Quantitative vs. Qualitative Research
Research can be performed two ways, and both methods are defined by the type of variables that are collected as data (see Table 3.3). Quantitative research is performed by evaluating numbers and numeric variables that result in measurable data. Qualitative research is performed by evaluating nonnumeric variables. Qualitative data are collected through descriptive characteristics that cannot be measured with numbers—observation, open-ended questions, or interview. It is through these nonnumerical variables that the research question can be answered. The type of research that is performed is determined by the researcher when developing the conceptual framework.
Qualitative vs. Quantitative Research
|Qualitative Research||Quantitative Research|
|Numerical dataMeasurable data collected (numbers and numeric variables)||✓|
|Nonnumerical dataData are most often collected through observation, open-ended questions, or text-based interviews||✓|
Quantitative research relies on measurement using the scales described previously— nominal level of measurement , ordinal level of measurement , interval level of measurement , and ratio level of measurement . The data collected are analyzed using statistical analysis to answer the research question. The type of statistical analysis used is determined when constructing the research question. Quantitative research generates numbers. The numerical information collected is reflective of the variable being analyzed. For example, gender is collected in many research studies. “Male” or “Female” is not numerical, but if 100 participants were enrolled and 40 were female and 60 were male, then the variable of gender becomes numeric. Once it is numeric, it can be manipulated and applied to all levels of measurement (see Table 4.4).
Variables for Each Level of Measurement
|Variable||Nominal Level of Measurement||Ordinal Level of Measurement||Interval Level of Measurement||Ratio Level of Measurement|
|X||Rank||60||60/10060 males out of 100 participants60%|
|Female||F||40||2nd||40||40/10040 females out of 100 participants40%|
In health care, quality, patient-centered care is provided to all patients. If health care professionals want to prevent hospital-acquired pressure ulcers, the entire population cannot realistically be participants in the study, so a number is chosen that is reflective of the entire population. Many large clinical trials can enroll up to 25,000 or more participants nationally. For health care research, that number is far too large.
When performing research, health care professionals usually formulate a hypothesis in regard to a problem. The researcher may choose a percentage of the population of the hospital served, or a number is chosen that is sufficient to obtain results. Saturation, a term used with qualitative research, occurs when enough data have been collected to support results of the study. Results of a research study have generalizability, meaning the results can be applied accurately to the general population. When generalizability is present, the quantitative research study is well-designed, and the results can be applied to the general population.
In qualitative research, data are most often collected through observation, open-ended questions, or interview. Data collected are words and not numbers. The researcher compiles lists of words, behaviors, and responses from participants as well as observational videos. The data collected is representative of commonalities observed. Participants’ rights are respected, and informed consent may be obtained if performing observational research. In order to maintain validity and reliability in qualitative research, rigor must be maintained. Rigor is consistency in data collection, as well as accuracy; as in the attention to all details. When rigor is maintained, the findings of the qualitative study are proven to be true and reliable.
If a qualitative study of handwashing compliance in the intensive care unit were being performed, the researcher would be present in the intensive care unit observing staff and taking notes or video of staff washing their hands. Qualitative research can be difficult because observation or interviewing can be very time consuming. Many times, the sample size may be small because of the massive amount of data collected for the study. If the sample size is too large, there would be a lot of redundancy. Redundancy occurs when information collected is repetitive, so no new information needs to be collected. One can say the sky is blue so many times that no one needs to say it again, at which point no new data is being generated. This is called the saturation point ,which occurs when no new data is being generated and the endpoint of the qualitative study is defined. When performing qualitative research, the investigator may get to the point where no new information is being obtained and decides that saturation has been met. This may be sooner than the expected end date or later than the predetermined end date, but once no new information is being generated, the investigator can call an end to the study. Table 4.5 reflects common terms in qualitative and quantitative research. While there are some terms that are used in both methods, some are more in one.
Qualitative and Quantitative Research Terms
|Qualitative Research||Quantitative Research|
|Enrolls Human Subjects||✓||✓|
|Statistical Data Analysis||✓|
Note. *There may be certain circumstances when informed consent and Institutional Review Board (IRB) approval are not required
Qualitative studies are usually completed when the end date is reached, or the point of saturation occurs. The investigator of a qualitative research study is deeply involved in the study and many times will make decisions regarding the course of the study as the data collection evolves. Because qualitative research consists of words and not numbers, analysis takes place through the development of commonalities and themes.
· Phenomenology is considered empirical research because data are collected through observation and experiences. It can be through direct contact with what is being observed or through indirect contact, which is solely observation.
· Grounded theoryis research that takes first person observations or interviews and develops a theory or concept about the population being observed.
· Ethnography is a type of qualitative research that studies cultures, everyday life, and cultural changes through observation or interview.
Well-designed qualitative research has transferability as well as generalizability. Transferability is the ability to apply the results of the qualitative study to similar experiences and similar groups of people. It goes hand-in-hand with generalizability in using these aspects of research studies to be well designed and fairly accurate. Transferability demonstrates claims and connections of the qualitative research that was performed. Generalizability is the ability of the results to be applied to people and situations.
A systematic review is a type of literature review in which information is collected from similar completed research studies and summarized. Before starting a systematic review, the researcher must have an objective as to why the review is being performed. There must be clear criteria and well-defined characteristics as to what types of studies are going to be reviewed and what characteristics are going to be collected. The systematic review is a nonexperimental research study because nothing new is being introduced. A meta-analysis is a statistical method used to evaluate multiple studies.
In statistics, prevalence is used to describe data collected regarding the number of health care related illnesses, conditions, and outcomes that commonly occur in a population. Prevalence is the number or percentage of the population that has a disease or health care related illness or problem over a specific period of time. This data is responsible for much of the research performed by nursing. Health care professionals want to provide quality, patient-centered care, and one way to improve care is to research common problems for better solutions. Every month, most hospitals and health care facilities report specific data as required to the Centers for Medicare & Medicaid Services (CMS), the Joint Commission (TJC), and the Agency for Healthcare Research and Quality (AHRQ). New protocols and procedures have been found by investigators as a result of the data reported and the analysis of the data collected. In health care, much of the data is collected to assure that quality of care is delivered.
Quality indicators include occurrence of hospital-acquired pressure ulcers, inpatient falls with and without injury, hospital-acquired pneumonia, and patient satisfaction. Some of the quality measures are collected in patient satisfaction surveys, which are sent out monthly. Patient satisfaction surveys include collecting data on nurse-doctor communication, nurse-patient communication, and pain management. Each month this data is reported to CMS, TJC, and AHRQ. The results of quality indicator reporting are posted monthly on most inpatient hospital units. As health care providers, knowing and adjusting care based on the results of data collected for quality measures is paramount to improving the quality of care provided to patients.
Another method of qualitative research is the case study. Case studies can be performed on an individual case or a group of similar cases. By researching and describing everything associated with a specific case, the researcher is able to get very specific details and data that could contribute to knowledge regarding the specific problem being investigated. Case studies are valuable, but when compared to the results of a randomized control study the results are not as valued. The hierarchy of evidence, sometimes called levels of evidence, is assigned to the different types of research designs that are used to perform research. Each research design has a value according to the strength of the results. Randomized controlled studies are considered the best approach to study the “efficacy and safety of a treatment” (Kabisch, Ruckes, Seivert-Grafe & Blettner, 2011, p. 663) (see Figure 4.8).
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