Figure 31.1 Logic Model Logic Models Karen A. Rand

Figure 31.1
Logic Model
Logic Models
Karen A. Randolph
A
logic model is a diagram of the relationship between a need that
a
p rogram is designed to addret>s and the actions to be taken to
address the
need and achieve program outcomes. It provides a concise, one-
page pic-
ture of p rogram operations from beginning to end. The diagram
is made
up of a series of boxes that represent each of the program's com
ponents,
inpu ts or resources, activities, outputs, and outcomes. The
diagram shows how these
components are connected or linked to one another for the
purpose of achieving
program goals. Figure 31.1 provides an example of the frame
work for a basic logic model.
Th e program connections illustrate the logic of how program
operations will result in
client change (McLaughlin & Jordan, 1999). The connections
show the "causal" relati on-

ships between each of the program components and thus are
referred to as a series of"if-
then" sequence of changes leading to th e intended outco mes
for the target client group
(Chinman, hum, & Wandersman, 2004). The if-then statements
represent a program's
theory of change underlying an intervention. As such, logic
models provide a framework
that g uides the evaluation process by laying out important
relationships that need to b e
tested to demonstrate program results (Watso n, 2000).
Logic models come from the field of program evaluation. The
idea emerged in
response to the recognition among program evaluators regardin
g the need to systema tize
the p r ogram evaluation process (McLaughlin & Jordan, 20 04).
Since then , logic models
have become increasingly popular among program managers for
program planning and
to monitor program performance. With a growing emphasis on
accountability and out-
come measurement, logic models make explicit the entire
change process, Lhe assu mp-
tions t hat underlie this process, and the pathways to reach ing
outcomes. Researchers have
begun to use logic models for intervention research planning
(e.g., Brown, Hawkins,
Arthur, Brin ey, & Abbott, 2007).
The followin g sections provide a description of the components
of a basic logic model
and how these compon ents are linked together, its relationship
to a p rogram's theory of
[ : Inputs 1--_.,•1 Ac~vities ,II----.~•{ .Outputs ·11---~·1

Outcomes I
AUTHOR'S NOTE: The author wishes to acknowledge Dr. Tony
Tripodi for his though lful comments
on a drafl of this chapter.
547
548 PART V • CONCEPTUAL RESEARCH
change, and its uses and benefits. The steps for creating a logic
model as well as the chal-
lenges of the logic modeling process will be presented. The
chapter concludes with an
example of how a logic model was u~cd to enhance program
outcomes for a family liter-
acy program.
Components of a Logic Model
Typically, a logic model has four components: inputs or
resources, activities, outputs, and
outcomes. Outcomes can be further classified into short-term
outcomes, intermediate
outcomes, and long-term outcomes based on the length of time
it takes to reach these
outcomes (McLa ughlin & Jordan , 2004) . The components
make up the connection
between the planned work and the intended results (W. K.
Kellogg Foundation, 2004).
The planned work includes the resources (the inp uts) needed to
im plement the program
as well as how the resources will be used (the activities) . The
intended results include the
outputs and outcomes that occur as a consequence of the

planned work. Figure 31.2
expands on the model illuslrated in Figure 3 1.1 by adding
examples of each component.
This particular logic model, adopted from frec htling (2007),
provides an illustration of
the components of an intervention designed to prevent substance
abuse and other prob-
lem behaviors among a population of youth. The interventi on is
targeted toward improv-
ing parenting skills, based on the assumption that positive
parenting leads to prosocial
behaviors among yo uth {Bahr, Hoffman, & Yang, 2005). The
following section provides
definitions and examples of each logic model component, using
this illustration.
Resources
Resources, sometimes referred to as inputs, in clude the human,
fin ancial, organizational,
and community asse ts that are available to a program to
achieve its objectives (W. K.
Kellogg Foundation, 2004). Resources are used to support and
facilitate the program
activities. They are usually categorized in terms of funding
resou rces or in -kind contribu-
tion s (Frechtling, 2007) .
Some resources, such as laws, regulations, and funding
requirements, are external to
the agency (United Way of America, 1996). Other resources,
such as staff and money, are
easier lo quantify than others (e.g., community awareness of the
program; Mertinko,
Novotney, Baker, & Lange, 2000). As Fn.:c:htli ng (2007)
notes, it is important to clearly and
tho roughly id ent ify the available resources during the logic

modeling process because this
information defines the scope and parameters of the program.
Also, this inCormation is
critical for others who may be interes ted in replicating the
program. The logic model in
Figure 31.2 includes fu nding as one of its resources.
Activities
Activities represent a program's service methodology, showing
how a program intends on
using the resources described previously to carry out its w ork.
Activities are also referred
to as ac tion step!; (McLaughlin & Jordan, 2004). They are the
highly specifi c tasks that
p rogram staffs engage in on a daily basis to provide services to
clients (Mertinko
et al., 2000) . They include all aspects of pro gram
implementation, the processes, tools,
events, technology, and program actions. The ac tivities form
the foundation toward facil-
itating intended client changes or reaching oulcornes (W. K.
Kellogg Fo undation, 2004).
Some examples are establishing community councils, providing
professional develop -
ment training, or initiating a media campaign (Frechtling,
2007). Other examples are
CHAPTER 31 • l OCIC MO DELS 549
Inputs Activities Outputs Outcomes
Short Term Intermediate Long Term
Feedback Loop j

_J
I
Decreased
K~
Increased
I
Develop and Numbe r of Increased
youth Funds .~ initiate ~edi a st~tions a~opti ng r-- awareness
f- positive 1-----+ of positive substance
-~m~tg~-- -.:::c -campatgn J pa renting parenti ng - abv?~d'
~-'.:-
/
I
Develop and Number of Increased
distribute - 1> fact sheets 1- enrollment
fact sheets distributed in parenting
programs
Fig ure 31.2 Example of l ogic Model With Com ponents, Two
Types of Connections, and a Feedbaclc loop
providing shelter for homeless families, educating the public
about signs of child abuse,
or providing adult mentors for youlh {United Way of Ame rica,
1996) . Two activities,
" Deve lop and initiate media campaign" and "Develop and
distribute fact sheets;' are
included in the logic model in Figure 31.2. Activities lead to or

produce the program o ut-
puts, described in the following section.
Outputs
The planned works (resources and activities) bring about a
program's des ired res ul ts,
including outputs and outcom es (W. K. Kell ogg Foundatio n,
2004) . Outputs, also referred
to as units of service, are the immediate results of program
activities in the form of types,
levels, and targets of services to be delivered by the program
(McLaughl in & Jordan ,
1999). They are tangible products, events, o r serv ices. They
provide the documentation
that activities have been implemented and, as such, indicate if a
program was delivered to
the intended audience at the intended dose (W. K. Kellogg
FounJation, 2004). Outputs
arc typical ly desc ribed in terms of th e size and/or scope of the
services an d products pro-
duced by the program and thus are expressed numerically
(Frechtling, 2007). Examples of
program ou tpu ts include the number of classes ta ught,
meetings held, o r materials p ro-
duced and distributed; program par ticipation rates and
demography; or hours of each
type of serv ice provided (W. K. Kellogg Foundation, 2004) .
Other examples are the
number of meals provided, classes taught, brochures distributed
, or participants ser ved
(Frecht1ing, 2007) . W hile outputs have little inherent value in
themselves, they provide
the link between a program's activ ities and a program's
outcomes (United Way of
America, 1996). The logic model in Figure 31.2 includes Lhc
number of stations adopting

the media campaign and the number of fact sheets distributed as
two outputs for the pre-
vention program.
550 PART V • CONCEPTUAL RESEARCH
Outcomes
Outcomes arc Lhe specific changes experienced by the
program's clients or target group as
a consequence of participating in the program. Outcomes occur
as a result of the program
activities and outputs. These changes may be in behaviors,
attitudes, skill level, status, or
level of functioning (W. K. Kellogg Foundation, 2004).
Examples include increased knowl-
edge of nut r itional needs, improved reading skills, more
effective responses to conflict,
and finding employment (United Way of America, 1996) .
Outcomes are indicalors of a
program's level of success.
McLa ughlin and Jordan (2004) make the point that some
programs have multiple,
sequential outcome structures in the form of short-term
outcomes, intermediate out-
comes, and long-term outcomes. In these cases, each type of
outcome is linked tempo-
rally. Short-term outcomes arc client changes or benefits th at
are mos t immediately
associated with the program's outputs. They are usually realized
by clients wi thin 1 to
3 years of program completion. Short-term outcomes are linked
to accomplishing inter-
mediate outcomes. Intermediate ou tcomes are generally attain

able in 4 to 6 years. Long-
term outcomes are also referred to as program impacts or
program goals. They occur as a
result of the intermediate outcomes, usually within 7 to 10
years. In this format, long-
term outcomes or goals are directed at macro-level change and
target organizations, co m-
munities, or systems (W. K. Kellogg Foundation, 2004).
As an example, a sequen tial outcome structure with short-
term, intermediate, and
long-term outcomes for the prevention program is displayed in
Figure 31.2. As a result of
hearing the public service announ cemen ts about positive
parenting (th e activity), parents
enroll in parenting programs to learn new parenting skills (the
short-term outcome).
Then they apply these newly learned skills with their children
(the intermediate out-
come), which leads to a reducti on in substance abuse among
youth (the long-term impact
or goal the parenting program was designed to achieve).
Outcomes ar e often confused with outputs in logic models
because their correct clas-
sification depends on the context within which they are being
included. A good exa mple
of this potential confusion, provided in the United Way of
America manual ( 1996, p. 19),
is as follows. The number of clients served is an output when it
is meant to describe the
volume of work accomplished. In this case, it does not relate
directly to cl ient changes or
benefits. H owever, the number of clients served is considered
to be an outcome when the
program's intention is to encourage clients to seek services,

such as alcohol treatment.
What is important to remember is that outcomes describe
intended client changes or
benefits as a result of participatin g in the program while
outputs document products or
services produced as a result of activities.
Links or Connections Between Components
A critical part of a logic model is the connections or links
between the components. The
connections illustrate the relationships between the components
and the process by
which change is hypothesized to occur among program
participants. This is referred to as
the program theory (Frechtling, 2007). It is the con nections
illustrating the program's
theory of change that make the logic model complicated.
Specifying the connections is
one of the more difficult aspects of developing a logic model
because the process requires
predicting the process by which client change is expected to
occur as a result of program
participation (Frech tling, 2007).
CHIII'TER 31 • lOGIC M ODtLS 551
Frechtling (2007) describes nvo types of connections in a logic
model: connections
that link items within each compo nent and connections that
illustrate the program's
theory of change. The first type, items within a component, is
connected by a straight line.
This line shows that the items make up a

particularcomponent.As an example, in Figure 31.2,
nvo activities, "Develop and initiate media campaign" and "
Develop and distribute fact
sheets," are linked together with a straight line beca use they
represent the items within the
activities component. Similarly, two outputs, "Number of
stations adop ting the cam-
paign" and "Number of fact sheets distributed;' arc connected as
two items within the
outputs component.
The second type of connection sh<.>ws how the components
interact with or relate to
each other to reach expected outcomes (Frechtling, 2007) . In
essence, this is the program's
theory of change. Thus, instead of straight lines, arrows are
used to show the direction of
influence. Frechtling (2007) clarifies that "these directional
connections are not just a
kind of glue ancho ring the otherwise floating boxes. Rather
they portray the changes thaL
arc expected to occur after a previous ac Livity has taken place,
and as a result of it" (p. 33).
She points out that the primary purpose of the evaluation is to
determine the nature of
the relationships between components (i.e., whether the
predictions are correct). A logic
mod el that illustrates a fully developed theory of change
includes links between every
item in each co mponent. In other words, every item in every
component must be co n-
nected to at least one item in a subsequent component. This is
illustrated in Figure 3 1.2,
which shows that each of the two items within th e activities co
mpon en t is linked to an
item within the output co mponent.

Figure 31.2 provides an example of the predicted relationships
between the compo-
nents. This is the program theory about how the target group is
expected to change. The
input or resource, funding, is co nnected to the tv,ro activities,
"Develop and initiate media
campaign" and "Develop and distribute fac t sheets." Simply
put, this part of Figure 31 .2
shows that funding will be used to support the development and
initiati on of PSA cam-
paigns and the distribution of fact sheets.
The sequencing of the connections between components also
shows th at these steps
occur over a period of time. While this may seem obvious and
relatively inconsequential,
specifying an accurate sequence has time-based implications, pa
rticularly when short-
term, intermediate, and long-term outco mes are proposed as a
part of the theory of
change (Frechtling, 2007). Rcca11 that the short-term outcomes
lead to achieving the
intermediate outcomes, and the intermediate outcomes lead to
ach ieving long-term out-
comes. Thus, the belief or underl}ing ass umption is that short-
term outco mes mediate
(or come between) relationships benv-een activities and
intermediate o utcomes, and
intermediate outcomes mediate relations between sho rt-te rm
and long-term outcomes.
Related, sometimes logic models display feedback loops.
Feedback loops show how the
information gained from implementing one item can be used to
refine and improve other

items (Frechlling, 2007). f or instance, in Figure 31.2, the
feedback loop from the short-
term outcome, " Increased awareness of positive parenting;'
back to the activity, "Develop
and initiate media campaign;' indicates that the findings for "
Increased awareness of pos-
itive parenting" arc used to im prove the PSA campaigns in the
next program cycle.
Contextual Factors
Logic models describe programs that exist and are affected by
contextual factors in the
larger environment. Contextual factors are those important
features of the environment
552 PART V • CONCEPTUAL R ESEARCH
in which the project or inter vention takes place. They include
the social, cultural, and
political aspects of the environment (Frechtling, 2007). They
are typically not under the
program's control yet are likely to influe nce the program either
positively or negatively
(McLa ughlin & Jordan, 2004 ). T hu s, it is critical to identify
relevant contextual factors
and to consider their potential impact on the program.
McLaughlin and Jordan (1999)
point out that understanding and articulating contex tual factors
co ntr ibu tes to an under-
standing of the fo undat io n u pon whi ch performance
expectatio ns a re established.
Mo reover, this knowledge h elps to establish the parameters for
explaining program

results and developing program improvement strategies that are
li kely to be more m ean-
ingful and thus more successful because the information is more
complete. finally, con-
textual factors clarify situations under which the program
results might be expected to
generalize and the issues that might affect replication
(Frechtling, 2007) .
Harrell, Burt, Hatry, Rossm an, a nd Roth ( 1996) identify two
types of contextual fac-
tors, antecedent and media6ng, as o utside facto rs that could
influence th e program's
design, implementa tio n, and results. Anteceden t factors are
thos e that exist prior to
program implemen tatio n, such as cha racteristics of the client
target population o r com-
munity characteristics such as geographical and economic
conditions. Mediating factors
are the environmental influences that emerge as the program
unfolds, such as new laws
and policies, a change in economic con ditions, or the startup of
other new programs pro-
viding similar services (McLaughlin & jordan, 2004).
Logic Models and a Program's Theory of Change
Definition
Log ic models p rovide an illustration of the compo nents of a
program's theo t-y and how
those components are linked togeth er. Program theory is
defined as "a plausible and sen-
sible model of how a program is supposed to wo rk" (Bickman,
1987, p. 5). Program
theory in corporates "program resources, program activities, and
intended program out-

comes, and specifies a chain of causal assumptions linking
resources, activities, interme-
di ate outcomes, and ulti mate goals" (Wholey, 1987, p. 78).
Program theory e.>..-plicates the
assumptions abou t how the program components link together
from program star t to
goal attainmen t to realize the program's intended outcomes
(Frechtling, 2007). Thus, it is
often referred to as a p rogram's theory of change. Frechtling
(2007) suggests that both
previous research and knowledge gained from practice
experience arc useful in develop-
ing a theory of change.
Relationship to logic Models
A logic model provides an illustration of a program's theory of
change. It is a useful tool
for describing program theory because it shows the connections
or if-then relationships
between program components. In other words, moving from left
to right from one com-
po nent to the next, logic models provide a diagram of the
rationale or reasoning underly-
ing the theory of change. If-th en statements connect the
program's co m po nents to form
the theory of change (W. K. Kellogg Founda tion, 2004). For
example, certain resources or
inputs are needed to carr y out a program's activities. The first
if-then statement links
reso urces to acti vities and is stated, " If you have access to
these resources, then yo u can use
them to accomplish yo ur planned activities" (W. K. Kellogg Fo
undation, 2004, p. 3). Each

CHAPTER 31 • LOCIC MODELS SS3
component in a logic model is linked to the other components
using if-then statemen ts to
show a program's chain of reasoning about how client change is
predicted to occur. The
idea is that "if the right resources are transformed into the right
activities for the right
people, then these will lead to the results the program was
designed to achieve"
(McLaughlin & Jordan, 2004, p. 11). It is important to define
the components of an inter-
vention and make the connections between them explicit
(Frechtling, 2007).
Program Theory and Evaluation Planning
Chen and Rossi (1983) were among th e first to suggest a
program theory-driven
approach to evaluation. A program's theory of change has
significant utility in develop-
ing and implementing a program evaluation because the theory
provides a framework
for determining the evalu ation questions (Rossi, Lipsey, &
Freeman, 2004) . As such, a
logic model that ill ustrates a program's theory of change
provides a map to inform the
developmen t of relevant eval uation questions at each phase of
t he evaluation. Rossi
et al. (2004) explain how a program theory-based logic mode l
enha nces the devel op-
ment of evaluation questions. First, the process of articulating
the logic of the
program's change process through the development of the logic
model prompts discus-
sion of relevant and meaningful evaluation questions. Second,
these questions then lead

to articulating expect ations fo r p rogram performance and
inform the identification o f
criteria to measure that performance. Third, obtaining input
from key stakeholders
about the theory of change as it is displayed in the logic model
increases the likelihood
of a more comprehensive set of questions and that critical issues
have not been over-
looked. To clarify, most agree that this is a team effort that
should include the program
development and program evaluation staff at a minimum, as
well as other stakeholders
both internal and external to the program as they are available
(Dwyer & Makin, 1997;
Frech tling, 2007; Mclaughlin & Jordan, 2004). The diversity of
perspective and skill sets
among the team members (e.g., program developers vs. program
evaluators) enhances
the depth of understanding of how the program will work, as
diagramed by the logic
model (Frechtling, 2007). As D"vyer and Makin (1997) state,
the team approach to
develop ing a theory-based logic model promotes "greater
stakeholde r invo lvement, the
opportunity for open negotiation of program objectives, greater
commitment to the
final co nceptualization of the program, a shared vis ion, and
increased likeliho od to
accept and utilize th e evaluation results" (p. 423) .
Uses of Logic Models
Logic models have many uses. They help Lo integrate the entire
program's planning and
implementation process from beginning to end, including the
evaluation process (D wyer

& Makin, 1997). They can be used at all of a program's stages
to enhance its success
(Frechlling, 2007; W. K. Kellogg Foundation, 2004). For
instance, at the program design
and planning stage, going through the process of developing
logic models helps to clarify
the purpose of the program, the development of program
strategies, resources that are
necessary to attaining outcomes, and th e identification of
possible barriers to
the program's success. Also, identifying program components
such as activities and
outcomes prior to program implementati on provides an
opportunity to ensure that
program outcomes inform program activities, rather than the
other way aroun d (Dwyer
& Makin, 1997) .
554 PART V • CoNcEPTUAl R ESEA RC H
During the p rogmm implementation phase, a logic model p
rovides the basis fo r th e
development of a management plan to guide program
monitoring ac tiv ities and to
improve program processes as issues arise. In other words, it
helps in identifying and
highlighting the key program processes to be tracked to ensure a
program's effectiveness
(United Way of America, 1996).
Most important, a logic model facilitates evaluatio n planning
by providing the evalua-
tion framework fo r shapin g the evalua tion across all stages of
a project. Intended out-

comes and the process for measuring these outcomes are
displayed in a logic model
(Watson, 2000), as well as key points at which evaluation
activities should take place
across the life of the program (McLaughlin & Jordan) 2004).
Logic models suppo rt both
formative and summative evaluations (Frechtli ng, 2007). They
can be used in conducting
summativc evaluations to determine what has been
accomplished and, importantly, the
process by which these accomplishments have been achieved
(Frechtling, 2007) . Logic
models can also support formative evaluations by organizing
evaluatio n activities, incl ud-
ing the meas urement of key variables or performance indicators
(McLaughlin & Jordan,
2004) . From this info rmation, evaluation questions, relevant
indicators, and data collec-
tion strategies can be developed. The following section expands
on using the logic model
to develop evaluation questions.
The logic m odel provides a framework for developing eval uat
ion q uestions about
prog r am co n text, program efforts, and p rogram effec
tiveness ( Frech t ling, 2007;
Mer ti nko et al., 2000). Together, these three sets of quest ions
help to explicate the
progr am's theory of change by describing the assumptions
about the r elationship s
between a program's operations and its predicted outcomes
(Ross i et al. , 2004) .
Context questio ns explore program capacity and relationships
external to the program
and help to identify and understand the impac t of confo unding
factors or externa l

infl uences. Pr ogram effort and effectiveness quest ions
correspond to particular co m -
ponents in the logic model and thus exp lore program processes
t oward ach ieving
program outcomes. Questions a bout effor t address the planned
work of the program
and come from the input and activities sections of the eva luatio
n mo d el. They address
program implementation issues such as the services that were
provided and to who m.
These questio ns focus on what happene d and why.
Effectiveness or outco m e questions
address program results as described in the output and outcomes
section of the logic
m odel. From the questions, indicators and da ta collection
strategies can the n be d evel-
oped. Guidelines for using logic mo d els to develop evaluation
questi ons, ind icators,
and data collection strategies are provided in the Logic Model
Development Guide
( W. K. Kellogg Foundation, 200 4 ).
In addition to supporting program effo rts, a logic model is a
useful comm unication
tool (McLaughlin & Jordan, 2004 ). For instance, developing a
logic model provides the
opportunity fo r key stakeholders to discuss and reach a
common understanding, includ-
ing underlying assumptions, about how the program opera tes an
d the resources needed
to achieve program p rocesses and outcomes. ln fact, some
suggest t hat the logic model
development process is actually a form of strategic planning
because it requ ires partici-
pants to articulate a program's vision, the rationale for the
program, and the program

processes and procedures ('Watson, 2000) . T his also promotes
stakeholder involvem ent in
program planning and consensus building on the program's
design and operations.
Moreover, a logic model can be used to explain program
procedures and sha re a compre-
hensive yet concise picture of th e p rogram to comm unity
partners, funders, and others
outside of the agency (McLaughlin & Jordan, 2004) .
CHAPTER 3 1 • LOGIC M ODF I S 555
Steps for Creating Logic Models
McLaughlin and Jordan (2004) descri be a five-stage process for
developing logic models.
The first stage is to gather extensive baseline information from
multiple sources abo ut the
nature of the problem or need and about alternative solutions.
The W. K. Kellogg
Foundation (2004) also suggests collecting information about
community needs and
assets. This information can then be used to both define the
problem (the second stage of
developing a logic model ) and identify the program clements in
the form of logic model
componen ts (the third stage of logic model development).
Possible information sources
include existing program documentation, interviews with key
stakeholders internal and
exte rn al to the program, strategic plans, annual performance
plans, previous program
evaluations, an d relevant legislation and regulations. It i s also
important to review the lit-

erature about factors related to the problem and to determ ine
the strategies others have
used in attemp ting to address it. This type of information
provides supportive evidence
that informs the approach to addressing the problem.
The information collected in the first stage is th en used to
define the problem, the
con textual factors that relate to the problem, and Lhus the need
for the program. The
program sho uld be conceptualized based on what is uncovered
abo ut the nature and
extent of the problem, as well as the factors that are correlated
with or cause the prob-
lem. It is also impor tan t at this stage to develop a clear idea of
the impact of the prob-
lem across micro, mezzo, and macro domains. The focus of the
program is then to
address the "causal" factors to solve t he problem. In addition,
McLaughlin and Jordan
(2004, p. 17) recommend identifyi n g the environmental factors
that are likely to affect
the program, as well as ho·w these conditions might affect progr
am outcomes.
Understanding the relationship between the program and relevan
t environmental fac-
tors contributes to framing its parameters.
During the third stage, the elemen ts or components of the logic
model are identified,
based on the findings that emerged in the second stage.
McLaughlin and Jorda n (2004)
recommend starting out by categorizing each piece of
information as a resource or input,
activity, o utput, short-term outcome, intermediate outcome,
long-term outcome, or con-

textual factor. While some suggest that the order in which the
components arc identified
is in consequen tial to developing an effective logic mod el,
most recommend beginning
this process by identifying long-term outcomes and working
backward (United Way of
America, 1996; W. K. Kellogg Foundation, 2004) .
The lo gic model is drawn in the fourth stage. Figure 31 .2
provi.des an example of a typ -
ical logic model. This diagram includes columns of boxes
representing the items for each
component (i.e., inputs, activities, outputs, and shor t-term,
intermediate, and long- ter m
outcomes). Text is provided in each box to describe the item.
The connections between
the items within a component are shown with straight lines. The
links or connections
between components are shown with one-way directional
arrows. Prog ram components
may or may not have one-on-one rela tionships with o ne
another. In fact, it is likely that
components in one group (e.g., inputs) will have multiple
connections to components in
another group (e.g., activities). For example, in Figure 31.2, we
show that the funding
resource leads to two activities, "Develop and initiate media
campaign" and "Develop and
distribute fact sheets." Finally, because activities can be
described at many levels of detail,
McLaughlin and Jordan (2004) suggest simplifying the model
by group ing activities that
lead to the same outcome. They also recommend including no
more than five to seven
activity groupings in one logic model.

556 PART V • CO NCEPTUAl RESEARCii
Stage 5 focuses on verifying the logic model by getting input
from all key stakeholders.
McLaughlin and Jordan (2004) recommend applying the if-then
statements presented by
United Way of America ( 1996) in developing hypotheses to
check the logic model in the
following manner:
given observations of key contextual factors, if resources, then
program activities; if
program activities, then out puts for targeted customer groups;
if outputs change
behavior, first short term, then intermediate outcomes occur. If
intermediate out-
comes occur, then longer-term outcomes lead to the problem
being solved. (p. 24)
They also recommend answering the following questions as a
part of the verification
process (pp. 24-25):
1. Is the level of detail sufficient to create understanding of the
elements and their
interrela ti onsh ips?
2. Is the program logic complete? That is, arc all the key
elements accounted for?
3. Is the program logic theoretically sound? Do all the elements
fit together logically?
Are there other plausible pathways to achieving the program
outcomes?

4. Have all the relevant external contextual factors been
identified and their potential
influences described?
Challenges in Developing Logic Models
Frechtling (2007 ) describes three sets of challenges in
developing and using logic models,
including (a) accurately portraying the basic features of the
logic model, (b) determining
the appropriate level of detail in the model, and (c) having
realistic expectations about
what logic models ca n and canno t contribute to program
processes. These challenges are
reviewed in more detail in the following section.
Portraying the Logic Model's Basic Features Accurately
The basic features of a logic model must be clearly understood
in order for the logic
model to be useful. In particular, logic model developers often
enco unter difficulty in four
areas: confusing terms, substituting specific measures for more
gene ral outcomes, assum-
ing unidirectionality, and failing to specify a timefrarne for
program processes (Frechtling,
2007; McLaughlin & Jordan, 2004).
One issue in developing the logic model is accurately
differentiating between an activity
or outp ut and an outcome. Frequently, activities and outputs
are confused witl1 outcomes
(Frechtling, 2007). They can be distinguished by remembering
that activities are steps or
actions taken in pursuit of producing the output and thus
achieving the outcome. Outputs

are products that come as a result of completing activities. They
are typically expressed
numerically (e.g., the number of training sessions held).
Outputs provide the documenta-
tion that activities have occurred. They also link activities to ou
tcomes. Outcomes are
statements about participant cha nge as a result of experiencing
the intervention.
Outcomes describe how participants will be different after they
finish the program.
Another issue in portraying the basic features of logic models
accurately is not confus-
ing outcomes with the instruments used to measure whether the
outcomes were achieved.
C HAP t ER 31 • l OGIC M ODHS 557
For example, the outcome may be decreased depression, as
measured by an instrument
assessing a participant's level of depression (Center for
Epidemiological Studies-
Depression Scale; Radloff, 1977). Some may confuse the
outcome (i.e., decreased depres-
sion) with the instrument (i.e., Center for Ep idem iological
Studies- Depression Scale) that
was used to determine whether the outcome was met. To
minimize the potential for this
confusion, Frechtling (2007) recommends developing the
outcome lirsl and then identify-
ing the appropriate instrument for determ ini ng that the
outcome has been reached.
A thiru issue in logic model development is avoiding the

assumption that the logic
model and, by implication, the theo ry of change that the logic
model portrays move in a
unidirectional progression from left to right {Frechtling, 2007;
McLaughlin & Jordan,
2004) . While the visual display may compel users to think
about logjc mod els in this way,
logic models and the programs they represent are much more
dynamic, with feedback
loops and interactions among components. The feedback loop is
illustrated in Figure 31.2,
showing that the experi ences and information generated from
reachin g short-term out-
comes are used to refine and, it is hoped, improve the activities
in the next program cycle
that are expected to lead to these outcomes. Also, assuming
uniform directionality can
enforce the belief that the inp uts dTi ve the project, rather than
attaining the outcomes.
This underscores the importance of starting with the
development of outcomes when
putting together a logic modeL
The final issue is including a timeframe for carrying out the
processes depicted in the
logic model. The lack of a tirneframe results in an incomplete
theory of chan ge as well as
problematic expectations about when outcomes will be reached
(Frechtling, 2007).
Whether outcomes are expected too soon or not soon enough,
key stakeholders may
assume that the theory of change was not accurate. Developing
accurate predictions of
when outcomes will be reached is often d ifficu lt, especially
with n ew projects in which
very li ttle is known abou t program processes and so forth. In

this case, as more clarity
emerges abo ut the amount of time it will take to complete
activities, tirneframes should
be revisited and modified to reflect the new information.
Determining the Appropriate Level of Detail
A second set of challenges is to determine how much detail to
include in the logic model.
T he underlying dilemma is the level of complexity. Models that
are too complex, with too
much detail, are lime-consuming to develop and difficult to
interpret. Thus, they are
likely to be cumbersome to use. Models that lack enough
information may depict an
incomplete theory of change by leaving out impor tant
information. For instance, if activ-
ities are combined into par ticular groups, it is possible that
important links between spe-
cific activiti es, outp uts, and outcomes wiJJ not be represented.
This increases Lhe
possibility of making faulty assumptions about program opera
lions and how these oper-
ations lead to positive participant outcomes.
Realistic Expectations
The fmal set of challenges in using logic models is no t
expecting more from logic models
than what th ey are intended to provide. Frechtling (2007, p. 92)
notes that some may
inaccurately view the logic model as a "cure-ali" a nd that, just
by its mere existence, the
logic model wi ll ensure the success of the program and the
evaluation. Of course, the effi-
cacy of a logic model depends on the quality of its design and
components. A log ic model
cannot overcome these types of problems. Frcchtling identifies

four commo n issues
here. First, sometimes new programs are such that applying the
theory of change and a
558 P11RT V • CoN ctPI'UAl R ESEARCH
representative logic model is premature. This is the case for
programs in which a priori
expectations about relationships between activities and
outcomes do not exist.
A second risk in this area is fai ling to consider alternative
theories of change.
Alternative explanations and competing hypotheses sho ul d be
explored. Focusing on only
one theory of change may result in not recognizing and
including important factors that
fall o utside of the theorys domain. Ignoring these competing
fac to rs may result in the
fail ure of the logic model and the program.
Third and related, it is critical to acknowledge the influence of
contextual factors that
arc likely to affect the program. Interventions always exist and
function wiLhi n a larger
environment. Contextual factors influence the success or failure
of these interventions.
For instance, one contextual factor that might affect outcomes
of the program diagrammed
in Figure 31 .2 is the diversity of the target group. As
Frechtling (2007) observes, this d iver-
sity may include language differences among subgroups, which
need to be accounted for
in developing program m aterials.

fin ally, logic models cannot fully co mp ensate for the rigor of
expe rimental design
when testing the impact of interventions o n outco m es (Frech
tling, 2007) . T he logic
model explicates the critical components of a program and the
processes that lead to
desired outcomes (the program theory of cha nge). The
implementation of the model
provides a test of th e accuracy of the theory. However,
validatio n of the logic model is not
as rigorous a proof as what is established through study designs
employing experimental
or quasi-experimental methodologies. Causality cannot be
determined through logic
models. Alhen possible, an evaluation can be strengthened by
combining the advantages
of logic modeling with experimental design.
Logic Modeling in Practice: Building
Blocks Family Literacy Program
The following provides an example of logic modeling in
practice. The example describes the
use of a program logic model in developing, implementing, and
evaluating the Building
Blocks family literacy program and how client exit data were
then used to revise the model in
a way that more explicitly illustrated the program's path•.vays
to achieving intended outcomes
(i.e., feedback loop; Unrau, 2001, p. 355). The original program
outcomes were to increase
(a ) children's literacy skills and (b) parents' abilities to assist
their children in developing lit-
eracy skills. The sam ple included 89 families who participated
in the 4-week program du ring

its initial year of operation. The following describes the process
by which the logic model was
developed and how the client outcome data were used to fme-
tune the logic model.
The family literacy program's logic model was created at a one-
day workshop facili-
tated by the evalua tor. Twenty key stakeholders representing
various constituenc ies,
including program staff (i.e., steering committee members,
administration, and literacy
workers), representatives from other programs (i.e., public
school teachers, child welfare,
and workers and clients from other literacy programs), and oth
er interested citizens, par-
ticipated in the workshop (Unrau, 2001, p. 354). A consensus
decision- making process
was used to reach an agreement on all aspects of the process,
including the program pur-
pose, the prog ram objectives, and the pro gram activities.
During the workshop, stakeholders created five products that
defined the program
parameters and info rmed the focus of the evaluation. These
products included an organi-
zational chart, the beliefs and assumptions of stakeholders about
client service delivery,
the questions for the eval uation, the program's goals and
objectives, and the program
CHAPTER 31 • l OGIC MoDElS 559
activities. The program goals, objectives, and activities were
then used to develop the orig-

inallogic model.
One of the evaluation methods used to assess client ou tcomes
was to conduct semi-
st ructured phone interviews with the parents after families
completed the program.
Random select ion procedu res were used to identify a su bset (n
= 35 or 40o/o) from the
list of all parents to participate in the interviews. Random
selection procedures were used
to ensure that the ex-periences of the interviewees represented
those of all clients served
during the evaluation time period. Relative to the two program
outcomes, respondents
were asked to provide examples of any observed changes in
both their children's literacy
skills (Outcome 1) and their ability to assist their children in
developing literacy skills
(Outcome 2; Unrau, 2001, p. 357). The co nstant comparison
method was used to analyze
the data (Pa tton, 2002 ). In this method, meani ngful units of
texi: are assigned to similar
categories to identify common themes.
What emerged from the parent interviews was more detailed
information about how
the two inten ded outcomes were achieved. Parent experiences
in the program suggested
four additional processes that li nk to reaching the two final
outcomes. Thi s infor mation
was added to the original logic model to more fully develop the
pathways to improving
children's literacy skills through the family literacy program.
These additional outcomes
were actually steps toward meeting the two originally intended
outcomes and thus iden-

tified as intermediate outcomes and ne-cessary steps toward ach
ieving the or iginally stated
long-term outcomes. Figure 31.3 provides a diagram of the
revised logic model. The
shaded boxes represent the components of the original logic
model. The other compo-
nents were added as a result of the parent exit interview data.
Input j I Activities I Short-Term Outcomes I [ Intermediate
Outcomes J I Long-Term :Outcomes j
Improve child's
behavior
Increase parent's
own literacy skills
Figure 31.3 Example of a Revised Program Logic Model for a
Family Literacy Program
SOURCE: Unrau (200 1}. Copyright November 21 , 2007 by
Elsevier limited. Reprinted with permission.
NOTE: The shaded boxes represent the logic model's original
components. The other boxes were added as a result of feedback
from clients
after program compl etion.
560 PART V • CONCEPTUAL R ESEARCH
While the parent in terview data were useful in revising the
program logic about client
change, it is important to interpret this process withi n the app
ropriate context. This part

of the evaluation does not provide evidence that the program
caused client change (Rossi
et al., 2004). This can only be determined through the use of
experimental methods with
random ass ignmen t. Nonetheless, these paren t data contr ibute
to developing a mo re fully
developed model fo r unde rstanding how fam ily literacy
programs wo rk to improve out-
comes for children. Experimental methods can then be used to
test the revised model for
the purpose of es tablishing the causal pathways to the intended
outcomes.
Conclusion
The purpose of this chapter was to introduce the rea der to logic
models and to the logic
modeling process. Logic models present an illustration of th e
components of a program
(inputs, activities, outputs, and outcomes) and how these
components connect with one
another to facilitate participant change (pro gram theory). They
are tools to assist key
stakeholders in program plann ing, program implementation and
monitoring, and espe-
cially program eva lu ation. They can also be used as
communication tools in expla ining
program processes to key stakeholders external to the program.
Creating a logic model is
a time-consuming process with a number of potential
challenges. Nonetheless, a well-
developed and thoughtful logic mo del is likely to ensure a
program's success in reaching
its intended outcomes.
References

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Chinrnan, M., Imrn, P., & Wandersman, A. (2004). Geuing to
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Dvvyer, J. J. M., & Makin, S. (1997) . Usi ng a program logic
model that focuses on perfo rmance mea-
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Frechtling, J. A. (2007). Logic modeling methods in program
evaluat.ion. San Francisco: Jossey-Bass.
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services programs: A guide for policy make1·s and providers.

Wash ington , DC: The Urban
Institute.
McLaughlin, J. A. , & Jordan, G. B. (1999) . Logic models: A
tool fo r tell ing you r program's pe rfor-
mance stor y. Evaluation and Program Plar~ning, 22, 65- 72.
McLaughlin, J. A., & Jordan, G. B. (2004). Using logic models.
In J. S. Wholey, H. P. Hatry, & K. E.
Newcomer (Eds.), Handbook of program evaluatiOn (pp. 7- 32).
San Francisco: )ossey- Bass.
Mertinko, E., Novotney, L. C., Baker, T. K., & Lange, J.
(2000). Evalual'ing your program: A beginner's
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Patton, M. (2002). Qualitative research and evaluation methods
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depression scale for research in the general
popuJation. Applied Psychological Measurement, 3, 385-401.
Rossi, P. H., Lipsey, M. W., & Freeman, I I. E. (2004) .
Evaluation: A systematic approach. Thousand
Oaks, CA: Sage.
United Way of America. (1996). Measuring program outcomes:
A practical approach. Retr ieved
N ovem ber I I, 2007, from ww·w.unitedway.o rg/Outcom

es/Resources/MPO/iudcx.cfm
Unrau, Y. A. (2001). Using client exit interviews to ill uminate
outcomes in program logic models: A
case example. Evaluation and Program Planning, 24, 353-361.
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W. K. Kellogg Foundation . (2001) . Logic model development
guide. Retrieved November Jl , 2007,
fr om h ttp://www. wkkf.org/d efau lt.aspx?tabid= l 01 &Cm
=28l&Catl0=28 l &ltemTD- 28 13669&
N ID= 20&La nguageiD=O
http:/ /www.wkkf.org
Web site from theW. K. Kellogg Foundation conta ining useful
templates and exercises in developing
a logic model for a resea rch proj ect.
http:/
/www.unitedway.org/Outcomes/Resources/MPO/index.cfm
Web site from the United Way's Outcome Mea su rement
Resource Network, demonstra ting th e use of
logic models in cla rifying and com municating outcomes.
http:/ /www.cdc.gov/eval/resources.htm#logic%20modcl

Web site from the Centers for Disease Control and Prevention's
Evaluatio1 Working Group, containing
logic model resources.
1. Define the term logic model.
2. Describe th e difference between program activities, program
outputs, and program outcomes.
3. Discuss the purpose of including lines with arrows in logic
models.
4. Discuss the relationship between a program's theory of
change and its logic model.
5. Describe the uses of logic models.

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