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The Development of Prosociality fromAdolescence to Early Adulthood:

The Role of Effortful Control

Bernadette P. Luengo Kanacri,1 Concetta Pastorelli,1

Nancy Eisenberg,2 Antonio Zuffian,1 and

Gian Vittorio Caprara11Sapienza University of Rome,2Arizona State University

Abstract

Objective: The present longitudinal study examined the development of self-reported prosociality (i.e., the tendency to enactprosocial behaviors) from adolescence to early adulthood and its prediction from teacher-reported effortful control (i.e.,dispositional regulation) at age 13.Method: Participants were 573 (276 girls) Italian adolescents aged approximately 13 (M = 12.98, SD = 0.80) at the firstassessment and 21 (M = 21.23, SD = 0.67) at the last assessment.The study used three different cohorts recruited across tenyears (from1994 to 2004) from a larger longitudinal project with a multiple-cohort design.

Results: Latent growth curve modeling indicated that the overall level of prosociality declined until approximately age 17 witha subsequent slight rebound until age 21. Significant inter-individual variability in developmental trends of prosociality in malesand females was observed.Youths effortful control was related to a lesser decline of prosociality in adolescence.

Conclusions: Being able to regulate ones own emotions and behaviors in early adolescence may not only affect the tendencyto behave prosocially, but also counter the self-centered tendencies observed across this phase of development.

Keywords: prosocial behavior, effortful control, adolescence, early adulthood, longitudinal analysis, individual differences

Prosocial behavior (PB), defined as voluntary behavior aimed

at benefiting others (Batson, 1998; Eisenberg, Fabes, &

Spinrad, 2006; Penner, Dovidio, Piliavin, & Schroeder, 2005),

has been identified as a significant contributor to successful

youth development (Lerner, Dowling, & Anderson, 2002).

Nonetheless, compared to antisocial behavior, the develop-

ment of prosociality (i.e., the tendency to enact prosocial

behaviors) across adolescence and early adulthood has

received less attention (see, however, Carlo, Crockett, Randall,

& Roesch, 2007; Fabes, Carlo, Kupanoff, & Laible, 1999).

This is true despite the fact that adolescents who frequently

enact PBs tend to perform better at school (e.g., Caprara,Barbaranelli, Pastorelli, Bandura, & Zimbardo, 2000; Wentzel,

McNamara-Barry, & Caldwell 2004), are prone to show posi-

tive feelings about themselves and others, and are inclined to

develop the sense of belonging to the community (e.g., Keyes,

1998; Van Willigen, 2000). PB has also been positively related

to a low levels of adolescents internalizing and externalizing

problems (e.g., Bandura, Barbaranelli, Caprara, & Pastorelli,

1996; Eccles & Barber 1999).

In this study, we sought to extend prior findings (Carlo et al.,

2007; Kokko, Tremblay, Lacourse, Nagin, & Vitaro, 2006;

Nantel-Vivier et al., 2009) by analyzing age-related changes in

prosocial development from adolescence until early adulthood

and its prediction from temperamental effortful control (self-

regulation). Although researchers have identified temperamen-

tal characteristics and related individual differences as factors

that play an important role in childrens PB (Eisenberg et al.,

2006), most of the relevant work has been conducted with

preschoolers and young children, and there is limited research

on how these variables might affect the development of PB

during the transition from early adolescence to early adulthood.

Effortful control (EC) has been defined as the efficiency of

executive attention, including the ability to inhibit a dominant

response and/or to activatea subdominant response,to plan, andto detect errors (Rothbart & Bates, 2006, p. 129). Behaving in

ways that favor others welfare often may require the capacity to

This research was partially supported by grants from the Spencer

Foundation and W.T. Grant Foundation to Albert Bandura, from the Italian

Ministry of Education University and Research (COFIN: 1998, 2000), from

the University of Rome La Sapienza to GianVittorio Caprara; and from

the National Institute of Mental Health to Nancy Eisenberg.

Correspondence should be addressed to Bernadette Paula Luengo

Kanacri, Sapienza University of Rome,Via dei Marsi 78, 00185 Roma (Italy).

Email: [email protected].

Journal of Personality :, 2013

2012 Wiley Periodicals, Inc.

DOI: 10.1111/jopy.12001

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manage ones own and others emotions effectively, to under-

stand others needs, to integrate information and plan, and to

select the proper behavior to alleviate others distress and to

positively impact their welfare. Thus, one would expect adoles-

cents who are able to control their attention and behavior and

handle their emotions to be better equipped to engage in proso-

cial actions as helping, caring, comforting, and sharing. In thisstudy, we examined EC as a predictor of both level of PB at age

13 and change across adolescence into early adulthood.

Developmental Trends in Prosocial

Tendencies from Adolescence to

Early Adulthood

The issue of age-related change in PB has been the focus of

investigation for decades (for reviews, see Eisenberg & Fabes,

1998; Eisenberget al., 2006). Eisenberg andFabes (1998) noted

in a meta-analysis a general increase with age in prosocial

responding, although they found that the pattern was dependent

on the method of assessing PB (i.e., using observation, self-

report and other-report), the design of the studies (e.g.,

correlational/naturalistic, structured/experimental studies), as

well as the target of PB (e.g., peer or adult). They also reviewed

work indicating that age-related changes were related to devel-

opmental processes (i.e., including cognitive, social, motiva-

tional, emotional mechanisms and physical processes).

Comparing children with adolescents in the meta-analysis,

Eisenberg and Fabes (1998) reported that older adolescents

were more likely than younger children to share or donate and

were more likely than preschoolers to share, donate, help, or

console others. When the target of the PB was a child ratherthan an adult, there was an increasing tendency to enact proso-

cial behaviors across adolescence; moreover, sharing/donating

but not instrumental helping increased during adolescence.

Because the development of PB is associated with sociocog-

nitive development, especially the emergence of internalized

moral reasoning and mature perspective taking (Eisenberg

et al., 2006), one might expect an increase in PB over the

course of adolescence. However, the study of age-related

changes of PB across adolescence has been limited and empiri-

cal findings are mixed. Fabes et al. (1999), focusing only on

adolescence and reexamining the aforementioned data in

Eisenberg and Fabess (1998) meta-analysis, found that whenearly and late adolescents were compared, prosocial behavior

did not, in general, increase with age within adolescence.

In a more recent study, Carlo et al. (2007) investigated

stability and change of an overall measure of PB in association

with the quality of parent and peer relationships in rural ado-

lescents. They found a decline in the mean overall level of

self-reported PB across early to middle adolescence and a

slight increase at 12th grade, for both boys and girls. In their

study, gender differences on PB (Eisenberg & Fabes, 1998)

were also corroborated. Girls trajectories in seventh grade

were higher than those of boys and boys PB declined more

rapidly over time than girls did. In contrast, Jacobs, Vernon,

and Eccles (2004), focusing on the relations between group

membership, time use, and the involvement in prosocial

actions, found a significant increase in self-reported PB from

12 to 14 years, as well as from 14 to 16.

Eisenberg, Cumberland, Guthrie, Murphy, and Shepards

(2005) study is, to our knowledge, the only empirical studypublished thus far to examine the development of PB during the

transition from adolescence to early adulthood. These authors

analyzed different related aspects of prosocial functioning in

youth from mid-adolescence (age 1516) to early adulthood

(age 2526). They found that sympathy(i.e.,feelingsof concern

for others based on the comprehension of others emotional

state) did not show a specific pattern of age-related change.

Most important, they obtained a cubic trend for helping behav-

ior, with a general decline fromlate adolescence to theearly20s,

followed by an increase in early adulthood. However, this study

had a small sample that was mostly upper middle-class Euro-

Americans; thus, the findings may not generalize to different

socioeconomic or racial/ethnic groups.

Effortful Control and Prosocial Behavior

Whereas most researchers have traditionally focused on the

situational determinants of PB and the rearing and socializa-

tion practices conducive to PB (Batson, 1998), relatively few

scholars have addressed the role of temperamental factors

associated with PB, especially in childhood or adolescence

(e.g., Graziano & Eisenberg, 1997). Both heredity and social-

ization processes likely contribute to individual differences in

PB, although psychological structures that crystallize over

time appear to produce stable tendencies to feel, think, andbehave prosocially (Caprara, Steca, Vecchio, Tramontano, &

Alessandri, 2008).

Currently, there is a broad consensus in considering EC as

a set of relatively deliberate control functions needed for vol-

untary, goal-directed behavior (Rothbart & Derryberry, 2002).

Thus, EC is related to the ability to modulate both behavior and

emotions, and includes some executive functioning capacities

(i.e., planning, detecting errors, assimilating information, etc.).

As highlighted by Rothbart and Derryberry (2002), the con-

stitutional temperamental basis of EC refers to the relatively

enduring makeup of the organism, influenced over time by

heredity, maturation, and experience. The capabilities that arepart of EC can be viewed as tools for regulation of emotion and

behavior in specific contexts, and EC provides the tempera-

mental bases for self-regulatory processes (Eisenberg & Zhou,

in press).

Individual differences in prosocial behaviors may be favor-

ably affected by the capacity to be self-regulated emotionally

and behaviorally. In fact, the idea that prosociality is partly

influenced by EC is consistent with theoretical arguments

(Rothbart & Rueda, 2005) and with empirical findings (e.g.,

Diener & Kim, 2004; Veenstra et al., 2008). Specifically,

researchers examining PB with others ratings of PB have

Luengo Kanacri, Pastorelli, Eisenberg, et al.2

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found that childrens EC was associated with peers (e.g.,

Eisenberg et al., 1996) or teachers reports (e.g., Diener &

Kim, 2004) of prosocial behaviors. When Veenstra et al.

(2008) used a person-centered approach to study teachers and

parents perceptions of preadolescents prosocial and antiso-

cial behavior, they found that prosocial clusters of preadoles-

cents included individuals with the highest level of EC.Related aspects of prosocial responding, such as empathy,

sympathy, and higher-level moral reasoning, have also been

positively associated with EC (e.g., Eisenberg et al., 2007;

Kochanska, Coy, & Murray, 2001). Eisenberg et al. (1996)

proposed that individuals high in EC tend to experience sym-

pathy (i.e., other-oriented response to anothers emotion or

condition) rather than personal distress (i.e., self-focused,

aversive response to anothers emotional state or condition)

because empathic overarousal is aversive and leads to a self-

focus and self-concern. Considering that EC appears to con-

tribute to the regulation of emotional reactivity, prosociality

would be expected to be more probable if individuals are, for

example, capable of both inhibiting dominant reactive negative

emotional responses and activating subdominant responses

that lead to the care of others. In addition, EC seems to play an

important role in the development of an internalized morality

that is likely to sustain prosocial tendencies (e.g., Kochanska,

Murray, & Coy, 1997). Thus, EC appears to provide the atten-

tional flexibility required to link negative affect, action, and

moral principles (Rothbart & Rueda, 2005).

In summary, the research is consistent with the view that

childrens and adolescents abilities to flexibly regulate their

own behavior and emotions contribute to their social compe-

tence, internalization of moral principles, and sympathy, all

factors that are conducive to PB. However, to our knowledge,no one has examined the relation of EC to individual differ-

ences in the developmental trajectory of PB across adoles-

cence or from adolescence to young adulthood. Thus, there is

a need for longitudinal studies to examine the potential role of

EC in promoting and consolidating individuals tendency to

behave prosocially from adolescence to early adulthood.

The Current Study

To this aim, the present study examined change in self-reported

prosociality across nine years (from age 13 to age 21), positing

EC as a potential factor affecting change in the tendency toenact prosocial behaviors from adolescence to early adulthood.

Taking into consideration the extensive literature that has iden-

tified gender differences in prosocial responding (see Fabes

et al., 1999), and highlighting that such differences are strong

during adolescence (e.g., Carlo et al., 2007; Eisenberg, Carlo,

Murphy, & Van Court, 1995), the relation between EC and PB

was examined separately for males and females. Specifically,

we analyzed the following: (a) change in self-reported prosoci-

ality from adolescence (age 13) to early adulthood (age 21), and

(b) prediction by teacher-rated adolescent EC of the starting

level and the trajectory of prosociality over time.

Based on previous research indicating that PB initially

decreases across adolescence (Carlo et al., 2007; Fabes et al.,

1999) and then, around the age of 1718 or later, increases

(Carlo et al., 2007; Eisenberg et al., 2005), we hypothesized

that the prosociality trajectory from age 13 to 21 would follow

a similar quadratic course, even if the time range was greater

than in prior research. Furthermore, we expected significantinter-individual variability to characterize this trend. In addi-

tion, in accordance with previous studies that have shown

positive associations between EC and childrens PB (e.g.,

Diener & Kim, 2004; Eisenberg et al., 1996), we predicted that

EC, as assessed by teachers reports at the age of 13, would be

related to the initial, concurrent level of prosociality for both

sexes. Furthermore, based on previous studies that have docu-

mented the protective role that EC may exert over time in

regard to socioemotional functioning (Eisenberg et al., 2006;

Verstraeten, Vasey, Raes, & Bijttebier, 2009), we also expected

EC to predict the pattern of change in adolescents prosociality

(specifically, greater increases, or lesser declines, in prosoci-

ality over time).

Method

Sample and Design

The 573 adolescents (276 girls and 297 boys), with a mean age

of 13 (Mage = 12.98, SD = 0.80) at the first assessment and 21(M age = 21.23, SD = 0.67) at the last one, were from a resi-dential community located 30 km from Rome. The community

of Genzano represents a socioeconomic microcosm of the

nations larger society, composed of families of skilled

workers, farmers, professionals, and local merchants and theirservice staff. The occupational socioeconomic distribution of

our sample matched the national profile as reported by the

National Institute of Statistics (ISTAT, 2002) in the years in

which the study was performed. At Time 1, 13% of families

were in professional or managerial ranks, 51% were merchants

or employees in various types of businesses, 11% were skilled

workers, 15% were unskilled workers, 6% were retired, 4%

were temporarily unemployed but with a salary, and 9% were

unemployed. The composition of the families also matched

national data with regard to type of family and number of

children. Most participants were from intact families (90.1%)

and only 5.9% were from single-parent homes (i.e., separatedor divorced). At Time 1, 93.6% of participants attended junior

high school, whereas at Time 8 81.9% attended university.

The present study is part of a larger longitudinal project that

started in 1993 with the primary goal of investigating the

personal and social determinants of children and adolescents

adjustment (Caprara, Pastorelli, Regalia, Scabini, & Bandura,

2005). During the projects first year, all the fourth, fifth, and

sixth graders from one of two large elementary schools in

Genzano were recruited for participation, and an additional

cohort of fourth graders was added from the same school over

the course of the following years. Overall, the project adopted

Prosociality and Effortful Control 3

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a staggered, multiple-cohort design, with four different cohorts

recruited in four consecutive school years, and annual assess-

ments were conducted until 1998. Since then, the project has

been focusing on the transition from adolescence to emerging

adulthood with assessments 2 years apart.

Due to the availability of the effortful control measure start-

ing from the year 1994, three of the four cohorts from the

larger study included that measure. As reported in Table 1,

prosociality was assessed at Time 1 (T1; age 13), Time 2 (T2;

age 14), Time 3 (T3; age 15), Time 4 (T4; age 16), Time 5 (T5;age 17), Time 6 (T6; age 18), Time 7 (T7; age 19), and Time 8

(T8; age 21). Effortful control was assessed at age 13. In this

study, for Cohort 1, there were six assessments, first, annually

from 1994 (age 13) to 1996 (age 15), and, then, biannually

from 1998 (age 17) to 2002 (age 21). For Cohort 2, the assess-

ments were yearly from 1995 (age 13 and 14) to 1996, and

biannually from 1998 to 2000 (T6, age 18, after which these

participants from this cohort were missing by design). For

Cohort 3, there were five assessments, performed biannually

from 1996 (age 13) to 2004 (age 21). No cohort effects were

found for sociodemographic or major study variables, so data

from the three cohorts were combined.

Cohort 1 started with 170 participants at T1 (age 13) andincluded 116 participants at T8 (age 21); Cohort 2 started with

201 adolescents and finished by design at T7 (age 18) with

169; Cohort 3 included 202 adolescents at T1 and finished at

T8 (age 21) with 117 participants Percentages of retained

participants from T1 to T8 were 68% for Cohort 1, 84% for

Cohort 2, and 58% for Cohort 3. Univariate analyses of vari-

ance indicated that there were no significant differences

between the participants who had complete data for the present

study and the ones who dropped out over the years in the

means of demographic characteristics, PB, or EC.

Procedures

From T1 to T6, the study was presented to parents, teachers,

and children as a project designed to gain a better understand-

ing of child and adolescent development. Parents gave their

signed consent and children were free to decline participation

(3% declined). Two researchers administered the scales in the

classroom. The researchers explained that responses to the

questionnaires would be confidential. When necessary, they

offered the children clarifications on the dimensions being

measured. Teachers were asked to complete measures for each

student in their class at T1. Almost all the teachers (97%) of

adolescents agreed to participate in this longitudinal study.

At T7 and T8, when the majority of participants were in

college, they were contacted by phone and invited to partici-

pate in the study for which they received a small payment.

Questionnaires were sent to participants by mail. Question-

naires and consent forms were returned by participants to

researchers during specifically scheduled meetings in a school.

Measures

Prosociality. The tendency to enact prosocial behaviors was

measured with self-reports on three items, unchanged in

wording over time, from the Prosociality Scale for Children

(Caprara & Pastorelli, 1993) and for adolescents and adults

(Caprara, Steca, Zelli, & Capanna, 2005). The scale was devel-

oped in Italy and reflects the three major generative compo-

nents of the tendency to enact prosocial behaviors, that is,

sharing, helping, and caring behaviors (I share the things that

I have with my friends, I try to help others, and I try to

console people who are sad, respectively). From T1 to T3,

participants rated their prosociality on a 3-point Likert scale(from 1 = almost neverto 3 = many times), whereas from T4 toT8 the three items were rated on a 5-point Likert scale (from

1 = never/almost never true to 5 = almost always/always true).Because the prosociality scale for children was rated on a

3-point scale, whereas the scale for adolescents and adults was

rated on a 5-point scale, prosociality scores were adjusted to

have the same range as the other scales prior to forming the

composite score1 (alphas =.72, .71, .80, .76, .79, .81, .73, and.78, respectively, for each time of assessment).

The psychometric properties of the prosociality scale have

been cross-gender and cross-nationally validated on large

samples of respondents (Tramontano et al., 2012). Recentstudies have supported the construct validity of the scale,

showing coherent sets of correlations with agreeableness and

emotional and empathic self-efficacy (Alessandri, Caprara,

Eisenberg, & Steca, 2009). Researchers have also found a

moderately high correlation (r= .54) between self- and other-ratings on this prosociality measure, further supporting its

validity (Caprara et al., 2008).

Effortful Control. In the present study, the construct of EC

included processes related to emotional regulation, as well as

the abilities to voluntarily focus and shift attention, to volun-

Table 1 Multiple-Cohort Longitudinal Design

1994 1995 1996 1998 2000 2002 2004

Cohort 1 Age 13 Age 14 Age 15 Age 17 Age 19 Age 21

Cohort 2 Age 13 Age 14 Age 16 Age 18 Missing by design

Cohort 3 Age 13 Age 15 Age 17 Age 19 Age 21


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tarily inhibit or initiate behaviors such as delaying and plan-

ning (Eisenberg et al., 2007). Specifically, at T1 (age 13), EC

was assessed with teachers ratings (0 = not true to 2 = verytrue or often true) on nine items from the Teacher Report Form

(TRF, Achenbach & Edelbrock, 1986) that were deemed to

reflect EC in the respective subdimensions of attentional

focusing and inhibitory control (e.g., He/she does not finishthings he/she started, he/she also talks when it is not his/her

turn, and his/her demands must be fulfilled immediately,

easily frustrated). The items were reversed as appropriate:

high scores indicated high EC (alpha = .87).A confirmatory factor analysis (CFA) of this set of items

was conducted in order to test one- versus two-factor (i.e.,

attentional focusing and inhibitory control) models for the

structure of EC. Similar to prior research with younger groups

(Sulik et al., 2010), the CFA suggested a better fit to the data

for the monofactorial structure of the scale when compared to

the two-factor solution. The monofactorial solution yielded a

chi-square, c2 (25) = 169.595, p < .001, a comparative fit index(CFI) = .90, and a standardized root mean square residual(RMSEA) = .07; whereas the two-factor solution yielded achi-square, c2 (26) = 209.163, p < .001, a (CFI) = .82, and aRMSEA = .11. Additionally, consistent with prior research(e.g., Roberts, Chernyshenko, Stark, & Goldberg, 2005; Eisen-

berg, Duckworth, Spinrad, & Valiente, in press), in correlations

there was a significant relation of .30 between teacher report of

EC and self-reported conscientiousness (i.e., a personality trait

which has regulation as one of its major components).

Level of Parents Education. Because income and education

are highly correlated (Hauser & Warren, 1997), and following

Sirins suggestions ( 2005), parental education was used as aproxy indicator of socioeconomic status. Participants reported

their mothers and fathers level of education at T1 on a scale

from 1 (elementary school) to 5 (college and post-college

education) and the two scores were averaged.

Missing Data Analysis

Full-information maximum likelihood (FIML) estimation in

Mplus 5.1 was used to handle missing data in our analyses.

This method offers unbiased estimates under ignorable

missing data pattern like missing completely at random

(MCAR) or missing at random (MAR). The pattern of miss-

ingness was tested by using the missing values option in SPSS18. The Little (1988) test for MCAR was statistically signifi-

cant, indicating that the variables in our analysis did not meet

the strict assumption of MCAR. However, by considering the

single t-test produced by the program output, the covariate EC

significantly predicted PB missingness at some time points,

suggesting that at least MAR could be supported (Tabachnick

& Fidell, 2007). Although we cannot exclude the possibility

that our data are not missing at random (MNAR), it must

be noted, as indicated by Baraldi and Enders (2010), that

maximum likelihood estimation relative to other traditional

techniques (e.g., single imputation method) produces less

biased estimates of missing values even when the pattern ofmissingness cannot be ignored as in MNAR.

Results

Preliminary Analyses

Observed means and standard deviations are reported in

Table 2. According to univariate analyses of variance

(ANOVA), there were sex differences in PB favoring girls at all

assessments, Fs(1, 571; 1, 359; 1, 397; 1, 177; 1, 321; 1, 167;

1, 308; 1, 231) = 55.472, 45.430, 45.093, 19.147, 44.696,17.296, 48.523; 28.091, ps < .001, respectively, from T1 to T8.

Thus, consistent with previous research (Carlo et al., 2007;Fabes et al., 1999), we estimated models using a multiple-

group procedure with sex.

When computing zero-order descriptive correlations,

because no significant cohort effects were found and to avoid

Table 2 Descriptive Statistics and Correlations Among Prosociality and Covariates

Variable 1 2 3 4 5 6 7 8 9

1. PB age 13 1

2. PB age 14 .48** 1

3. PB age 1516 .39** .46** 1

4. PB age 1718 .38** .50** .55** 1

5. PB age 19 .32** .47** .44** .58** 1

6. PB age 21 .26** .31** .28** .47** .58** 1

7. LPE T1 .09* .06 -.01 .01 -.06 -.07 1

8. EC T1 .22** .23** .26** .09* .08 .13 .11** 1

9. Gender .30** .33** .34** .33** .37** .33** -.01 -.24** 1

Mean 3.93 3.89 3.70 3.80 3.80 3.92 2.37 0.36

Standard deviation 0.90 0.91 0.81 0.72 0.73 0.70 0.76 0.42

Note. PB = prosociality; LPE = level of parents education; EC = effortful control;T1 = variable assessed at time 1 (age = 13).

*p < .05. **p < .01.


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the problem that at some assessments there were participants

from only one cohort, age 15 data were combined with age 16

data, and age 17 with age 18 data (see Table 2).

Longitudinal Invariance

Change can only be unambiguously interpreted as a reflectionof a developmental process when items do not change conno-

tation or contribution to the construct over time (Obradovic,

Pardini, Long, & Loeber, 2007). According to some scholars,

metric invariance is a prerequisite for analyzing longitudinal

intra-and inter-individual changes (Vandenberg & Lance,

2000). Full metric longitudinal invariance occurs when there is

no significant difference in the c2 value between unconstrained(configural invariance) and constrained (metric invariance)

models (Muthn & Muthn, 2006).

For longitudinal invariance models, the evaluation of the

goodness of fit was based on the Comparative Fit Index (CFI)

values of at least 0.90 (Kline, 2005) and the Root-Mean-Square Error of Approximation (RMSEA) values lower than

0.07 (Browne & Cudeck, 1993) because the significance value

of the chi-square is sensitive to large sample sizes and easily

produces a statistically significant result (Kline, 2005). In

order to analyze longitudinal factorial invariance of the PB

factor structure, we grouped participants at each time by col-

lapsing them into four different age groups, i.e., Group 1 (age

1314), Group 2 (age 1516), Group 3 (age 1718), and Group

4 (age 1921), aggregating the different developmental phases

in only four representative stages.

The analysis of full configural invariance (i.e., same factor

structure across groups for the measure of prosocial behavior)

had a good fit, c2 (n = 573; df= 30) = 44.291, p = .041, CFI=.99, RMSEA =.030. Further, the c2 difference test supportedthe full metric longitudinal invariance (i.e., same pattern of

factor loadings across groups), c2 (n = 573; df= 36) = 46.544,p = .11, CFI =.99, RMSEA =.024, Dc2 (6) = 2.253, p = .813.

Models for Assessing Longitudinal Change in

PB and Its Prediction from EC

To study the longitudinal relations across different phases of

individuals prosociality development, a latent growth curve

(LGC) model was used to assess inter-individual differences inintra-individual change over time (Curran, Obeidat, &

Losardo, 2010). The LGC model included three latent factors

for which variances were decomposed: an intercept, a slope,

and a quadratic term. The intercept represents the initial level,

whereas the slope represents the rate of change (i.e., linear or

nonlinear), and the quadratic component corresponds to the

simple curvature or rate of acceleration/deceleration over time

in the linear slope. To identify the optimal functional form of

growth for the outcome data (i.e., prosociality), we first fit a

series of unconditional growth curve models. Simultaneously,

these models allowed the establishment of a baseline model for

moving to conditional growth models that examined the effects

of two predictors (i.e., EC and the level of parents education)

on variability in the initial level and rates of change of proso-

ciality. As suggested by Muthn (2004), PB was centered at the

beginning of the curve to reduce multicollinearity that occurs

between the linear and quadratic effects.

Models were tested separately for males and females usinga multiple-group approach from a SEM framework (Curran,

2000). In both conditional and unconditional structural

models, the equivalence between both groups was evaluated by

including constraints imposing identical unstandardized esti-

mates for the models parameters across the sexes; the plausi-

bility of these equality constraints was examined with the c2

difference test between nested models (i.e., constrained vs. the

baseline unconstrained models), in which the invariance across

sex can be supported if the equality constraints produce a

nonsignificant increase of the chi-square. Modification indices

were also used to assess the equality of the constraints across

sexes. For the unconditional models, we first examined a

no-growth model (intercept only) and then a linear model

representing a constant change over time (factor loadings were

fixed to 0, 1, 2, 3, 4, 5, 6, and 8). Finally, we examined a

quadratic growth to better test the form of the curve or its

acceleration over time (factor loadings were fixed to 0, 1, 4, 9,

16, 25, 36, and 64). For unconditional and conditional growth

models the evaluation of the goodness of fit was based on CFI

values of at least 0.90 (Kline, 2005) and RMSEA values lower

than 0.07 (Browne & Cudeck, 1993). Because all these models

are nested, we performed a chi-square difference test (Dc2) tocompare them (Kline, 2005).

The Developmental Trajectory of prosociality. The initialno-growth model (with the intercept factor only) had a very

poor fit (see Table 3). The linear model (with intercept and

slope factors) fit better, c2 (46) = 97.800, p < .001; CFI = .89;and RMSEA = .063. The more complex model with aquadratic term fit even better than the linear model, c2

(38) = 51.188, p = .074; CFI = .97; and RMSEA = .035, andthe c2 difference test comparing linear and quadratic modelsupported the need for this latent factor, Dc2 (8) = 46.612,

p < .001. Regarding the multiple-group analysis across gender

the difference in the chi-square statistic, comparing the con-

strained model (c2 (52) = 102.207, p < .001) with the uncon-

Table 3 Fit Indices for Unconditional Prosociality Growth Models

Model c2 df CFI RMSEA c2 diff df diff

Intercept only 135.408 52 .61 .075

Lineara 97.800 46 .89 .063 37.608 6

Quadraticb 51.190 38 .97 .035 46.612 8

Note: RMSEA = root mean square error of approximation.aComparison for the chi-square difference test is between intercept and linear

models.bComparison is between linear and quadratic models.


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strained one (c2 (38) = 51.188, p = .0101), was significant(Dc2(14) = 51.019, p < .001), suggesting that equality of allparameters did not hold across gender. This inequality is con-

sidered in depth in the conditional model.

The significant mean of the intercept of prosociality for

both males and females, ts(296; 275) = 3.64 and 4.20,

ps < .001, respectively, indicated that both groups reported apositive average starting point different than zero at age 13,

and the significant variance of the intercept indicates inter-

individual variability around this mean for both males and

females, ts(296;275) = .38 and .27, ps < .001. The mean ofthe slope was negative for both males and females, ts(296;

275) = - 0.07 and - 0.082, ps < .006 and .001, respectively,showing a tendency for prosociality to decline in a linear

fashion across time. The variance of the linear slope was sig-

nificant for both males and females, t(296; 275) = .042 and.032, ps = .028 and .012, indicating inter-individual variabilityin growth over time. The mean quadratic slope was positive for

males and females, ts(296; 275) = .009 and .009, ps = .004 and.001, respectively, reflecting a modest decrease in the first part

of the curve (age 1317) and a further slight increase in its

second part (age 1721). The unconditional growth trajectory

explained a moderate to high proportion of the variance in the

time-specific indicator of prosocial behavior at age 13, 14, 15,

16, 17, 18, 19, and 21 (44%, 44%, 46%, 56%, 67%, 52%, 51%,

and 63%, respectively, for males, and 42%, 35%, 33%, 53%,

55%, 59%, 56%, and 95%, for females).

Effortful Control as a Predictor of the Development of

Prosociality OverTime. We computed a multigroup analysis

across sex in which we included EC as a predictor of the

tendency to enact prosocial behaviors, considering also in themodel the potential effect of the level of parents education. The

difference in the chi-square statistic between the constrained

model, c2(78) = 146.641, p < .001, and the unconstrained one,c2(58) = 86.312, p = .010, was significant, Dc2(20) = 60.331,

p < .001, suggesting that equality of all parameters did not hold

across sex. In a partially constrained model, also following

modification indices, we found that if the equality constraints

were lifted from the paths from the level of parents education

and EC to the quadratic latent factor, as well as from the

correlation between the level of parents education and EC, the

mean change in overall chi-square between the unconstrained

model and the partially constrained model was no longer sig-nificant, Dc2(8) = 14.816, p = .063. The conditional LGCmodel fit the data adequately, c2 (70) = 131.825, p < .001;RMSEA = .05; CFI = .90. In regard to differences across bothgroups,our results showed that the correlation between the level

of parents education and EC was significant only for females.

In addition, the paths from the level of parents education and

EC to the latent quadratic factor were different for males and

females, albeit not significant in either case; see Figure 1 for the

conditional trend of prosociality.

For both males and females, EC was significantly and posi-

tively related to the initial level of prosociality at age 13,

bs = .38 (.083), p < .001; and significantly and negatively pre-dicted the linear decline in prosociality for both males and

females, bs = -.11 (.048), ps = .038, whereas the level ofparents education was not significantly related to the inter-

cept, the linear and the quadratic factors for either males and

females (see Figure 2). These findings suggest that EC was

associated, for both sexes, with both high initial status of

prosociality at age 13 and with less of a linear change (typi-

cally decline) in the tendency to enact prosocial behaviors.

Overall, for females, the percentage of variance explained in

the model was 10% for the intercept, 7% for the slope, and 4%

for the quadratic trend; for males, the analogous percentages of

variance explained were 14%, 7%, and 1%.

Discussion

To our knowledge, this is the first study either to use LGC

models to examine age-related change in overall prosociality

across the transition from adolescence to young adulthood or

to examine the prediction by EC of individual differences in

trajectories of the tendency to enact prosocial behaviors. Ourresults corroborate some previous findings, showing an initial

decline in prosociality from age 13 to 17 (Carlo et al., 2007;

Fabes et al., 1999), and a subsequent increase until age 21

(Eisenberg et al., 2005). These findings are also in line with

research that has shown an increasing path in self-focused

modes of prosocial moral reasoning from early to middle

adolescence, as well as with the generally increase in

self-reflective and empathic reasoning modes of prosocial

moral judgment from late adolescence into the early adulthood

(Eisenberg et al., 2005). In addition, as has been found by

others (Kokko et al. 2006, Nantel-Vivier et al., 2009), our

3,00

3,20

3,40

3,60

3,80

4,00

4,20

4,40

13 14 15 16 17 18 19 21

AGE

PB

MALES FEMALES

Figure 1 Prosociality development from age 13 to age 21 (conditionalgrowth model).Note. PB = Prosociality.


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results suggest the existence of diverse groups that vary in theirdifferent developmental trajectories.

Consistent with other studies (e.g., Diener & Kim, 2004;

Eisenberg et al., 1996; Veenstra et al., 2008), for both sexes,

EC at age 13 predicted a greater tendency to enact prosocial

behaviors concurrently. Furthermore, EC seemed to counteract

the typical decline of prosociality from age 13 to age 17 for

both males and females. These results point to the potential

role of EC in the development of prosociality, especially

during adolescence. EC appears to be a predictor differentiat-

ing those youth who behave relatively prosocially in the

coming years from those who are less prosocial, even when a

contextual variable, such as the level of parents education,was taken into account. Being able to regulate ones own

emotions and behaviors in early adolescence not only may

affect the tendency to behave prosocially, but also may counter

the self-centered tendencies observed across this phase of

development. It seems likely that being sensitive to others

requires a strong capacity to effortfully regulate negative reac-

tions such as sadness or anger, to delay gratification, to hold

ones personal needs in abeyance, and to plan and activate a

course of action that benefits others.

Even though EC is believed to have a genetic and constitu-

tional basis (Goldsmith, Pollak, & Davidson, 2008), most theo-

rists argue that this self-regulative dimension of temperamentis shaped by experience in the social world (Gottman, Katz, &

Hooven, 1997; Rothbart & Rueda, 2005). Thus, individual

differences in enacting PBs could be partly explained by

opportunities to practice, maintain, and improve adolescents

tendencies to effortfully self-regulate their own emotions and

conducts. Because the neural regions underlying EC are still

developing in adolescence (Casey, Giedd, & Thomas, 2000),

and the peer context especially in this phase may offer oppor-

tunities to master prosocial experiences (Youniss, McLellan, &

Mazer, 2001), adolescence should be considered a critical

period for the development of prosociality.

Although not the primary focus of our paper, sex differ-ences in our study confirmed those from other research (e.g.,

Carlo et al., 2007; see also Fabes et al., 1999). The higher level

of reported prosociality in females from adolescence until

early adulthood probably is related with gender stereotypes

(Fabes et al., 1999; Hill & Lynch, 1983). Males are more likely

prone to inhibit their caring and not enact helping or sharing

behaviors across adolescence. Similar results regarding sex

have been found in studies examining agreeableness, a con-

struct quite related to prosociality, with males being less agree-

able than girls across adolescence (e.g., Branje, Van Lieshout,

& Gerris, 2007; Klimstra, Hale, Raaijmakers, Branje, &

PBPB

Age13

EFFORTFUL CONTROLEFFORTFUL CONTROL

Teacher reportedTeacher reported

Age 13Age 13

PBPBInterceptIntercept

PBPB

SlopeSlope

PBPBQuadraticQuadratic

ComponentComponent

PBPB

Age 14

-.08*(-.08*).38***(.3

8***)

PBPB

Age 15

PBPB

Age 16

PBPB

Age 17

PBPB

Age 18

PBPB

Age 19

PBPB

Age 21

LEVEL OFLEVEL OF

PARENTPARENT

EDUCATIONEDUCATION

.03 (.05*)

Figure 2 Significant paths between effortful control and prosociality.Note. PB = prosocial behavior; the first coefficient is for males, the second coefficient (in parentheses) is for females.*p < .05. **p < .01. ***p < .001.


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Meeus, 2009; McCrae et al., 2002). However, in those studies,

the linear trend of agreeableness, especially for girls, increased

over the course of adolescence (Branje et al., 2007), and thus

appears to be somewhat different from the quadratic trend

shown by prosociality. These differences are possibly due to

the larger age span (until young adulthood) considered in the

present study and/or to the specificity of the construct of proso-ciality as compared to the broader trait of agreeableness, which

also includes facets of compliance and politeness.

Methodological strengths of this study include the use of

multiple reporters and longitudinal data over 9 years, as well as

the use of a sample outside of North America. Limitations

include the use of a self-report measure of prosociality might

be considered a potential disadvantage. However, in line with

Nantel-Vivier et al.s (2009) arguments, prosocial behaviors

may become more private over time and self-reports are likely

a key source of information, especially after childhood. One

can argue that people are in the best situation to know and

subsequently to report on their own tendencies to act proso-

cially. Further, the high correlations found in other studies

between self-reports and others reports of PB (e.g., Caprara

et al., 2008; Nantel-Vivier et al., 2009) provide some evidence

regarding the validity of self-report prosocial measures. Thus,

we believe that self-reported prosociality is a measure that

should be neither overestimated nor underestimated. In addi-

tion, we had only one index of EC, although teacher-reported

EC generally correlates with parental reports and behavioral

indices of EC (e.g., Sulik et al., 2010). It is also possible that

the findings in an Italian sample do not generalize to other

cultural groups. We acknowledge that another possible limita-

tion of the current study is the scaling of our PB measure that

was not initially identical at the different assessments points.However, we believe the method used to convert the scale

addressed this potential limitation.

Studies of antisocial and other disturbing behaviors have

traditionally outnumbered studies of prosocial behaviors, but

understanding the origins and the determinants of prosocial

behaviors appears to be crucial in guiding interventions. Our

findings suggest that adolescence could be an appropriate

phase to strengthen prosocial behavior, to counter its decline,

and to set the basis for the subsequent successful youth devel-

opment. The rapid social changes that occur in adolescence

may exacerbate youths individualistic identities and, as a con-

sequence, societal efforts may be needed to promote sharedgoals, harmonious relationships, and a more prosocial orien-

tation. Thus, interventions in high schools that promote strat-

egies of self-regulation could have beneficial secondary effects

on adolescents prosocial tendencies.

Note

1. In order to compare means across time, we converted PB at ages

13, 14, and 15 (from a 3-point scale) to the same range for the

response scale of PB at age 16, 17, 18, 19, and 21 (to a 5-point scale).

First we shifted participants responses on the 3-point scale down so

the lowest category was zero (so the scale was 0 to 2 instead of 1 to3)

and then we multiplied scores by 2 (i.e., a number that made the

highest score value one less than the desired maximum score of 5).

Finally, we shifted the scale up by adding 1.0 to each score.

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