The contribution of the developmental assets framework to positive youth development theory and practice

Abstract

The framework of developmental assets posits a theoretically-based and research-grounded set of opportunities, experiences, and supports that are related to promoting school success, reducing risk behaviors, and increasing socially-valued outcomes including prosocial behavior, leadership, and resilience. A considerable body of literature on developmental assets has emerged in the last two decades, informing research and practice in education, social work, youth development, counseling, prevention, and community psychology. In addition to synthesizing this literature, this chapter discusses: the recent development of the Developmental Asset Profile, an instrument designed, in part, to assess change-over-time; the utilization of asset measures in international research; the expansion of the assets framework to early childhood and young adults; and new research using latent class analysis (LCA) to identify classes or subgroups of youth.

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From: Peter L. Benson, Peter C. Scales, and Amy K. Syvertsen, The Contribution of the
Developmental Assets Framework to Positive Youth Development Theory and Practice.
In Richard M. Lerner, Jacqueline V. Lerner and Janette B. Benson, editors: Advances in Child
Development and Behavior, Vol. 41, Burlington: Academic Press, 2011, pp. 197-230.
ISBN: 978-0-12-386492-5
© Copyright 2011 Elsevier Inc.
Academic Press.

THE CONTRIBUTION OF THE DEVELOPMENTAL
ASSETS FRAMEWORK TO POSITIVE YOUTH
DEVELOPMENT THEORY AND PRACTICE
Peter L. Benson, Peter C. Scales, and Amy K. Syvertsen
SEARCH INSTITUTE, MINNEAPOLIS, MINNESOTA, USA
I. INTRODUCTION
II. DEVELOPMENTAL ASSETS: OVERVIEW OF RESEARCH
A. THE ACCUMULATION HYPOTHESIS
B. THE DIVERSITY HYPOTHESIS
C. THE DIFFERENTIATION HYPOTHESIS
III. APPLICATION OF THE ASSET FRAMEWORK TO
POLICIES AND PROGRAMS
IV. RESEARCH FROM NEW MEASURES OF DEVELOPMENTAL ASSETS
V. TRACKING CHANGE IN DEVELOPMENTAL ASSETS OVER TIME
A. EXPANSION OF THE ASSETS FRAMEWORK TO YOUNGER
CHILDREN AND YOUNG ADULTS
VI. DEVELOPMENTAL ASSET PROFILES
A. METHOD AND MODEL INDICATORS
B. LATENT CLASS DESCRIPTIONS AND MEMBERSHIP
C. MULTIGROUP ANALYSES
D. THRIVING AND RISK BEHAVIOR
VII. NEXT STEPS IN RESEARCH AND PRACTICE
REFERENCES
Abstract
The framework of developmental assets posits a theoretically-based and
research-grounded set of opportunities, experiences, and supports that are
related to promoting school success, reducing risk behaviors, and increasing
socially-valued outcomes including prosocial behavior, leadership, and
resilience. A considerable body of literature on developmental assets has
emerged in the last two decades, informing research and practice in educa-
tion, social work, youth development, counseling, prevention, and commu-
nity psychology. In addition to synthesizing this literature, this chapter
197
Advances in Child Development and Behavior Copyright ©2011 Elsevier Inc. All rights reserved.
Richard M. Lerner, Jacqueline V. Lerner and Janette B. Benson : Editors
Author's personal copy

discusses: the recent development of the Developmental Asset Profile, an
instrument designed, in part, to assess change-over-time; the utilization of
asset measures in international research; the expansion of the assets frame-
work to early childhood and young adults; and new research using latent
class analysis (LCA) to identify classes or subgroups of youth.
I. Introduction
The framework of developmental assets, first posited in 1990 (Benson,
1990) and refined in 1995 (Benson, 1997, 2006), was explicitly designed
to provide greater attention to the positive developmental nutrients that
young people need for successful development, not simply to avoid high-
risk behaviors, and to accent the role that community plays in adolescent
well-being. As described in a series of publications (Benson, 2002, 2003;
Benson, Leffert, Scales, & Blyth, 1998; Leffert et al., 1998; Scales &
Leffert, 1999, 2004; Scales, Benson, Leffert, & Blyth, 2000), the frame-
work establishes a set of developmental experiences and supports hypothe-
sized to have import for all young people during the second decade of life.
Recent work is taking a broader lifespan perspective, positing that develop-
mental assets reflect developmental processes that have age-related
parallels in infancy, childhood, and young adulthood (Leffert, Benson, &
Roehlkepartain, 1997; Mannes, Benson, Kretzmann, & Norris, 2003; Scales,
Roehlkepartain, & Benson, in press; Scales, Sesma, & Bolstrom, 2004a;
VanderVen, 2008). This work will be addressed later in this chapter.
The framework synthesizes research in a number of fields with the goal
of selecting for inclusion those developmental nutrients that (a) have been
demonstrated to prevent high-risk behavior (e.g., substance use, violence,
dropping out of school), enhance thriving, or strengthen resilience; (b)
have evidence of generalizability across social location; (c) contribute
balance to the overall framework (i.e., of ecological- and individual-level
factors); (d) are within the capacity of communities to effect their acquisi-
tion; and (e) are within the capacity of youth to proactively procure
(Benson & Scales, in press; Benson, Scales, Hamilton, & Sesma, 2006).
Because the developmental assets framework for adolescents ages
12–18 was designed not only to inform theory and research but also to
have practical significance for the mobilization of communities, the 40
assets included in the model (Benson et al., 2006)are placed in categories
that have conceptual integrity and can be described easily to the residents
of a community. As seen in Table I, the assets are grouped into 20 exter-
nal assets (i.e., environmental, contextual, and relational features of
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Table I
The Framework of 40 Developmental Assets
Ò
for Adolescents
Search Institute has identified the following building blocks of healthy development that help
young people grow up healthy, caring, and responsible.
External Assets
Support
1. Family support—Family life provides high levels of love and support.
2. Positive family communication—Young person and her or his parent(s) communicate
positively, and young person is willing to seek advice and counsel from parent(s).
3. Other adult relationships—Young person receives support from three or more nonparent
adults.
4. Caring neighborhood—Young person experiences caring neighbors.
5. Caring school climate—School provides a caring, encouraging environment.
6. Parent involvement in schooling—Parent(s) is actively involved in helping young person
succeed in school.
Empowerment
7. Community values youth—Young person perceives that adults in the community value
youth.
8. Youth as resources—Young people are given useful roles in the community.
9. Service to others—Young person serves in the community 1 h or more per week.
10. Safety—Young person feels safe at home, at school, and in the neighborhood.
Boundaries and expectations
11. Family boundaries—Family has clear rules and consequences and monitors the young
person’s whereabouts.
12. School boundaries—School provides clear rules and consequences.
13. Neighborhood boundaries—Neighbors take responsibility for monitoring young people’s
behavior.
14. Adult role models—Parent(s) and other adults model positive, responsible behavior.
15. Positive peer influence—Young person’s best friends model responsible behavior.
16. High expectations—Both parent(s) and teachers encourage the young person to do well.
Constructive use of time
17. Creative activities—Young person spends three or more hours per week in lessons or
practice in music, theater, or other arts.
18. Youth programs—Young person spends three or more hours per week in sports, clubs, or
organizations at school and/or in the community.
19. Religious community—Young person spends one or more hours per week in activities in
a religious institution.
20. Time at home—Young person is out with friends “with nothing special to do”two or
fewer nights per week.
Internal Assets
Commitment to learning
21. Achievement motivation—Young person is motivated to do well in school.
22. School engagement—Young person is actively engaged in learning.
23. Homework—Young person reports doing at least 1 h of homework every school day.
24. Bonding to school—Young person cares about her or his school.
25. Reading for pleasure—Young person reads for pleasure three or more hours per week.
(Continued)
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socializing systems) and 20 internal assets (i.e., skills, competencies, and
values). The external assets comprise four categories: (a) support, (b)
empowerment, (c) boundaries and expectations, and (d) constructive use
of time. The internal assets are also placed into four categories: (a) com-
mitment to learning, (b) positive values, (c) social competencies, and (d)
positive identity. The scientific foundations for the eight categories and
each of the 40 assets are described in more detail in Scales and Leffert
(1999, 2004). An exploratory factor analysis conducted with 150,000
6th–12th grade students showed that 14 scales emerged for middle school
students and 16 for high-school students, all conceptually reflecting the
eight a priori asset categories; in addition, a second-order factor analyses
identified two major superordinate scales, labeled individual assets and
ecological assets, that mirrored the a priori designation of assets into inter-
nal and external classes (Theokas et al., 2005).
Table I
(Continued )
Positive values
26. Caring—Young person places high value on helping other people.
27. Equality and social justice—Young person places high value on promoting equality and
reducing hunger and poverty.
28. Integrity—Young person acts on convictions and stands up for her or his beliefs.
29. Honesty—Young person “tells the truth even when it is not easy.”
30. Responsibility—Young person accepts and takes personal responsibility.
31. Restraint—Young person believes it is important not to be sexually active or to use
alcohol or other drugs.
Social competencies
32. Planning and decision making—Young person knows how to plan ahead and make
choices.
33. Interpersonal competence—Young person has empathy, sensitivity, and friendship skills.
34. Cultural competence—Young person has knowledge of and comfort with people of differ-
ent cultural/racial/ethnic backgrounds.
35. Resistance skills—Young person can resist negative peer pressure and dangerous situations.
36. Peaceful conflict resolution—Young person seeks to resolve conflict nonviolently.
Positive identity
37. Personal Power—Young person feels he or she has control over “things that happen
to me.”
38. Self-Esteem—Young person reports having a high self-esteem.
39. Sense of Purpose—Young person reports that “my life has a purpose.”
40. Positive View of Personal Future—Young person is optimistic about her or his personal
future.
Note. The 40 Developmental Assets
Ò
for Adolescents may be reproduced for educational,
noncommercial uses only. Copyright 2005 by Search Institute
Ò
, Minneapolis, MN; 800-888-7828;
www.search-institute.org. All Rights Reserved.
200 Peter L. Benson et al.
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The developmental assets approach has become acknowledged as one of
the most widespread and influential frameworks for understanding and
strengthening positive youth development (PYD; Eccles & Gootman,
2002; Small & Memmo, 2004). Google Scholar shows that the developmental
assets approach and/or Search Institute have been referenced in more than
17,000 peer-reviewed journal articles and other academic/professional
publications since 1999. In addition to the assets framework, some of the
most well-known approaches to PYD include the social development model
and Communities That Care (promulgated by the University of Wash-
ington’s Social Development Research Group), the 5Cs of PYD, and the 5
Promises of the America’s Promise Alliance. A search in December 2010
of three major citation sources, Google Scholar, Academic Search Premier,
and Psychinfo, showed that citations of the developmental assets approach
and/or Search Institute far outstripped all the others in the 5 years from
2005 to 2010, with developmental assets/Search Institute being named
12,567 times, the social development model/Communities That Care cited
2182 times, the 5 Promises named 149 times, and the 5Cs cited 97 times.
Google Scholar does not distinguish peer-review mentions from others,
but in the Academic Search Premier and Psychinfo listings, developmental
assets/Search Institute had a total of 1618 citations, compared with the clos-
est other PYD approach, the social development model/Communities That
Care, with 324 peer-reviewed mentions.
In addition to its predominance in the literature, the developmental assets
framework has become a central organizing feature of youth programming
in major national systems, such as the Y (formerly the YMCA of the
USA) and Y Canada, Boys and Girls Clubs of America, Girl Scouts of the
USA, the American Camp Association, the Salvation Army, major national
religious denominations spanning the conservative to progressive spectrum,
thousands of service-learning programs in schools, congregations, and youth
organizations (through the National Youth Leadership Council and the sup-
port of the Corporation for National and Community Service), and more
than 600 formal community coalitions trying to strengthen their com-
munities as environments for young people, by focusing on initiatives for
building the assets. In 2009 alone, more than 10,000 schools and youth pro-
grams were using Search Institute resources, and in the last 15 years, more
than 20 million of the Institute’s books and other resources have been
disseminated worldwide. In the past decade, more than 300,000 leaders in
education, health, social services, religion, youth development, and other
fields have been trained in the assets framework, and more than 5 million
people from over 180 countries have visited the Institute’s Web site (www.
search-institute.org). Scholars, educators, religious leaders, and youth work
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practitioners in more than 60 countries across the globe are using the asset
approach in programs and data collection.
The national and international spread of the research on and practice of
developmental assets is rooted in five strategies, each of which has fueled
interest and action in the framework. First, the extensive research on the
asset framework has, as noted earlier, created considerable attention
within a number of fields of inquiry, including developmental psychology,
community psychology, education, social work, and clinical/counseling
psychology. This multidisciplinary exposure not only has fueled research
by scholars and graduate students but has also activated practitioners in
these fields to apply the research in countless communities and programs.
Second, a long-term effort at the diffusion of the developmental asset
research and its implications has brought the work, via Search Institute’s
training, public speaking, consulting, media communications, and
conferences, to scholars and practitioners in every state and multiple
nations. Third, the asset framework names developmental nutrients that
are—in the words of many practitioners—both practical and actionable.
Accordingly, thousands of professionals and citizens bring the work to
local agencies and communities as an approach that helps deepen the
impact of a wide range of other initiatives, including mentoring, service
learning, youth leadership development, after-school programming, and
parent education. Fourth, the asset framework, with its broad ecological
approach, empowers many sectors—family, school, neighborhood, after-
school programs, faith communities—to take action. Fifth, and perhaps
most importantly, the asset framework (as shown by the research that
undergirds it) can be positioned in a city or state or nation as a set of
nutrients that matters, developmentally and behaviorally, for all youth
regardless of race, ethnicity, family composition, gender, parental educa-
tion, or geographic location. Hence, the asset model has the potential to
create the kind of shared vision that can lessen fractured and siloed
approaches that inhibit cooperation and collaboration.
II. Developmental Assets: Overview of Research
The foundational appeal of the assets framework is that it is rooted in
and anchored by a vast scientific literature in child and adolescent devel-
opment. The assets framework was originally conceived in 1990, with a
review of the prevention, youth program evaluation, and resilience
literatures yielding an initial framework of 30 developmental assets
arrayed across six broad developmental categories that seemed rather
consistently to be linked to a variety of indicators of youth well-being
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(Benson, 1990). After several years of utilizing the framework in both
research studies and community mobilization efforts, Search Institute
solicited feedback from educators, youth workers, and others which led
to the refinement of the framework into a final list of 40 assets that com-
prised the current eight categories (Benson et al., 1998).
Simultaneous with the revising of the framework on the basis of practi-
tioner wisdom, a new and more comprehensive review of the empirical liter-
ature on adolescent development was conducted, with more than 1000
largely quantitative studies reviewed, and ultimately, more than 800
meeting criteria around sample size and design being cited in a wide-ranging
synthesis that documented both the correlational and causational findings
linking asset-like constructs (whether called protective factors, resilience
factors, strengths, or assets) to PYD (Scales & Leffert, 1999,revised and
updated further in Scales & Leffert, 2004). Subsequently, a similar literature
review focusing on middle childhood yielded a comparably comprehensive
synthesis of the assets literature–PYD association for younger children in
middle childhood, listing and discussing more than 600 empirical citations
(Scales et al., 2004a). Collectively, this demonstration of the rootedness of
the assets framework in more than 1400 studies of child and adolescent
development and its infusion with both empirical findings and practitioner
insights provided considerable support for the construct, convergent, and
predictive validity of the developmental assets approach.
Search Institute’sown research with surveys that specifically defined the 40
developmental assets consistently has produced results that have fed the
growing theoretical and applied utility of the framework. Major research
findings are addressed in the following three sections: the accumulation
hypothesis, the diversity hypothesis, and the differentiation hypothesis.
A. THE ACCUMULATION HYPOTHESIS
One of the central hypotheses in the developmental asset model is that
assets are additive or cumulative. The consequence of this additive func-
tion is the reverse of that found in the research on risk factors. A risk fac-
tor “is an agent or characteristic of the individual or environment that is
related to the increased probability of a negative outcome”(Campos,
2004,p. 264). Risks include a wide range of individual and community
factors, including family conflict, neighborhood violence, poverty, physical
and/or sexual abuse, and underperforming schools. A significant research
literature has empirically established the cumulative impact of risk factors
(Rutter, 1987a, 1987b). As the number of risks increase, the health and
well-being of adolescents decline (Friedman & Chase-Lansdale, 2002).
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As Campos (2004) succinctly puts it, “negative outcomes increase addi-
tively or exponentially as the number of risk factors increases”(p. 265).
Playing off the definition of risk given above, a developmental asset is
an agent or characteristic of the individual or his/her developmental
ecologies (e.g., family, peer group, neighborhood, school, community) that
is related to the increased probability of positive outcomes. Like the risk
model, but in reverse, positive outcomes (e.g., school success, social and
emotional health, contribution, caring, and the absence of health-
compromising behaviors such as alcohol use, drug use, violence, antisocial
behavior) increase additively or exponentially as the number of develop-
mental assets increases. This hypothesis is described in more detail in a
recent systematic review of PYD theory and research (Benson et al.,
2006). It should be noted here that the reduction of risk factors and the
promotion of developmental assets are complementary approaches to pro-
moting adolescent health (Scales, 1999).
Multiple studies confirm the additive developmental asset hypothesis,
showing that the more developmental assets young people experience,
the better off they tend to be, across a range of academic, psychological,
social–emotional, and behavioral indicators of well-being. Search Institute
has administered more than 3 million of its assets surveys to 4th–12th
graders in the United States, involving more than 2000 communities large
and small, urban, suburban, and rural in nature, and characterized by sig-
nificant racial/ethnic and socioeconomic diversity. Four large aggregate
samples ranging in size from roughly 50,000 to 215,000 students have been
studied in 1990, 1995–1996, 1999–2000, and 2003 (a new aggregate sample
of roughly 60,000 students is being constructed from 2010 surveys but was
not available for analysis at the time of this writing).
In each of those large studies, assets have been scored on a binary basis
(a youth has or does not have the asset), yielding a total number of assets
experienced. Each of the samples was divided into quartiles based on this
total number of assets, and the quartiles compared on their mean scores
on 10 risk behavior patterns (e.g., problem alcohol use, engaging in violent
behavior) and eight indicators of thriving (e.g., high GPA at school, per-
sistence in the face of adversity). Across those differing samples spanning
two decades, the same patterns relating assets to developmental outcomes
have been observed: For nearly every outcome, every increase in
the quartile level of assets experienced (e.g., going from 0–10 assets
to 11–20, or from 21–30 assets to having 31–40) is associated with a
significant increase in mean outcome scores. Because the very large
sample sizes can be expected to render even small differences
statistically significant, we look both at effect sizes and at the differences
204 Peter L. Benson et al.
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in the proportion of youth experiencing outcomes, as a function of their
asset levels.
For example, Table II displays the standardized means and effect sizes
for the quartile differences in means on problem alcohol use and engaging
in violence (examples of the risk behaviors), and high grades in school and
feeling physically healthy (examples of thriving indicators). “Asset-rich”
youth, those with 31–40 of the 40 assets, are used as the reference group.
The effect sizes for the difference between asset-rich and asset-poor youth
are all equal to or greater than 1.0, a level well beyond what is tradition-
ally considered a “large”effect. Even the differences between asset-rich
youth and those with the next-highest level of assets, 21–30 or above-aver-
age, still are great enough to yield effect sizes in excess of .25. Although
Cohen (1988) heuristically described that level as a “small”effect, the
U.S. Department of Education’s What Works Clearinghouse has
established .25 as the level that signifies a “substantively important”effect
(p. 20). These results show most of the effect sizes to be well above that
substantively important criterion.
B. THE DIVERSITY HYPOTHESIS
Acritical concern about any framework for preventing youth problems
and promoting PYD is whether the approach works equally well for dif-
ferent groups of students, and if not, to understand better how to adapt
the approach as needed to strengthen its efficacy for different youth
populations. Throughout the varied studies Search Institute has conducted
over the past 20 years, the most consistent finding in this regard is that the
asset framework appears to have comparable validity across young
people’s gender, race/ethnicity, geographic residence, and socioeconomic
background. Although absolute levels of assets sometimes do vary in
these demographic comparisons, the effect sizes of those differences usu-
ally are quite small (Benson, Scales, Leffert, & Roehlkepartain, 1999).
More importantly, the patterns noted above, of higher levels of assets
being associated with lower levels of risk and higher levels of thriving,
are consistently replicated across those demographic groups
(Roehlkepartain, Benson, & Sesma, 2003; Scales et al., 2005). Girls gener-
ally have a higher average number of assets than boys (e.g., Scales &
Leffert, 2004), but each gender shows the same patterns of correlation
between higher levels of assets and both lower levels of risk behaviors
and higher levels of thriving indicators. In one study more closely looking
at the developmental asset of service to others, the asset was found to
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Table II
Relation of Asset Quartiles to Selected Developmental Outcomes: Standardized Means and Effect Sizes
Total number of assets
F Statistic
Asset poor Average Above average Asset rich
0–10 Assets 11–20 Assets 21–30 Assets 31–40 Assets
M
Pooled
SD
Effect
sizes M
Pooled
SD
Effect
sizes M
Pooled
SD
Effect
sizes M
Pooled
SD
Effect
sizes
Problem
alcohol use
.45 .42 1.0 .26 .41 .56 .11 .28 .29 .01 ––F(3,131612)¼
4854.84***
Engaging in
violence
.61 .42 1.31 .37 .43 .69 .17 .36 .31 .06 ––F(3,131612)¼
6536.19***
High grades
in school
.08 .27 1.70 .19 .37 .95 .35 .44 .43 .54 ––F(3,131612)¼
4339.47***
Feel
physically
happy
.27 .41 1.49 .47 .35 1.17 .69 .44 .43 .88 ——F(3,131612)¼
6701.91***
Notes: *** p.0001. All variables standardized to mean of 0 and standard deviation of 1. Cohen’sdwas used to calculate effect sizes, using youth with 31–40 assets
as the reference group (M
1
), using the formula (M
1
M
2
/Pooled SD). Pooled SD ¼√(n
1
1)SD
12
þ(n
2
1)SD
22
/(n
1
þn
2
2), calculated for each pair of 31–40 asset
group with the other three quartile groups.
Author's personal copy

have a compensatory influence over socioeconomic status (SES). Poor
students who reported engaging in community service had scores on
school success measures that were much more like affluent students’
scores, whereas their poor peers who did not engage in service had signif-
icantly worse scores on those school success measures (Scales,
Roehlkepartain, Neal, Kielsmeier, & Benson, 2006).
C. THE DIFFERENTIATION HYPOTHESIS
The sheer number of developmental assets youth experience clearly has
considerable implications for their health and well-being, regardless of the
target outcome. But it would also strain credulity to imagine that every
outcome is affected similarly by exactly the same assets. Rather, in addi-
tion to the accumulation hypothesis, we have also hypothesized and found
through both stepwise and logistic regression analyses, that particular
clusters of assets are especially influential predictors of various outcomes,
both concurrently and longitudinally.
For example, in predicting GPA, youth who experienced in middle
school a cluster of assets that, for the most part, thematically suggests
community involvement (participation in after-school youth programs,
religious community involvement, service to others, engaging in creative
activities, and reading for pleasure) were three times more likely to have
Bþor higher GPAs 3 years later in high school than youth who did not
experience that cluster of assets as younger adolescents (Scales, Benson,
Roehlkepartain, Sesma, & van Dulmen, 2006). Similarly, students who
experienced a cluster of assets thematically suggesting adherence to norms
of responsibility (positive peer influence, the value of restraint, spending
time at home, peaceful conflict resolution, and school engagement) were
twice as likely as other students to have high GPAs later in high school.
Likewise, several assets including positive peer influence, school engage-
ment, and the social skill of peaceful conflict resolution have been
identified in both our cross-sectional and longitudinal studies as the best
predictors of lower levels of antisocial behavior (e.g., stealing, vandalism)
and violence (e.g., physical fighting, threatening to hurt others; Benson &
Scales, 2009). Similar results have been found for other risk behavior
patterns (Leffert et al., 1998) and indicators of thriving (Scales et al.,
2000), that is, that several specific assets best predict concurrent and lon-
gitudinal (Roehlkepartain et al., 2003) outcomes, with the assets varying
depending on the outcome in question.
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III. Application of the Asset Framework to
Policies and Programs
The research base suggests the likely efficacy of a dual-pronged applied
policy and program strategy, of both attempting to build all 40 assets
throughout young people’s ecologies and especially targeting the promo-
tion of specific clusters of assets that will vary depending upon the PYD
goals of a program, organization, neighborhood, or community, for exam-
ple, whether they are promoting school success (Starkman, Scales, &
Roberts, 2006) or preventing substance abuse (Scales & Fisher, 2010).
One applied result of this research has found particular recent relevance
in the arena of school reform, an application that is likely to grow in
importance, given the high public policy priority given to the nonstellar
performance of U.S. students in relation to the rest of the world’s eco-
nomic powers. Across various Search Institute studies, nine of the assets
have been found in both bivariate and multivariate analyses to be the ones
most consistently linked to indicators of school success that have included
attendance, academic self-confidence, effort, sense of belonging to school,
grades, and test scores (Roberts & Scales, 2005; Scales & Benson, 2007;
Starkman et al., 2006). These assets—the “internal”assets of achievement
motivation, school engagement, bonding to school, reading for pleasure,
and the “external”or ecological assets of a caring school climate, parent
involvement in schooling, service to others, high expectations, and partici-
pation in high quality after-school youth programs—increasingly are being
used as both targets and measures to assess the effectiveness of school
reform efforts.
In a series of pilot studies Search Institute conducted in Hawai’iw
i
th
Kamehameha Schools (Scales & Tibbetts, in preparation), existing
measures of those nine assets were strengthened to be both more internally
consistent and more sensitive to detecting change-over-time, making them
appropriate to use for tracking purposes. For example, the Dallas Indepen-
dent School District will be surveying 50,000 middle- and high-school
students, from 2011 on, for at least the next 4 years, with both a global mea-
sure of assets (Search Institute’sDevelopmental Assets Profile (DAP),
described more fully below), and specific measures of several of the nine
“school success”assets, and tracking the relation of levels of and changes
in those assets with more ultimate measures of school success such as grades
and test scores, and other indicators of college and career readiness. Search
Institute also was awarded in 2010 one of just 49 (out of 1700 applicants)
highly competitive Investing In Innovation grants by the U.S. Department
of Education to replicate and expand over 4 years a successful student
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intervention program based on the assets framework—Building Assets
Reducing Risk (BARR)—in school districts in California, Maine, and
Minnesota, with the goals of reducing disciplinary problems, school failure,
and substance use, in part through promoting assets. As in the Dallas ISD, a
global measure of developmental assets is paired with the specific school
success asset measures, and other measures of school climate and success,
as part of the evaluation of the BARR program.
Another major application illustrates the use of asset-building as a PYD
strategy, in this case for achieving prevention goals. The RAND Corpora-
tion is leading a consortium including Search Institute and the Collaboration
for Children and Youth in Maine (the latter spearheaded by the Governor’s
Children’s Cabinet) in a landmark 5-year National Institute of Drug Abuse
effort to use asset-building to reduce substance use and other risk-taking
behaviors among Maine youth. A principal strategy is to train and provide
technical assistance to educators, youth workers, and others in using a
10-step, research-based logic model called assets getting to outcomes
(AGTO; Fisher, Imm, Chinman, & Wandersman, 2006)as a means of sys-
tematically building the capacity of community coalitions to promote assets
in the service of reaching those prevention goals. The research design
includes six community coalitions receiving the technical assistance on
developmental assets and the AGTO model, and six control coalitions not
receiving that intervention. A variety of measures are being used to assess
changes in coalitions’PYD-promotion capacity over time, and one of the
institute’s surveys, the DAP, is used to measure related changes in youth’s
experience of developmental assets (Chinman et al., in press). In addition,
a set of DAP implementation items was created that ask youth how much
the program undertook activities to try to increase particular assets. Thus,
for the first time, researchers will be able to directly link observations of
change in youth assets with youth reports of explicit program efforts to pro-
mote that change, thereby helping scholars and practitioners alike to better
understand how to build these developmental strengths.
IV. Research from New Measures of Developmental Assets
The Search Institute Attitudes and Behaviors: Profiles of Student Life
(A&B) survey is a 160-item instrument that includes measures of the 40
individual assets, numerous risk-taking behaviors, and several indicators
of positive behavior. It is the most widely used assets survey, accounting
for more than 80% of the more than 3 million assets surveys the institute
has administered over the past two decades. Its great strength lies in the
clarity and simplicity of its accompanying data reports, with the two
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primary metrics being the mean total number of assets youth report
experiencing, and the percentage of youth who experience asset-poor
(0–10 assets), average (11–20), above-average (21–30), or asset-rich
(31–40 assets) lives. Such ease of communicating results has fueled the
survey’s use as a mobilizing tool for communities. More than 3000 com-
munities have used the A&B results to organize and strengthen initiatives
to improve young people’s developmental experiences. As discussed
above, numerous research studies, using both cross-sectional and longitu-
dinal designs, have shown that the accumulation of developmental assets
as measured by the A&B survey (i.e., experiencing a relatively more
asset-rich life) is strongly linked to better youth developmental outcomes,
from lower substance use and violence to more volunteering and school
success (Benson & Scales, 2009; Benson et al., 1998, 2006; Leffert et al.,
1998; Scales & Leffert, 2004; Scales, Benson, et al., 2006; Scales et al.,
2000, 2004a). Along with these strengths, the survey has some limitations.
The measures of the 40 individual developmental assets reflect a mixture
of psychometrically stronger and weaker measures. A number of them
are measured with single items, for example, and a number of others have
internal consistency reliabilities below the standard of .70 for an accept-
able measure, and .60 for a promising one. Stability reliability is unknown
for most of the asset measures, making it impossible to assess their appro-
priateness for change-over-time applications. Thus, although the survey is
highly recommended for mobilization and communication purposes, it is a
lengthy survey, has uneven psychometric quality, and it is not appropriate
for the tracking, longitudinal, or program evaluation purposes that
increasing numbers of potential users wish to pursue.
To provide an alternative asset measure, Search Institute created the
DAP, a58-item instrument that measures the eight categories of develop-
mental assets originally identified by Search Institute scholars: support,
empowerment, boundaries and expectations, constructive use of time
(“external”relationships and opportunities provided by others for youth),
and commitment to learning, positive values, social competencies, and
positive identity (“internal”values, skills, and self-perceptions youth
develop on their gradual path to self-regulation). The survey provides sub-
scale scores for each of those eight asset categories and, by regrouping the
items, subscale scores that suggest how asset-rich young people’s asset
experience is in various life contexts: Personal, Social, Family, School,
and Community. Developed in 2005, the DAP was designed to be com-
pleted in 10–15 min, to be usable in both group administration and
individualized clinical settings, and to be sensitive to change-over-time.
It is the only assets survey that is an appropriate instrument for use in
pre–post program evaluation applications. Each of the eight asset category
210 Peter L. Benson et al.
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subscales, five context view subscales, internal assets scale, external assets
scale, and the overall DAP as a total scale have been found to have
acceptable internal consistency reliabilities (per Cronbach’s alpha) and
stability or test–retest reliabilities, and there is considerable evidence for
the DAP’s construct, convergent, discriminant, and predictive validity
(MGS Consulting, 2008; Search Institute, 2005; Wilson, O’Brien, &
Sesma, 2009). The singular drawback of utilizing the DAP is that it
measures assets at the level of the eight asset categories, whereas many
provocative research questions and applied youth development programs
focus on one or more of the 40 individual assets. Thus, since the DAP and
A&B offer different strengths and limitations, users are able to choose
either to serve as their primary data collection source on developmental
assets, depending upon their specific data needs.
Because of its brevity and psychometric quality as a PYD instrument, in
the past several years, scholars and practitioners around the globe have
requested to adapt and translate the DAP for use in their cultural con-
texts. As a result, the DAP has now been used in more than a dozen
countries, including Albania, Armenia, Azerbaijan, Bangladesh, Bolivia,
Brazil, China, Colombia, the Dominican Republic, Egypt, Gaza, Iraq,
Japan, Jordan, Lebanon, Mexico, Morocco, Nepal, the Philippines,
Rwanda, and Yemen. A detailed secondary analysis of data from five of
those countries with sufficiently sizeable datasets (Albania, Bangladesh,
Japan, Lebanon, and the Philippines), including comparative U.S. data,
concluded that most of the scales have acceptable reliability in other
languages than English and cultural settings other than the United States,
some of the scales have acceptable stability reliability, and there is evi-
dence of the DAP having comparable validity in those countries as with
U.S. samples (Scales, 2011).
Table III displays the percentages of youth in those five countries (and
the United States) that report experiencing various levels of developmen-
tal assets.
V. Tracking Change in Developmental Assets Over Time
Because the DAP was designed for pre–post applications (so long as sur-
vey administrations are at least 3 months apart), it is rapidly becoming an
instrument of choice to include in youth program evaluations and
assessments. It already is a principal instrument in a major quasi-experimen-
tal study of community coalitions’impact on PYD (the AGTO project in
Maine, described above); a large school district’s long-term strategic data
collection to assess its progress on College and Career Readiness for all
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Table III
Percentage of Youth, by Country, in Quartile Levels of Developmental Assets
Profile (DAP) Scores
United States Japan Lebanon Albania
Bangladesh Philippines
T
1
T
2
T
1
T
2
Overall DAP score quartiles
Poor
Fair
Good
Excellent
14
38
34
15
2
33
50
15
11
47
37
5
5
44
48
3
31
58
10
1
3
35
55
8
16
61
20
3
8
46
31
14
Support
Poor
Fair
Good
Excellent
16
28
31
25
28
31
26
15
15
25
41
18
7
19
43
31
37
43
16
2
2
25
56
17
15
44
33
9
9
31
43
17
Empowerment
Poor
Fair
Good
Excellent
8
31
33
28
20
43
27
10
12
41
34
13
49
41
8
2
45
44
8
3
1
48
37
15
19
51
24
6
14
36
34
15
Boundaries and expectations
Poor
Fair
Good
Excellent
16
29
34
22
26
34
28
12
13
31
38
17
5
17
43
34
30
41
23
5
4
23
39
33
15
39
35
11
8
28
39
25
Constructiveuse of time
Poor
Fair
Good
Excellent
26
38
22
14
43
41
12
4
42
36
15
7
18
47
27
8
42
51
7
5
6
49
30
16
39
44
13
5
24
40
24
13
Commitment to learning
Poor
Fair
Good
Excellent
19
30
34
18
34
35
24
7
23
33
32
11
4
17
49
31
18
34
36
11
6
18
44
31
11
42
37
10
8
31
40
22
Positive values
Poor
Fair
Good
Excellent
15
39
29
17
39
44
14
3
7
34
42
17
9
39
39
13
29
57
14
1
1
41
45
13
21
56
20
3
12
47
26
15
(Continued)
212 Peter L. Benson et al.
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Table III
(Continued )
United States Japan Lebanon Albania
Bangladesh Philippines
T
1
T
2
T
1
T
2
Social competencies
Poor
Fair
Good
Excellent
10
32
35
24
20
44
28
9
7
30
41
22
7
31
42
20
40
46
10
4
13
40
38
9
25
45
23
8
12
37
31
19
Positive identity
Poor
Fair
Good
Excellent
16
38
28
18
46
37
14
4
21
40
26
13
14
37
35
14
39
44
13
5
20
41
28
12
29
48
18
5
20
35
27
17
Personal
Poor
Fair
Good
Excellent
1
40
30
15
35
46
16
4
10
40
39
11
6
36
46
12
28
52
16
4
3
36
48
13
21
55
20
4
13
43
27
18
Social
Poor
Fair
Good
Excellent
12
34
31
23
21
44
26
9
7
37
38
18
7
39
43
10
48
41
9
2
17
44
31
8
24
54
18
5
12
42
29
17
Family
Poor
Fair
Good
Excellent
11
23
28
38
25
34
26
16
8
19
33
40
5
16
47
32
9
40
38
13
1
3
34
62
11
39
36
14
9
27
35
30
School
Poor
Fair
Good
Excellent
17
33
30
21
25
38
25
12
17
32
31
21
4
20
42
35
22
37
33
8
5
13
40
42
10
37
37
17
6
29
35
31
Community
Poor
Fair
Good
Excellent
19
42
27
13
50
37
10
2
33
44
18
5
24
51
22
4
68
28
4
0
16
54
22
8
35
51
12
2
22
43
23
12
N¼1312 13,946 1138 259 498 703
Note: This table was adapted from Scales (2011).
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students (Dallas ISD, described above); a new effort by the Salvation Army
to infuse PYD and asset-building to all of its youth programming across the
country; the replication and expansion in California, Maine, and Minnesota
of the Building Assets Reducing Risk program for promoting school suc-
cess, and the evaluation of that potentially landmark effort; and the mea-
surement of youth development programs worldwide.
Regarding its use globally, the DAP was a primary data collection
instrument in two youth development initiatives in Bangladesh and the
Philippines. The Bangladesh effort focused on providing basic educational
and social competence skills to young girls—an especially vulnerable pop-
ulation in that country—and the Philippines effort was a program to pro-
vide education and livelihood skills to out of school youth in a region that
had suffered considerable conflicts and religious tension, as a way of con-
necting those youth more to mainstream institutions of school and work,
and lessening their attractiveness as recruits for extremists. In both
countries, youth participated in the PYD programs for 6–9 months, and
the DAP was administered at the beginning and end of the programs. In
Bangladesh, there also was a control group of girls included in the
research design, with girls randomly assigned to intervention or control
conditions. In each country, considerable gains in youths’assets were seen
from pre- to posttest, 12% in the Philippines and 30% in Bangladesh.
Even after statistically accounting for contamination and control group
effects, the net gain in Bangladesh was 24%, as displayed in Figure 1.
The mean increase in asset level was from a “fair”experience of assets
to a “good”one, a change that, in U.S. samples, has been linked to signifi-
cant differences in well-being outcomes, such as a 53% drop in youth
engagement in violence and a 79% increase in youth getting high grades
in school (Scales, 2011). Those results demonstrated both the potential
of PYD programs to significantly affect youths’developmental assets,
and the ability of the DAP to detect such change, in non-U.S. settings.
A. EXPANSION OF THE ASSETS FRAMEWORK TO YOUNGER
CHILDREN AND YOUNG ADULTS
The assets framework originally was developed out of a review of the
literature on adolescent development, but conceptually it has apparent
relevance for younger and older age groups as well. A considerable body
of research has been synthesized to demonstrate the framework’s theoret-
ical utility for research and program development during early childhood
(VanderVen, 2008)and middle childhood (Scales et al., 2004a). Although
essentially the same 40 assets have been elaborated throughout the first
214 Peter L. Benson et al.
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two decades of life, distinct accents and points of emphasis have also been
described so that the assets have unique developmental integrity at each
of the different age ranges of 3–5, 5–9, 9–12, and 12–18. More recently,
similar although not yet as comprehensive synthesis work has been
conducted to develop a revised framework of developmental assets for
the period of young or emerging adulthood (Scales et al., in press). The
research reviewed for this effort amply demonstrates that although the
transition to new roles characterizes the essence of young adulthood,
the social and psychological processes at work are much the same as in
the first two decades of life. Other efforts have addressed pathways to suc-
cessful young adult development, and defined what successful young
adulthood entails (Schorr & Marchand, 2007), but are essentially about
what adolescents need subsequently to have a successful young adulthood.
The new assets framework for young adulthood, however, describes what
young adults need during those years from 18 to 25 in order to enjoy cur-
rent well-being and successful transition to later life.
A survey has been developed to measure the 40 individual assets in
4th–6th graders—Search Institute’sMe and My World survey (Scales,
Sesma, & Bolstrom, 2004b)—that shows generally acceptable evidence
of reliability and validity across the asset measures. In addition, a Devel-
opmental Assets Profile for preteens (DAP-P), measuring assets at the
level of the eight categories of assets, is in pilot testing in several sites in
24%
29% 30%
0%
5%
10%
15%
20%
25%
30%
35%
DAP score change
Net minus control Minus contamination
Gross
Fig. 1. Bangladesh net DAP score change, T
1
–T
2
(6–9 months).
215The Contribution of the Developmental Assets Framework
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2010–2011, with versions for children in grades 3–5 and parents of children
in grades K-3 being tested. A new survey measuring the 40 individual assets
for young adults ages 18–25 has also been developed—the Search Institute
Young Adult Developmental Assets Survey—and is undergoing pilot testing
at several universities in 2010–2011. At the conclusion of the various survey
tests, by early 2012, it is anticipated that there will be a fleet of conceptually
and theoretically sequenced, and psychometrically strong, measurement
tools available for assessing the developmental assets experience of chil-
dren, youth, and young adults from Kindergarten to age 25.
Me and My World: A Search Institute Survey of Developmental Assets
for Grades 4 Through 6 (MMW)(Scales et al., 2004b) is the first survey
for 4th–6th graders specifically focused on measuring Developmental
Assets
TM
. Through MMW, 4th–6th graders can report on their experience
of the 40 developmental assets identified by Search Institute that have
been shown to contribute to lessened risky behavior and greater thriving
and resilience in the face of challenge. The MMW survey is conceptually
based on the survey Search Institute has used for two decades to study
the developmental assets of 6th–12th graders—the Search Institute A&B
survey—and assesses positive experiences that research shows are partic-
ularly important for the developmental well-being of upper-elementary
children (Scales et al., 2004a). The survey was piloted among 191, 4th–5th
graders in New Brighton, Minnesota; 402, 4th–6th graders in Norman,
Oklahoma; and 411, 4th–6th graders in Oklahoma City, Oklahoma. The
pilot tests suggested extensive revisions, which were incorporated into a
new version that was field-tested in 2003 with nearly 1300 4th–6th graders
in California, Nevada, and New York. After field-testing, several addi-
tional revisions were made to improve the survey.
A relatively large dataset of completed MMW surveys was created
by aggregating surveys from 6927 4th–6th grade students from 23 U.S.
communities in 10 states, who were administered the survey in calendar
2008. The sample was evenly divided between boys and girls, and
included 46% in the 4th grade, 33% in the 5th grade, and 21% in
the 6th grade. The sample was racially/ethnically diverse, with 61%
being white, 12% Hispanic/Latino, 9% multiracial, 8% African-American,
2% each Native American and Asian, less than 1% Hawai’ian, and 5%
other.
Consistently, the accumulation of multiple assets is strongly related to
better developmental outcomes among 6th–12th graders, with youth
reporting each successively higher quartile of the assets (0–10, 11–20,
21–30, and 31–40) almost always reporting significantly better outcomes.
The 2008 aggregate sample data show that the same patterns hold for
4th–6th graders, as displayed in Table IV.
216 Peter L. Benson et al.
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On six of the seven positive behavior outcome variables (86%), every
level of increase in the assets students report experiencing is associated
with a significantly better outcome, and on the seventh outcome, cor-
egulation, students with the two highest levels of assets do better
than students with only average levels of assets, who, in turn, do better
Table IV
The Relationship Between Asset Levels and Thriving and Risk Indicators Among 4th–6th
Grade Students
Total number of assets
Asset
poor Average
Above
average
Asset
rich
F Statistic
0–10
Assets
11–20
Assets
21–30
Assets
31–40
Assets
High grades .49
d
.66
c
.77
b
.88
a
F(3,5808)¼
116.53***
Helps others .27
d
.54
c
.73
b
.91
a
F(3,5877)¼
320.01***
Values diversity .50
d
.71
c
.83
b
.94
a
F(3,5900)¼
175.17***
Delays gratification .16
d
.33
c
.50
b
.74
a
F(3,5899)¼
273.52***
Shares in self-regulation
with parents
.71
c
.79
b
.82
a,b
.87
a
F(3,5894)¼
23.41***
Has coping skills .14
d
.25
c
.44
b
.71
a
F(3,5854)¼
310.17***
Has life satisfaction .43
d
.61
c
.82
b
.94
a
F(5867)¼
290.29***
Uses alcohol .15
c
.09
b
.03
a
.03
a
F(3,5836)¼
46.40***
Smokes cigarettes .08
c
.04
b
.01
a
.01
a
F(3,5837)¼
38.91***
Uses marijuana .08
b
.03
a
.01
a
.01
a
F(3,5824)¼
26.07***
Engages in vandalism .20
c
.09
b
.03
a
.01
a
F(3,5838)¼
91.33***
Commits aggressive or
violent acts
.40
d
.27
c
.16
b
.08
a
F(3,5826)¼
110.87***
Is often sad .48
b
.43
b
.43
b
.36
a
F(35,834)¼
17.46***
N¼283 1321 2387 1877
Notes. *** p.0001. All variables standardized to mean of 0 and standard deviation of 1. Standardized
means in the same row, with differing superscripts, are significantly different from each other.
217The Contribution of the Developmental Assets Framework
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than the students with the lowest levels of assets. The risk behaviors do
not show as dramatic a linear association between assets and outcomes,
simply because so few of these younger students in upper-elementary
grades, relatively speaking, report engaging in those negative behaviors.
Even here, however, lower levels of assets are linked to poorer scores
on the outcomes, that is, a higher likelihood of experiencing risky
behaviors. For most of the risk indicators, students in the top two
levels of assets have about same outcome scores, but for aggression/
violence and sadness, the asset-rich students are better off than all other
students.
Overall, the MMW measures of the school success assets for 4th–6th
graders show the same kinds of patterns by demographics, and the same
kinds of links to developmental outcomes, as seen for asset measures
developed for older youth. Girls and younger students tend to have
more of the assets (Scales et al., 2004a), and the more of these assets
upper-elementary students have, the fewer high-risk behaviors they
engage in, and the more they report engaging in positive behaviors. These
results suggest a good base of construct validity for the 4th–6th grades
asset measures. A majority of the 4th–6th grade measures also showed
acceptable to good internal consistency reliability (Scales et al., 2004b).
VI. Developmental Asset Profiles
To date, nearly all the research on developmental assets has been vari-
able centered. For this chapter, we also undertook a person-centered
approach, using latent class analysis (LCA) to identify classes or sub-
groups of youth, differentiated on the basis of their respective patterns
of reported assets. Variable-centered analysis is useful in understanding
the typical or average experiences of young people but leaves unexplored
the interindividual variability and complexity that is a hallmark of human
growth. A person-centered approach, by naming patterns of asset com-
binations that seem to characterize young people, also offers additional
applied lessons for program responsiveness and organizational change to
better the developmental opportunities youth experience. For example,
differing PYD strategies may be implicated for young people (and the
adults around them) who seem to be lacking in social competencies, and
yet somehow seem to experience considerable social support, and those
who are lacking in both social competencies and social support. We briefly
present here the highlights of the LCA. Additional methodological details
may be found in a forthcoming paper (Syvertsen, Scales, & Benson, in
preparation).
218 Peter L. Benson et al.
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A. METHOD AND MODEL INDICATORS
The eight asset categories—for example, support, constructive use of
time, positive values, social competencies, described in Table II—were
used to fit the developmental asset profiles. To focus our analyses on those
asset categories present in youths’lives, a score of “1”was assigned to
youth who had 50% or more of the assets in a given category, while a
score of “0”was assigned to those with less than 50% of the assets. The
frequencies of youth having 50% or more of the assets in a category
ranged from 36% (social competencies) to 66% (positive values), with
about half of youth having 50% or more for each asset category.
B. LATENT CLASS DESCRIPTIONS AND MEMBERSHIP
Statistical fit indices were used to identify the best fitting model. Four sub-
groups of adolescents with distinct constellations of developmental assets
emerged: Supported–Competent–Confident,Supported Social Marginal,
Unsupported Engaged, and the Unsupported–Unengaged–Unconfident.
These labels were assigned based on the pattern of item–response pro-
babilities for each class. The item–response probabilities summarized in
Table V represent the probability of having 50% of the assets in a category
conditional on membership in a specific latent class.
The Supported–Competent–Confident class is definedbyhighprobabilities
of having half or more of the assets in all eight asset categories. More than a
quarter (27%) of participants displayed this rich constellation of external
and internal assets. These analyses reveal that one out of every four
adolescents in this dataset reported having 50% or more of the support,
empowerment, boundaries, and expectations, constructive use of time, com-
mitment to learning, positive values, social competencies, and positive iden-
tity assets. In stark contrast, the Unsupported–Unengaged–Unconfident
class—best representing 29% of adolescents in this sample—is characterized
by low probabilities of having any of the eight asset categories. The promi-
nence of this response pattern in the data gives us cause for concern as it
suggests that nearly one-third of adolescents are unlikely to experience at
least half of the assets in each category.
The Supported Social Marginal and Unsupported Engaged classes are
defined by more nuanced response patterns. Adolescents estimated to
fit in the Supported Social Marginal class have moderate probabilities
of having 50% or more of all four external asset categories as well as
a high probability of embracing a positive self-identity. These
adolescents are likely to feel supported by the contexts that structure
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Table V
Probabilities of Having 50% of the Assets in an Asset Category and Prevalence of Latent Class Membership
Parameter
Latent classes
Supported–
Competent–
Confident
Supported
Social
Marginal
Unsupported
Engaged
Unsupported–
Unengaged–
Unconfident
GSE GSE GSE GSE
Class
Membership
Prevalence
Full sample .27 .002 .20 .004 .24 .004 .29 .003
Random subsample
range
.24–.30 –.16–.27 –.17–.28 –.24–.33 –
Item–Response Probabilities PSE PSE PSE PSE
External asset categories
Support Full sample .92 .003 .61 .008 .24 .006 .05 .002
Random subsample
range
.89–.94 –.51–.67 –.16–.30 –.02–.07 –
Empowerment Full sample .81 .003 .58 .006 .25 .005 .15 .003
Random subsample
range
.78–.84 .50–.67 –.23–.32 –.12–.18 –
Boundaries and
expectations
Full sample .94 .002 .59 .006 .59 .005 .17 .003
Random subsample
range
.92–.96 –.49–.64 –.54–.62 –.14–.20 –
Constructive use
of time
Full sample .84 .002 .63 .005 .67 .004 .38 .003
Random subsample
range
.82–.85 –.59–.67 –.62–.71 –.22–.42 –
Internal asset categories
Commitment to
learning
Full sample .89 .002 .41 .006 .65 .005 .13 .003
Random subsample
range
.88–.91 –.35–.45 –.59–.69 –.11–.15 –
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Positive values Full sample .97 .002 .54 .007 .87 .004 .28 .003
Random subsample
range
.95–.98 –.45–.58 –.83–.94 –.24–.32 –
Social
competencies
Full sample .79 .004 .11 .006 .48 .006 .04 .002
Random subsample
range
.73–.83 –.06–.16 –.41–.59 –.02–.05 –
Positive identity Full sample .92 .002 .79 .005 .53 .005 .36 .003
Random subsample
range
.91–.94 –.72–.85 –.51–.59 –.31–.38 –
Notes. The probabilities of having 50% of the assets in an asset category are reported. The full sample was 155,927 participants. To assess model fit, 10 random
subsamples of n¼5000 were drawn. To demonstrate the similarity between the 4-class model in the full sample and in the random subsamples, the range of
item–response probabilities (rho estimates) for these 10 subsamples are also reported. Bold typeface was used to highlight those item–response probabilities in the
moderate to high range (.55–1.0).
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their daily lives and cared for at home, at school, and by their com-
munities. Moreover, these adolescents feel good about themselves and
their future. Yet, they are unlikely to possess a strong commitment to
school and learning, positive values, and the skills to competently handle
social situations. Thus, while these adolescents may feel supported by
others and confident about themselves, they are likely to be at the mar-
gins of social situations. One in five adolescents (20%) displayed this
asset profile. The Unsupported Engaged class is best characterized by
moderate probabilities of having half or more of the boundaries and
expectations, constructive use of time, and commitment to learning asset
categories and a high probability of having positive values. Despite feel-
ing unsupported and unempowered at home, school, and in the commu-
nity, the 24% of adolescents estimated to fit in this class feel bound by
others’expectations, find themselves constructively engaged in school
and community activities, and are likely to espouse a prosocial orienta-
tion toward values like caring, responsibility, restraint, integrity, and a
commitment to equality and social justice.
C. MULTIGROUP ANALYSES
Gender, school level, race/ethnicity, and mothers’education were
added, separately, to the 4-class LCA model as grouping variables to iden-
tify differences, if any, in adolescents’item–response probabilities and
latent class membership (Collins & Lanza, 2010). The 4-class LCA model
with the item–response probabilities held invariant across each of the
groups was selected.
Table VI displays the prevalence of adolescents, broken down by grouping
characteristics, in each latent class. Females were more likely than their male
peers to be fitintheSupported–Competent–Confident and Unsupported
Engaged classes, while males were more likely than females to be in the
Supported Social Marginal and Unsupported–Unengaged–Unconfident clas-
ses. Comparisons of middle- and high-school-aged adolescents revealed an
interesting, although unsurprising, developmental pattern. While middle-
and high-school students shared similar probabilities of being fitintothe
Supported Social Marginal and Unsupported Engaged classes, younger
adolescents were more likely to be in the Supported–Competent–Confident
class, while older students were more likely to be in the
Unsupported–Unengaged–Unconfident class. These LCA findings reflecting
a better asset profile for younger adolescents and girls quite neatlymirror var-
iable-centered analyses that repeatedly have found the same patterns (e.g.,
Benson et al., 1998; Scales & Leffert, 2004).
222 Peter L. Benson et al.
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Table VI
Prevalence of Latent Classes by Gender, School-Level, Race, and Family SES
Class
membership
prevalence
Full
sample
Latent classes
Supported–
Competent–
Confident
Supported
Social
Marginal
Unsupported
Engaged
Unsupported–
Unengaged–
Unconfident
%GSE GSE GSE GSE
Gender Males 49 .19 .003 .34 .004 .11 .003 .36 .004
Females 51 .33 .003 .09 .003 .37 .004 .21 .003
School level 6th–8th Grade 43 .35 .003 .20 .005 .22 .005 .23 .003
9th–12th Grade 57 .20 .002 .19 .005 .26 .005 .34 .003
Race/ethnicity American
Indian
2 .21 .009 .26 .013 .18 .012 .35 .013
Asian 3 .22 .008 .04 .007 .47 .011 .26 .007
Black 7 .21 .006 .33 .010 .23 .009 .22 .010
Hispanic 6 .18 .005 .15 .007 .30 .008 .37 .007
White 76 .28 .003 .21 .004 .22 .004 .29 .004
Multiracial 7 .22 .005 .19 .007 .27 .008 .32 .007
Mothers’
education
More than HS 64 .32 .003 .24 .003 .23 .005 .24 .003
HS or less 36 .19 .003 .37 .004 .25 .005 .37 .004
Notes. All comparisons were tested in separate multigroup LCA analyses. In each analysis, item–response probabilities were constrained to be equal across
groups. With the exception of Family SES, participants self-identified group membership.
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Unsupported–Unengaged–Unconfident was the most prevalent class for
American Indian (35%), Hispanic (37%), and Multiracial (32%)
adolescents (and also included a large proportion—29%—of White
youth), while nearly half of Asian adolescents (47%) fit into the Unsup-
ported Engaged class and one-third of Black adolescents (33%) fit into
the Supported Social Marginal class (a class that was nearly devoid of
Asian adolescents). Compared to adolescents of different races and
ethnicities, White adolescents were the most likely to be in the
Supported–Competent–Confident class. Adolescents whose mothers had
a high-school education or less were disproportionately fit into the
Supported Social Marginal and Unsupported–Unengaged–Unconfident
classes, as compared to those whose mothers had obtained some postsec-
ondary training. Using mothers’education as a rough proxy for familial
SES, these data suggest that adolescents from high SES families are more
likely than their peers from low SES families to experience an adequate
and diverse array of developmental assets.
D. THRIVING AND RISK BEHAVIOR
To further understand the correlates of being estimated to fitinany
given latent class, we tested the association between latent class member-
ship and two behavioral indices: thriving (e.g., school grades, help-giving
behavior) and risk (e.g., substance use, fighting) behavior. The effects of
the thriving and risk behavior covariates were both highly significant.
Consistent with our expectations and previous variable-centered
analyses (Scales et al., 2000), we found that a one standard deviation
increase in thriving is associated with increased odds of being in the
Supported–Competent–Confident (OR ¼40.83), Supported Social Marginal
(OR ¼4.94), and Unsupported Engaged (OR ¼8.71) as compared to the
Unsupported–Unengaged–Unconfident class. Similarly, the odds of
membership in the Supported–Competent–Confident (Inverse OR ¼125),
Supported Social Marginal (Inverse OR ¼1.84), and Unsupported
Engaged (Inverse OR ¼5.56) classes, relative to the
Unsupported–Unengaged–Unconfident class, increased with a standard
deviation decrease in risk behavior, a result also in line with previous vari-
able-centered analysis (Leffert et al., 1998) and person-centered
(Syvertsen, Cleveland, Gayles, Tibbits, & Faulk, 2010) analyses.
In other words, compared to their peers fiti
nt
he
Unsupported–Unengaged–Unconfident class, youth in the asset-rich
Support–Competent–Confident class had much greater odds of engaging
in thriving and refraining from risk behaviors. While this also held true
224 Peter L. Benson et al.
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for youth in the Supported Social Marginal and Unsupported Engaged
classes as well, the odds of thriving and decreased risk (when expressed
as inverse odds ratios) were substantially lower. The pattern of these
findings suggests that youth estimated to fit in the Supported Social Mar-
ginal class are only slightly better off than their peers in the
Unsupported–Unengaged–Unconfident class.
VII. Next Steps in Research and Practice
The growing research on developmental assets supports many of the
hypotheses central to the theory of PYD (Benson et al., 2006). Among
these are
developmental nutrients such as assets are cumulative for enhancing
thriving and reducing risk behaviors;
developmental ecologies (e.g., schools, after-school programs) can be
intentionally altered to enhance developmental assets;
ecologies are also cumulative, in the sense that youth gain strength
when multiple ecologies support and nourish assets;
persons (in this case, youth) and contexts are in dynamic relationship to
each other such that contexts inform assets and youth, by their actions,
can change contexts; and
particular clusters or “packages”of developmental strengths are influ-
ential predictors of various outcomes, both concurrently and
longitudinally.
This said, we would argue that the research underpinnings for PYD can
and should be strengthened, as well as critical applied implications. Five
key challenges and opportunities are the lack of longitudinal research in
this arena, the possibilities and pitfalls of growing international interest
in the developmental assets approach, the maturation of the applied sci-
ence of turning ecologies into asset-building contexts, the activation of
all sectors as asset-building forces, and the stimulating of widespread
social change that turns asset-building into a national movement.
A particularly glaring “hole”in the literature has to do with longitudinal
research. Although as a collective the studies on developmental assets have
been quite consistent in their findings, the great majority have been cross-
sectional and correlational. Thus, we continue to lack the kinds of focused
studies that help clarify the role of asset-building interventions in a wide
range of critical issues, including successful transitions into middle school
and high school, the prevention of risk behaviors, the enhancement of
thriving, and the successful launch of youth into adulthood. All these foci
225The Contribution of the Developmental Assets Framework
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require longitudinal designs to more validly link change in the experience of
developmental assets to particular future developmental outcomes.
The spread of the asset model to many other nations presents some
important opportunities for both knowledge and practice. A global system
of research and consulting needs to be developed to both better ensure
responsible applications, and to discover how well the model addresses
and promotes healthy development in emerging and transitional as well
as developed nations. A particularly challenging issue is to ensure the cul-
tural equivalence of developmental assets surveys in a manner that allows
rapid adaptation and, therefore, more widespread use of those measure-
ment tools.
One of most surprising lacunae in the understanding of developmental
assets is how to build more asset-building environments for young people.
Central to the idea of PYD is that developmental contexts (e.g., schools,
families, neighborhoods, programs) matter for promoting the develop-
mental nutrients youth need to succeed in life. Given this obvious truth,
one would think that there is a robust science on how to change less
asset-building ecologies into more vibrant asset-building ones. Other than
the more narrowly focused prevention programs that have traditionally
dominated the youth development field, there are at best, however, only
episodic and sporadic efforts to (a) develop a science-based approach to
ecological change, (b) orchestrate that change, (c) measure change in
the intended context, and (d) assess how context changes actually inform
individual-level development. Until this science develops and matures, the
promise of PYD for changing outcomes will be limited.
A fourth issue is broadening the participation of various sectors in asset-
building. PYD principles embodied in the developmental asset model
have moved quickly into some areas of practice. Schools, after-school pro-
grams, and community-building initiatives are among the formal settings
that have embraced this approach. The model of asset-building, however,
explicitly and intentionally, requires the activation of two sectors that are
both more difficult to reach and essential for raising asset-rich youth. The
first is family; however, it is constituted. Family adults, we would hypoth-
esize, have disproportionate power for promoting assets. Simultaneously,
parents and guardians serve as gatekeepers for how youth access quality,
asset-building community resources. If we are to strengthen the asset
infrastructure for young people, a major national initiative to reach and
equip families is necessary.
The second sector that is critical but underutilized is the general public.
Awakening public engagement requires a shift in national consciousness
toward the idea that “all kids are our kids.”This idea is not a central
organizing principle in the United States (Benson, 2006; Scales et al.,
226 Peter L. Benson et al.
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2003). Changing the public mindset may seem a Herculean task, but until
this shift happens, much of the best energy for asset-building lays dormant.
Finally, there is the issue of social change and its role in elevating the asset
profile of a nation’s youth. As we have noted earlier, a considerable volume
of research on developmental assets (and aligned frameworks like the 5
Promises of America’s Promise Alliance—Scales et al., 2008)documents
that many and perhaps most middle- and high-school youth in the United
States experience low rather than high levels of critical developmental nutri-
ents. Youth policy and funding in the United States is largely shaped around
specific outcomes like school graduation rates/test scores or substance abuse
prevention and rarely around the kinds of developmental building blocks/
nutrients/assets that are so critical for the production of those and numerous
other outcomes. Orchestrating national efforts around enhancing critical
“inputs”for success is long overdue. In this regard, there may be something
to be learned from the role of comparative studies in motivating action. In
the first decade of the twenty-first century, for example, much has been
made of international studies of math and science test scores and high school
and college graduation rates. As the United States slides down the interna-
tional rankings of developed nations on these kinds of measures, policy and
funding is rallied around these issues. To mobilize a similar kind of wake-up
call around developmental “inputs,”an international comparison of youth
developmental assets just might provide both a sobering national portrait
and the spark that fuels a national call to action.
The irony in such national “calls,”of course, is that these actions to
improve the lives of individuals invariably improve national well-being.
This relationship demonstrates at a grand scale the enduring validity of
a staple principle of developmental systems theories, namely, that truly
adaptive development enhances both the individual and the context. In
this sense, thriving civil society and thriving young people go hand in hand
(Benson & Scales, 2009; Lerner, 2004; Lerner, Brentano, Dowling, &
Anderson, 2002; Scales, Benson, & Roehlkepartain, 2010). Thus, the
stakes for both scholars and practitioners to better understand and more
widely apply the framework of developmental assets and the science of
PYD could not be higher.
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