Step 5 Checklist

Step 5: Generate and Support Conclusions

In this step, evaluators analyze data, interpret findings, and generate conclusions and recommendations to answer your evaluation questions established in Step 3. You are going beyond data reporting to explore what the findings mean.

Applying the Cross-Cutting Actions and Evaluation Standards

As with all the evaluation framework steps, it is important to integrate the cross-cutting actions and evaluation standards when generating and supporting conclusions in Step 5. See Table 9 in the CDC Program Evaluation Framework, 2024 to determine if you have effectively applied the cross-cutting actions and evaluation standards.

Review Expectations with Interest Holders

☐ Refer to expectations identified in Step 4

Planning Data Analysis

☐ Plan data analysis and interpretation (relies upon earlier steps and should occur prior to implementation)

☐ Develop an analysis plan, minimally including (refer to Table 5.1, Table 5.2, and Worksheet 5A in the Action Guide):

• What data to analyze
• Analysis to be performed
• When it should be performed
• By whom it will be analyzed

☐ Identify appropriate analytic tools (i.e. data analysis software)

☐ Assess whether you have followed the data and analysis plan developed prior to data collection

• Make note of where you may have deviated from the original plan and why
• Communicate this to interest holders before conducting your data analysis

☐ Identify the steps taken to systematically protect privacy and confidentiality during data analysis

☐ Reflect on how scientific rigor and objectivity have been upheld in your evaluation plan and methodologies: Are there areas for improvement?

• If so, improve identified areas of the evaluation where possible and make note of any outstanding areas for improvement that can be included in your final evaluation report

☐ Ensure your selected methods were chosen based on the evaluation questions you intend to answer and the traits of the collected data

☐ Determine if you require analytic experts (e.g., statisticians) to ensure accurate and credible analyses

Conducting Data Analysis

☐ Develop data codebooks

☐ Analyze your data using appropriate techniques that interest holders and the evaluation team have decided are the most meaningful for the evaluation

☐ Check for data errors and consistency, both in your collected data and when running your analyses

Interpret Analytic Findings

☐ Synthesize analytical results with other relevant sources (e.g. program standards)

☐ Compare interest holder expectations identified in Step 4 with your results to inform your interpretation

☐ Identify what contextual factors (Step 1) and limitations should inform your analysis and conclusions

☐ Identify any existing strengths, areas for improvement, and/or best practices

☐ Consider how existing literature, scientific theories/models or evidence base (if applicable) can help in interpreting your findings

☐ Form conclusions, which should answer (wholly or in part) at least one of your evaluation questions

Forming Recommendations

☐ Ensure all recommendations are:

• Clearly worded

• Provide multiple potential options for action

• In alignment with potential users' roles and responsibilities

• Feasible to implement in context

☐ Prioritize your recommendations in collaboration with interest holders:

• Develop recommendations that are feasible to implement

• Limit the number of recommendations you provide in your final evaluation report to increase uptake/adoption