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Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6-7 year-old children's daily, annual, and typical schedules. We categorized children's activities as "structured" or "less-structured" based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up.
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ORIGINAL RESEARCH ARTICLE
published: 17 June 2014
doi: 10.3389/fpsyg.2014.00593
Less-structured time in children’s daily lives predicts
self-directed executive functioning
Jane E. Barker1*, Andrei D. Semenov 1, Laura Michaelson1, Lindsay S. Provan1, Hannah R. Snyder2
and Yuko Munakata1
1Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
2Department of Psychology, University of Denver, Denver, CO, USA
Edited by:
Yusuke Moriguchi, Joetsu University
of Education, Japan
Reviewed by:
Adele Diamond, The University of
British Columbia, Canada
Angeline Lillard, University of
Virginia, USA
*Correspondence:
Jane E. Barker, Department of
Psychology and Neuroscience,
University of Colorado Boulder, 345
UCB, Boulder, CO 80309, USA
e-mail: jane.barker@colorado.edu
Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great
interest in attempts to improve EFs early in life. Many interventions are led by trained
adults, including structured training activities in the lab, and less-structured activities
implemented in schools. Such programs have yielded gains in childrens externally-driven
executive functioning, where they are instructed on what goal-directed actions to carry
out and when. However, it is less clear how children’s experiences relate to their
development of self-directed executive functioning, where they must determine on
their own what goal-directed actions to carry out and when. We hypothesized that
time spent in less-structured activities would give children opportunities to practice
self-directed executive functioning, and lead to benefits. To investigate this possibility,
we collected information from parents about their 6–7 year-old children’s daily, annual, and
typical schedules. We categorized children’s activities as “structured” or “less-structured”
based on categorization schemes from prior studies on child leisure time use. We
assessed childrens self-directed executive functioning using a well-established verbal
fluency task, in which children generate members of a category and can decide on their
own when to switch from one subcategory to another. The more time that children
spent in less-structured activities, the better their self-directed executive functioning.
The opposite was true of structured activities, which predicted poorer self-directed
executive functioning. These relationships were robust (holding across increasingly strict
classifications of structured and less-structured time) and specific (time use did not
predict externally-driven executive functioning). We discuss implications, caveats, and
ways in which potential interpretations can be distinguished in future work, to advance
an understanding of this fundamental aspect of growing up.
Keywords: cognitive development, self-directed executive function, leisure time, unstructured activities, verbal
fluency
INTRODUCTION
Why do young children often forget (or outright refuse) to put
on a coat before leaving the house on a snowy day? The choice
to put on a jacket may seem frustratingly obvious to parents and
older siblings, but this simple decision arises from a surprisingly
complex interplay of behaviors. Children must keep in mind a
goal (staying warm and dry) that is not yet relevant in the comfort
of a warm house. They must inhibit the urge to proceed with a
regular sequence of tasks (put on socks and shoes and head out
the door), and instead modify their routine to include something
new (pulling a coat from the closet). Unless someone intervenes,
this change in the status quo must be accomplished without any
external reminders (a visible coat, or a well-timed reminder from
a caregiver).
To accomplish each of these tasks, children must engage
executive functions (EFs), the cognitive control processes that
regulate thought and action in support of goal-directed behav-
ior. EFs develop dramatically during childhood (e.g., Gathercole
et al., 2004; Zelazo et al., 2008; McAuley et al., 2011; Munakata
et al., 2012), and support a number of higher-level cogni-
tive processes, including planning and decision-making, mainte-
nance and manipulation of information in memory, inhibition
of unwanted thoughts, feelings, and actions, and flexible shift-
ing from one task to another. Researchers have used a variety
of laboratory tasks to measure child EFs, including table-
top behavioral tasks (e.g., the classic marshmallow test, card-
sorting tasks) and computerized tasks (e.g., Go/No-go, Flanker),
many of which tap multiple aspects of EF. Over the past
decade, EFs have emerged as critical, early predictors of suc-
cess across a range of important outcomes, including school
readiness in preschoolers (Miller et al., 2013), as well as aca-
demic performance at school entry (Blair and Razza, 2007;
Cameron et al., 2012) and beyond (St Clair-Thompson and
Gathercole, 2006; Best et al., 2011). Moreover, children with
worse EF go on to have poorer health, wealth, and social out-
comes in adulthood than children with better EF, even after
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Barker et al. Less-structured time and executive function
controlling for differences in general intelligence (Mofttetal.,
2011).
Given the established links between early EFs and later life out-
comes, a number of studies have investigated whether EF abilities
can be changed through experience, with some notable successes.
Most of this work has involved adult-led training or interventions,
which allow children to practice EFs in an environment where
adults provide some guidance. For example, children’s working
memory, or their ability to maintain and manipulate information
across a delay, can be improved through short periods of targeted
training (e.g., Holmes et al., 2009; Bergman Nutley et al., 2011).
During such training, children are presented with sequences of
spoken or visual stimuli. After a brief pause, the child is instructed
to reproduce the sequence either in forward order (requiring
maintenance of information, but no manipulation) or in reverse
order (requiring maintenance and manipulation). After training,
children often show better performance in similar tasks assess-
ing the same skills (e.g., Holmes et al., 2009, 2010; Thorell et al.,
2009; Bergman Nutley et al., 2011;reviewedinDiamond and
Lee, 2011; Shipstead et al., 2012). In addition, children’s cogni-
tive flexibility, or ability to change tasks or strategies in response
to new environmental demands, can be improved via interven-
tions implemented in preschool curricula (Lillard and Else-quest,
2006; Diamond et al., 2007; Bierman et al., 2008; Röthlisberger
et al., 2012). These curricula have ranged from partial-day, small-
group sessions where children play games developed to exercise
EFs (Röthlisberger et al., 2012), to comprehensive, full-day imple-
mentations, such as those found in Tools of the Mind (Diamond
et al., 2007) and Montessori (Lillard and Else-quest, 2006) class-
rooms, where teachers are trained to scaffold developing EFs
throughout the day. Relative to children in business-as-usual
classrooms, children enrolled in such curricula have subsequently
shown better performance in tasks where they must flexibly shift
from one rule (e.g., sorting cards by their shape) to another (e.g.,
switching to sorting the cards by color).
Altering children’s experiences with such training and inter-
ventions has thus led to improvements in children’s externally-
driven EF, where they are instructed on what to do (e.g., sort cards
according to shape; remember a sequence of digits), and when
(e.g., now switch and sort according to color; now recall the digits
in reverse order). In the real world, children who have developed
externally-driven EF might behave in a goal-directed way when
given reminders. For example, a child might successfully put on a
coat in the morning after a reminder from a caregiver. However,
it is less clear how children’s experiences relate to their devel-
opment of more self-directed executive functioning, where they
must determine on their own what goal-directed actions to carry
out and when. A self-directed child, for example, might put a coat
on just before going outside without being told what to do.
The development of self-directed EF is a critical part of grow-
ing up. Self-directed EFs develop later than externally-driven
forms of executive control (Welsh et al., 1991; Jacques and Zelazo,
2001; Smidts et al., 2004; Snyder and Munakata, 2010; Chevalier
et al., 2011), and prove to be more cognitively demanding, even
in adults (e.g., Bryck and Mayr, 2005; Forstmann et al., 2005; Lie
et al., 2006). Tasks assessing self-directed control typically pro-
vide an overall goal, but challenge participants to generate their
own rules for how and when to employ EFs to achieve that goal.
For example, in the verbal fluency task, which is a frequently-used
and longstanding measure of EF (e.g., Troyer et al., 1997, 1998;
Henry and Crawford, 2004; Sauzéon et al., 2004; Costafreda et al.,
2006; Birn et al., 2010; Raboutet et al., 2010; Unsworth et al.,
2010), participants are given a category (e.g., foods), and asked
to produce as many words falling within that category as possi-
ble across a 1-min interval. To produce many items, participants
may cluster responses (by grouping words that fall within the
same semantic subcategory) and switch between subcategories
whenavailableexemplarsareinshortsupply(e.g.,Tr oye r e t a l .,
1997, 1998; Abwender et al., 2001; Koren et al., 2005). Individuals
must endogenously detect the need to switch (e.g., when they
cannot think of more breakfast foods) and select what to switch
to (e.g., desserts, vegetables, or fruits). Each process critically
relies on generation of internal cues and becomes less executively
demanding when external cues are instead provided (Randolph
et al., 1993; Tremblay and Gracco, 2006; Snyder and Munakata,
2010). Consistent with this analysis of the self-directed nature of
this task, switching among subcategories has been well-validated
as the most executively-demanding component of verbal fluency
tasks: switching (as opposed to naming items within clusters)
activates prefrontal cortex (e.g., Hirshorn and Thompson-Schill,
2006), is impaired by prefrontal lesions (e.g., Troyer et al., 1998),
and has the most protracted developmental course, with per-
formance continuing to increase through adolescence (e.g., Kave
et al., 2008). Young children often fail to switch from one subcate-
gory to another, and instead perseverate on an initial subcategory
(e.g., naming five different breakfast foods, and then indicating
to the experimenter that they are finished). However, like patients
with frontal lobe dysfunction, who benefit from semantic cueing
during verbal fluency (Randolph et al., 1993; Drane et al., 2006;
Iudicello et al., 2012), children can improve on the task when
demands on self-directed EF are reduced by providing example
subcategories prior to the task (Snyder and Munakata, 2010).
This body of literature highlights the role of self-directed EF in
switching among subcategories in the verbal fluency task.
We predicted that children’s self-directed EFs might benefit
from participation in less structured activities, where children,
rather than adults, choose what they will do and when. Such
experiences could support the practice of self-directed executive
functioning, and lead to benefits. For example, children may prac-
tice engaging self-directed forms of EF by establishing goals and
carrying them out across an afternoon (“first I’ll read this book,
then I’ll make a drawing about the book, then I’ll show every-
one my drawing”) or during a visit to a museum (“first I want to
see the dinosaur exhibit, and then I want to learn about rocks”).
These types of self-directed choice and planning are central to the
Tools of the Mind and Montessori classrooms, although the exact
form they take and the types of activities emphasized differ across
these programs (Montessori, 1976; Bodrova, 2003; Bodrova and
Leong, 2007).
For example, extended, social pretend play figures centrally
in the Tools of the Mind program. This program is based on
the work of Vygotsky (Bodrova and Leong, 2007), who theorized
that imaginative play supports the development of self-directed
EF, in children’s transitions from other-regulated to self-regulated
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Barker et al. Less-structured time and executive function
cognitive processes (Vygotsky, 1967). During pretend play, chil-
dren may practice engaging self-directed forms of EF by develop-
ing and maintaining their own goals to guide their behavior, even
in the presence of conflicting environmental signals: a child who
uses a wooden spoon as a wand maintains a pretend use while
inhibiting a typical use (stirring a pot). Children’s pretend play, as
assessed during laboratory tasks with an adult experimenter, does
predict their externally-driven EFs (Albertson and Shore, 2009;
Kelly et al., 2011; Carlson et al., 2014); however, this relationship
has been observed less reliably when pretend play is assessed dur-
ing naturalistic play (e.g., Elias and Berk, 2002; Kelly et al., 2011;
cf. Harris and Berk, as discussed in Lillard et al., 2013).
While preschool programs such as Tools of the Mind and
Montessori implement the types of activities that we predict will
benefit self-directed EFs, and such programs improve children’s
externally-driven EFs as discussed above, little work has inves-
tigated the relationship between such activities and the devel-
opment of self-directed EFs. One study found that 12-year-old
Montessori students were rated more highly on a measure of
creativity than non-Montessori students, when writing answers
to complete the prompt, “__ had the best/worst day at school”
(Lillard and Else-quest, 2006). While such findings are sugges-
tive because open-ended writing assignments have the potential
to tap self-directed EFs, the prompt completion task is not an
established measure of self-directed EFs, and there is some debate
about the extent to which creativity reflects EF (e.g., Groborz
and Ne¸cka, 2003; Chrysikou and Thompson-Schill, 2011; Ellamil
et al., 2012; Jarosz et al., 2012). In addition, improved perfor-
mance on this task may also reflect other benefits from such
programs to language or writing skills; additional benefits were
in fact observed on this task in the Montessori students’ sentence
sophistication. Moreover, it is unclear whether a broader range of
less-structured activities outside of formal schooling yield EF ben-
efits. Investigating this question is important, given that effects
observed inside formal settings with trained adults may not gen-
eralize to other settings (as in the case of the pretend play effects
discussed above), and given that not all families have access to the
school settings where effects have been observed.
As a first step in examining the question of how children’s
experiences outside of formal schooling relate to EFs, we con-
ducted a naturalistic, correlational study, in which we measured
the time that 6-year-old children spent in their daily lives in struc-
tured and less-structured activities and tested whether it predicted
performance in the lab on well-established executive function
tasks, both externally-driven and self-directed. At this age, chil-
dren spend some time in both structured and less-structured
activities (e.g., Meeks and Mauldin, 1990; Hofferth and Sandberg,
2001a) and show some ability in self-directed control tasks, with-
out showing high levels of proficiency (e.g., Welsh et al., 1991;
Brocki and Bohlin, 2004; Kave et al., 2008; Snyder and Munakata,
2010, 2013).
To classify structured and less-structured activities, we
relied on studies of child leisure time use (e.g., Meeks and
Mauldin, 1990; Larson and Verma, 1999; Hofferth and Sandberg,
2001b; Fletcher et al., 2003; Osgood et al., 2005), which
have attempted to discriminate between activities constituting
structured, or constructive leisure, and “unstructured” leisure
activities. “Unstructured” activities in this literature might be bet-
ter thought of as “less-structured” activities, given that they can
include some adult structuring, so we use the latter terminology
throughout this paper. Most leisure time studies have identified
structured leisure activities as those that are “supervised to some
degree by a conventional adult, are highly structured, and pro-
vide [children] with a clear set of conventional activities in which
to engage” (Agnew and Petersen, 1989, p. 335). Such activities
are...organized by adults around specific social or behavioral
goals” (Fletcher et al., 2003, p. 641). Thus, structured time in
the present study was defined to include any time outside of
formal schooling1spent in activities organized and supervised
by adults (e.g., piano lessons, organized soccer practice, com-
munity service, homework). Less-structured activities have been
described more loosely, and generally include voluntary leisure
activities where adults provide fewer guidelines or direct instruc-
tions, such as activities that are “spontaneous, [taking] place
without formal rules or direction from adult leaders, and [fea-
turing] few goals related to skill development” (Mahoney and
Stattin, 2000, p. 116). Our coding scheme follows existing coding
schemes documented in Meeks and Mauldin (1990) and Hofferth
and Sandberg (2001b). In cases where these coding schemes dif-
fered, we reviewed the literature to ensure that our coding was in
accordance with the majority of other time use studies2.Inthe
present study, less-structured activities included activities such as
free play, family and social events, reading, drawing, and media
time. While these classifications are imperfect (e.g., they do not
capture the degree of structure within and across classifications—
an issue we return to in the Discussion), they allow us to build on
the existing literature, and serve as an important starting point
for testing our predictions; further analyses allow us to test the
importance of particular activities within these classifications.
We hypothesized that the amount of time children spent in
less-structured activities would predict their self-directed EF, over
and above any differences attributable to age, general vocabulary
knowledge, and household income. We expected these effects to
be specific, such that less-structured activities would not predict
externally-driven EF and structured activities would not predict
self-directed EF.
METHODS
PARTICIPANTS
Seventy children participated in the study [Mage =6.58 years;
range =(6.01–7.00 years); males =37]. All participants were
1We did not classify time spent in school as “structured” because the degree
of structure in school settings can vary a great deal, and parent reports are
likely to be inaccurate (since parents often do not have direct knowledge of
child activities during schooling hours). Our definition of structured activi-
ties is also consistent with past studies of structured leisure time, which have
excluded time spent in school (e.g., Meeks and Mauldin, 1990; Larson and
Verma, 1999; Mahoney and Stattin, 2000; Hofferth and Sandberg, 2001b;
Fletcher et al., 2003; Osgood et al., 2005).
2Hofferth and Sandberg (2001b) separately identify reading, studying, and
television watching as learning activities. However, we have classified read-
ing and television as less-structured time, and studying as structured time, in
keeping with other studies (e.g., Meeks and Mauldin, 1990; Eccles and Barber,
1999; Fletcher et al., 2003).
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Barker et al. Less-structured time and executive function
recruited from a database of families who had volunteered to
participate in research. During subject recruitment, parents were
informed that they would be asked to document child activities
during the week prior to the study visit. Three participants were
excluded from analyses because detailed information on their
weekly activities was unavailable, either because parents did not
wish to provide this information (2), or because data were lost
due to a technical error at the time of parent submission (1).
Of the remaining participants, one child did not complete the
Flanker task, one child did not complete the digit span task, and
two children did not complete the verbal fluency task; each of
these children was excluded from the analysis of only that task. All
other participants completed all study tasks. Prior to their partic-
ipation, parents gave informed consent, and children gave verbal
assent. Children received small gifts (e.g., gliders, balls) through-
out the project for their participation, and parents received $5 as
compensation for travel.
DESIGN AND PROCEDURE
Children were individually tested in a single session lasting
approximately 1.5 h, with breaks given as needed. All children
completed tasks in the same order: AX-CPT, Flanker, forward
digit span (for other purposes, not discussed further in this
report3), verbal fluency, and the Expressive Vocabulary Test.
During the child tasks, parents provided demographic infor-
mation and completed surveys of children’s daily, annual, and
typical schedules, as well as an exploratory “helicopter parenting”
scale (not discussed further in this report; from Obradovic, pers.
commun., October 26, 2011).
Parent questionnaires
Parent survey of child time use. Parents reported all child activ-
ities during the week prior to the laboratory test session using a
computer-based survey. At the time that the study visit was sched-
uled, parents were informed that they would complete a detailed
child activity survey during their visit, and were encouraged to
take notes on their child’s activities throughout the week. Parents
were allowed to consult notes as they completed the survey. The
survey was formatted as a 36 ×7 grid, such that each cell rep-
resented a 30-min time interval during the prior week (intervals
occurring between midnight and 5:30 am were excluded to reduce
burden). In each cell, parents wrote short, open-ended descrip-
tion of their child’s activities, excluding times where children were
sleeping or in school (parents indicated sleep and school sched-
ules in a separate section of the survey). Before completing the
survey, parents were asked to indicate the extent to which their
family’s activities over the prior week reflected typical patterns of
time use. Parents rated their level of agreement with the prompt,
“Was your family’s schedule last week unusual or atypical?” via
a 7-point scale anchored by “Strongly agree” and “Strongly dis-
agree.” Parents were then given verbal and written instructions, as
follows:
3Forward digit span tasks (where children repeat numbers in the order they
are presented by an experimenter) primarily index storage capacity, rather
than combined storage and processing capacity, and therefore do not serve
as a reliable measure of EF (Daneman and Merikle, 1996; Engle et al., 1999).
“Be as specific as possible for every activity you report. For exam-
ple, for time spent in the car during a commute, rather than
writing, “Drove from ___ to ___,” you could write, “Watched
a DVD with his sister in the car while driving to the city for a
research appointment.
Indicate who your child was interacting with during a given
activity. For example, if your child had free time to play outside
between dinner and bedtime, rather than writing “Free time out-
side,” you could write, “Played tag outside with older sister and
friends from the neighborhood.” Or, if your child reads before
bedtime, rather than writing, “Reading time,” you could write,
“Read aloud to mom before bed.
Indicate simultaneous activities. For example, if your child ate
a snack after school or camp while he/she had some down time,
rather than writing “Snack time,” you could write, “Ate a snack
while coloring.
As parents completed the survey, experimenters periodically
reviewed responses and asked that parents modify entries that
were difficult to interpret or insufficiently detailed. Experimenters
were also available during breaks between tasks to respond to
parent questions about specific responses.
Child activity data were coded by three independent raters
who were blind to data on all other tasks during each stage
of the coding process. Coders assigned a numeric code to each
cell-based survey entry using an activity classification scheme
(Table 1). To ensure consistency across raters and reduce proce-
dural drift, all raters independently classified each cell for the first
35 participants. Coders then met to discuss major discrepancies
and to generate additional generalizable rules. Coders categorized
responses from the final 32 participants using these agreed-upon
criteria. The final 32 subjects were used to establish inter-rater
reliability; reliabilities among pairs of coders ranged from 0.96 to
0.97, with coders agreeing on 7942 to 8021 cells out of 8288 total
(i.e., 2 cells per hour ×18.5 h/day ×7daysaweek×32 par-
ticipants). Excluding sleep and school cells (where there were no
discrepancies between coders), reliabilities among pairs of coders
were also high, ranging from 0.93 to 0.95. The three coders met to
discuss discrepancies and generate a final, coded data set for each
participant.
After the raters generated the final set of activity codes, each
activity was further classified as either “Structured” or “Less-
Structured” based on the coding scheme outlined in Table 1,
following existing coding schemes (Meeks and Mauldin, 1990;
Eccles and Barber, 1999; Mahoney and Stattin, 2000; Hofferth
and Sandberg, 2001b; Fletcher et al., 2003; Osgood et al., 2005).
All child-initiated activities (play, spontaneous practice, reading,
watching television) and outings and events (museum or library
visits, sporting events) were coded as “Less-Structured.” Adult-led
lessons and practices, homework and studying, religious activi-
ties, and organization meetings (e.g., community service) were
coded as “Structured.
Parent survey of typical child time spent in less-structured
activities. In a separate survey, parents were asked to indi-
cate how often their children engaged in typical play activities
by using a 7-point scale (“Never,” “Less than once a month,
Once a month,” “2–3 times a month,” “Once a week,” “2–3
times a week,” “Daily”) to rate the following items: “Surf the
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Barker et al. Less-structured time and executive function
Table 1 | Classification of child time use (structured, less-structured,
and other activities).
STRUCTURED ACTIVITIES
Physical lessons (e.g., soccer practice, karate)
Non-physical lessons (e.g., piano lessons, art class)
Tutoring
Homework and study
Chores
Religious activities
Other formal organizational meetings and activities (e.g., community
service)
LESS-STRUCTURED ACTIVITIES
Unguided, child-initiated practice (e.g., playing piano or singing outside
of scheduled practice times; shooting goals outside of soccer practice)
Free play alone
Free play with others
Social outings
Visits to family and friends
Parties
Camping
Picnics
Other group activities (e.g., walks, bike rides, skiing, swimming,
bowling, golf)
Enrichment activities
Sightseeing
Aquarium and zoo visits
Museums
Miscellaneous educational events (e.g., science fair)
Other entertainment (e.g., live sporting events, performances, movies)
Reading
Media and screen time (e.g., TV, internet, video games)
OTHER ACTIVITIES
Sleeping
Meals/eating
School
Care by others
Personal care and hygiene
Child appointments
Commuting and travel time
Unknown/Unreported
All entries that parents provided in the child time use survey were classified into
these categories, following existing coding schemes (Meeks and Mauldin, 1990;
Eccles and Barber, 1999; Mahoney and Stattin, 2000; Hofferth and Sandberg,
2001b; Fletcher et al., 2003; Osgood et al., 2005).
internet,” “Watch television, videos/DVD, or online media,” “Play
video games (non-instructional),” “Play interactive instructional
or learning games,” “Play with toys alone,” “Play with toys
with friends/siblings,” “Play physical games with friends/siblings,
“Play physical games alone,” “Play non-physical games alone,
“Play card or board games with family,” “Read,” “Help with
housework or cooking,” “Play musical instrument”, “Listen to
music.” Scores on each item (where 1 =“Never” and 7 =“Daily”)
were summed to produce a typical less-structured activity score.
Parent survey of seasonal child activities. In a separate sur-
vey, parents were asked to indicate the number of hours their
child spent in structured lessons during the past year. Parents
responded to 18 common structured lessons (basketball, base-
ball, tennis, hockey, soccer, football, golf, swimming, dance,
gymnastics, martial arts, skiing/snowboarding, ice skating, music,
art, theater, and tutoring) and were asked to write in any
structured lessons that did not fall into these categories (most
commonly, religious activities, and organizational meetings). To
reduce burden, parents provided seasonal time estimations for
each activity (e.g., the typical hours per week a child spent partic-
ipating in music lessons over the prior fall). Data were reviewed
for accuracy to ensure that parent-reported structured activities
adhered to the same coding guidelines used to evaluate the Parent
Survey of Weekly Activities. Cumulative hours spent in structured
activities across the year were summed to produce an annual
structured hours score.
Household income. Parents reported annual household income
via an interval scale (median bracket: $100,000—$124,999;
range: <$25,000 to >$150,000 USD). Fourteen parents chose
not to disclose income information.
Child endogenous executive function measure
Verbal fluency. In the verbal fluency task, children were asked to
generate words in response to a categorical prompt. The task was
presented as a game to make it more engaging for children (as in
Snyder and Munakata, 2013). Children were told, “We’re going to
play a game where we think of lots and lots of words. I bet you’re
really good at thinking of words, aren’t you? I’ll tell you what kinds
of words to think of, and every time you tell me one, I’ll put a
pom-pom in your cup. Let’s see how many pom-poms you can
get before all the sand is gone (experimenter pointed to a 1-min
sand timer children could use to estimate how much time was
left). I’ll bet you can get a lot! And when we are all done think-
ing of words, you can trade the pom-poms for a prize.” Before
each category, the experimenter said, “This time I want you to
tell me as many [category name] as you can think of. Can you
think of lots and lots of [category name]? Ready, go!” The exper-
imenter placed a pom-pom in a clear plastic cup in front of the
child for each new exemplar. If children paused for 10 s or longer
between items, they were encouraged to continue (“Good job, can
you tell me some more [category name]?”). In the rare instance
where a child stated that she/he had named all words, the experi-
menter double-checked with the child (e.g., “Are you sure? What
other [category name] can you think of?”) and waited with the
child until the end of the block. Children completed three blocks
using this procedure, each of 1-min duration: a practice block
(with the prompt “household items”), and two test blocks (with
the prompts “animals” and “foods,” which were counterbalanced
across participants).
Verbal fluency data were transcribed from audio recordings,
and coded by the experimenter and two independent raters blind
to data on all other tasks. Coders identified clusters of items that
were semantically related (e.g., “cookies, pie, cake” when produc-
ing foods). Switches between clusters of related items were iden-
tified and summed to generate cumulative switch scores. Switch
scores were weighted by cluster size (as in Snyder and Munakata,
2010, 2013), such that 1 point was awarded for a switch after a
cluster of 2 related items, 2 points for a switch after 3 related items,
3 points for switch after 4 related items, and so on. Weighted
switch scores were used because they reflect increasing confidence
as cluster size increases that children are indeed clustering and
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Barker et al. Less-structured time and executive function
switching. Unweighted scoring systems (e.g., Troyer et al., 1997),
which count every transition between subcategories equally
(including between single, unclustered items), have been criti-
cized for confounding switching with a failure to cluster (e.g.,
Abwender et al., 2001). Inter-rater reliabilities were high between
all pairs (>85%). To generate cumulative switch scores for each
participant, weighted switch scores were averaged across coders
within each prompt, and then summed.
Child externally-driven executive function measures
Flanker. Children completed a computerized flanker task
(Eriksen and Schultz, 1979) assessing their ability to resolve
conflicting visual information by appropriately responding to a
central stimulus while ignoring flanking stimuli. The Flanker task
is a commonly-used measure of externally-directed EF in 6-year-
olds (e.g., Ridderinkhof and van der Molen, 1995; Rueda et al.,
2004, 2005; McDermott et al., 2007; Röthlisberger et al., 2012)
and has been shown to be sensitive to some interventions target-
ing EF in this age group (Fisher et al., 2011; Röthlisberger et al.,
2012). During the task, children were instructed to indicate the
orientation (left or right pointing) of a centrally-presented target
stimulus, via a corresponding button press. In congruent trials,
the target stimulus (the center fish) was surrounded by fish with
the same orientation. In incongruent trials, the target image was
surrounded by fish with an opposite orientation. In neutral tri-
als, only the target image was presented and was not surrounded
by any fish. Following a 10-trial practice block (4 congruent, 4
incongruent, 2 neutral), children completed three 32-trial blocks
of the task: two incongruent blocks (for each block, incongruent
trial N=16; neutral trial N=16), separated by one congruent
block(congruenttrialN=16; neutral trial N=16). Trials were
presented in random order within blocks.
Reaction times were used to assess children’s ability to resolve
interference among conflicting stimuli, as in past work with this
age group (e.g., Rueda et al., 2005; McDermott et al., 2007;
Röthlisberger et al., 2012). Incongruent trials require children to
attend to only the target middle fish and to ignore the surround-
ing fish. Therefore, the flanker task can be used to assess children’s
ability to filter out irrelevant information. Larger interference
costs (i.e., the difference between average response time on incon-
gruent trials and average response time on neutral trials) reflect
greater difficulty filtering irrelevant information. To assess filter-
ing ability, we first calculated participant mean response times
for each trial type (neutral, incongruent/congruent) within each
block across trimmed, correct trials (trials <100 and >3000 ms
were excluded, as well as any trials three standard deviations out-
side that participant’s mean for that trial type and block). To
generate robust estimates of possible interference effects (as sug-
gested by Lavie, 1995, and implemented in D’Ostilio and Garraux,
2012), incongruent/congruent trial mean RTs were contrasted
with neutral trial mean RTs from the same block, yielding one
congruent-neutral contrast and two incongruent-neutral con-
trasts within each participant. Flanker conflict scores were gener-
ated by subtracting the congruent contrast from each incongruent
contrast (yielding two conflict scores, one arising from each
incongruent block). These conflict scores were averaged to gen-
erate a summary flanker conflict score.
AX-CPT. Children completed the AX Continuous Performance
Task (AX-CPT), which provides a measure of proactive control,
or the tendency to maintain goal-relevant information until it
is needed (Braver et al., 2007). All procedures and analyses were
conducted as in Chatham et al. (2009). In this touchscreen-based,
child-friendly version, children are allowed to prepare for future
circumstances (the appearance of either “X” or “Y” image probes)
based on previous experiences (the appearance of “A” or “B”
image cues).
Children were instructed to respond with a target response
wheneverthe“A”contextcuewasfollowedbyan“X”probe.
Children were instructed to provide a non-target response to all
other cue-probe sequences (A – Y; B – X; B – Y). To improve child
engagement during the task, popular cartoon characters were
used as image stimuli, and the instructions took the form of char-
acter preferences. For example, children were told, “Spongebob
likes watermelon, so press the happy face when you see
Spongebob and then the watermelon,” and, “Blue doesn’t like the
slinky, so press the sad face when you see Blue and then the slinky.
After the experimenter explained the task rules, children com-
pleted a “verification” phase to ensure that they understood the
instructions and were capable of following rules. During this
phase, each cue–probe pair was presented sequentially, and par-
ticipants were asked to indicate the correct response for each pair.
If subjects responded incorrectly to a cue-probe pair, the experi-
menter repeated the relevant rule (“Remember, when you see [A,
B] and then you see [X, Y], tap this button [appropriate button
blinks] as quickly as you can!”) and subjects were allowed to try
again. Participants then completed 7 practice trials. Cues were
presented for 500 ms, followed by a 120 ms delay period, and a
subsequent 6 s probe, as in test trials. Test trials were presented in
four 30-trial blocks, where 70% of trials were target (A – X) trials,
and 30% were non-target trials (A – Y; B – X; B – Y, appearing in
equal proportion).
Proactive children show a characteristic behavioral profile that
can be used to generate an RT-based measure of proactive con-
trol. Children who engage proactive control generate fast RTs in
BX and BY trials, since maintenance of the “B” cue supports a
non-target response to the subsequent “X” probe, and slower RTs
on AY trials, since active maintenance of the “A” cue leads to
anticipation of an “X” probe (due to the expectancy generated
by asymmetric trial type frequencies). Proactive control was thus
calculated using the median of trimmed RTs on correct AY and
BX trials, which were entered into the formula (AY – BX)/(AY +
BX). All responses made <200 ms after the presentation of the
probe were removed from the analysis, resulting in the exclusion
of <1% of all trials.
Expressive vocabulary test. The EVT (Pearson Assessments,
Bloomington, MN) is a standardized, nationally normed,
expressive vocabulary test, which we used (as in Snyder and
Munakata, 2010) to control for differences in vocabulary that
might have influenced verbal fluency performance (i.e., a child
with a robust vocabulary might be capable of generating larger
clusters than a child with a limited vocabulary, independent of
either child’s switching ability). On each trial of the EVT, children
are shown a colored picture and are asked to name it or provide
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Barker et al. Less-structured time and executive function
a synonym (e.g., “Can you tell me another word for father?”).
Testing continues until children incorrectly answer five items in
a row, and raw scores are then converted into a standardized score
basedonage.
RESULTS
PRELIMINARY RESULTS AND ANALYSIS APPROACH
Weekly and annual/typical estimates of how children spent their
time (Figures 1A–C) were marginally correlated, for both struc-
tured activities (r=0.24; p<0.06) and less-structured activities
(r=0.23; p<0.071). We thus generated composite scores across
weekly and annual/typical estimates to provide a more accurate
and reliable measure of children’s time. Each composite measure
(for structured time, and separately for less-structured time) was
formed by summing z-scored time in prior-week activities with
z-scored ratings from the parent survey of annual/typical child
activities, within each participant.
All analyses were conducted using standard linear regression.
We included age, gender, and family income as factors in all
models, given that they or related factors are often predictive of
children’s EF: age (e.g., Welsh et al., 1991; Huizinga et al., 2006),
gender (e.g., Blair et al., 2005; Diamond et al., 2007), family
income Hughes et al., 2009; as a component of SES: (Farah et al.,
2006; Noble et al., 2005, 2007; Raver et al., 2013). Child vocabu-
lary, as indexed by EVT performance, was included as a covariate
in all tests of verbal fluency performance. Descriptive statistics for
executive function, vocabulary, and time use measures are given
in Table 2. Individual EF measures were not correlated, before
or after controlling for age (p’s >0.4). For all analyses, outlying
observations were identified (Cook’s D >3 standard deviations
above the mean) and removed. This resulted in the exclusion of
no more than four cases from any analysis.
CHILD TIME USE AND SELF-DIRECTED EF
Less-structured time
As predicted, children who spent more time in less-structured
activities demonstrated better self-directed EF, as indexed by
verbal fluency performance [η2
p=0.07; F(1,44) =4.46; p<0.05;
Figure 2A;Table 3]. In addition, older children and children
with higher vocabulary scores demonstrated better verbal fluency
performance [Age: η2
p=0.11; F(1,44) =7.45; p<0.01; EVT:
η2
p=0.10; F(1,44) =6.30; p<0.02]. In subsequent tests for
interactions, we found an unexpected interaction between less-
structured time and age [Less-structured time ×Age: η2
p=0.08;
F(1,43) =5.48; p<0.03]. Post-hoc tests indicated that additional
time in less-structured activities predicted better self-directed
control in most but not all children; specifically, this finding
held in both the youngest sample quartile [Mage =6.38 years,
Less-structured time: η2
p=0.07; F(1,43) =10.37; p<0.003]
and at the median [Mage =6.65 years, Less-structured time:
η2
p=0.07; F(1,43) =6.81; p<0.02], but not in the oldest quar-
tile (Mage =6.86 years; p>0.8). When the interaction between
less-structured time and age was included in the model, children
from higher-income households demonstrated marginally better
verbal fluency performance {Income: η2
p=0.05; [F(1,43) =3.36;
p<0.08]}. Age, vocabulary, and time in less-structured activities
also continued to predict self-directed EF [Age: η2
p=0.12;
F(1,43) =5.76; p<0.03; Vocabulary: η2
p=0.07; F(1,43) =4.80;
p<0.04; Less-structured time: η2
p=0.07; F(1,43) =6.81;
p<0.02].
Exploratory analyses. We next investigated whether specific
kinds of less-structured activities were driving the observed rela-
tionship between less-structured time and self-directed control.
Composite variables representing common less-structured activ-
ities were created by aggregating similar responses across prior-
week and annual/typical measures4. This procedure yielded seven
broad categories of less-structured activities: unguided practice;
play alone; play with others; social events with family (includ-
ing parties, camping, picnics, and other group outings, such as
hiking, biking, and swimming5), enrichment events (visits to
the museum, library, aquarium, or zoo; sightseeing; and miscel-
laneous educational events), other entertainment (movies, per-
formances, and live sporting events); reading; and media and
screen time. Enrichment activities [η2
p=0.11; F(1,44) =6.95;
p<0.02] and social events [η2
p=0.10; F(1,43) =7.26; p<0.01]
significantly predicted self-directed EF, and play with others
was marginally predictive [η2
p=0.05; F(1,44) =3.42; p<0.072].
Interactions with age were not significant in these models, and
were therefore excluded (p’s >0.2). No other classes of less-
structured activities predicted verbal fluency performance.
We then considered whether the relationship between less-
structured time and self-directed EF persisted when we excluded
from our less-structured time composite measure, in sequential
analyses:
(1) media and screen time (which might reflect passive, rather
than self-directed leisure activity);
(2) activities within the less-structured time classification that
may have included more structure than other such activities;
and
(3) enrichment activities that may have yielded benefits spe-
cific to verbal fluency performance (rather than self-directed
control, per se).
When media and screen time were excluded, less-structured
time continued to demonstrate a positive relationship with self-
directed EF [η2
p=0.06; F(1,41) =5.23; p<0.03]. This finding
persisted when we also excluded less-structured activities that
may have included more structure than other such activities (e.g.,
board games played with a group; rule-based physical games
such as golf and bowling; movies and performances; reading
with others6)[η2
p=0.06; F(1,43) =6.17; p<0.02]. As a final
step, we also excluded visits to museums, aquariums, and zoos,
which may have benefitted organization of semantic clusters on
4Aggregate within-measure scores were z-scored, then summed to create
cross-measure composites.
5Social and enrichment events included only prior-week reporting, as these
were not adequately identified in the annual less-structured time measure,
which included only general activities (e.g., playing outdoor with friends) that
could occur in many contexts.
6Here and in the following analysis, we also excluded all reading from our
typical-activities measure, because this measure did not discriminate between
reading alone and reading with others.
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Barker et al. Less-structured time and executive function
FIGURE 1 | Parent-reported child time use. (A) Activities in week prior
to laboratory visit (green, less-structured; blue, structured; gray, other).
(B) Typical less-structured activities (1, Never; 2, Less than once a
month; 3, Once a month; 4, 2–3 times a month; 5, Once a week; 6,
2–3 times a week; 7, Daily). (C) Typical structured activities during a
typical week (averaged across 4 seasons). Prior-week and typical
measures of parent-reported child time use were correlated and
combined into z-scored composite estimates of structured and
less-structured time. For all figures, error bars indicate standard error of
the mean.
the verbal fluency task (e.g., exposure to zoo animals may have
helped to organize animal clusters, and thus yielded performance
benefits). Using this fully-restricted measure of less-structured
time, child time in less-structured activities continued to pre-
dict better self-directed EF [η2
p=0.06; F(1,43) =6.23; p<0.02].
Interactions with age were significant and were included in each
of these restricted analyses (all p’s <0.05).
We also explored whether participation in types of less-
structured activities changed with age, and whether such chang-
ing patterns of time use could speak to the diminished link
Frontiers in Psychology | Developmental Psychology June 2014 | Volume 5 | Article 593 |8
Barker et al. Less-structured time and executive function
between less-structured time and self-directed control in the old-
est quartile of children in our sample. Media and screen time
use was more prevalent in older children [η2
p=0.05; F(1,61) =
5.15; p<0.03]. Time spent in other categories of less-structured
activities did not vary with age (p’s >0.2).
Structured time
Additional time in structured activities predicted marginally
worse self-directed control [η2
p=0.06; F(1,43) =3.57; p<0.07;
Figure 2B;Table 3]. Again, self-directed EF was predicted by
age [η2
p=0.13; F(1,43) =4.43; p<0.01], and vocabulary [η2
p=
0.08; F(1,43) =5.02; p<0.04], and marginally predicted by
household income [η2
p=0.05; F(1,43) =3.50; p<0.07]7.
Exploratory analyses.We next examined whether the relationship
between structured time and self-directed EF persisted when we
7This finding was not driven by a negative correlation between compos-
ite time in structured activities and time in less-structured activities. The
less-structured and structured time composites were not significantly related
(p>0.8).
Table 2 | Descriptive statistics for executive function, vocabulary, and
time use measures (Ns = 65–67).
Measure Mean (SD)
SELF-DIRECTED EF
Verbal fluency combined switch score 10.13 (4.1)
EXTERNALLY-DRIVEN EF
AX-CPT proactive control score 0.094 (0.12)
Flanker conflict score 164.5(168.7)
Vocabulary: EVT standardized score 112.9(9.4)
PRIOR WEEK CHILD TIME USE
Structured hours 6.03 (5.9)
Less-structured hours 32.2(14.2)
Typical child less-structured activities (combined score) 78.5(8.8)
Seasonal child structured activities (annual hours) 91.5(89.0)
excluded religious services and household chores, where children
may have been supervised less often by adults, relative to other
structured activities. Time in structured activities continued to
predict worse self-directed EF when religious services and chores
were excluded from thecomposite structured time measure [η2
p=
0.06; F(1,43) =4.28; p<0.05].
CHILD TIME USE AND EXTERNALLY-DRIVEN EF
No measure of child time predicted any aspect of externally-
driven EF (Figures 3A–D). Specifically, child time spent in
less-structured activities did not relate to performance on
either externally-driven EF measure (Flanker conflict score: p>
0.2; AX-CPT proactive control score: p>0.8). Similarly, time
in structured activities was unrelated to externally-driven EF
(Flanker conflict score: p>0.6; AX-CPT proactive control score:
p>0.3)8. Males demonstrated better Flanker conflict scores than
females [η2
p=0.10; F(1,46) =4.64; p<0.04]. No other variables
predicted externally-directed EF9.
DISCUSSION
Our findings offer support for a relationship between the time
children spend in less-structured and structured activities and the
8Although it is not a targeted measure of conflict resolution, overall accuracy
across all trials on the Flanker task has also been tested in prior intervention
work with children (Rueda et al., 2005; Fisher et al., 2011; Röthlisberger et al.,
2012), and is what improved in two prior intervention studies targeting EF in
this age group (Fisher et al., 2011; Röthlisberger et al., 2012). Overall accuracy
didimprovewithageinoursample[η2
p=0.16; F(1,47) =4.67; p<0.04],
but was not predicted by any other variables (ps>0.15).
9In separate analyses, we investigated whether the completeness of parent
reporting of child time influenced observed relationships between child time
use and EFs. For example, if parents who left fewer cells blank in the time use
survey had children with higher self-directed EF, this could have contributed
to the observed correlation between less-structured time and self-directed
EF, since parents who left fewer cells blank might report more time in less-
structured activities. However, completeness of reported time use did not
affect the results: it showed no relationship with any aspect of EF performance
(verbal fluency, AX-CPT, and Flanker ps>0.3), and controlling for it did not
change whether or not any findings were significant.
FIGURE 2 | Children’s self-directed EF (as measured in Verbal
Fluency) was predicted by more time spent in less-structured
activities (A), and marginally predicted by less time spent in
structured activities, although this relationship is not apparent
because the figure does not capture how the effects of age,
income, gender, and EVT were controlled for in all analyses (B).
Outlying observations have been excluded [N=3in(A);N=2
in (B)].
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Barker et al. Less-structured time and executive function
Table 3 | Effects of age, gender, income, vocabulary and time use on child verbal fluency performance.
Age, income, EVT, age, income, Less-structured time +age,
and gender and gender income, gender, and EVT
Var ia b le βtbPβtbPβtbP
(Intercept) 9.99 22.48 <0.001*** 9.95 22.13 <0.001*** 9.94 22.67 <0.001***
Age (days) 0.008 1.79 <0.09 0.013 2.95 <0.01** 0.011 2.73 <0.01**
Gender (1 =female;
1 = male)
0.008 0.02 >0.9 0.194 0.42 >0.6 0.392 0.82 >0.4
Household income 0.743 3.17 <0.01** 0.301 1.13 >0.2 0.372 1.48 >0.1
Vocabulary (EVT) 0.177 2.78 <0.01** 0.142 2.51 <0.05*
Less-structured time – – – 0.713 2.11 <0.05*
Less-structured time x age – – –
Structured time – – –
Model F-value 4.05 4.88 4.56
Model Adjusted R20.16 0.24 0.27
Less-structured time ×age Structured time +age,
+income, gender, and EVT income, gender, and EVT
Var ia b le βtbPβtbP
(Intercept) 10.09 23.86 <0.001*** 9.73 21.97 <0.001***
Age (days) 0.010 2.40 <0.05*0.012 2.90 <0.01*
Gender (1 =female;
1 = male)
0.375 0.82 >0.4 0.169 0.36 >0.7
Household income 0.442 1.83 <0.08 0.487 1.87 <0.07
Vocabulary (EVT) 0.120 2.19 <0.05*0.128 2.24 <0.05*
Less-structured time 0.854 2.61 <0.05*–– –
Less-structured time x age 0.008 2.34 <0.05*–– –
Structured time 0.596 1. 8 9 <0.07
Model F-value 5.10 4.34
Model Adjusted R20.33 0.26
Age, income, EVT scores, and less-structured and structured time composite scores are mean-centered. For each model, observations where Cook’s D >3 standard
deviations above the mean were identified and removed. NModel1 =45; NModels2–3 =44; NModels4–5 =43; *p<0.05; **p<0.01; *** p<0.001.
development of self-directed executive function. When consider-
ing our entire participant sample, children who spent more time
in less-structured activities displayed better self-directed con-
trol, even after controlling for age, verbal ability, and household
income. By contrast, children who spent more time in structured
activities exhibited poorer self-directed EF, controlling for the
same factors. The observed relationships between time use and EF
ability were specific to self-directed EF, as neither structured nor
less-structured time related to performance on externally-driven
EF measures. These findings represent the first demonstration
that time spent in a broad range of less-structured activities out-
side of formal schooling predicts goal-directed behaviors not
explicitly specified by an adult, and that more time spent in
structured activities predicts poorer such goal-directed behav-
ior. Consistent with Vygotskian developmental theory and pro-
grams that build on that theory, such as Tools of the Mind,
less-structured time may uniquely support the development of
self-directed control by affording children with additional prac-
tice in carrying out goal-directed actions using internal cues and
reminders. That is, less-structured activities may give children
more self-directed opportunities. From this perspective, struc-
tured time could slow the development of self-directed control,
since adults in such scenarios can provide external cues and
reminders about what should happen, and when.
Surprisingly, the relationship between less-structured time and
self-directed control changed with age in our participant sam-
ple, such that less-structured time predicted self-directed control
in all but the oldest quartile of participants. This interaction
between less-structured time and age was reliably observed across
increasingly restrictive measures of less-structured time. One
interpretation is that most but not all age groups within our sam-
ple spent their less-structured time in activities that encourage
the development of self-directed control. Indeed, despite a rela-
tively limited age range, our sample demonstrated differences in
the content of less-structured time across 6–7 years of age, with
older children spending more time engaged in media and screen
activities. However, time spent in unguided practice, enrichment
outings, and some forms of play was the main driver of the rela-
tionship between less-structured time and self-directed control in
our data, and time spent in such activities did not change as a
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Barker et al. Less-structured time and executive function
FIGURE 3 | Children’s externally-driven EF (as measured in AX-CPT and Flanker) was not predicted by their time spent in either less-structured
activities (A,C) or structured activities (B,D). Outlying observations have been excluded [N=1in(A,B);N=2in(C,D)].
function of age. Another possibility is that children who have less
developed self-directed control are more likely to benefit from
less-structured time (in the same way that some interventions
show the greatest benefits to children who show the worst ini-
tial performance, Connor et al., 2010; Diamond and Lee, 2011;
cf. Bierman et al., 2008), such that the oldest and most advanced
quartile of participants showed the least benefit.
While promising, it will be important for the present findings
to be replicated and extended to address a number of limitations.
For example, our sample came primarily from an affluent, subur-
ban sample. This sample nonetheless included a broad enough
range of incomes that income was predictive of self-directed
EF, and the relationship between less-structured time and self-
directed EF held even when controlling for income. However,
less-structured time may be especially beneficial to children in
safe, quiet, resource-rich environments, so it will be important
to test whether it differentially relates to self-direction in more
impoverished environments. In addition, although the current
test of the relationship between less-structured time and self-
directed EFs emerged from a targeted hypothesis, we conducted
multiple post-hoc exploratory analyses to explore the relationship
between specific activities and self-directed control, which are not
ideal conditions for statistical inference.
Another limitation of the present study relates to our con-
structions of less-structured and structured time, which are
imprecise, and most likely fail to capture important differences
across activities. The broad, standardized definitions of struc-
tured and less-structured time adopted in this study (e.g., Meeks
and Mauldin, 1990) ignore differences in the degree of indepen-
dence that children experience within and across activities. In the
present study, trips to museums, libraries, and sporting events are
each classified as less-structured, but may vary in relative struc-
ture. That is, a typical library visit, where children may select their
own sections to browse and books to check out, may involve much
less structure (and more self-directed time) than a typical sport-
ing event, where attention is largely directed toward the action on
the field or court. Similarly, although any activity within the cat-
egory of “media and screen time” counts as less-structured time,
this category includes activities that range from passive movie-
watching to self-directed internet searches to more structured
video games. Even those activities that seem less-structured by
definition, such as free play, can quickly become more structured
when adults, older siblings, or peers impose additional rules or
criteria. Indeed, many programmatic interventions have high-
lighted the importance of some structure to improve the quality
of children’s play and other learning experiences, and produce
benefits (Schweinhart et al., 2005; Lillard and Else-quest, 2006;
Diamond et al., 2007; Heckman et al., 2010; Lillard, 2012).
We note however, that even though our classification system
based on the existing literature does not capture these variations
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Barker et al. Less-structured time and executive function
in exactly how structured various activities are, our primary
finding of the relationship between less-structured time and
self-directed EF holds across analyses dropping potentially more
difficult-to-interpret classifications (e.g., media and screen time,
various games, movies and performances, and visits to muse-
ums, aquariums and zoos). To generate a more precise estimate
of the amount of time children spend pursuing activities in a
self-directed way, one would ideally assess child time directly,
possibly by supplementing parent-reported child time use data
with direct observation. One possibility along these lines could be
to employ experience sampling techniques (Miller, 2012), where
parents are frequently queried (via cell phone or another mobile
device) throughout the day and asked to provide specific detail
about their child’s activities in the moment. Such methods would
also minimize the need to rely on a parent’s memory for their
child’s daily activities and experiences. We view our work as
providing an important starting point for this kind of more time-
intensive study of children’s time outside of formal schooling and
its relationship to their self-directed EF.
Inaddition,althoughwehaveidentiedlinksbetweenchild
time use and self-directed EF, we are unable to draw firm con-
clusions about whether the observed relationships were driven by
activities occurring in the week preceding the test session (as has
been observed in other domains, e.g., Berns et al., 2013; Mackey
et al., 2013), activities occurring over a longer period, or some
combination. We used composite measures incorporating both
recent and more distal/typical experiences, given that these mea-
sures were correlated and in an attempt to maximize the accuracy
and reliability of parental estimates. We can test which one is more
predictive of self-directed EF, recent or more distal/typical expe-
riences, but it is difficult to make strong claims based on such
analyses. For example, when examining less-structured activities
and self-directed EF, we find that recent experiences predict self-
directed EF [F(1,60) =6.10; p<0.02], but typical experiences do
not (p>0.6). This finding could reflect the greater importance
of recent experiences, or it could reflect the greater precision of
the time-diary measure, which indexes recent experiences but is
also representative of more distal/typical experiences10
. Similarly,
when examining structured activities and self-directed EF, we
find that neither recent nor annual experiences alone predict self-
directed EF (p’s >0.2). This finding could reflect the importance
of the combination of recent and distal experiences, or simply the
greater robustness of using a composite measure. Therefore, while
10Recent less-structured experiences also predict self-directed EF when con-
trolling for parent-reported typicality of the prior week [η2
p=0.02; F(1,57) =
9.12; p<0.004; Mtyp =4; SD =2.05; range =1–7], and there is no inter-
action between less-structured experiences and typicality in predicting self-
directed EF (p>0.8). These findings might suggest that the prior week’s expe-
rience is predictive separate from the extent to which it reflects typical/distal
experiences. However, this interpretation rests on the validity and sensitiv-
ity of the typicality measure, which is unknown. Parent-reported typicality
is at least internally consistent with parent-reported time use. Specifically,
recent less-structured experiences predicted typical/distal experiences when
parent-reported typicality of the prior week was high [Mtyp =6; η2
p=0.03;
F(1,60) =5.81; p<0.02], but not when typicality of the prior week was low
(Mtyp =2; p>0.9), yielding a marginally significant interaction [Mtyp =2;
η2
p=0.04; F(1,60) =2.92; p<0.093].
we have posited that less-structured experiences allow children to
practice self-directed, goal-oriented behavior, producing benefits
over time, we cannot discount the possibility that observed link-
ages may have been driven by recent experiences which increased
self-directed behavior. In either scenario, regular participation in
less-structured activities would yield benefits.
Future investigations of the relationship between self-directed
control and less-structured time would also benefit from the
inclusion of additional measures of self-directed control, which
more closely approximate real-world child behaviors. This pro-
cess may benefit from the development and validation of new
measures of self-directed control in children. Establishing effects
using tasks tapping other forms of self-direction would also
ensure generalizability. For instance, in the present study, time in
less-structured activities such as family outings may have benefit-
ted verbal fluency performance in a specific way, by fostering the
development of more well-organized semantic networks, rather
than by more generally improving children’s abilities to generate
their own rules for how and when to employ EFs to achieve their
goals. This alternative account cannot explain the full pattern of
results in the link between less-structured time and self-directed
EF (e.g., the fact that this link persists when enrichment activ-
ities are excluded, and other less-structured categories such as
unguided practice and play predict self-directed EF); however,
a broader range of measures could provide a more robust and
generalizable assessment of self-directed EF.
The findings of the current study are consistent with previ-
ous research in showing a link between children’s experiences
and EF (Lillard and Else-quest, 2006; Diamond et al., 2007;
Bierman et al., 2008; Holmes et al., 2009; Bergman Nutley et al.,
2011; Diamond, 2012; Röthlisberger et al., 2012; Zelazo and
Lyons, 2012; Titz and Karbach, 2014). However, while the cur-
rent study found specific effects of time use on self-directed but
not externally-driven EF, previous research found effects of train-
ing and preschool interventions on externally-driven EF (e.g.,
see discussion in Diamond, 2012), but did not evaluate self-
directed EF. There are several possible reasons for this discrep-
ancy. First, previous training studies that have shown benefits for
externally-driven EF have specifically trained children on aspects
of externally-driven EF (e.g., working memory span tasks; e.g.,
Holmes et al., 2009; Bergman Nutley et al., 2011). Likewise, while
preschool and other interventions include a wide variety of expe-
riences, they likely include considerable practice with externally-
driven EF. In contrast, we hypothesize that less-structured time
primarily affords children practice with self-directed EF, and thus
may not transfer to improving externally-driven EF. Second, it
is possible that differences between the current versus previ-
ous studies could be accounted for by differences between the
externally-driven EF tasks they employed. Many previous studies
that have found effects of interventions on externally-driven EF
used task-switching or working memory span tasks (e.g., Lillard
and Else-quest, 2006; Diamond et al., 2007; Bierman et al., 2008;
Holmes et al., 2009, 2010; Thorell et al., 2009; Bergman Nutley
et al., 2011; Röthlisberger et al., 2012), whereas the current study
used tasks assessing proactive control (AX-CPT) and conflict
resolution (Flanker). It may be that specific aspects of externally-
driven EF are more sensitive to children’s experiences, or that
Frontiers in Psychology | Developmental Psychology June 2014 | Volume 5 | Article 593 |12
Barker et al. Less-structured time and executive function
specific tasks are more sensitive to individual differences in gen-
eral due to better psychometric properties11
. Future research using
a more comprehensive battery of EF tasks could address these
possibilities.
Another key difference between our study and such prior
research is the correlational nature of our study, which supports
at least two alternatives to the interpretation that how children
spend their leisure time shapes their EF. First, children with bet-
ter self-directed EFs may engage in (or be encouraged to engage
in) less-structured activities more often. Likewise, children with
poorer self-directed control may be more likely to engage in struc-
tured activities. Alternatively, the observed relationship between
less-structured time and self-directed control may be driven by a
third, unmeasured variable. Although we have attempted to con-
trol for some characteristics that might influence both time spent
in less-structured activities and verbal fluency, such as household
income, we have not controlled for other possibilities, such as par-
ent EF and child’s fluid intelligence (which we did not assess).
However, we did control for child vocabulary (an index of crys-
tallized intelligence), which may serve as a proxy for fluid intelli-
gence in testing relationships with EF, given that EF fully mediates
the correlation between crystallized and fluid intelligence in 7-
years-old (Brydges et al., 2012)12
. Moreover, such factors might
be expected to predict both children’s self-directed EF and their
externally-driven EF (Ardila et al., 2000; Mahone et al., 2002;
Kalkut et al., 2009), and so seem unlikely to explain why less-
structured time predicts only the former. Similar issues have been
raised in interpreting links observed between children’s EF and
pretend play: rather than reflecting a uniquely causal role for pre-
tend play in EF, EF may instead play a causal role in supporting
pretend play, or pretend play may be one of many activities pro-
moting EF development in young children (Lillard et al., 2013).
An important direction for future work lies in establishing the
directionality of relationships between child time use and self-
directed EF, through experimental manipulation. Longitudinal
studies could provide the first step toward establishing direc-
tionality. Specifically, if time spent in less-structured activities
prospectively predicts change in self-directed EF, this would sug-
gest that less-structured time may play a causal role in the devel-
opment of self-directed EF. If, on the other hand, self-directed
EF prospectively predicts changes in the amount of time children
spend in less-structured activities, this would suggest that self-
directed EF may play a causal role in children’s time use (e.g.,
because parents might allow children with strong self-directed
EF skills to play with less supervision). While such longitudinal
11For example, some EF-interventions have not improved performance on the
Flanker task in this age group (Rueda et al., 2005, 2012; see also Diamond et al.,
2007, which introduced switching demands that did show effects of interven-
tion, and included only incongruent trials so that a standard conflict score
could not be computed). The Flanker task can be sensitive to minor variations
in stimulus parameters (Paquet, 2001) and intervention dosage in adults (Liu-
Ambrose et al., 2012). Failures to find effects of interventions have also been
attributed in part to the task’s sensitivity to practice effects in pre-post mea-
sure designs (as discussed in Rueda et al., 2012), which are not an issue in the
present study.
12We also note that there is ongoing debate regarding the inappropriateness
of IQ as a control in models of cognitive processes (Dennis et al., 2009).
studies could thus provide important information about tem-
poral precedence, this information is not sufficient evidence of
causality (e.g., additional unmeasured variables could actually
be the causal factors). Thus, future research using experimental
manipulations of time spent in less-structured activities is nec-
essary to definitively test causality. One approach would be to
attempt to randomly assign children to more structured or less
structured environments, such as summer camps, where child
activities could be carefully monitored via regular sampling of
staff and/or on-site observation. Although this kind of work is
ambitious, and poses challenges, it could be used to inform more
targeted laboratory-based training studies.
Finally, we hope that future explorations of the relationship
between child time use and developing self-directed EFs will
inform a wider question: specifically, whether societal shifts in
child time use over the past 50 years have influenced devel-
opment. Hours formerly devoted to less-structured, social play
have been replaced by media time (Vandewater et al., 2007;
Bavelier et al., 2010; Hofferth, 2010; Johnson, 2010), and struc-
tured, adult-led activities (Hofferth and Sandberg, 2001a; Larson,
2001; Bianchi et al., 2006). Some commentators have warned
that these changes have been to the detriment of children (e.g.,
Ginsburg, 2007; Milteer and Ginsburg, 2012). Others have argued
that children benefit more from regular skill practice in structured
settings (e.g., Chua, 2011; Ramdass and Zimmerman, 2011). Our
findings indicate that during children’s time outside of formal
schooling, participation in less structured activities may bene-
fit the development of self-directed EFs, while participation in
structured activities may hinder the development of self-directed
EFs. Thorough testing of this hypothesis remains an important
direction for future work.
AUTHOR CONTRIBUTIONS
Jane E. Barker, Andrei D. Semenov, and Yuko Munakata con-
tributed to the development of the study hypothesis. All authors
contributed to study design. Jane E. Barker performed the data
analysis and drafted the manuscript with input from Yuko
Munakata. Critical revisions were contributed by Hannah R.
Snyder, Laura Michaelson, and Yuko Munakata. All authors dis-
cussed the results, implications, and literature, and approved the
final version of the manuscript for submission.
ACKNOWLEDGMENTS
The authors wish to thank Julia Stadele for her assistance in cod-
ing verbal fluency data and coordinating research subjects, Joe
Brill for his assistance in coding time diary data, and Ryan Guild
for his helpful comments on manuscript revisions. This research
was supported by a grant from the National Institute of Child
Health and Human Development (RO1 HD37163). Publication
of this article was funded by the University of Colorado Boulder
Libraries Open Access Fund.
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Conflict of Interest Statement: The authors declare that the research was con-
ducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 04 February 2014; accepted: 27 May 2014; published online: 17 June 2014.
Citation: Barker JE, Semenov AD, Michaelson L, Provan LS, Snyder HR and
Munakata Y (2014) Less-structured time in children’s daily lives predicts self-directed
executive functioning. Front. Psychol. 5:593. doi: 10.3389/fpsyg.2014.00593
This article was submitted to Developmental Psychology, a section of the journal
Frontiers in Psychology.
Copyright © 2014 Barker, Semenov, Michaelson, Provan, Snyder and Munakata.
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Frontiers in Psychology | Developmental Psychology June 2014 | Volume 5 | Article 593 |16
... However, research exploring young children's typical activities at home, and links with executive function skills, is scarce. Prior work indicates that time in less-structured activities-where children have many opportunities to make choices and set goals-predicts 6-year-olds' self-directed executive function skills (Barker et al., 2014); yet it is not known whether similar patterns hold for younger children. ...
... Less-structured activities have been posited to help children develop self-directed executive function skills-which involve engaging control in response to internal cues-by allowing children to practice using it by making choices (Barker et al., 2014). Self-directed executive function contrasts with cued executive function, where children engage control in response to others' explicit instructions. ...
... Optimizing performance on this task requires determining for oneself when to shift to a new subcategory (e.g., from fruit to vegetables). Findings held when controlling for various potential confounds (e.g., socioeconomic status and verbal skills; Barker et al., 2014). The authors theorized that exercising self-directed control by making one's own choices in daily life fosters its development. ...
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... Si bien se ha demostrado un efecto favorable de los ambientes y las actividades estructurados, social e intelectualmente estimulantes en procesos cognitivos de alto nivel (Center on the Developing Child at Harvard University, 2017; Dickinson et al., 2019), existe evidencia de que las actividades no estructuradas, como el juego libre, los eventos sociales con familia y amigos, la práctica de un deporte u otras actividades de entretenimiento, ofrecen oportunidades para la práctica de las funciones ejecutivas autodirigidas. Los niños que experimentan una gama más amplia de actividades e interacciones sociales tienen un mejor desempeño en este tipo de funcionamiento, incluso al controlar por otras variables, como la edad, la habilidad verbal y el ingreso familiar (Barker et al., 2014). ...
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... Sport can also offer youth opportunities to experience challenges, enjoyment, increased self-efficacy, choice of autonomy (decision making), and decreased stress (Carreres Ponsoda et al., 2012). Youth sport participation has been associated with adult career achievement (Barker et al., 2014) and reduced school dropout and delinquent behavior (Chang et al., 2021). These findings highlight the potential for sport to enhance positive development, especially among underserved children. ...
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... Better childhood EF has been related to more positive parenting (e.g., warmth and responsiveness), less negative parenting (e.g., control and intrusiveness), and parenting that is more cognitive (e.g., autonomy support and scaffolding) (Valcan et al., 2018). When children have more unstructured time in their daily life for using engaging EFs, better self-directed executive functioning is displayed on laboratory tasks (Barker et al., 2014). By contrast, when parents and other adults in children's lives show unpredictable and unreliable behavior, this is associated with poorer executive functioning on tasks regarding delayed gratification and temporal discounting (Mauro and Harris, 2000). ...
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... Contemporary longitudinal and experimental evidence provides some support for the theory that EFs are developed during play. Increased free time is associated with self-directed executive functioning (Barker et al., 2014), positive adaptive behavior, and even academic success (Lehrer et al., 2014), suggesting that children's autonomy over their activities may practice EFs (Barker and Munakata, 2015). Large longitudinal data suggest that time spent playing at 2-5 years of age predicts self-regulation, including inhibition and other EFs, 2 years later (Colliver et al., 2022). ...
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Background Young children’s play is theorized to develop executive functions, skills strongly predictive of many later advantages. The current study sought to validate a practicably short play behavior survey for kindergarten teachers ( N = 18) and compare the reported behaviors to the executive functions (EFs) of their 443 Russian kindergarteners ( M age = 78.6 months; SD = 4.04). Research Findings The factor model with satisfactory construct validity and internal consistency included three factors: leadership, play preferences and rule conformity. Analyses provide partial support for Vygotsky’s theory that play supports EF development, but particular behaviors were related to different EF components. However, kindergarteners exhibiting more leadership, preferences and conformity overall rated higher on most EF components. Practice and Policy These findings do not support the theory that play skills improve unidirectionally with age and EFs, suggesting particular profiles of types of players and complex changes with age. The play behavior survey may be a practicable way to trace different profiles across the early years.
... • Play strengthens social skills, including turn taking, collaboration, rule following, empathy, impulse control, and motivation (Corsaro 2003;Krafft and Berk 1998;Ramani 2012); the ability to express emotions (Rogers and Sawyers 1988); and the development of self-regulation and executive functioning in young children (Barker et al. 2014;Bodrova and Leong 2007;Elias and Berk 2002). It also has benefits for self-esteem and overall well-being (Knight 2009;Whitebread 2017). ...
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