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Applied Developmental Science
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The Interest-Driven Pursuits of 15 Year Olds: “Sparks”
and Their Association With Caring Relationships and
Developmental Outcomes
Adar Ben-Eliyahu a , Jean E. Rhodes a & Peter Scales b
a University of Massachusetts Boston
b Search Institute
Published online: 22 Apr 2014.
To cite this article: Adar Ben-Eliyahu , Jean E. Rhodes & Peter Scales (2014) The Interest-Driven Pursuits of 15 Year Olds:
“Sparks” and Their Association With Caring Relationships and Developmental Outcomes, Applied Developmental Science, 18:2,
76-89, DOI: 10.1080/10888691.2014.894414
To link to this article: http://dx.doi.org/10.1080/10888691.2014.894414
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The Interest-Driven Pursuits of 15 Year Olds: ‘‘Sparks’’
and Their Association With Caring Relationships and
Developmental Outcomes
Adar Ben-Eliyahu and Jean E. Rhodes
University of Massachusetts Boston
Peter Scales
Search Institute
In this study, we examined the characteristics of adolescents’ deep interests or ‘‘sparks,’’
the role of relationships in supporting the development of sparks, and whether having a
spark was associated with positive developmental outcomes. Participants included 1,860
15 years olds from across the United States who participated in the national Teen Voice
survey (56% European American, N¼1,860). Profile-centered analyses suggested that
sparks are characterized by the intensity of positive feelings, immersion, and utility.
The strongest sparks were associated with pursuits requiring more interpersonal engage-
ment, such as sports, drama and dance, participating in politics, and serving others.
Spark intensity was related to better social, academic, and affective outcomes. Addition-
ally, youth with stronger sparks reported more encouragement, financial support, and
transportation to spark activities from parents, mentors, extended-family, neighbors,
school-based adults, and peers. Benefits of adolescents’ engagement in interest-driven
activities and the role of caring relationships in supporting such interests are highlighted.
A growing body of literature suggests that engagement
in satisfying and optimally challenging interest-driven
activities can provide individuals with an enhanced sense
of well-being and happiness (Blomfield & Barber, 2011;
Seligman & Csikszentmihalyi, 2000; Fredricks & Eccles,
2006; Larson, 2011; Seligman, 2002; Vallerand et al.,
2003). Within this context, researchers have explored
how immersion in such activities can generate a range
of positive experiences including ‘‘flow’’ experiences
(Abuhamdeh & Csikszentmihalyi, 2012a, 2012b), char-
acterized by deep concentration, sharp focus, and, para-
doxically, deep relaxation. The experience of flow can be
so engrossing and exhilarating that it becomes its own
reward, a vital source of happiness, and a driving force
of achievement in life (Csikszentmihalyi, 1990). Others
have focused on the value that activities have for youth
(Eccles, 2005; Eccles et al., 1983), with a specific focus
on the utility or usefulness that certain subjects or activi-
ties have for longer term goals such as career aspirations
(Durik, Vida, & Eccles, 2006). At the core of both of
these approaches are the inherently adaptive and posi-
tive forms of psychological processes that motivate
learning. Drawing from this work, researchers from
within the positive youth development (PYD) frame-
work (Lerner, Lerner, & Benson, 2011; Schwartz,
Pantin, Coatsworth, & Szapocznik, 2007) have explored
the developmental benefits of youth’s engagement in
intense interests or ‘‘sparks’’ (Benson & Scales, 2009).
Scales, Benson, and Roehlkepartain (2011) character-
ized a spark as a ‘‘passion for a self-identified interest,
skill or capacity that metaphorically lights a fire in the
adolescents’ life, providing energy, joy, purpose and
direction’’ (p. 264). Drawing from a large, national
dataset, Scales et al. (2011) found that a range of factors,
including sparks, relational opportunities, and a sense of
empowerment were associated with better academic,
Address correspondence to Jean E. Rhodes, Department of
Psychology, University of Massachusetts Boston, Boston, MA
02125. E-mail: jean.rhodes@umb.edu
APPLIED DEVELOPMENTAL SCIENCE, 18(2), 76–89, 2014
Copyright #Taylor & Francis Group, LLC
ISSN: 1088-8691 print=1532-480X online
DOI: 10.1080/10888691.2014.894414
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psychological, social, and behavioral well-being for
adolescents.
In the current study, we build on these findings to
explore sparks in greater depth. Because we were parti-
cularly interested in pursuits that were indicative of
the kind of engagement that characterize flow states
(Abuhamdeh & Csikszentmihalyi, 2012a, 2012b) and
value (Eccles, 2005), we sought to decipher subgroups
of adolescents on the basis of their investment in their
sparks. We applied an ecological assets model perspec-
tive (Bowers et al., 2011; E. Bronfenbrenner, 1977;
U. Bronfenbrenner, 1965; U. Bronfenbrenner & Ceci,
1994) to explore the role of parents, teachers, mentors,
other caring adults, and peers that support the develop-
ment of these intensive interests.
Background
Researchers generally define interests as a person’s
‘‘long-term relationship with a specific domain, charac-
terized by positive feelings, higher values, and deeper
knowledge that displays itself in the tendency to reengage
voluntarily in interactions over time’’ (Hofer, 2010, p.
152). Certain criteria are included when determining
whether a domain is of particular interest and in calibrat-
ing that interest. These include the extent to which
interests are self-initiated, meaningful (i.e., providing
emotions of social relatedness, competence, and plea-
santness), novel, challenging, and valued highly as a
means of contributing to a goal or ideal self (Hofer,
2010; Krapp, 2005; Krapp, Hidi, & Renninger, 1992;
Larson, 2011; Renninger & Hidi, 2011). Along these
lines, Markus and Nurius (1986) have referred to
possible selves as an individual’s ideas of what they
might become, what they would like to become, and
what they fear becoming. The concept of possible self
is particularly relevant to understanding the develop-
ment of interests because such visions are the moti-
vational link between the present and imagined future
and can facilitate self-regulation, steering behavior
toward attainment of goals (Hofer, 2010; Oyserman,
Bybee, Terry, & Hart-Johnson, 2004).
Of course, conceptualizing one’s possible self and,
more generally, moving from exploration to actual
interests depends, at least in part, on a young person’s
capacity for conscious self-awareness. The move toward
a defined interest enables one to determine whether a
given interest domain fits with conceptions of the self,
and to evaluate whether his or her experiences within that
domain are characterized by the aforementioned criteria
(i.e., self-initiation, challenge, relatedness, novelty, posi-
tive feelings, and values) (Oyserman et al., 2004). As
such, engagement and interest development may be parti-
cularly important in the middle adolescent years, as indi-
viduals become more focused on identity development,
more adept at abstract, complex, relativistic, and
hypothetical thinking, and better able to evaluate interest
domains in terms of their alignment with notions of
possible selves (Larson, 2011; Pintrich & Zusho, 2002).
Moreover, it is during this period that adolescents begin
high school, gain greater autonomy from their parents,
and begin to grapple with questions of identity and pur-
pose (Collins & Steinberg 2006; Erikson, 1968; Damon,
Menon, & Bronk, 2003). By high school, adolescents
have generally been through significant physical changes,
including puberty, and are increasingly challenged with
making decisions regarding high-risk behaviors, such as
sexual activity, violence, and alcohol, tobacco, and other
drug use. Even though adolescents have an increased
capacity for self-regulation (Pintrich & Zusho, 2002),
their behaviors are strongly influenced by their peers.
Consequently, they are more prone to participate in
‘‘sensation seeking’’ activities such as drug use (Romer,
Duckworth, Sznitman, & Park, 2010). Engagement in
interest-driven activities can serve to offset such influ-
ences, leading adolescents to defer gratification by focus-
ing on activities that lead to skill development (Diener,
Emmons, Larsen, & Griffin, 1985; Lerner et al., 2011;
Seligman & Royzman, 2003). Similarly, Romer et al.
(2010) found that having a longer-term perspective was
positively associated with the ability to delay gratification.
Consequently, a deep level of engagement in interest-
driven activities has been associated with the avoidance
of risk as well as a range of developmental benefits
(Diener et al., 1985; Lerner et al., 2011; Romer et al.,
2010; Seligman & Royzman, 2003; Vallerand et al.,
2003) across school and non-school contexts (Dawes &
Larson, 2011; Eccles & Wigfield, 2002). Scales et al.
(2011) proposed that having a spark energizes an individ-
ual and leads towards general growth and development.
This energizing can be considered in the context of
Fredrickson’s broaden-and-build theory (Fredrickson,
2001), according to which positive emotions such as
interest and flow, broaden individual’s thought-action
repertoires by creating an urge to play, explore, take in
new information and experiences, and expand the self
in the process. In this way, having a spark not only
creates a positive experience within a specific domain,
but the positive valence can generalize, leading to general
growth and development. Additionally, learning and
developing a certain talent might teach individuals to
broaden their valuing of learning and developing in gen-
eral, thereby adopting mastery goal orientations (Dweck
& Legget, 1988). This line of work challenges the notion
that positive emotions signal to the individual that every-
thing is good and that one can stop exerting effort
(Carver, Lawrence, & Scheier, 1996), but rather posits
that the positive emotions that accrue from pursuing one’s
deep interests with tenacity and becoming more adept
continue to promote individual striving toward additional
INTEREST-DRIVEN PURSUITS OF 15 YEAR OLDS 77
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goals and mastery (Seligman & Csikszentmihalyi, 2000;
Lerner et al., 2011; Seligman & Royzman, 2003). As such,
youth with deep interests are likely to be more engaged
and invigorated, not just in their sparks activities, but in
their schools and communities, resulting in higher grades,
attendance, and a mastery focus in school (Vallerand
et al., 2003).
Of course, decisions to engage in certain behaviors or
interest areas cannot be understood purely in terms of
cognitive and motivational processes. Indeed, adoles-
cents’ capacity to pursue their interests is often con-
ditioned by the investment of their families, schools,
peer groups, and communities in supporting these pur-
suits (U. Bronfenbrenner & Ceci, 1994; Buday, Stake, &
Peterson, 2012; Lerner et al., 2011; Simpkins, Fredricks,
& Eccles, 2012). Learning and mastering interest-related
skills can require a considerable financial and time com-
mitment, and youth’s access to people who are willing
to make such investments can affect their progression
from nascent interests to deep passions. Moreover, many
creative interests are not well supported in schools, heigh-
tening the need for more private investments in skills
development. Such resources are not equally distributed
across individuals and settings, as they depend on the
resources and nature of the organizations in which
youth participate and the quality and availability of
youth’s relationships with parents, peers, and extended
network of supports and settings (Bowers et al., 2011;
U. Bronfenbrenner & Ceci, 1994; Buday et al., 2012;
Cairns, Elder, & Costello, 1996; Lerner et al., 2011).
At the most basic level, youth with access to caring
adults who expose them to athletic programs, museums,
zoos, music, theater, and libraries are more likely to dev-
elop interests in these domains. Moreover, when youth
have access to rich, socially interactive learning environ-
ments that stretch them to higher levels of achievement,
cognitive growth is facilitated (Rhodes, 2005; Rogoff,
1990; Vygotsky, 1978). For example, Scales, Benson,
and Mannes (2006) reported that young people with
more exposure to developmental relationships through
participation in youth programs, religious activities,
and community service in middle school, not only had
more frequent interaction with non-familial adults but
also qualitatively different interactions. These interac-
tions were often characterized by meaningful intergenera-
tional conversations where adult values areexpressed and
youth opinions are solicited and considered.
To explore adolescents’ interests, we thus considered
these broader social-cultural contextual influences,
focusing on the support provided by parents, extended
family, adults at school, neighbors, friends, mentors,
and other caring persons. In doing so, we offer a comp-
lementary perspective to the more individualistic
emphasis on emotional regulation or individual ‘‘grit,’’
in accounting for adolescents’ capacity to develop
expertise and engage in interest-driven learning
(Tough, 2012).
STUDY HYPOTHESES AND FOCUS
The current study was somewhat exploratory in that we
examined how the emerging construct of deep interests
or ‘‘sparks’’ is related to a variety of social, emotional,
and academic outcomes and demographic characteristics
in a sample of young adolescents. Within this context, we
applied an ecological assets perspective to determine how
relationships support the development of deep interests.
Although previous researchers have considered sparks as
either present or absent (e.g., Scales et al., 2011), youth’s
interests and passions are likely to fall on a continuum.
As a first step, we sought to empirically delineate how
components of sparks combine using person-centered
analyses (Magnusson, 2003; Muthe
´n & Muthe
´n, 2010),
which allow examination of the varying combinations
of the subcomponents of spark under the assumption
that their combination yields a holistic construct that
cannot be decomposed. Given the situated nature of
engagement in interests, we also sought to investigate
how emotional and instrumental supports were related
to sparks.
Finally, we investigated how sparks were related to a
range of outcomes amongst 15 year olds. We proposed
that adolescents with deeper interests would have more
support for these interests, and that having deep,
impassioned interests would be associated with impor-
tant outcomes across the social, academic, and affective
domains. We were also interested in hours per week
spent online. Recent research points to both creative
and skill building use of online digital media (Ito et al.,
2013) as well as passive online use such as watching
YouTube videos and social networking (Lenhart,
Purcell, Smith, & Zickuhr, 2010). Thus, we were inter-
ested in whether online use would be related to certain
forms of activities over others, especially because the
passive popular online engagement was recently found
to be associated with negative social comparisons (Pantic
et al., 2012; Whitehill, Brockman, & Moreno, 2013).
METHOD
Participants
Participants included 1,860, 15 years olds from across the
United States who were participating in the Teen Voice
study (Scales et al., 2011). About half identified as male
(49.5%), and 1,035 (55.6%) identified as White, 339
(18.2%) as Hispanic, 278 (14.9%) as Black=African
American, 82 (4.4%) as mixed race, 77 (4.2%) as Asian
78 BEN-ELIYAHU ET AL.
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or Pacific Islander, 10 (0.5%) as some other race or
ethnicity, and 30 (1.6%) did not identify a racial or ethnic
group. The youth represented a range of socioeconomic
statuses, as measured by parents’ highest education level,
with 172 (9.3%) not having completed high school, 992
(53.4%) having completed high school but not college,
406 (21.8%) having completed college, and 239 (12.8%)
having completed graduate school.
Procedure
Participants were recruited through the Harris Poll
Online, which includes millions of people who have
agreed to participate in Harris Interactive surveys. Cri-
teria for participation in the study included being 15
years old and a U.S. resident. Password protected email
invitations were sent to thousands of individuals ident-
ified either as U.S. residents and 15 years old, or U.S.
residents and 18 years olds with a 15-year-old child in
the household. Reminder invitations were sent two days
after the initial email to those who had not yet completed
the survey. Participants received points in a rewards pro-
gram and were offered entry in a sweepstakes drawing
for completing surveys. This recruitment process resulted
in 1,860 participants completing surveys between
October 12 and November 9, 2009. Online surveys were
self-administered, and participants took an average of 20
minutes to complete the surveys.
Measures
Below we provide details regarding the study measures.
Some of the scales are single indicators, whereas others
were the simple mean of the scale items as described in
the following section.
Participant Characteristics
Demographic characteristics. Participants reported
demographic characteristics including gender, race,
and parents’ highest level of education by choosing from
multiple choices presented in each question separately.
Spark. Youth were asked about their talents, inter-
ests, and hobbies. To determine whether they had a
talent, interest, or hobby that met the criteria for being
named a ‘‘spark,’’ a follow-up question taken from the
Search Institute Thriving Orientation Survey (TOS;
Benson & Scales, 2009) was asked that included a
description of the criteria of sparks: ‘‘When people are
really happy, energized, and passionate about their
talents, interests, or hobbies, we say they have a ‘spark’
in their life. This spark is more than just interesting or
fun for them. They are passionate about it. It gives them
joy and energy. It is a really important part of their life
that gives them real purpose, direction, or focus. Do
you have this kind of spark in your life?’’ Respondents
could answer with yes, not sure, or no. Respondents
who answered ‘‘not sure’’ and ‘‘no’’ were included in
the ‘‘No Spark’’ group.
Those who answered ‘‘yes’’ were counted as having a
spark and were asked to respond to an additional 7 items
about their main spark. Three items tapped into the flow
component of spark: Youth were asked, when they were
engaged with their primary spark how much did they
(1) ‘‘feel joy or energy;’’ (2) ‘‘lose track of time;’’ and
(3) ‘‘feel a sense of purpose or focus.’’ Four additional
items tapped into components of spark value: Youth
were asked, how much has pursuing their spark (4)
‘‘Given me skills that will help me in a job or career;’’
(5) ‘‘Helped me get along with other people;’’ (6) ‘‘Given
me chances to improve my family, school, or com-
munity;’’ and (7) ‘‘Encouraged me to learn new or extra
things outside of the schoolwork I have’’ (1 ¼not at all,
2¼some,3¼a lot,4¼a great deal).
Social, Academic, and Affective Outcomes
Social behaviors. Four forms of social behaviors
were examined as outcomes of spark. Leadership and
vandalism each were taken from the Search Institute
A&B survey (Scales et al., 2011). They were measured
with single items on a 5-point scale from 1 ¼never to 5 ¼
5 or more times, asking, respectively, how many times in
the last year youth had been a leader in a group or organi-
zation, and how many times in the last year they had
damaged property just for fun (such as breaking windows,
scratching a car, putting paint on walls, etc.). Social good
contribution was measured using a single item taken from
the National Promises Study (Scales et al., 2008), asking
youth how many hours in an average week, including
weekends, they spend doing ‘‘volunteer work to help
other people or to help make your community a better
place.’’ There were four response options for this ques-
tion: none (scored as 1), up to 2 hours, 2 to 5 hours, more
than 5 hours (scored as 4). Civic engagement (Cronbach’s
alpha ¼.86) was measured using six items from the
Monitoring the Future study (Johnston, Bachman, &
O’Malley, 2006), which asked youth how important it
was to them to improve race relations or help people
who were economically disadvantaged. This was a
4-point response scale (1 ¼not important,2¼somewhat
important,3¼quite important,4¼extremely important).
Finally, youth were asked to estimate the amount of hours
they spend online per week.
Academic outcomes. Four academic related out-
comes were examined.
Mastery goals (Cronbach’s alpha ¼.80) was a 3-item
scale adapted from Anderman, Urdan, and Roeser
INTEREST-DRIVEN PURSUITS OF 15 YEAR OLDS 79
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(2005), asking how much statements like this described
the youth: ‘‘One of my goals in school is to learn as much
as I can.’’ Response choices were from 1 ¼does not
describe me at all to 4 ¼describes me a lot.Attendance
was a single item taken from the Search Institute A&B
survey (Benson, Leffert, Scales, & Blythe, 1998) asking
how many days of school a youth skipped class in the last
4 weeks. To calculate grade point average (GPA), youth
were asked in how many classes ‘‘in your most recent
school marking period’’ they received grades of A, B, C,
D, or below D. Four points were awarded for As, 3 for
Bs, and so on, and GPA was calculated as the mean grade
for the total number of classes. (The number of classes
taken was controlled for in these calculations, so that
small numbers of classes did not artificially inflate a stu-
dent’s GPA.) School effort was a single item from the
National Promises Study (Scales et al., 2008) asking
how often the respondent works up to his or her ability
in school, on a 4-point scale from 1 ¼never to 4 ¼very
often.
Affective outcomes. Three indicators of well-being
were used to examine how having strong passions and
interests about something influences general well-being.
Sense of purpose was comprised of five items (Cronbach’s
alpha ¼.76) taken from the Search Institute TOS
(Benson & Scales, 2009), which incorporated conceptual
aspects of purpose described in Damon et al. (2003). Four
items were on a 4-point scale from 1 ¼strongly disagree to
4¼strongly agree (e.g., I feel hopeful when I think about
my future) and a fifth item ‘‘Finding purpose and mean-
ing in my life ...’’ on a four-point scale from 1 ¼not at all
important to 4 ¼extremely important.Positive future out-
look was one item taken from the Search Institute TOS
(Benson & Scales, 2009) asking ‘‘How certain are you
that you will have a good life when you are an adult?’’
Participants could choose one of five answer options
from 1 ¼not at all certain to 5 ¼extremely certain.Wor-
ries (Cronbach alpha ¼.79) was a modified version of five
items asking about possible worries or concerns, taken
from the Washington Post=Kaiser Family Foundation=
Harvard University African-American Men Study
(Washington Post=Kaiser Family Foundation=Harvard
University, 2006). For example, how worried are you
‘‘about doing poorly in school.’’ These items had a
four-point answer scale from 1 ¼very worried to 4 ¼not
at all worried.
Relationships Supporting Youth Sparks
To investigate relationships supporting sparks, parti-
cipants were asked about the extent to which different
people in their lives provided encouragement, financial
help, and transportation to spark-related activities.
Three separate questions were asked, each followed by
the list of people. Participants were asked to respond
using a 4-point scale (1 ¼never,2¼once in a while,
3¼sometimes,4¼often). ‘‘How often do the following
people help you develop your main spark by giving
you encouragement or support, or by pushing you to
get better at those talents, interests, or hobbies?’’ was
used to assess Encouragement or emotional support.
‘‘How often do the following people help you develop
your main spark by providing money or financial help?’’
was used to assess Funding assistance. And ‘‘How often
do the following people help you develop your main
spark by providing transportation?’’ was used to assess
help with Transportation. Participants were asked to rate
how often each of the following people provide such
assistance: your parents (Parents); your grandparent=s
or other family members (Extended family); your
neighbors (Neighbors); your friends (Friends); teachers,
counselors, or other adults at your school (School); your
mentor (Mentor); A coach or other adult in a youth
organization or after-school program (Adult).
Analysis Plan
The analysis plan aligned with our three research ques-
tions. First, we aimed to empirically delineate whether
there were varying intensities of spark by employing a
latent class analysis on the seven indicators of spark,
that is, the three indicators of spark flow and four
indicators of spark value (Asparouhov & Muthe
´n,
2013; Magnusson, 2003; Muthe
´n & Muthe
´n, 2010). In
addition to the participants who reported on spark
activities, there was a group of youth who reported that
they had no spark. This group was included in further
analyses in order to determine how varying levels of
spark were related to a variety of outcomes, we next
ran three separate Multiple Analysis of Variance (MAN-
OVA): (1) social behaviors, (2) academic outcomes, and
(3) affective outcomes. In all of our analyses across all
the MANOVAs, we report the results for the Bonferroni
correction to account for the many simultaneous analy-
ses. To investigate how varying levels of support were
associated with spark (on the Low, Moderate, and High
Spark groups), we used the DCON function in the 3-Step
procedure with latent classes in MPlus7 (Asparouhov &
Muthe
´n, 2013) on three forms of support: encourage-
ment, funding, and transportation.
RESULTS
Profiles of Spark
Latent class profile analyses in MPlus version 7 were
used to determine how the seven components of spark
naturally grouped together to form groups of individuals
(Muthe
´n & Muthe
´n, 2010). A 2-group through 4-group
80 BEN-ELIYAHU ET AL.
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solution was examined. The number of participants in
each group and comparison between the Bayesian
Information Criteria (BIC) and the Aikaike Information
Criteria (AIC) across latent class solutions (Nylund,
Asparouhov, & Muthe
´n, 2007) and entropy were used
to determine how many groups of sparks fit the data
best. As recommended by Nylund et al. (2007), solutions
with lower values of BIC and AIC are considered to have
a better fit. Additionally, groups with less than 25
participants may be an artifact of the forced solution;
therefore, any solution with a group comprised of less
than 25 participants was thought to be questionable. A
4-group solution did not converge and had one group
with just 10 participants, suggesting it is not a good
description of the data. A 2-group solution and a
3-group solution fit the data well. Because the model fit
was similar across these two solutions (2-group: BIC ¼
24,614.048, AIC ¼24,497.128; 3-group: BIC ¼24123.641,
AIC ¼23,964.205), as well as similar entropy (.77), A
3-group solution was chosen as it is more descriptive of
the data and in line with the recommendation for lower
BIC and AIC.
Overall the three groups that emerged differed in their
levels of the components of sparks as indicated by a
Multiple Analysis of Variance (MANOVA) (F(14,
2986) ¼317.066, p<.001). Further examination between
groups revealed between group differences across the
seven components of sparks (F
Joy
¼694.68; F
LoseTrack
¼
120.77; F
Focus
¼677.07; F
Skills
¼526.67; F
GetAlong
¼
543.29; M
ImproveSurroundings
¼483.29; M
Learning
¼585.05,
p<.001 for all tests). In examining which group differ-
ences were significant, post-hoc analyses (Bonferonni-
corrected) revealed significant differences between the
groups on all seven indicators of sparks. Individuals in
the Low Spark group (see Figure 1) reported the lowest
levels of joy and energy (M¼1.39, SE ¼.04), not really
losing track of time (M¼.73, SE ¼.06) or being highly
focused (M¼1.30, SE ¼.05). They reported the lowest
levels of feeling that their spark activity provided skills
for future career choices (M¼.82, SE ¼.05), how to
get along with others (M¼.96, SE ¼.05), or improve
their surroundings (M¼.70, SE ¼.05). They also
thought that their sparks activity provided little encour-
agement for learning (M¼.98, SE ¼.05). The High
Spark group reported the highest level on all of these,
suggesting that they recognize the utility value of their
spark activity for current and future quality of life, and
also consistently experience flow when engaged with
their spark (M
Joy
¼.66, SE
Joy
¼.03; M
LoseTrack
¼.37,
SE
LoseTrack
¼.04; M
Focus
¼.74, SE
Focus
¼.03; M
Skills
¼
.89, SE
Skills
¼.04; M
GetAlong
¼.86, SE
GetAlong
¼.04;
M
ImproveSurroundings
¼.89, SE
ImproveSurroundings
¼.04;
M
Learning
¼.87, SE
Learning
¼.03). The Moderate Spark
group was somewhere in the middle: neither very low on
these nor reaching a state of flow and high perceived value
(M
Joy
¼.06, SE
Joy
¼.03; M
LoseTrack
¼.02, SE
LoseTrack
¼.03; M
Focus
¼.02, SE
Focus
¼.03; M
Skills
¼.28,
SE
Skills
¼.03; M
GetAlong
¼.21, SE
GetAlong
¼.03;
M
ImproveSurroundings
¼.33, SE
ImproveSurroundings
¼.03;
M
Learning
¼.22, SE
Learning
¼.03).
In examining the types of activities reported across the
different groups there were slight differences between
spark groups (v
2
(32) ¼60.32, p¼.002). Youth in the
Low Spark group had a somewhat even distribution
(20–25%) of computer=electronic use, art=dance=
drama=music, and sports engagement (Table 1). This
FIGURE 1 The 3-group latent class profiles solution for the 7 components of sparks.
Note.N
LowSpark
¼263; N
ModerateSpark
¼756; N
High Spark
¼483. In addition to these three groups, a group of 358 youth reported that they did not
have a spark. This group of youth was labeled the ‘‘No Spark’’ group.
INTEREST-DRIVEN PURSUITS OF 15 YEAR OLDS 81
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TABLE 1
Types of Activities Reported as Sparks, Organized by Spark Group
Low Spark Moderate Spark High Spark Total
Count %Count %Count %Count %
Using computers, electronics, or other types of technology 66 25.10 118 15.60 78 16.10 262 17.40
Participating in or leading art, dance, drama, music, writing, etc. 65 24.70 223 29.50 141 29.20 429 28.60
Participating in sports, athletics, or other physical activity 56 21.30 225 29.80 127 26.30 408 27.20
Studying, reading, doing research, or other ways of learning 24 9.10 48 6.30 31 6.40 103 6.90
Being in nature, caring for animals, or participating in out 17 6.50 43 5.70 23 4.80 83 5.50
Serving others, participating in politics, etc. 8 3.00 15 2.00 7 1.40 30 2.00
Doing construction, architecture, or other types of mechanic 7 2.70 14 1.90 8 1.70 29 1.90
Doing religious or spiritual activities, or learning about religion 6 2.30 23 3.00 34 7.00 63 4.20
Other 4 1.50 8 1.10 2 0.40 14 0.90
Being an entrepreneur, running a business, or inventing things 3 1.10 12 1.60 5 1.00 20 1.30
Teaching, leading others, or public speaking 3 1.10 10 1.30 16 3.30 29 1.90
Being with friends=talking with friends=hanging out 2 0.80 8 1.10 4 0.80 14 0.90
Cooking 1 0.40 3 0.40 2 0.40 6 0.40
Participating in scouts 1 0.40 0 0.00 2 0.40 3 0.20
All=Many 0 0.00 3 0.40 1 0.20 4 0.30
Being with family 0 0.00 3 0.40 0 0.00 3 0.20
ROTC 0 0.00 0 0.00 2 0.40 2 0.10
Total 263 100.00 756 100.00 483 100.00 1502 100.00
Note. According to a Pearson-Chi Square analysis, the distribution of types of activities differed from chance Chi-Sq (32)¼60.317, p¼.002.
FIGURE 2 Demographic characteristics: a) gender; b) race; and c) parent education of participants in each spark group.
82 BEN-ELIYAHU ET AL.
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distribution is somewhat different from the Moderate
and High Spark groups, where only 15–16% of youth
in those groups reported computer=electronic use as
their main spark, and slightly more youth (26–29%) were
involved in art=dance=drama=music or sports.
Finally, in looking at the gender, racial, and parent
education of youth in these different spark groups, there
is little difference across groups (see Figure 2). While
there were comparable distributions of gender across
spark groups (v
2
(3) ¼6.75, p¼.080), racial distribution
seemed to slightly vary across groups (v
2
(21) ¼55.15,
p<.001). There were also slight differences in parent edu-
cation (v
2
(21) ¼52.67, p<.001) as parents in the Middle
and High Spark groups completed high school and col-
lege more than those in the No and Low Spark groups.
Online Use
Because interest-driven learning is often facilitated by
digital media (Ito et al., 2013), we examined whether
Spark time or intensity was related to the average
amount of hours online per week. There were no differ-
ences in online use amongst spark intensity groups or
interaction between spark group and type of spark
(F(26) ¼.570, p¼.960). Not surprisingly, however, there
was a main effect for type of spark (F(16) ¼3.442,
p<.001), wherein youth who reported their main spark
in computers=electronics reported significantly more
time spent online (M¼20.72, SE ¼1.12) than those
who reported sports (M¼11.14, SE ¼1.02), being in
nature (M¼11.97, SE ¼2.08), studying=reading
(M¼12.03, SE ¼1.08), or arts (M¼14.48, SE ¼0.96)
as their main Spark.
Relationship of Spark Intensities to Well-Being
Outcomes
Next, we conducted three separate MANOVAs to
examine how having a spark was related to social beha-
viors, academics, and well-being. For these analyses, we
included the No Spark group to investigate the con-
tinuum from not having a spark to the highest level of
spark. Thus, we had all four groups of participants in
all of the reported analyses (No Spark, Low Spark,
Moderate Spark, and High Spark) Bonferroni post-hocs
analysis results are reported for each MANOVA
separately.
Social Behaviors
The overall MANOVA for social behaviors was sig-
nificant (F(12, 3363.041) ¼20.442, p<.001), suggesting
that there are significant differences among the spark
groups worthy of further investigation. As can be seen
TABLE 2
Mean and Standard Error for Social Behaviors by Spark Groups
Vandalism Leadership Social Good Civic Engagement
Mean Std. Error Mean Std. Error Mean Std. Error Mean Std. Error
No Spark 1.35 0.06 2.42
ab
0.11 1.85 0.07 2.56
a
0.05
Low Spark 1.24 0.05 2.23
a
0.11 1.60 0.07 2.28
b
0.05
Moderate Spark 1.20 0.03 2.70
b
0.06 1.66 0.04 2.54
a
0.03
High Spark 1.19 0.04 3.27
c
0.07 1.92 0.04 3.01
c
0.03
F¼2.42 p¼.064 F¼27.99 p<.001 F¼9.79 p¼.001 F¼62.63 p¼.001
Note. Different letters denote significant differences between spark groups (rows) on the particular outcome (columns) as found in post-hoc
group comparisons. For example, the means of ‘‘a’’ and ‘‘b’’ are significantly different from each other, whereas there was no significant difference
between ‘‘a’’ and ‘‘ab.’’
TABLE 3
Mean and Standard Error of Academic-Related Outcomes by Spark Group
Mastery Goals Attendance Effort Grade Point Average
Mean Std. Error Mean Std. Error Mean Std. Error Mean Std. Error
No Spark 2.62
a
0.04 0.71
a
0.02 2.92
a
0.05 3.06
a
0.04
Low Spark 2.60
a
0.05 0.50
ab
0.02 2.94
a
0.05 3.20
a
0.05
Moderate Spark 2.91
b
0.03 0.18
b
0.01 3.13
b
0.03 3.38
b
0.03
High Spark 3.28
c
0.03 0.36
b
0.02 3.35
c
0.04 3.43
b
0.03
MANOVA F¼70.354 p<.001 F¼12.826 p<.001 F¼23.713 p<.001 F¼21.285 p<.001
Note. Different letters denote significant differences between spark groups (rows) on the particular outcome (columns) as found in post-hoc
group comparisons. For example, the means of ‘‘a’’ and ‘‘b’’ are significantly different from each other, whereas there was no significant difference
between ‘‘a’’ and ‘‘ab.’’
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from Table 2, even though the overall MANOVA for
social good indicated differences among the spark
groups, there were no between group differences when
examining the post-hoc Bonferroni tests for vandalism.
However, youth in the High Spark group reported more
involvement as leaders, caring for the social good, and
civic engagement. The Low Spark group had a lower
average on these three social outcomes from the No
Spark group, but this was not always statistically signifi-
cant (see Table 2 for details).
Academic Outcomes
The overall MANOVA for academic outcomes was
significant (F(12, 4640.939) ¼22.486, p<.001), suggesting
that there are significant differences amongst the different
TABLE 4
Mean and Standard Error of Well-Being Outcomes by Spark Group
Hopeful Purpose Positive Future Worry
Mean Std. Error Mean Std. Error Mean Std. Error
No Spark 2.87
a
0.03 2.91
a
0.06 2.51
a
0.04
Low Spark 2.88
a
0.03 2.80
a
0.07 2.35
ab
0.05
Middle Spark 3.14
b
0.02 3.21
b
0.04 2.34
b
0.03
High Spark 3.52
c
0.02 3.88
c
0.05 2.29
b
0.04
MANOVA F¼163.681 p<.001 F¼76.561 p<.001 F¼6.059 p<.001
Note. Different letters denote significant differences between spark groups (rows) on the particular outcome (columns) as found in post-hoc
group comparisons. For example, the means of ‘‘a’’ and ‘‘b’’ are significantly different from each other, whereas there was no significant difference
between ‘‘a’’ and ‘‘ab.’’
TABLE 5
Means and Standard Errors for Encouragement, Providing Funding, and Providing Transportation
Encourages Funding Transportation
Parent Low Spark 3.20
a
0.07 3.11
a
0.07 3.21
a
0.07
Moderate Spark 3.52
b
0.03 3.42
b
0.04 3.45
b
0.04
High Spark 3.68
c
0.03 3.63
c
0.03 3.68
c
0.03
Pairwise v
2
v
2
¼44.90 p<.001 v
2
¼50.69 p<.001 v
2
¼44.32 p<.001
Extended Family Low Spark 2.68
a
0.07 2.37
a
0.07 2.03
a
0.06
Moderate Spark 3.00
b
0.04 2.65
b
0.04 2.30
b
0.05
High Spark 3.48
c
0.04 3.13
c
0.05 2.87
c
0.06
Pairwise v
2
v
2
¼137.55 p<.001 v
2
¼96.92 p<.001 v
2
¼109.07 p<.001
Neighbors Low Spark 1.64
a
0.05 1.52
a
0.05 1.44
a
0.05
v
2
(6, 2514) ¼15.565 Moderate Spark 1.92
b
0.04 1.55
a
0.03 1.54
a
0.03
High Spark 2.52
c
0.06 2.05
b
0.05 2.02
b
0.05
Pairwise v
2
v
2
¼134.44 p<.001 v
2
¼68.18 p<.001 v
2
¼74.93 p<.001
Friends Low Spark 2.57
a
0.07 1.94
a
0.07 1.80
a
0.05
Moderate Spark 3.22
b
0.03 2.17
b
0.04 2.33
b
0.04
High Spark 3.48
c
0.03 2.61
c
0.06 2.82
c
0.06
Pairwise v
2
v
2
¼154.09 p<.001 v
2
¼66.14 p<.001 v
2
¼184.15 p<.001
School Low Spark 2.31
a
0.07 1.71
a
0.06 1.42
a
0.05
v
2
(6, 2550) ¼17.600 Moderate Spark 2.70
b
0.04 1.87
a
0.04 1.57
a
0.04
High Spark 3.26
c
0.04 2.38
b
0.06 1.95
b
0.06
Pairwise v
2
v
2
¼168.99 p<.001 v
2
¼75.12 p<.001 v
2
¼53.27 p<.001
Mentor Low Spark 2.96
a
0.09 2.38
a
0.13 1.97
a
0.10
Moderate Spark 3.39
b
0.05 2.66
a
0.07 2.48
b
0.06
High Spark 3.65
c
0.04 2.90
b
0.06 2.75
c
0.07
Pairwise v
2
v
2
¼51.31 p<.001 v
2
¼15.07 p¼.001 v
2
¼43.05 p<.001
Adult Low Spark 2.11
a
0.08 1.67
a
0.06 1.44
a
0.06
v
2
(6, 2418) ¼14.015 Moderate Spark 2.44
b
0.05 1.80
b
0.04 1.65
b
0.04
High Spark 2.93
c
0.05 2.29
c
0.06 2.08
c
0.04
Pairwise v
2
v
2
¼86.12 p<.001 v
2
¼66.52 p<.001 v
2
¼75.08 p<.001
Note. Different letters denote significant differences between spark groups (rows) on the particular outcome (columns) as found in post-hoc
group comparisons for each relationship. For example, the means of ‘‘a’’ and ‘‘b’’ are significantly different from each other, whereas there was
no significant difference between ‘‘a’’ and ‘‘ab.’’
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spark groups (see Table 3). More specifically, the High
Spark group reported a higher focus on learning (mastery
goals), exerting more effort in school, and obtaining
higher grades than the No and Low Spark groups. The
No Spark group missed the most days of school, but
did not differ from the Low Spark group on any of the
academic outcomes. In this sense, having a low spark
and not having a spark at all are quite similar, whereas
having moderate or high sparks was associated with
academic benefits for youth.
Affective Outcomes
In examining the affective nature of youth across
the spark groups, the overall MANOVA for affective
outcomes was significant (F(9, 4405.215) ¼55.016,
p<.001), suggesting that there are significant differences
among individuals based on sparks (see Table 4). Youth
in the High Spark group reported higher levels of hopeful-
ness and purpose, a positive future outlook, and less
worrying. The Low Spark and No Spark groups were
lowest in their sense of hope=purpose and positive future
outlook, and highest in worrying.
Relational Supports for the Development of Sparks
A single model incorporating the latent class profiles and
relational supports (i.e., encouragement, funding, and
transportation) was run using MPlus7 (Asparouhov &
Muthe
´n, 2013). We report the overall Chi-Square for
the between group comparison and pairwise analyses in
Table 5. For all forms of relationships, the High Spark
group tended to receive the most encouragement for their
spark, while the Low Spark group reported the lowest
levels of encouragement and the Moderate Spark group
reported moderate levels. This pattern was also apparent
for providing financial support for spark-related activi-
ties, with the High Spark youth receiving the most fund-
ing for their spark, while the other groups received
progressively less. Although the Low and Moderate
Spark groups did not differ significantly across relation-
ships with regards to transportation, the High Spark
group tended to report the highest levels of others
providing them transportation.
DISCUSSION
In the current study we were interested in exploring
intense interest areas identified as ‘‘sparks,’’ by a large,
ethnically-diverse group of 15-year-old adolescents, the
extent to which such sparks were related to a range of
developmental outcomes, and the role of relationships
in supporting spark development. Youth identified a
wide range of sparks, and spark intensity was positively
associated with positive outcomes and supportive
relationships.
The Nature of Sparks
Profile-centered analyses suggested that sparks could be
characterized by the intensity of positive feelings, immer-
sion, and utility that youth find when engaged. Although
youth were prompted to answer affirmatively only when
they had deep interests or passions (i.e., ‘‘this spark is
more than just interesting or fun for them. They are pas-
sionate about it’’), the intensity of their commitment
varied considerably, as has been previously found with
regard to other motivational and psychological con-
structs (e.g., Csikszentmihalyi, 1999; Wigfield, Eccles,
Schiefele, Roeser, & Davis-Kean, 2006).
And, although the question about sparks was not
focused on a specific content, it is interesting to note that
more youth in the Low Spark group reported that
computer=electronic use was their spark than youth in
the Moderate and High Spark groups. Youth in this
group spent many more hours per week online. Compu-
ters and other forms of digital media are often used in cre-
ative and skill-enhancing ways (e.g., advanced gaming,
programming, blogging, or video production) (Ito et al.,
2013), and are a major channel for youth to pursue
interest-driven learning. Yet, other popular online activi-
ties, such as watching YouTube videos and social net-
working, are both more common and passive in nature
(Lenhart et al., 2010). Recent findings point to an associ-
ation between high levels of this latter form of engage-
ment and negative social comparisons (Pantic et al.,
2012; Whitehill et al., 2013). Future studies should differ-
entiate the extent to which online activities are pursued in
the context of interest-driven learning across the domains
(e.g., musical instruction, engagement in learning com-
munities) versus more passive engagement.
Youth in the Low Spark group were also more likely
to describe their interest as related to ‘‘studying, reading,
research, or other ways of learning.’’ Like some forms of
computer use, these are generally more solitary, less
active pursuits which, although enriching, may involve
fewer opportunities for the kinds of scaffolded support
and challenge that are more characteristic of the
sense of flow (Abuhamdeh & Csikszentmihalyi, 2012a,
2012b).
By contrast, higher levels of spark appear to occur
through pursuits that require more active social engage-
ment such as sports, drama and dance, participating in
politics, or serving others. Activities that include social
interactions present more opportunities for the kinds of
cooperative learning and feedback that can lead to opti-
mal states (Abuhamdeh & Csikszentmihalyi, 2012a,
2012b). More research is needed to identify the specific
types of activities within these somewhat broad categories
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and their particular associations with outcomes. Like-
wise, it will be important to understand the mechanisms
that account for these associations. The more active nat-
ure of the Moderate and High Spark relative to the Low
Spark activities also imply metabolic and other physio-
logical corollaries which, in turn, can heighten learning
and engagement (Bla
¨sing et al., 2012; Winter et al., 2007).
Relationship of Spark Intensities to Well-Being
Outcomes
Next, we explored associations between levels of sparks
and outcomes. Although there were no group differences
in vandalism, those in the High Spark group reported the
most social involvement, suggesting that intensive activi-
ties provide a rich context for the development of peer
and intergenerational relationships. These same High
Spark youth also report achieving higher levels of mas-
tery, missing fewer days of schools, working harder than
others in school, and having a stronger focus on learning
and developing in school, in line with research suggesting
that preference influences learning processes and out-
comes (Ben-Eliyahu, 2011; Ben-Eliyahu & Linnenbrink-
Garcia, 2013). Engaging in favored activities may not
only enhance youth’s general energy levels and readiness
to learn (Bla
¨sing et al., 2012; Cowley, Ravaja, &
Heikura, 2013; Winter et al., 2007), but also contribute
to a stronger connection to the school and determination
to excel more generally. In this way, schools may enjoy
the positive benefits of High Spark youths’ broadened
interest in learning beyond the particular focus of their
interests. Youth who are deeply engaged in interest-
driven activities may be transferring the drive and
discipline that is necessary for skill development in that
domain to positive experiences and adaptive self-
regulation in learning to their schoolwork, the com-
munity, and other aspects of their lives. It is therefore
not surprising that High Spark youth also have a higher
sense of purpose and positive future outlook, and report
being less worried than their No and Low Spark counter-
parts. Longitudinal research is needed to determine the
direction of these associations, as it could also be argued
that those with strong social and regulatory skills
are more likely to develop sparks (Tough, 2012). Devel-
opmental theory and research, however, (Benson, Scales,
Hamilton, & Sesma, 2006; Lerner, Brentano, Dowling, &
Anderson, 2002) would more likely support bi-
directional relations between sparks, social skills, and
self-regulation over time.
Taken together, these findings also suggest the bene-
fits that could derive from schoolwork being more inten-
tionally connected to students’ sparks. Particularly as
nearly a quarter of high school students report being
bored in school every day (Yazzie-Mintz, 2010), explicit
efforts to help students identify and develop knowledge
and expertise around their sparks, and to build interest-
driven learning, may contribute to student achievement
(Ito et al., 2013). This sort of connected learning could
help facilitate active learning across developmental
settings and shift the way we approach education and
learning (Ito et al., 2013).
Relational Supports for the Development of Sparks
Compared to youth in the Low or Moderate Spark
groups, youth in the High Spark group reported that par-
ents, extended family members, neighbors, friends, adults
at school, ‘‘other adults,’’ and mentors tended to provide
higher levels of transportation to the spark activity, fund-
ing for spark-related expenditures, and encouragement
to continue in the spark activity. Importantly, this was
true for ‘‘other adults’’ in youth’s lives, for example,
coaches or other adults in a youth organization or
after-school program, perhaps because of the constraints
prescribed by those roles and settings and the low ratio of
adults to youth in many sports programs and settings.
Nevertheless, a recent study with more comprehensive
information on the coaching relationship reported that
the more coaches created a ‘‘task-involving’’ climate
(parallel to the pursuit of sparks as described herein),
the more committed athletes were to continuing in their
sport, and the less likely they were to cheat (Ntoumanis,
Taylor, & Thorgersen-Ntoumani, 2011). Fostering a
learning environment that deemphasizes appearing com-
petent and focuses on developing and learning (i.e., mas-
tery goal structure) is also related to a lower need for
seeking approval from others in order to feel a sense of
self-worth (O’Keefe, Ben-Eliyahu, & Linnenbrink-
Garcia, 2013), thereby contributing to positive develop-
ment. In this way, having a spark may also focus the
youth away from situations in which their self-worth is
contingent on performance rather than learning and
enhancing one’s skill set.
Our findings are consistent with a growing body of
research that suggests that young people’s subjective
well-being is derived from engagement in satisfying
activities and the developmental relationships and sense
of connectedness that such engagement provides (Larson,
2011; Seligman, 2002; Seligman & Royzman, 2003).
Importantly, a range of adults (not just parents) provided
key support for developing interest-driven interest.
Particularly among youth with limited social and cultural
capital, caring relationships with nonparent adults
appear to provide valuable exposure to and compensa-
tory support for pursuing interest activities and domains.
Such exposure, in turn, may facilitate identity develop-
ment by providing experiences on which children and
adolescents can draw to construct their sense of self
(Yates & Youniss, 1996). Indeed, Waterman (1982)
has proposed that activities provide opportunities for
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discovering special talents and abilities and are thus a
primary source through which identity is formed.
Beyond this function, participation in prosocial activi-
ties and settings may expose youth to more socially desir-
able or high-achieving peer groups with whom they can
identify and forge shared interests (Fredricks & Eccles,
2006). For caring adults to facilitate this process, it will
be important to continue to explore how sparks develop
and the role of social relationships in shaping these inter-
ests. The current study adds to knowledge about how
developmental relationships work to promote learning
and other positive outcomes in adolescence, but these
operative pathways should be further explored for their
basic and applied scientific implications.
Limitations
Data were collected via an online, cross-sectional self-
report survey and, consequently, it is impossible to deter-
mine the direction of the effects. As mentioned above,
youth intense interests might be particularly appealing
to adults, such that close connections with caring adults
may be the byproduct of intense interests rather than a
cause of it. Youth who have intense interests may be
primed for higher levels of involvement with adults than
are peers who lack these qualities. Werner and Smith
(1982) observed that youth who have thrived despite
adversity tend to have hobbies or other interests and a
unique capacity to engage with adults through those
activities. Additionally, this sample was drawn from 15
year olds whose families were already part of an ongoing
panel that receives incentives to enroll in the panel and
participate in research studies (Scales et al., 2011). This
willingness to participate and the access to online surveys
might make this sample less vulnerable and more devel-
opmentally advantaged than a truly representative sam-
ple of American 15 year olds. Thus, more research is
needed to examine how developmental assets and devel-
opmental relationships across a wider range of youth
provide opportunities, and thereby support the develop-
ment of deep interests or sparks.
More research is also needed to expand beyond the
limited age range of this sample and examine how
interest-driven passions are shaped from a younger age.
Although a common belief is that youth change their
minds frequently, Low and Rounds (2007) found that
vocational interests change very little. Likewise, more
research is needed to determine how crucial it is to have
stable interest-driven passions. Perhaps the consistency is
not a critical component if the intensity of the interest is a
driving ingredient of resilience. That is, it might not mat-
ter if youth lose and gain new interests over time so long
as there is a depth of commitment. In fact, the versatility
might actually enable youth to gain a wider range of
skills and explore possibilities. This possibility may be
particularly true for younger adolescents, for whom
exploration and frequent change of interests is both a
common and necessary part of development (Scales,
2010). Longitudinal methods would allow assessment
of the stability of sparks, and how changes in develop-
mental relationships and changes in spark stabilities
affect positive outcomes.
Parents of youth in the Moderate and High Spark
groups tended to have slightly higher levels of education
than youth in the Low Spark and No Spark groups, sug-
gesting that they may have had more resources to devote
to the development of their children’s interests. Future
research should explore how such factors as parent edu-
cation, work schedules, socioeconomic status, and fam-
ily size influence the development of interest-driven
passions in youth.
There might also be issues with participant scaling in
their answering of questions due to shared method vari-
ance. Variability across outcomes and providers of sup-
port, however, suggest that the findings were not simply
the result of response bias. For example, although the
spark groups differed on some dimensions, they did
not differ in others (e.g., anti-social, prosocial behaviors),
and the findings were not significant for the very broad
category of ‘other adults.’ Nonetheless, to mitigate shared
method variance issues, future research should collect
data from multiple reporters, especially in relation to per-
ceptions of support provided for spark development.
Despite these limitations, this study contributes to
our understanding of young people’s sparks and how
supporting their development may contribute to positive
youth development. Taken together, our results
highlight the variation in intensity with which youth
approach their interests and the important role of social
resources. To the extent that all youth are provided with
opportunities to explore and pursue their deepest inter-
ests, the next generation of young people will be in a
better position to pursue activities that bring them hap-
piness, well-being, and more positive contributions to
their schools, communities, and society.
ACKNOWLEDGMENTS
The authors gratefully acknowledge the support of the
MacArthur Foundation Research Network on Connec-
ted Learning, the Best Buy Foundation, and MENTOR:
The National Mentoring Partnership.
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