Posted: March 18th, 2022
My research is being designed to investigate the efficacy of a culturally appropriate and targeted diabetes education program on the reduction of A1C levels after six months. The population I am focusing on is Asian Americans with Type II diabetes, within a specific age range. My hypothesis is that after three months of the program, the A1C levels of the experimental group will be lower than they were prior to starting the program.
Because I intend to measure the same population of people before and after the intervention, the ideal methodology to be used would be a pre/post test. I would like to employ quantitative research methods regardless, particularly for measuring the dependent variable (A1C levels). This is a unifactorial study, focusing only on one diabetes factor (A1C levels), making it relatively straightforward. Another way I can approach this study is to design a correlational study in which I compare two different samples of Asian Americans with diabetes. However, the pre/post method controls for intervening variables because it is testing the exact same group. I need to operationalize the education intervention and clearly define how it will be implemented in the research.
The opposite methodology, such as qualitative methods, may be useful if I were to change my research question. Qualitative methods used may include interviews or case studies. For example, in addition to measuring A1C levels, I would also measure patient perceptions of the program, and other subjective markers. It might be helpful to do so in order to determine whether the program needed to be redesigned. Both qualitative and quantitative methods are efficacious in evidence-based practice but not all research questions can be appropriately designed as quantitative studies. I happen to have a research question that does lend itself to quantitative analysis.
Patient perceptions of health and wellness, of treatment interventions, of nursing staff and hospital facility, and of quality of care all have a bearing on patient outcomes. Healthcare institutions and their administrators have long known that “patient perception is reality,” (Koska, 1989, p. 40). To improve healthcare outcomes, administrators and nurses need to change patient perceptions. Changing perceptions can be challenging, but in some cases entails low-cost or no-cost changes to human resources policies and the environmental design of healthcare institutions (Balfour, 2012).
A person’s epistemology or way of knowing also informs perceptions. Thus, a patient’s worldviews, values, attitudes, background, and beliefs will all impact how that individual perceives healthcare delivery and health itself. The subjective way of knowing is all about perceptions, not about measurable, verifiable reality. For example, many patients do not care about numbers in their chart or whatever percentage of persons benefitted from a specific treatment intervention. The patient also cares more about how the nurse communicates, and whether eye contact or touch was used, and less about whether the nurse referred to clinical studies before recommending a course of treatment. What the patient cares about is how they feel, and whether their perceptions align with their expectations. Nurses need to understand the salience of subjective reality.
If patients had an objective paradigm of the world, they would have a detached view towards their health and treatment options. They would make decisions based on calculations and algorithms, not on psychological motives. Even nurses who are guided by evidence-based practice models still do operate within a subjective paradigm of the world. It is important to recognize the difference between subjective and objective ways of knowing when making improvements to care delivery.
The different levels of evidence point to a hierarchy of credibility within the corpus of nursing research. Level One evidence is considered the most robust: including meta-analyses and systematic reviews. Evidence like this reflects a wide range of experimental research designs with a high degree of external and internal validity. The performance of a meta-analysis or systematic review widens the population sample exponentially, allowing researchers to determine more readily if there is a causal relationship between variables or how to definitively identify patterns in the research. Advantages to using this method are clear: there is little to refute the results of the claims. The only problem is that few issues in healthcare are covered completely with Level One evidence. Level One evidence is not always going to be available to access. As a researcher, it can be extremely difficult and costly to conduct this type of research, too. Yet I have used this method in my current practice when attempting to offer support for a particular treatment intervention.
Level Two evidence includes randomized controlled trials conducted at multiple sites, with large population samples and tight controls (“Evidence-Based Practice Toolkit,” n.d). Second only to Level One evidence in terms of reliability and validity, this method is useful when seeking information about the efficacy of a treatment intervention.
Other levels of evidence include quasi-experimental research, cohort studies, and qualitative research, none of which is as robust or useful as Level One or Level Two research. Understanding the different levels of evidence are important for selecting empirical articles for my ROI, and for any other healthcare application. The higher on the Level of Evidence hierarchy, the more reliable the data, and therefore the better my own work will be.
The barriers to transforming research into practice can be frustrating at times, but at other times, completely understandable if not wholly reasonable. For one, the research needs to be proven efficacious, reliable, and generalizable enough to warrant changes to practice. One landmark study should not change nursing practice. If that were the case, then nursing practice would be at the risk of changing every day. Not all research designs are solid, and it would be dangerous to change nursing practice haphazardly. Therefore, nurses should always scrutinize research before making policy recommendations.
Oftentimes, the barriers to implementing research into practice are more detrimental than they are helpful. The barriers to implementation include organizational culture, politics, financing, lack of training, patient perceptions, and ineffectual public policy (Haynes & Haynes, 1998). In my own practice, I have seen almost every single one of these barriers come in the way of putting research into action.
For example, organizational culture often puts up barriers to change. Nurses get stick in their ways, set in their routines, and reluctant to make any but the most necessary changes. Laziness or lack of training are other issues that prevent nurses from applying evidence to practice. Administrators sometimes do not do enough, simply asking that nurses make changes to procedures without telling them why or even how.
Sometimes, administrators and nurses want to make changes to practice but are constrained by lack of financial or political support. For instance, if a new technology or tool is needed to make the change, the administration needs the funding. Patient perception can also be a barrier, because if patients are suspicious of a new technique or procedure, compliance rates will be low.
Balfour, W. (2012). Make excellent patient satisfaction a reality. IVantage. https://www.ivantagehealth.com/patient-satisfaction-a-matter-of-perception/
“Evidence Based Practice Toolkit,” (n.d.). http://libguides.winona.edu/c.php?g=11614&p=61584
Haynes, B. & Haynes, A. (1998). Barriers and bridges to evidence based clinical practice. BMJ 317(7153): 273-276.
Koska, M.T. (1989). Satisfaction data: patient perception is reality. Hospitals 63(13): 40.
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