Chapter 21: Generating Evidence Through Quantitative Analysi ✓ Solved

Chapter 21 Generating Evidence Through Quantitative and Qualitative

Research is external evidence. Quantitative research—the investigation of phenomena using manipulation of numeric data with statistical analysis. Emphasizes precise measurement of variables. Use the most rigorous methodology possible. Types of quantitative research include: Randomized controlled trials (RCTs), controlled trials without randomization, case-controlled studies, cohort studies, and descriptive studies.

Identify who will be the principal investigator (PI)—the person responsible and accountable for overseeing all elements of the research study. Create the team and bring them together for a research design meeting. The team will address issues around study design, feasibility, outcomes (“So What?” outcomes), inclusion/exclusion criteria, and how the integrity of the intervention will be maintained.

Answer to Question #1: The primary consideration when deciding if a clinical question merits research is whether the question has been addressed by earlier research. This statement is false. Rationale: A researcher should prioritize the question of whether the answer would improve patient outcomes. The existing knowledge base must be assessed, but the potential impact on patients is central.

Steps in designing a quantitative study include: formulate the study question, establish the significance of the problem, search and appraise aggregated evidence, determine a theoretical or conceptual framework, generate hypotheses when appropriate, select the appropriate research design, identify the sample to enhance external validity, determine measures, outline the data collection plan, apply for human subjects approval, implement the study, prepare and analyze the data, interpret the results, disseminate the findings, and incorporate findings into evidence-based practice and evaluate outcomes.

Factors to consider in determining a quantitative study design include the significance of the question, the “So What?” factor, and feasibility, which asks if the study can be conducted in a reasonable time frame, whether there are enough potential subjects, if recruitment settings are accessible, if the lead person has enough time and expertise, whether there are legal or ethical constraints, and if adequate resources are available.

A theoretical or conceptual framework is comprised of interrelated statements that attempt to describe, explain, and/or predict a phenomenon. The framework guides the selection of important study variables, construction of interventions, development or search for appropriate measurement instruments, type of data analyses performed, and explanation of the findings.

Nonexperimental studies are often used to describe, explain, or predict a phenomenon when it is undesirable or unethical to manipulate the independent variable. Experimental research designs include randomized controlled trials (RCTs), which are the “Gold Standard” for evaluating the effects of a treatment or intervention and provide the strongest evidence to support cause-and-effect. RCTs must meet certain criteria: the independent variable must precede the dependent variable in time, there must be a strong relationship between them, and other explanations for the relationship must be eliminated.

Quasi-experimental designs can manipulate the independent variable but may lack random assignment or a control group. Other types of designs include pre-experimental studies and comparative effectiveness trials, which seek to determine which of at least two established healthcare interventions are more effective.

Internal validity threats include attrition, confounding variables, nonadherence, history, maturation, and testing. Strategies to mitigate these threats involve careful planning and design, including random assignment, user-friendly study designs, and thoughtful measurement approaches.

Sampling is key to external validity and requires defining the theoretical population, assessing the available population for recruitment, and using appropriate sampling strategies such as random or stratified sampling. Sample size estimates must account for attrition to avoid type 2 errors when concluding group differences.

Qualitative research seeks to understand a phenomenon or lived experience, using methods like interviews, focus groups, and observational studies. Data is analyzed thematically and presented in words rather than numbers.

Paper For Above Instructions

Research methodologies play a vital role in generating evidence that informs clinical practice, policy-making, and healthcare delivery. This paper discusses the importance of both quantitative and qualitative research methods in generating sound evidence for practice. The clarity and integrity of research processes are foundational in ensuring that the resulting evidence is valid, reliable, and applicable.

Quantitative research is celebrated for its ability to manipulate numeric data and apply statistical analysis, which allows researchers to ascertain clear, measurable outcomes. This method is built on specific protocols and rigorous methodologies, ensuring that findings can be replicated and validated. A principal investigator (PI) oversees the entire research process to ensure adherence to methodological rigor and ethical standards, which is crucial for the trustworthiness of research outcomes.

The research design process starts with formulating a clear study question, followed by assessing the problem's significance. Only then should researchers delve into existing literature to determine what has already been established in their field. Theoretical and conceptual frameworks guide researchers through this process, helping to define the scope of the study and tailor interventions and measurement instruments for optimal data collection and analysis.

Experimental designs, particularly randomized controlled trials (RCTs), are considered the gold standard in research as they provide compelling evidence for cause-and-effect relationships. RCTs' strength lies in their capacity to control for confounding variables through random assignment, leading to robust findings applicable across populations. Feasibility studies further support the planning process by identifying potential participant availability and ensuring resources are adequate.

On the other hand, qualitative research emphasizes understanding the context and lived experiences of participants. Through methods such as interviews and focus groups, qualitative research provides depth to findings and highlights factors that quantitative studies may overlook. This methodology allows researchers to capture the complexities of human behavior and make sense of the subtleties in clinical settings.

The balance of quantitative and qualitative research approaches is paramount. For instance, when significant descriptive and predictive studies exist regarding the effects of early term delivery on breastfeeding success, moving towards experimental studies represents a progression that adds to the existing body of research. Experimental studies help to identify interventions that can positively impact outcomes while providing a deeper understanding of the quantitative data.

Understanding the threats to internal validity is essential for any research design. Factors such as attrition, history, and nonadherence can skew results, leading to inaccurate conclusions. Proactive strategies, such as maintaining communication with participants and designing user-friendly protocols, can mitigate these risks and enhance the overall integrity of the study.

External validity also hinges on the representativeness of the sample. Researchers must ensure that their sampling methods accurately reflect the larger population to which they hope to apply their findings. Using strategies such as stratified sampling or snowball sampling can enhance external validity and ensure that diverse perspectives are represented.

Ultimately, both quantitative and qualitative research serve as complementary tools in evidence generation. While quantitative methods provide the rigor and statistical backing for identifying relationships, qualitative methods offer rich insights into the human experiences behind the data. Understanding how to effectively leverage both methodologies will enable researchers and practitioners to generate comprehensive evidence that leads to better clinical outcomes.

References

• Polit, D. F., & Beck, C. T. (2017). Nursing Research: Generating and Assessing Evidence for Nursing Practice (10th ed.). Wolters Kluwer.
• Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). SAGE Publications.
• De Vaus, D. A. (2013). Research Design in Social Research. SAGE Publications.
• Burns, N., & Grove, S. K. (2016). The Practice of Nursing Research: Appraisal, Synthesis, and Generation of Evidence (7th ed.). Elsevier.
• Sullivan, G. M., & Artino, A. R. (2013). Analyzing and Interpreting Data From Likert-Type Scales. Journal of Graduate Medical Education, 5(4), 541-542.
• McKinlay, J. B., & Marceau, L. D. (2000). A Weaving of Evidence: The Importance of Qualitative Research in Evidence-Based Practice. Social Science & Medicine, 51(1), 1-3.
• Guba, E. G., & Lincoln, Y. S. (2018). Competing Paradigms in Qualitative Research. In N. K. Denzin & Y. S. Lincoln (Eds.), The Landscape of Qualitative Research (4th ed., pp. 219-227). SAGE Publications.
• Fain, J. A. (2017). Reading, Understanding, and Applying Nursing Research (4th ed.). Jones & Bartlett Learning.
• Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin.
• Loeb, M., & Forster, R. (2013). The Role of Quality Improvement in Evidence-Based Practice. Missouri Medicine, 110(5), 442-447.