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College of Public Health and Human Sciences

Learn about the different types of evaluation, why evaluation is important, and how to design a comprehensive evaluation plan for public health policies. Presented by Dr. Jangho Yoon, this session will cover measurement techniques, perception measures, and experimental design. Join us on August 23, 2013, at the College of Public Health and Human Sciences.

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College of Public Health and Human Sciences

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  1. College of Public Health and Human Sciences Public Health Policy Institute Making a Policy Evaluation Plan Presenter: Jangho Yoon, PhD Date: August 23, 2013

  2. Evaluation

  3. Types of evaluation

  4. Why? • Improved decision making When? • All phases of program development and implementation

  5. Evaluation tool

  6. Major realms and components

  7. Measurement • Program effects must be measured accurately. • Numbers • The number of people served by the program, dollars budgeted and expended by the program, net value in cost analysis, etc. • Rates • A ratio of two measures • Standardization: clients served per dollar spent. • Useful for making comparisons across a number of similar programs of substantially different size. • Prevalence and incidence • Prevalence: the number of people at any time who actually show evidence of a disease. • Incidence: the number of people who succumb to the condition or disease within a given time range.

  8. Measurement • Perception • Represents a broad category of measures that are generally defined along ordinal or interval scales. • A common measure of attitudes, beliefs, or perceptions, uses a five-point scale: e.g., (1) strongly disagree; (2) disagree; (3) neutral; (4) agree; (5) strongly agree. • Particular measures may be more or less appropriate in certain settings. • Rates are more useful in discussing geographic areas or programs. • Perception measures are often more useful when the individual is the unit of analysis.

  9. Designing evaluation • Pretest-posttest, single-group design • Limitations • Experimental design • Pinnacle of evaluation research efforts.

  10. Pretest-posttest, single-group design • Effect of program: (OP2 – OP1) . T1 T2 P OP1 X OP2

  11. Design problems • Suppose a health department implement a program to promote regular leisure-time physical activity.

  12. Design problems • Additional events–Something else caused the outcome. • Time trends (or maturation)–It is due to general “upward” time trend in physical activity. • Drop-outs–Participants dropped out of the program during the evaluation time period. • Regression to the mean–Statistical phenomenon that occurs whenever you have a nonrandom sample from a population and two measures that are imperfectly correlated.

  13. Regression to the mean

  14. Experimental design • Pretest-posttest design with treatment and control groups • Effect of Program: (OP2– OP1) – (OC2– OC1)

  15. Experimental design • Multiple group pretest-posttest design

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