Walk for well-being: The main effects of walking on approach motivation

Abstract

The purpose of this study was to investigate the role of exercise in the development of self-efficacy and approach motivation. An 8-week blind experimental design was used (N = 185), with two control and two treatment groups. Already physically active participants were assigned to one control group, while participants that reported a sedentary lifestyle at pretest were randomly assigned to either a sedentary control group or one of two treatment groups that began a brisk walking intervention. Treatment group participants walked either outdoors or indoors for 30 min per day, 4 days per week, for 8 weeks. The indoor/outdoor treatment group assignment was implemented to determine if exercising outdoors enhanced the outcomes. Significant main effects of walking were found for exercise self-efficacy, general self-efficacy and global approach motivation tendencies. Walking outdoors resulted in the greatest gains in general self-efficacy and global approach motivation. Given the alarmingly sedentary nature of American culture, these findings further evidence how simple changes in physical activity may have profound effects on well-being.

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Motivation and Emotion
https://doi.org/10.1007/s11031-018-9726-y
ORIGINAL PAPER
Walk forwell-being: The main effects ofwalking onapproach
motivation
ChristineWeinkauDuranso1
© Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract
The purpose of this study was to investigate the role of exercise in the development of self-efficacy and approach motivation.
An 8-week blind experimental design was used (N = 185), with two control and two treatment groups. Already physically
active participants were assigned to one control group, while participants that reported a sedentary lifestyle at pretest were
randomly assigned to either a sedentary control group or one of two treatment groups that began a brisk walking interven-
tion. Treatment group participants walked either outdoors or indoors for 30min per day, 4days per week, for 8weeks. The
indoor/outdoor treatment group assignment was implemented to determine if exercising outdoors enhanced the outcomes.
Significant main effects of walking were found for exercise self-efficacy, general self-efficacy and global approach motiva-
tion tendencies. Walking outdoors resulted in the greatest gains in general self-efficacy and global approach motivation.
Given the alarmingly sedentary nature of American culture, these findings further evidence how simple changes in physical
activity may have profound effects on well-being.
Keywords Approach motivation· Emerging adulthood· Exercise· Outdoors· Self-efficacy
A significant body of research supports the importance of
physical activity for staving off obesity (Annesi and Ten-
nant 2014), symptoms of depression (review in Stanton and
Raeburn 2014), stress (Clark etal. 2014; Klaperski etal.
2013), heart disease (Joyner and Green 2009; Kalenderian
etal. 2009; Korhonen etal. 2011), high cholesterol (Alpert
2010; Mediano etal. 2010), and other physical maladies
that are endemic in the United States. Additionally, sig-
nificant research supports the role of exercise in develop-
ing self-esteem (Fox 2000; Joseph etal. 2014; Opdenacker
etal. 2009) and enhancing positive affect (Joseph etal. 2014;
Sibold and Berg 2010). While the body of exercise research
is substantive, less empirical work has focused on ways that
exercise, especially exercise in outdoors, may contribute to
the broader context of human flourishing.
While flourishing is not a new concept (ancient philos-
ophers held discourse on the meaning of life and what it
meant to live well, centuries ago), positive psychologists
have brought a new energy to the topic (Seligman and Csik-
szentmihalyi 2000). Positive psychologists have worked to
highlight the importance of understanding the better things
in life, or the more positive elements of the human condition,
since the field officially began nearly 20years ago (Seligman
and Csikszentmihalyi 2000). In those 20years, many gains
have been made in understanding the good life. Research on
flourishing has uncovered several theories about the many
influences across the lifespan (Lopez 2008; Ryff 1989; Selig-
man 1990). The concept of well-being is one of these areas
of interest: what is well-being, how do we measure it, and
how do we experience it?
One of the foundational principles of positive psychology
is that well-being, specifically subjective well-being, is more
than the absence of disease or disorder, but is highlighted
by life satisfaction and frequent positive affect with low
levels of neuroticism (anxiety) and negative affect (Selig-
man 1990). Additions to this foundational work in positive
psychology include Ryff’s (1989) theory of psychological
well-being, defined as the presence or pursuit of autonomy,
environmental mastery, personal growth, life purpose,
Portions of this study were presented at the Society for the
Study of Emerging Adulthood conference (November, 2017),
Washington, D.C.
* Christine Weinkauff Duranso
cweinkau@csusb.edu
1 Department ofPsychology, California State University – San
Bernardino, SanBernardino, CA92407, USA

Motivation and Emotion
1 3
positive relationships, and self-acceptance. Since the goal
of positive psychology is to not merely the alleviation or
prevention of health issues like obesity, depression, heart
disease or high cholesterol, but more globally to strive for
flourishing (growth, mastery, satisfaction), scholars should
support this goal by studying the variables and contexts that
may contribute to flourishing.
Approach motivation
Approach motivation is the desire to focus energy or behav-
ior toward positive stimuli (objects, events, possibilities) and
to promote and sustain positive situations (Elliot 2008). A
person that practices approach motivational tendencies dem-
onstrates a willingness to face challenges and perceives them
as opportunities for learning and personal growth (McClel-
land 1985). Avoidant motivation is the desire to focus energy
or behavior away from negative stimuli (objects, events, pos-
sibilities) and to prevent or escape from negative situations
(Elliot 2008). A person who practices avoidance motiva-
tional tendencies experiences a desire to avoid failure or
conflict (McClelland 1985), and perceives challenge as an
opportunity to fail (Elliot etal. 2006; Nikitin and Freund
2008; Urry etal. 2004). Nikitin and Freund (2008) found
that embracing an approach motivation positively predicted
approach goals, which in turn positively predicted well-
being (Elliot etal. 2006; Nikitin and Freund 2008).
Approach motivation is correlated with exercise (Loch-
baum etal. 2013). Additionally, Vogt etal. (2010) found that
a sustained walking program for elderly individuals resulted
in increases in frontal brain activity, suggesting an increase
in approach-related tendencies. Vogt etal. (2010) measured
frontal brain activity immediately following a 45–60min
walk, but did not measure for long term changes in approach
tendencies, leaving unanswered whether these changes are
short lived or long term. It is not clear, yet, whether exer-
cise, including walking, might promote approach motive
tendencies long term. Previous research has suggested that
tendencies toward approach motivation are malleable (Fryer
and Elliot 2007), influenced largely by life experiences that
inform an individual’s evaluations of competency (Elliot
and Church 1997; Senko and Harackiewicz 2005). In other
words, high competency beliefs (self-efficacy) contribute to
an approach motivation tendency (Elliot and Church 1997).
Self‑ecacy
Bandura (1997) defined general self-efficacy (GSE) as a
belief that you have the skills necessary to accomplish goals
or to exert control over the events of your life. Bandura also
noted that this belief could be more specific to tasks in a
particular life domain (Bandura 1997). As such, exercise-
specific self-efficacy (ESE) is a belief about your ability
to successfully complete a type of exercise (“I can walk
5 miles.”). A common finding in exercise research is that
regular physical activity provides incremental successes that
contribute to heightened ESE as well as general self-efficacy
(GSE; Biddle etal. 2003; Caldwell etal. 2009).
Exercise
Regular exercise has also been positively associated with
increases in a variety of positive psychological components,
such as psychological well-being, optimism, and self-effi-
cacy across the lifespan (Bray and Born 2004; Caldwell etal.
2009; Johnson and Krueger 2007). According to Bray and
Born (2004), regular vigorous exercise, enough to elicit psy-
chological benefit, is an activity requiring effort strenuous
enough to cause heavy breathing or sweating, sustained for a
minimum of 20min, at least three times per week for at least
2months. This definition of exercise allows for flexibility
or variation in exercise intensity based on each individual’s
state of fitness and physical health.
There has been speculation in the exercise literature
regarding variations in outcomes due to contextual varia-
bles, such as the location of the exercise. When choosing to
exercise outdoors or indoors, it appears that stepping outside
might help.
Exercise context: indoors versusoutdoors
An interesting subsection of exercise research has studied
the influence of context on exercise outcomes, such as how
exercising outdoors has a stronger effect on positive affect
(Loureiro and Veloso 2014), vitality (Plante etal. 2007),
and focus (Ryan etal. 2010) when compared to exercising
indoors. Considering this seeming moderating effect that
being outdoors brings to exercising, this study assigned
some participants to exercise indoors and others outdoors.
This assignment allowed for comparisons to see if exercising
outdoors increased the strength of the outcome variables.
To summarize, the goal of this study was to test the con-
tributions of exercise to self-efficacy (exercise-specific and
general) and approach motivation (exercise-specific and
global). Given the extant literature on exercise and approach
motivation, it was hypothesized that participants who exer-
cise regularly would exhibit higher levels of approach moti-
vation tendencies than those who do not exercise at pre-
test. The second hypothesis predicted that participants who
exercise, both long term-exercisers and those who exercised
in this study for 8weeks, would report higher ratings on all
outcome variables than participants who do not exercise.

Motivation and Emotion
1 3
A secondary goal of this study was to investigate the
influence of exercising outdoors on the outcome variables.
Considering the seeming moderating effect that being out-
doors brings to exercising, this study assigned some partici-
pants to exercise indoors, and others outdoors. This assign-
ment allowed for outcome comparisons to see if exercising
outdoors changed, specifically if it increased the strength
of, the relationship between exercise, self-efficacy (exercise-
specific, and general), and approach motivation (exercise-
specific and global). The third hypothesis predicted par-
ticipants who exercise outdoors would experience greater
increases in all outcome variables than participants who
exercise indoors, or those who do not exercise at all.
Methods
Research design
To provide sufficient time for exercise to have a meaning-
ful effect, an 8-week brisk walking intervention was imple-
mented. A two-treatment, two-control group experimen-
tal design allowed for several baseline comparisons and
between-within group changes longitudinally.
Participants
Participants were recruited at a southern California uni-
versity campus with age (18–22years old) and full-time
undergraduate college student status as inclusion variables.
Participants earned extra credit for each week of participa-
tion in the study. Participants who completed the study were
entered in a drawing for a fitness watch, a $50 gift card, and
four computer tablets.
Pretest sample size was N = 235. After attrition and
removal of missing data, the post-test sample was N = 185,
which included: 77.3% females, 20.5% males, and 2.2%
gender not reported. Mean age was 19years (range 18–22).
Ethnicity closely reflected campus demographics: 66.5%
Hispanic, 8.1% White, 5.9% Asian, 5.4% African-Ameri-
can, and 14.1% reported multiple ethnicities, other, or not
reported.
Group assignment
Participants who indicated on the demographic form that
they currently exercise (for at least 6months) were assigned
to the exercising control group. All other participants
responded “no” when asked if they exercised, and were ran-
domly assigned to one of three groups: the non-exercising
control group, indoor, or outdoor walking treatment groups.
Instruments andmaterials
Exercise-specific approach motivation scale
Conroy etal. (2003) Achievement Goals Questionnaire
for Sport (AGQ-S) was used to measure exercise-specific
approach motivation (EXAM). This 12-item inventory is a
sport-specific adaptation of Elliot and McGregor’s (2001)
2 × 2 Achievement Goals Questionnaire. Conroy etal. (2003)
revised the wording of the original questionnaire from an
academic achievement goal focus to an exercise-specific one,
and surveyed 356 recreational athletes at a large university in
the United States. Just as in Elliot and McGregor’s findings
in the 2 × 2 framework (Mastery Approach, Mastery Avoid-
ance, Performance Approach, Performance Avoidance), the
Mastery Approach component was the only variable not
strongly correlated with fear of failure. For this study, only
the three questions targeting Mastery Approach were used.
For the Mastery Approach questions, participants responded
to questions such as “It is important to me to perform as well
as I possibly can,” and “It is important for me to master all
aspects of my performance”. Participants were instructed
to consider their thoughts and feelings about their current
physical activities when responding, using a 7-point Likert
scale ranging from 1 (not at all like me) to 7 (completely
like me).
Exercise-specific self-efficacy measure
Kroll etal. (2007) Exercise Self-Efficacy Scale (ESES) was
used to measure ESE. This 10-item scale showed strong reli-
ability (Cronbach’s alpha = 0.93) and high internal consist-
ency (confirmed using split halves; EQ Length Spearman
Brown = 0.88). The ESES was initially designed to test ESE
in individuals with spinal cord injury, but has since been
used in a variety of settings, both clinical and non-clinical,
especially for low-fitness individuals beginning or return-
ing to exercise (Bland etal. 2013; Nessen etal. 2015). This
scale was chosen because of the low-fitness/new exercise
element. Using this scale, participants in this study were
asked to respond to questions such as “I am confident that I
can accomplish my physical activity and exercise goals that
I set,” and “I am confident that I can be physically active
or exercise even when I am tired.” Participants rated their
responses using a 4-point Likert scale ranging from 1 (not
at all true) to 4 (always true).
General self-efficacy measure
The New Generalized Self-Efficacy Scale (Chen etal. 2001)
was used to measure GSE. This 8-item scale has high inter-
nal consistency and reliability (alpha = 0.86, 0.90), as well as
convergent and discriminant validity, as evidenced in three

Motivation and Emotion
1 3
studies carried out by the measure’s authors (Chen etal.
2001). Using this scale, participants in this study responded
to such statements as “I will be able to achieve most of the
goals that I have set for myself,” and “I will be able to suc-
cessfully overcome many challenges,” using a 5-point Likert
scale with 1 indicating strong disagreement and 5 indicating
strong agreement.
Global approach motivation measure
A revised version of The Appetitive Motivation Scale
(Leone etal. 2011) was used to measure individual behav-
ioral tendencies toward global approach motivation (GAM).
This 14-item revision of Jackson and Smillie’s (2004) origi-
nal Appetitive Motivation Scale was found to have a suitable
fit with a 2-factor correlated model (r = .39,, p < .01) and
a Cronbach’s alpha of 0.83 for the first factor (appetitive
motivation) and 0.79 for the second factor (impulsivity). A
CFA was also conducted (Leone etal. 2011) and showed
satisfactory results for the same model [χ2(76) = 486.10,
p < .01; RMSEA 0.079; CFI 0.95]. Using this scale, partici-
pants responded to such statements as “I like to put plans
into action,” and “I actively look for new experiences,” using
a 5 point Likert scale with 1 indicating strongly disagree and
5 indicating strongly agree.
Activity logs
Participants used weekly activity logs to record their leisure
or physical activities. These logs were used to capture day,
time, duration, and context of each activity. Active partici-
pants (exercising control group, or treatment group mem-
bers) tracked exercise activities, including the location of the
exercise (indoors, outdoors), presence of other individuals,
and any interactions they had with others. The non-exercis-
ing control group participants logged leisure activities such
as relaxing with friends or playing video games.
Mapmywalk smartphone application
Participants in the outdoor walking group were instructed
to establish a free account on the Mapmywalk (2016) smart
phone application. This application provides walking maps
for trails and routes across the country, with distance and
elevation statistics provided free to individuals who register.
This application was used to measure the time, distance, and
pace of their walking activities as a manipulation check.
While participants may find it rather easy to falsify informa-
tion on activity logs, it is more difficult to manufacture data
in the smartphone application that uses the GPS from their
phone to map their route, distance, and time spent walking
with a date and time stamp embedded in the application.
Participants in the outdoor walking group were instructed
to submit the data from the Mapmywalk (2016) app along
with their activity logs at the study’s conclusion. Participants
in the indoor walking group were instructed to use the smart-
phone application, but this was abandoned during the study
due to complications with its use indoors. For instance, the
application could not track distance when a participant was
walking on a treadmill.
Procedure
This study was listed in an IRB-approved university research
database to recruit participants. It was described as an
investigation of leisure activities and well-being, to shield
participants from the true nature of the study. Interested
students attended an informational meeting, at which time
they received a brief introduction to the study and participa-
tion requirements; those who wished to participate read and
signed the informed consent.
Participants completed the pre-test surveys then met by
group assignment to receive further instructions and the first
week’s activity log. Participants in the exercising control
group were instructed to track their exercise on the weekly
activity logs (exercise type, duration and location), and to
maintain their usual exercise habits. Participants in the non-
exercising control group were instructed to track their leisure
activities on the weekly activity logs. Leisure activities were
defined as any activity that was freely chosen by the partici-
pant such as listening to music, hanging out with friends, or
playing video games.
Indoor walking group members were instructed to walk
briskly indoors for at least 30min, four times per week, for
8weeks. Outdoor walking group members were instructed
to walk briskly outdoors for at least 30min, four times per
week, for 8weeks. Participants in both groups were encour-
aged to find a walking pace that raised their heart rate and
breathing and could be maintained for the entire 30min. To
eliminate potential confounding effects from social inter-
action, participants in both groups were instructed to walk
alone.
The outdoor walkers were instructed to avoid walking
at night or with headphones, to minimize risk to personal
safety. Indoor and outdoor walkers were instructed to stop
walking if they felt faint, short of breath, dizzy, or injured.
They were instructed to seek medical assistance immediately
if the condition persisted.
After 8 weeks, participants completed post-test measures
and participants from the outdoor walking group submit-
ted the information from the Mapmywalk application. All
participants were debriefed, and the raffle for the prizes was
conducted. Members in the two control groups were given
information regarding the walking program and the Map-
mywalk application.

Motivation and Emotion
1 3
Results
Data management andattrition analyses
Participants who did not turn in all of the required forms
(n = 4), or did not complete the study (n = 46), were
removed from the data set (n = 50). T-tests on demo-
graphics were run to compare the groups before and after
attrition/missing data removal. No significant differences
were found. Because of variability in group drop-out rates,
t-tests were run to see if there was a significant difference
in pre-test scores in the participants that remained in the
study (N = 185) and those that dropped out (N = 50). There
were no significant differences.
A one-way ANOVA was run to test the first hypothesis:
Regular exercisers will report higher levels of EXAM and
GAM tendencies than those who do not exercise. Exercis-
ing control group participants were compared to all oth-
ers at pre-test. The test for EXAM was not significant,
t(183) = 1.21, p = .23. The test for GAM was also not sig-
nificant, t(183) = 1.79, p = .08.
Post‑test betweengroup comparisons
The second hypothesis predicted that there would be a
significant difference on all variables at post-test, when
comparing both long term (exercising control group) and
new exercisers (indoor and outdoor walkers) with the
non-exercisers (non-exercising control group). A one-way
ANOVA revealed partial support. While there was no sig-
nificant difference between group mean scores at post-test
for GSE, F(1) = 2.442, p = .120, scores on EXAM neared
significance, F(1) = 3.761, p = .054. For post-test scores
on ESE, exercisers were significantly higher (M = 34.466,
SD = 4.152) than non-exercisers (M = 30.000, SD = 5.770),
F(1) = 29.397, p = .000, d = 0.99. Finally, at post-test, exer-
cisers reported significantly higher scores (M = 56.344,
SD = 6.040) than non-exercisers (M = 53.676, SD = 6.067)
on GAM, F(1) = 5.883, p = .016, d = 0.44.
One-way repeated measures ANOVA analyses were run
to determine the main effect of walking on ESE, EXAM,
GSE, and GAM, for participants in the 8-week indoor/
outdoor walking intervention (compared to the two con-
trol groups: long term exercisers and non-exercisers). The
main effect of walking was significant for three of the four
variables (EXE, GSE, GAM; see Fig.1).
The one-way repeated measures ANOVA for EXE
uncovered significant results. The within subjects effects,
by group, were F(3, 181) = 5.10, p = .00, η2 = 0.07. The
between subjects effects, by group, were also significant,
F(3, 181) = 11.24, p < .001. The simple main effects of
walking for exercise self-efficacy were not significant for
the control groups, but were significant for the indoor
walking group, F(1) = 12.09, p = .00, and the outdoor
walking group, F(1) = 8.58, p = .01.
For GSE, the one-way repeated measures ANOVA
uncovered significant results within subjects, by group, F(3,
181) = 2.42, p = .07, η2 = 0.03. The simple main effects of
walking for general self-efficacy were significant for both
the indoor walkers, F(1) = 13.17, p < .001, and the outdoor
walkers, F(1) = 18.15, p < .001.
The one-way repeated measures ANOVA for GAM
uncovered significant results for both within subjects, by
group, F(3, 181) = 4.67, p = .00, η2 = 0.07, and between
subjects, by group, F(3, 181) = 3.70, p = .01, η2 = 0.06. The
simple main effects of walking on GAM were significant for
both the indoor walkers, F(1) = 7.04, p = .01, and the outdoor
walkers, F(1) = 16.70, p < .001.
Change withingroups
T-tests were run on pre- and post-test scores, by group, to
further explicate the changes that were predicted for exer-
cisers (the second hypothesis). Indoor and outdoor walkers
experienced significant improvements in ESE, GSE, and
GAM. Group change scores provide partial support for the
third hypothesis (outdoor walkers will experience the great-
est gains on all variables). Outdoor walkers experienced the
greatest gains (with moderate to large effect sizes) on GSE
and GAM. Pre and post-test means, standard deviations,
t-values, and effect sizes are listed below (see Table1).
Discussion
The aim of this study was to investigate the role of exercise
in the development of self-efficacy and approach motivation.
Specifically, the aim was to investigate whether exercise
(indoor and outdoor) has a causal relationship with self-effi-
cacy and approach motivation. The use of random assign-
ment at the study’s onset allowed for this investigation, and
the results support a causal nature between the variables.
The results of this study suggest that a rather simple walk-
ing intervention, when practiced regularly, could contribute
significantly to both self-efficacy and approach motivation,
and that walking outdoors enhances the outcomes.
The first hypothesis predicting exercisers would report
higher scores on measures of EXAM and GAM (compared
to non-exercisers) was not supported. Previous research has
suggested a strong correlation between exercise participa-
tion and approach motivation tendencies (Lochbaum etal.
2013), however the pre-test comparisons did not show evi-
dence of any difference between groups on either measure of
approach motivation. The post-test scores on EXAM found

Motivation and Emotion
1 3
no significant change for the exercising control group or the
new exercisers. It is possible that three questions from the
EXAM scale (Conroy etal. 2003) were not enough to meas-
ure any difference.
An 8-week intervention may have been too short to
witness change in new exercisers’ desire to approach new
challenges in physical activity (EXAM). The malleabil-
ity of approach motive tendencies have been studied by
other researchers (Elliot and Church 1997; Fryer and Elliot
2007; Senko and Harackiewicz 2005), however little has
been studied regarding the dose–response or timing of the
relationship.
Fig. 1 Simple main effects of
walking, by group, for exercise
self-efficacy (ESE), general
self-efficacy (GSE), and global
approach motivation (GAM).
Graphs show group means at
pre-test and post-test for each
variable
29.00
30.00
31.00
32.00
33.00
34.00
35.00
PreTest ESEPostTest ESE
Simple Main Effects for
Exercise Self-Eficacy
ExControl
NoExControl
Indoor Ex
Outdoor Ex
29.00
30.00
31.00
32.00
33.00
34.00
35.00
PreTest GSEPostTest GSE
Simple Main Effects for
General Self-Eficacy
ExControl
NoExControl
Indoor Ex
Outdoor Ex
51.0
0
52.0
0
53.0
0
54.0
0
55.0
0
56.0
0
57.0
0
58.0
0
PreTest GAMPostTest GAM
Simple Main Effects for
Global Approach Motivation
ExControl
NoExControl
Indoor Ex
Outdoor Ex

Motivation and Emotion
1 3
Post-test comparisons of exercisers and non-exercisers
found partial support for the second hypothesis (exercis-
ing would result in increases in self-reported scores on all
measures). While there was not a significant improvement
for EXAM, participants in both treatment groups experi-
enced significant improvement in ESE, GAM, and GSE.
The non-exercising control group experienced significant
improvements in GSE also, but the treatment groups expe-
rienced larger improvements. To some degree, it might be
typical to see improvements in general self-efficacy at the
end of the first quarter of college, with or without exercise
contributions.
Despite the lack of significant improvement in exercise-
specific approach motivation, it is important to note that the
8-week walking intervention did contribute to significant
improvements in global approach motivation, which was the
overarching question this study sought to answer. Addition-
ally, experienced the greatest gains of all the groups in GSE
and GAM. The data partially supported the final hypothesis
that walking outdoors would enhance the outcomes on all
variables.
Previous research has suggested that the time of year
or time of day influence tendencies toward approach or
avoidance motivations (Peterson etal. 2008; Peterson and
Harmon-Jones 2009). Specifically, Peterson and Harmon-
Jones (2009) found that right, more than left, cortical activ-
ity is greater in fall and winter months, and mornings more
than afternoons. Right cortical activity is associated with
avoidance motivational tendencies, while left cortical activ-
ity is associated with approach motivational tendencies.
Given that this current study was conducted in the fall and
winter months, the impact of the intervention is even more
profound: walking, indoors or outdoors, contributed signifi-
cantly to increases in approach motivation at a time of year
when avoidance tendencies are more likely to dominate.
Past research has focused on the correlational relation-
ship between exercise and approach motivation (Lochbaum
etal. 2013). This study is the first known to the authors to
suggest that a causal relationship exists. The impact that
brisk walking seemed to have for the participants provides
hope that many individuals currently living a more seden-
tary lifestyle might find it easy to experience the benefits
of walking, especially given that brisk walking, either out-
doors or indoors, requires no expensive equipment or gym
membership. Additionally, new exercisers that begin a self-
paced brisk walking program are more likely to remain
Table 1 Pre- and post-test
means, standard deviations,
T-values, and effect sizes by
variable and group
*p = .05.; **p = .01
Variable/group Pre-test Post-test t d
M SD M SD
Exercise-specific self-efficacy
Exercising control (60) 34.43 3.99 34.83 3.61 0.94 0.10
Non ex. control (38) 30.16 4.47 30.00 5.77 0.21 0.03
Indoor walkers (39) 30.87 5.38 34.46 4.82 3.48** 0.70
Outdoor walkers (48) 31.10 5.29 34.02 4.25 2.93** 0.61
Total (185) 31.94 5.04 33.55 4.86 3.94** 0.33
Exercise-specific approach motivation
Exercising control (60) 18.55 1.93 18.53 1.86 0.06 0.01
Non ex. control (38) 17.79 2.07 17.95 2.24 0.43 0.07
Indoor walkers (39) 18.49 1.73 18.69 2.07 0.56 0.11
Outdoor walkers (48) 18.21 2.07 18.73 1.80 1.62 0.27
Total (185) 18.29 1.97 18.50 1.98 1.27 0.10
General self-efficacy
Exercising control (60) 32.20 4.12 32.80 5.14 0.96 0.13
Non ex. control (38) 30.29 6.42 32.32 6.23 2.47* 0.32
Indoor walkers (39) 32.26 3.78 34.36 3.31 3.63** 0.56
Outdoor walkers (48) 31.17 4.49 34.13 3.34 4.26** 0.75
Total (185) 31.55 4.74 33.37 4.70 5.28** 0.40
Global approach motivation
Exercising control (60) 55.44 6.14 56.54 6.50 1.68 0.17
Non ex. control (38) 54.32 6.20 53.68 6.07 0.93 0.10
Indoor walkers (39) 55.47 5.60 57.70 5.43 2.65* 0.40
Outdoor walkers (48) 51.68 5.90 55.01 5.75 4.09** 0.57
Total (185) 54.24 6.14 55.80 6.13 4.03** 0.25

Motivation and Emotion
1 3
committed than a new exerciser that begins a more physi-
cally demanding exercise program, while still reaping the
fitness and health benefits it affords (Ekkekakis etal. 2008;
National Institutes of Health Consensus Development Panel
on Physical Activity and Cardiovascular Health 1996; Perri
etal. 2002; Sallis etal. 1986).
Limitations andfuture directions
The rather short duration of the study, lack of control over
the variations in outdoor walking environs, reported safety
issues by outdoor walkers, and a truncated version of the
EXAM measure may have impacted the strength of the out-
comes, and should be considered in future studies. Walking
was used as one type of exercise for this study, but it is not
known, from this study, if walking accurately represents the
outcomes that may be found from other forms of exercise,
such as yoga, weight lifting, or running. Additionally, it is
not known if the results found in this study are long lasting.
Future studies might consider long term follow up testing to
investigate the life of the impact walking has on approach
motivation.
Conclusions
The results of this study suggest that walking as a form as
exercise contributes to GSE and GAM tendencies in as lit-
tle as 8weeks, in an exercise form that is neither intensive
nor expensive (walking indoors or outdoors requires no
special gear or gym membership). This is significant, given
that individuals may find this walking routine a manage-
able behavior that contributes to their well-being by building
self-efficacy and approach motivation. Given today’s cultural
concern with obesity and the number of adults who chose
to live sedentary lifestyles, this study provides good news:
a simple brisk walking regimen can have a positive impact
on elements of human flourishing that permeate other areas
of life. Specifically, previous research has found that indi-
viduals with approach motivation tendencies are likely to
embrace approach goals (e.g., approach challenges in order
to grow and learn), which predicts well-being (Elliot etal.
2006; Nikitin and Freund 2008). It is hoped that this study,
and others like it, will shine a light on the great benefits
found from a simple, inexpensive, self-paced walking regi-
men: one that reaps psychological benefits as well as health
benefits.
Acknowledgements This study was based on a doctoral dissertation
completed by Christine Weinkauff Duranso under the direction of
Mihaly Csikszentmihalyi. The author thanks Mihaly Csikszentmihalyi,
Jason Siegel, and Jeanne Nakamura for guidance in the development
of this study.
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