Friend Influence on Prosocial Behavior: The Role of Motivational ...

Developmental Psychology Copyright 2006 by the American Psychological Association
2006, Vol. 42, No. 1, 153–163 0012-1649/06/$12.00 DOI: 10.1037/0012-1649.42.1.153
<strong>Friend</strong> <strong>Influence</strong> on Prosocial Behavior: The Role of Motivational Factors
and <strong>Friend</strong>ship Characteristics
Carolyn McNamara Barry
Loyola College in Maryland
Kathryn R. Wentzel
University of Maryland
This study examined motivation (prosocial goals), individual characteristics (sex, ethnicity, and grade),
and friendship characteristics (affective quality, interaction frequency, and friendship stability) in relation
to middle adolescents’ prosocial behavior over time. Ninth- and 10th-grade students (N 208) attending
a suburban, mid-Atlantic public high school and having at least 1 reciprocated friendship were followed
for 1 year. Hierarchical regression analyses revealed that a friend’s behavior is related to an individual’s
prosocial goal pursuit, which in turn, is related to an individual’s prosocial behavior. Further, the
affective quality of a friendship and the frequency with which friends interact moderate relations of a
friend’s prosocial behavior to an individual’s prosocial goal pursuit.
Keywords: friendship, prosocial behavior, motivation, friendship quality, adolescence
Theory as well as research supports the notion that friends can
be important socializers of prosocial behavior. According to Piaget
(1932/1965), friendships are more egalitarian than any other type
of peer relationship or the parent–child relationship. Therefore,
friendships afford a unique context for interaction and collaboration
wherein children socially construct their morality of interpersonal
responsibility and mutual concern (e.g., Corsaro & Eder,
1990; Damon, 1988; Youniss, 1981). Others (Berndt, 1999; Hartup
& Stevens, 1997) have argued that friends can have motivational
significance by modeling positive forms of social behavior; as
friends interact with and observe each other, change in their
behavior can be explained by characteristics of the friendship.
Research provides some support for these theoretical assertions in
that, compared with acquaintances, friends engage in more frequent
and positive social interactions that facilitate the development
of moral actions (Azmitia & Montgomery, 1993; Damon &
Killen, 1982; Nelson & Aboud, 1985). In addition, children who
observe prosocial behavior of peers are likely to behave similarly
(Bryan & Walbek, 1970; Elliott & Vasta, 1970; Hartup & Coates,
1967), in part because friends tend to reinforce each other for
behavior that is like their own (Hartup, 1983).
Of interest in the present study is the fact that few researchers
have examined the positive influence of friends on social devel-
Carolyn McNamara Barry, Department of Psychology, Loyola College
in Maryland; Kathryn R. Wentzel, Department of Human Development,
University of Maryland.
The first wave of data collection was used for Carolyn McNamara
Barry’s fulfillment of the doctoral dissertation at the University of Maryland.
Portions of this study were presented at the biennial meetings of the
Society for Research in Child Development, Minneapolis, Minnesota,
April 2001, and Tampa, Florida, April 2003. We extend our gratitude for
a research grant from the Department of Human Development, University
of Maryland, given to Carolyn McNamara Barry.
Correspondence concerning this article should be addressed to Carolyn
McNamara Barry, Department of Psychology, Loyola College in Maryland,
4501 North Charles Street, Baltimore, MD 21210-2699. E-mail:
cbarry@loyola.edu
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opment, especially prosocial behavior during adolescence. Much
more is known about how peers influence one another to engage in
various forms of risk-taking behaviors (Pleydon & Schner, 2001;
Prinstein, Meade, & Cohen, 2003). In addition, studies of positive
friend influence have been conducted primarily with younger
children. However, adolescents spend increasingly more time with
their friends (Crockett, Losoff, & Petersen, 1984) and are more
dependent on their peers than are younger children (Larson &
Richards, 1991). In light of these issues, the focus of the present
study was on relations between friends’ and individuals’ prosocial
behavior as adolescents make their way through high school.
Toward this end, we examined individuals’ pursuit of goals to
behave prosocially as a motivational process that links their perception
of a friend’s prosocial behavior and their own prosocial
behavior (as assessed by the collective peer group). In addition, we
studied affective quality, interaction frequency, and stability
among friends as characteristics that might explain significant
relations between an individual’s perception of a friend’s prosocial
behavior and an individual’s prosocial goal pursuit.
<strong>Friend</strong>ships and Prosocial Behavior
Although the research is limited, significant relations between
friendships and prosocial behavior have been documented. First,
friends are similar in the degree to which they display prosocial
behavior and are motivated to do so (Wentzel, Barry, & Caldwell,
2004; Wentzel & Caldwell, 1997). In addition, prosocial behavior
occurs more frequently between friends than between peers who
are not friends (Berndt, 1985; Berndt, Hawkins, & Hoyle, 1986).
Young adolescents who have friends are more likely to be prosocial
than are those without friends (McGuire & Weisz, 1982).
Also, similarity of levels of prosocial intentions and prosocial
behavior between friends increases over time (Berndt, 1981a).
Finally, not only is prosocial behavior more common among
friends than among nonfriends, but children conceptualize friendships
as involving prosocial interactions such as sharing and cooperating
(Berndt, 1981b; Bigelow & LaGaipa, 1980).

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It is likely that these significant relations partly reflect the fact
that adolescents who demonstrate one type of social competence
(i.e., making friends) often display other types as well. Of additional
interest, however, is whether these relations also reflect a
process of friend influence (Berndt, 1999; Hartup, 1996). As noted
by Hartup and Stevens (1997), theoretical models to explain the
process of friend influence are scant. However, some scholars
(e.g., Berndt, 1999; Wentzel et al., 2004) have adopted a sociallearning
perspective to explain this process. For instance, individuals
might develop specific behavioral styles or interests because
these are considered to be desirable characteristics of their close
friends (Bukowski & Hoza, 1989; Hartup, 1996; Hartup &
Stevens, 1997). Specifically, the tenets of observational learning
(e.g., Bandura, 1986) support the notion that if a friend models
certain types of behavior, an individual is likely to behave like the
friend subsequently, because exposure to modeled behavior is
frequent and affectively charged.
Adolescents report greater frequency in observing their friends’
behavior than their nonfriends’ behavior (Crockett et al., 1984).
Moreover, friendships typically are characterized by strong emotional
bonds, thereby increasing the likelihood that friends will
imitate each other’s behavior (Berndt & Perry, 1986). Given the
strong emotional bonds between friends (Berndt & Perry, 1986),
especially during adolescence, it is plausible that friends might
mimic each other’s behavior. Therefore, friend influence by way
of observational learning is most likely to occur when (a) the
affective quality of a friendship is high, such that a friend provides
an important source of nurturance to the individual, and (b) the
interaction frequency and friendship stability between an individual
and a friend is high, such that they spend a significant amount
of time together.
Bandura (1986) further argued that although behavior can be
learned by observing others, it is likely to be enacted to the extent
that an individual is motivated to do so. Therefore, an individual’s
behavior might become more similar to a friend’s behavior because
of a change in underlying motivational processes, such as
goals and values. In the current study, therefore, we predicted that
the affective quality, interaction frequency, and stability of a
friendship would moderate the relation between a friend’s prosocial
behavior and an individual’s goal pursuit. In turn, an individual’s
prosocial goal pursuit was predicted to relate to an individual’s
prosocial behavior, thereby providing a pathway between
friends’ and individuals’ prosocial behavior. A prosocial goal was
defined as a cognitive representation of the extent to which an
individual would like to display prosocial behavior in a given
situation (Ford, 1992; Wentzel, 1994); goal pursuit marks the
frequency with which individuals see themselves as trying to
achieve the goal. Personal goals are one component of a larger
system of motivation that includes the direction (personal goals),
energization (emotional arousal), and regulation (personal agency)
of behavior (see Eccles, Wigfield, & Schiefele, 1998; Ford, 1992).
In summary, although the similarity of friends’ behavior has
been noted for some time (Kandel, 1978a, 1978b), the process by
which friends influence one another is less well understood. In the
current study, we examined how friendship stability and the affective
quality and interaction frequency between friends increased
the likelihood that a friend’s prosocial behavior would motivate an
individual to behave prosocially. In turn, motivation to behave
prosocially was posited to be related directly to displays of proso-
BARRY AND WENTZEL
cial behavior (e.g., Wentzel, 1994), as shown in Figure 1. According
to Kandel (1978a), the similar behavior exhibited by friends is
likely the result of two distinct processes: selection and influence.
Similarity among friends explains, in part, why individuals become
friends (Hallinan & Williams, 1990); however, friends’
characteristics explain change in adolescents’ behavior over time
(Berndt & Keefe, 1995). Research designs typically have confounded
selection with influence by not accounting for the extent
to which two friends are similar at the point of friendship formation.
Therefore, to study influence, one must control for selection.
In the current longitudinal study, we did this by examining the
extent to which friends’ behavior at Time 1 predicted individuals’
behavior at Time 2 while taking into account individuals’ behavior
at Time 1.
Research Questions
In the current study, we examined the processes by which a
friend’s prosocial behavior is related to change in an individual’s
prosocial behavior over 1 year. Two specific questions were
addressed:
1. Does prosocial goal pursuit provide a pathway that links a
friend’s prosocial behavior and an individual’s (i.e., target’s)
prosocial behavior? Target’s prosocial goal pursuit was believed to
explain the association between a friend’s prosocial behavior at
Time 1 and change in target’s prosocial behavior over 1 year.
2. To what extent do friendship characteristics of affective
quality, interaction frequency, and friendship stability moderate
the relation of a friend’s prosocial behavior to an individual’s
prosocial goal pursuit? These relations (depicted in Figure 1) were
examined while taking into account sex, grade, and ethnicity;
research has documented that prosocial behavior varies as a function
of these variables (Carlo, Hausmann, Christiansen, & Randall,
2003; Eisenberg & Fabes, 1998; Fabes & Eisenberg, 1996 [as cited
in Fabes, Carlo, Kupanoff, & Laible, 1999]).
Participants
Method
Students attending a suburban public high school in the New York
metropolitan area participated in the 2-year longitudinal study. The median
annual household incomes for the two towns that comprised the high
school student population were $106,208 and $101,991 (U.S. Bureau of the
Census, 2000). The Time 1 sample consisted of 287 9th-grade (n 145)
and 10th-grade (n 142) students, and the longitudinal sample consisted
of 265 9th-grade (n 134) and 10th-grade (n 131) students. Data were
collected in the spring of each consecutive year. All students participated
unless parental permission was denied (n 26), the students were absent
Figure 1. Proposed conceptual model of friend influence.

on the day of data collection (n 24), or the students themselves chose not
to participate on the day of data collection (n 1). At both time points, the
demographic characteristics of the sample were as follows: 58% female,
42% male, 90% Caucasian, 6% Asian, 2% Hispanic, and 1% members of
other minority groups. Students who did not participate in the second data
collection because of attrition or absence (n 21) did not differ significantly
from those in the longitudinal sample with respect to demographic
characteristics or study variables.
Procedure
At each of the two data collections, C.M.B. collected data from all
participating 9th-grade and 10th-grade students in their 43-min social
studies classes (18 classes for Time 1, 17 classes for Time 2) in the spring
of each year. Data collection that occurs later in the school year is
advantageous, because students’ familiarity with their peers is maximized.
Students were assured confidentiality for all responses and informed that
they did not have to answer any question that they did not want to answer.
The researcher remained in the classroom and clarified instructions as
needed. Classroom teachers (N 6 at Time 1 and Time 2) remained in the
classroom throughout the data collection.
Measures
All measures were administered at both time points.
Background information. Students were asked to complete a demographic
questionnaire that specified their sex (0 male, 1 female),
grade level (9 or 10 for Time 1, 10 or 11 for Time 2), and ethnicity (1
Caucasian, 2 African American, 3 Asian, 4 Hispanic, 5
American Indian, 6 other).
<strong>Friend</strong>ship. Students were instructed to write the first and last names of
their three best friends from their high school; however, they were informed
that they could choose fewer names if they so desired. Only same-sex friendships
were investigated in the current study because these capture the majority
of best friendships for adolescents (Hartup, 1992), and they differ in quality
from opposite-sex friendships (Sharabany, Gershoni, & Hofman, 1981). Samegrade
friendships were examined to maximize the interaction frequency in
these school-based relationships. From the names provided, reciprocated
friendships were determined by matching students’ school-based best friend
nominations with each other. At Time 1, 21% of the students had no reciprocated
friendships, 34% had one reciprocated friendship, 30% had two reciprocated
friendships, and 15% had three reciprocated friendships. At Time 2,
16% of the students had no reciprocated friendships, 31% had one reciprocated
friendship, 36% had two reciprocated friendships, and 17% had three reciprocated
friendships. Data from students who had at least one reciprocated
friendship were used in all analyses (n 228, Time 1; n 221, Time 2); cases
in which nominated best friendships were not reciprocated (n 59, Time 1;
n 44, Time 2) were disregarded.
All data corresponding to a target individual’s reciprocated friends were
obtained from either the sole reciprocated friendship or a randomly selected
reciprocated friend (if the target had more than one). For all analyses, listwise
deletion was used, resulting in a final longitudinal sample of 208. Among the
original sample of ethnic minority students at Time 1, 42% did not have a
reciprocated friendship. Among ethnic minority students with a reciprocated
friendship, only 4 (i.e., 29%) had a same-race friendship, and all of these were
between Asian Americans. The remaining 71% of the reciprocated friendships
among ethnic minorities were cross-race, with most (50%) of those friendships
between Asian American and Caucasian students.
Affective quality. Two measures were used to assess affective quality:
friendship closeness and friendship importance. <strong>Friend</strong>ship closeness was
assessed with the Affective Bond and Reflected Appraisal subscales of the
<strong>Friend</strong>ship Qualities Scale (Bukowski, Hoza, & Boivin, 1994). Students
were asked to indicate how true five statements were about each of their
nominated friendships on a scale of 1 (not true) to5(really true). Because
PROSOCIAL BEHAVIOR
students could nominate up to three friends, three copies of this questionnaire
were provided to each student. Students were asked to write the name
of their respective friend on a line labeled <strong>Friend</strong> #1, <strong>Friend</strong> #2, or<strong>Friend</strong>
#3; each item referred to <strong>Friend</strong> #1, #2, or #3, respectively. A sample item
from the Affective Bond subscale is “I feel happy when I am with <strong>Friend</strong>
#1,” and a sample item from the Reflected Appraisal subscale is “When I
do a good job at something, <strong>Friend</strong> #1 is happy for me.” The five scores
for each friend were averaged to form a single closeness score; only Time
1 scores were used for analyses (M 4.00, SD 0.75, Cronbach’s
.85). According to Bukowski et al. (1994), reciprocated friendships have
higher closeness scores than do unreciprocated friendships, and stable
friendships over a 6-month period have been associated with significantly
higher ( p .05) closeness scores than have unstable friendships.
Affective quality was also assessed by a target individual’s perceived
importance of a friendship. After students indicated the names of their three
school-based best friends, they were instructed to rate each friendship on a
scale of 1 (important) to3(extremely important); only Time 1 scores were
used for analyses (M 2.48, SD 0.65). The two indicators of affective
quality were related significantly (r .55, p .001), and thus, scores were
averaged to form a composite (M 3.24, SD 0.62).
Interaction frequency. Students completed the Interaction Frequency
subscale of Berndt and Keefe’s friendship features questionnaire (T. J.
Berndt, personal communication, October 1997). Students were asked to
indicate how frequently they interacted with their friend by rating six items
(see the Appendix) on a scale of 1 (never) to5(every day). (With Berndt’s
permission, we made a minor modification to the wording of the scale such
that “this friend” was replaced with “<strong>Friend</strong> #1,” “<strong>Friend</strong> #2,” or “<strong>Friend</strong>
#3” so as to remind the students of the particular friendship about which
they were answering questions.) The six scores for each friend were then
averaged to form a single interaction-frequency score; only Time 1 scores
were used for analyses (M 3.44, SD 0.70, Cronbach’s .78).
<strong>Friend</strong>ship stability. As noted above, the longitudinal sample consisted
only of individuals with a reciprocated friend at Time 1. <strong>Friend</strong>ship-stability
scores reflected whether the target maintained a reciprocated friendship over
time. If target’s reciprocated friendship at Time 1 was also reciprocated at
Time 2, then friendship stability was coded as 3; if target’s reciprocated
friendship at Time 1 was unreciprocated (but mentioned) at Time 2, friendship
stability was coded as 2; if target’s reciprocated friendship at Time 1 was not
mentioned as a friend at Time 2, then friendship stability was coded as 1. On
the basis of the sample of only those with reciprocated friendships at Time 1,
the frequencies for friendship stability were as follows: 31.8% for 1, 9.8% for
2, and 58.4% for 3.
Prosocial goal pursuit. Students were asked to complete the Prosocial
Goal Pursuit scale (Wentzel, 1991), which consists of academic (e.g.,
“How often do you try to share what you’ve learned with your classmates?”)
and social (e.g., “How often do you try to cheer someone up when
something has gone wrong?”) subscales. Students rated on a scale of 1
(rarely) to5(almost always) how often they tried to accomplish various
prosocial behaviors. The two subscales were correlated significantly (r
.46, p .001), and thus, scores were averaged to form a composite (M
3.78, SD 0.56, Cronbach’s .75).
Target’s prosocial behavior. Peer nominations were used to assess
target’s prosocial behavior (see Wentzel, 1994). Students were given three
sheets of paper, with a different behavioral description on each, along with
a list of 15 randomly generated names of same-sex students from their
grade. Lists of names were randomly generated to obtain independent
nominations for each behavior, to gain the perspective of the peer group at
large, and to minimize the amount of time necessary for data collection.
The three questions were as follows:
1. Who cooperates and shares?
2. Who helps other kids when they have a problem?
3. Who shares things with you when you need something?
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156
Each student’s name appeared on other students’ lists approximately 12
times for each question. Students were asked to circle the names of
classmates who fit each behavioral description and to cross out all names
of classmates whom they did not know. Scoring consisted of computing a
ratio of the number of nominations a student received divided by the
number of times the student’s name appeared minus the number of times
the student was not known by classmates. Because these items were
correlated significantly (for Time 1, r .60 for Questions 1 and 2, r .62
for Questions 1 and 3, and r .56 for Questions 2 and 3; for Time 2, r
.58 for Questions 1 and 2, r .65 for Questions 1 and 3, and r .64
for Questions 2 and 3; for all six correlations, p .001), the three
nomination scores were averaged to form a prosocial behavior composite
at each time point.
<strong>Friend</strong>’s prosocial behavior. Each participant was asked to complete
the Prosocial Interaction scale of the questionnaire on friendship features
(Berndt & Keefe, 1995) and the Help scale of the <strong>Friend</strong>ship Qualities
Scale (Bukowski et al., 1994). A sample item for the Prosocial Interaction
scale is “<strong>Friend</strong> #1 helps me if I can’t do something by myself.” The Help
scale consists of two subscales: Aid (e.g., “<strong>Friend</strong> #1 would help me when
I needed it”) and Protection (e.g., “<strong>Friend</strong> #1 would stick up for me if
another kid was causing me trouble”). The original scales have two
different rating systems; to keep the directions as clear and simple as
possible for the participants, we adopted the Bukowski et al. (1994) rating
system. Thus, students were asked to rate on a scale of 1 (not true) to5
(really true) how often the specified friend exhibits various indicators of
prosocial behavior. Each participant was asked to respond to these prosocial
items for each nominated friend. Then the nine scores for each friend
were averaged to form a single prosocial-behavior score (for Time 1, M
4.04, SD 0.68, Cronbach’s .76; for Time 2, M 4.18, SD 0.76,
Cronbach’s .75).
Results
In this study, we sought to identify the process by which friends’
prosocial behavior relates to targets’ prosocial behavior by addressing
two research questions. For the first research question,
goals were posited to provide a pathway between a friend’s prosocial
behavior and changes in a target’s prosocial behavior. Specifically,
we predicted that a friend’s behavior would be related to
changes in goal pursuit over time; in turn, a target individual’s goal
pursuit would be related to that target’s change in prosocial behavior.
To examine this question, we applied the most stringent
test of mediation. As described by Baron and Kenny (1986),
Table 1
Intercorrelations Among Variables
support for mediation is found when (a) the independent variable
significantly predicts both the mediator and the outcome (i.e.,
friend’s prosocial behavior significantly predicts both target’s
prosocial goal pursuit and target’s prosocial behavior), (b) the
mediator significantly predicts the outcome (i.e., target’s prosocial
goal pursuit significantly predicts target’s prosocial behavior), and
(c) the independent variable predicts the outcome less (partial
mediation) or nonsignificantly (complete mediation) when the
mediator also is included as a predictor (i.e., friend’s prosocial
behavior is a less significant or nonsignificant predictor of target’s
prosocial behavior when target’s prosocial goal pursuit is included
in the regression equation).
We also examined the role of friendship characteristics (affective
quality, interaction frequency) in moderating the relation
between friend’s prosocial behavior at Time 1 (T1) and change in
target’s prosocial goal pursuit over time; and we examined the role
of friendship stability in moderating the relation between friend’s
prosocial behavior at Time 2 (T2) and change in target’s prosocial
goal pursuit over time (in this case, the T2 score for friend’s
behavior was used, because friendship stability occurred over two
time points). According to Baron and Kenny (1986), support for
moderation is found when interaction terms entered at the final
step of a hierarchical regression are significant. Support for moderation
may also be found when an individual interaction term
(e.g., Affective Quality <strong>Friend</strong>’s Prosocial Behavior) is a significant
predictor, even if the overall step for the interaction term
is not significant. A power analysis was conducted in accordance
with Cohen (1992), and the final longitudinal sample size was
found to be adequate to detect medium effect sizes.
Question 1: Does Prosocial Goal Pursuit Provide a
Pathway That Links a <strong>Friend</strong>’s Prosocial Behavior
and an Individual’s Prosocial Behavior?
Target’s prosocial goal pursuit was predicted to explain the
association between a friend’s prosocial behavior (T1) and a
target’s prosocial behavior 1 year later, as depicted in Figure 1. To
examine this hypothesis, we first computed zero-order correlations.
As shown in Table 1, friend’s prosocial behavior was related
significantly and positively to target’s prosocial goal pursuit at
Variable 1 2 3 4 5 6 7 8 9
1. Sex —
2. <strong>Friend</strong>’s prosocial behavior, T1
(target’s perception of behavior) .36*** —
3. Affective quality, T1 .42*** .73*** —
4. Interaction frequency, T1 .15* .39*** .49*** —
5. <strong>Friend</strong>ship stability .03 .06 .19*** .12 —
6. Target’s prosocial goal pursuit, T1 .35*** .34*** .25*** .17** .01 —
7. Target’s prosocial goal pursuit, T2 .35*** .32*** .24*** .09 .00 .59*** —
8. Target’s prosocial behavior, T1
(peer-nominated behavior) .26*** .01 .09 .06 .09 .25*** .18** —
9. Target’s prosocial behavior, T2
(peer-nominated behavior) .43*** .14* .22** .07 .08 .37*** .28*** .75*** —
Note. n 208. T1 Time 1; T2 Time 2.
* p .05. ** p .01. *** p .001.
BARRY AND WENTZEL

oth time points and to target’s prosocial behavior at T2 (on the
basis of peer nominations) but not to target’s prosocial behavior at
T1 (also on the basis of peer nominations). Moreover, target’s
prosocial goal pursuit at both time points was related significantly
and positively to target’s prosocial behavior at both time points.
Sex was related significantly and positively to friend’s prosocial
behavior, target’s prosocial goal pursuit (T1 and T2), and target’s
prosocial behavior (T1 and T2). In other words, girls were more
likely to perceive their friends as prosocial, to report frequent
prosocial goal pursuit, and to be nominated by same-sex, samegrade
classmates as more prosocial than were boys. 1
The significant correlations indicated that testing for mediation
had merit, in that variables of interest were related in the expected
directions. To test for mediation more formally, we next examined
the pathway from friend’s prosocial behavior to target’s prosocial
goal pursuit with a series of regression models. First, we regressed
prosocial goal pursuit at T1 on friend’s prosocial behavior (Condition
a of Baron & Kenny, 1986). As shown in Table 2, friend’s
prosocial behavior significantly and positively predicted target’s
prosocial goal pursuit, F(2, 174) 16.35, p .0001. (Step 3 was
included to test moderation, which is described in the next section.)
We next examined relations between friend’s prosocial behavior
and change in goal pursuit over time by regressing prosocial
goal pursuit at T2 on friend’s prosocial behavior at T1, after
controlling for prosocial goal pursuit at T1 (an extension of Baron
& Kenny’s, 1986, Condition a). As shown in Table 3, friend’s
prosocial behavior was not a significant predictor of target’s prosocial
goal pursuit (T2), although target’s prosocial goal pursuit (T1)
significantly predicted target’s prosocial goal pursuit (T2). Finally,
we regressed prosocial behavior at T2 on both friend’s prosocial
behavior at T1 and prosocial goal pursuit at T2 (Conditions b and
c of Baron & Kenny, 1986), after controlling for prosocial goal
pursuit at T1. As shown in Table 4, target’s prosocial goal pursuit
(T1, but not T2) predicted target’s prosocial behavior at T2 with
friend’s prosocial behavior at T1 controlled for.
Taken together, the results of the regression analyses indicate
that target’s prosocial goal pursuit (T1) served as a pathway that
links friend’s prosocial behavior (T1; on the basis of target’s
perception) to target’s prosocial behavior (T2; on the basis of peer
nominations), in that friend’s prosocial behavior (T1) was related
to target’s prosocial goal pursuit (T1), and target’s prosocial goal
Table 2
Results of Hierarchical Regression Analysis on Target’s
Prosocial Goal Pursuit, Time 1
Variable Step 1 Step 2 Step 3
1. Sex
2. <strong>Friend</strong>’s prosocial behavior
.30*** .20** .19**
(FPB), T1 .28*** .35***
3. Interaction Frequency FPB, T1 .16*
Affective Quality FPB, T1 .21**
<strong>Friend</strong>ship Stability FPB, T2 .01
R 2
.09*** .07*** .05*
Total R 2
.21***
Note. n 177. The standard errors for each step are as follows: .55 (Step
1), .53 (Step 2), and .52 (Step 3). T1 Time 1; T2 Time 2.
* p .05. ** p .01. *** p .001.
PROSOCIAL BEHAVIOR
pursuit at T1 was related to the change in target’s prosocial
behavior over time. However, complete mediation, as defined by
Baron and Kenny (1986), was not supported given that friend’s
prosocial behavior (T1) was a nonsignificant predictor of change
in target’s prosocial goal pursuit, and target’s prosocial goal pursuit
(T2) was a nonsignificant predictor of target’s prosocial behavior
(T2).
Question 2: How Do <strong>Friend</strong>ship Characteristics of
Affective Quality, Interaction Frequency, and <strong>Friend</strong>ship
Stability Moderate the Relation of a <strong>Friend</strong>’s Prosocial
Behavior to a Target Individual’s Prosocial Goals?
157
In keeping with social-learning theory (Bandura, 1986), we
hypothesized that behavior is learned, in part, through observing
best friends. Moreover, we predicted that friend influence is most
likely to occur by way of goal pursuit when (a) the affective
quality of a friendship is high, and (b) the interaction frequency
and friendship stability between an individual and a friend are high
such that the individual and friend spend a significant amount of
time together.
To test for these moderating effects, we included interaction
terms at the last step of the regression analyses presented in Tables
2 and 3: Affective Quality <strong>Friend</strong>’s Prosocial Behavior, Interaction
Frequency <strong>Friend</strong>’s Prosocial Behavior, and <strong>Friend</strong>ship
Stability <strong>Friend</strong>’s Prosocial Behavior. Affective quality, interaction
frequency, and friend’s prosocial behavior were mean centered
to reduce the redundancy of each interaction term.
As shown in Table 2, two interaction terms (involving affective
quality and interaction frequency) included at Step 3 significantly
predicted target’s prosocial goal pursuit at T1; however, friendship
stability was not a significant predictor. As shown in Table 3, the
Affective Quality <strong>Friend</strong>’s Prosocial Behavior interaction term
was not a significant predictor of T2 goal pursuit with T1 goal
pursuit controlled for. (We tested models in which each interaction
term was entered as a separate step, and the results were not
significantly different from those reported in Tables 2 and 3).
To explore further the significant Affective Quality <strong>Friend</strong>’s
Prosocial Behavior interaction for target’s prosocial goal pursuit at
T1, we regressed goal pursuit (T1) on friend’s prosocial behavior
for each of three levels of affective quality, as determined by a
subdivision of the affective quality variable along the 33rd and
67th percentiles (see Aiken & West, 1991). <strong>Friend</strong>’s behavior was
a significant, positive predictor ( .38, p .001) of goal pursuit
at T1 only when affective quality was high, F(1, 68) 11.43,
SE 0.43, p .001 (see Figure 2). These findings thereby suggest
that friend’s prosocial behavior is related to target’s prosocial goal
pursuit at T1 when the target perceives the friendship to have high
levels of affective quality.
To explore further the significant Interaction Frequency
<strong>Friend</strong>’s Prosocial Behavior interaction for target’s prosocial goal
pursuit at T1, we regressed goal pursuit (T1) on friend’s prosocial
behavior for each of three levels of interaction frequency, as
determined by a subdivision of the interaction frequency variable
1 Initially, grade and ethnicity were included within the first step for all
three regressions; however, the two variables were nonsignificant and,
thus, omitted from what is reported here.

158
Table 3
Results of Hierarchical Regression Analysis on Target’s Prosocial Goal Pursuit, Time 2
along the 33rd and 67th percentiles. <strong>Friend</strong>’s behavior was a
significant, positive predictor ( .42, p .0001) of goal pursuit
at T1 only when interaction frequency was low, F(1, 76) 16.67,
SE 0.57, p .0001 (see Figure 3). Thus, friend’s prosocial
behavior was related to target’s prosocial goal pursuit at T1 when
the target had low levels of interaction frequency with the friend.
Finally, as shown in Table 3, Interaction Frequency <strong>Friend</strong>’s
Prosocial Behavior was a significant, positive predictor of change
in target’s prosocial goal pursuit over time. Because the latter
interaction term was positive, in contrast to the negative interaction
term shown in Table 2, a close examination through follow-up
analyses is required to understand such significant results, because
inspection of the sign of the interaction term can be misleading
(Mossholder, Kemery, & Bedeian, 1990). As a result, we further
explored this finding, in accordance with Aiken and West (1991),
by regressing target’s goal pursuit (T2) on both goal pursuit (T1)
and friend’s prosocial behavior for each of the three levels of
interaction frequency. <strong>Friend</strong>’s behavior was a significant, positive
predictor ( .29, p .002) of goal pursuit at T2 only when
interaction frequency was high, F(2, 72) 30.97, SE 0.41, p
.0001 (see Figure 4). Therefore, low frequency of interaction
appeared to have a significant and positive impact on concurrent
Variable Step 1 Step 2 Step 3 Step 4
1. Sex .32*** .15* .11† .11†
2. Prosocial Goal Pursuit, T1 .57*** .54*** .57***
3. <strong>Friend</strong>’s prosocial behavior (FPB), T1 .12† .05
4. Interaction Frequency FPB, T1 .13*
Affective Quality FPB, T1 .06
<strong>Friend</strong>ship Stability FPB, T2 .09
R 2
.10*** .30*** .01† .02
Total R 2
.43***
Note. n 177. The standard errors for each step are as follows: .57 (Step 1), .47 (Step 2), .46 (Step 3), and
.46 (Step 4). T1 Time 1; T2 Time 2.
† p .10. * p .05. *** p .001.
Table 4
Results of Hierarchical Regression Analysis on Target’s
Prosocial Behavior, Time 2
Variable Step 1 Step 2 Step 3 Step 4
1. Sex .43*** .21*** .20*** .20***
2. Target’s prosocial
behavior, T1
.65*** .66*** .66***
Target’s prosocial goal
pursuit, T1
.14** .12** .13*
3. <strong>Friend</strong>’s prosocial
behavior, T1
.04 .04
4. Target’s prosocial goal
pursuit, T2
.01
R 2
.18*** .45*** .00 .00
Total R 2
.63***
Note. n 206. The standard errors for each step are as follows: .16 (Step
1) and .11 (Steps 2, 3, and 4). T1 Time 1; T2 Time 2.
* p .05. ** p .01. *** p .001.
BARRY AND WENTZEL
relations between friends’ prosocial behavior and targets’ goal
pursuit, whereas high interaction frequency appeared to have a
significant and positive impact on relations between friends’
prosocial behavior and targets’ goal pursuit over time.
Discussion
In this study, we examined the process by which a best friend
might influence an individual’s prosocial behavior. As predicted, a
friend’s prosocial behavior (as observed by the target individual)
was related to a target’s prosocial behavior (on the basis of peer
nominations) over time by way of a target’s pursuit of goals to be
prosocial at T1. In addition, friendship characteristics moderated
the relation between a friend’s prosocial behavior and a target’s
goal pursuit such that relations differed as a function of the
affective quality and frequency of interaction between friends.
Therefore, our findings provide further confirmation that motivational
processes can explain significant associations between the
behaviors of two friends, highlighting the importance of friendship
characteristics in defining the nature of relationships between a
friend’s behavior and an individual’s goal pursuit. Finally, the
significant gender differences in prosocial behavior and prosocial
goal pursuit found in our adolescent sample extend empirical
research (e.g., Parker & Asher, 1993) that has found such differences
in early and middle childhood (e.g., Eisenberg & Mussen,
1989), and they support theoretical contentions (see Eisenberg &
Figure 2. Effect of Affective Quality <strong>Friend</strong>’s Prosocial Behavior on
target’s prosocial goal pursuit at Time 1 (T1).

Figure 3. Effect of Interaction Frequency (Int Freq) <strong>Friend</strong>’s Prosocial
Behavior on target’s prosocial goal pursuit at Time 1 (T1).
Fabes, 1998) that girls are expected to behave in prosocial ways to
a greater extent than are boys.
Prosocial Goal Pursuit as an Intermediary Process
According to the tenets of observational learning (Bandura,
1986), an individual is likely to behave similarly to a friend
because exposure to modeled behavior is frequent and affectively
charged. In addition, Bandura (1986) proposed that although behavior
can be learned by observing others, it is likely to be enacted
to the extent that an individual is motivated to do so. The findings
of the current study support these notions, in that an individual’s
pursuit of prosocial goals (at both time points) was related to his or
her perception of his or her friend’s prosocial behavior. In addition,
changes in prosocial behavior (observed by the peer group)
over time were related to levels of goal pursuit at T1. These results
also replicate previous findings linking the prosocial behavior of
friends by way of goal pursuit (Wentzel et al., 2004), and they
provide further demonstration that friendships can have a significant
influence on motivational processes (e.g., Rose & Asher,
1999). The findings also affirm that prosocial goal setting is related
to displays of prosocial behavior over the course of 1 year (e.g.,
Nelson & Crick, 1999; Wentzel et al., 2004).
Our findings indicate that the amount of change in an individual’s
goal pursuit explained by a friend’s behavior is fairly small.
Indeed, the prosocial behavior of the students in our study was
highly stable over time. This was not surprising given that the
sample was composed of adolescents who enjoyed close friendships
and, therefore, were socially competent at the outset. In
addition, given the potential influence of adults (e.g., parents,
teachers, relatives), other children (e.g., siblings, rivals), and the
media on an adolescent’s behavior, our findings support the notion
that a friend’s behavior can be meaningful in the life of a student.
It also is important to note, however, that measures of a single
best friend’s prosocial behavior also might be a proxy for behavior
displayed by a larger group of friends and close acquaintances. For
example, Sage and Kindermann (1999) found that adolescents’
classroom motivation varies as a function of peer-group approval
and disapproval. Therefore, influence processes within friendship
cliques (see Wentzel & Caldwell, 1997) and peer networks (see
Kindermann, 1993) might be important targets for future research.
PROSOCIAL BEHAVIOR
In addition, an individual might observe and become motivated to
display the behavior of peers with whom he or she wants to
become friends. Pairings among potential or new friends have yet
to be examined in research on friend influence. However, research
on friendship-making strategies has shown that the display of
prosocial behavior (e.g., sharing) is a successful strategy for making
friends (Wentzel & Erdley, 1993). Therefore, changes in
prosocial behavior over time might reflect, in part, changes in
investments in forming and maintaining new friendships.
An unexpected finding was the nonsignificant concurrent relation
between a friend’s and a target’s prosocial behavior at T1
(depicted in Table 1). This lack of similarity in friends’ prosocial
behavior has not been reported elsewhere (cf. Wentzel et al.,
2004). A methodological explanation for this finding is that a
friend’s prosocial behavior was established on the basis of observations
of one individual, whereas a target’s prosocial behavior
was established on the basis of a larger set of peer nominations.
Therefore, a friend’s behavior scores reflected a relatively subjective
and less reliable assessment of a close friend, whereas a
target’s behavior scores were based on a more objective set of
assessments. In addition, items used to assess a friend’s prosocial
behavior were much more specific, reflecting behavior that is
likely to be observed more frequently by a friend than by the larger
peer group. For these reasons, the lack of significant overlap
between these two scores is understandable.
<strong>Friend</strong>ship Characteristics as Moderators
159
The results of our study also extend work in this area by
documenting the importance of friendship characteristics in explaining
relations between a friend’s behavior and an individual’s
goal pursuit. As suggested by the literature on observational learning,
the affective quality of a friendship and the frequency of
friends’ interactions, as perceived by an individual, appear to
influence relations between a friend’s behavior and the individual’s
goal pursuit. However, this influence only seems to occur
under specific conditions. For example, findings indicate that a
friend’s prosocial behavior is related positively to an individual’s
goal pursuit only when the target perceives the affective quality of
a friendship to be high. In other words, a friend’s prosocial
behavior is most likely to be associated with an individual’s
Figure 4. Effect of Interaction Frequency (Int Freq) <strong>Friend</strong>’s Prosocial
Behavior on target’s prosocial goal pursuit at Time 2 (T2).

160
motivation to be helpful and cooperative when the individual has
a strong, positive bond with that friend.
Significant moderating effects also were found for the frequency
of interactions between friends. In this case, at T1, a friend’s
observed behavior was related positively to an individual’s goal
pursuit only when the individual interacted infrequently with the
friend. However, over time, a friend’s prosocial behavior was
related positively to an individual’s goal pursuit when interaction
with that friend was frequent. This latter finding would be expected
on the basis of tenets of observational learning; behavior is
likely to be modeled if an individual has more frequent and stable
exposure to it over time. In contrast, the moderating effect at T1
might suggest that over the short term, modeling effects are not as
strong. One alternative explanation is that individuals who interact
with their best friends infrequently might expend greater effort to
behave prosocially simply to establish and maintain these friendships.
Although suggestive, our findings cannot support causal conclusions
concerning the effects of friendship qualities on an individual’s
prosocial goal pursuit. Indeed, it is possible that these
interaction effects may reflect perceived similarity, such that perceiving
high levels of prosocial behavior in a friend to whom one
is emotionally attached might lead to perceptions of one’s self as
behaving in similar ways and, thus, reporting high frequencies of
goal pursuit. However, some adolescents reported high levels of
prosocial goal pursuit even when their friends did not display
correspondingly high levels of prosocial behavior (e.g., the high
interaction-frequency group in Figure 3), suggesting that an explanation
based on similarity of friends does not hold for all cases.
Other factors beyond the friendship dyad might also be important
for understanding the link between a friend’s behavior and an
individual’s goal pursuit. For instance, cognitive processes described
by Bandura (1986)—such as how observations of prosocial
behavior are interpreted and stored in memory—and strategy
knowledge concerning how to actually produce prosocial behavior
might be particularly critical processes to examine in this regard.
Moreover, other motivational constructs, such as an individual’s
attributional style (Weiner, 1985) and perceived efficacy for prosocial
behavior (Bandura, 1994), and affective factors such as empathy
(Eisenberg, Wolchik, Goldberg, & Engel, 2002) should be
considered to understand more fully the circumstances under
which a target individual’s perception of a friend’s behavior might
influence an individual’s goal pursuit.
Methodological Issues
Several methodological aspects of our study also are important
to note. First, our measure of friendship placed restrictions on who
could be nominated as a friend: same-grade and same-sex individuals
who attended the same public high school. In reality, adolescents
often have friends who are of the opposite sex or are in a
different grade or school than they are. It is important to note,
however, that all of the study’s participants, even those without
reciprocated friendships, were able to list at least one best friend
who met our criteria. In addition, a limit of three best-friend
nominations was established. Although it is possible that students
had more than three best friends, it is highly unlikely that a
significant portion of students had more than three reciprocated
best friendships (only 15% of the study participants had three
reciprocated best friendships at T1). In general, however, our
BARRY AND WENTZEL
findings must be tempered with the reality that restrictions on
friendship nominations might result in identification of reciprocated
friendships that do not represent the best friendships or the
friendships of greatest quality for all participants.
In addition, our measure of interaction frequency did not include
interactions that take place via e-mail, instant messaging, text
messaging, or other venues that do not require physical proximity.
Indeed, these forms of interaction are becoming increasingly common
among adolescents (Bonebrake, 2002; Coffey & Stipp, 1997;
Odell, Korgen, Schumacher, & Delucchi, 2000). As a result, the
extent to which interaction frequency might influence how a
friend’s prosocial behavior is related to an individual’s motivation
is likely to be underreported in this study, especially given the high
socioeconomic status (SES) of the sample and the participants’
likely access to these technologies. Finally, a friend’s prosocial
behavior and a target’s prosocial-behavior scores were assessed on
the basis of information from the same individual. Although this
practice likely inflated the relation between these two variables,
our model was based on the assumption that an adolescent’s
observations of his or her friend’s behavior (rather than observations
made by the larger peer group) had the most proximal
influence on his or her subsequent behavior.
Sampling issues also are important to note, in that these friendships
occurred in fairly affluent and predominantly European
American communities. The preponderance of upper-middle-class
European American students in our sample allows for conclusions
about this population. However, the current investigation does not
further the understanding of friendship influence among ethnic
minority populations or students from lower SES communities. A
small literature suggests that friendships differ as a function of
ethnicity. For instance, African Americans tend to report denser
networks of neighborhood friends but talk to few friends during
school (DuBois & Hirsch, 1990). Moreover, Asian American
adolescents are more likely to have friends of the same race than
are both Latino and African American adolescents; however, African
Americans report greater close friendship support than do
Asian Americans (Way & Chen, 2000). Prosocial behavior also
varies as a function of ethnicity, such that Mexican American
adolescents tend to prefer cooperative to competitive behaviors
(see Knight, Bernal, & Carlo, 1995) more than do European
Americans. Further, cross-cultural research has documented variations
in prosocial behavior (for a review, see Carlo, Fabes, Laible,
& Kupanoff, 1999). Therefore, research that uses more ethnically
diverse samples is needed to investigate the generalizability of the
influence processes suggested by our findings to other groups of
non-Caucasian adolescent students.
Although our sample was limited, our findings indicate that
compared with almost 80% of European American students who
had reciprocated friendships, only 58% of the ethnic minority
students in the sample had a reciprocated friend. It is possible that
these students were more likely to have friendships outside of the
school context. However, the majority of the Asian American
students (the largest ethnic minority group in the school studied)
reported having either a same-race (25%) or cross-race (50%)
friendship (with the remaining 25% reporting no reciprocated
friendship). Therefore, adolescents in at least one minority group
appeared to be integrated into the social culture of the school to a
greater extent than were other ethnic minority adolescents. These
differences in friendship formation as a function of ethnicity

clearly deserve further study, with a focus on possible confounding
effects of SES of individual students, heterogeneity of values
within ethnic groups, and the degree to which these groups are a
minority within a particular school. Given that not all adolescents
are able to form friendships of high quality, scholars should also
examine influence processes among adolescents with low levels of
friendship quality.
Conclusion
The results of the present study suggest that the influence of best
friends on prosocial behavior might be explained, in part, by
observational learning processes. Specifically, goal pursuit appears
to provide a pathway that links a friend’s prosocial behavior to a
target’s prosocial behavior, with friendship characteristics (i.e.,
affective quality and interaction frequency) determining the nature
of relations between a friend’s prosocial behavior and a target’s
goal pursuit. To date, the body of literature on friend influence has
focused on numerous negative behaviors, such as alcohol (e.g.,
Urberg, Degˇirmenciogˇlu, & Pilgrim, 1997) and cigarette use (e.g.,
Ennett & Bauman, 1994). Therefore, the current findings also
extend the literature on adolescent friend influence to more positive
behaviors. Immediate directions for future research should
include the examination of individual characteristics (e.g., empathy),
other motivational constructs, and the roles of multiple
friends within an ethnically and socioeconomically diverse sample.
The study of friend influence could also be broadened to include
other peer socializers (e.g., members of cliques and peer networks)
to yield more ecological validity in the study of how and why
adolescents are motivated to display prosocial behavior.
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Appendix
Interaction Frequency Subscale (T. J. Berndt, Personal Communication, October 1997)
1. How often do you talk to <strong>Friend</strong> #1 on the phone?
2. How often do you and <strong>Friend</strong> #1 get together on weekends or after school?
3. How often do you and <strong>Friend</strong> #1 go places together, like a movie,
skating, shopping or a sport’s event?
4. How often do you and <strong>Friend</strong> #1 go over to each other’s houses?
5. How often do you and <strong>Friend</strong> #1 just sit around and talk about things
like school, sports, or anything else?
PROSOCIAL BEHAVIOR
Members of Underrepresented Groups:
Reviewers for Journal Manuscripts Wanted
6. How often do you spend time with <strong>Friend</strong> #1 when you have free time
during the school day?
If you are interested in reviewing manuscripts for APA journals, the APA Publications and
Communications Board would like to invite your participation. Manuscript reviewers are vital to the
publications process. As a reviewer, you would gain valuable experience in publishing. The P&C
Board is particularly interested in encouraging members of underrepresented groups to participate
more in this process.
If you are interested in reviewing manuscripts, please write to the address below. Please note the
following important points:
To be selected as a reviewer, you must have published articles in peer-reviewed journals. The
experience of publishing provides a reviewer with the basis for preparing a thorough, objective
review.
To be selected, it is critical to be a regular reader of the five to six empirical journals that are most
central to the area or journal for which you would like to review. Current knowledge of recently
published research provides a reviewer with the knowledge base to evaluate a new submission
within the context of existing research.
To select the appropriate reviewers for each manuscript, the editor needs detailed information.
Please include with your letter your vita. In the letter, please identify which APA journal(s) you
are interested in, and describe your area of experitise. Be as specific as possible. For example,
“social psychology” is not sufficient—you would need to specify “social cognition” or “attitude
change” as well.
Reviewing a manuscript takes time (1–4 hours per manuscript reviewed). If you are selected to
review a manuscript, be prepared to invest the necessary time to evaluate the manuscript
thoroughly.
Write to Journals Office, American Psychological Association, 750 First Street, NE, Washington,
DC 20002-4242.
163
Received August 25, 2004
Revision received June 3, 2005
Accepted June 9, 2005