EVALUATING THE IMPACT OF COMMUNITY

Running head: EVALUATING THE IMPACT OF COMMUNITY

Evaluating the Impact of Community Coalitions in Rural Areas on

Residents’ Actions and Beliefs about Substance Use: A Case Study

Analysis of Time Series Data

EVALUATING THE IMPACT OF COMMUNITY 1

Abstract

Community coalitions in the United States (U.S.) are composed of

representatives from a cross section of stakeholders and

agencies. In response to recent studies indicating differences in

substance use by young residents living in urban and rural areas,

the Office of National Drug Control Policy (ONDCP) created grants

to support the work of community coalitions. This article

presents results from a case study of one community coalition

situated in a rural area of the U.S. This article also presents a

model used to describe the impact of that coalition and identify

possible relationships between two populations in the community.

Results suggest programs implemented and/or supported by the

coalition reduced the substance use of both young and older

residents. Use of the model further suggests the coalition may

have impacted older residents’ beliefs as well. Implications for

researchers and practitioners in health education and community

coalitions are discussed.

Keywords: community coalition, case study, substance use


Evaluating the Impact of Community Coalitions in Rural Areas on

Residents’ Actions and Beliefs about Substance Use: A Case Study

Analysis of Time Series Data

Community coalitions are composed of representatives from a

cross section of stakeholders and agencies (Butterfoss, 2013;

Butterfoss & Kegler, 2002; Motley et. al., 2013). Although

typically situated within the community itself, these

representatives may also be found outside the area physically

encompassing the community (Butterfoss, 2013). Regardless of

where these representatives are situated, coalitions are created

to assist residents in a community manage a community action or

belief leading to a negative impact (Green, Daniel, & Novick,

2001). Those coalitions created to impact substance use typically

work across agencies through the collaboration of stakeholders to

change programs and policies occurring in the community (Granner

& Sharpe, 2004). Evaluating the impact of these coalitions,

however, is difficult (Butterfoss, 2013; Fawcett et. al., 1997;

Motley, Holmes, Hill, Plumb, & Zoellner, 2013).

Negative Impact of Substance Use on Communities


Researchers often measure the negative impact of substance

use on communities in financial and social terms (CASU, 2011;

Feinstein, Richter, & Foster, 2012; Fettes, Aarons, & Green,

2013; National Drug Intelligence Center [NDIC], 2011). In

financial terms, the NDIC (2011) recently estimated the annual

financial cost of substance use by residents of the United States

(U.S.) community at almost $200 billion. In another example, the

CASU (2011) estimated the financial cost of alcohol use to the

same community by young residents under the age 18 at almost $70

billion. In social terms, Feinstein, Richter, and Foster (2012)

determined residents using tobacco, alcohol, and other substances

were at greater risk to develop physical and mental health issues

later in life. In addition, Fettes, Aaron, and Green (2013)

identified unintended pregnancies, sexual risk taking, poor

academic performance, and delinquency as outcomes associated with

young resident’s substance use.

Using Community Coalitions to Reduce Substance Use in Rural Areas

Borders and Booth (2008) determined rural areas often lack

the social structure to address the negative impact of substance


use. Community coalitions are thought by some researchers as an

effective structure in rural areas to address substance use by

young residents (Dew, Elifson, & Dozier, 2007; Spoth, 2007).

Should this be true, social researchers, practitioners, community

leaders and other stakeholders require practical means for

evaluating the impact of these coalitions (Butterfoss, 2013).

For some time, a number of stakeholders in the U.S. assumed

young residents in rural areas were at less risk to become

substance users (Feinstein, Richter, & Foster, 2012; Gfroerer,

Larson, & Colliver, 2007). Changes in research focus (Spoth,

2007) and national drug policy (Office of National Drug Control

Policy, 1997) at the beginning of this century modified views on

the role of community in rural areas (Borders and Booth, 2007).

In addition, these changes modified views on the importance of

collaboration among stakeholders within rural areas to reduce all

substance use (Center on Addiction and Substance Use [CASU],

2011; Dew, Elifson, & Dozier, 2007; Feinstein, Richter, & Foster,

2012). A recent report by the Substance Abuse and Mental Health

Services Administration, Center for Behavioral Statistics and


Quality (2012) modeled information from over one million

substance users. The authors of the report conclude young

residents from rural areas are as likely to be admitted to a

substance use program as their counterparts from urban areas.

These authors further conclude young residents are at greater

risk to use alcohol or marijuana when living in rural areas than

young residents living in urban areas. Efforts to reduce young

residents’ substance use, therefore, in rural areas may appear

different than efforts in urban areas (CASU, 2011).

Previous researchers have identified personal and contextual

factors associated with substance use (Aarons, Hurlburt, & McCue

Horwitz, 2011; Marsh, Cao, Guerrero, & Shin, 2009). Many

researchers now support the conclusion young residents in rural

areas experience unique lives (Feinstein, Richter, & Foster,

2012; Spoth, 2007). In addition, researchers conclude these lives

put young residents at greater risk to use certain substances

(e.g., alcohol and marijuana). However, efficacy studies of

community coalitions designed to reduce substance use in rural

areas is scarce (Office of National Drug Control Policy [ONDCP],


2012). Most often, researchers use national and regional datasets

to either model use of specific substances (Fettes, Aarons, &

Green, 2013) or compare substance use between urban and rural

areas (CASU, 2011). In the current article, we compiled survey

data from both young and older residents within one rural U.S.

County. We use case study analysis of time series data to

describe the impact of community coalitions in rural areas on

residents’ actions and beliefs. To the best of our knowledge, no

other researchers have compiled and analyzed data in a similar

manner to describe the impact of community coalitions situated in

rural areas.

Community Cognition Model

In this article, we use Bandura’s social cognitive theory

(1986) to create a community cognition model linking young

residents’ action with older residents’ action and belief (see

Figure 1). In our model, we assume only older residents possess

the community capital to create, maintain, and manage community

coalitions. As a result, our model leads us to assume young

residents’ action (i.e., substance use) results from some


combination of older residents’ action (i.e., substance use) and

belief (i.e., value judgment concerning substance use and

health). However, we further assume action and belief of older

residents’ are each influenced by the action of young residents.

Insert Figure 1 about here

Although simple in scope, this model allows us to describe

the impact of community coalitions situated in rural areas and

make suppositions about relationships between resident

populations. Specifically, this model allows us to use results

from our case study to illustrate potential links between young

residents’ substance use with older residents’ substance use and

value judgment concerning substance use and health. Should this

be accurate, the action and belief of representatives within

community coalitions should also impact young residents’

substance use. Evidence to support these links can assist

practitioners working to impact substance use in rural areas and


social researchers working to understand the underlying

mechanisms of community coalitions.

In this article, we first describe a community coalition

situated in a rural area; including goals identified and programs

supported by the coalition. Second, we describe how stakeholders

evaluated the impact of the coalition. Third, we answer the

overarching question: What is the impact of community coalitions

in rural areas on residents’ actions and beliefs about substance

use? Finally, we discuss these results within the context of

literature related to the impact of community coalitions situated

in rural areas.

The Parsons County Community Coalition

In this article we describe a case study analysis of time

series data describing actions and beliefs for young and older

residents found within a community. This community encompasses

one county situated within a rural area of a southwestern U.S.

state. According to the U.S. census bureau, in 2010 the county

encompassed 860 square miles with a total population of 16,622

residents. This combination results in a population density of 19


residents per square mile. The majority racial population in this

county is identified as white (66%), the gender ratio of males to

females is 0.9:1, and 21% of the county’s residents live below

the poverty line. For the purpose of this article, the names of

the county and the community coalition have been masked.

To identify and address health issues in Parsons County,

local and state agencies came together at the turn of the century

to establish the Parsons County Community Coalition (PCCC). The

current objective of the PCCC is to create a healthy community

throughout Parsons County by changing unhealthy actions and

beliefs while providing young residents with every opportunity

for success. Past programs supported by the PCCC, include:

mentoring programs for teenaged residents in Parsons County and

training programs for college-aged residents at a community

college located in an adjacent county. Also, representatives of

the PCCC have encouraged greater community involvement by working

with local city councils in the county, chapters of both

Crimestoppers and Neighborhood Watch, and public school leaders.


Altogether, the PCCC has functioned for over a decade to create a

better life for all residents in the county.

The PCCC received a $625,000 five-year grant in 2009 from

the Office of National Drug Control Policy (ONDCP). The grant, a

result of the Drug Free Communities Act of 1997, provided public

monies to the PCCC for (a) engaging with residents about

substance use in the community, (b) collaborating with community

stakeholders on the issue of substance use, and (c) generating

strategies to positively influence the community. The PCCC has

used monies from the grant for (a) limiting young residents’

access to substances, (b) changing the culture and context of the

county, and (c) reducing negative consequences associated with

substance use. As a requirement for the ONDCP grant, the PCCC is

required to make annual reports detailing past activities,

potential outcomes from those activities, and plans for future

activities.

Goals of the PCCC to Reduce Substance Use. One focus of the

PCCC, supported by the DFC grant, has been to reduce substance

use by young residents in Parsons County. In 2009, the PCCC


identified two goals and seven associated actions to achieve this

focus. The first goal was to establish and strengthen

collaboration among communities, private nonprofit agencies, and

Federal, State, local, and tribal governments to support the

efforts of community coalitions to prevent and reduce substance

use among young residents. To achieve this goal, representatives

of the PCCC proposed three associated actions. The first action

was the expansion of the PCCC by recruiting a broad base of

representatives from the community, local businesses, and

collaborative organizations. The second action was the election

of leaders responsible for determining the standing of ad hoc

committees. The third action was the creation of vision and

mission statements as well as clear organizational goals and

objectives based on activities and environmental strategies.

The second goal identified in 2009 was to reduce substance

use among young residents by addressing factors in the community

that increase the risk of substance abuse. To achieve this goal,

representatives of the PCCC proposed four associated actions. The

first action was determination of baseline data regarding


alcohol, tobacco and other drug (ATOD) use/abuse issues in

Parsons County. The second action was the identification of

effective environmental strategies to reduce risk factors and

enhance protective factors regarding ATOD use/abuse in Parsons

County. The third action was the implementation of frequent ATOD

educational programming using local agencies whenever possible to

educate community residents. The fourth action was the

organization of ATOD-Free activities for all community residents,

regardless of age.

Programs implemented and/or supported by the PCCC. To

achieve the goals presented above, the PCCC chose to both

implement and/or support multiple programs in Parsons County.

Monthly meetings by the PCCC were used to gather and disseminate

information from stakeholders for identifying specific programs.

As a result of these meetings, a number of programs have been

implemented and supported on an annual basis by the PCCC;

including (a) community forums, Neighborhood Watch programs, and

town hall meetings since 2009; (b) the Above the Law Campaign,

Against the Law/Make the Call Campaign, and Boys and Girls Club


since 2010; (c) the Drug Enforcement Agency’s Rx Pill Round-up,

Safe Prom Program, and Safe Graduation Program since 2011; (d)

the PCCC Youth PSA program since 2012; and, (e) the Crimestoppers

and Red Ribbon Week program since 2013. In addition to these

programs, the PCCC supported two local initiatives in 2012. The

first initiative led to the destruction of abandoned homes in the

community. These homes were thought to be used by local substance

providers and users. The second initiative resulted in passage of

the DWI “No Refusal” ordinance, a local policy created to reduce

alcohol related accidents and fatalities in Parsons County.

Evaluating the Impact of the Parsons County Community Coalition

To evaluate the impact of the PCCC, we conducted a case

study analysis of time series data collected by the PCCC from

2009 to 2013. We first collected extant data from two survey

instrument sources; the Texas School Survey (TSS): Parsons County

and the Parsons County Community Needs Assessment (PCCNA) survey.

After collecting extant data, we identified relevant results from

the two data sources. Those results identified as relevant fit

into our community cognition model described in figure 1. We


concluded our case study analysis by describing the impact of the

PCCC on young residents in terms of emergent trends over time

from the two data sources.

The Extant Data Sources. The TSS survey is administered by a

policy research institute every two years for the state of Texas.

The PCCC, in collaboration with the research institute,

administered the TSS survey in the public school districts

situated in Parsons County. The survey is designed specifically

to measure actions and beliefs of secondary students (12-18 years

old) about substance use. The PCCNA survey is administered by the

PCCC every year. Unlike the TSS, this survey is designed to

measure actions and beliefs for older residents about the

substance use.

Since 2009, the TSS and PCCNA survey instruments have been

used by social researchers, policymakers, and/or PCCC

representatives to gather information on the actions and beliefs

of residents in Parsons County. The TSS survey is administered

using randomized survey participant selection to ensure an

accurate and unbiased picture of young residents’ actions and


beliefs about substance use. The PCCNA survey is administered

using nonrandomized survey participant selection. Thus, results

of this survey cannot be described as either accurate or unbiased

from a statistical analysis perspective. We feel the results of

the PCCNA survey, combined with the unbiased TSS survey results;

provide information for evaluating the impact of the PCCC on

substance use in Parsons County since 2010.

Relevant Results from the Extant Data Sources

Relevant Results from the TSS: Parsons County Survey. The

TSS: Parsons County survey, a 41-item instrument, was

administered annually from 2010 to 2013. Each year, a random

sample of secondary students was selected to represent all young

residents between the ages of 12 and 18 years living in Parsons

County. We identified the results to items 16 through 19 as

relevant to our community cognition model. These four items asked

students to declare if and how often they had engaged in

substance use during the previous thirty days.

We examined the results from items 16 through 19 on the TSS:

Parsons County survey. We chose results from 2010 to 2013, those


years during which the PCCC implemented and/or supported programs

to reduce young residents’ substance use. The results showed no

apparent impact on marijuana use by young residents from 2010

(9.8%) to 2013 (9.5%; see Figure 2). However, the results for

other substances do suggest change. Tobacco use by young

residents steadily declined from 17.8% in 2010 to 13.1% in 2013.

In addition, prescription and OTC use declined sharply between

2010 and 2012. Prescription use declined from 13.4% in 2010 to

3.6% in 2012 as OTC use declined from 8.9% to 1.4 % during the

same period. Alcohol use declined sharply from 38.3% to 32. 5%

after the first year; however, use remained constant at just

under 33% from 2011 to 2013.


Relevant Results from the Parsons County Community Needs

Assessment Survey. The PCCNA survey, a 54-item instrument, was

administered annually from 2010 to 2013. Each year, a convenient


sample of approximately 200 older people was selected to

represent all older residents over the age of 18 years living in

Parsons County. We identified the results to items 31, 33, 37,

38, and 41 as relevant to our community cognition model. The

first two of these items asked older residents to declare if and

how often they had engaged in the behavior of substance use

during the previous thirty days. The last three of these

questions asked older residents if they Agreed or Strongly Agreed

with the statement regarding substance use and health.

We examined the results from items 31 and 33 on the PCCRNA

survey to describe the substance use of older residents in

Parsons County. As with the results for the TSS: Parsons County

survey, we chose results from 2010 to 2013. The results suggest

tobacco use by older residents in the county was low and remained

constant from 2010 (16%) to 2013 (14%; see Figure 3). Conversely,

alcohol use by older residents in the county was relatively

higher in 2010 (72%) but appeared to decline sharply between 2012

(75%) and 2013 (63%).



We examined the results from items 37, 38, and 41 on the

PCCRNA survey to describe the beliefs about substance use and

healthy living of older residents in the county. As with the

previous data, we chose results from 2010 to 2013. The results

suggest the belief by older residents that smoking is

incompatible with healthy living remained constant from 2010

(95%) to 2013 (95%; see Figure 4). However, belief about heavy

alcohol use and healthy living declined from 2012 (94%) to 2013

(88%). A similar observation was made for results concerning

belief about abusing drugs and healthy living from 2012 (90%) to

2013 (85%).


The Impact of Community Coalitions in Rural Areas on Residents’

Actions and Beliefs about Substance Use


In 1997, the U.S. federal government passed the Drug Free

Communities Act. This act set aside monies for stakeholders

interested in reducing substance use by residents in U.S.

communities. In 2009, the PCCC received a $625,000 five-year DFC

grant to establish and support collaboration among those

stakeholders in Parsons County working to reduce young residents’

substance use. As a result of the work begun in 2009, the PCCC

implemented and/or supported multiple programs between 2010 and

2013 to reduce substance use in Parsons County. As the DFC grant

support begins to fade, stakeholders in the PCCC are left with

the same question all stakeholders in community coalitions are

left with, “What is the impact of community coalitions?”

The community cognition model we use proposes links between

three elements found within a community: (a) young residents’

action, (b) older residents’ action, and (c) older residents’

belief. By means of data describing young residents’ substance

use, older residents’ substance use, and older residents’ value

judgment about healthy living and substance use; we provide

linear illustrations in Figure 5 to visualize the relationship


between these three elements. The linear illustrations reveal

reductions in young residents’ alcohol, tobacco, prescription,

and OTC substance use from 2010 to 2013. Over the same time,

these reductions correspond with a reduction in older residents’

alcohol use and in the value judgments that healthy living is not

compatible with alcohol or other drug use. These illustrations

also reveal no reduction in young residents’ marijuana use, older

residents’ low and constant tobacco use with a constant high

value judgment that healthy living is not compatible with tobacco

use.


Discussion

Young residents provide the foundation for the future of

communities situated in rural areas. Substance use by these

residents is, therefore, a concern for stakeholders involved in

these areas. Young residents not only provide foundation for the


future but are also likely indicators of older residents’ actions

and beliefs. As a result, social researchers continue to study

relationships among residents within communities while

practitioners, community leaders and other stakeholders work to

reduce substance use.

In this article we briefly reviewed the importance of

community coalitions in addressing social issues and the need to

evaluate the impact of these coalitions when situated in rural

areas. We proposed a simple model, the community cognition model,

with which to describe residents’ action and belief as well as

identify relationships between resident populations. Results from

our case study analysis of time series data from two resident

populations in a rural area suggest programs implemented and

supported by community coalitions positively impact young

residents’ substance use. Specifically, results of our analysis

for young residents show declines in alcohol, tobacco,

prescription pills, and OTC use during the period that the PCCC

actively implemented and/or supported programs to reduce

substance use. We note the majority of programs implemented


and/or supported by the PCCC were focused on two of these

substances (i.e., alcohol and prescription pill). Unfortunately,

our analysis for young residents shows no decline in marijuana

use. Finally, survey results for older residents show declines in

alcohol use and no decline in tobacco use during the same period.

We proposed the community cognition model to link three

elements: (a) young residents’ action, (b) older residents’

action, and (c) older residents’ belief. By means of data

describing young residents’ substance use, older residents’

substance use, and older residents’ value judgment between

substance use and healthy living we illustrated the relationship

between these three elements. As stakeholders working for

community coalitions attempt to justify the public monies spent

to address serious social issues (e.g., substance use), the

community cognition model used in this article provides a

framework for evaluating the impact of coalitions in rural areas.

Although other factors play a role in reducing young residents’

substance use, the similarity in linear illustrations for the

model suggest community coalitions not only impact young


residents’ substance use, but older residents’ substance use and

value judgments as well.

Using the community cognition model also allows stakeholders

to explore potential relationships between resident populations.

For example, this model illustrates that older residents in

Parsons County are highly unlikely to be involved in tobacco use

or believe tobacco use is compatible with healthy living. This

would suggest the impact of the PCCC on young residents’ tobacco

use was facilitated by extant adult residents’ action and belief.

In addition, this model illustrates the PCCC was initially

successful in reducing young residents’ alcohol use while older

residents’ alcohol use remained constant before reducing in the

final year of data collection. Similarly, until the final year of

data collection, a large percent of older residents held the

value judgment that alcohol use is not compatible with healthy

living. This might suggest the impact of the PCCC on young

residents’ alcohol use has a delayed impact on older residents’

action and belief.


Challenges in evaluating the impact of community coalitions and

limitations to the current study

Several challenges exist when evaluating the impact of

community coalitions situated in rural areas. First, the usual

goal for researchers, establishing clear links between

implemented and/or supported programs with outcomes can be a

particular challenge. Community coalitions, as the name implies,

work as a loose confederation of agencies and stakeholders using

separate programs and policies to address the same, similar, or

associated populations. In rural areas there are typically fewer

of these agencies and stakeholders in place. Consequently,

researchers studying the impact of coalitions in rural areas must

take care in creating models useful for understanding the

mechanisms at play in the community while also presenting a

narrative for the sources in which data is collected. A second

challenge relates to the delayed nature of change. Community

coalitions in rural areas work through a small array of programs

to influence residents’ action and belief. As a result,

evaluating the impact of coalitions in these areas should be


continued over time to learn about the size and scope of change

brought about by each of the programs. Finally, community

coalitions in rural areas are likely to influence all residents.

Therefore, fully evaluating the impact of community coalitions in

these areas may require access to data from a comparable

community. Future cohort or longitudinal studies in similar rural

areas may inform us as to the strength of our community cognition

model and the impact of programs implemented and/or supported by

community coalitions in these areas.

Although the current study addresses some of the challenges

mentioned above, as practitioners we introduced limitations into

the study as well. First, as practitioners we are not experts in

the field of social survey research. Consequently, we employed

experts in the field of policy survey research to increase the

accuracy and validity of data describing young and older

residents’. Using these experts allowed us to focus on

implementing and/or supporting the programs from 2010 to 2013.

Second, our data were compiled y multiple researchers having

individual perspectives. We, therefore, worked to improve honesty


of data reporting through occasional stakeholder meetings and

follow-up discussions. These meetings and discussions allowed us

to review the current status of data collection, data analysis

and report writing over time. Third, this study makes use of

cohort samples. We attempted to reduce the influence of cohort

samples over time through instrumentation. Specifically, although

the data analyzed for this article came from eight different

resident samples within the same rural area over a four year

period, the four young resident samples were surveyed with the

TSS instrument whereas the four older resident samples were

surveyed with the PCCRNA instrument.

Implications for Health Education and Community Coalitions in

Rural Areas

Millions of public dollars have been spent in the pursuit of

reducing substance use by residents in the U.S. community;

however, we are only now beginning to fully understand the role

of personal and contextual factors. This case study provides

evidence suggesting community coalitions in rural areas, created

to reduce substance use by young residents’ populations, also


have an impact on older resident populations. Since previous

research has shown significant association between coalition

impact and community change, our results may provide an important

intermediate point useful for stakeholders to monitor as they

evaluate coalition functionality over time.


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Figure 1. A community cognition model illustrating the

interrelationships between young residents’ action (i.e.,

substance use) with older residents’ action (i.e., substance use)

and belief (i.e., attitude about substance use)


2010 2011 2012 20130

5

10

15

20

25

30

35

40

45

AlcoholTobaccoMarijuanaPrescriptionOTC

Year

Percent of young residents in Parsons

County using a specified substance over a

30 day period

Figure 2. The percent of young residents in Parsons County

claiming to have used a specified substance at least once during

a 30 day period (Results taken from the TSS: Parsons County

survey administered from 2010 through 2013)


2010 2011 2012 20130

10

20

30

40

50

60

70

80

AlcoholTobacco

Year

Percent of

older residents in Parsons

County using

a specified substance over a

30 day period

Figure 3. The percent of older residents in Parsons County

claiming to have used a specified substance at least once during

a 30 day period (Results taken from the PCCNA survey administered

from 2010 through 2013)


2010 2011 2012 201370

75

80

85

90

95

100

People risk harming themselves if they have five or more alcoholic drinks close togetherPeople risk harming themselves if they smoke one or more packs of cigarettes per dayPeople cannot stay healthy if they abuse drugs

Year

Perc

ent of

old

er res

iden

ts i

n Pa

rson

s Co

unty

who

res

ponded

Agr

ee o

r St

rong

ly

Agre

e

Figure 4. The percent of older residents in Parsons who Agreed or

Strongly Agreed to questions related to substance use and healthy

living (Results taken from the PCCNA survey administered from

2010 through 2013)


Youn

g re

side

nts'

alc

ohol

use

Youn

g re

side

nts'

tob

acco

use

Youn

g re

side

nts'

mar

ijua

na u

se

Youn

g re

side

nts'

pre

scri

ptio

n us

e

Youn

g re

side

nts'

OTC

use

Olde

r re

side

nts'

alc

ohol

use

Olde

r re

side

nts'

tob

acco

use

Peop

le r

isk

harm

ing

them

selv

es i

f th

ey h

ave

five

or

more

alc

ohol

ic

drin

ks c

lose

tog

ethe

rPe

ople

ris

k ha

rmin

g th

emse

lves

if

they

smo

ke o

ne o

r mo

re p

acks

of

ciga

rett

es p

er d

ayPe

ople

can

not

stay

hea

lthy

if

the

y ab

use

drug

s

Young residents' action Older residents' action

Older residents' belief

2010201120122013

Figure 5. Illustration of the community cognition model using

element names, variable names and percent values from Figures 1,

2, 3, and 4

EVALUATING THE IMPACT OF COMMUNITY

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