Capella University Ecological Systems and Systems Theory Paper

• Ecological Systems

Discuss and examine the ecological systems present to individuals who are experiencing the issue you are examining on a local or national level. Focus on the environment, government, ecological, and other forces that impact individuals and groups with this concern. Explain how ecological theory contributes to the maintenance of that issue and how adjustments within the ecological paradigm can create change that impacts individuals struggling with their concerns.

How does Bronfenbrenner’s concept of ecological development challenge the strict use of stage developmental processes in human development? Of what importance is it to know the ecological systems concepts in understanding the implementation of programs in the community provided for ethnically, economically, and socially diverse individuals?

• Systems Theory

Forte’s expansive description of systems theory provides a solid basis for understanding the concept of systemic thinking within a social organization that is created across disciplines. Understanding leadership, advocacy, participation, and encouragement to contribute to the system develops responses that are valid and applicable to the issues you may be examining in such a group. Issues of cultural diversity must also be considered as responses in systems theory approaches and should vary according to the needs of groups.

The concept of systems theory as only a clinical or organizational component is expanded as we understand the power, resources, participants, structure and problem-solving skills that can be incorporated in a unique way. The clients, participants, stakeholders, and interested individuals who understand a systemic approach to addressing community issues and creating a stable system that can focus on addressing community issues, benefit from the simplicity of the concept of systems and organizations. Systems theory provides another perspective from which to view your issue. This lens allows you to divide the components of the issue and view them in metaphorical ways.

After reading Forte’s concepts of systems theory, explain how systems theory and the association of images with systems theory enhances your understanding of the issue you have chosen to study. Would the application of concepts from systems theory and your personal understanding of how clinicians may utilize theory in working with groups, contribute to your ability to manage a group that has united to resolve community issues or provide support for concerns?

Am J Community Psychol (2008) 42:94–104
DOI 10.1007/s10464-008-9182-z
ORIGINAL PAPER
What Motivates People to Participate More in Community-based
Coalitions?
Rebecca Wells Æ Ann J. Ward Æ Mark Feinberg Æ
Jeffrey A. Alexander
Published online: 2 July 2008

Springer Science+Business Media, LLC 2008
Abstract The purpose of this study was to identify
potential opportunities for improving member participation
in community-based coalitions. We hypothesized that
opportunities for influence and process competence would
each foster higher levels of individual member participation. We tested these hypotheses in a sample of 818
members within 79 youth-oriented coalitions. Opportunities for influence were measured as members’ perceptions
of an inclusive board leadership style and members’
reported committee roles. Coalition process competence
was measured through member perceptions of strategic
board directedness and meeting effectiveness. Members
reported three types of participation within meetings as
well as how much time they devoted to coalition business
beyond meetings. Generalized linear models accommodated clustering of individuals within coalitions.
Opportunities for influence were associated with individuals’ participation both within and beyond meetings.
Coalition process competence was not associated with
R. Wells (&)
Department of Health Policy and Administration, School of
Public Health, University of North Carolina, Campus Box 7411,
1104F McGavran-Greenberg Hall, Chapel Hill,
NC 27599-7411, USA
e-mail: rswells@email.unc.edu
A. J. Ward
WHO Iraq Local Area Development, Queen Margaret University
College, Edinburgh, Scotland
M. Feinberg
Prevention Research Center, The Pennsylvania State University,
State College, PA, USA
J. A. Alexander
Department of Health Management and Policy, School of Public
Health, University of Michigan, Ann Arbor, MI, USA
123
participation. These results suggest that leadership inclusivity rather than process competence may best facilitate
member participation.
Keywords Community-based coalitions
Participation

Inclusion
Empowerment
Shared leadership

Competence
Introduction
Throughout the United States, community-based coalitions
have become a prominent mechanism for addressing issues
as diverse as heart disease, substance abuse, AIDS, and
violence (Alexander et al. 2003; Butterfoss et al. 1996;
Butterfoss and Kegler 2002; Kumpfer et al. 1993; Mayer
et al. 1998). Community-based coalitions are collaborative
organizations whose members represent multiple sectors.
Together they address common goals, typically related to
health promotion, broadly defined (Butterfoss and Kegler
2002). Coalitions often have ambitious agendas for
improving public health, including health behavioral
changes and reduced disease burden. They address these
goals through outreach and media campaigns and services
such as health screening, healthy lifestyle classes, and
support groups. Another major function of coalitions is
enhancing coordination among existing services provided
by member organizations (Fawcett et al. 1997; Francisco
et al. 1993; Knoke 1990; Mitchell and Shortell 2000).
Community-based coalitions’ primary asset is their
membership (Wandersman et al. 1987), which frequently
includes representatives of nonprofits, business, schools,
government, and health care, as well as private citizens.
Members of coalitions do not cede authority over any of
their own operations to a common governing body. One of
Am J Community Psychol (2008) 42:94–104
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the central leadership challenges coalitions face is thus to
engage and retain such diverse constituents (Alexander
et al. 2003; Butterfoss et al. 1996; Goodman et al. 1998).
This challenge motivated the current study, which focused
specifically on what coalition characteristics were associated with higher levels of individual member participation.
Previous theory has portrayed the motivations for
member participation in coalitions in terms of three
dimensions (Clark and Wilson 1961; Knoke 1990). The first
is interpersonal. Examples include an enhanced sense of
group identification (when ‘‘you’’ becomes ‘‘we’’), status
within the group (Clark and Wilson 1961), and enjoyment
of leading and organizing (Perlman 1976; Rich 1980). The
second type of member motivation is instrumental, relating
to private benefits only achievable through participation in
the coalition (Knoke 1990). Theoretically, instrumental
benefits have monetary value (Clark and Wilson 1961),
such as could be ascribed directly to additional external
funding, for instance, or indirectly to increased referrals. In
practice, however, instrumental goals may also include such
vital intangibles as better information about the local
community (Prestby et al. 1990) and increased agency
legitimacy. Third, members may have normative goals such
as population well-being. These public goods are collective
and typically mirror the goals of the coalition (Chinman and
Wandersman 1999). When members speak in terms of duty,
responsibility, and values, they are discussing normative
incentives for participation (Clary et al. 1998).
Coalition leaders may potentially influence a range of
incentives for member participation, including helping
people make new contacts, facilitating agencies’ goal
achievement through coalition activities, and demonstrating community impact. In this study, we examine two
incentives, each of which is foundational in that it relates to
coalition capacity to achieve other member goals. These
incentives are the opportunities people experience for
influence within the coalition and how competent they
perceive coalition processes to be. In terms of individual
decisions about how much to participate in coalitions, these
two factors might be framed as ‘Can I influence what this
coalition does?’ and ‘How capable is this group of
achieving those goals?’
1979; Knoke 1990). This family of organizations, which
includes community-based coalitions as well as national
and international associations, is distinguished from other
organizations by having members who are committed to
pursue a public good and very few paid participants.
The collective action organizations literature frames
member participation in terms of incentives (Prestby and
Wandersman 1985; Rogers et al. 1993; Roussos and Fawcett
2000). Previous research has found that coalition members
engage according to their opportunities to thereby meet their
own agendas (Barkan et al. 1993; Butterfoss et al. 1996;
Chinman and Wandersman 1999; Omoto and Snyder 1995).
Knoke (1990) builds on exchange theory (Wilson 2000) to
argue that collective action organizations with more inclusive governance structures foster participation by enhancing
the return on member time investment. Other frameworks of
collaboration have also treated inclusivity as essential to
translating member capabilities into coalition capacity,
using the language of empowerment and shared leadership.
A quarter century ago, authors in this journal noted the
heuristic potential of an empowerment perspective on
community psychology (Rappaport 1981). More recently,
Lasker and Weiss (2003) have argued that individual
empowerment is an essential precondition of collaborative
problem solving and enhanced community health. Similarly,
based on a national study of community health promotion
partnerships, Alexander et al. (2003) identified power sharing as essential to fostering collective action.
As these authors put it (p. 168):
What Affects Participation?
Characterizing Member Participation in Coalitions
As noted previously, this study drew on both the collective
action organization and more recent coalition literatures.
Collective action organizations are goal-directed, boundary-maintaining activity systems that seek non-market
solutions to individual or group problems; maintain formal
criteria for membership on a voluntary basis; sometimes
employ people as leaders; and provide formal democratic
procedures to involve members in policy decisions (Aldrich
There are essentially two ways people contribute their time
and energy to coalitions: within coalition meetings and
through effort devoted to coalition activities beyond
meetings. During regularly scheduled coalition meetings,
members decide on their collective mission and strategies,
share information among member agencies (often lobbying
for their respective agendas), plan interventions (Chinman
and Wandersman 1999), and design related materials and
In many respects, the collaborative community health
partnership operates as a virtual organization. It often
lacks a formal legal status; occupies no physical space
of its own; relies heavily on financial contributions
from partnering organizations; and accomplishes the
bulk of its work through the donated time and effort of
partnering organization employees, community
groups, and concerned citizens. By sharing power to
set priorities, allocate resources, and evaluate performance, partnership leaders foster a sense of joint
ownership and collective responsibility, from which
collateral leadership emerges.
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tools. These interactions facilitate ties between individuals
and agencies within coalitions as well as formalize and refine
collective plans (Butterfoss et al. 1996; Kegler et al. 1998).
The second dimension of coalition participation is the
effort that takes place outside meetings. Given very limited
paid staff, coalitions typically rely heavily on members for
such contributions. Between meetings coalition members
often recruit new members, draft and distribute meeting
agendas and minutes, design and implement needs assessments, and plan, implement and evaluate outreach
activities (Butterfoss et al. 1993; Butterfoss and Kegler
2002; Goodman et al. 1998; Granner and Sharpe 2004).
Thus, whereas participation in some types of groups might
be adequately measured within meetings, for coalitions
time outside meetings is also vital.
The current study contributes to the coalition literature
in five key respects. First, we explicitly build on previous
theory by identifying and testing common predictions from
literatures that have not been generally linked, that is, a
framework of ‘‘collective action organizations’’ as well as
more recent work on coalitions (Knoke 1990; Lasker and
Weiss 2003). This offers the opportunity to draw more
effectively on all potentially relevant previous work on
factors affecting participation in coalitions. Second, we
examine potential ways to improve participation in operational terms. The results are practical implications for
coalition leaders in terms of actions they can take. Third,
because coalitions need multiple forms of member
engagement to succeed, we measure participation within
meetings in terms of attendance, time spent in meetings,
and talking, as well as the time members devote to coalition efforts beyond meetings. Fourth, we draw on data from
coalitions that address a range of related youth risky
behaviors, including violence, sex, and delinquency, in
addition to the substance use which has been the focus of
most previous coalitions studied (Zakocs and Edwards
2006). This offers the possibility of extending generality to
other health promotion coalitions that are addressing interrelated sets of health behaviors. Finally, we control for
individual member attributes that may also affect participation, such as coalition tenure, education, and agency
affiliation versus status as a private citizen, as well as
demographics such as age, race/ethnicity, and sex (Perkins
et al. 1990; Prestby and Wandersman 1985). This improves
our ability to isolate the unique effects of factors that
coalition leaders can shape.
Opportunities for Influence
One way leaders may share power is by explicitly asking
for member input and recognizing people for the contributions they make. Path analysis of survey data from a
national sample of health promotion coalition members
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Am J Community Psychol (2008) 42:94–104
revealed that an empowering leadership style, including
member perceptions that leaders sought and recognized
member talents, predicted consensus on coalition vision
and in turn greater perceived participation benefits and self
reported participation levels (Metzger et al. 2005). Previous evidence also generally suggests that individuals
participate more when they receive personal recognition
from coalition leaders (Butterfoss et al. 1996; Butterfoss
and Kegler 2002; Christensen et al. 1999; Fisher and
Ackerman 1998; Zweigenhaft et al. 1996).
Shared leadership may also facilitate member participation by increasing member commitment and opportunities to
affect collective goals (Knoke 1990). Previous evidence
suggests that opportunities to influence decision making
encourage member participation (Wandersman et al. 1987)
For instance, Butterfoss et al. (1996) found that opportunities to influence decisions were positively associated with the
numbers of hours individual members reported devoting to
coalition activities outside meetings. A recent comparative
case study found that the more active coalition had a much
more inclusive pattern of information seeking than did its
less active counterpart (Wells et al. 2007).
Together, these studies support the prediction that:
H1 Coalition members will participate more when they
perceive more opportunities for influence.
Coalition Process Competence
Another precondition of active member participation in
coalitions is arguably members’ perception that coalition
processes are sufficiently competent to facilitate goal
achievement, a construct we refer to as ‘coalition process
competence.’ This may matter at both strategic and tactical
levels. At the strategic level, coalition leaders may develop
their overarching goals and decision making processes with
varying levels of clarity and realism. Such ‘‘big picture’’
direction, if provided effectively, may make these virtual
organizations real enough to inspire active member
engagement. Tactically, the day-to-day processes through
which coalitions pursue strategies may also foster participation. An organization whose members only meet for a
few hours a month may be particularly reliant on the efficiency and focus with which that time is used to meet
member goals.
Previous theory has tended to assert the importance of
process competence in fairly global terms. Knoke (1990,
p. 15), for instance, argues that competence is ‘‘critical to
generating support for collective actions…’’ In a similar
vein, Reininger et al. (1999) argue that coalitions can
reduce member frustrations and increase commitment by
clearly defining their scope and intended efforts. Lasker
and Weiss (2003) posit that collective ‘‘synergy,’’ which
Am J Community Psychol (2008) 42:94–104
they define as the successful combination of knowledge,
skills, and other resources, is a necessary precondition of
effective collaborative problem solving. They note that this
is an inherently collective dynamic, although we further
observe that its motivational effects on participation are
filtered through members’ individual perceptions. Finally,
previous analyses on a subset of the coalitions examined in
the current study revealed a significant correlation between
board directedness and later sustainability (Gomez et al.
2005).
The modest body of empirical evidence to date about
coalition process competence and member participation has
been framed in terms of formalization of rules and procedures. Whereas such structure could imply rigidity in
bureaucratic contexts, given coalitions’ fluid boundaries,
more structure is likely essential to focusing member
engagement. An early study reported that block associations’ ‘order and organization’ were significantly correlated
with member reports of becoming increasingly involved
over time (Giamartino and Wandersman 1983), but a later
reanalysis found nonsignificant associations at both the
individual and group levels when controlling for the effects
of the other level (Florin et al. 1990). Another study also
conducted at the organizational level revealed that mean
perceived competence was higher in active block associations than in inactive associations, although not
significantly so (Prestby and Wandersman 1985). Butterfoss
et al. (1996) found that both perceived leader competence
and ‘order and organization’ (Moos 1986) were positively
associated with the number of hours individuals reported
spending outside meetings on coalition activities.
Overall, we may predict based on admittedly mixed
prior evidence that:
H2 Members will participate more when they perceive
greater coalition process competence.
Methods
Sample
Communities That Care is a model for involving community leaders in coordinated strategies to reduce adolescent
problem behaviors such as violence, drug and alcohol use,
sex, and delinquency, and promote positive youth development (Hawkins et al. 2002). Each community’s leaders
form a ‘‘prevention board’’ that undergoes training and
then systematically assesses local risk and protective factors related to youth. They are then supposed to prioritize
problems, select one or more empirically based prevention
programs, and evaluate impact over time. In the United
States, a randomized trial funded by four National Institutes of Health and the Center for Substance Abuse and
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Prevention (CSAP) is currently measuring delinquency,
violence, and sexual behavior as well as tobacco, alcohol
and other drug use of adolescents in intervention and
control communities. Previous work has demonstrated the
utility of the Communities That Care model for addressing
other problem behaviors, such as bullying (e.g., the Elizabethtown Area Communities That Care). Communities
That Care initiatives are currently being implemented
throughout New York State and in the Seattle public
schools. In the United Kingdom, the Rowntree Foundation
currently funds over 30 Communities That Care coalitions.
Other initiatives are underway in Australia and the
Netherlands.
In Pennsylvania, four state agencies supported implementation of Communities That Care coalitions by pooling
funds with federal Title V funds in the mid-1990s. A state
steering committee has overseen over $15 million in
funding for a total of 115 coalitions throughout the state.
Coalition catchment areas have ranged from neighborhoods to counties. External support has included 1 year
planning grants, 3 year implementation grants that have
underwritten ongoing technical assistance and evaluation,
and subsequent continued technical assistance (Feinberg
et al. 2004).
Data
The unit of analysis for this study was the individual
member. All but one measure (coalition founding dates,
from Prevention Research Center records) were from 2004
web questionnaires of members. The web questionnaires
were sent to all active members of smaller coalitions and to
the most active 25 members of larger coalitions, as identified by coalition leaders. Two and six week reminders
were emailed to members, who also had the option of
completing pen-and-paper surveys (Feinberg et al. 2008).
This procedure was followed for 1,502 individuals in 100
coalitions; 867 within 79 coalitions responded, 818 of
whom provided information about their participation. Thus
the final response rates were 54% at the individual level
and 79% at the coalition level (Feinberg et al. 2008).
Researchers at the Penn State Prevention Research Center
then produced a report with each coalition’s average score
on each scale compared either to the average for other sites
or to the coalition’s scores the previous year and a summary of the coalition’s strengths and weaknesses.
Technical assistants presented these results on site to the
prevention boards, and facilitated discussions about how to
build on strengths and address areas of concern.
Item missingness for seven variables exceeded 5% (the
highest being 19%, for member age). In addition, although
comparable in some other respects, members who were
missing information on covariates tended to be less active:
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the mean response about the percentage of meetings attended
was 3.20 on the 1–4 scale for individuals with complete
information on all variables, versus 2.95 for omitted cases
(t-value -3.08, 816 df, p \ 0.01). Multiple imputation in
SAS PROC MI reduced the bias due to this pattern of
missingness by using all available information for each case
to insert plausible values for missing data (Schafer 1997).
This also conserved statistical power by retaining all 818
cases in each final regression model. We generated five
imputed files. Very low variance in imputation parameter
estimates indicated that this number of data sets was sufficient to yield stable estimates of imputed values.
The Institutional Review Board at Penn State approved
the data collection process and coalition members signified
informed consent by completing the on-line questionnaire.
Measures
Dependent Variables
One measure corresponded to each aspect of member participation, each based on member recollections relative to
the prior year: meeting attendance (framed in the survey as
1 = less than 25%, 2 = 25–50%, 3 = 50–75%, 4 = 75–
100%), whether or not the member remembered talking in
meetings (1 = yes, 0 = no), the number of hours per month
the individual spent in meetings, and the number of hours
per month spent on coalition activities beyond meetings.
When a member provided the number of hours/month spent
in meetings but left time beyond meetings blank we treated
the time outside meetings as =0 (running the model without
those cases led to the same pattern of results).
Independent Variables
To test hypothesis 1, that opportunities for influence would
be associated with member participation, we used one perceptual scale and two members self reports of their roles in
the coalition. The perceptual scale was calculated as the
mean of responses to three items, concerning how coalition
leadership ‘‘gives praise and recognition at meetings,’’
‘‘intentionally seeks out your views,’’ and ‘‘asks you to assist
with specific tasks’’ (called simply ‘‘board leadership style’’
in Feinberg et al. 2008). The Chronbach’s alpha coefficient
of 0.80 indicated acceptable reliability. The two self-reports
indicated belonging to and chairing committees, respectively (each coded as 1 when true and 0 when not).
Two additional scales were used to test hypothesis 2,
that members would participate more when they perceived
greater coalition process competence. The first scale
addressed the coalition’s board directedness at the strategic
level (Feinberg et al. 2008). This was the mean of four
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Am J Community Psychol (2008) 42:94–104
perceptual items: ‘‘The [coalition] Prevention has …
agreed on how it will govern itself, make decisions, and
clarify the roles of members; developed clear goals and
objectives; identified, and is building upon, individual and
community strengths; explored financing and resource
development strategies to support new efforts’’ (a = 0.85)
(Feinberg et al. 2008). The second scale used to test
hypothesis 2 characterized meeting effectiveness through
three items: ‘‘There’s a lot of time wasted because of
inefficiencies (reverse coded)’’; ‘‘This is a highly efficient,
work-oriented team’’; and ‘‘Team members work very
hard’’ (a = 0.77).
In addition to the theoretical predictors, we included as
controls one coalition-level attribute, the age in years, and
several individual level attributes, all from the member
survey: member age, sex, race/ethnicity (which the survey
had framed in terms of black, Asian, Native American, or
Hispanic, with the referent group being non-Hispanic
white), coalition tenure in years, whether or not the
member had a bachelor’s degree or higher, and whether or
not participating as a ‘‘concerned citizen’’ rather than an
agency representative. Thus the only coalition level measure was coalition age. The Prevention Research Center did
not ask members about their sexual orientation, disability
status, or income.
Data Analyses
Although there was fairly high agreement among members
about leader style and coalition process competence (mean
RWG index indicating within-coalition agreement =0.81
for leader style, 0.78 for board directedness, and 0.71 for
perceived meeting effectiveness, on a 0–1 scale (James
et al. 1984)) coalition-level factors only explained 1–6% of
the variance in study outcomes (Bryk and Raudenbush
1992). We therefore ran the regression models at the
individual level, using generalized linear models to
accommodate the clustering of individuals within coalitions. The link function for each model reflected the nature
of the dependent variable: an ordered logit for meeting
attendance (Agresti 2002), regular logit for whether or not
the member recalled talking in recent meetings, and identity links for the models predicting the two continuous
measures, time in and beyond meetings, respectively. After
imputing five data sets, we used SAS PROC MI ANALYZE to combine the results.
Results
Table 1 lists descriptive statistics for study measures. On
average, respondents indicated having attended at least 75%
of coalition meetings in the previous year (3.07 on a 1–4
Am J Community Psychol (2008) 42:94–104
Table 1 Descriptive statistics
(Original data, prior to multiple
imputation)
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Variable
Mean
STD
Range
Meeting attendance (1–4 scale)
3.07
1.15
1–4
Talking in meetings (1 = yes)
0.93
0.26
0–1
Time spent in meetings per month
4.15 h
4.14 h
0–20
Time beyond meetings per month on coalition activities
6.23 h
13.00 h
0–80
Inclusive board leadership style
5.73
1.14
1–7
Committee member
0.74
0.44
0–1
Committee chair
0.35
0.48
0–1
Board directedness
5.77
1.21
1–7
Meeting effectiveness
5.47
1.24
1–7
Coalition age (n = 79)
4.29 years
1.75 years
2.50–8.75
Member age
46.38 years
10.41 years
14–85 years
Male
0.33
0.47
0–1
Hispanic or nonwhite
0.07
0.25
0–1
Tenure in coalition
3.12 years
2.25 years
1.08–6.44
Member formal education bachelors or above
Private citizen
0.84
0.11
0.37
0.32
0–1
0–1
scale). Over nine out of ten members (93%) reported having
spoken in coalition meetings in the previous year. The mean
time spent in meetings per month was 4.15 h and the mean
time per month spent outside meetings on coalition activities was 6.23 h. There was much less variation in time spent
within meetings (standard deviation = 4.14 h) than on time
spent beyond meetings (standard deviation = 13.00 h). The
mean perceived level of board directedness was 5.77 on a
1–7 scale. Member appraisals of meeting effectiveness were
slightly lower, at 5.47, also on a 1–7 scale. The mean
member perception of how encouraging their leaders’ style
was 5.73 out of 7. Three quarters (74%) of respondents had
served as committee members during the past year and over
a third (35%) reported having chaired committees.
The mean coalition age at the beginning of 2004 was
4.29 years, reflecting the relative recency of the Communities That Care rollout from its initial cohort of 21
coalitions to 115. However, this may understate how long
some individuals and agencies within coalitions had
worked together, given the tendency for community organizations to cooperate under multiple auspices over time.
The average coalition member was 46 years old, female
(67% of members), and white (only 7% of members
reported race/ethnicity as Hispanic or nonwhite). The mean
reported coalition tenure was 3.12 years. The vast majority
(84%) had a bachelor’s degree or higher formal education.
Only 11% were participating as private citizens rather than
representing organizations.
Table 2 shows final model results. There was partial
support for the first hypothesis, that coalition members
would participate more when they had more opportunities
for influence. Members who perceived more inclusive
styles of board leadership were significantly more likely to
report having attended a higher percentage of meetings in
the previous year (OR = 1.361, p \ 0.001) and to have
spent more time beyond meetings on coalition business
(with a 1 point difference on the 7 point scale assessing
leaders’ style being associated with 1.725 more reported
hours per month spent, p \ 0.01).
Both belonging to and chairing committees or other
subgroups were also positively associated with members’
reported participation. Members who belonged to coalition
committees were more likely to attend a higher percentage of
meetings than were non-committee members (OR = 2.646,
p \ 0.001), to talk in meetings (OR = 3.661), and spend
more time in those meetings (an additional hour per month
(1.102), all else being equal, p \ 0.01). There was no association, however, between committee membership and
amount of time on coalition activities beyond meetings.
Committee chairs were more likely to report attending a
higher percentage of meetings than were non-chairs
(OR = 2.685, p \ 0.001), were more likely to talk
(OR = 6.047, p \ 0.05), spent almost two more hours per
month in meetings than non-chairs (1.856, p \ 0.001), and
also devoted almost five more hours per month beyond
meetings to coalition business (4.693, p \ 0.001).
There was no support for the second hypothesis, that
coalition members would participate more when they
perceived greater process competence. Neither board
directedness nor meeting effectiveness was associated with
members’ self-reported participation in or beyond coalition
meetings.
There were scattered associations between member
attributes included as controls and participation. Members
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0.173**
0.416
Intercept2
Intercept3
0.144
0.059
0.024
1.205
0.503
0.210
0.762
0.099
2.646***
2.685***
Committee member
Committee chair
1.844
1.873
1.162
3.909
3.739
1.593
6.047*
3.661***
1.294
0.825
0.559*
1.084
0.990
0.671
Member age
Male
Hispanic or nonwhite
Tenure in coalition
Bachelors or above
Private citizen
*** p \ 0.001
** p \ 0.01
* p \ 0.05
0.889*
1.007
Controls
Coalition age
0.966
1.004
Board directedness
Meeting effectiveness
0.428
0.614
0.997
0.327
0.582
0.992
0.819
0.849
0.830
1.052
1.594
1.178
0.954
1.171
1.023
0.964
1.187
1.124
1.149
1.416
1.047
1.175
0.851
1.033*
0.842*
0.824
1.009
H2: Coalition process competence will be associated with higher levels of participation
1.361***
Inclusive board leadership style
0.444
0.635
0.868
0.400
0.451
1.004
0.725
0.572
2.970
3.162
1.262
3.445
1.603
1.064
0.977
1.186
1.352
30.847
1.185
0.754
7.037
1.813
5.851
1.904
0.923
H1: Greater opportunities for influence will be associated with higher levels of participation
0.072***
95% CI
Odds ratio
Odds ratio
95% CI
Talked in meetings (Binary)
% meetings attended (Ordinal)
Intercept1
Parameter
Table 2 Generalized linear models of coalition attributes and participation levels
0.730
-1.068
0.095
1.367*
-0.627*
0.005
-0.151
-0.023
0.001
1.856***
1.102**
0.326
1.769
Coefficient
-0.175
-2.226
-0.068
0.232
-1.244
-0.030
-0.317
-0.324
-0.314
1.184
0.351
-0.086
-0.373
95% CI
1.635
0.090
0.259
2.502
-0.010
0.040
0.015
0.277
0.315
2.527
1.853
0.738
3.910
Time in meetings (Continuous)
0.050
-1.677
0.183
2.618
-2.319*
-0.024
-0.128
-0.047
-0.488
4.693***
0.331
1.725**
0.324
Coefficient
-2.909
-4.707
-0.282
-0.990
-4.307
-0.141
-0.631
-1.010
-1.455
2.590
-1.992
0.748
-7.508
95% CI
3.008
1.354
0.648
6.227
-0.331
0.092
0.375
0.915
0.480
6.796
2.653
2.702
8.155
Time beyond meetings (Continuous)
100
Am J Community Psychol (2008) 42:94–104
Am J Community Psychol (2008) 42:94–104
of older coalitions were less likely to report having attended a higher percentage of meetings (OR = 0.889,
p \ 0.05) or having talked in those meetings (OR = 0.842,
p \ 0.05). Conversely older members were more likely
than younger members to report having talked in meetings
(OR = 1.033, p \ 0.05). In keeping with previous research
on volunteering (Obradovic and Masten 2007), male coalition members reported spending about a half an hour less
per month in meetings (-0.627, p \ 0.05) and over 2 h
less per month outside meetings (-2.319, p \ 0.05). Hispanic and nonwhite coalition members were less likely to
attend a high percentage of meetings (OR = 0.559,
p \ 0.05) but also spent over an hour more per month in
meetings than did Non-Hispanic white members (1.367,
p \ 0.05). Individuals’ coalition tenure, possession of a
college degree or higher, and status as private citizens
versus agency representatives were all unrelated to all
forms of coalition participation in this sample.
Discussion
Inferences from any non-experimental study are inherently
speculative. Nonetheless, based on our interpretation of
results from the current sample, we offer below what we
believe are some useful implications for coalition leaders
and funders.
Findings from this study are congruent with the intuitive
notions that people do more when they believe they can
personally influence events and when they feel appreciated
for doing so. Both perceptions of leader style and committee roles were associated with higher participation
levels within and beyond meetings. The leadership style
finding suggests that coalition leaders can foster higher
participation by showing a general appreciation for member contributions and by asking people individually for that
help. Being on committees may also enable members to
build interpersonal ties and learn more about coalitions in
the relative safety of smaller groups. This may improve
socialization by providing opportunities to ask questions
that people would hesitate to ask in larger group contexts,
thus supporting more active (and potentially more effective) participation.
From a policy perspective, this study’s central finding
raises the issues of how to select leaders who are actively
inclusive as well as how to cultivate these skills and attitudes in existing leaders. There is some previous evidence
that public health departments are particularly good at
practicing ‘‘the politics of inclusion’’ (Fleishman et al.
1992, p. 554; Wells et al. 2004), although they can also be
hindered by their governmental context and an attendant
rule-bound culture (Kramer et al. 2005). A recent coalition
study found that community-based organizational
101
leadership was associated with lower member reports of
some aspects of effectiveness, which the authors speculated
might be due to the fact that such organizations may not
have had sufficiently broad networks (Kramer et al. 2005).
Coalition leaders and sponsors might best identify lead
agencies in terms of how extensive their networks are
relative to the coalition’s mission. For instance, a community-based organization focusing on violence prevention
might have better networks for a violence prevention
coalition than the public health department. On the other
hand, a public health department might be the best lead
agency for a coalition emphasizing early disease screening.
Most consultants probably believe that they already train
toward an inclusive leadership style, and most coalition
leaders undoubtedly share this norm. In a previous study,
however, we found that coalition leaders were not always
perceived by rank-and-file members to be as inclusive as
they perceived themselves to be (Wells et al. 2004). It may
therefore be useful to survey all members about how much
opportunity they perceive to influence the coalition’s work.
Depending on the dynamics within a coalition, this might
best be accomplished through a group discussion, small
group or one-to-one discussions, and/or an anonymous
survey. It will be particularly important to solicit the views
of less active members.
Although it is not surprising that people with committee
member roles were generally more active than other
members, only the people chairing committees spent
above-average time beyond meetings on coalition activities. This may in part be an artifact of how active members
in this sample were, who reported spending on average
almost a day a month outside coalitions meetings on coalition business. When coalitions need more member time
investment, however, forming temporary work groups to
accomplish specific tasks might be a way to increase the
participation of some additional members. Individuals who
cannot make multi-year commitments may be willing to
chair groups that have such limited time horizons.
Empirically the current study provides useful nuance to
the empowerment perspective on coalitions by finding that
opportunities for influence rather than process competence
may be key to encouraging participation. These findings
suggest the importance of distinguishing among facets of
leadership. Metzger et al. (2005), for instance, measured
coalition member perceptions of leadership through a 14item scale including items reflecting how actively they
included members as well as strategic and tactical process
competence. Although this combined scale was associated
with participation, the authors may have found differential
results across subscales if they had separately measured
distinct aspects of leadership behaviors.
At the same time, this study’s findings may have contributed to the identification of commonalities in what a
123
102
recent review has criticized as a conceptually fragmented
literature (Zakocs and Edwards 2006), despite admittedly
partial measures of the constructs of interest. Those authors
noted that leadership style had been measured in five different ways across empirical studies: incentive management,
empowerment, shared leadership, task-focus, and multiple
characteristics. Tracing our conceptual foundation back to
Knoke’s (1988) framework of collective action organizations, with its basis in exchange theory, through previous
coalition research (Prestby et al. 1990), we argue that
incentive management is an appropriate overarching construct for understanding why people participate in coalitions.
In turn, empowerment and shared leadership are two facets
of inclusivity that provide members with incentives to participate actively. Greater task focus is likely to better align
coalition activities with member goals, thus enhancing their
incentive to participate.
The lack of associations between coalition members’
perceptions of board directedness and meeting effectiveness with their participation does not mean that process
competence does not matter. An early model of team
effectiveness offers another perspective on the potential
role of process competence in fostering coalition effectiveness. Hackman and Morris (1975) posited that group
synergies could increase the positive effects of group
incentives to participate. However, unlike Lasker and
Weiss (2003) and the current study’s second hypothesis,
Hackman and Morris suggested that process competence
might have a moderating rather than a direct effect on
member participation. Such exploration is beyond the
scope of the current study but illustrates another potential
way that process competence may relate to member participation and coalition effectiveness.
Limitations
This study had some limitations worth noting. Contacting
only the most active 25 individuals in larger coalitions
yielded a sample that over-represented active members.
The 54% response rate also makes it likely that there was
substantial self selection bias, with more active members
being more likely than others to complete the questionnaire. Previous studies suggest that active members may
differ from less active members in both background attributes and perceptions of benefits and costs of participation
(Norton et al. 1993; Obradovic and Masten 2007; Perkins
et al. 1990; Prestby et al. 1990). Thus, inferences from
study findings about how leaders may involve less active
members remain speculative until further research tests
associations for all coalition members. However, the study
sample did include the members of the most concern to
leaders, that is, those who have already shown the most
interest in contributing to coalition activities. The fact that
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Am J Community Psychol (2008) 42:94–104
there was variation in the level of participation in this
sample comprised largely of active members makes the
study a conservative test of our hypotheses. In other words,
we would likely find more variation in a broader sample
and potentially greater effect sizes.
We also did not examine what affected whether or not
people joined coalitions in the first place. This is a critical
issue, given that coalitions are supposed to be grassroots,
voluntary organizations that broadly represent their communities but in reality are often comprised primarily of
health and social service agency employees who participate
as additional duties. Another important issue we did not
have the data to address was that of participation costs to
members (Chinman and Wandersman 1999). Finally, all the
coalitions in the current study sample were in Pennsylvania
and most were fairly young. Although these coalitions were
located in a range of rural, suburban, and urban locations, it
is possible that some dynamics affecting their participation
may not generalize nationally or to more mature coalitions.
Conclusion
Despite a growing empirical literature on coalition success
factors (Giamartino and Wandersman 1983; Hays et al.
2000; Kegler et al. 1998; Prestby and Wandersman 1985;
Rogers et al. 1993), there has been very little evidence
about exactly how coalitions can foster greater member
participation. The current study has addressed at least part
of this gap, indicating that opportunities for influence may
affect participation more than how competent leaders are at
either strategic or tactical levels. More actively soliciting
and rewarding member participation will take time and
energy from very busy coalition leaders. The good news is
that they may thereby better share the hard work of
translating often ambitious public health goals into reality.
Acknowledgement This research is supported by R03 CA11314101 National Cancer Institute.
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Am J Community Psychol (2009) 44:213–220
DOI 10.1007/s10464-009-9266-4
ORIGINAL PAPER
Introduction to Special Issue on Social Ecological Approaches
to Community Health Research and Action
David William Lounsbury Æ Shannon Gwin Mitchell
Published online: 24 September 2009
Ó Springer Science+Business Media, LLC 2009
Abstract We have the potential to make new, substantive
contributions to resolving our most pressing community
health problems. However, to do so we must adopt a philosophy of science that is directed towards understanding
the dynamic complexity and full contextual reality surrounding these issues. A social ecological approach to
science is ideally suited to this challenge. This framework
is systems-oriented and defines research problems in terms
of structures and processes, generating research outcomes
that give insight into the dynamic interaction of individuals
with their environment across time and space. Though
community psychology is built upon social ecological
principles, researchers from other disciplines have also
noted its utility and implemented interventions based on
this framework. In our introductory article to this special
issue on social ecological approaches to community health
research and action, we present a brief review of the theoretical foundations of the social ecological approach,
present highlights from our selected manuscripts, and
conclude with some reflections about the need to build
further capacity to conduct effective social ecological
research to foster community health and well-being.
Keywords Social ecological
Community health

Research and action
D. W. Lounsbury (&)
Department of Epidemiology and Population Health, Albert
Einstein College of Medicine, Moses Campus, 3300 Kossuth
Avenue, Bronx, NY 10467, USA
e-mail: david.lounsbury@einstein.yu.edu
S. G. Mitchell
Friends Research Institute, 1040 Park Avenue, Suite 103,
Baltimore, MD 21201, USA
e-mail: sgwinmitchell@hotmail.com
Introduction
We have the potential to make new, substantive contributions to resolving our most pressing community health
problems. However, to do so we must adopt a philosophy
of science that is directed towards understanding the
dynamic complexity and full contextual reality surrounding
these issues. While we enjoy an unprecedented rate of
scientific discovery and a seemingly infinite, immediate
capacity to share ideas and opinions, our ability to clearly
see ‘the big picture’ and to effectively collaborate to
address our most complicated problems (e.g., global
warming, epidemics, economic instability and poverty)
remains limited.
Social ecological research and interventions are ideal for
addressing these types of community health-related issues.
A social ecological approach is systems-oriented and
defines research problems in terms of structures and processes, generating research outcomes that give insight into
the dynamic interaction of individuals with their environment across time and space.
The Community Health Interest Group of the Society
for Community Research and Action (SCRA) has been
discussing various ways in which we, as community
psychologists, apply the social ecological framework to
our community health research endeavors in an attempt
to account for the diverse forces affecting health. We
tend to hold both the theories and the methods we use as
central to our identity as community psychologists,
though in our conversations we are forced to acknowledge the fact that we often work within multi-disciplinary settings, alongside other researchers who are equally
wedded to the social ecological framework for investigating and addressing complex health needs in the
community.
123
214
This recognition of multidisciplinary efforts was the
genesis for this special series of articles on social ecological
approaches to community health research and action, an
activity that would serve multiple purposes for our interest
group. First, it created a specific, goal-focused activity that
would take our discussion of social ecological health
research to a more refined level. Second, it was an opportunity to comparatively examine how researchers across a
variety of fields weave the thread of social ecological theory
throughout their work. Finally, it was a shameless attempt to
draw more ‘community-minded’ researchers into the field of
community psychology. This last purpose was achieved via
the inclusion of numerous authors who had not previously
published within the field, and by inviting the authors whose
work is presented in this special issue to present in a series of
symposia on the topic at the 12th Biennial Meeting of SCRA
held in Montclair, New Jersey in June 2009. From our perspective, we were successful on all counts.
Social Ecological Health Research: A Timely Topic
The utility of social ecological research has received
increased attention in recent years from diverse communities
of scientists. Notably, the National Institutes of Health (NIH)
Office of Behavioral and Social Science Research (OBSSR)
and the Centers for Disease Control and Prevention (CDC)
have called for health research that links transdisciplinary
models in biomedical science (i.e., molecular and physiological causal mechanistic science) with social ecological
models that use ‘systems methodologies’ (e.g., social networking, complex adaptive systems analysis, system
dynamics modeling) to understand multi-level effects on
health outcomes (Mabry et al. 2008). In their strategic prospectus, OBSSR identifies six ecologic-centered domains,
namely: (1) gene-environment interactions; (2) environmental effects on physiology; (3) technology, measurement,
and methodology; (4) social integration and social capital;
(5) complex adaptive systems; and (6) social movements and
policy change. New research in these domains is expected to
inform innovative strategies that can foster multi-level
change and improve population health.
In this article, we present a brief review of the theoretical foundations of the social ecological approach in
community research and action, present highlights from
our selected manuscripts, and conclude with some reflections on the need to build further capacity to conduct
effective social ecological research in order to foster
community health and well-being.
Theoretical Foundations of an Ecological Paradigm
Social ecological models are not new to public health or to
socio-behavioral science (Darling 2007; McLeroy et al.
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Am J Community Psychol (2009) 44:213–220
1988; Trickett 2009). In community psychology, an ecological perspective on human behavior was a founding
tenet of the field (Martin et al. 2004) and our current
conceptualizations stem from the rich theoretical foundations built by such luminaries as Lewin (1936), Barker
(1964a, b), Barker and Schoggen (1973a), James Kelly
(1966), Sarason (1972), Watzlawick et al. (1974), Bronfenbrenner (1977, 1979, 1999), and Weick (1984). Each
made major, complementary contributions as they added
different perspectives or dimensions to our notion of social
ecology, dimensions such as how we define social ecology,
ways in which settings influence behaviors, and the
dynamic processes of systems change.
Defining Context in Social Ecology
Barker and his colleagues focused their research on the
ecological environment, which they defined as ‘‘naturally
occurring phenomena: (1) outside a person’s skin, (2) with
which his molar actions are coupled, but (3) which function
according to laws that are incommensurate with the laws
that govern his molar behavior’’ (Barker 1964a, p. 5).
Barker described the need to delineate a scope of reference
wide enough to capture sufficient context to allow a
meaningful assessment of a specified behavior. ‘Ecological
units’ comprise the setting, which could be physical, social,
biological, or behavioral. Good ecological research is
explicit in selecting its units of interest. A valid ecological
unit is: (1) self-generated (i.e., occurring naturally without
involvement of the investigator), (2) given a specific time–
space locus, and (3) internally constrained (i.e., has internal
forces that impose patterns on their own internal components). An atom, a person, a family, a classroom, and a
town are each examples of possible ecological units of
analysis.
Sarason’s (1972) work on creation of settings, which he
presented as a marker of social change as well as a strategy
to promote social change, further adds to our understanding
of context. Sarason’s settings are organizations of people,
two or more, and can include something as personal as a
marriage or as public as a political revolution. Without
fully appreciating a setting’s history, efforts to transform it
or to build a new one may unwittingly fail.
The principles of social systems proposed by community psychologist, Kelly (1966), are analogous to biological
eco-systems. Kelly identified four key principles of ecology. The first is interdependence, which refers to structural
characteristics, whereby a change in one component of a
system affects all other components of the system. This
concept reflects the reciprocal or mutual influence among
components that occurs over time. The second is cycling of
resources, which refers to the use and distribution of
resources within an eco-system. Environmental biologists
Am J Community Psychol (2009) 44:213–220
would point to the food chain as one example of the cycling
of resources, but an equally good social example would be
economics and how money flows from one person to
another in exchange for goods and services. The third
principle is adaptation, the process by which individuals
and communities effectively use (or reuse) resources, such
as how they change or respond to accommodate a new
situation. The last principle is that of succession. Succession is a special case of cycling of resources. Whereas
cycling of resources helps us understand the movement of
resources into and out of a community, succession refers to
the movement of people themselves into and out of a
community. Another way of describing the process of
succession could be cycling of populations. Succession
tends to be characterized as a long-term process, one within
which changes occur from one generation to another, and it
is often the collective result of adaptation. These four
principles represent processes and structures that define the
dynamic complexity with an eco-system.
Influence of Settings on Behaviors (and Vice Versa)
Lewin (1936) was an early adopter of the ecological perspective. He endorsed an interactionist concept for understanding how behavior is shaped through processes of
nature and nuture, which he summarized in the formula
B = f(P|E), ‘Behavior is a function of Person and Environment.’ As a scientist and a European Jew who witnessed
firsthand the rise of Nazi Germany, he pondered the
capacity for inhumanity among ordinary people. The
problem, he argued, was the social environment and the
behavior it enabled among those who lived in that place
and time (Lewin 1935). Lewin’s formula is a highly
aggregated social ecological model. The constructs of
‘person’, ‘environment’, and ‘behavior’ are not well
defined, but the concept that individuals are shaped by their
environment is clear, and this is Lewin’s main point.
Subsequent theorists have continued to elaborate on
Lewin’s basic model.
Urie Bronfenbrenner, a student of Lewin’s, is probably
most often credited for ecological theorizing, and his work
is widely cited whenever the topic of social ecology is
evoked. Bronfenbrenner (1979) applied a contextual
approach to studying human development, yielding ecological systems theory, which is often summarized with a
figure composed of concentric circles representing four
types of systems: the microsystem (e.g., the home or
classroom of a child); the mesosystem (two interacting
microsystems; e.g., the effect of the home on the classroom); the exosystem (external environments which indirectly influence development, e.g., the mother’s place of
work); and the macrosystem (the larger socio-economiccultural context). Contained within each of these systems is
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the individual (e.g., the child of focus). A fifth system that
incorporated the notion of succession came later. Bronfenbrenner referred to it as the ‘chronosystem’, the patterning of environmental events and transitions over the
life course, as well as socio-historical circumstances
(Santock 2007).
Ecological systems theory treats individuals as active
agents who constantly shape, and are shaped by, their
environments. Like behavior setting theory, ecological
systems theory attends to the way that roles, norms and
rules shape behavior, with the objective of understanding
developmental processes (Bronfenbrenner 1977, 1979).
Bronfenbrenner emphasized the underlying utility of
studying behavior as it unfolds in a natural environment, as
opposed to a contrived laboratory, where behavior was
recorded as an outcome of a controlled setting.
Perception played an important role in Bronfenbrenner’s
theory. He embraced phenomenology and the importance
of perceptual factors in understanding behavior and human
development. How one perceives his or her situation
explains behavior motivations. Individual differences
should not be ignored, as observational work demonstrated
that different environments invoke different behaviors
from different people (Bronfenbrenner 1999). Identifying
and analyzing patterns of behavior was key to understanding developmental outcomes (Bronfenbrenner 1961).
For example, pattern analyses could explain why the same
systems generated different outcomes for boys relative to
girls.
Barker, also a student of Lewin’s, developed behavior
setting theory to explain how settings generate ‘forces’
necessary for their own maintenance and survival. These
forces regulate behavior in the setting. Barker and Schoggen (1973b) used the term ‘circuits’ to underscore the
notion of a constant feedback that would be experienced
between person and setting. First there are program circuits, which are expected behavior patterns based on particular agendas. These circuits differentiate one setting
from another. Second are the goal circuits, which refer to
the intrinsic purpose of the setting. Deviant-countering
circuits, forces which eliminate or reduce deviance from
behavior settings, are the third type of setting force defined
by Barker. Finally, there are the veto (ejection) circuits
which account for the way that a setting is able to jettison a
non-conforming member. If a person reaches a particular
threshold of person-setting incongruity, they are literally
forced away. In short, behavior setting theory identifies
structures and processes that interact to control or explain
behavior, within a given ecological context. The theory
also provides a rigorous method for describing and
assessing human behavior at any ecological level, including
the community level (Barker and Schoggen 1973b). The
approach used to conduct behavior setting assessments,
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however, involves resource-intensive observational data
collection and categorizing.
The Dynamics of Systems Change
From a social ecological perspective, change is quite literally part of the process. Sarason’s (1972) study of creating new settings is ultimately understood as a strategy for
introducing innovation and renewal into our social and
physical ecologies. As needs change, or as the players in
the setting change (such as with Kelly’s concept of succession) the setting itself can be modified. Additionally,
Barker and colleagues’ in their concept of ‘circuits’ include
a systems-oriented component in their social ecological
model by adding a way to identify patterns of behavior
over time so as to assess dynamic change.
From an ecological perspective, we need ways of conceptualizing and researching how things change and how
they may also stay the same (i.e., be sustained or persist).
Paul Watzlawick has written about a theory of persistence
and change as a means to studying clinical problem formation and problem resolution (Watzlawick et al. 1974).
Watzlawick defines two types of change. First-order
change is change that occurs within a given system, which
itself remains unchanged, or when a condition (i.e., a
particular need or symptom) is addressed but there is no
modification of the system as a whole. The existing
structures or processes that make up the system remain the
same. Second-order change is change that occurs when a
fundamental modification is made to the system, when a
new structure or process is added to an existing system.
Waltzlawick calls this type of change ‘change in change’.
We can think of first-order and second-order change in
terms of ecological levels of change. First-order change is
change that occurs within the confines of a Barkerian
‘ecological unit’. Second-order change is change that
occurs as a function of an outside, environmental impact.
These definitions of change have profound implications
for social ecological research. Within the context of a
particular ecological unit, for example a hospital or a
school or some other setting, a problem of concern may
persist due to multiple, ineffective ‘first-order’ changes. By
stepping back and seeing the environment containing the
hospital or school, transformative strategies that create
‘second-order’ change are now visible. When we invoke a
second-order change, we are studying the impact of
structural interventions, which are often equivalent to
attempting change at the community level or higher,
changing circumstance for multiple stakeholders. Secondorder change is relevant to studies of natural disasters and
other large-scale catastrophes (Lovett 1979).
However, in order to affect large change, big initiatives
are not always necessarily required. Weick’s (1984)
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Am J Community Psychol (2009) 44:213–220
promotion of the notion of ‘small wins’ is implicitly
a social ecological construct. Here, big problems are
addressed through the cumulative effect of many, tiny
contributions from many individuals over time. A small
wins approach may be an effective way to put into place
policies that can eventually reverse major problems, such
as HIV transmission. The key is to motivate small changes
in individual behavior that are easy for everyone to make,
which in turn would produce overall significant effects. As
people recognize these small wins further behavioral
change can be promoted, and so on. In this way, a small
wins strategy recasts large social problems into smaller,
less burdensome or more appealing ones. Small wins
capitalizes on a reinforcing process that begets more of the
desired action which, over time, can generate substantive
improvements in the problem.
Social ecological models also allow (and require)
researchers to work with more complexity and added
context. For example, Glass and McAtee (2006) have
developed a social ecological model that facilitates the
study of several logical, but understudied assumptions
about health behavior problems. These assumptions
include that: (1) a single cause of a specified health problem is unlikely; (2) problems are likely to be effected by
combinations of factors at multiple levels of influence; (3)
small changes in one or more key factors may, over time,
generate large and potentially non-linear influences on the
health problem; and (4) both socio-environmental and
biological processes are involved in the expression of any
given individual’s behavior. This comprehensive model
can be used to stimulate social ecological research about
virtually any health-related problem or intervention.
Overview of Selected Social Ecological Health Papers
The works selected for this special issue are diverse in
purpose, context, questions posed and methods used, but
each article applied a social ecological approach to address
a salient problem in community health. A review of these
manuscripts revealed a number of commonalities, which
we assess below.
Relationships Between/Among Ecologic Levels
All fourteen works examined relationships between/among
multiple ecologic levels. The typical study presented in this
special issue incorporated three levels of analysis, with all
manuscripts including reference to the individual level.
A level of analysis was most often defined as a specific
type of setting, such as in Kloos and Shah’s article on the
impact of housing and neighborhood settings on persons
with serious and persistent mental illnesses. They
Am J Community Psychol (2009) 44:213–220
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examined how physical aspects of housing and neighborhoods, social environment of neighborhoods, and interpersonal relationships tied to housing allowed for
identification of opportunities for health promotion and
facilitation of participation in community-based settings.
Freedman identified ‘local food environments’ as an
important level of analysis with which to understand dietary health behaviors. Results of her study showed that
characteristics of neighborhood food stores were associated
with social hierarchies of race, class, and gender, as well as
environment. She discusses the utility of a social ecological
approach to unraveling the politics of space.
Other manuscripts defined a level of analysis in terms of
a social institution, such as ‘the media’ or ‘higher education’. DeBate, Baldwin, Thompson, and colleagues assessed
the effectiveness of a school-based intervention to promote
physical activity among adolescents and found that the
media served as an important linking structure between
schools, families, and the community. Similarly, in her
article on the potential utility of educational benefits for
today’s returning U.S. veterans, Smith-Osborne argues that
the institution of higher education can play an important
role in helping persons adapt to civilian life, including those
with service-connected impairments and disabilities.
One of the selected manuscripts included a sub-individual level (i.e., the genetic level). In her article on
childhood obesity, Lytle presents results of baseline data
from a sample of youth and parents. She used a longitudinal design to develop a dynamic, multi-level perspective
on a child’s home, school and community, linked to
hypothesized biological and genetic factors. Her study
procedures included a youth blood draw for the purpose of
assessing biogenetic correlates of obesity in children. Such
studies fit the comprehensive ecological framework for
public health research by Glass and McAtee (2006).
Wicke and Silver examined the community-level impact
of a single violent event, charting a process of adapting to
the storm of negative media and unwanted attention in a
Southeast Texas town. They found that specific local social
institutions played an important role in helping the community’s residents find constructive ways of adjusting to
these pressures, over time.
Hovmand and Ford present a community-level model of
domestic violence cases moving through a criminal justice
response. They use an innovative method, system dynamics
modeling, to evaluate the impact of implementing three
interventions—namely mandatory arrest, victim advocacy,
and changes in level of cooperation—on two system-level
outcomes: improving offender accountability and increasing victim safety. Their model’s simulations illustrate the
complex nature of interdependent relationships. Hoffer,
Bobashev and Morris also present a community-level
model to build a deeper understanding of the dynamics of
operation, organization, and structure of a local heroin
market. They used agent-based modeling to simulate the
behaviors of customers, private dealers, street-sellers,
brokers, and the police to examine aggregated patterns of
behavior and outcomes over time. Their model is a compelling illustration of the principles of cycling of resources
and interdependence.
Finn, Bishop and Sparrow present a dynamic process
model of GROW—a mutual help organization for mental
health—which examined its impact at the group level,
GROW program/community level, and at the individual
level. They use GROW findings to assist with the development of a dynamic multi-dimensional process model to
explain how mutual help groups can promote positive
change. The use of feedback, as an ecological means of
understanding change and as a therapeutic device to promote change, is carefully examined.
Dynamics of Change
Multiple Methods
All manuscripts explicitly or implicitly described or
assessed how, for example, individuals, families, and
communities change over time. Kelly’s principles of systems were evident in selected works. Diverse conceptualizations and methods were used to do so, as noted in the
following works:
Ta, Marshall, Kaufman, Loomis, Casteel, and Land
studied the dynamics of succession using an innovative,
area-based approach to assess socioeconomic factors
associated with the presence of workplaces belonging to
industries reported to be at high risk for worker homicide.
They found that the relationship between human/economic
capital and block group proportion of high risk industry
workplaces was modified by indicators of transience/
instability.
All manuscripts applied multiple methods (e.g., survey,
archival/secondary data analyses, GIS coding, focus
groups, key informant interviews) in their analytic
approach. Notably, we found that nearly all manuscripts
(85%, n = 12) used a least one qualitative method for data
collection and analysis.
A study by Chilenski and Greenberg was used to
develop a multiple-method measurement strategy to
examine associations among community risks, resources,
and rates of early adolescent substance use and delinquency in 28 rural and small town communities. Measures
included five domains of community risk, four domains of
community resources, and population rates of early adolescent substance use and delinquency. Methods combined
correlational techniques, Geographic Information Systems
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(GIS) coding, survey, and in-depth qualitative interviewing. Results of Chelinski and Greenberg’s study showed
that several measures of context were significantly associated with community rates of adolescent substance use
and delinquency, and different risks and resources appear
important for different outcomes, underscoring the need for
mixed methods of data collection and analysis.
Most articles reported using a collaborative research
strategy, either an academic-community partnership or
some form of participatory method, to engage stakeholders,
validate outcomes, and/or sustain involvement. For example, the manuscript by Umemoto, Baker, Helm, Miao,
Goebert, and Hishinuma illustrates the role of both a
partnership with a university and applied principles of
community-based participatory research (CBPR) in promoting youth violence prevention. These collaborative
approaches to research fostered relationships with diverse
community stakeholders, such that health interventions are
durable and long-lasting.
Similarly, in their study of the process of implementing
a health education curriculum in selected Canadian high
school settings, Wharf Higgins, Begoray and MacDonald
used a participatory design to build an understanding of
health literacy, develop research questions, select data
collection strategies, and interpret findings. They describe
how applying principles of CBPR fostered more valid,
efficient research, as it helped manage the complexities of
engaging and navigating diverse school settings. Baffour
and Chonody also applied principles of CBPR to examine
participants’ definitions of infant mortality, views on the
community impact of infant mortality, and strengths and
vulnerabilities in the health care service delivery system.
Qualitative methods combined with CBPR elicited personal narratives that helped these researchers articulate
complexities about the impact of structural, macro-systemic forces on the personal lives of individuals and families in specific neighborhood settings.
Multi-disciplinary
We also found that half of the manuscripts described
research teams that included two or more types of expertise, drawing from diverse disciplines (i.e., psychology,
anthropology, urban planning, social work, engineering,
psychiatry, nursing, education, criminal justice, epidemiology and/or public health). For example, Lytle incorporated feedback from a team of scientists with expertise in
urban planning, exercise physiology, nutrition, epidemiology, physiologists, and psychology in their study of
childhood obesity. Similarly, Ta et al.’s analytic model of
industries at high risk for violence in the workplace was the
product of collaborative input from researchers in epidemiology, public health and sociology.
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Order of This Special Issue
The fourteen manuscripts encompassing this special issue on
social ecological approaches to community health research
and action can be broadly organized into three substantive
themes: understanding and preventing violence in the community; implementing community-focused mental health
and substance abuse interventions; and promoting individual
health and designing healthy environments. These three
categories are used to order the presentation of the manuscripts included in this special issue, as follows:
Understanding and Preventing Violence
in the Community
We begin with the school-based violence prevention program by Umemoto and colleagues, followed by Ta et al.’s
assessment of community resilience, Wicke and Silver’s
case study of collective trauma and community adaptation,
Hovmand and Ford’s system dynamics modeling of
domestic violence policies, and finally Hoffer et al.’s
agent-based modeling of drug marketing dynamics.
Implementing Community-focused Mental Health
and Substance Abuse Interventions
Chelinski and Greenberg’s model for assessing community
risks, resources, and rates of early adolescent substance
abuse leads this category, followed by Finn et al.’s GROW
intervention, Kloos and Shah’s housing for persons with
severe mental illness, and Smith-Osborne’s assessment of
returning veteran’s use of education benefits and mental
health needs.
Promoting Individual Health and Designing Healthy
Environments
The etiology of childhood obesity and the IDEA project by
Lytle is presented first, followed by Debate et al.’s
implementation of VERBTM, a community-based physical
activity intervention for ‘tweens’ and Wharf Higgins
et al.’s work on implementing a health literacy curriculum
for 10th graders in Canadian high schools. Balfour and
Chonody’s study of understanding health disparities from
the perspective of African American mothers is featured
next. The final manuscript featured is Freedman’s study of
local food environments.
Conclusion
Via this introductory article to the special issue on social
ecological approaches to community health research and
Am J Community Psychol (2009) 44:213–220
action, we have provided a brief review of the theoretical
foundations of an ecological paradigm. Lewin’s formula
B = f(P|E) ‘Behavior is a function of Person and Environment’ is the cornerstone to these theoretical foundations. The manuscripts that comprise this special issue
work with this premise in a consistent manner. Future
social ecological research in community health should
explore how individual behavior can, through a cumulative
process, affect the environment. For example, how might
we foster consciousness-raising interventions that motivate
collective action to decrease fossil fuel emissions in a
timely, sustainable manner?
Through the work featured in this special issue we
identified a number of themes that speak to the utility and
the challenges of employing a social ecological approach.
Although social ecological research can facilitate the study
of relationships between and among multiple ecologic
levels and the dynamics of change, to do so well requires a
systems-orientation, one that hypothesizes the role of
structures and processes that contain the problem of study.
However, coming to an adequate conceptualization of these
structures and processes may require a significant investment in exploratory or formative research, as most of the
research presented here included. This may explain the
popularity of qualitative methods used among the works
featured. We assert that the utility of using qualitative
methods to develop a basic understanding of multi-level,
dynamic, interacting structures and processes within an
ecosystem cannot be understated. Arguably, qualitative
methods and data analyses can more easily generate the
contextual data and narrative needed to see the system or
the problem of interest than traditional quantitative methods and analyses alone.
The importance of formative research further underscores the utility of building multi-disciplinary, collaborative research capacities. Such capacities can enable us to
‘see the big picture’ with greater clarity while building the
long-term relationships needed to conduct multi-level
interventions. The role of participatory involvement seems
to be integral to effective social ecological research. The
majority of the work presented in this special issue demonstrated how effective execution of social ecological
health programs required the involvement of multiple
stakeholders, such as families, schools, churches, health
clinics, and other community-based organizations.
Even before such capacities are in place, a social ecological perspective forces different kinds of research
questions, different, that is, from a purely clinical perspective or even a purely public health perspective, where
the focus is almost always exclusively on the individual, or
the patient, and how he or she can be treated, or cured,
or immunized. A social ecological approach demands
careful specification of the relationships among the causal
219
processes operating within and across levels, and across
orders of change. This approach also demands careful
consideration of the unintended consequences of one or
more interventions, in the near or long-term future.
Assessing readiness for change among individuals, their
families, schools, or workplaces is needed (Goodman et al.
1996).
As many of the authors featured here write, a social
ecological approach helped them see what was and was not
within the scope of individuals’, families’, or communities’
control. A productive social ecological intervention can be
used to leverage contextual aspects of the social and
physical environment, taking into consideration individual
biology and preferences (Huang et al. 2009). According to
Glass and McAtee (2006), leverage comes from understanding how ecologic levels are connected by ‘bridges’.
They note that ‘bridges’ between levels act as conduits
between macro-level forces and the local environment,
where behavior ultimately manifests. Cultural norms,
social networks, prices, taxes, access to public transportation, stress or poverty are potentially important ‘bridges’.
Regulations and policies established at various levels in
education, agriculture, transportation, urban development,
communications, and trade from local government to
international bodies (e.g., the World Bank) are also
examples of ‘bridges’.
To summarize, we assert that the problems we face
today will require solutions that yield an understanding of
the dynamic complexity and full contextual reality that
surrounds them. Contemporary research must have the
capacity to help us clearly see ‘the big picture’ and to
effectively collaborate to address our most complicated
problems. We view as a positive step the fact that the social
ecological approach appears to be growing in acceptance
and use among researchers and interventionists in diverse
fields. The popularity of this approach can further link our
field and other disciplines in the health sciences, promote
deeper understanding of each other, and can foster broader
impact of our collective work. As our review of the works
selected for this special issue indicated, this is, in fact, a
marker of good practice. The insights we gain from our
application of a social ecological approach will inform how
we can collaboratively disseminate, implement and sustain
effective interventions and policies in the coming years.
Acknowledgments The authors wish to thank Catherine Kane for
serving as our senior editorial advisor and all those who served as
reviewers of the manuscripts included in this special issue, namely
Holly Angelique, Paul Florin, Chetali Gupta, Richard Jenkins, Sheila
LaHousse, Ralph Levine, Pamela Martin, Jon Miles, Robert Mitchell,
William Neigher, RaeJean Proescholdbell, Heather Schacht Reisinger, Rebecca Rios, Laura Ryniker, Robert Schwartz, Hayley Thompson
and Elisa Weiss. We also wish to thank John Leonard for his expert
copy editing of the entire special issue.
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