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Identifying mechanisms of adoption of tobacco and alcohol use among youth: The Bogalusa heart study
Social Networks 13 (1991) 91-104 North-Holland
91
Identifying mechanisms of adoption of tobacco and alcohol use among youth: The Bogalusa heart study * Saundra MacD. Hunter, Igor A. Vizelberg and Gerald S. Berenson * * Department
of Medicine, Louisiana State University Medical Center, New Orleans, LA 70112, USA
Network procedures revealed social influence mechanisms on alcohol and tobacco adoption. Children who smoke have best friends who smoke. Children who drink additionally develop drinking cliques. Smokeless tobacco is less social. Tobacco and alcohol adoption also spreads indirectly by imitation of an admired other’s friends. Children’s healthful programs must develop techniques which consider the sociability, visibility, social norms and public acceptance of the behavior, indirect nature of role models, and social support for non- or alternate use.
1. In~~uetion Few studies explore friendship structures among youth and their influence on health behavior adoption/diffusion. Most recently, “Just Say NO” campaigns assume that the only mechanism influencing children to use tobacco, alcohol and drugs is direct verbal pressure from peers (Evans et al. 1981). While not denying that this is sometimes true, children are also influenced by observing others and the consequences of ‘the other’s behavior (Bandura 1986). Thus, if children observe another person punished for behaving one way, they will not likely imitate that behavior. Conversely, if children see another being rewarded for an action, then they are more likely to imitate that action. * This research was supported by research grant (ROI-HL-38844) from the National Heart, Lung, and Blood Institute of the United States Public Health Service (USPHS). We thank Mrs. Bettye Seal for her work as community coordinator, the nurses of the project staff, the teachers and staff of the Bogalusa school system, the Bogalusa community volunteers, and the children of Bogalusa and their parents for making this study possible. ** Reprint requests to Gerald S. Berenson, M.D., Department of Medicine, Louisiana State University Medical School, 1542 Tulane Avenue, New Orleans, LA 70112 USA. 037%8733/91/$03.50
0 1991 - Elsevier Science Publishers B.V. (North-Holland)
92
S.MacD. Hunter et al. / Tobacco and alcohol USCamong youth
Most prevention programs teach children communication techniques involving refusal skills to handle direct peer pressure to use tobacco (Flay 1985). Children may also make choices and act based on the circuitous, non-verbal influence of others as role models. Interventions do not take into account the informal and non-verbal nature of the social influence process. This may account for recent findings which show that long-term effects of school based intervention programs lose their effectiveness over time (Flay 1985, 1987). However, it is difficult to research indirect, non-verbal influences of role models. Network analysis, which examines relations that connect peers within a group, may uncover non-verbal influences by producing a descriptive view of peer structures and the self reported behaviors of their members. This method may detect emergent behavior and its mechanism of diffusion throughout a peerage. It has the potential to illustrate how the child influences others as well as being influenced by them, either directly or circuitously. The purpose of this paper is to present findings from a large network of children who were asked questions about the use of tobacco and alcohol. The goal was to get a clearer description of the direct and indirect mechanisms underlying the emergent use of tobacco and alcohol. A network approach will develop a model of peer structures and allow comparisons of those structures to self-report behaviors of their members. Most previous research on the influence of friends on the use of tobacco or alcohol relied on the respondent’s perception of his or her friend’s use. Reporting the friend’s behavior in this way may overestimate the similarity between the friend’s use and the respondent’s own behavior. Using the friend’s actual report of behavior reduces the chance of misclassification and avoids the methodological problem associated with potentially incorrect perception of the friend’s behavior by matching the respondent with the friend’s actual reported tobacco or alcohol use. Findings from this method may provide information for intervention programs specifically designed to cultivate successful adoption of health enhancing behaviors in children and adolescents. 2. Data During a cross-sectional screening of cardiovascular risk factor variables in the biracial community of Bogalusa, Louisiana (Berenson 1980,
XMacD.
Hunter et al. / Tobacco and alcohol use among youth
93
1986) 2305 students, ages 8-17, completed a questionnaire consisting of alcohol/tobacco use and friendship choices. The children were assured of confidentiality. They sat behind specially constructed booths. It was administered by trained monitors in the school setting and took an average of 5-15 minutes to complete. In Grades 3-6, posters were used to help the children understand the question; and, the questions were read to them on a tape recorder. Two weeks later 449 children were retested to assess reliability. 2. I. Measures Students were asked to answer: (1) “Who from school are your best friends?” (2) “Who from school would you like to be your friend?” (3) “Who from school do you spend the most free time with?” A fixed format was followed with three spaces provided to the children to write their choices. This may have underestimated the actual linkages present in the system (Holland and Leinhardt 1975). Children wrote the first and last name of each friend. If there was difficulty with the spelling, the monitor provided assistance. The local telephone directory was also available to aid with spelling. Children were requested not to write “ nick names.” A population census was developed which contained all children currently enrolled in Bogalusa schools and their identification number. After the children completed the questionnaires, identification numbers were assigned manually to each friend selected by the research staff. In this manner, selected friends were linked with the respondent. Of those who completed the sociometric questionnaire, 51% were female and 49% were male; 65% white and 35% black. The sample represented over 80% of all children who were screened that year in Bogalusa. Test-retest reliability over two points in time found that the youngest and oldest age groups were the most consistent in their choices (82% for 8 years old; and, 95% for 17 years old) and there was a general increase in consistency from age 9 through age 17 (Shrum et al. 1988) in naming “Best Friends” and “Free-time Friends”. Others have similar findings of a positive association between consistency and age (Hallinan 1979; Bemdt 1982). Each child was asked to respond to questions about the use of cigarettes, snuff, chewing tobacco and alcohol. Current cigarette smokers were defined as someone who smoked at least one cigarette per week; or, someone who smoked less than one cigarette per week.
94
S. MacD. Hunier et al. / Tobacco and alcohol use among youth
Current alcohol use was defined as someone who drank at least one drink of beer, wine or hard liquor per week; or, less than-one drink per week. Users of chewing tobacco or snuff were defined as anyone who tried these products. Cigarette smoking behavior was validated with plasma thiocyanate. Measures of cigarette smoking, smokeless tobacco, and alcohol indicated reasonable reliability and validity. Methods used to insure the collection of reliable and valid data, as well as, related findings are reported elsewhere (Hunter, et al. 1980, 1982, 1986a, 1987; Webber et al. 1982; Voors et al. 1982; Bat@ et al. 1982; Croft et al. 1985; Freedman et al. 1986; Burke et al. 1988; Johnson et al. 1989).
3. Results Three procedures utilizing network data to reveal direct and indirect social influence mechanisms on tobacco and alcohol adoption is presented. 3. I. Attribute
analyses
Using attribute analyses, Figures 1, 2 and 3 show the relationship between personal tobacco use patterns in white males (N approximately 700) with those of their Best Friends (BF), Free-time Friends (FTF), and Admired Friends (AF) (Knoke and Kuklinski, 1983). Only
* Subject Friend
Does
Not
Dips Snuff
Use
* Subject
Selected
Friend
Uses
Does Not Dip Snuff
*
White N ::
Males:
8-17
yews
old
700
Fig. 1. Attribute analysis of friends’ snuff dipping behavior: The Bogalusa heart study.
95
S.MacD. Hunter et al. / Tobacco and alcohol we among youth * Subiect Friend Does Not Use -
*
Subject
Chews Tobacco
Does
Not
Chew
*
Selected Friend Uses
Tobacco
White Males: 8-17
years old
N 2 700 Fig. 2. Attribute
analysis
of friends’ chewing
behavior:
The Bogalusa
heart study.
white males are selected because there is < 1% usage of these products for the other race/gender groups. Approximately 19-2156 of white males did not select friends in any of the categories. There is a significant difference in the friends selected by cigarette smokers and non-smokers (FTF and BF Chi Square: P = 0.000; AF: ns). Nonsmoking males are much more likely to select friends who do not smoke than those who smoke (11% BF, 14% AF, 7% FTF). Similarly, among cigarette using males, 47% had Best Friends, 24% Admired Friends, and 43% Free-Time Friends who smoked cigarettes. This was
l Subject iriend Does Not Use
* Subject
Smokes
Cigarettes Selected Friend Uses
Does Not Smoke
*
Cigarettes
White Males: 0-17
years old
N :: 700 Fig. 3. Attribute
analysis
of friends’ cigarette
smoking
behavior:
The Bogalusa
heart study.
96
ShfacD.
Hunter et al. / Tobacco and alcohol use among youth
* Subiect
* Subject
Uses Alcohol
Does Not Use_Alcohol
*
White Males: 8-17
years old
N :: 700 Fig. 4. Attribute analysis of friends’ alcohol use: The Bogalusa heart study.
not the case for the use of chewing tobacco and snuff (BF: Chi Square: P = 0.000; FTF (chew) Chi Square: P = 0.05: AF: ns). Even if the subject did not use, he was just as likely to have friends who did. Over 30% of those males who did not use snuff or chew tobacco had a Best Friend who did. Figure 4 shows attribute analysis for alcohol use. Close to 80% of all friends drink if the subject also drinks. Whereas, if the subject does not drink, 56% of those admired Friends do (FTF, BF: Chi Square, P = 0.000; AF: Chi Square, P = 0.02). 3.2. Cliques Cliques were identified as highly cohesive subsets of children where three or more children all chose each other as “Best Friends” or “Free-Time Friends.” These are presented as digraphs (directional graph). Paths (a connection with someone outside the clique) were identified also. Overall 48 cliques consisting of 140 children were identified. Thirtyfour cliques used no tobacco or alcohol products. The following discussion will concern only those seven cliques which have two or more members using alcohol and/or tobacco. Strongly connected digraphs are presented in Figures 5, 6, 7 and 8 indicating cliques and their tobacco and alcohol behaviors. Figure 5 displays alcohol behavior among three females cliques. Two of these cliques contain only black females and one is composed of white
SMacD.
Hunter et al. / Tobacco and alcohol use among youth
Fig. 5. Alcohol behavior among three
97
: cliques: The Bogalusa heart study.
females. All three cliques had members which were bridge children. All of the girls in the cliques were 14-17 years old. Except in one case, female bridge children related to an older outside male. In one clique (white), there was one member who did not drink. She had a reciprocal relationship with another non-drinker outside of the clique. One of the black cliques had a member who did not drink. In this case, that member had a non-reciprocal relationships with two drinking males
Fig. 6. Chewing behavior within lo-year-old
white male clique: The Bogalusa heart study.
98
S.MacD.
Hunter et al. / Tobacco and alcohol use among youth 10-17 --~
*0* 81.Ck Whl,. Y.8.
El
F.l7l.l.
Cl3 m
Smoklns
Clsarattes
Ch.wl”g
TOS.CCO
Snuff Drlnklnp =
Fig. 7. Multibehavioral
Yisslng
C11sokOl D.1.
h
B.,1
F,l.“lI
w
F,..
Tlrn.
r\
Cllq”. - (All r.slpr0s.l clwlc..: I).., Friend .nd F,.. Tim. Frland)
F,l.“d
risk factors among two white male cliques: The Bogalusa heart study.
outside the clique. Two cliques had drinking bridge children who connected with non-drinkers outside the clique who she considered to be her Best Friend or Free-Time Friend.
Female
Smoking
CIgarettea
Chewing
Tobacco
Snuff Drinking
Alcohol
MI.slng
Data
Beat
Friend
Free
Time
Clique
- (All
choices: and
Free
Frland
reclprqcal Be.1
Frlond
Time
Fig. 8. Health behavior of gender integrated white clique: The Bogalusa heart study
FrIendI
SiUacD.
Hunter et al. / Tobacco and alcohol use among youth
99
The youngest clique (Figure 6) consisted of lo-year-old white males who chewed tobacco. It is interesting to note that in this clique, one member also used snuff. Figure 7 portrays two unconnected cliques which has members who are polyusers. Both are comprised of white males, one is age homogenous (13 years old). A reciprocal relationship exists between a younger boy within the clique (age 13) and older one outside of it (age 14). Finally, Figure 8 demonstrates that cliques can consist of both genders. This clique’s focal attribute seems to be alcohol, with all members choosing the same person outside of the clique as their Best Friend. He, however, did not choose any members of the clique as neither a Free-time Friend nor a Best Friend. The male member of the clique has two other friends outside the clique, with a total of four Best Friends who drink alcohol. 3.3. Ego-centered The last procedure is identified as an ego-centered-relational digraph. The first research question is to identify the most popular person
Fig. 9. Characteristics and health habits of respondents who picked Mary as the person who they wanted to be their best Friend: The Bogalma heart study.
loo
S. MacD. Hun!er et al. / Tobacco and alcohol we among youth
13-14 ----
Apa Black While
SmokinQ Cigarettea
ChewhQ Tobacco
,,rl,lklAQ Alcohol
Ml&,inQ Data 13
13 14
Fig. 10. Health habits of children
who mary chose as friends:
The Bogalusa
heart study.
during this survey year. In response to the question, “Who from school would you like to be your friend. 7” 25 children selected a white female (pseudonym “Mary”) who did not drink alcohol or use any tobacco products (see Figure 9). She was the most popular person of all the children in the survey. Of these 13 were boys (one black) and 12 were girls (one black). Even though Mary was age 13, she had children ages 11-15 choose her as someone they wanted to be their friend. Only two of the girls used either tobacco or alcohol (one smoked and drank; one only drank). It appears that, for the most part, those girls who admire Mary imitate her behavior. This was not the case for the boys. During this year, about 24% of 80, lZyear-old white boys surveyed used these products (mainly smokeless tobacco). Of those who choose Mary, however, 86% used at least one of these products. Thus, 12-year-old boys who choose Mary are over represented for this survey year. Overall, 62% of all boys who picked Mary used at least one product. To uncover why so many boys were using, Mary’s choices were examined (see Figure 10). Mary selected 2 females (Best Friend and Admired Friend). Neither of these girls used any products. However, she also picked “Fred” as her Free-Time Friend. “Fred” uses all four products. It appears from these Figures that those younger boys who wanted Mary to be their friend, may be imitating Fred. Perhaps they
S.MacD. Hunter et al. / Tobacco and alcohol use among youth
101
are thinking that Mary will like them if they act like Fred and use any of these products.
Discussion During adolescence, close friends assume an increasingly important influence on each other’s behavior. This paper presents new insights regarding the structure of these relationships and influence mechanisms for behavior diffusion. Attribute, ego-centered and cliques were the methods used for this purpose. Attribute analysis does not have much of the explanatory potential that relational analysis provides. It does, however, give a general overview of friendship patterns. In this case, the findings illustrate that even at an early age, there is a segregation of cigarette smokers from non-cigarette smokers. Because of new legislative ruling in many States, smokers are increasingly becoming segregated from non-smokers. This norm of separation appears to apply for childhood friendships as well. Additionally, the influence mechanism may be the behavior itself since cigarette smoking is a more obvious behavior than the use of smokeless tobacco. Currently, alcohol drinking is more socially acceptable than tobacco use, especially cigarettes. It may be more likely that best friends will get together just to smoke cigarettes, cliques to drink, but not to chew tobacco or use snuff. By combining both attributional and relational data, the examination of cliques provided much insight and raised many questions about the mechanisms involved in the diffusion of tobacco and alcohol. One way of diffusion of health behaviors may occur through bridge children if they transmit information, influence and resources between cliques. Since these analyses were performed with a restricted choice format and the measurement of cliques was very narrow, this study may have underestimated the number of cliques in this population of children. However, it does appear very clear that children develop cliques around a preferred behavior, especially for females. In this case, alcohol seems to be the main behavior. Additionally, it is clear that some behaviors in cliques are gender, age and race specific. One question which emerges from the study of these cliques is: What happens to a non-drinking child who is in a clique which drinks and has a non-drinking reciprocal friend outside the clique? Will the
102
S.MacD.
Hunter et al. / Tobacco and alcohol we among youth
non-drinking friend provide social support for continuation of nondrinking; or, will the members of the drinking clique have a greater influence (as in Figure 4)? In the case where the non-drinking member of a drinking clique has friends outside the clique who also drink, perhaps this person is more likely to become a drinker later. The direction of choices may also be important. In those cases where the member chooses a person outside the clique, but it is not reciprocal, the person outside of the clique may have a greater influence than members of the clique. Or, they may not. In summary, which is more important for the adoption of certain behaviors, such as alcohol and tobacco use, clique membership or the total number of friends using? The presentation of the ego-centered-relational digraph illustrated the potential power of vicarious learning and influence as a mechanism of diffusion. In this situation, the young boys may have been influenced circuitously as a result of observing the behavior of another (Fred) and the perceived consequences of Fred’s tobacco and alcohol use, e.g. having Mary for a friend. Thus, a very popular person may have an influence on others, not just by example, but also by observation of the behavior of their associates. Finally, the product itself appears to influences its diffusion. Children who smoke tend to have Best Friends, Free-Time Friends and Admired Friends who smoke. While children who drink, not only have Best Friends who drink but, also develop drinking cliques. Smokeless tobacco use is less social. Perhaps its use is only connected with a sport, such as baseball or hunting. Then there is the case of influence by role models indirectly. In this situation, the adoption of tobacco and alcohol is spread by copying the behavior of someone who associates with an Admired Other. One wonders if this would be true for other behaviors, such as scholastic achievement and physical activity. Obviously, a longitudinal study and follow-up of these children is essential to test these hypotheses. This study provided an innovative methodology for uncovering the mechanisms of diffusion by analyzing friendship structures and their influence on the adoption of health behaviors. It is apparent that intervention/ prevention programs for children must develop techniques and procedures which will take into consideration sociability, social norms and public acceptance of the behavior, the circuitous and indirect nature of role models, and the availability of social support for non-use (Hunter et al. 1990).
S.MacD. Hunter et al. / Tobacco and alcohol use among youth
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References Bandura, A. 1986 Social Founaixtions of Thought and Action, Englewood Cliffs, NJ: Prentice Hall. Bat@, J.G., SMacD. Hunter, L.S. Webber and G.S. Berenson 1982 “Developmental trends of first cigarette smoking experience of children: The Bogalusa heart study”. American Journal of Public Health 72: 1161-164. Berenson, G.S. 1980 Cardiovascular Risk Factors in Children, New York: Oxford University Press. Berenson, G.S. 1986 Causation of Cardiovascular Risk Factors: Perspective on Risk in Earty Life, New York: Raven Press. Bemdt, T. 1982 “The features and effects of friendship in early adolescence”. Child Deuelopment 53: 1447-1460. Burke, G.L., S.MacD. Hunter, J.B. Croft, J. Cresanta and G.S. Berenson 1988 “The interaction of alcohol and tobacco use in adolescents and young adults”. Addictive Behaviors 13: 387-393. Croft, J.B., SMacD. Hunter, L.S. Webber and G.S. Berenson 1985 “Cigarette smoking behavior distinctions between experimental nonadopters and adopters in children and adolescents: The Bogalusa heart study”. Preuentiue Medicine 14: 109-122. Evans, RI., R.M. Rozelle, SE. Maxwell, B.E. Raines, C.A. Dill, T.J. Guthrie, A.H. Henderson and P.C. Hill 1981 “Social modeling films to deter smoking in adolescents: Results of a three-year field investigation”. Journal of Applied Psychology 66: 399-414. Flay, B.R. 1985 “Psychosocial approaches to smoking prevention: A review of findings”. Health Psychology 4: 449-488. Flay, B.R. 1987 “Social psychological approaches to smoking prevention: Review and recommendations”. In W. Ward, S. Simonds, P.D. Mullen and M.H. Becker (eds.), Aduances in Health Promotion and Education, Vol. 2. Greenwich, CT: JAI Press. Freedman, D.S., S.R. Srinivasan, C.L. Shear, et al. 1986 “Cigarette smoking initiation and longitudinal changes in serum lipids and lipoproteins in early adulthood: The Bogalusa heart study”. American Journal of Epidemiology 124: 207-219. Hallinan, M. 1979-1980 “The process of friendship formation”. Social Networks 1: 193-210. Holland, P. and S. Leinhardt 1975 “The structural implications of measurement error in sociometry”. Journal of Mathematical Sociology 3: 85-112. Hunter, S.MacD., L.S. Webber and G.S. Berenson 1980 “Cigarette smoking and tobacco usage behavior in children and adolescents: The Bogalusa heart study”. Preventive Medicine 9: 701-712. Hunter, SMacD., L.S., Webber, J.G. Baugh and G.S. Berenson 1982 “Social learning effects on trial and adoption of cigarette smoking in children: The Bogalusa heart study”. Preventive Medicine 11: 29. Hunter, S.MacD., J.B., Croft, G. Burke, F.C. Parker, L.S. Webber and G.S. Berenson 1986a “Longitudinal patterns of cigarette smoking and smokeless tobacco use in youth: The Bogalusa heart study”. American Journal of Public Health 76: 193-195.
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Hunter et al. / Tobacco and alcohol use among youth
Hunter, SMacD., J.B. Croft, G.L. Burke, LA. Vizelberg and G.S. Berenson 1986b “Influences and longitudinal patterns of smokeless tobacco use. Health implications of smokeless tobacco use”. NIH Consensus Development Conference 32-31. Hunter, SMacD., J.B. Croft, LA. Vizelberg and G.S. Berenson 1987 “Psychosocial influences on cigarette smoking among youth in a southern community: The Bogalusa heart study”. In Psychosocial Predictors of Smoking Among Adolescents. Morbidity and Mortality Weekly Report 36 (suppl. no. 4s): 17S-23s. Hunter, S.MacD., C.C. Johnson, S. Little-Christian, T.A. Nicklas, D. Harsha, M.L. Arbeit, L.S. Webber and G.S. Berenson 1990 “Heart Smart: A multifactorial approach to cardiovascular risk reduction for grade school students”. American Journal of Health Promotion 4: 352-360. Johnson, C.C., SMacD. Hunter, C.I. Amos, S.T. Elder and G.S. Berenson 1989 “Cigarette smoking, alcohol and oral contraceptive use by type A adolescents”. Journal of Behavior Medicine 12: 13-24. Knoke, D. and J.H. Kuklinski 1983 Network Analysis, Beverly Hills: Sage Publications. Shrum, W., N.H. Cheek, Jr. and S.MacD. Hunter 1988 “Friendship in school: Gender and racial homophily”. Sociology of Education 61: 221-239. Voors, A.W., S.R. Srinivasan, S.MacD. Hunter, L.S. Webber, M.C. Sklov and G.S. Berenson and serum lipid and lipoprotein levels in children of a 1982 “Smoking, oral contraceptives, total biracial community”. Preventive Medicine II: l-12. Webber, L.S., S.MacD. Hunter, J.G. Bat&, S.R. Srinivasan, M.C. Sklov and G.S. Berenson of cigarette smoking, oral contraceptives use, and cardiovascular risk 1982 “The interaction factor variables in children: Bogalusa heart study”. American Journal of Public Health 72: 266.
91
Identifying mechanisms of adoption of tobacco and alcohol use among youth: The Bogalusa heart study * Saundra MacD. Hunter, Igor A. Vizelberg and Gerald S. Berenson * * Department
of Medicine, Louisiana State University Medical Center, New Orleans, LA 70112, USA
Network procedures revealed social influence mechanisms on alcohol and tobacco adoption. Children who smoke have best friends who smoke. Children who drink additionally develop drinking cliques. Smokeless tobacco is less social. Tobacco and alcohol adoption also spreads indirectly by imitation of an admired other’s friends. Children’s healthful programs must develop techniques which consider the sociability, visibility, social norms and public acceptance of the behavior, indirect nature of role models, and social support for non- or alternate use.
1. In~~uetion Few studies explore friendship structures among youth and their influence on health behavior adoption/diffusion. Most recently, “Just Say NO” campaigns assume that the only mechanism influencing children to use tobacco, alcohol and drugs is direct verbal pressure from peers (Evans et al. 1981). While not denying that this is sometimes true, children are also influenced by observing others and the consequences of ‘the other’s behavior (Bandura 1986). Thus, if children observe another person punished for behaving one way, they will not likely imitate that behavior. Conversely, if children see another being rewarded for an action, then they are more likely to imitate that action. * This research was supported by research grant (ROI-HL-38844) from the National Heart, Lung, and Blood Institute of the United States Public Health Service (USPHS). We thank Mrs. Bettye Seal for her work as community coordinator, the nurses of the project staff, the teachers and staff of the Bogalusa school system, the Bogalusa community volunteers, and the children of Bogalusa and their parents for making this study possible. ** Reprint requests to Gerald S. Berenson, M.D., Department of Medicine, Louisiana State University Medical School, 1542 Tulane Avenue, New Orleans, LA 70112 USA. 037%8733/91/$03.50
0 1991 - Elsevier Science Publishers B.V. (North-Holland)
92
S.MacD. Hunter et al. / Tobacco and alcohol USCamong youth
Most prevention programs teach children communication techniques involving refusal skills to handle direct peer pressure to use tobacco (Flay 1985). Children may also make choices and act based on the circuitous, non-verbal influence of others as role models. Interventions do not take into account the informal and non-verbal nature of the social influence process. This may account for recent findings which show that long-term effects of school based intervention programs lose their effectiveness over time (Flay 1985, 1987). However, it is difficult to research indirect, non-verbal influences of role models. Network analysis, which examines relations that connect peers within a group, may uncover non-verbal influences by producing a descriptive view of peer structures and the self reported behaviors of their members. This method may detect emergent behavior and its mechanism of diffusion throughout a peerage. It has the potential to illustrate how the child influences others as well as being influenced by them, either directly or circuitously. The purpose of this paper is to present findings from a large network of children who were asked questions about the use of tobacco and alcohol. The goal was to get a clearer description of the direct and indirect mechanisms underlying the emergent use of tobacco and alcohol. A network approach will develop a model of peer structures and allow comparisons of those structures to self-report behaviors of their members. Most previous research on the influence of friends on the use of tobacco or alcohol relied on the respondent’s perception of his or her friend’s use. Reporting the friend’s behavior in this way may overestimate the similarity between the friend’s use and the respondent’s own behavior. Using the friend’s actual report of behavior reduces the chance of misclassification and avoids the methodological problem associated with potentially incorrect perception of the friend’s behavior by matching the respondent with the friend’s actual reported tobacco or alcohol use. Findings from this method may provide information for intervention programs specifically designed to cultivate successful adoption of health enhancing behaviors in children and adolescents. 2. Data During a cross-sectional screening of cardiovascular risk factor variables in the biracial community of Bogalusa, Louisiana (Berenson 1980,
XMacD.
Hunter et al. / Tobacco and alcohol use among youth
93
1986) 2305 students, ages 8-17, completed a questionnaire consisting of alcohol/tobacco use and friendship choices. The children were assured of confidentiality. They sat behind specially constructed booths. It was administered by trained monitors in the school setting and took an average of 5-15 minutes to complete. In Grades 3-6, posters were used to help the children understand the question; and, the questions were read to them on a tape recorder. Two weeks later 449 children were retested to assess reliability. 2. I. Measures Students were asked to answer: (1) “Who from school are your best friends?” (2) “Who from school would you like to be your friend?” (3) “Who from school do you spend the most free time with?” A fixed format was followed with three spaces provided to the children to write their choices. This may have underestimated the actual linkages present in the system (Holland and Leinhardt 1975). Children wrote the first and last name of each friend. If there was difficulty with the spelling, the monitor provided assistance. The local telephone directory was also available to aid with spelling. Children were requested not to write “ nick names.” A population census was developed which contained all children currently enrolled in Bogalusa schools and their identification number. After the children completed the questionnaires, identification numbers were assigned manually to each friend selected by the research staff. In this manner, selected friends were linked with the respondent. Of those who completed the sociometric questionnaire, 51% were female and 49% were male; 65% white and 35% black. The sample represented over 80% of all children who were screened that year in Bogalusa. Test-retest reliability over two points in time found that the youngest and oldest age groups were the most consistent in their choices (82% for 8 years old; and, 95% for 17 years old) and there was a general increase in consistency from age 9 through age 17 (Shrum et al. 1988) in naming “Best Friends” and “Free-time Friends”. Others have similar findings of a positive association between consistency and age (Hallinan 1979; Bemdt 1982). Each child was asked to respond to questions about the use of cigarettes, snuff, chewing tobacco and alcohol. Current cigarette smokers were defined as someone who smoked at least one cigarette per week; or, someone who smoked less than one cigarette per week.
94
S. MacD. Hunier et al. / Tobacco and alcohol use among youth
Current alcohol use was defined as someone who drank at least one drink of beer, wine or hard liquor per week; or, less than-one drink per week. Users of chewing tobacco or snuff were defined as anyone who tried these products. Cigarette smoking behavior was validated with plasma thiocyanate. Measures of cigarette smoking, smokeless tobacco, and alcohol indicated reasonable reliability and validity. Methods used to insure the collection of reliable and valid data, as well as, related findings are reported elsewhere (Hunter, et al. 1980, 1982, 1986a, 1987; Webber et al. 1982; Voors et al. 1982; Bat@ et al. 1982; Croft et al. 1985; Freedman et al. 1986; Burke et al. 1988; Johnson et al. 1989).
3. Results Three procedures utilizing network data to reveal direct and indirect social influence mechanisms on tobacco and alcohol adoption is presented. 3. I. Attribute
analyses
Using attribute analyses, Figures 1, 2 and 3 show the relationship between personal tobacco use patterns in white males (N approximately 700) with those of their Best Friends (BF), Free-time Friends (FTF), and Admired Friends (AF) (Knoke and Kuklinski, 1983). Only
* Subject Friend
Does
Not
Dips Snuff
Use
* Subject
Selected
Friend
Uses
Does Not Dip Snuff
*
White N ::
Males:
8-17
yews
old
700
Fig. 1. Attribute analysis of friends’ snuff dipping behavior: The Bogalusa heart study.
95
S.MacD. Hunter et al. / Tobacco and alcohol we among youth * Subiect Friend Does Not Use -
*
Subject
Chews Tobacco
Does
Not
Chew
*
Selected Friend Uses
Tobacco
White Males: 8-17
years old
N 2 700 Fig. 2. Attribute
analysis
of friends’ chewing
behavior:
The Bogalusa
heart study.
white males are selected because there is < 1% usage of these products for the other race/gender groups. Approximately 19-2156 of white males did not select friends in any of the categories. There is a significant difference in the friends selected by cigarette smokers and non-smokers (FTF and BF Chi Square: P = 0.000; AF: ns). Nonsmoking males are much more likely to select friends who do not smoke than those who smoke (11% BF, 14% AF, 7% FTF). Similarly, among cigarette using males, 47% had Best Friends, 24% Admired Friends, and 43% Free-Time Friends who smoked cigarettes. This was
l Subject iriend Does Not Use
* Subject
Smokes
Cigarettes Selected Friend Uses
Does Not Smoke
*
Cigarettes
White Males: 0-17
years old
N :: 700 Fig. 3. Attribute
analysis
of friends’ cigarette
smoking
behavior:
The Bogalusa
heart study.
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Hunter et al. / Tobacco and alcohol use among youth
* Subiect
* Subject
Uses Alcohol
Does Not Use_Alcohol
*
White Males: 8-17
years old
N :: 700 Fig. 4. Attribute analysis of friends’ alcohol use: The Bogalusa heart study.
not the case for the use of chewing tobacco and snuff (BF: Chi Square: P = 0.000; FTF (chew) Chi Square: P = 0.05: AF: ns). Even if the subject did not use, he was just as likely to have friends who did. Over 30% of those males who did not use snuff or chew tobacco had a Best Friend who did. Figure 4 shows attribute analysis for alcohol use. Close to 80% of all friends drink if the subject also drinks. Whereas, if the subject does not drink, 56% of those admired Friends do (FTF, BF: Chi Square, P = 0.000; AF: Chi Square, P = 0.02). 3.2. Cliques Cliques were identified as highly cohesive subsets of children where three or more children all chose each other as “Best Friends” or “Free-Time Friends.” These are presented as digraphs (directional graph). Paths (a connection with someone outside the clique) were identified also. Overall 48 cliques consisting of 140 children were identified. Thirtyfour cliques used no tobacco or alcohol products. The following discussion will concern only those seven cliques which have two or more members using alcohol and/or tobacco. Strongly connected digraphs are presented in Figures 5, 6, 7 and 8 indicating cliques and their tobacco and alcohol behaviors. Figure 5 displays alcohol behavior among three females cliques. Two of these cliques contain only black females and one is composed of white
SMacD.
Hunter et al. / Tobacco and alcohol use among youth
Fig. 5. Alcohol behavior among three
97
: cliques: The Bogalusa heart study.
females. All three cliques had members which were bridge children. All of the girls in the cliques were 14-17 years old. Except in one case, female bridge children related to an older outside male. In one clique (white), there was one member who did not drink. She had a reciprocal relationship with another non-drinker outside of the clique. One of the black cliques had a member who did not drink. In this case, that member had a non-reciprocal relationships with two drinking males
Fig. 6. Chewing behavior within lo-year-old
white male clique: The Bogalusa heart study.
98
S.MacD.
Hunter et al. / Tobacco and alcohol use among youth 10-17 --~
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El
F.l7l.l.
Cl3 m
Smoklns
Clsarattes
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TOS.CCO
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Fig. 7. Multibehavioral
Yisslng
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h
B.,1
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Tlrn.
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risk factors among two white male cliques: The Bogalusa heart study.
outside the clique. Two cliques had drinking bridge children who connected with non-drinkers outside the clique who she considered to be her Best Friend or Free-Time Friend.
Female
Smoking
CIgarettea
Chewing
Tobacco
Snuff Drinking
Alcohol
MI.slng
Data
Beat
Friend
Free
Time
Clique
- (All
choices: and
Free
Frland
reclprqcal Be.1
Frlond
Time
Fig. 8. Health behavior of gender integrated white clique: The Bogalusa heart study
FrIendI
SiUacD.
Hunter et al. / Tobacco and alcohol use among youth
99
The youngest clique (Figure 6) consisted of lo-year-old white males who chewed tobacco. It is interesting to note that in this clique, one member also used snuff. Figure 7 portrays two unconnected cliques which has members who are polyusers. Both are comprised of white males, one is age homogenous (13 years old). A reciprocal relationship exists between a younger boy within the clique (age 13) and older one outside of it (age 14). Finally, Figure 8 demonstrates that cliques can consist of both genders. This clique’s focal attribute seems to be alcohol, with all members choosing the same person outside of the clique as their Best Friend. He, however, did not choose any members of the clique as neither a Free-time Friend nor a Best Friend. The male member of the clique has two other friends outside the clique, with a total of four Best Friends who drink alcohol. 3.3. Ego-centered The last procedure is identified as an ego-centered-relational digraph. The first research question is to identify the most popular person
Fig. 9. Characteristics and health habits of respondents who picked Mary as the person who they wanted to be their best Friend: The Bogalma heart study.
loo
S. MacD. Hun!er et al. / Tobacco and alcohol we among youth
13-14 ----
Apa Black While
SmokinQ Cigarettea
ChewhQ Tobacco
,,rl,lklAQ Alcohol
Ml&,inQ Data 13
13 14
Fig. 10. Health habits of children
who mary chose as friends:
The Bogalusa
heart study.
during this survey year. In response to the question, “Who from school would you like to be your friend. 7” 25 children selected a white female (pseudonym “Mary”) who did not drink alcohol or use any tobacco products (see Figure 9). She was the most popular person of all the children in the survey. Of these 13 were boys (one black) and 12 were girls (one black). Even though Mary was age 13, she had children ages 11-15 choose her as someone they wanted to be their friend. Only two of the girls used either tobacco or alcohol (one smoked and drank; one only drank). It appears that, for the most part, those girls who admire Mary imitate her behavior. This was not the case for the boys. During this year, about 24% of 80, lZyear-old white boys surveyed used these products (mainly smokeless tobacco). Of those who choose Mary, however, 86% used at least one of these products. Thus, 12-year-old boys who choose Mary are over represented for this survey year. Overall, 62% of all boys who picked Mary used at least one product. To uncover why so many boys were using, Mary’s choices were examined (see Figure 10). Mary selected 2 females (Best Friend and Admired Friend). Neither of these girls used any products. However, she also picked “Fred” as her Free-Time Friend. “Fred” uses all four products. It appears from these Figures that those younger boys who wanted Mary to be their friend, may be imitating Fred. Perhaps they
S.MacD. Hunter et al. / Tobacco and alcohol use among youth
101
are thinking that Mary will like them if they act like Fred and use any of these products.
Discussion During adolescence, close friends assume an increasingly important influence on each other’s behavior. This paper presents new insights regarding the structure of these relationships and influence mechanisms for behavior diffusion. Attribute, ego-centered and cliques were the methods used for this purpose. Attribute analysis does not have much of the explanatory potential that relational analysis provides. It does, however, give a general overview of friendship patterns. In this case, the findings illustrate that even at an early age, there is a segregation of cigarette smokers from non-cigarette smokers. Because of new legislative ruling in many States, smokers are increasingly becoming segregated from non-smokers. This norm of separation appears to apply for childhood friendships as well. Additionally, the influence mechanism may be the behavior itself since cigarette smoking is a more obvious behavior than the use of smokeless tobacco. Currently, alcohol drinking is more socially acceptable than tobacco use, especially cigarettes. It may be more likely that best friends will get together just to smoke cigarettes, cliques to drink, but not to chew tobacco or use snuff. By combining both attributional and relational data, the examination of cliques provided much insight and raised many questions about the mechanisms involved in the diffusion of tobacco and alcohol. One way of diffusion of health behaviors may occur through bridge children if they transmit information, influence and resources between cliques. Since these analyses were performed with a restricted choice format and the measurement of cliques was very narrow, this study may have underestimated the number of cliques in this population of children. However, it does appear very clear that children develop cliques around a preferred behavior, especially for females. In this case, alcohol seems to be the main behavior. Additionally, it is clear that some behaviors in cliques are gender, age and race specific. One question which emerges from the study of these cliques is: What happens to a non-drinking child who is in a clique which drinks and has a non-drinking reciprocal friend outside the clique? Will the
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non-drinking friend provide social support for continuation of nondrinking; or, will the members of the drinking clique have a greater influence (as in Figure 4)? In the case where the non-drinking member of a drinking clique has friends outside the clique who also drink, perhaps this person is more likely to become a drinker later. The direction of choices may also be important. In those cases where the member chooses a person outside the clique, but it is not reciprocal, the person outside of the clique may have a greater influence than members of the clique. Or, they may not. In summary, which is more important for the adoption of certain behaviors, such as alcohol and tobacco use, clique membership or the total number of friends using? The presentation of the ego-centered-relational digraph illustrated the potential power of vicarious learning and influence as a mechanism of diffusion. In this situation, the young boys may have been influenced circuitously as a result of observing the behavior of another (Fred) and the perceived consequences of Fred’s tobacco and alcohol use, e.g. having Mary for a friend. Thus, a very popular person may have an influence on others, not just by example, but also by observation of the behavior of their associates. Finally, the product itself appears to influences its diffusion. Children who smoke tend to have Best Friends, Free-Time Friends and Admired Friends who smoke. While children who drink, not only have Best Friends who drink but, also develop drinking cliques. Smokeless tobacco use is less social. Perhaps its use is only connected with a sport, such as baseball or hunting. Then there is the case of influence by role models indirectly. In this situation, the adoption of tobacco and alcohol is spread by copying the behavior of someone who associates with an Admired Other. One wonders if this would be true for other behaviors, such as scholastic achievement and physical activity. Obviously, a longitudinal study and follow-up of these children is essential to test these hypotheses. This study provided an innovative methodology for uncovering the mechanisms of diffusion by analyzing friendship structures and their influence on the adoption of health behaviors. It is apparent that intervention/ prevention programs for children must develop techniques and procedures which will take into consideration sociability, social norms and public acceptance of the behavior, the circuitous and indirect nature of role models, and the availability of social support for non-use (Hunter et al. 1990).
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References Bandura, A. 1986 Social Founaixtions of Thought and Action, Englewood Cliffs, NJ: Prentice Hall. Bat@, J.G., SMacD. Hunter, L.S. Webber and G.S. Berenson 1982 “Developmental trends of first cigarette smoking experience of children: The Bogalusa heart study”. American Journal of Public Health 72: 1161-164. Berenson, G.S. 1980 Cardiovascular Risk Factors in Children, New York: Oxford University Press. Berenson, G.S. 1986 Causation of Cardiovascular Risk Factors: Perspective on Risk in Earty Life, New York: Raven Press. Bemdt, T. 1982 “The features and effects of friendship in early adolescence”. Child Deuelopment 53: 1447-1460. Burke, G.L., S.MacD. Hunter, J.B. Croft, J. Cresanta and G.S. Berenson 1988 “The interaction of alcohol and tobacco use in adolescents and young adults”. Addictive Behaviors 13: 387-393. Croft, J.B., SMacD. Hunter, L.S. Webber and G.S. Berenson 1985 “Cigarette smoking behavior distinctions between experimental nonadopters and adopters in children and adolescents: The Bogalusa heart study”. Preuentiue Medicine 14: 109-122. Evans, RI., R.M. Rozelle, SE. Maxwell, B.E. Raines, C.A. Dill, T.J. Guthrie, A.H. Henderson and P.C. Hill 1981 “Social modeling films to deter smoking in adolescents: Results of a three-year field investigation”. Journal of Applied Psychology 66: 399-414. Flay, B.R. 1985 “Psychosocial approaches to smoking prevention: A review of findings”. Health Psychology 4: 449-488. Flay, B.R. 1987 “Social psychological approaches to smoking prevention: Review and recommendations”. In W. Ward, S. Simonds, P.D. Mullen and M.H. Becker (eds.), Aduances in Health Promotion and Education, Vol. 2. Greenwich, CT: JAI Press. Freedman, D.S., S.R. Srinivasan, C.L. Shear, et al. 1986 “Cigarette smoking initiation and longitudinal changes in serum lipids and lipoproteins in early adulthood: The Bogalusa heart study”. American Journal of Epidemiology 124: 207-219. Hallinan, M. 1979-1980 “The process of friendship formation”. Social Networks 1: 193-210. Holland, P. and S. Leinhardt 1975 “The structural implications of measurement error in sociometry”. Journal of Mathematical Sociology 3: 85-112. Hunter, S.MacD., L.S. Webber and G.S. Berenson 1980 “Cigarette smoking and tobacco usage behavior in children and adolescents: The Bogalusa heart study”. Preventive Medicine 9: 701-712. Hunter, SMacD., L.S., Webber, J.G. Baugh and G.S. Berenson 1982 “Social learning effects on trial and adoption of cigarette smoking in children: The Bogalusa heart study”. Preventive Medicine 11: 29. Hunter, S.MacD., J.B., Croft, G. Burke, F.C. Parker, L.S. Webber and G.S. Berenson 1986a “Longitudinal patterns of cigarette smoking and smokeless tobacco use in youth: The Bogalusa heart study”. American Journal of Public Health 76: 193-195.
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Hunter, SMacD., J.B. Croft, G.L. Burke, LA. Vizelberg and G.S. Berenson 1986b “Influences and longitudinal patterns of smokeless tobacco use. Health implications of smokeless tobacco use”. NIH Consensus Development Conference 32-31. Hunter, SMacD., J.B. Croft, LA. Vizelberg and G.S. Berenson 1987 “Psychosocial influences on cigarette smoking among youth in a southern community: The Bogalusa heart study”. In Psychosocial Predictors of Smoking Among Adolescents. Morbidity and Mortality Weekly Report 36 (suppl. no. 4s): 17S-23s. Hunter, S.MacD., C.C. Johnson, S. Little-Christian, T.A. Nicklas, D. Harsha, M.L. Arbeit, L.S. Webber and G.S. Berenson 1990 “Heart Smart: A multifactorial approach to cardiovascular risk reduction for grade school students”. American Journal of Health Promotion 4: 352-360. Johnson, C.C., SMacD. Hunter, C.I. Amos, S.T. Elder and G.S. Berenson 1989 “Cigarette smoking, alcohol and oral contraceptive use by type A adolescents”. Journal of Behavior Medicine 12: 13-24. Knoke, D. and J.H. Kuklinski 1983 Network Analysis, Beverly Hills: Sage Publications. Shrum, W., N.H. Cheek, Jr. and S.MacD. Hunter 1988 “Friendship in school: Gender and racial homophily”. Sociology of Education 61: 221-239. Voors, A.W., S.R. Srinivasan, S.MacD. Hunter, L.S. Webber, M.C. Sklov and G.S. Berenson and serum lipid and lipoprotein levels in children of a 1982 “Smoking, oral contraceptives, total biracial community”. Preventive Medicine II: l-12. Webber, L.S., S.MacD. Hunter, J.G. Bat&, S.R. Srinivasan, M.C. Sklov and G.S. Berenson of cigarette smoking, oral contraceptives use, and cardiovascular risk 1982 “The interaction factor variables in children: Bogalusa heart study”. American Journal of Public Health 72: 266.