What Are Kids Getting Into These Days?
Demographic Differences in Youth Out-of-School Time Participation
Christopher Wimer, Research Assistant
Suzanne M. Bouffard, Research
Analyst
Pia Caronongan, Research Assistant
Eric Dearing, Consultant
Sandra Simpkins, Consultant
Priscilla M. D. Little, Associate
Director
Heather Weiss, Director
Harvard Family Research Project
March 2006
Abstract: With support from the William T. Grant Foundation, Harvard
Family Research Project (HFRP) is conducting a research study on the factors
associated with whether children and youth participate in out-of-school time
(OST) programs and activities. Building on our previous work, we are using national
data to examine the many factors and contexts in children's lives that predict
participation.
This research brief distills findings from the first phase of the study, which
examines demographic differences in youth's OST participation rates. It first
provides information on current demographic differences in OST participation
rates, and then looks at whether there is any evidence that such differences
have changed in recent years. The brief concludes with implications for practitioners,
policymakers, and researchers.
Download the executive summary:
Download the full report:
Executive Summary
Out-of-school time (OST) programs and activities constitute a vital set of
complementary learning supports-that is, nonschool supports for children and
families that can enhance and promote learning and development by complementing
school-day efforts.1
Research demonstrates that participation in various structured OST contexts
benefits youth socially, emotionally, and academically2
and may have the most positive effects for youth who are most at risk.3
As a result, attention to measuring and promoting participation in these OST
contexts has grown among a broad range of stakeholders. However, little research
has explored the questions of who participates and why. This research is crucial
in order to address issues of access and equity, to document service gaps, and
to target resources accordingly.
This research brief provides reliable estimates of the numbers and characteristics
of youth across the country who participate in structured OST programs and activities.
It uses two nationally representative data sets, the Panel Study of Income Dynamics—Child
Development Supplement and the National Survey of American Families, to examine
whether there are differences in participation in a variety of OST contexts
among youth from varying family income levels and youth from varying racial
and ethnic groups. It also examines whether any such differences have changed
over recent years. It considers participation in any structured OST context,
including before and after school programs, other structured OST programs (e.g.,
community programs and recreation programs), and other structured OST activities
(e.g., school-based extracurricular activities and religious clubs and activities).
Key Findings
- Across virtually all OST contexts, youth from higher income families
were more likely to participate than youth from lower income families. This
held for before and after school programs, other OST programs, and other OST
activities. This finding suggests a continuing need to target nonschool
resources to the most disadvantaged youth. This is particularly important
given that our results show that these youth are also far less likely to participate
in other OST activities, such as lessons, clubs, and sports. Given evidence
of unmet demand for OST programs among disadvantaged families,4
there remains a clear need to target resources toward recruiting and retaining
these youth in OST programs and activities.
- For tutoring programs, however, youth from lower income families
were more likely to participate than youth from higher income families.
This finding may indicate that the academic deficits of disadvantaged youth
are limiting their ability to participate in other types of enrichment activities
and programs. Youth with academic deficits should continue to be a focus for
youth workers and other OST stakeholders.
- Across most types of programs and activities, Latino youth are consistently
underrepresented, and White youth are consistently overrepresented, with Black
youth somewhere in between. These differences may be generated by the
same factors driving socioeconomic gaps, though some factors specific to different
racial and ethnic groups may also be at work. For example, Latino youth's
low participation levels may also be partially driven by linguistic and cultural
differences between families, youth, and activity providers. This evidence
indicates a continuing need to focus resources on recruitment of minority
youth in a variety of OST contexts, with a particular need to concentrate
resources on serving underserved Latino youth.
- Black youth, however, showed particularly high participation rates in
some OST contexts, such as before and after school programs and summer camps.
Many after school and summer programs specifically target minority youth,
which may help explain why Black youth participate at relatively high rates
in these types of programs.
- The historical analysis revealed a general pattern of stability in demographic
differences in participation rates over the late 1990s. This finding indicates
a continuing challenge to practitioners and policymakers to assist in closing
gaps in youth OST participation rates.
- For before and after school programs, however, there have been increases
over time in participation rates at every level of family income, but the
increase was greatest among the lowest income youth, resulting in a narrowing
of the gap between youth from low-income families and youth from higher income
families. The increasing policy emphasis on OST programs, especially for
disadvantaged youth, is a likely contributor to the declining socioeconomic
gap in before and after school program participation. A key component of this
recent attention to disadvantaged youth has been the rapid increase in funding
for the federal 21st Century Community Learning Centers program.
What Are Kids Getting Into These Days?
Demographic Differences in Youth Out-of-School Time Participation
Out-of-school time (OST) programs and activities constitute a vital set of
complementary learning supports—that is, the nonschool supports for children
and families that can enhance and promote learning and development by complementing
school-day efforts.5
Among these opportunities, families report an interest in and unmet demand for
after school programs.6
Other structured nonschool activities, such as sports and arts lessons, also
enroll a large number of youth.
Research demonstrates that OST programs, extracurricular activities, and other
structured nonschool contexts benefit youth socially, emotionally, and academically7
and may have the most positive effects for youth who are at risk for academic
and social problems.8
As a result, attention to measuring and promoting participation in these activities
has grown among a broad range of stakeholders. However, little research has
explored the questions of who participates in OST programs and activities and
why. This research is crucial in order to address issues of access and equity,
to document service gaps, and to target resources accordingly. Previous studies
have examined reasons for participation in after school programs among ethnic
minority youth9
and have documented that at-risk urban youth are less likely to participate
in some extracurricular activities.10
However, in order to get a clearer picture of participation patterns and gaps,
we need reliable descriptions of youth participants from national research.
This research brief provides reliable estimates of the numbers and characteristics
of youth across the country who participate in structured OST programs and activities.
It uses two nationally representative data sets to examine whether there are
demographic differences in participation in a variety of OST contexts and whether
any such differences have changed over recent years. Additionally, this research brief has several features that make it unique and valuable for the field.
First, this research brief looks at participation in a variety of OST contexts,
including community-based and school-based after school programs, sports teams,
arts lessons, extracurricular activities, and summer camps. Youth have a number
of competing opportunities and responsibilities in the nonschool hours,11
and many participate in several types of programs and activities.12
For example, some youth may participate in a school-sponsored drama group two
afternoons per week and attend the Boys & Girls Club program in their neighborhood
on the other three afternoons. In order to understand the big picture of participation
and the current needs of youth, it is important to look at participation across
this constellation of contexts.13
By examining all of these activities, we can discover broader patterns-for instance,
whether disadvantaged youth participate less in all OST contexts or in fact
participate more in some contexts (e.g., after school programs) and less in
others (e.g., paid arts lessons) than their peers.
Second, this research brief examines whether participation patterns have changed
over time. Of particular interest is the question of whether disadvantaged youth
have become more likely to participate in structured OST contexts in the past
decade. The OST field has grown rapidly since the early 1990s14
due to several factors. One important development was the establishment of the
21st Century Community Learning Centers initiative, which has increased financial
and social investments in before and after school programs for low-income youth.
Other major policy changes have also contributed to the growth of the field,
including the welfare reform efforts of the 1990s. Welfare reform meant that
more low-income parents entered the workforce and needed positive, supervised
contexts for their children in the nonschool hours. Some welfare-to-work initiatives
included funding for OST care.15
The participation trends described in this research brief have important
implications for OST practitioners and policymakers. They document both progress
and challenges. We report evidence of gaps in service for youth from certain
backgrounds and point out the need to target programming, as well as recruitment
and retention efforts, to disadvantaged youth, who are the least likely to participate
in many activities, and who may be, paradoxically, most likely to benefit. However,
our results also reveal some positive trends, particularly a narrowing of the
income gap in before and after school program participation over the past half
decade.
Research Methodology
This study uses two nationally representative data sets that provide rich information
on OST participation and the family characteristics and contextual factors that
may be associated with participation. It examines differences in participation
according to family income16
and race/ethnicity. Differences by child's gender were also examined, with results
indicating little evidence of consistent gender inequality across OST programs
and activities (although boys participated more in athletics and recreation
programs and girls participated more in lessons and school-based extracurricular
activities). For simplicity, the gender results are not presented in this research
brief but are available from the authors on request.
The Panel Study of Income Dynamics (PSID)
The Panel Study of Income Dynamics (PSID) is a national survey study that collects
data on individuals from over 7,000 families. This study began in 1968 and is
still ongoing, continuously expanding to include families of children from earlier
waves who have now become heads of households themselves. The PSID's Child Development
Supplement (PSID/CDS) began in 1997, in order to gain detailed information about
children's experiences, and is based on information from children, their caregivers,
and other important figures in their lives. In its initial year, the PSID/CDS
consisted of over 3,500 randomly selected 0–12-year-old children from the
main PSID sample. A second wave of data was collected in 2002 for nearly 3,000
children whose families had remained active in the study. OST activity data
for the current study are taken from the 2002 wave, when children were ages
5–19.
The National Survey of American Families (NSAF)
The National Survey of American Families (NSAF) collected data on the well-being
of nationally representative samples of families in 1997, 1999, and 2002. While
different families were included each year, sample sizes are similar across
all 3 years with information about 40,000 children in over 30,000 families.
Information about children was obtained from the most knowledgeable adult in
the household for each child, who, for convenience, we will call the child's
caregiver throughout this research brief. In addition, demographic information
was also collected at the household level. The current study presents data from
all 3 years of the survey.
Research Measures
Demographic Variables
- Income – We created five family income categories, or quintiles,
by dividing total family income by family size and dividing the sample into
five groups, with the highest income families in the top quintile and the
lowest income families in the bottom quintile. For the PSID, total family
income was obtained by averaging each family's income from 1994–2000,
while total income from the previous year was used for the NSAF.
- Race/ethnicity – Race/ethnicity categories were created for
each child based on caregiver interviews. Because of sample sizes, and to
ensure comparability between the two datasets, we examine participation rates
for White, Black, and Latino youth only.
Participation in OST Programs and Activities
PSID
We used activity participation indicators from the 2002 child and caregiver
interviews of the PSID. (Appendix Table 1 provides the exact wording of questions
from the PSID). When questions were worded in terms of youth's intensity or
frequency of participation, we created an indicator from these questions measuring
any participation versus no participation. Youth ages 10–19
were asked about their participation in school-based extracurricular activities
and organized sports or recreation programs occurring after school or during
the summer, while caregivers were asked about youth's participation in before
and after school programs, summer camp, and Scouting. More specifically:
- Caregivers of all children were asked if the child was a member of any group
or program in the community in the last 12 months, where groups or programs
in the community included Scouts, service, or hobby clubs.
- Caregivers of all children were asked how often the child had participated
in any tutoring programs, Scouting, church, or religious clubs (excluding
religious services) in the last 12 months.
- Caregivers of all children were also asked about OST arrangements that they
used for child care purposes. One of these options was summer camps;
caregivers were asked if their child participated in overnight or day camp
regularly during the last summer.
- Children ages 10 or older were also asked about their membership or participation
in tutoring programs, organized summer or after school sports or recreation
programs, and other school activities (such as clubs or student government)
in the last 12 months.
NSAF
In the NSAF, caregivers were asked about youth's participation in before school
and after school programs, organized OST clubs or activities, lessons, and sports
(Appendix Table 2 provides the exact wordings of all questions from the NSAF).
More specifically:
- For children ages 6–11, caregivers were asked if the child participated
in any clubs or organizations after school or on weekends, such as
Scouts, religious groups, or Boys & Girls Clubs.
- For children ages 12–17, caregivers were asked about the child's participation
in any clubs or organizations, such as youth group; student government;
drama, band, or chorus; or a religious or community group after school or
on weekends.
- Caregivers were also asked whether the child participated regularly (at
least once a week during the previous month) in before or after school
programs.
- All caregivers were asked whether the child had taken lessons after school
or on weekends in subjects like music, dance, language, or computers, or if
the child had participated in a sports team in the last year.
Research Findings
Below, we present two sets of findings. In the first section, we use the two
data sets to describe demographic differences in OST participation in 2002,17
in order to describe the current state of OST participation. In the next section,
we use the NSAF to examine changes in participation patterns over time, in order
to explore whether participation rates have changed along with changes in the
OST field.
In each section, we organize our results by demographic characteristic—that
is, whether participation varied according to family income, and whether participation
varied according to race. Findings are presented separately for different types
of activities. First, we describe participation using the broadest indicator
available—that is, whether youth participated in any club, program, or
structured activity in the nonschool hours (from NSAF). Next, we describe participation
in programs—that is, before or after school programs, community programs,
tutoring programs, and summer programs. Lastly we describe participation in
extracurricular activities—for example, sports teams, arts lessons, and
religious activities.
Although we attempt to avoid statistical jargon, it is worth noting that our
discussion of these findings is based on empirical analyses with close attention
paid to both statistically significant differences and the sizes of these differences.18
Only statistically significant findings are reported below.
Demographic Differences in Participation in 2002
Family Income
Figures 1–5 show how participation in several contexts varied by family
income quintiles in the 2002 waves of the NSAF and PSID. With the exception
of participation in tutoring programs, virtually all types of OST participation
reveal a general pattern of higher participation among youth with higher family
incomes. This finding was consistent across both data sets.
Figure 1 shows income differences in our broadest and most inclusive OST measure—participation
in any organized OST club or activity. Large income differences were found for
both younger and older youth. Among younger youth, only 31% of the lowest income
youth participated in an OST club or activity, whereas fully 58% of the highest
income youth participated. Among older youth, participation rose from 43% to
72%.
Figure 2 shows income differences in before and after school programs in the
NSAF. These differences were moderate in size. Thirteen percent of the lowest
income youth participated in a before or after school program in 2002, as compared
to over 20% of the highest income youth.
Figure 3 shows income differences in programs in the PSID. There were large
income differences in organized recreation programs, where participation in
such programs rose from 29% among the lowest income youth to 55% among the highest
income youth. There were moderate income differences in community programs and
summer camps. For community programs, 16% of the lowest income youth participated,
as compared to 35% of the highest income youth. For summer camps, 4% of the
lowest income youth participated, as compared to 18% of the highest income youth.
Only in tutoring programs was a countertrend evident, with a moderate difference
across income groups: 26% of the lowest income youth participated in tutoring
programs, as compared to 17% of the highest income youth.
Figure 4 shows large income differences in OST activities in the NSAF. Participation
in sports rose from 36% among the lowest income youth to 67% among the highest
income youth. The corresponding figures for OST lessons were 23% and 48%.
Figure 5 shows income differences in OST activities in the PSID. Moderate differences
were found for each of the three activities examined, religious clubs/activities,
Scouting, and school-based extracurricular activities. Religious club/activity
participation rose from 47% to 64% across income groups, school-based extracurricular
activities from 38% to 60%, and Scouting from 6% to 18%.
Race/Ethnicity
Figures 6–10 show how participation in several contexts varied by race/ethnicity
in the 2002 waves of the NSAF and PSID. Across most types of programs and activities
in both data sets, Latino youth are consistently underrepresented, and White
youth are consistently overrepresented, with Black youth somewhere in between.
Black youth, however, showed particularly high participation rates in some OST
contexts, such as before and after school programs and summer camps.
Figure 6 shows that in the broadest indicator of participation in any structured
OST context, Whites were more likely to participate than Blacks, who, in turn,
were more likely to participate than Latinos. Differences between Whites and
Blacks were moderate among younger youth and small among older youth. Differences
between Whites and Latinos were large among younger youth and moderate among
older youth. Differences between Blacks and Latinos were moderate for both age
groups. Overall, 56% of young White youth participated in any OST club or activity,
as compared to 42% of young Black youth and 30% of young Latino youth. Similarly,
65% of older White youth participated in any OST club or activity, as compared
to 58% of older Black youth and 43% of older Latino youth.
Figure 7 shows that in before and after school programs, Black youth were moderately
more likely than Whites or Latinos to participate, while there were no significant
differences between Whites and Latinos. Overall, 26% of Black youth in the NSAF
participated in before or after school programs, while only 13% and 12% of Whites
and Latinos participated, respectively.
Figure 8 shows racial/ethnic differences in participation in OST programs in
the PSID, where Latinos were least likely to participate in all programs except
tutoring. For community programs, White youth (34%) demonstrated moderately
higher participation rates than Black or Latino youth (15% for both). For organized
recreation programs, White and Black youth both demonstrated moderately higher
rates than Latino youth, with 45% of Whites, 39% of Blacks, and 28% of Latinos
participating. For summer camps, Black youth showed a large advantage in participation
rates over Latino youth and a small advantage over White youth, while Whites
showed a moderate advantage over Latinos. Overall, 13% of Black youth, 9% of
White youth, and only 2% of Latino youth participated in summer camps. Lastly,
for tutoring programs, large differences were found between Black and White
youth, and moderate differences were found between Black and Latino youth and
between Latino and White youth. Black youth had the highest rates of participation
in tutoring programs (33%), while Latinos had the second highest (21%) and White
youth the lowest rates (14%).
Figure 9 shows that in the NSAF, Whites were moderately more likely to be involved
in sports than both Black and Latino youth, while there were no differences
found between Blacks and Latinos. In total, 58% of Whites, 43% of Blacks, and
42% of Latinos participated in sports. In lessons, there was a small difference
between the participation rates of Whites and Blacks on the one hand and Latinos
on the other hand. White and Black youth's participation rate in OST lessons
was 34%, while for Latinos the figure was 26%.
Similarly, Figure 10 shows that participation rates in extracurricular activity
participation in the PSID were relatively equivalent, although White youth demonstrated
slightly higher rates than Black or Latino youth (49% among Whites vs. 42% for
Black and Latino youth).19
In religious clubs and activities, there were large differences in the participation
rates of Black and White youth compared to the participation rates of Latino
youth. Overall, 64% of Black youth and 65% of White youth participated in religious
clubs or activities, whereas only 29% of Latino youth did so. Lastly, White
youth participated in Scouting at the highest rates (16%), which was moderately
higher than the rates for Black and Latino youth (7% for each).
Demographic Differences in OST Participation: 1997–2002
While Figures 1–10 provide a snapshot of demographic differences in a
variety of OST programs and activities in 2002, it is also important to see
if demographic differences in OST participation have changed over time. Studying
this change allows us to better understand whether gaps in OST participation
have narrowed or widened over time, which can inform debates about where to
target resources moving forward. To answer this question, we turn to data from
the NSAF, which contains information on five types of OST participation across
three points in time—1997, 1999, and 2002. Again, when we discuss widening
or narrowing gaps, we only report statistically significant results.20
In general, across all the OST measures and demographic gaps examined in the
historical analysis, only two significant changes were found over time, indicating
a general pattern of stability in demographic differences in participation rates
over the late 1990s. Figures 11 and 12 show the two changes that were found.
As Figure 11 demonstrates, for participation in before and after school programs,
there have been increases over time in participation rates at every level of
family income, but the increase was greatest among the lowest income youth,
resulting in a narrowing of the gap between youth from low-income families and
youth from higher income families.
The income gap in before and after school program participation rates between
the lowest and highest income youth fell from 11.2 % in 1997 to 7.6 % in 2002.
Gaps remain fairly steady for other OST activities: OST club participation (both
younger and older children), OST lessons, and sports.
As Figure 12 shows, between 1997 and 2002, young Blacks experienced a sharp
drop in participation—nearly 10 %—in participation in any OST club,
resulting in a widening gap between Black and White youth over the 1997–2002
period.
Young White youth's participation in OST clubs dropped only from 58% to 56%
between 1997 and 2002, whereas for young Black youth, this drop was from 51%
to 41%.
Gaps between Whites and Latinos and Blacks and Latinos held steady across all
OST programs and activities, while gaps between Blacks and Whites also remained
stable for the other four OST indicators.
Summarizing Trends and Gaps in Participation: Progress and Challenges
Our analysis of demographic differences in youth's OST program and activity
participation reveals a detailed story of both progress and challenges.
We found substantial inequality in youth OST participation by demographic background,
with low-income youth participating at markedly lower rates than their higher
income peers across many types of OST programs and activities, including before
and after school programs. This finding suggests a continuing need to target
nonschool resources to the most disadvantaged youth. This is particularly important
given that our results show that these youth are also far less likely to participate
in other OST activities, such as lessons, clubs, and sports. Given evidence
of unmet demand for OST programs among disadvantaged families,21
there remains a clear need to target resources toward recruiting and retaining
these youth in OST programs and activities.
Our data also show that disadvantaged youth participate at higher rates than
more advantaged youth in tutoring programs. This finding may indicate that the
academic deficits of disadvantaged youth are limiting their ability to participate
in other types of enrichment activities and programs. Youth with academic deficits
should continue to be a focus for youth workers and other OST stakeholders.
These socioeconomic gaps may stem from differences in access to affordable,
quality OST activities in the communities and schools of youth from different
family backgrounds. Family- and child-level factors may also be important in
explaining these gaps; disadvantaged families may have different family management
routines or may have work situations that make OST participation challenging—for
example, due to transportation barriers. Finally, children with fewer resources
may have certain characteristics (e.g., lower self-efficacy, more problem behavior)
that make them less likely to engage in OST activities and programs. Future
publications from this research project will explore these possibilities.
We found less, though still substantial, inequality in OST participation by
race/ethnicity, with White youth participating at the highest rates in many
structured OST contexts, Latino youth participating at the lowest rates, and
Black youth typically in the middle (though with the highest rates in certain
activities, such as before and after school programs and summer camps). It should
be noted that our study did not test the independent effects of race and socioeconomic
status. Since Blacks and Latinos are overrepresented among the American poor,22
the findings about race may in fact be related to income and education.
However, these findings may also be driven by other factors specific to families
of different racial and ethnic backgrounds. For instance, many after school
and summer programs specifically target minority youth, which may help explain
why Black youth participate at relatively high rates in these types of programs.
Latino youth's low participation levels may also be partially driven by linguistic
and cultural differences between families, youth, and activity providers.
In examining demographic gaps over time, we found both positive and negative
trends. One encouraging finding was that the gap in before and after school
program participation between lower and higher income youth narrowed over time.
On a more negative note, younger Blacks fell further behind White youth in their
overall OST club participation rates.
While accounting for these over-time trends is beyond the scope of this research brief, a number of factors may be at work. The increasing policy emphasis
on OST programs, especially for disadvantaged youth, likely contributed to the
declining socioeconomic gap in before and after school program participation.
A key component of this recent attention to disadvantaged youth has been the
rapid increase in funding for the federal 21st Century Community Learning Centers
program. Widening gaps between younger White and Black youth in overall OST
club participation seem to be more of a mystery, indicating that further research
should be devoted to understanding the sources of these changes.
Implications for Youth Stakeholders
This study offers an important message for practitioners and policymakers about
recruitment and retention. Our findings provide further evidence that OST activity
leaders need to ramp up their efforts to attract and sustain disadvantaged youth
and to pay particular attention to specific ethnic groups, most notably Latino
youth. The good news is that participation in before and after school programs
has increased among all youth, especially low-income youth, since 1997. However,
there is much progress to be made. As described by Lauver and Little, traditional
methods of recruitment do not work well for some youth and their families, and
youth practitioners may need to conduct more tailored and targeted recruitment
efforts to reach those who are least likely to participate.23
Our results suggest that this recruitment and retention challenge exists across
a wide range of programs and activities, including before and after school programs,
recreation programs, school-based extracurricular activities, and sports. No
single type of OST activity is “off the hook” from needing to address
these challenges.
A second message for policymakers and funders is that there exists a continued
need to target resources to activities and programming for underserved youth—that
is, youth from families with lower incomes, with less education, and from some
ethnic minority groups. Although this study does not allow us to directly tie
increases in OST investments to decreasing service gaps, this is an encouraging
trend, which suggests that progress can be made in order to support all youth
in the nonschool hours.
The implications of this work for researchers and evaluators include the importance
of incorporating demographic factors into data collection and analysis. By continuing
to document the characteristics of youth participants, program evaluators and
researchers can encourage continued attention to issues of access and equity
and can document future progress in these areas. By collecting this information,
researchers and evaluators can also begin to ask questions about whether outcomes
of these activities vary according to youth characteristics.
Moving forward, it is imperative that all stakeholders take seriously the growing
evidence base that some youth—particularly those from disadvantaged families—are
less likely to participate in OST programs and activities than their peers.
Incorporating this evidence into practice, policy, and research can help in
the ongoing effort to provide access to quality OST programming for all youth.
Notes
1 Weiss,
H. B., Coffman, J., Post, M., Bouffard, S., & Little, P. M. D. (2005). Beyond
the classroom: Complementary learning to improve achievement outcomes. Evaluation
Exchange, 11(1), 2–6, 17. Available at www.gse.harvard.edu/hfrp/eval/issue29/
theory.html.
2 Eccles,
J., & Barber, B. L. (1999). Student council, volunteering, basketball, or
marching band: What kind of extracurricular participation matters? Journal
of Adolescent Research, 14(1), 10–43; Mahoney, J. L., Larson,
R. W., Eccles, J. S., & Lord, H. (2005). Organized activities as development
contexts for children and adolescents. In J. L. Mahoney, R. W. Larson, &
J. S. Eccles (Eds.), Organized activities as contexts of development
(pp. 3–22). Mahwah, NJ: Lawrence Erlbaum Associations; Simpkins Chaput,
S., Little, P. M. D., & Weiss, H. B. (2004). Understanding and measuring
attendance in out-of-school time programs. Cambridge, MA: Harvard Family
Research Project. Available at www.gse.harvard.edu/hfrp/projects/afterschool/resources/
issuebrief7.html.
3 Mahoney,
J. L. (2000). School extracurricular activity participation as a moderator in
the development of antisocial patterns. Child Development, 71,
502–516; Roeser, R. W., & Peck, S. C. (2003). Patterns and pathways
of educational achievement across adolescence: A holistic-developmental perspective.
In S. C. Peck & R. W. Roeser (Eds.), Person-centered approaches to studying
development in context (pp. 39–62). San Francisco: Jossey-Bass.
4 Duffet,
A., Johnson, J., Farkas, S., Kung, S., & Ott, A. (2004). All work and
no play? Listening to what kids and parents really want from out-of-school time.
New York: Public Agenda.
5 Weiss,
Coffman, Post, Bouffard, & Little, 2005.
6 Duffet,
Johnson, Farkas, Kung, & Ott, 2004.
7 Eccles
& Barber, 1999; Mahoney, Larson, Eccles, & Lord, 2005; Simpkins Chaput,
Little, & Weiss, 2004.
8 Mahoney,
2000; Roeser & Peck, 2003.
9 Borden,
L. M., Perkins, D. F., Villarruel, F. A., & Stone, M. R. (2005). To participate
or not to participate: That is the question. New Directions for Youth Development,
105, 33–50.
10 Pedersen,
S., & Seidman, E. (2005). Contexts and correlates of out-of-school activity
participation among low-income urban adolescents. In J. L. Mahoney, R. W. Larson,
& J. S. Eccles (Eds.), Organized activities as contexts of development
(pp. 85–110). Mahwah, NJ: Lawrence Erlbaum Associations.
11 Larson,
R. W. (2001). How U.S. children and adolescents spend time: What it does (and
doesn't) tell us about their development. Current Directions in Psychological
Science, 10, 160–164.
12 Eccles
& Barber, 1999.
13 Vandell,
D. L. (2005). What we know and what we need to know to improve program quality:
Let's talk. Presented at the After School Evaluation Symposium, Washington,
DC.
14 Bartko,
W. T. (2005). The ABCs of engagement in out-of-school-time programs. New
Directions for Youth Development, 105, 109–120.
15 Brock,
T., Doolittle, F., Fellerath, V., & Wiseman, M. (1997). Creating new
hope: Context, implementation, and service utilization in a work-based anti-poverty
program. New York: Manpower Demonstration Research Corporation.
16 We also
tested demographic differences by parental education but for simplicity concentrate
on family income as our measure of socioeconomic status. The findings for parental
education were very similar to those for family income and are available on
request.
17 Since
the surveys were administered in 2002, the participation rates largely reflect
youth's activities in the previous 12 months—that is, 2001. The same holds
true for the years encompassed in the NSAF.
18 All
analyses of demographic differences in OST participation were estimated in univariate
2 models, from which we computed effect sizes (i.e., Phi). Evaluations in the
text of whether demographic differences were small, moderate, or large in size
were based on comparisons of effect sizes within the empirical context of the
present study (for a discussion of the value of this method, see McCartney and
Rosenthal, 2000). For example, Phi values of .10 and smaller were described
as small and those of .20 and larger were described as large. The exact effect
size estimates are available from the authors on request. Only statistically
significant differences are discussed in the text.
19 The
difference between Blacks and Whites was small and statistically significant.
For Latinos and Whites, the effect size was virtually the same as between Blacks
and Whites, but the difference was not quite statistically significant, likely
because of the smaller sample size for Latino youth. Thus, the differences here
between White and Latino youth should be viewed with caution.
20 For
the historical analysis, we ran a series of regression models predicting each
type of OST activity by the demographic variable of interest, year, and an interaction
between the demographic variable of interest and year. For instance, for income,
we ran five regression equations, one for each OST activity. These equations
included the income variable, the year variable, and an income/year interaction.
For race, we omitted Whites as the reference group, and ran similar equations
with dummy variables for Black and Latino, year, and interactions between Black
and Latino with year. Only interactions that were statistically significant
are discussed.
21 Duffet,
Johnson, Farkas, Kung, & Ott, 2004.
22 Blank,
R. M. (2001). An overview of trends in social and economic well-being, by race.
In N. J. Smelser, W. J. Wilson, & F. Mitchell (Eds.), America becoming:
Racial trends and their consequences (Vol. 1, pp. 21–39). Washington,
DC: National Academies Press.
23 Lauver,
S., & Little, P. M. D. (2005). Finding the right hook: Strategies for attracting
and sustaining participation in after-school programs. The School Administrator,
62(5). Available at www.aasa.org/publications/saarticledetail.cfm?ItemNumber=2522&sn
ItemNumber=950&tnItemNumber=951.
Acknowledgements
Preparation of this brief was made possible through the support of the William
T. Grant Foundation. The principal investigator on this grant is Heather B.
Weiss. We would also like to thank Holly Kreider and Sherri Lauver of Harvard
Family Research Project for their insightful review and feedback.
Appendix A
Descriptions and Sources of Information for OST Activity Categories from the
PSID
| OST Program/Activity |
Questionnaire |
Item |
| Community group or program |
Caregiver interview |
Was (CHILD) a member of any groups or programs in the community in the
last 12 months? Groups or programs in the community include Scouts and service
or hobby clubs. |
| Tutoring program |
Child interview |
Were you in a tutoring program in the last 12 months? |
| Caregiver interview |
Was (CHILD) in a tutoring program in the last 12 months? |
| Organized summer or after school sports or recreation |
Child interview |
During the last summer, were you involved in any organized summer or after
school sports or recreation programs? |
| Summer overnight or day camp |
Caregiver interview |
Now I'm going to ask you some questions about child care arrangements
last summer.
Please tell me which of these you used for (CHILD) on a regular basis
during last summer:
• Overnight camp
• Day camp
|
| Scouting
|
Caregiver interview |
Please tell me how often (CHILD) has participated in the following activities
within the past 12 months:
• Scouting |
| Church or other religious club or activity |
Caregiver interview |
Please tell me how often (CHILD) has participated in the following activities
within the past 12 months:
• Church (or other religious) club or activity (not religious service
or mass) |
| Other school activities |
Child interview |
Besides athletic teams, did you take part in any other school activities,
such as clubs or student government, in the last 12 months? |
Appendix B
Descriptions and Sources of Information for OST Activity Categories from the
NSAF
| OST Program/Activity |
Item |
Description |
| OST clubs (ages 6–11) |
In the last year, has (CHILD) participated in any clubs or organizations
after school, or on weekends, such as scouts, a religious group or Girls
or Boys club? |
Participation means regular or fairly regular attendance at the group's
meetings or activities. This does not include sports clubs or teams that
were already counted. |
| OST clubs (ages 12–17) |
In the last year, has (CHILD) participated in any clubs or organizations
after school, or on weekends, such as a youth group or student government,
drama, band or chorus, or a religious or community group? |
Participation means regular or fairly regular attendance at the group's
meetings or activities. This does not include sports clubs or teams that
were already counted. |
| Before and after school programs |
We'd like to know how (CHILD) spent (his/her) time when (he/she) was not
with you during the last month.
I'm going to read a list of different kinds of programs children attend
and of people who care for children. I'd like you to tell me which ones
you used for (CHILD), at least once a week during the last month. Did
(CHILD) attend before or after school programs?
|
This variable deals with special programs to care for children before
school begins or after school is over.
These programs are often located within schools, community centers, and
youth development agencies. Interviewers were instructed not to include
care from a neighbor or relative in the hours before or after school.
This question was only asked about focal children 2 years of age or older. |
| Sports |
In the last year, has (CHILD) been on a sports team either in or out of
school? |
If needed, interviewers were to define a sports team as any formally organized
team that meets regularly for practices and games. Indoor and outdoor sports
such as soccer, bowling, swimming, tennis, or softball were to be included.
Interviewers were instructed not to include competitive games, such as a
chess team, or informal, individual exercise, such as jogging. This question
was asked of MKAs about children aged 6–17 years old). |
| OST lessons |
In the last year, has (CHILD) taken lessons after school or on weekends
in subjects like music, dance, language, or computers? |
“Lessons after school or on weekends” include any lessons or
classes that are not part of the regular school curriculum. Lessons can
be offered by private or public organizations, and they can be individual
or in a group. Music, dance, language, and computers are offered as examples,
but lessons can include a wide variety of activities. Sports teams were
not included, as they were already counted. This question was asked about
focal children between the ages of 6 and 17. |
|
