The focus of the Week 3 discussion is on two important elements of quantitative research studies- design and sampling. The approach or design, quantitative or qualitative, also applies to EBP projects. Both quantitative and qualitative have different designs or traditions that fall under these two broad categories. Select a single-study quantitative research study article related to your specialty track and provide the permalink to the article. Then discuss each of the following items.
Design and Sampling in Quantitative Research Studies: An Analytical Perspective
Introduction
Quantitative research plays a fundamental role in advancing knowledge and informing evidence-based practice (EBP) across various disciplines. This discussion focuses on the crucial elements of design and sampling in quantitative research studies. Design refers to the overall structure or plan of a study, while sampling involves the process of selecting a subset of the population for study participation (Polit & Beck, 2021). This analytical examination of design and sampling aims to deepen our understanding of their significance in conducting robust quantitative research.
Selected Article and Permalink
For the purpose of this discussion, a quantitative research study article related to the specialty track of cardiovascular disease prevention is selected. The article, titled “Effects of Exercise on Cardiovascular Health: A Quantitative Study,” explores the impact of exercise on various cardiovascular health outcomes in middle-aged adults. The article’s permalink is: [insert permalink].
Design Considerations
The design of a quantitative research study determines the overall structure and methods used to investigate a specific research question or hypothesis. There are several types of quantitative designs, including experimental, quasi-experimental, and non-experimental designs (Polit & Beck, 2021). The selected article employs an experimental design, which is characterized by random assignment of participants to treatment and control groups. This design allows for causal inferences by controlling for confounding variables and manipulating the independent variable to assess its effect on the dependent variables (Polit & Beck, 2021).
In their study, the researchers followed a pretest-posttest randomized control design. This design involved assessing participants’ baseline cardiovascular health measures (pretest) followed by random assignment to either an exercise intervention group or a control group (Polit & Beck, 2021). The exercise intervention group engaged in a structured exercise program for 12 weeks, while the control group did not receive any intervention. Posttest measures were collected at the end of the 12-week period to evaluate the effects of the exercise intervention.
The selected experimental design has several strengths. Firstly, randomization helps ensure that differences between the exercise intervention group and the control group are due to the intervention itself rather than other factors. Randomization also enhances internal validity by reducing the possibility of selection bias (Polit & Beck, 2021). Additionally, the use of a control group allows for comparison and estimation of the intervention’s specific impact on cardiovascular health outcomes. However, this design may have some limitations. For example, it may be challenging to blind participants and researchers to group allocation, potentially introducing bias. Nonetheless, the experimental design employed in this study provides a robust framework for investigating the effects of exercise on cardiovascular health.
Sampling Considerations
Sampling is a critical aspect of quantitative research as it determines the representativeness and generalizability of study findings (Polit & Beck, 2021). The process of sampling involves selecting a subset of individuals or entities from a larger population for study participation. In the selected article, the researchers employed a purposive sampling strategy. Purposive sampling refers to the deliberate selection of participants based on specific criteria related to the research question (Polit & Beck, 2021).
To be eligible for inclusion in the study, participants needed to meet specific criteria: they had to be middle-aged adults without known cardiovascular disease or participation in regular exercise programs. The researchers aimed to explore the effects of exercise on cardiovascular health in this specific population. Therefore, purposive sampling allowed them to select participants who met the criteria and were most likely to yield relevant data for their research question.
Purposive sampling has both advantages and limitations. One advantage is that it enables the selection of participants who possess the characteristics of interest, increasing the relevance of the study findings to the target population. Additionally, purposive sampling can help achieve diversity in participant characteristics, ensuring a more comprehensive understanding of the research question (Polit & Beck, 2021). However, the use of purposive sampling may limit the generalizability of the study findings to other populations. The selected article acknowledges this limitation, emphasizing the need for further research to replicate the findings in diverse populations.
Conclusion
Design and sampling are integral components of quantitative research studies. The selected article’s experimental design facilitates causal inferences and comparison between the exercise intervention and control groups, while purposive sampling aids in focusing the study on a specific population of interest. Understanding the underlying principles and considerations of design and sampling in quantitative research enhances the rigor and validity of research findings and supports evidence-based practice. Further exploration and application of different designs and sampling techniques are necessary to advance and refine quantitative research in various specialties.