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 intervention 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 work. 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 implementation 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 is 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

Bahr, S., Hoffman, J., & Yang, X. (2005) . Parental and peer influence on the risks of adolescent drug use. journal ofPrirnary Prevention, 26, 529- 551.

Bickman, L. (1987) . The function of program theory. In L. Bickman (Ed .), New directions in evalu-ation: Vol. 33. Using program theory in evaluation (pp. 1- 16). San Francisco: Jossey- Bass.

Brown, E. C., Hawkins, J. D., Arthur, M. W., Briney, J. S., & Abbot t, R. D. (2007) . Effects of Comm un ities that Care on prevention services systems: Findings from the Community Youth Devcloprnenl sLudy at 1.5 years. Prevention Science, 8, 180-191.

Chen, H.-I., & Ross i, P. H. (1983) . Evaluating with sense: The theory-driven approach. Evaluation Review, 7, 283- 302.

Chinrnan, M., Imrn, P., & Wandersman, A. (2004). Geuing to outcomes 2004. Santa Monica, CA: RAND Corporation.

Dvvyer, J. J. M., & Makin, S. (1997) . Usi ng a program logic model that focuses on perfo rmance mea-surement to develop a program. Canadian journal of Public Health, 88, 421-425.

Frechtling, J. A. (2007). Logic modeling methods in program evaluat.ion. San Francisco: Jossey-Bass. Harrell, A., Burt, M ., Hatry, H ., Rossman, S., & I"l.oth, J. ( 1996). Evaluation strategies for human

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 self-evaluation workbook for mentoring programs. Potomac, MD: Information Technology International.

CHAPTER 3 I • l OviC Moons 561

Patton, M. (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, CA: Sage. Radloff, L. S. (1977). The CES-D scale: A self-report 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. Watson, S. (2000). Using results to improve the lives of children and families: A guide for public-private

child care partnerships. Retrieved ~ovember 11, 2007, from www.nccic.acf.hhs.gov/ccpart:nerships/ resource.htm

Wholey,) . S. (1987) . Evalu ability assessment: Developing program theory. In L. Bickman ( Ed.), New directions in evaluation: Vol. 33. Using program theory in evalua.tio11 (pp. 77 92) . Sa n Francisco: Jossey-Bass.

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.