Comment 1

A research experiment need a research design. The design helps the researcher stay on track. Experimental research design works like an instruction manual that researchers follow during the experimentation process. The design lists how the experiment was conducted to determine its effectiveness and success (Reference, 2018). Experimental designs can be “simple or complex and have been developed for studies focused on examining causality” (Grove, 2081). An example of an experiment is the effect of chlorohexidine mouthwash on the prevention of ventilator associated pneumonia on ICU patients. The research is controlled, manipulated and random.

Nonexperimental designs are descriptive and correlational. They focus is on “examining variables as they naturally occur in environments and not on the implementation of a treatment by the researcher”(Grove, 2018). It is not controlled or manipulated. An example of descriptive design is assessing Multiple sclerosis, its frequency of symptoms and treatment during the disease.  A correlational example could be the effects of second hand smoke on non-smokers.

Comment 2

Sampling is choosing a determinate within a research study. There are many steps in the process of choosing a sample. “Sampling theory was developed to determine the most effective way of acquiring a sample that accurately reflects the population under study” (Grove, Gray, & Burns, p.278, 2015). The subjects in a qualitative study are called participants, they are not chosen by random sampling as in quantitative studies. The sampling for a qualitative study is usually smaller in size. “Data collected for quantitative studies are numerical.Numerous methods exist for data collection including observation, scales, and questionnaires” (GCU, 2012). Quantiative studies generally require a larger amount of participants because the results are based on numbers and percentages. The sampling process comprises several stages. Defining the population of concern, specifying the sampling frame, specifying a sampling method for selecting the items of events from the sampling frame, determining the appropriate sample size, implementing the sampling plan, sampling and data collecting, and data that can be selected. 

An example of sampling in a qualitative study would be a collection of participants to discuss their opinions, perspectives and feelings on a subject matter, like family members to hospice patients and their experiences with palliative care. An example of sampling in a quantitative study would be participants with same medical history with the same objective or goal in their health, like type 1 diabetes ages 19-24 in a research study on how glycemic control is obtained.

Generalizability is taking the same study used in a smaller sample and applying it to a larger population (Grove, Gray, & Burns, 2015). An example of this would be the results of a study of male patients with the diagnosis of MS in a specific state can be generalized to a larger population of male patients with diagnosis of MS in the nation.