnaires (3%). Usable data were obtained for greater than 95% of the students present on the day of the survey. Control group. Students in the control group (n = 262) completed the questionnaire prior to receiving a verbal explanation and live demonstration of the carbon monoxide (CO) measurement procedures. Pencils were withdrawn prior to the CO testing to prevent alteration of the self-reports. Live pipeline. Students in the live pipeline group (n = 254) received the explanation and demonstration of the CO measurement procedures prior to completing the questionnaire. Live-plus-video pipeline. Students in the live-plus-video group (n = 254) also received the explanation and demonstration of carbon monoxide testing prior to completing the questionnaire; following the live demonstration, a videotaped version also was presented to emphasize the pipeline message. Measures Self-report. Self-report data were collected from all students via computer-scored questionnaires. The questionnaire included items on demographics; smoking, alcohol, and marijuana use; and on a number of psychosocial factors associated with drug use.
12
D.M. MURRAY
et al.
Three smoking self-report items were used to form a summary INDEX scaled to reflect the number of cigarettes smoked in the week prior to the survey. This INDEX is well correlated to both expired air carbon monoxide (CO) and salivary thiocyanate (SCN) (Pechacek, Murray, Luepker, Mittelmark, Johnson, & Shultz, 1984). The correlation between the INDEX and CO in this sample was 0.58 (p < .OOl). Carbon Monoxide. CO was measured immediately following the self-report survey in the control group and during the survey in the two pipeline groups. Students were tested individually: they exhaled fully, inhaled, held their breath for 15 seconds, exhaled half their volume, and then exhaled as much remaining air as possible into a balloon attached to a MiniCO device (Catalyst Research Corp, Owens Mills, Maryland). Each sample was filtered through activated charcoal and analyzed for CO, read in parts per million. Students were not shown their CO value to avoid any effect on their selfreports (Hansen & Evans, 1982). Analysis methods Subjects were classified as current smokers separately by CO level ( I 8 ppm) (Pechacek, Murray, Luepker, Mittelmark, Johnson, & Shultz, 1984) and by the composite self-report INDEX (at least one cigarette in the past week). The smoking prevalence rates in the three study groups were compared separately using the two classification methods and again based on the cross-classification of the two methods. Chi-square and log-linear modeling techniques were used to analyze the two- and three-way tables (Feinberg, 1980). All analyses were conducted using BMDP (Dixon & Brown, 1979). RESULTS
Comparability of Groups Since noncomparability of the three groups could inadvertently mask or exaggerate the effects of the pipeline manipulations, we examined the prevalence of CO levels above 8 ppm. The differences between groups were highly significant: the rate in the control group was 19% while it was only 6% and 8% in the live and live-plus-video pipeline groups respectively (X’ = 24.36, df = 2, p < .OOl). In spite of the random assignment of at least 10 classes to each condition, the groups were not equivalent in the prevalence of elevated CO levels, suggesting differences in recent smoking. Self-Reported Smoking Levels The self-report data were first analyzed without consideration for the CO levels. This type of analysis was the only one presented in nine of the previous studies and it may have contributed to the current confusion surrounding the pipeline procedure. By ignoring the CO levels, one is forced to assume that the study groups have equivalent true smoking rates. When the data were analyzed without regard for CO levels, the smoking prevalence rate in the control group was estimated as 18070,while the rates in the two pipeline groups were estimated at 21% and 18% respectively; these differences were nonsignificant and suggested that the pipeline procedure had no effect. The self-report data then were analyzed after partitioning the study groups by CO level. The frequency distribution of self-reported weekly smoking by study group and CO level is presented in Table 2. The log-linear analysis identified a highly significant three-way interaction (LR xz = 17.43, df = 2, p < .OOl). Among students having a low CO level, there were no differences based on treatment condition in the proportion
13
Validity of smoking self-reports
Table 2.
Prevalence of Self-Reported Weekly Smoking by Study Group and CO Level.
Treatment Group
<8 ppm CO n Rate
rl3 ppm CO n Rate
Control Live Pipeline Live and Video Pipeline
199 11.1% 233 15.5% 227 12.3%
46 45.7% 15 100.0% 19 89.5%
who reported smoking. Among students with elevated CO levels, twice as many students in the two pipeline groups admitted smoking compared to the control group. There was no difference between the two pipeline conditions. DISCUSSION
Previous research on the bogus pipeline effect in adolescent populations has produced inconsistent results. Most studies contained design weaknesses which make it difficult to interpret their findings. These weaknesses relate to the equivalence of the study groups, the power of the analyses, the credibility of the pipeline message, the selection of the study sample or the level of social pressure to underreport, Though the majority of the studies failed to support the pipeline hypothesis, their unique and common problems left doubt as to whether the originally postulated pipeline effect was real and about the conditions necessary for achieving such an effect. The present study differs from previous reports in several ways. It was based on a nearly complete sample from a representative high school population in the Twin Cities area. Efforts were made to assure adequate power by including at least 250 subjects per condition. We tested the comparability of the study groups and made adjustments when the groups were not equivalent. Finally, two pipeline messages, believed to differ in credibility, were tested. The data from this experiment support the hypothesis that adolescent smokers are more willing to disclose cigarette use under pipeline conditions. This effect was properly limited to the smokers in the sample; within Jones and Sigall’s (1971) conceptualization, the nonsmokers had not engaged in an undesirable behavior and had no reason to underreport. The pipeline effect also was apparent only when the smokers were partitioned from the total sample. None of the studies which failed to replicate the pipeline effect reported partitioning their samples in this way. Even in this study, where there was strong evidence for the pipeline effect, the effect was masked by collapsing across CO levels. While it is unlikely that this pattern also occurred in each of the previous studies, it demonstrates the danger inherent in assuming study group equivalence when it may not exist. While these data suggest that the pipeline procedure can increase disclosure, they do not support the argument that this will always be the case. To understand this point it is important to recall the original description of the pipeline. Jones and Sigall (1971) argued that persons would be more likely to disclose a socially undesirable behavior if they believed the investigator had an independent and valid method to measure that behavior. There are two necessary conditions: the behavior must be socially undesirable and the subjects must believe the investigator has such a method. As Botvin et al. (1984) have suggested, smoking may not always be a socially undesirable behavior. This is probably the case where smoking is quite common or where
14
D.M. MURRAY et al.
there are few social sanctions against smoking. There may also be less pressure to underreport when students feel assured their responses will be kept confidential. In other situations, there may be considerable social pressure to underreport. The other necessary condition requires that subjects believe the investigators have an independent and valid method to assess the undesirable behavior. When credibility is missing, the pipeline procedure should have no effect. There is evidence from this study, and from the work of Evans et al. (1977), Botvin et al. (1984), Bray et al. (1979), Hill et al. (1981) and Luepker et al. (1981) that the use of a videotape presentation may help to produce a pipeline effect. Botvin et al. (1984) reported results favoring a cartoon presentation. These methods may carry greater credibility through more powerful communication channels. This study suggests that a live presentation and demonstration can be an adequate stimulus. The protocol stated that carbon monoxide would be measured as a “way to more accurately assess your smoking behavior.” This message was followed by a demonstration of the technique by members of the survey staff; thus the live presentation was more graphic than simply reading a prepared statement. The credibility of the message may also depend on the type of independent measure used. Evans et al. (1977) used saliva nicotine assays. These may have high face validity to adolescents since it is widely known that tobacco contains nicotine. Other studies have used saliva thiocyanate or expired air CO, or both. The difference between a saliva test and a breath test has not been tested, but the data from Bauman and Dent (1982) and the current study suggest that a breath test is adequate to produce an effect. Obviously, the more accurate the measure is, and the more familiar it is, the more persuasive is the message. If the students do not recognize the test, they also may not believe the pipeline message. The results from this study suggest that the pipeline effect is replicable, given the appropriate mix of conditions. Previous failures to replicate the pipeline effect may have resulted from the absence of one or both of those conditions or from weaknesses in research design. Future research may help refine the procedures to increase the validity of the smoking assessments. Other research may eventually permit identification of characteristics of populations which reduce the need for a pipeline procedure. Now, it would appear both prudent and conservative to employ as credible a pipeline procedure as possible. Until we can identify in advance those samples for whom the pipeline is not necessary, use of this procedure offers the best assurance of a valid assessment. REFERENCES Akers, R.L., Massey, J., Clarke, W., & Lauer, R.M. (1983). Are self-reports of adolescent deviance valid? Biochemical measures, randomized response, and the bogus pipeline in smoking behavior. Social Forces, 62, 234-251. Bauman, K.E., &Dent, C.W. (1982). Influence of an objective measure on self-reports of behavior. Journal of Applied Psychology, 67, 623428. Bauman, K.E., Koch, G.G., & Bryan, E.S. (1982). Validity of self-reports of adolescent cigarette smoking. The International Journal of the Addictions, 17, 1131-l 136. Biglan, A., Gallison, C., Ary, D., & Thompson, R. (1985). Expired air carbon monoxide and saliva thiocyanate: Relationships to self-reports to marijuana smoking and cigarette smoking. Addiction Behavior, 10, 137-144. Botvin, E.M., Botvin, G.L., Renick, A.D., & Filazzola, J.P. (1984). Adolescents’ self-reports of tobacco, alcohol, and marijuana use: Examining the comparability of videotape, cartoon, and verbal bogus pipeline procedures. Psychological Reports, 55, 379-386. Bray, J.H., Hill, P.C., & Henderson, A.H. (1979). Increasing the validity of self-reports of drug use: Generalizability of a bogus pipeline procedure used a study cigarette smoking. Paper presented at the annual convention of the Southwestern Psychological Association, San Antonio, Texas. Cook, T.D., & Campbell, D.T. (1979). Design and analysis issuesforfield settings. Chicago: Rand McNally Publishing Company.
Validity of smoking self-reports
15
Dixon, W.J., & Brown, M.B. (1979). BMDP biomedical computer programs P-series. University of California Press, Berkeley, California. Evans, RI., Hansen, W.B., & Mittelmark, M.B. (1977). Increasing the validity of self-reports of smoking behavior in children. Journal of Applied Psychology, 62, 521-523. Fienberg, S.E. (1980). The analysis of cross classified categorical data. Cambridge, MA: The MIT Press. Gillies, P.A., Wilcox, B., Coates, C., Kristmundsdottir, F., & Reid, D.J. (1982). Use of objective measurement in the validation of self-reported smoking in children aged 10 and 11 years: Saliva thiocyanate. Journal of Epidemiology
and Community Health, 36, 205-208.
Hansen, W.B., & Evans, RI. (1982). Feedback versus information concerning carbon monoxide as an early intervention strategy in adolescent smoking. Adolescence, 17, 89-98. Hansen, W.B. (1983). Behavioral predictors of abstinence: Early indicators of a dependence on tobacco among adolescents. The International Journal of the Addictions, 18, 913-920. Hansen, W.B., Malotte, C.K., & Fielding, J.E. (1985). The bogus pipeline revisited: The use of the threat of detection as a means of increasing self-reports of tobacco use. Journal of Applied Psychology. Hill, P.C., Henderson, A.H., Bray, J.H., & Evans, R.I. (1981). Generalizing a self-report validator of cigarette smoking to older adolescents. Replications of Social Psychology, 1, 38-40. Jones, E.E., & Sigall, H. (1971). The bogus pipeline: A new paradigm for measuring affect and attitude. Psychological Bulletin, 76, 349-364.
Kandel, D. (1975). Reaching the hard-to-reach: Illicit drug use among high school absentees. Addictive Diseases, 1, 465-480. Lauer, R.M., Akers, R.L., Massey, J., & Clarke, W.R. (1982). Evaluation of cigarette smoking amongst adolescents: The Muscatine study. Preventive Medicine, 11, 417-428. Luepker, R.V., Pechacek, T.F., Murray, D.M., Johnson, C.A., Hurd, P., & Jacobs, D.R. (1981). Saliva thiocyanate: A chemical indicator of cigarette smoking in adolescents. American Journal of Public Health, 12, 1320-1324. Pechacek, T.F., Fox, B., Murray, D.M., & Luepker, R.V. (1984). Review of techniques for measurement of smoking. In J.D. Matarazzo, S.M. Weiss, J.A. Herd, N.E. Miller, S.M. Weiss (Eds.), Behavioral health: A handbook of health enhancement and disease prevention. New York: John Wiley and Sons, Inc. Pechacek, T.F., Murray, D.M., Luepker, R.V., Mittelmark, M.B., Johnson, CA., & Shultz, J.M. (1984). Measurement of adolescent smoking behavior: Rationale and methods. Journal of BehavioralMedicine, 7, 123-140.
Severson, H.H., & Ary, D. (1983). Sampling bias due to consent procedures with adolescents. Addictive Behaviors, 3, 433-437.