MERCKEN ET AL. 99

Dynamics of Friendship Networks and Alcohol Use in Early and Mid-Adolescence

LIESBETH MERCKEN, PH.D.,a,b,* CHRISTIAN STEGLICH, PH.D.,c RONALD KNIBBE, PH.D.,a,b AND HEIN DE VRIES, PH.D.a,b

aCare and Public Health Research Institute (CAPHRI), Maastricht, The NetherlandsbDepartment of Health Promotion, Maastricht University, The NetherlandscDepartment of Sociology, University of Groningen, The Netherlands

99

ABSTRACT. Objective: Similarity in alcohol consumption among adolescent friends could be caused by the infl uence of friends or by the selection of friends who consume similar levels of alcohol. This article aims to disentangle infl uence and selection processes while specifi cally examining changes over time in these processes and possible differences between reciprocal and nonreciprocal friendships. Method: The design was longitudinal with four observations (Time 1–Time 4 [T1–T4]). Data consisted of a longitudinal sample of 1,204 Finnish adolescents in 10 ju-nior high schools. The main measurements were adolescents’ friendship networks and alcohol consumption. For three successive periods, T1–T2, T2–T3, and T3–T4, actor-based models for the co-evolution of networks and behavior were analyzed (Mage: T1 = 13.6 years, T2 = 14.6 years, T3 = 15.6 years, T4 =16.1 years). Results: Selection, as well as infl uence

processes, played an important role in adolescent alcohol consumption. Infl uence was found during the fi rst period (T1–T2), whereas support for selection was found during the last two periods (T2–T3 and T3–T4). The strength of infl uence and selection processes did not differ for reciprocal and nonreciprocal friendships. Conclusions: The impact of selection and infl uence processes changed over time such that infl uence was only present during early adolescence, whereas selection was present during mid-adolescence. During early adolescence, youngsters would benefi t from learning to resist social infl uence. Alcohol-consumption preven-tion programs targeting mid-adolescence should consider peer selection processes. These fi ndings stress the importance of considering changes over time in future practice and research. (J. Stud. Alcohol Drugs, 73, 99–110, 2012)

Received: August 25, 2010. Revision: July 25, 2011. The European Smoking Prevention Framework Approach project was funded by a grant from the European Commission (The Tobacco Research and Information Fund; 96/IT/13-B96 Soc96201157). *Correspondence may be sent to Liesbeth Mercken at Maastricht Univer-sity, Department of Health Promotion, P.O. Box 616, 6200 MD Maastricht, The Netherlands or via email at: liesbeth.mercken@maastrichtuniversity.nl.

ALCOHOL USE AMONG ADOLESCENTS is a major public health concern (Kosterman et al., 2000). Drunk-

enness is more prevalent in adolescence and young adult-hood than in any other life period (Gmel et al., 2003), and a trend toward earlier onset is already observed among middle and high school students (Guo et al., 2009). Besides play-ing a key role in leading causes of death among teenagers (such as motor vehicle accidents, unintended injuries, and suicides), alcohol consumption often co-occurs with other problem behaviors (Kann et al., 2000). Early drinkers and experimenters were found to be more likely to report aca-demic problems, substance use, and delinquent behavior dur-ing adolescence and employment problems, other substance use, and criminal and violent behavior by young adulthood (Ellickson et al., 2003). Insights into different processes that might explain alcohol use during adolescence may facilitate the development of intervention programs aiming to reduce alcohol use among youngsters. During adolescence, peer groups play an important role in alcohol consumption, as evidenced by research suggesting

that alcohol use tends to be similar among friends (Bauman and Ennett, 1994; Fisher and Bauman, 1988; Urberg et al., 1997). The propor t ion of friends that were similar in their alcohol use ranged from 65% to 81% (Fisher and Bauman, 1988; Urberg et al., 1997). This similarity, which can be regarded as network autocorrelation (Doreian, 1989), could be caused by the selection of similar others as friends, by the infl uence processes whereby friends adjust their drinking behavior to each other, or by a combination of these factors. This article aims to disentangle these infl uence and selection processes in the context of alcohol consumption while spe-cifi cally examining changes over time in these processes dur-ing early and mid-adolescence and exploring the moderating role of friendship reciprocity. Insights into these processes may benefi t the development of prevention programs and adaptation of policies regarding effective alcohol prevention. Several earlier studies, using traditional methods, at-tempted to disentangle selection and infl uence processes in the context of alcohol consumption and suggested that the selection of friends based on similar alcohol consumption may be just as important as, or even more important than, in-fl uence processes to explain similarity among friends (Bau-man and Ennett, 1996; Bot et al., 2005; Fisher and Bauman, 1988; Sieving et al., 2000). However, these previous studies had three main shortcomings. First, although researchers did include important covariates that may explain changes in alcohol consumption—such as gender, school achievement, and smoking behavior (Kirkcaldy et al., 2004; Wetzels et

100 JOURNAL OF STUDIES ON ALCOHOL AND DRUGS / JANUARY 2012

al., 2003)—they did not control adequately for alternative explanatory selection mechanisms. An alcohol-consuming adolescent, for example, may select another alcohol-con-suming adolescent as a friend because this new friend had already indicated that the adolescent was his friend (return-ing a friendship—reciprocity) or because this new friend was already a friend of the adolescent’s other friends (selecting a friend of a friend—transitivity). Furthermore, the selection of a friend can be based on the adolescents’ age, gender, smoking behavior, school achievement, or similarities in such attributes instead of similarities in their alcohol con-sumption. The importance of these alternative causes of tie formation was already demonstrated by previous researchers (Burk et al., 2007; McPherson, 2001; Mercken et al., 2009; Snijders and Baerveldt, 2003). Failing to control for alterna-tive mechanisms might result in an overestimation of the strength of substance use–based selection processes. Second, researchers have not considered the continuous changes of friendship networks and alcohol consumption over time happening between observations. Longitudinal data have been mostly gathered at only a few discrete mo-

ments, which makes it impossible to unequivocally iden-tify the processes responsible for a network or behavioral change. In between two observation moments, changes will occur in friendships and alcohol consumption, and a change may even be followed by a change back to the original value before the next observation moment. Figure 1 demonstrates infl uence and selection processes that are likely to be di-agnosed incorrectly on the basis of discrete observations if change between the observations is not accounted for. Analysis techniques that are based on classifying observed changes as being because of infl uence or selection without accounting for the possibility of other intervening changes may be misleading, and it is preferable to use a technique that does take this possibility into account. Third, independence assumptions that underlie the statis-tical methods used were often violated in previous studies. Even more advanced statistical techniques, such as structural equation modeling used for this type of data (Bullers et al., 2001; Sieving et al., 2000), assume incorrectly that there are no dependencies caused by the network structure of an ado-lescent. For example, a given individual’s value on alcohol

FIGURE 1. Incomplete observation of behavior and network change

MERCKEN ET AL. 101

consumption could appear within more than one observation (e.g., as the alcohol-consumption dependent variable for one case and as alcohol consumption of one of the friends sup-plying data for the independent variables in other cases). Recently, these shortcomings of previous research have been overcome by using newly developed advanced social-network–analysis methods. These stochastic actor-based models for network and behavior co-evolution (Snijders, 2001, 2005; Snijders et al., 2007a; Steglich et al., 2010) are able to consider alternative explanatory selection mecha-nisms, model continuous-time changes in alcohol consump-tion and friendship networks, and take dependencies caused by the network structure into account. Until now, stochastic actor-based models for network and behavior co-evolution had been used to examine the spread of alcohol consumption in early and mid-adolescence in only a few studies (Knecht et al., 2011; Pearson et al., 2006; Steglich et al., 2006, 2010). Two of these studies (Pearson et al., 2006; Steglich et al., 2006) found evidence for both selection and infl uence, whereas only one found support for the infl uence of friends (Steglich et al., 2010). Knecht and colleagues (2011) found selection to play a more signifi cant role than social infl uence in predicting similarity between friends’ alcohol use. The disparities in these fi ndings may be caused by not taking into account changes in selection and infl uence processes over time and possible moderating effects of friendship reciprocity. Reciprocal friendships offer higher friendship quality and may therefore result in more opportunities for infl uence pro-cesses to cause similarity (Parker and Asher, 1993; Urberg et al., 2003). Studies using conventional statistical analysis techniques showed mixed results. One study found stronger support for the infl uence within reciprocal compared with nonreciprocal friendships (Urberg et al., 2003), whereas another study found stronger support for the infl uence of nonreciprocal or desired friends compared with the infl uence of reciprocal friends (Bot et al., 2005). The present study used stochastic actor-based models to examine the role of reciprocity, overcoming the three previously described short-comings of conventional analysis techniques. It is important to consider possible changes in the se-lection and infl uence processes and the role of friendship reciprocity over time during adolescence. As adolescents grow older, they experience fewer environmental and pa-rental constraints on their social contacts and gain a longer perspective on friendships (Aboud and Mendelson, 1996). Behavioral strategies to maintain already-formed friend-ships, such as assimilating to friends’ alcohol-consumption behavior, may become less important when social cognitive skills mature, whereas sharing social and emotional experi-ences within existing friendships gain importance (Aboud and Mendelson, 1996; Berndt and Hoyle, 1985; Brown, 1981). The impact of infl uence processes may, therefore, decrease when adolescents grow older. Selection based on

similar alcohol use may also decrease during adolescence. Older children’s criteria for choosing friends become more relevant for later phases of friendship, friendship satisfac-tion, and durability (Aboud and Mendelson, 1996). There-fore, it is feasible that the importance of selecting friends based on similar alcohol use may decrease with age be-cause similar alcohol use probably will not be regarded as a selection criterion anymore. The present study was the fi rst to disentangle alcohol-related selection and infl uence processes and the role of reciprocity in these processes among a large sample of adolescents. We examined three separate successive periods covering early and mid-adolescence using stochastic actor-based models for the co-evolution of friendship networks and alcohol consumption. Three main research questions were addressed: (a) Do adolescents select friends based on similar alcohol consumption, and are they infl uenced by friends to adjust to their level of alcohol consumption? (b) Do selection and infl uence processes change over time? (c) Does the strength of selection and infl uence processes differ for nonreciprocated and reciprocated friendships?

Method

Participants

The sample consisted of 10 Finnish schools containing 1,204 adolescents who participated as a control group in the European Smoking Prevention Framework Approach study (de Vries et al., 2003, 2006), which was an intervention study taking place at the community level. The participating Finnish organizations requested that participating schools be located exclusively in Helsinki, the capital and only large city of Finland. In this region, communities/neighborhoods were randomly selected. Junior high schools within the target communities were asked to participate and were told they would have a 50% chance of becoming an experimental school. Experimental schools were excluded in this study because the intervention may have changed the relationship between variables of interest. All 10 schools participated at each of the four measurement times, and participants within schools had less than 15% missing values on alcohol consumption.

Procedure

Self-administered questionnaires were distributed in schools among seventh graders (Mage = 13.61 years) dur-ing autumn 1998. Follow-up was conducted 12, 24, and 30 months later (de Vries et al., 2003, 2006). On the days of data collection, students who were present were asked to complete the questionnaire. Adolescents were told that re-sponses would be treated confi dentially and that they could refuse to participate. Questionnaires were returned in sealed

102 JOURNAL OF STUDIES ON ALCOHOL AND DRUGS / JANUARY 2012

envelopes to guarantee confi dentiality. The overall rate of refusal to participate was 3%.

Questionnaire

Friendship ties were assessed by one question in which adolescents could name up to fi ve best friends inside and/or outside school (McCallister and Fischer, 1978). Only best friends inside school in the same grade were included here to have complete networks. Alcohol consumption was measured by one question as-sessing how often adolescents drink alcohol (0 = never, 1 = sometimes, 2 = less than once a month, 3 = not weekly but at least once a month, 4 = at least once a week) (Wetzels et al., 2003). Gender (0 = boy, 1 = girl), self-reported school achievement (1 = lower third of the class, 2 = middle third, 3 = highest third), and smoking behavior (0 = 0 cigarettes a week, 1 = between 0 and 1, 2 = 2–10, 3 = 11–30, 4 = >30) were also recorded.

Plan of analysis

Model development. An actor-based model was construct-ed to realistically represent the mutual dependencies between

friendship formation and changes in alcohol consumption. The model consists of two parts: One part instantiates the evolution of the friendship network (which allows the study of selection processes), and the other part expresses the evolution of alcohol consumption (for studying infl uence processes). The combined model simulates selection and infl uence processes simultaneously while controlling either process for the other one. A detailed mathematical specifi ca-tion of actor-based models is given elsewhere (Snijders et al., 2007a, 2010). Table 1 presents the list of descriptions of all the included effects, and a detailed description of the model appears in the following. Friendship-network change: Selection. The friendship-network-evolution part of the model specifi es the preferred direction of network change by including a list of effects that determine probabilities of changes in friendship sta-tus, such as the current network structure and attributes of adolescents. This list contains three alcohol consumption–related friendship-selection main effects: (1) the effect of ado-lescents’ own alcohol consumption on number of friends chosen (alcohol consumption ego): to model whether adolescents drinking alcohol at higher rates choose more friends themselves compared with adolescents drinking at

TABLE 1. Included effects for modeling selection and infl uence processes simultaneously

Description

Friendship-network change: Selection Alcohol consumption ego Effect of the adolescent’s own alcohol consumption on selection of friends Alcohol consumption alter Effect of potential friends’ alcohol consumption on selection of friends Alcohol consumption alter squared Effect of potential friends’ squared alcohol consumption on selection of friends Alcohol consumption similarity Preference for choosing a friend based on similar alcohol consumption Outdegree General preference for choosing a friend Reciprocity Preference to choose those who have already chosen the adolescent as a friend Transitivity Preference for being a friend of a friend’s friend Gender similarity Preference for choosing a friend based on similar gender School achievement similarity Preference for choosing a friend based on similar school achievement Smoking behavior alter Effect of potential friends’ smoking behavior on selection of friends Smoking behavior alter squared Effect of potential friends’ squared smoking behavior on selection of friends Smoking behavior ego Effect of the adolescent’s own smoking behavior on selection of friends Smoking behavior similarity Preference for choosing a friend based on similar smoking behavior Extra effect tested with score test: Alcohol Consumption Similarity × Reciprocity Effect to test whether selection based on similar alcohol consumption differs when selecting a nonreciprocal or reciprocal friendAlcohol consumption change: Infl uence Alcohol consumption of friendsa Effect of friend’s alcohol consumption on his own alcohol consumption Shape General preference to consume alcohol Shape squared Feedback effect of adolescent’s own alcohol consumption on itself Gender adolescent Effect of an adolescent’s gender on his own alcohol consumption School achievement adolescent Effect of an adolescent’s school achievement on his own alcohol consumption Smoking adolescent Effect of an adolescent’s smoking behavior on his own alcohol consumption Extra effect tested with score test: Alcohol Consumption of Friends × Reciprocity Effect to test whether the effect of friend’s alcohol consumption differs among nonreciprocal or reciprocal friend Incoming friendship ties Effect of number of nominations by others on own alcohol consumption Outgoing friendship ties Effect of adolescents’ number of nominated friends on own alcohol consumption Being an isolate Effect of being an isolate on own alcohol consumption

Notes: Adequate modeling selection based on similar alcohol consumption results in a large number of effects included in the friendship evolution part. This is because of the multidimensional nature of selection processes. The probability to select a friend may depend on the alcohol use of the adolescent, the alcohol use of the potential friend (alter effects), and similarities in use of both. Including only the alcohol-consumption similarity effect could possibly lead to a biased estimation of selection based on similar alcohol consumption. aAverage alter effect.

MERCKEN ET AL. 103

lower rates or not drinking; (2a) the effect of adolescents’ alcohol consumption on the probability of them being chosen as a friend by others (alcohol consumption alter): to model whether adolescents drinking alcohol at higher rates have a higher probability to be chosen as a friend compared with adolescents drinking at lower rates or not drinking; and (3) the effect of similar alcohol-consuming behavior on friendship selection (alcohol consumption sim-ilarity): to model whether adolescents select friends based on similar alcohol-consumption behavior. We also included (2b): the effect of the squared value of adolescents’ alco-hol-consumption behavior on the probability of them being chosen as friends (alcohol consumption alter squared). This effect will examine whether the probability of adolescents being chosen as friends keeps increasing or starts to de-crease if their alcohol consumption continues to increase (Snijders et al., 2010). It is possible that adolescents select friends who drink alcohol at higher rates but not those who drink at very high rates. Because network dynamics have major endogenous components (McPherson et al., 2001; Snijders, 2001; Van De Bunt et al., 1999), several characteristics of the current network and individual attributes were included as control variables. These were the general tendency to choose arbitrary friends (outdegree), the tendency to reciprocate friendships (reciprocity), and the tendency to choose friends who are also a friend-of-a-friend (transitivity). Furthermore, as control ef-fects, similarity on gender, school achievement, and smoking behavior were included, as was the effect of smoking behavior on the number of friends chosen (smoking behavior ego) and on the propensity to be chosen as a friend (smoking behavior alter and smoking behavior alter squared). Additionally, the interaction effect of Alcohol Consump-tion Similarity × Reciprocity was tested by means of a score test (Schweinberger, in press) to examine whether the strength of selection based on similar alcohol use differs when selecting nonreciprocal friends or reciprocating friend-ships. Whenever an effect is expected to correlate highly with other effects in the model, and typically for higher order interaction terms, this score test procedure is preferable to at-tempts of direct estimation of the effect. The latter procedure runs the risk of not obtaining convergence in the estimation algorithm and not being able to identify the newly included effect, and possibly others (Schweinberger, in press). The friendship-network-evolution part of the combined model is summarized in the upper part of Table 1. Alcohol-consumption change: Infl uence. The alcohol-consumption-evolution part of the model likewise specifi es the preferred direction of change in alcohol consumption by including a list of effects such as network effects, ado-lescent alcohol consumption, and other attributes on which probabilities of changes in alcohol use may depend. This list contained one friendship-related infl uence main effect: the infl uence effect of alcohol consumption of friends on adoles-

cent alcohol use (alcohol consumption of friends—average alter effect). Included control effects were the basic tendency to con-sume alcohol (expressed as a quadratic function of alcohol consumption and, therefore, represented by two param-eters—one for the linear term and one for the quadratic term) and the main effect of gender, school achievement, and smoking behavior. To examine whether the strength of infl uence of friends differs within nonreciprocated and reciprocated friendships, an interaction effect of the infl uence of friends with reciproc-ity was tested by means of a score test. Extra effects of the number of received and outgoing friendship nominations and being an isolate on which changes in alcohol consump-tion might depend were also tested by means of score tests (Schweinberger, in press). The complete list is given in the lower part of Table 1.

Statistical analysis

For each period and each school network separately, the combined model, including the fi ve score tests, was analyzed using SIENA (Simulation Investigation for Empirical Network Analysis) Version 3.17y (Snijders et al., 2007b). The included effects were tested on the basis of t ratios defi ned as estimate divided by standard error, with an approximate standard normal null distribution (Snijders, 2001). Subsequently, the results of all separate school network analyses were combined in a meta-analysis for each of the periods. The t ratios were combined separately for each of the effects in Table 1. For each effect, the overall null hypothesis that the correspond-ing parameter is 0 in all schools was tested by using Fisher’s combination procedure (Hedges and Olkin, 1985) existing out of two one-sided tests. In the right-sided test, the null hypotheses is that, in all schools, the effect is nonpositive, and the alternative hypothesis is that, in at least one school, the effect is positive. In the left-sided test, the same is done with interchanged roles of positive and negative. The test statistic in Fisher’s procedure is minus twice the sum of the natural logarithms of the p values of the one-sided tests for the individual schools, with under the combined null hypothesis a chi-square distribution having, for 10 schools, 20 degrees of freedom. To control for multiple (right and left) testing, there was deemed to be signifi cant support for an effect if either of these combination tests was signifi cant at the .025 level. Fisher’s combination procedure o f one-sided tests is preferred over the Snijders–Baerveldt method for meta-analysis (two-sided test) (Snijders and Baerveldt, 2003) because it does not make the assumption that estimated standard errors and estimated parameter values are uncorrelated. Time homogeneity was tested by basing p values on differences between two successive periods’ parameter es-timates and their standard errors (Steglich et al., in press). Calculations are carried out on school level and then aggre-

104 JOURNAL OF STUDIES ON ALCOHOL AND DRUGS / JANUARY 2012

gated according to Fisher’s combination procedure (Hedges and Olkin, 1985), as explained above. In addition, the null hypothesis that effect parameters are constant across schools was tested by the maximum-likelihood method under the assumption of a normal distribution.

Attrition analyses

During the three periods, all actors in the school networks were included, and the model accounted for some actors entering the study later or leaving earlier (Snijders et al., 2007a). Attrition analyses were performed separately for each of the three periods. In the fi rst period, 931 of 1,027 respondents (91%) completed the questionnaire. Logistic re-gression analysis showed that those adolescents who smoked less (odds ratio [OR] = 0.919, 95% CI [0.879, 0.960], p < .001) and scored higher on school achievement (OR = 1.610, 95% CI [1.206, 2.151], p < .01) were more likely to respond. In the second period, 908 of 1,013 respondents (90%) com-pleted the questionnaire. Participation was not signifi cantly predicted by any of the included determinants. In the third period, 820 of 1,037 respondents (79%) completed the questionnaire. Respondents who smoked less (OR = 0.965, 95% CI [0.936, 0.995], p < .05) were more likely to respond. During all three periods, adolescents who dropped out and those remaining in the study did not differ signifi cantly on their alcohol consumption, gender, and age. Missing values on adolescents’ attributes and alcohol consumption were allowed and treated as noninformative in the estimation

procedure and imputed by a mean value for the start of the simulations (Snijders et al., 2007a).

Results

Descriptive statistics

At baseline, participants were on average 13.6 years old, and 48.4% of the sample was female. Table 2 shows base-line characteristics and the average school network structure and adolescent alcohol consumption for each period. The average numbers of friends increased signifi cantly between subsequent periods, although the slight decrease after T i me 2 (T2) was also statistically signifi cant (p < .01). Overall alcohol consumption increased signifi cantly during each period (p < .01). At T2 and T4, alcohol consumption differed signifi cantly between males and females (p < .01). Table 3 shows for each period the percentages of adolescents who changed and did not change their alcohol-consuming behav-ior. A large proportion of adolescents either did not make a change or increased their alcohol consumption with one step (i.e., changing their alcohol consumption from drinking alcohol sometimes [Score 1] at the fi rst observation to drink-ing alcohol less than once a month [Score 2] at the second observation).

Friendship-network evolution

Results for the friendship-network-evolution part of the model are reported in the upper part of Table 4. In discuss-

TABLE 2. Descriptive statistics of school network structure and individual characteristics.

T1 T2 T3 T4

Average network structure Average number of adolescents in school 77 76 70 61 Average number of friends 1.62 2.02 1.74 1.79 Reciprocity fractiona .37 .35 .30 .31 Transitivity indexb .25 .29 .26 .27 Average observed network autocorrelation (Moran’s I)c .42 .42 .41 .39Individual characteristics Average adolescent alcohol consumption 0.95 1.50 1.97 2.05 % never (0) 45.9 31.7 20.4 16.4 % sometimes (1) 31.8 26.4 21.2 21.5 % less than once a month (2) 7.7 11.1 14.4 16.5 % at least once a month but not weekly (3) 10.5 21.4 28.5 31.5 % at least weekly (4) 4.2 9.4 15.5 14.1 Average alcohol consumption, males 0.98 1.32 1.93 1.91 Average alcohol consumption, females 0.92 1.69 2.02 2.19 Average age, in years 13.61 14.57 15.61 16.07 Average smoking behavior at baselined 0.47e

Average percentage females 48.4 Average school achievementf 1.97 % adolescents with both parents working 5 or more days a week 51.1 % adolescents with only one parent working 5 or more days a week 25.6 % adolescents with no parents working 5 or more days a week 8.6

Notes: T = Time. aThe proportion of friendship ties that are mutual; bthe proportion of ties to friends of an adolescent’s other friends in the network; cdescriptive statistic measuring the similarity of individuals linked in a network; dsmoking behavior is coded: 0 = 0 cigarettes each week; 1 = between 0 and 1; 2 = 2–10; 3 = 11–30; 4 = >30; eonly baseline smoking behavior correlated signifi cantly with baseline alcohol consumption (r = .530, p < .001); fschool achievement is coded: 1 = among the lower third of the class; 2 = middle third; 3 = highest third.

MERCKEN ET AL. 105

ing these, we fi rst focus on the effects linking friendship and alcohol consumption. In the fi rst period, no signifi cant alcohol consumption–based selection effects were found. In turn, in the last two periods, adolescents who scored high on alcohol consumption did show a greater tendency to choose friends who likewise scored high on alcohol consumption, as indicated by the signifi cant right one-sided tests of the alcohol-consumption similarity effects. In Period 2, the strength of this effect differed between the included schools (p < .05, 95% CI [0.001, 0.072], estimated true SD = .12). In Period 3, the left one-sided test was signifi cant also for the alcohol-consumption alter-squared effect, implying that the more the alcohol-consumption score of friends increased, the less they became attractive to be chosen as a friend. None of these effects showed a signifi cant change over time between successive periods. The additionally included interaction effects with reci-procity were not signifi cant, implying that the tendency to select similar alcohol-consuming friends was not different when selecting nonreciprocated friends as compared with reciprocal friends in each of the three periods. The included control effects indicated that, in all three periods, adolescents tended to choose relatively few friends (outdegree), to reciprocate friendship choices (reciprocity), to become and remain friends with friends of their friends (transitivity), and to select friends based on similar gender. In Periods 2 and 3, adolescents also selected friends based on similarities in their smoking behavior.

Alcohol-consumption evolution

The results of the alcohol-consumption-evolution part of the social-network analysis, which specifi es the preferred direction of change in alcohol use, are reported in the lower part of Table 4. In discussing these, we fi rst focus on the effects linking alcohol consumption with friendship. Dur-ing the fi rst period, adolescents’ alcohol consumption was infl uenced by the alcohol consumption of their friends. This signifi cant infl uence effect was not found in Periods 2 and 3. The infl uence of friends effect showed a signifi cant change over time between Periods 1 and 2 (Fisher p = .018) but no signifi cant change over time between Periods 2 and 3. The score tests of the interaction between friends’ alcohol consumption and reciprocity in its effect on alco-hol-consumption dynamics showed that the infl uence of friends did not differ between reciprocal and nonreciprocal friendships. The effects of the number of incoming and outgoing friendship nominations, and the effect of being an isolate on alcohol consumption, also turned out not to be signifi cant. With regard to the included control effects, there was a signifi cant tendency to consume alcohol in the fi rst period, as indicated by the signifi cant alcohol-consumption shape effect. During the fi rst period, girls indicated that they con-sumed alcohol more often compared with boys. In Period 3, those adolescents who smoked had a higher tendency to consume alcohol more frequently.

Discussion

The main goal of the present study was to disentangle selection and infl uence processes among a large sample of adolescents. For the fi rst time, changes over time in these processes and differences between reciprocal and nonrecip-rocal friendships were studied in three successive periods covering early and mid-adolescence, T1–T2, T2–T3, and T3–T4 (Mage: T1 = 13.6 years, T2 = 14.6 years, T3 = 15.6 years, T4 = 16.1 years), using stochastic actor-based models for network behavior co-evolution. This recently developed social-network–analysis method can account for alternative mechanisms explaining selection and infl uence, as well as dependencies caused by network structure, and is capable of modeling continuous-time changes in alcohol consumption and friendship networks. In line with several previous studies (Bauman and Ennett, 1996; Bot et al., 2005; Fisher and Bauman, 1988; Kiuru et al., 2010; Steglich et al., 2006, 2010), our fi ndings demon-strated that selection and infl uence processes both played an important role in alcohol-consumption similarity among friends. Adolescents selected friends who were similar with regard to their alcohol consumption and adapted their alcohol-consumption behavior to the alcohol consumption of their friends.

TABLE 3. Cross-tabulation of alcohol consumption across observation mo-ments (all statistics presented are percentages)

T2

0 1 2 3 4

0 51.5 30.6 5.4 9.7 2.8 1 15.7 33.6 15.3 26.1 9.3T1 2 11.5 11.5 30.8 30.8 15.4 3 4.6 12.6 17.2 43.7 21.8 4 6.5 12.9 3.2 35.5 41.9

T3

0 1 2 3 4

0 48.9 29.3 6.7 8.1 7.0 1 11.4 33.3 21.9 25.0 8.3T2 2 2.2 15.2 20.7 54.3 7.6 3 2.3 6.4 19.8 52.3 19.2 4 4.5 6.0 3.0 27.4 58.2

T4

0 1 2 3 4

0 64.2 23.3 5.0 5.0 2.5 1 10.1 49.2 20.1 14.5 6.1T3 2 6.9 18.1 42.2 27.6 5.2 3 0.5 7.0 16.0 60.1 16.4 4 1.0 9.9 5.9 43.6 39.6

Notes: Alcohol consumption was coded as follows: 0 = never, 1 = some-times, 2 = less than once a month, 3 = at least monthly but not weekly, 4 = at least weekly. T1 = Time 1; T2 = Time 2; T3 = Time 3; T4 = Time 4.

106 JOURNAL OF STUDIES ON ALCOHOL AND DRUGS / JANUARY 2012

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MERCKEN ET AL. 107

Furthermore, our fi ndings showed that the infl uence of friends was not stable over time during early and mid-adolescence. Only in the fi rst period was support found for the infl uence of friends. This effect signifi cantly decreased between Periods 1 and 2. Selection based on similar alcohol consumption was not found during Period 1 but was present during Periods 2 and 3. These results suggest that, during early adolescence, infl uence processes play an important role, whereas during mid-adolescence, selection processes seem to become more important. These results contrast the results of previous studies among similar-aged adolescents, arguing that infl uence processes are stable over time and overall more important than peer selection processes (Siev-ing et al., 2000) or that both processes are important and stable over time (Curran et al., 1997). However, in these previous studies, alcohol consump-tion of friends was not reported by the friends themselves but by the adolescents who nominated the friends, and traditional statistical methods were used that do not fully account for the dependencies caused by the network struc-ture, both possibly resulting in biased estimations of peer infl uence and selection. Differences in the measurement of alcohol use may also account for some of the variation in fi ndings across studies. Whereas the present study focused on alcohol consumption, ranging from never to at least once a week, Curran and colleagues (1997) combined four questions about the frequency of alcohol use in the past 12 months, and Sieving and colleagues (2000) used three questions measuring monthly, past year, and lifetime alco-hol use. Measuring the frequency of alcohol use over larger periods may cause higher over-time stability in alcohol use and in peer infl uence and selection processes based on al-cohol consumption. Additionally, the results of the fi rst period were not in line with a study by Knecht and colleagues (2011), who found selection processes to play a more signifi cant role than social infl uence processes during a comparable period of early ado-lescence. Whereas actor-based models were used to examine selection and infl uence processes in this previous study, ado-lescents were restricted to nominating classmates only, which may have resulted in less power to detect infl uence effects. Adolescents can select and maintain friends outside their own classroom context. Collecting network and behavioral data within complete school grades instead of classrooms increases the amount of information on friendship changes and changes in alcohol consumption possibly caused by the infl uence of friends. Finally, differences in results between current and previ-ous research may also refl ect variation in social infl uence and selection among adolescents from various cultural back-grounds. Finnish drinking culture is rather different from the drinking culture in other European or North American countries. Future research may focus on cross-cultural com-parisons in selection and infl uence processes.

Our fi ndings are in line with theory and research sug-gesting that, during early adolescence, children are most susceptible to peer infl uences (Steinberg, 2004; Urberg et al., 1991). With age, adolescents gain a longer perspective on friendship and start to evaluate what each partner gives and receives (Aboud and Mendelson, 1996). Older children’s disagreements are known to become less disruptive and do not necessarily lead to negative evaluations of the self or others anymore (Enright and Lapsley, 1981; Ladd and Em-erson, 1984), allowing for more dissimilarity among friends in certain behaviors such as alcohol use. During early adolescence, youngsters also had a signifi -cant general tendency to use alcohol besides the tendency to assimilate to friends, which suggests that whole groups seem to start consuming alcohol. During Periods 2 and 3, these tendencies were not present. In terms of social dynamics related to changes in alcohol consumption, most seem to be happening during early adolescence; it would be benefi cial to investigate this specifi c period more closely in the future. Although our fi ndings indicated that infl uence processes seemed to lose importance during mid-adolescence, a re-cent study also on Finnish subjects did show that infl uence processes played an important role during late adolescence (Kiuru et al., 2010), stressing the need for studies that focus on the dynamics of friendship networks and alcohol con-sumption not only during early and mid-adolescence but also during late adolescence. We found that the strength of infl uence of friends did not differ between nonreciprocated and reciprocated friendships, implying that adolescents were infl uenced equally by their nonreciprocal and reciprocal friends. This contrasts with the results of a previous study that argued that adolescents were most likely to adopt their friend’s alcohol-consumption be-havior when this was a nonreciprocal friend with a high so-ciometric status (Bot et al., 2005). Because of the complexity of stochastic actor-oriented models, higher level interactions with sociometric status were not included, and we therefore cannot exclude that infl uence would be stronger among those nonreciprocal friends that also have a high sociometric status. Our fi ndings also suggested that selection processes based on similarities in alcohol-consumption behavior were equally present when selecting a nonreciprocal friend or returning a friendship. Future research should explore the intertwined role of sociometric status and reciprocity in selection and infl uence processes. Contrary to previous studies using conventional analysis techniques, the present study included a number of alterna-tive explaining mechanisms to counter biased estimations of friendship selection based on alcohol consumption. In line with previous studies, our fi ndings showed that adolescents highly tended to reciprocate friendships and to become friends with friends of their friends (Burk et al., 2007; Snij-ders and Baerveldt, 2003) and to select friends based on gender and smoking behavior similarities (McPherson et

108 JOURNAL OF STUDIES ON ALCOHOL AND DRUGS / JANUARY 2012

al., 2001; Mercken et al., 2010). When examining selection processes, these alternative mechanisms should be taken into account. The following limitations of this study should be men-tioned. First, the use of a name generator limited to a maximum of fi ve friends might have limited adolescents’ possibilities to nominate all of their best friends. However, previous research that allowed seventh graders to nominate any number of friends showed that, on average, only 4.09 friends were nominated (Cairns et al., 1995). Allowing adolescents to nominate more than fi ve best friends might provoke them to nominate peers who are not “best” friends. Second, we focused on friendships within the same school grade. Although for adolescents these specifi c friends form an important social environment, they do not represent their entire social network of peers. Previous research has argued that problem behaviors accumulate for those adolescents hanging out with out-of-school friends (Mahoney and Stat-tin, 2000); hence, it is feasible that those adolescents who have many friends outside school could be less susceptible to the infl uence of their friends inside school. Having mainly older, younger, or same-aged friends could also moderate in-fl uence and selection processes. Future social-network stud-ies should, therefore, aim to include all friends outside and inside school. Third, we could not include classroom mem-bership effects because this information was not available. This might have led to an overestimation of selection based on similar alcohol use because adolescents in the same class-room may have a higher chance to become friends. Fourth, we did not distinguish between selection and de-selection. If, during the fi rst period, there was a positive effect of alcohol-based selection but also a negative effect of deselection (a signifi cant tendency not to drop friends because they are similar on alcohol consumption), then both could cancel out in the analysis. Because previous research found evidence for such deselection processes in the context of depression (Van Zalk et al., 2010), we encourage future research to explore this possibility. Fifth, the participants in the present study were from the capital city area of Finland. Future stud-ies should examine whether the living environment of ado-lescents (living in a small or large city vs. in the countryside) moderates selection and infl uence effects. Finally, it was not yet possible to model infl uence effects focusing on specifi c levels of the modeled alcohol-consumption scale (i.e., the infl uence of only those adolescents who drink at very high rates or the susceptibility of only those adolescents who do not drink to the specifi c infl uence of drinkers or abstainers) using actor-based models for network behavior co-evolution. This study has several practical implications. First, alco-hol-prevention programs should not solely focus on social infl uence processes but should also consider peer selection processes. Previous research has already emphasized that peer network structure needs more attention within preven-tion programs besides the promotion of social infl uence

skills (Dishion and Owen, 2002; Pearson and West, 2003; Valente et al., 2003). Second, prevention programs should draw on different strategies for early and mid-adolescence. Although the legal drinking age in Finland is 18, more than half of the 13.6-year-olds had already consumed alcohol and were particularly susceptible to the infl uence of friends. Therefore, programs targeting youngsters in early adoles-cence should teach adolescents not to adjust their drinking behavior to their alcohol-consuming friends. A reduction in susceptibility to peer infl uence might postpone initiation of drinking. During mid-adolescence, programs might prevent adolescents from selecting friends based on similar alcohol use by making adolescents aware of how friendships are formed and which characteristics predict a long-lasting friendship. Furthermore, the changes in selection and infl u-ence processes demonstrated in the present study stress the importance of considering such changes over time while modeling selection and infl uence processes in future re-search. Third, adolescents in the present study signifi cantly selected friends based on similar gender, which indicates that there are gender-segregated social networks of boys and girls. Future research should explore the possible differ-ences in selection and infl uence processes between male and female friendship networks in the context of alcohol use.

Acknowledgments

Ethical approval was obtained from the research institute CAPHRI, Maastricht University Maastricht, The Netherlands. The authors thank Dr. Erkki Vartiainen, co-contractor of the European Smoking Prevention Framework Approach project.

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