MPH 505 Module 3 Goals, Objectives and Logic Model Example

Setting the Targets: Goals, SMART Objectives and a Logic Model for a Diabetes Prevention Program

Student Name

Master of Public Health Program, Aspen University

MPH 505: Public Health Education and Program Oversight

Instructor Name

Month Day, Year

Setting the Targets: Goals, SMART Objectives and a Logic Model for a Diabetes Prevention Program

A program without measurable objectives cannot show whether it worked. Goals state the broad change a program seeks; objectives state exactly what will change, for whom, by how much and by when; and a logic model shows how resources and activities are expected to lead to results. This paper writes the goals, objectives and logic model for the county's new Spanish-language lifestyle class for adults at high risk of type 2 diabetes.

Program Goal

The program's goal is to reduce the development of type 2 diabetes among Spanish-speaking adults with prediabetes on the county's south side. A second goal is to raise awareness of prediabetes in the wider community so that more residents are screened.

What Makes an Objective SMART

Every objective passes the SMART test: it names a specific change, can be measured, is within reach, matters to the goal and carries a deadline. Objectives are written at three levels: process objectives about delivering the program, impact objectives about changes in knowledge, behavior and weight, and outcome objectives about disease. Setting achievable targets requires realistic benchmarks.

Benchmarks From National Results

A participant-level evaluation of the first four years of the National Diabetes Prevention Program, covering 14,747 adults, found a median of 14 sessions attended, 35.5% reaching the 5% weight loss goal, an average loss of 4.2% and 41.8% meeting the goal of 150 minutes of weekly activity; each additional session and each additional 30 minutes of activity were linked to more weight lost (Ely et al., 2017). These figures anchor the program's targets.

Process Objectives

By the end of year one, promotoras will screen 1,500 adults for prediabetes at churches and community events. By the end of year one, 300 adults with prediabetes will enroll in the year-long lifestyle class. By the end of each cohort, at least 60% of those enrolled will have completed 14 or more sessions.

Impact Objectives

By the end of the 12-month class, 35% of participants who attend at least four sessions will lose at least 5% of their starting weight. By the end of the class, 45% of participants will report at least 150 minutes of physical activity per week. By six months, 70% of participants will correctly identify three ways to lower their risk of diabetes.

Outcome Objective

By the end of year three, the rate at which participants progress to diabetes will be at least 40% lower than the expected rate for adults with prediabetes who do not take part, measured through health center records. The trial that established the model found a reduction of 58% (Diabetes Prevention Program Research Group, 2002), but community delivery usually produces smaller effects.

The Logic Model

The logic model links the program's parts.

Assumptions and External Factors

The model assumes that participants can attend evening classes, that health centers will share A1C data and that churches remain willing hosts. External factors that could affect results include food prices, local employment and whether the state Medicaid program covers the lifestyle class. Naming these helps interpret results honestly.

Linking Objectives to Evaluation

Each objective names its data source: screening logs, attendance records, weight measurements at sessions, activity logs, a short knowledge survey and health center records. CDC's 2024 program evaluation framework emphasizes describing the program clearly, including its logic, before designing an evaluation, and engaging partners throughout (Kidder et al., 2024).

Equity in Objectives

Objectives will be tracked separately for men and women, for participants with and without insurance and by age group. The national evaluation found that attendance was the strongest predictor of success, so retention targets matter most for groups more likely to drop out. Reporting results by subgroup ensures the program closes gaps rather than widening them.

Writing Objectives Well

Weak objectives use verbs that cannot be observed, such as understand or appreciate, or omit the population, the amount of change or the deadline. The team rewrote early drafts that read like 'participants will learn about healthy eating' into statements that name who, what, how much and by when. Each objective was checked against the question: at the end of the period, could two people looking at the data agree whether it was met?

Medium-Term Outcomes

Between the short-term and long-term columns sit medium-term outcomes: sustained weight loss at 12 months, maintained activity and lower A1C values at follow-up clinic visits. These matter because weight regained after a program ends reduces its benefit. Health center records will allow the program to check A1C for participants who consent, offering an intermediate measure before diabetes incidence can be assessed.

Community Review of Objectives

The community advisory board reviewed the draft objectives. Members questioned whether 300 participants in year one was realistic given work schedules, and the team kept the target but added weekend classes. Board members also asked that the program measure something residents cared about directly, which led to an added objective on participants reporting that they had more energy for family activities at the end of the class.

Using the Logic Model

The logic model is not a one-time exercise. Staff will review it quarterly to check whether activities are producing the expected outputs and whether assumptions still hold. If screening events draw fewer people than planned, for example, the model makes clear that enrollment and later outcomes will also fall short, prompting early changes such as adding radio segments or workplace screening.

Timeline for Measurement

Process measures will be reviewed monthly, impact measures at six and twelve months of each cohort, and the outcome measure at the end of years two and three. Setting these dates now lets staff plan data collection into their work rather than scrambling at reporting time.

Conclusion

Clear goals, SMART objectives at three levels and a logic model give the program a map and a yardstick. Benchmarks from national results keep targets realistic, and linking each objective to a data source prepares the evaluation. With these in place, the program can move from planning to choosing and adapting its intervention.

References

Diabetes Prevention Program Research Group. (2002). Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England Journal of Medicine, 346(6), 393-403. https://doi.org/10.1056/NEJMoa012512

Ely, E. K., Gruss, S. M., Luman, E. T., Gregg, E. W., Ali, M. K., Nhim, K., Rolka, D. B., & Albright, A. L. (2017). A national effort to prevent type 2 diabetes: Participant-level evaluation of CDC's National Diabetes Prevention Program. Diabetes Care, 40(10), 1331-1341. https://doi.org/10.2337/dc16-2099

Kidder, D. P., Fierro, L. A., Luna, E., Salvaggio, H., McWhorter, A., Bowen, S.-A., Murphy-Hoefer, R., Thigpen, S., Alexander, D., Armstead, T. L., August, E., Bruce, D., Clarke, S. N., Davis, C., Downes, A., Gill, S., House, L. D., Kerzner, M., Kun, K., ... Young, K. (2024). CDC program evaluation framework, 2024. MMWR Recommendations and Reports, 73(6), 1-37. https://doi.org/10.15585/mmwr.rr7306a1