Start here
If you’re early in your DNP project, this page is for you. It covers what a DNP project is, how this site is organized, and the decisions that are much easier to get right now than to fix later.
What a DNP project is, and isn’t
A DNP project usually puts existing evidence to work in a real practice setting and evaluates what happened. It is not a PhD dissertation. Its main job isn’t to generate new knowledge, but to show that you can translate evidence into practice and judge the results.
Beyond that, programs differ a great deal. What counts as an acceptable project, which frameworks you must use, what review your project needs, and what your final product looks like are all set by your program. Your program’s handbook and your faculty advisor are the final word.
How this site is organized
By stage. The Roadmap follows a project from defining the problem to sharing what you learned. Each stage lists what to check before you move on.
By project type. Project Types covers ten common kinds of DNP projects and the problems each one tends to run into.
Free tools. The tools help you find your project type, choose a statistical approach, and read a run chart. They run in your browser.
Ten things to settle before you start
- Your problem shows up in local data you can actually get. Evidence from the literature isn’t enough. You need a baseline from your own setting. Read the guide
- Your outcome can change within your timeline. Some outcomes move slowly. Check before you commit. Read the guide
- Your measure captures what you mean. Easy-to-get data can measure something close to, but not the same as, what you care about. Read the guide
- You have outcome, process, and balancing measures. One number rarely tells the whole story. Read the guide
- You’ll use the same instrument, the same way, every time. Changing the questions or how they’re given makes before and after hard to compare. Read the guide
- You can link each person’s before and after responses, or you’ve planned for not linking them. This choice affects your sample size and your analysis. Read the guide
- You have permission to use your instrument. Published instruments often require it. Read the guide
- You know what review your project needs. Whether it counts as quality improvement or research, and who decides, varies by institution. Read the guide
- Your data layout and codebook are ready before you collect. Fixing a messy spreadsheet after the fact costs far more time. Read the guide
- Your analysis is chosen and approved before you collect data. It should follow from your design and your data, not from the results. Read the guide