DNP 830 Discussion1 AND 2 Paper
DNP 830 Discussion1 AND 2 Paper
DNP 830 Discussion1 AND 2 Paper
Measuring DPI Project Outcomes
DPI projects are intensive and should accurately demonstrate the status of care quality in a particular setting. As a result, project outcomes should be precise and correctly expressed through different variables. Project leaders should understand the types and levels of the variables used to measure project outcomes and use them appropriately. Errors that can affect judgment should be avoided as much as possible.
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Variables are classified into nominal, ordinal, interval, and ratio levels. The nominal level represents the data that can only be categorized. According to Shreffler and Huecker (2022), nominal data has no natural ranking or ordering since it is discrete and discontinuous. A suitable example of such data is the gender or marital status of research participants. The ordinal variable has clear ordering in the data since it can be categorized and ranked. For instance, care quality can be classified as excellent, good, or poor. The interval variables can be categorized, ranked, and spaced but without a true zero point (Mishra et al., 2018; Fain, 2020). For instance, personality inventories fall into the interval level. The ratio level represents data that can be categorized and ranked with equal intervals and a true zero point. Examples of ratio scales are age and weight.
Some errors can be made by failing to understand the proper use of measurement variables based on the level and type of comparison. Such errors include analysis and statistical errors. Generally, the level at which a variable is measured determines how data is analyzed. As Mishra et al. (2018) further observed, proper knowledge of data categories is crucial to ensure data is analyzed with appropriate statistical methods. This understanding informs researchers on the type of inferential statistics to be performed on the data to refute or prove the hypothesis. Imperatively, the measurement level should be identified even before the data collection process commences.
References
Fain, J. A. (2020). Reading, understanding, and applying nursing research. FA Davis.
Mishra, P., Pandey, C. M., Singh, U., & Gupta, A. (2018). Scales of measurement and presentation of statistical data. Annals of Cardiac Anaesthesia, 21(4), 419–422. https://doi.org/10.4103/aca.ACA_131_18
Shreffler, J., & Huecker, M. R. (2022). Types of variables and commonly used statistical designs. StatPearls Publishing.
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Discussion 1
The DPI Project is conducted using a quantitative method driven by quality improvement. Provide a rationale for using a quantitative method in contrast to other methods (e.g., qualitative method or mixed method). Describe how the quantitative method is in line with quality improvement. Provide evidence supporting your response.
Discussion 2
Define and distinguish among nominal, ordinal, interval, and ratio variables used in the measurement of DPI Project outcomes. Discuss the errors which can be made by failing to understand the proper use of measurement variables based on level and type of comparison.
