Psychosocial Mediators of Physical Activity Behavior
Among Adults and Children
Beth A. Lewis, PhD, Bess H. Marcus, PhD, Russell R. Pate, PhD, Andrea L. Dunn, PhD
Background: Researchers examining theory-based, physical activity (PA) interventions postulate that
interventions are effective by changing theoretical constructs hypothesized to mediate the
relationship between the intervention and PA behavior. Research indicates that PA
interventions are effective for increasing PA behavior. However, whether effective interventions are due to predicted changes in theoretical constructs remains poorly understood.
Methods:
Studies that examined theoretical constructs (i.e., mediators) in PA interventions of adults
or children, which used experimental designs and met other criteria for evaluating
mediation, were collected via literature searches, personal searches of files, and personal
communications. Only studies examining the direct effect of the intervention on the
hypothesized mediator were considered relevant for this study.
Results:
Based on our criteria, the adult literature search yielded ten studies and the child literature
search yielded two studies. The most common mediators examined included behavioral
processes of change, cognitive processes of change, self-efficacy, decisional balance, social
support, and enjoyment. Research indicates that behavioral processes are likely mediators.
There was some support for the importance of self-efficacy as a mediator.
Conclusions: Few studies have used statistically recommended methods to examine mediators in PA
intervention studies. Therefore, definitive conclusions about the importance of the
mediators reviewed are not possible at this time. Additional PA mediator–intervention
studies using recommended statistical methods are necessary to truly test if theory-based PA
interventions are effective due to predicted changes in theoretical constructs.
Medical Subject Headings (MeSH): adult, child, exercise, health behavior, intervention
studies, physical fitness, psychological theory (Am J Prev Med 2002;23(2S):26 –35) © 2002
American Journal of Preventive Medicine
Introduction
R
esearch indicates that theory-based, physical
activity interventions successfully influence
physical activity behavior.1– 4 However, why
these interventions are effective in promoting physical
activity behavior remains poorly understood. Researchers who conduct physical activity interventions based on
theoretical frameworks such as social cognitive theory
(SCT)5 and the transtheoretical model (TTM)6 postulate that interventions influence physical activity behavior by changing theoretical constructs that are primarily psychosocial in nature and that are believed to be
important for behavior change, such as behavioral
From the Centers for Behavioral and Preventive Medicine, Brown
Medical School (Lewis, Marcus) and The Miriam Hospital (Lewis,
Marcus), Providence, Rhode Island; Department of Exercise Science,
University of South Carolina (Pate), Columbia, South Carolina; and
The Cooper Institute (Dunn), Dallas, Texas
Address correspondence and reprint requests to: Beth A. Lewis,
PhD, Centers for Behavioral and Preventive Medicine, Brown Medical School and The Miriam Hospital, 1 Hoppin Street, Coro Building,
Suite 500, Providence, RI 02903. E-mail: [email protected].
26
processes, cognitive processes, self-efficacy, and social
support (e.g., Dunn et al.2 and Pinto et al.7). Even
though the focus on theoretical constructs mediating
physical activity behavior change has increased in recent years, only a few studies have examined whether
interventions change postulated mediators and
whether mediators influence physical activity behavior
(e.g., Pinto et al.7 and Sallis et al.8).
Mediators can be defined as “intervening causal
variables that are necessary to complete a cause– effect
pathway between an intervention and physical activity.”9 Baranowski et al.10 recommended that researchers
examine the role of mediators in successful interventions by specifying which mediators are targeted in an
intervention, determining if the intervention successfully changed the targeted mediators, and evaluating if
changes in mediators predict change in physical activity
behavior. Because researchers hypothesize that theorybased interventions are effective due to changes in
particular mediators (e.g., self-efficacy), it is important
to measure both whether the intervention influences
changes in the mediators and whether the mediators
Am J Prev Med 2002;23(2S)
0749-3797/02/$–see front matter
© 2002 American Journal of Preventive Medicine • Published by Elsevier Science Inc.
PII S0749-3797(02)00471-3
Figure 1. Overview of mediation analysis examining self-efficacy
influence physical activity behavior change. By examining several potential mediators, researchers may learn
which mediators are most effective for increasing physical activity behavior, which in turn may lead to more
effective interventions. As an example, a physical activity intervention may be hypothesized to increase selfefficacy and social support; however, if the intervention
effectively increases physical activity by increasing selfefficacy but not social support, we learn that selfefficacy is the important component in this
intervention.
Baranowski et al.10 recommended that mediator
analyses be conducted using the framework suggested
by Baron and Kenny.11 According to Baron and Kenny,11 a variable mediates the relationship between an
intervention and an outcome if a positive relationship
between the intervention and an outcome variable is
attenuated after statistically controlling for the mediator. Physical activity intervention studies have examined
the effect of the intervention on mediators2,7,8,12–22 and
the effect of mediators on outcome.2,7,8,12–16,18,19,21,22
However, we found only two studies7,22 that specifically
tested mediators as suggested by Baron and Kenny11
and more recently, Kramer et al.23,24 As an example,
self-efficacy is one mediator that has been examined in
physical activity interventions (e.g., Calfas et al.12 and
McAuley et al.13). Self-efficacy can be considered a
mediator if it meets the following criteria11:
1. The intervention causes an increase in self-efficacy.
2. Self-efficacy is associated with increases in physical
activity behavior.
3. The relationship between the intervention and physical activity behavior is attenuated when controlling
for changes in self-efficacy (see Figure 1).
Perfect mediation occurs when the intervention has no
effect on physical activity behavior when controlling for
changes in self-efficacy (i.e., the mediator). Although
theoretically possible, it would be unusual for perfect
mediation to occur in clinical trials examining mediators. Therefore, self-efficacy would be conceptualized as
a mediator if the relationship between the intervention
and physical activity behavior is attenuated when controlling for self-efficacy (in addition to meeting the
criteria described above). The higher the attenuation
of the effect, the greater the potency of the mediator.
The purpose of this article is to discuss findings and
future directions regarding the physical activity–intervention literature that examines mediators among
adults and children.
Method
Adult Studies
Studies for the present paper were collected via a literature
search (e.g., PsycINFO, Medline), personal searches of files,
and personal communications. The literature search yielded
3378 articles, using a combination of keywords, such as
mediator, theory, behavior change, physical activity, sport,
exercise, intervention, program, treatment, and several words
associated with SCT, the TTM, health belief model, protection motivation theory, theory of planned behavior, and
self-determination theory. Several studies identified in the
literature examined the relationship between potential mediators and physical activity behavior without examining the
effect of an intervention on the mediator. These can be
considered studies of correlates of physical activity behavior;
they are beyond the scope of this article and are discussed
elsewhere.25 Other exclusionary criteria for the adult search
included studies not written in English, studies using nonexperimental designs, nontheoretical interventions, and intervention studies targeting multiple risk factors. Studies examining the effect of the intervention on the mediator but not
the effect of the mediator on outcome were included. Ten
overall studies described in 14 articles constitute the focus of
the article for adults.
Child Studies
A similar process was used to search the literature for relevant
studies with participants who were children or youth (age
range, 0 to 18 years). The keyswords were similar to those
used in the adult literature search described above. The
search yielded 209 articles, but most were excluded from this
review using similar criteria as were applied for studies of
adults. However, unlike the adult literature search, multiple
risk–factor studies were included because there were very few
studies in children. Two studies described in four publications constitute the focus of this article for children.
Am J Prev Med 2002;23(2S)
27
Table 1. PA intervention studies examining mediators of PA behavior change
Study
Sample
Design
Intervention Theory
Mediators
Group vs
SCT
SE, partner
Miller et al., 200222 554 Mothers Exp
(grp/print/control)
print
support
target
mothers
Marcus, 199816;
150 Adults Exp (Tx vs AHA)
Tailored
TTM, SCT, B, C, SE, DB
Marcus et al.,
print
DM
199826
intervention
Pinto et al., 20017 355 Elderly Exp, physician office Physician
TTM, SCT B, C, SE, DB
(Tx vs control)
counseling
Nichols et al.,
200020
64 Adults at Exp (grp vs control)
a work
site
Calfas et al.,
200027; Sallis et
al., 19998
Castro et al.,
199914
338
Exp (Tx vs control)
University
students
128 Ethnic Exp (Tx vs AHA)
minority
women
Hallam and Petosa, 86 Adult
Quasi-exp work site
199817
employees
(tx vs control)
Dunn et al.,
19972,28
235 Adults
Exp (life style vs
structured)
Calfas et al., 1997
and 199612,29
McAuley et al.,
199413
255 Adults
Exp, physician office
(tx vs control)
Exp (Tx vs control)
114 Middle
aged
adults
5106
Children
in 96
schools
Edmundson et al.,
Exp (Tx vs control
199615; Luepker
schools)
et al., 199618;
Nader et al.,
199919
Parcel et al., 198921 72–175
Quasi-exp (Tx vs
Children
control schools)
per
school (4)
Assessment time
point
Baseline, 8-week
post-test, 5-month
follow-up
Baseline, 1 month, 3
months, 6-month
post-test
Baseline, 6 week
follow-up, 8-month
follow-up
Course ⫹ PA SCT, TTM B, C, SE, barriers, Baseline, 3-month
trainer
benefits,
post-test, 9-month
support,
follow-up
enjoyment
16-week PA TTM, SCT B, C, SE, support, Baseline, 16-week
course
benefit/barrier,
post-test
enjoyment
Phone/mail SCT
SE, support,
Baseline, 8-week
target
barriers,
post-test, 5-month
walking
enjoyment
follow-up
Four face-to- SCT
SE, selfBaseline, 4-week
face
regulation,
post-test
sessions
outcome
expectations
Lifestyle or TTM, SCT, B, C, SE, DB
Baseline, 6-month
structured
DM
post-test
PA
Physician
TTM, SCT B, C, SE, support Baseline, 4 to 6 week
counseling
follow-up
Targeted PA SCT
SE
Baseline, 1 month, 2
selfmonths, and 4
efficacy
months
School, CVD SCT
SE, social support Baseline, 1-year, 2risk factors
year, and 3-year
follow-ups
School-based SCT
PA and
diet
SE, knowledge,
skills
Baseline, follow-up
AHA, American Heart Association materials; B, behavioral; C, cognitive; CVD, cardiovascular disease; DB, decisional balance; DM, decision
making; exp, experimental; grp, experimental intervention group; PA, physical activity; SCT, social cognitive theory; SE, self-efficacy; TTM,
transtheoretical model; Tx, treatment.
Results
Overview of Mediator Studies
Theory-based interventions examining potential mediators in physical activity–intervention studies are highlighted in Table 1. The sample, design, setting, intervention, theory, potential mediators, and assessment
time points for each study are presented. Studies were
conducted in several settings (e.g., community, primary
care, home, or university) and delivered by various
channels (e.g., face-to-face, telephone, or tailored print
materials).
28
The most common theoretical frameworks used in
these studies included SCT and the TTM.7,8 SCT postulates that there are multiple multidirectional influences on behavior, including both cognitive and social
factors.5 For example, one aspect of SCT relevant to
physical activity is self-efficacy, which refers to one’s
confidence (i.e., cognitive component) to engage in
physical activity despite encountering social (e.g., family obligations) and environmental barriers (e.g., bad
weather). TTM hypothesizes that individuals adopt
physical activity by moving through the following stages: precontemplation (not intending to become physi-
American Journal of Preventive Medicine, Volume 23, Number 2S
Table 2. Effect of intervention on behavioral processes and effects on outcome
Study
Effect of intervention on behavioral processes
Effect of behavioral processes on outcome
Marcus, 199816;
Marcus et al., 199826
Pinto et al., 20017
Increased in both groups from base to post
(tailored and AHA)
Intervention increased more than control at 6
weeks but not 8 months
Intervention increased more than controls
(maintained at 1 and 2 years for women)
Intervention increased more than control for
behavioral and cognitive processes
(combined)
No differences across groups (lifestyle vs
structured)
Increases associated with three of three outcome
variables for both groups
Mediator at 6 weeks but not 8 months
Calfas et al., 200027;
Sallis et al., 19998
Nichols et al., 200020
Dunn et al., 19972,28
Calfas et al., 199712;
199629
Intervention increased more than controls
Related to none of the outcome variables
Not assessed
Increases from 0 to 24 months predicted
meeting CDC/ACSM recommendations 3.5
years later
Increases predicted two of four outcomes
Note: The behavioral process subscales of the Processes of Change Questionnaire consist of the following: counterconditioning (substituting
alternative, helping relationships (enlisting social support), reinforcement management (rewarding yourself), self-liberation (committing
yourself), and stimulus control (reminding yourself) (Marcus et al.30).
ACSM, American College of Sports Medicine; AHA, American Heart Association materials; CDC, Centers for Disease Control and Prevention.
cally active); contemplation (intend to become physically active in the next 6 months); preparation (intend
to become more physically active and physically active
some but not regularly); action (regularly physically
active but for ⬍6 months); and maintenance (regularly
physically active for ⱖ6 months).30
Related to these theories, the most common theoretical constructs examined as mediators in the literature
included behavioral processes of change (e.g., rewarding yourself); cognitive processes of change (e.g., increasing knowledge); self-efficacy (i.e., confidence in
becoming physically active); decisional balance (i.e.,
weighing the pros and cons related to physical activity);
social support; and enjoyment of physical activity.2,7,8,12–22 A summary of the findings for each of these
six theoretical constructs follows.
Summary of Mediator Studies in Adults
Behavioral processes of change. Table 2 summarizes
the studies examining behavioral processes as mediators of physical activity interventions. All studies examining behavioral processes2,7,8,12,16,20 administered the
full or a shortened version of the Processes of Change
Questionnaire,30 which measures the following behavioral processes: substituting alternatives, enlisting social
support, rewarding yourself, committing yourself, and
reminding yourself.31 Most of the studies indicated that
physical activity interventions designed to change behavioral processes significantly increased use of behavioral processes, and increased use of behavioral processes was significantly related to increases in physical
activity behavior.2,7,8,16,20 However, findings are not
entirely consistent across type of physical activity outcome variable12 or time points.7
Cognitive processes of change. Research examining
cognitive processes as mediators of physical activity is
described in Table 3. All studies examining cognitive
processes2,7,8,12,16,20 used the full or a shortened version
of the Processes of Change Questionnaire,30 which
measures the following cognitive processes: increasing
knowledge, warning of risks associated with physical
inactivity, caring about consequences to others, comprehending benefits, and increasing health opportunities by becoming more physically active. Results from
studies examining the effects of the intervention
on cognitive processes have varied across studies,2,7,8,12,16,20 in addition to varying within a study
regarding gender8,12 and time-point assessment.7 A
majority of the studies that investigated the link between cognitive processes and physical activity did not
find that cognitive processes significantly influenced
physical activity behavior.7,8,16
Despite the inconsistent findings, results from other
types of research indicate that cognitive processes are
likely to be important in shaping behavior or moving
individuals along the stage-of-change continuum as well
as in changing physical activity behavior itself.30,32
Perhaps cognitive processes change when an individual
decides to participate in a physical activity intervention
and prior to the actual start of the intervention. This is
consistent with the TTM, as it postulates that cognitive
processes change earlier and prior to behavioral
processes.
Self-efficacy. Studies examining self-efficacy as a mediator in intervention studies are summarized in Table 4.
Self-efficacy for physical activity refers to one’s confidence regarding participating in specific types of physical activity, or specific amounts of physical activity, or
both. Some studies indicate that interventions significantly increase self-efficacy, or that self-efficacy is significantly related to physical activity behavior, or
both,2,7,8,12,13,16,22 although support for self-efficacy has
Am J Prev Med 2002;23(2S)
29
Table 3. Effect of intervention on cognitive processes and effects on outcome
Effect of intervention on cognitive
processes
Study
16
Marcus, 1998 ;
Marcus et al., 199826
Pinto et al., 20017
Calfas et al., 200027; Sallis et
al., 19998
Nichols et al., 200020
Dunn et al., 19972,28
Calfas et al., 199712 and
199629
Decreased in both groups from base to post
(tailored and AHA)
Intervention marginally increased relative to
control at 6 weeks but not 8 months
Intervention more than controls for women,
not men (women maintained at 1 and 2
years
Intervention increased more than control
for behavioral and cognitive processes
(combined)
No differences across groups (lifestyle vs
structured)
Intervention increased more than controls
Effect of cognitive processes on outcome
Related to none of the outcome variables
Was not a mediator at either time point
Related to none of the outcome variables
Not assessed
Increases from 0 to 24 months predicted
meeting CDC/ACSM recommendation 3.5
years later
Increases predicted one of four outcomes
Note: The cognitive process subscales of the Processes of Change Questionnaire consist of the following: consciousness raising (increasing
knowledge), dramatic relief (warning of risks), environmental re-evaluation (caring about consequence to others), self-re-evaluation (comprehending benefits), and social liberation (increasing healthy opportunities) (Marcus et al.30).
ACSM, American College of Sports Medicine; AHA, American Heart Association materials; CDC, Centers for Disease Control and Prevention.
varied across time point,7 gender,8 and outcome variable.8,12 The two studies that examined the effect of the
intervention on self-efficacy but not the effect of selfefficacy on physical activity behavior found that the
intervention group did not report more of an increase
in self-efficacy than the control group.17,20 Of the two
studies that examined if self-efficacy was a mediator
based on Baron and Kenny’s11 criteria, one of the
studies22 found self-efficacy to be a physical activity
mediator among mothers, and another study conducted in a primary care setting found that self-efficacy
was not a mediator.7 Although studies that did not
examine the direct effect of the intervention on the
mediator are not the focus of this paper, it is important
to note that many studies have found significant correlations between self-efficacy and physical activity behavior (e.g., Dzewaltowski33, Garcia and King34, and
McAuley35).
Table 4. Effect of intervention on self-efficacy and effects on outcome
Study
Effect of intervention on self-efficacy
Effect of self-efficacy on outcome
Miller et al., 200222
Group-based intervention increased relative to
other groups
Increased in both groups from base to post
(tailored and AHA)
A mediator based on Baron and
Kenny10 criteria
Increases associated with two of three
outcome variables for IT and three of
three for ST
Not a mediator at either time point
based on Baron and Kenny10 criteria
Resisting relapse, SE related to two of
five outcomes for men and one of five
for women
Not assessed
Marcus, 199816;
Marcus et al., 199826
Pinto et al., 20017
Calfas et al., 200027;
Sallis et al., 19998
Nichols et al., 200020
Hallam and Petosa,
199817
Dunn et al., 19972,28
Castro et al., 199914
Intervention increased more than control at 6
weeks but not 8 months
Intervention increased more than controls for
women but not men
No differences between intervention and
control
Intervention did not increase more than
control
No differences across groups (lifestyle vs
structured)
Calfas et al., 199712 and
199629
Decreased from base to follow-up and from
post to follow-up for both groups
No differences between intervention and
control for either measure
McAuley et al., 199413
No direct effect of intervention on self-efficacy
Not assessed
Increases 0 to 24 months predicted
CDC/ACSM recommendations 3.5
years later
Self-efficacy inversely related to change
in walking from base to follow-up
Making Time SE: two of four outcomes;
Sticking to it SE: three of four
outcomes
Related to exercise frequency
ACSM, American College of Sports Medicine; AHA, American Heart Association materials; CDC, Centers for Disease Control and Prevention;
IT, Intervention; SE, self-efficacy; ST, Standard Treatment.
30
American Journal of Preventive Medicine, Volume 23, Number 2S
Table 5. Effect of intervention on decisional balance and effects on outcome
Effect of decisional balance on
mediator
Study
16
Marcus, 1998 ;
Marcus et al., 199826
Pinto et al., 20017
Calfas et al., 200027;
Sallis et al., 19998
Nichols et al., 200020
Dunn et al., 19972,28
Castro et al., 199914
No increase in either group from
base to post (tailored and AHA)
Intervention increased more than
control at 6 weeks but not 8
months
Intervention increased barriers for
men, no effect for women
No differences between intervention
and control
No differences across groups
(lifestyle vs structured)
Barriers decreased in both groups
from base to post
Effect of decisional balance on outcome
Related to none of the outcome
variables
Was a mediator at 6 weeks but not 8
months
Women: zero of five outcomes; men:
benefits and barriers positively related
to one of five outcomes
Not assessed
Increases in pros, not cons, from 0 to 24
months predicted meeting
CDC/ACSM recommendations 3.5
years later
Not related to walking
ACSM, American College of Sports Medicine; AHA, American Heart Association materials; CDC, Centers for Disease Control and Prevention.
Decisional balance/benefits and barriers. Table 5 describes studies examining decisional balance and benefits and barriers as mediators in the physical activity
interventions being targeted. One of the six studies
indicated that the decisional balance index (i.e., pros
minus cons) significantly increased more in the intervention group than in the control group at 6 weeks but
not 8 months,7 while another study found that barriers
significantly decreased in both intervention and control groups.14 The remaining studies indicated no
effect of the intervention on decisional balance,2,16,20
with the exception of one study showing a significant
increase in barriers for men.8 Two of the five studies
reported a significant relationship between decisional
balance and physical activity behavior.2,7,28 Overall, the
support for decisional balance as a mediator in physical
activity–intervention studies appears mixed. The construct of decision making has been examined differently across studies (e.g., decisional balance index, and
benefits and barriers), which may contribute to the
mixed findings (e.g., Pinto et al.7 and Sallis et al.8).
Similar to cognitive processes, perhaps individuals’
decisional-balance index changes prior to beginning an
intervention, making it difficult to detect changes in
decisional balance following initiation of the
intervention.
Social support. Table 6 summarizes studies examining
social support as a mediator in the physical activity
intervention being targeted. Contrary to hypotheses,
one of the five studies indicated that social support
among the intervention group significantly decreased
from baseline to follow-up relative to the control
group20; another study found no significant differences
between intervention and control groups12; one study
found that it significantly increased from baseline to
post-test and follow-up14; one study found that the
intervention significantly increased social support more
than the control for women but not men8; and a final
study found that social support significantly increased
in the intervention group but not the control group.17
The only study that examined social support based on
Table 6. Effect of intervention on social support and effects on outcome
Study
Effect of intervention on social support
Effect of social support on outcome
Miller et al., 200222
Group intervention increased relative to other groups
Calfas et al., 200027;
Sallis et al., 19998
Nichols et al., 200020
Hallam and Petosa,
199817
Calfas et al., 199712 and
199629
Intervention increased more than controls for women
but not men
Intervention decreased more than control
Intervention increased more than control
A mediator based on Baron and Kenny10
criteria (partner support)
Friends related to one of five outcomes
for women and zero of five for men
Not assessed
Not assessed
Castro et al., 199914
Intervention increased from base to post and base to
follow-up; intervention decreased from post to followup
No differences between intervention and controls for
either measure
Increases predicted one of four
outcomes for family and three of four
for friend
Not related to walking
Am J Prev Med 2002;23(2S)
31
Table 7. Effect of intervention on enjoyment and effects on outcome
Study
Effect of intervention on enjoyment
Effect of enjoyment on outcome
Calfas et al., 200027;
Sallis et al., 19998
Nichols et al.,
200020
Castro et al., 199914
No significant differences between
intervention and control
No differences between intervention
and control
Decreased in both groups from base to
post and base to follow-up
Men: two of five outcomes (including one positive and one
negative); women: one of five outcomes
Not assessed
Baron and Kenny’s11 recommendation found that social support (i.e., spousal support) was a mediator
among mothers with young children.22 Because spousal
support among this population is particularly important, this intervention emphasized spousal support and
perhaps this emphasis increased the likelihood of finding a mediation effect. Overall, the relationship between social support and physical activity behavior was
inconsistent across studies8,12,14; however, it is important to note that other correlational studies that did not
directly examine the influence of the intervention on
the mediator have found social support to be an
important predictor of physical activity behavior.36,37
Enjoyment of physical activity. Studies investigating
enjoyment of physical activity as a mediator are summarized in Table 7. Two of the three studies found that
the intervention did not significantly influence enjoyment,8,20 and the remaining study found that enjoyment decreased in both the intervention and control
groups from baseline to post-test.14 Thus, past research
provides no support that enjoyment is a mediator of
physical activity. However, our conclusion should be
interpreted with caution, given that when compared to
other mediators, fewer studies have examined enjoyment as a potential mediator.
Other mediators. Hallam and Petosa17 examined the
effect of a physical activity intervention on outcome
expectancy (i.e., individual’s estimate that participating
in physical activity will lead to a particular outcome and
the value of the expected outcome) and self-regulation
(i.e., skills used to carry out physical activity intentions
and ability to overcome situational and personal barriers). Results indicated that participants in the intervention group increased their overall scores on the selfregulation and outcome-expectancy value relative to
control. The effect of outcome-expectancy value and
self-regulation on physical activity was not examined.
Summary of Mediator Studies in Children and
Youth
Our review of the scientific literature on interventions
to promote physical activity in children or youth revealed only two investigations in which the influence of
the intervention on both physical activity and potential
32
Not related to outcome
mediators was examined. Neither of these studies directly addressed the effects of mediators as has been
recommended by Baron and Kenny11 or Kraemer et
al.23,24 For one of the pertinent studies, the effects of
the intervention on physical activity and mediators were
presented in separate papers.
Parcel et al.21 observed the effects of an elementary
school– based intervention that included physical education and classroom health education components
using a quasi-experimental design. They reported evidence that the intervention produced significant improvements in physical activity self-efficacy and behavioral capability (knowledge and skills). However, selfreported physical activity increased between baseline
and follow-up in both control and intervention groups,
and the difference between the groups was not
significant.
Perhaps the most extensive examination of potential
mediators in physical activity interventions in children
was performed in the CATCH (Child and Adolescent
Trial for Cardiovascular Health) investigation, a multicenter randomized controlled trial based in 96 elementary schools. CATCH examined the effects of a schoolbased intervention to increase physical activity and
improve diet in students who were initially in the third
grade. As reported by Leupker et al.,18 both physical
activity observed in physical education classes and selfreported, vigorous physical activity, when measured in
the students as fifth graders, were significantly greater
in the intervention group than the control group. In a
separate paper based on the same sample of children,
the CATCH investigators15 reported that physical activity self-efficacy and perceived social support for physical
activity were significantly greater in the intervention
children than controls in observations made when the
students were in the third and fourth grades. However,
at the conclusion of the active intervention phase of the
study, when the children were fifth graders, no differences between intervention and control groups were
observed. When follow-up observations of the CATCH
cohort were made during the subjects’ eighth-grade
year, self-reported, vigorous physical activity remained
greater in in the intervention group than in the control
group. However, positive social support for physical
activity was not different between the groups.
American Journal of Preventive Medicine, Volume 23, Number 2S
Discussion
Behavioral processes of change have received the most
consistent support for mediating the relationship between theory-based, physical activity interventions and
physical activity behavior, although self-efficacy has also
received some support as a mediator. There are several
potential reasons why certain mediators were supported and others were not, such as statistical, methodologic, and measurement differences across studies.
For example, statistical procedures varied across studies, interventions differed regarding their effectiveness,
mediator measures were delivered at various time
points, and different measures were used to examine
mediators.2,7,8,12–22
Since 1998, when Baranowki et al.10 recommended
that studies examine mediators as instructed by Baron
and Kenny,11 only two research studies7,22 that we are
aware of have conducted a mediator analysis according
to this or similar recommendations.11,23,24 Therefore,
definitive conclusions about the importance of mediators in theoretically based, physical activity–intervention studies are not possible at this time. One problem
with conducting mediator studies as recommended by
Baron and Kenny11 and Kraemer et al.23,24 is that it is
not always possible to fully test mediation because some
studies lack a true control group, or have a crosssectional (i.e., examining mediator and outcome at the
same time point) rather than a prospective design (i.e.,
how change in mediator effects outcome at a later time
point), or both. It is important to note that it is not
always possible to have a true control group due to
ethical reasons. In addition, it may be premature for
studies examining new mediators to conduct a full
analysis of mediators before the effect of the intervention on the potential mediator is established.
Another problem with the existing physical activity
literature on mediators is that some studies did not find
differences between the intervention and control
groups. For example, one study found that the intervention was effective for women but not for men8;
another study found that both the intervention and
control groups increased walking14; and still another
study found that both groups increased physical activity.2 In these studies, the effect of the intervention on
the mediator and the effect of the mediator on physical
activity behavior can be assessed. However, when no
physical activity differences are found between the
intervention and control groups, one of the criteria for
mediation is not met and consequently, a full mediator
analysis as recommended by previous studies11,23,24 will
indicate that the theoretical construct is not a mediator.
Another limitation of the existing physical activity–
intervention studies examining mediators is the inconsistency of measures administered across studies. This
inconsistency creates difficulty in comparing findings
across studies. Another measurement problem is that
some studies have used shortened versions, adapted
versions, or both shortened and adapted versions of
previously validated measures of mediators.8,14,20 It is
important to note that a few studies found effects of the
mediator in the opposite direction as hypothesized.8,14,16,20 For example, one study found that the
intervention was associated with subsequent decreases
in self-efficacy for physical activity.14 A possible explanation is that participants became more realistic in
their expectations and therefore, became more accurate at estimating their self-efficacy after attempts to
maintain their physical activity. Another potential measurement problem is that changes in mediators (e.g.,
decisional balance and cognitive processes) may occur
prior to the start of the intervention. For example,
changes in one’s beliefs about the pros and cons
associated with becoming physically active (i.e., decisional balance) may lead an individual to enroll in a
physical activity study. This makes it difficult to detect
mediator changes following the intervention due to
ceiling effects. Future studies should take steps to better
understand findings such as these (e.g., assessments at
multiple time points and collecting qualitative data).
Research Recommendations
Measurement issues. In order to adequately test if a
mediator is important in physical activity–intervention
studies, psychometrically sound measurement tools
should be used. A formal review of the measures
available for examining mediators is beyond the scope
of this paper; however, the following summarizes recommendations regarding measurement issues.
1. Studies should avoid using part of or adapting scales
without validating the new version of the scale.
There will be cases in which scales will not be
appropriate for particular populations. In these
cases, adapted measures should be validated prior to
use in the study in order to increase confidence in
the results of the mediator analysis.
2. Fewer physical activity–intervention studies have examined mediators in children (e.g., Parcel et al.21)
than in adults (e.g., Pinto et al.7 and Sallis et al.8)
and, therefore, fewer mediator measures are available for children.15 Future studies should develop
and test age-appropriate measures designed to examine mediators in children and youth.
3. All six of the adult studies examining behavioral and
cognitive processes used the processes of change
instrument.30 Future studies should continue to use
this scale; however, because of the inconsistent support for cognitive processes at different time
points,7,28 it will be especially important for researchers examining this mediator to examine it at
several time points.
4. Studies have examined the pros, cons, and barriers
related to physical activity using the decisional balAm J Prev Med 2002;23(2S)
33
ance instrument,38 the Barriers to Physical Activity
Scale,39 and the Benefits of Physical Activity Scale.39
In order to make comparisons across studies, additional studies are needed to determine which of
these scales, or others, are most appropriate, or if
some combination of these scales should be used.
5. A variety of scales have been used to examine
self-efficacy (e.g., Garcia and King34, Marcus et al.40,
and Sallis et al.41) and social support17,42 among
adults. All three of the studies examining enjoyment
used the Physical Activity Enjoyment Scale.43 It is
unclear whether inconsistent findings for these mediators are due to measurement problems or actual
differences in the importance of a particular mediator. Therefore, it is premature to discard existing
measures and future research regarding the appropriateness of the scales are needed.
6. To move the field forward, future studies should
focus on determining if inconsistent findings are
due to measurement error, lack of importance of a
particular mediator, or interventions being unsuccessful at changing mediators. Even though consistency across studies is important, it is also noteworthy that particular scales may be more relevant to
particular populations and this should be taken into
consideration. For example, different scales may be
more developmentally appropriate for different age
groups.
Methodologic issues. Based on the limitations of the
studies highlighted in this paper, several methodologic
issues should be addressed in future studies.
1. Studies including control groups and prospective
designs are needed to adequately examine mediators as recommended by Baron and Kenny11 and
more recently, Kraemer et al.23,24 to truly test if
theory-based, physical activity interventions are effective due to predicted changes in theoretical constructs. Furthermore, the influence of mediators
across different groups of individuals may vary and
should be examined in future studies. For example,
there is some evidence that the importance of
mediators may differ between genders,8 (i.e., gender
may be a moderator of intervention-mediator intervention relationships) and this should be explored
further. Also, additional research is needed among
ethnically diverse populations and across different
age groups, including children and older adults.
2. The first step for researchers examining new mediators or mediators with little or mixed support
should be to examine if the intervention is more
likely to produce changes in the theoretical construct than a control group. Because there are fewer
studies examining mediators among children than
among adults, this recommendation is particularly
relevant for the former population. Furthermore, a
full mediator analysis may be premature for inter34
ventions that have not been shown to be effective,
given that one of the criteria for mediation is not
met when an intervention is ineffective. For interventions that are not effective, the first step of a
mediation analysis (i.e., the effect of the intervention on the theoretical construct) could be conducted to better understand why the intervention
was ineffective.
3. Because there is some preliminary evidence that
certain mediators may be more important at particular time points (e.g., cognitive processes),7,28 future studies should examine mediators at multiple
time points, including both short-term (i.e., weeks)
and long-term time points (i.e., years). Optimally,
studies would examine the effect of the intervention
(i.e., Time Point 1) on changes in the mediators at a
later time point (i.e., Time Point 2). Next, studies
would examine the effect of changes in the mediators (i.e., Time Point 2) on physical activity behavior
at a later time point (i.e., Time Point 3). This design
is necessary to infer causality, such that changes in
mediators caused changes in physical activity behavior rather than changes in physical activity causing
changes in the mediators.
4. Finally, studies examining new theories (e.g., social
ecologic) and additional theoretical constructs are
needed to move the field forward to better understand how interventions influence physical activity
behavior. For example, there is some preliminary
evidence that self-regulation and outcome-expectancy value may be influenced by a physical activity
intervention.17 Because previous studies indicate
that mediators account for a small percentage of the
variance, it will be especially important to examine
new theories to improve our understanding of physical activity– behavior change. For example, theoretical constructs based on the theory of planned
behavior and the theory of reasoned action have
been shown to be predictive of physical activity
behavior in correlational studies that did not examine the direct effect of the intervention on physical
activity behavior.44,45 It is likely that a plethora of
theoretical constructs, including those extending
beyond psychosocial domains (e.g., program-specific or environmental domains)46 that have not
been previously examined will significantly contribute to our understanding of physical activity– behavior change.
We are grateful to Ross Brownson, PhD, Cora Craig, PhD, and
Bernardine Pinto, PhD, for their review of this manuscript.
This project was supported in part through grants from the
National Heart, Lung, and Blood Institute (HL68422 and
HL64342).
American Journal of Preventive Medicine, Volume 23, Number 2S
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