solved: Reply Post Your reply post should read approximately 250 to 350 words in length and should reference

From the Sch
University,
Israel, Sand,
Detroit His
Parkside (Ro

Address
nity Health
97201. E-ma

0749-379
http://dx

& 2015 Am

Leader Behaviors, Group Cohesion, and
Participation in a Walking

Group Program

Betty T. Izumi, PhD, Amy J. Schulz, PhD, Graciela Mentz, PhD, Barbara A. Israel, DrPH,

Sharon L. Sand, MPP, Angela G. Reyes, MPH, Bernadine Hoston, MA, ED, Dawn Richardson, DrPH,
Cindy Gamboa, Zachary Rowe, BBS, Goya Diaz

o
Po
H
pa
w
co
, P
il
7/
.do

e

Introduction: Less than half of all U.S. adults meet the 2008 Physical Activity Guidelines. Leader
behaviors and group cohesion have been associated with increased participation or adherence in
sports team and exercise class settings. Physical activity interventions in community settings that
encompass these factors may enhance intervention adherence. The purpose of this study is to
examine the impact of Community Health Promoter leader behaviors and group cohesion on
participation in a walking group intervention among racially/ethnically diverse adults in low to
moderate–income communities in Detroit, Michigan.

Design: Data for the current study were drawn from the Walk Your Heart to Health (WYHH) data
set. WYHH was a multisite cluster RCT with a lagged intervention and outcome measurements at
baseline and 4, 8, and 32 weeks. Pooled survey data from both intervention arms were used for the
current study. Data were analyzed between August 2013 and October 2014.

Setting/participants: A total of 603 non-Hispanic black, non-Hispanic white, and Hispanic adults
across five cohorts that began the 32-weekWYHH intervention between March 2009 and October 2011.

Intervention: The intervention was a 32-week walking group program hosted by community- and
faith-based organizations and facilitated by Community Health Promoters. Walking groups met
three times per week for 90 minutes per session. To promote participation in or adherence to
WYHH, Community Health Promoters used evidence-based strategies to facilitate group cohesion.
Group members assumed increasing leadership responsibility for facilitating sessions over time.

Main outcome measures: Participation in WYHH as measured by consistency of attendance.

Results: Community Health Promoter leader behaviors were positively associated with participation in
WYHH. Social but not task cohesion was significantly associated with consistent participation. Social
cohesion may mediate the relationship between leader behaviors and walking group participation.

Conclusions: Providing leaders with training to build socially cohesive groups may help motivate
individuals to continue participation in community-based physical activity programs.
(Am J Prev Med 2015;49(1):41–49) & 2015 American Journal of Preventive Medicine

ol of Community Health (Izumi, Richardson), Portland State
rtland, Oregon; School of Public Health (Schulz, Mentz,
oston, Gamboa, Diaz), University of Michigan, Ann Arbor;
nic Development Corporation (Reyes); and Friends of
e), Detroit, Michigan
rrespondence to: Betty T. Izumi, PhD, School of Commu-
ortland State University, 506 SW Mill St., Portland OR
: [email protected]
$36.00
i.org/10.1016/j.amepre.2015.01.019

rican Journal of Preventive Medicine � Published by Else

Introduction

Thehealth benefits associated with regular physical
activity include reduced risk for chronic diseases
such as cardiovascular disease, type 2 diabetes,

metabolic syndrome, and some cancers.1–6 Yet, less than
half of all adults meet the 2008 Physical Activity Guide-
lines,7 which include at least 150 minutes per week of
aerobic (e.g., brisk walking) and muscle-strengthening
activities that involve all major muscle groups, on 2 or

vier Inc. Am J Prev Med 2015;49(1):41–49 41

Izumi et al / Am J Prev Med 2015;49(1):41–4942

more days per week. Furthermore, rates of physical activity
and inactivity vary across race/ethnicity. Studies focusing
primarily on leisure-time activity have found that more
non-Hispanic white adults meet physical activity guide-
lines than non-Hispanic black and Hispanic adults.8–10 In
addition, adults with more education and whose family
incomes are above the poverty level are more likely to meet
physical activity guidelines than those with less education
and whose family incomes are at or below the poverty
level.5,11 To date, physical activity intervention research
among such underserved populations has been limited.12

Therefore, effective programs that reach low-income and
racially/ethnically diverse groups are needed.
Over the past two decades, interventions based on

group dynamics principles have successfully been used to
promote physical activity among adults.13,14 Such inter-
ventions have used a wide range of strategies to influence
the group environment, process, and structure to
increase cohesion among members. Although the mech-
anisms underlying intervention effectiveness are poorly
understood, studies have shown that group cohesion is
positively associated with physical activity outcomes,
including intervention adherence,15–19 physical activ-
ity,20–22 and cardiorespiratory fitness.23 Group cohesion
in the physical activity context has been defined as a
construct that includes the following dimensions: indi-
vidual attraction to the group task (e.g., walking);
individual attraction to the social dimensions of the
group (e.g., opportunities to interact with others);
perception of integration of the group around its task
(e.g., shared commitment to walking); and perception of
integration of the group around social concerns (e.g.,
social bonding within the group).13,24

A small body of research25–29 suggests that group
leader behaviors may be crucial factors for developing
and maintaining group cohesion in physical activity
interventions. Recently, for example, Caperchione and
colleagues28 reported that in women’s walking groups,
participant perceptions of leader enthusiasm, ability to
motivate, and availability outside of the group were
positively related to task and social dimensions of group
cohesion. In a qualitative study of adults in a Danish
community-based intervention, Christensen et al.29

found that, in addition to the exercise activity itself and
the composition of the group, the teaching ability of the
instructor was critical for forming cohesive groups.
To date, few studies have applied group dynamics

principles to physical activity interventions outside of
exercise class or sports team settings or in community-
based settings that reach individuals from diverse racial/
ethnic and socioeconomic backgrounds. Furthermore,
although research has shown that both leader behaviors
and group cohesion are related to positive outcomes, only

one study has considered their joint effects on physical
activity.30 In that study, Loughead and colleagues found
that, among older adults involved in exercise classes (e.g.,
tai chi, line dancing) for 1–120 months, the relationship
between leader behaviors and exercise program attend-
ance or perceived exertion was mediated by task but not
social dimensions of group cohesion.30 Thus, although
group dynamics–based interventions have been associ-
ated with positive physical activity outcomes, further
research on the mechanisms underlying intervention
effectiveness is warranted. The current study examines
the impact of a group dynamics–based intervention on
walking group participation (i.e., physical activity adher-
ence) among predominantly non-Hispanic black and
Hispanic adults participating in Walk Your Heart to
Health (WYHH), a walking group program in low to
moderate–income communities in Detroit, Michigan.
WYHH is part of a larger study, Community Approaches
to Cardiovascular Health, designed to increase active
living and improve heart health among Detroit residents
at increased risk for cardiovascular disease.31,32 This
study was conducted by the Healthy Environments
Partnership (HEP), a community-based participatory
research partnership established in 2000 to examine
and develop interventions to reduce cardiovascular
inequities in Detroit. HEP is overseen by a Steering
Committee, which meets monthly and is responsible for
oversight of all aspects of the Partnership’s work (partner
organizations listed in the Acknowledgments). Previously
published results from the WYHH intervention have
demonstrated its effectiveness in increasing physical
activity and reducing multiple indicators of cardiovascular
risk.32 The current study investigates the role of leader
behaviors and group cohesion in shaping adherence to the
WYHH intervention. Specifically, the hypotheses that
group leader behaviors and group cohesion were positively
associated with participation in WYHH and that associ-
ations between group leader behaviors and participation in
WYHH were mediated by group cohesion were tested.

Methods
Design and Setting

Data for the current study were drawn from the WYHH data set.32

TheWYHH intervention was a multisite cluster RCT with a lagged
intervention group. It was conducted in Detroit, Michigan, where
residents experience excess mortality due to cardiovascular disease
compared to the state and the nation.33,34 The sample consisted of
603 participants, enrolled across five cohorts that began the 32-
weekWYHH intervention betweenMarch 2009 and October 2011.
Individuals were recruited by HEP Steering Committee members,
staff, and the Community Health Promoters who facilitated the
walking groups. Individuals interested in participating in WYHH
were given a flier describing the intervention and completed an

www.ajpmonline.org

Izumi et al / Am J Prev Med 2015;49(1):41–49 43

interviewer-administered modified version of the Physical Activity
Readiness Questionnaire35 to determine eligibility. Those who
were eligible completed the baseline Health Risk Assessment and
were randomly assigned into one of two groups: intervention or
lagged intervention (control). Those enrolling with one or more
friends or family members were randomized as clusters to ensure
that they were in the same walking group. Walking groups were
facilitated by Community Health Promoters. Following tests for
statistical differences, the data from the intervention and the
lagged intervention groups were pooled for the current study. Data
were analyzed between August 2013 and October 2014. The
University of Michigan IRB approved all study procedures on
January 31, 2008. The Clinical Trials registration number is
NCT02036593. Further detail on the WYHH intervention is
described in Schulz and colleagues (Figure 1).32

Intervention

WYHH was a 32-week long walking group program facilitated by
Community Health Promoters and hosted by community- and
faith-based organizations located in Detroit neighborhoods. The

Figure 1. CONSORT flow diagram for Walk Your Heart to Health

July 2015

organizations received a rental fee for use of their space, which
included a room large enough for warm-up and cool-down
exercises and for indoor walking in the case of inclement weather.
The Community Health Promoters were paid staff members who
were also residents of Detroit.
In spring 2009, the health promoters received 60 hours of initial

training, which focused on study procedures (e.g., recruitment,
data collection); walking group facilitation; benefits of physical
activity; nutrition for heart health; and strategies to promote group
cohesion. Throughout the study period, the health promoters met
weekly for additional training and for technical and social support.
Each Community Health Promoter facilitated two walking

groups (intervention and lagged intervention groups) per cohort.
The average group size was 15 members. For the first 8 weeks in
each group, the health promoter facilitated three 90-minute
sessions per week. Each session included a warm-up period, 50
minutes of walking in the neighborhood, and a cool-down period.
The health promoters used evidence-based strategies13,14,36–38 to
influence the group environment, processes, and structure to
promote group cohesion (Table 1). In addition to promoting
group cohesion, these strategies also encouraged group members

Table 1. Examples of Evidence-Based Strategies Used to Facilitate Group Cohesion in Walk Your Heart to Health32

Components Strategies

Group
environment

Distinctiveness Encourage members to wear Walk Your Heart to Health T-shirts and use Walk Your Heart to Health
water bottles14

Identify group name14

Group
processes

Collective
goals

Set group goals for number of steps walked37

Cooperation Organize carpools for members to travel to and from walking group location23

Interaction Facilitate peer sharing and problem solving on topics related to nutrition and physical activity38

Encourage members to attend events (e.g., Thanksgiving dinner, concert) organized by other
members

Group
structure

Roles Request volunteers to assume responsibility for walking group facilitation tasks (e.g., attendance,
warm-up, cool-down)36

Norms Establish group norms (e.g., arrive on time)14

Izumi et al / Am J Prev Med 2015;49(1):41–4944

to assume increasing responsibility for facilitating the sessions.
Over the initial 8-week period, the health promoters gradually
reduced their roles and encouraged group members to assume
more responsibility for session facilitation. This process was
tailored to the group: in some groups, by the end of 8 weeks,
group members had assumed most of the responsibility for
facilitating the sessions, including identifying walking routes,
taking attendance, and leading warm-up and cool-down exercises.
In other groups, the process unfolded over a longer period of time,
with, for example, the health promoter attending the first 30
minutes during two sessions per week whereas group members
assumed responsibility for facilitating the third session.

Measures

Items assessing age (years); gender; self-reported race or ethnicity
(Hispanic, non-Hispanic black, non-Hispanic white); education;
and annual household income were drawn from the Health Risk
Assessment.

A modified version of the Physical Activity Group Environ-
ment Questionnaire (PAGE-Q)39 was used to measure group
cohesion. The 21-item PAGE-Q measures four dimensions of
group cohesion: (1) attraction to group task (ATG-T); (2)
attraction to group as a social unit (ATG-S); (3) perception of
group integration around task factors (GI-T); and (4) perception
of group integration around social factors (GI-S). All 21 items
were modified for use in the current study by replacing physical
activity group and program with walking group program. The
items were rated on a 5-point Likert-type scale, with 1 indicating
strongly disagree and 5 indicating strongly agree. The modified
items were included in a self-administered survey completed at
Week 4 and interviewer-administered surveys completed at
Weeks 8 and 32. The possibility of reducing the dimensionality
of the cohesion measure using exploratory factor analysis
techniques was investigated. Two factors were identified: task
cohesion (ATG-T, GI-T; Cronbach’s α¼0.87) and social cohesion
(ATG-S, GI-S; Cronbach’s α¼0.85). Models were subsequently
run using these factors for task and social cohesion. Table 2
provides examples of survey items used to measure task and
social cohesion.

A 21-item survey was developed to measure group members’
perceptions of community health promoters’ leader behaviors.
The development of the survey was iterative and involved
several steps, including reviewing relevant literature and
tools,25,40 conducting key informant interviews with HEP
Steering Committee members, pre-testing measures, and con-
sulting experts. Four dimensions of leader behaviors were
assessed in the survey, including three proposed by Chemers40

and applied to the physical activity context by Estabrooks
et al.25: image management (i.e., leader qualities that result in
trust and credibility to facilitate walking groups); relationship
development (i.e., ability of leader to develop relationships
with individual members); and resource deployment (i.e.,
ability to use knowledge, skills, and resources within the group
to achieve group goals). A fourth dimension, community
commitment, was added to reflect the importance of com-
munity health and community improvement, themes identi-
fied by members of the HEP Steering Committee. All items
were rated on a 5-point Likert-type scale, with 1 indicating
strongly disagree and 5 indicating strongly agree. The leader
behavior survey was self-administered at Week 4 and inter-
viewer administered at Weeks 8 and 32. Using similar
dimension reduction techniques as those described for group
cohesion, one leader behaviors factor was identified (Cron-
bach’s α¼0.88). Models were subsequently run using this
factor for leader behaviors. Table 2 provides examples of
survey items used to measure leader behaviors.

The dependent variable used in these analyses was walking
group participation, as a measure of intervention adherence.
Walking group participation was defined as the number of weeks
in which the participant attended at least one walking group
session (i.e., consistency of participation). Attendance was
obtained from records kept by Community Health Promoters.

Statistical Analysis

Exploratory data analysis techniques were used to assess the
distribution of adherence to WYHH. Q-Q plots and histograms
were constructed to confirm the normal assumptions; thus,
Gaussian models were used to assess the research questions.

www.ajpmonline.org

Table 2. Items Used to Measure Group Cohesion and Leader Behaviors in Walk Your Heart to Health32

Measure Item
Factor
loading

Task
cohesion

I like how much physical activity I get in this walking group.
This walking group provides me with a good opportunity to improve my health in
areas that are important to me.
I am happy with the intensity of the physical activities in this program.
I like the different types of physical activities done in this walking group.
I feel safe walking on the routes.

0.70645
0.99421

0.99175
0.70561
0.72311

Social
cohesion

This walking group is an important social group for me.
I enjoy my social interactions within this walking group.
I like meeting the people who come to this walking group.
If this walking group was to end, I would miss my contact with the other members.
In terms of the social experiences in my life, this walking group is very important.
The social interactions I have in this walking group are important to me.

0.73401
0.77318
0.74925
0.79841
0.70225
0.73869

Leader
behaviors

Our community health promoter creates opportunities for us to help out with organizing our group sessions.
Our community health promoter creates walking routes that match my abilities.
Our community health promoter is committed to helping our group achieve our goals.
Our community health promoter gives public recognition when group members help out with the
sessions.
Our community health promoter cares about my well-being.
Our community health promoter encourages everyone to participate in our discussions.
Our community health promoter encourages discussion between group members when there is
conflict.
Our community health promoter finds creative ways to solve problems.
Our community health promoter motivates us to work hard to achieve our goals.
Our community health promoter has taken the time to get to know me.
Our community health promoter would understand if I had to miss a session.
Our community health promoter is a good listener.
Our community health promoter makes me feel like I am an important member of our group.

0.70704
0.66704
0.77677
0.60722

0.77425
0.77196
0.63566

0.63673
0.77258
0.62993
0.73394
0.79818
0.74830

Izumi et al / Am J Prev Med 2015;49(1):41–49 45

Statistics including frequencies, means, and SDs were used to
identify basic characteristics of potential predictors. Independent
and joint effects of leader behaviors, task cohesion, and social
cohesion on physical activity were assessed using generalized
estimating equation (GEE) models, controlling for race/ethnicity,
age, gender, education, and household income. The GEE approach
with normal distribution and identity link with exchangeable
correlation structure was used to account for the clustering and
imbalance of the longitudinal data. Initial models test for the
individual effect of the leader behaviors factor and the two group
cohesion factors on walking group participation. Next, two models
to assess the joint effects of the leader behaviors factor with each of
the group cohesion factors on physical activity participation were
run. Owing to high correlations between the group cohesion
factors, a model to assess the effect of the leader behaviors factor
and the two group cohesion factors on physical activity partic-
ipation was not run. A formal mediation test41 was run to confirm
the extent to which group cohesion factors mediated associations
between leader behaviors and participation. Women-specific anal-
yses were also conducted to assess sensitivity of the models. Similar
patterns were found. Models presented here include the full sample.

Results
The average age of participants was 47.5 years, and 90%
were women. Approximately 35.5% of participants were
Hispanic and 61.2% were Non-Hispanic black, 54.7%
had more than 12 years of education, and 42.6 had a

July 2015

mean annual income o$20,000. Retention among those
who attended one or more sessions per week was 91% at
8 weeks and 65% at 32 weeks. Those who remained active
in WYHH at 8 and 32 weeks were older, 48.6 and 49.6
years, respectively, compared to 47.5 years at baseline
(po0.05) (Table 3). Week 4 means (SDs) for leader
behaviors, task cohesion, and social cohesion were 4.8
(0.4), 4.7 (4.7), and 4.3 (0.6), respectively. At 8 weeks, on
average, participants had attended at least one walking
group session in 6.6 (SD¼2.1) of the 8 weeks. At 32
weeks, on average, participants had attended at least one
walking group session in 19.6 (SD¼9.4) of the 32 weeks.
As shown in Table 4, leader behaviors were positively

associated with walking group participation (β¼2.71,
po0.001) (Model 1). Individual effects of task and social
cohesion on walking group participation are shown in
Models 2 and 3, respectively. Task cohesion was not
significantly associated with walking group participation
(β¼0.28, p¼0.63). However, social cohesion was posi-
tively and significantly associated with walking group
participation (β¼1.53, po0.001). When task cohesion
was added to Model 1, the association between leader
behaviors and walking group participation was strength-
ened (β¼3.83, po0.001) (Model 4). When social cohe-
sion was added to Model 1, associations between leader

Table 3. Demographic Characteristics of Walk Your Heart to
Health32 Study Participants (N¼603)

Characteristics Baseline

Age, M (SD) 47.5 (13.6)

Female (%) 90.0

Race/ethnicity (%)

Hispanic 35.5

Non-Hispanic black 61.2

Non-Hispanic white 3.3

Education 412 years (%) 54.7

Annual household income, $ (%)

r9,999 18.0

10,000–19,999 24.6

20,000–34,999 25.2

Z35,000 32.2

Employed (%) 28.0

Izumi et al / Am J Prev Med 2015;49(1):41–4946

behaviors and walking group participation were attenu-
ated but remained significant (β¼1.81, p¼0.02) (Model
5). Results from a formal mediation test (results not
shown) were suggestive of a partial mediation effect of
social cohesion on the association between leader behav-
iors and walking group participation (c-c/se¼1.622,
p¼0.083); the effect of task cohesion on the association
between leader behaviors and walking group participa-
tion was not significant (c-c/se¼–1.748, p¼0.983).

Discussion
There are three main findings from the results presented
here. First, participants who perceived that their Com-
munity Health Promoters developed relationships with
individual group members and harnessed the group’s
knowledge, skills, and resources to achieve group goals

Table 4. Walking Group Participation Regressed on Leader Beh
Characteristicsa**

Model 1 Model 2
β (SE) β (SE)

Intercept –7.04 (3.28) 4.74 (2.88)

Leader behaviors 2.71** (0.60)

Task cohesion 0.28 (0.58)

Social cohesion

Note: Boldface indicates statistical significance (*po0.05; **po0.001).
aIndividual characteristics include race/ethnicity, age, gender, education, an

had more consistent participation in WYHH. To date,
few quantitative studies have tested the effect of leader
behaviors on adherence in community-based interventions
to promote physical activity.28,30,42 Loughead and col-
leagues30 reported that among older adults participating
in group exercise classes, leader motivation, availability,
and enthusiasm were related to adherence. In a study of
university students enrolled in exercise classes for course
credit, Remers et al.42 found that instructor behavior did
not influence adherence. In both studies, leader behavior
was measured using four statements assessing partic-
ipants’ perceptions of their exercise instructors’ enthusi-
asm, ability to motivate, availability outside class, and
ability to provide personal instruction.30,42 Neither study
included measures of leader ability to develop relation-
ships with individual group members and to mobilize
resources within the group. As described in qualitative
studies, however, effective physical activity leaders also
show personal interest in and concern for participants and
facilitate opportunities for participants to make contribu-
tions to the group.25,29 In addition to personally recruiting
neighborhood residents to participate in WYHH, Com-
munity Health Promoters showed an interest in and
concern for their group members by, for example, calling
participants to remind and encourage them to come to
walking group sessions, facilitating carpools to attend
walking group sessions for participants with transportation
issues, and creating walking routes for participants with
varying levels of fitness. Community Health Promoters also
drew on group member knowledge, skills, and interests as
an important strategy to sustain their walking groups
beyond the initial 8 weeks of the intervention period.
Second, social but not task cohesion was associated with

more consistent participation in WYHH. This finding is
somewhat inconsistent with sport psychology research18,43,44

in which task dimensions of cohesion have been most
strongly associated with physical activity adherence. How-
ever, the nature of the relationship between group cohesion
and physical activity outcomes may be situation specific and

aviors, Task, and Social Cohesion, Adjusting for Individual

Model 3 Model 4 Model 5
β (SE) β (SE) β (SE)

–0.79 (1.80) –5.70 (3.28) –7.43* (3.24)

3.83** (0.91) 1.81* (0.76)

–1.42 (0.72)

1.53** (0.37) 1.05* (0.42)

d household income.

www.ajpmonline.org

Izumi et al / Am J Prev Med 2015;49(1):41–49 47

differ across settings.44 Most group cohesion studies have
been conducted in settings such as fitness classes in which
individuals typically have little structured opportunity to
interact with others. It may be that in such settings, task
cohesion motivates physical activity participation. In
WYHH, participants had multiple opportunities to socialize
with their peers during each of the 90-minute sessions. In
addition, the neighborhood-specific location of the walking
groups and faith- and community-based host organizations
may have facilitated interaction between participants outside
of the sessions, and contributed to the importance of social
cohesion in facilitating participation.
Finally, the findings presented here suggest that

Community Health Promoters fostered social cohesion
within their groups, which in turn led to more con-
sistent participation in the walking groups. This result
differs from findings reported by Loughead and col-
leagues,30 in which task but not social cohesion medi-
ated the relationship between leader behaviors and
exercise class adherence. The inconsistent findings
between the current study and the study conducted by
Loughead et al. may reflect the design of the WYHH
intervention, which directed Community Health Pro-
moters to use their leadership positions to implement
strategies aimed at building cohesive groups. In the
study conducted by Loughead and colleagues, it is
unclear whether or to what degree such strategies were
used. Further research on the mediational role of social
cohesion in community-based physical activity inter-
ventions is needed.
There are a number of strengths associated with this

study. First, WYHH is among few community-based
physical activity interventions based on group dynamics
principles. Of particular importance is identification of
strategies that may be used to promote physical activity
among racially/ethnically diverse adults in low to
moderate–income urban settings. Some of these strat-
egies include collaborating with faith- and community-
based organizations to increase opportunities for par-
ticipants to develop and strengthen social bonds outside
of walking group sessions, peer sharing, and problem
solving to overcome challenges associated with consis-
tent walking, and facilitating opportunities for members
to contribute to group goals. Second, the cluster ran-
domization allowed us to maintain social support
between friends and family who enrolled in the study
together while simultaneously using a randomized study
design. Third, the community-based process used to
develop and implement WYHH increased the relevance
of the intervention and the likelihood of identifying and
addressing challenges (e.g., identifying safe walking
routes) that may erect barriers to meeting physical
activity recommendation in urban areas.

July 2015

Limitations
There are also several limitations of this study that should
be noted. First, the focus of this study was on associations
between leader behaviors and group cohesion on con-
sistent participation in walking groups. The association
between consistent participation and increases in ped-
ometer steps over time as an indicator of physical activity
has been demonstrated elsewhere.32 In the current study,
associations between leader behaviors and group cohe-
sion on steps were not examined. Future studies should
investigate the impact of leader behaviors and group
cohesion on physical activity outcomes, including, for
example, changes in steps or other indicators of physical
activity. Second, this study did not assess the impact of
weather on walking group participation. Sensitivity
analyses conducted to evaluate seasonal effects on walk-
ing group adherence found no significant differences in
participation across seasons. In addition, sensitivity
analyses to determine effects of indoor versus outdoor
walking on walking group adherence also found no
significant differences in participation. Further research
to better understand how weather and walking locations
affect participation in walking group interventions would
be useful for assessing factors that influence adherence.
Finally, this study analyzed participation in a walking
group program designed to promote physical activity.
The implications of the findings presented here for
interventions designed to promote muscle-strength-
ening exercises, as another important component of
overall physical activity, were not assessed.

Conclusions
The results reported here suggest benefits of physical
activity interventions based on group dynamics princi-
ples. Given high rates of physical inactivity among
underserved populations, interventions facilitated by
leaders trained to use group dynamics strategies to build
group cohesion may be particularly effective in socio-
economically and racially/ethnically diverse areas.

The Healthy Environments Partnership (HEP) is an affiliated
partnership of the Detroit Community–Academic Urban
Research Center. We thank the members of the HEP Steering
Committee at the time this study was conducted for their
contributions to the work presented here, including representa-
tives from Brightmoor Community Center, Eastside Commun-
ity Network, Institute for Population Health, Detroit Hispanic
Development Corporation, Friends of Parkside, Henry Ford
Health System, University of Michigan School of Public Health
and Survey Research Center, and community members at large.
We also thank the four anonymous peer reviewers for their
insights and detailed suggestions for improving our manuscript.

Izumi et al / Am J Prev Med 2015;49(1):41–4948

The work presented here was supported through a grant from
the National Institute of Minority Health and Health Disparities
(number R24 MD001619) and through the W.K. Kellogg
Foundation’s Kellogg Health Scholars Program.

Portland State University, University of Michigan, Detroit
Hispanic Development Corporation, Friends of Parkside,
National Institute for Minority Health and Health Disparities,
and W.K. Kellogg Foundation did not play any role in study
design, collection, analysis, and interpretation of data; writing
the report; and the decision to submit the report for
publication.

No financial disclosures were reported by the authors of
this paper.

References
1. Tully MA, Cupples ME, Chan WS, McGlade K, Young IS. Brisk

walking, fitness, and cardiovascular risk: a randomized controlled trial
in primary care. Prev Med. 2005;4(2):622–628. http://dx.doi.org/
10.1016/j.ypmed.2004.11.030.

2. Murphy MH, Murtagh EM, Boreham CAG, Hare LG, Nevill AM. The
effect of worksite based walking programme on cardiovascular risk in
previously sedentary civil servants. BMC Public Health. 2006;6(136).

3. Murphy MH, Nevill AM, Murtagh EM, Holder RL. The effect of walking
on fitness, fatness and resting blood pressure: a meta-analysis of rando-
mised, controlled trials. Prev Med. 2007;44(5):377–385. http://dx.doi.org/
10.1016/j.ypmed.2006.12.008.

4. Ainsworth BE, Haskell WL, Herrmann SD, et al. 2011 Compendium of
Physical Activities: a second update of codes and MET values.Med Sci
Sports Exerc. 2011;43:1575–1581. http://dx.doi.org/10.1249/MSS.
0b013e31821ece12.

5. CDC. Facts About Physical Activity. www.cdc.gov/physicalactivity/
data/facts.html.

6. Kassavou A, Turner A, French DP. Do interventions to promote
walking in groups increase physical activity? A meta-analysis. Int J
Behav Nutr Phys Act. 2013:10.

7. USDHHS. 2008 Physical Activity Guidelines for Americans. www.
health.gov/paguidelines/pdf/paguide.pdf.

8. CDC. Prevalence of self-reported physically active adults—United
States, 2007. MMWR Morb Mortal Wkly Rep. 2008;57(48):1297–1300.

9. Marshall SJ, Jones DA, Ainsworth BE, Reis JP, Levy SS, Race/ethnicity
Macera CA. social class, and leisure-time physical inactivity. Med Sci
Sports Exerc. 2007;39(1):44–51. http://dx.doi.org/10.1249/01.mss.
0000239401.16381.37.

10. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M.
Physical activity in the United States measured by accelerometer. Med
Sci Sports Exerc. 2008;40(1):181–188. http://dx.doi.org/10.1249/mss.
0b013e31815a51b3.

11. Schiller JS, Lucas JW, Peregoy JA. Summary health statistics for U.S.
adults: National Health Interview Survey, 2011. Vital Health Stat.
2012;10(256).

12. Marcus BH, Williams DV, Dubbert PM, et al. Physical activity
intervention studies: what we know and what we need to know.
Circulation. 2006;114:2739–2752. http://dx.doi.org/10.1161/CIRCULA
TIONAHA.106.179683.

13. Estabrooks PA, Harden SM, Burke SM. Group dynamics in physical
activity promotion: what works? Soc Pers Psychol Compass. 2012;6(1):
18–40. http://dx.doi.org/10.1111/j.1751-9004.2011.00409.x.

14. Carron AV, Spink KS. Team building in an exercise setting. Sport
Psychol. 1993;7:8–18.

15. Spink K, CarronA. Group cohesion effects in exercise classes. Small Group
Res. 1994;25(1):26–42. http://dx.doi.org/10.1177/1046496494251003.

16. Estabrooks PA, Carron A. Group cohesion in older adult exercisers:
prediction and intervention effects. J Behav Med. 1999;22(6):
575–588. http://dx.doi.org/10.1023/A:1018741712755.

17. Carron AV, Widmeyer WN, Brawley LR. Group cohesion and
individual adherence to physical activity. J Sport Exerc Psychol.
1988;10:127–138.

18. Annesi JJ. Effects of minimal group promotion on cohesion and exercise
adherence. Small Group Res. 1999;30:542–557. http://dx.doi.org/
10.1177/104649649903000503.

19. Kwak L, Kremers S, Walsh A, Brug H. How is your walking group
running? Health Educ. 2006;106(1):21–31. http://dx.doi.org/
10.1108/09654280610637175.

20. Wilson MG, Basta TB, Bynum BH, DeJoy DM, Vandenberg RJ, Dishman
RK. Do intervention fidelity and dose influence outcomes? Results from
the move to improve worksite physical activity program.Health Educ Res.
2010;25:294–305. http://dx.doi.org/10.1093/her/cyn065.

21. Estabrooks PA, Fox EH, Doerksen SE, Bradshaw MH, King AC.
Participatory research to promote physical activity at congregate-meal
sites. J Aging Phys Act. 2005;13:121–144.

22. Lee RE, O’Connor DP, Smith-RayMA, et al. Mediating effects of group
cohesion on physical activity and diet in women of color: health is
power. Am J Health Promot. 2012;26(4):e116–e125. http://dx.doi.org/
10.4278/ajhp.101215-QUAN-400.

23. Perry CK, Rosenfeld AG, Bennett JA, Potempa K. Heart-to-heat:
promoting walking in rural women through motivational interviewing
and group support. J Cardiovasc Nurs. 2007;22:304–312. http://dx.doi.org/
10.1097/01.JCN.0000278953.67630.e3.

24. Carron AV, Widmeyer WN, Brawley LR. The measurement of
cohesion in sports teams: the Group Environment Questionnaire.
Can J Sport Sci. 1989;14:55–59.

25. Estabrooks PA, Munroe KJ, Fox EH, et al. Leadership in physical
activity groups for older adults: a qualitative analysis. J Aging Phys Act.
2004;12:232–245.

26. Carron AV. Cohesiveness in sports groups: interpretations and
considerations. J Sport Psychol. 1982;4:123–128.

27. Gardner DE, Shields DL, Bredemeier BJ, Bostrom A. The relationship
between perceived coaching behaviors and team cohesion among
baseball and softball players. Sport Psychol. 1996;10:367–381.

28. Caperchione C, Mummery WK, Duncan M. Investigating the relation-
ship between leader behaviours and group cohesion within women’s
walking groups. J Sci Med Sport. 2011;14:325–330. http://dx.doi.org/
10.1016/j.jsams.2011.03.005.

29. Christensen U, Schmidt L, Budtz-Jorgensen E, Avlund K. Group cohesion
and social support in exercise classes: results from a Danish Intervention
Study. Health Educ Behav. 2006;33(5):677–689. http://dx.doi.org/
10.1177/1090198105277397.

30. Loughead T, Colman M, Carron A. Investigating the mediational
relationship of leadership, class cohesion, and adherence in an exercise
setting. Small Group Res. 2001;32(5):558–575. http://dx.doi.org/10.
1177/104649640103200503.

31. Schulz AJ, Israel BA, Coombe C, et al. A community-based partic-
ipatory planning process and multilevel intervention design: toward
eliminating cardiovascular health inequities. Health Promot Pract.
2011;12(6):900–911. http://dx.doi.org/10.1177/1524839909359156.

32. Schulz AJ, Israel BA, Mentz G, et al. Effectiveness of a walking group
intervention to promote physical activity and cariovascular health in
predominantly non-Hisapnic Black and Hispanic urban neighbor-
hoods: findings from the Walk Your Heart to Health Intervention.
Health Educ Behav. 2015;42(3):380–392. http://dx.doi.org/10.1177/
1090198114560015.

33. Murphy SL, Xu JQ, Kochanek KD. Deaths: preliminary data for 2010.
Natl Vital Stat Rep. 2012;60(4).

34. Michigan Department of Community Health.Mortality Statistics 2012.
www.mdch.state.mi.us/pha/osr/CHI/Deaths/frame.asp.

www.ajpmonline.org

Izumi et al / Am J Prev Med 2015;49(1):41–49 49

35. Cardinal BJ, Esters J, Cardinal MK. Evaluation of the revised physical
activity readiness questionnaire in older adults. Med Sci Sports
Exerc. 1996;28(4):468–472. http://dx.doi.org/10.1097/00005768-1996040
00-00011.

36. Johnson DW, Johnson FP. Joining Together: Group Theory and
Group Skills. 11th ed., Boston, MA: Pearson Education Limited,
2014.

37. Burke SM, Shapcott KM, Carron AV, Bradshaw MH, Estabrooks PA.
Group goal setting and performance in a physical activity context. Int J
Sport Exerc Psychol. 2010;8(3):245–261. http://dx.doi.org/10.1080/
1612197X.2010.9671952.

38. Cramp AG, Brawley LR. Moms in motion: a group-mediated cogni-
tive-behavioral physical activity intervention. Int J Behav Nutr Phys
Act. 2006;3(23).

39. Estabrooks PA, Carron AV. The Physical Activity Group Environment
Questionnaire: an instrument for the assessment of cohesion in

July 2015

exercise classes. Group Dyn. 2000;4(3):230–243. http://dx.doi.org/
10.1037/1089-2699.4.3.230.

40. Chemers MM. Leadership research and theory: a functional integration.
Group Dyn. 2000;4(1):27–43. http://dx.doi.org/10.1037/1089-2699.4.1.27.

41. Freedman LS, Schatzkin A. Sample size for studying intermediate
endpoints within intervention trials of observational studies. Am J
Epidemiol. 1992;136:1148–1159.

42. Remers L, Widmeyer WN, Williams JM, Myers L. Possible mediators
and moderators of the class size-member adherence relationship in
exercise. J Appl Sport Psychol. 1995;7:38–49. http://dx.doi.org/
10.1080/10413209508406299.

43. Spink KS, Carron AV. Group cohesion and adherence in exercise
classes. J Sport Exerc Psychol. 1992;14:78–86.

44. Spink K. Group cohesion and adherence in unstructured exercise
groups. Psychol Sport Exerc. 2013;15(3):293–298. http://dx.doi.org/10.
1016/j.psychsport.2013.11.008.