Case Study Frameworks For Nursing Research: A Group Of Nurse ✓ Solved

Case Study Frameworks For Nursing Researcha Group Of Nurses Working I

Develop a comprehensive understanding of a nursing research case study that explores the relationship between renal insufficiency, ambulation, and family presence in hospitalized patients. The case involves nurses observing that patients with chronic renal insufficiency exhibit decreased cooperation, increased anxiety, impaired thinking, and reduced ambulation unless family members are present. The nurses conducted a literature review, collaborated with a doctoral-level educator, and created a descriptive, longitudinal study framework based on physiological principles and family presence theory. The study aims to investigate how renal insufficiency, ambulation, and family presence evolve during hospitalization and how these factors are interrelated. You are asked to describe the physiological theory underpinning the link between renal insufficiency and ambulation, and to determine the appropriate statistical analysis for the study’s second research question, assuming a parametric test is suitable.

Sample Paper For Above instruction

Introduction

Nursing research often involves exploring intricate relationships between physiological factors and patient behaviors to improve care outcomes. The case study in question examines how chronic renal insufficiency affects patient ambulation and the role of family presence during hospitalization. It emphasizes the importance of theoretical frameworks to support research hypotheses and the selection of appropriate statistical analyses to interpret data accurately.

Physiological Theory Supporting the Relationship Between Renal Insufficiency and Ambulation

The physiological basis linking renal insufficiency and reduced ambulation primarily involves disruptions in body systems that regulate fluid balance, electrolyte stability, and metabolic waste removal. Chronic renal insufficiency impairs renal function, leading to accumulation of toxins and imbalances in key electrolytes such as potassium, sodium, and calcium. These disturbances can cause fatigue, muscle weakness, decreased stamina, and neurological symptoms like confusion, which collectively diminish a patient’s capacity for ambulation (Kasiske et al., 2012).

Moreover, fluid overload resulting from impaired kidney function can lead to edema and cardiovascular strain, further impairing mobility (Himmelfarb et al., 2017). Uremic toxins influence central nervous system function, resulting in cognitive impairment that hampers coordination and motivation for movement (Leung et al., 2019). Collectively, these physiological alterations diminish physical capacity and contribute to decreased ambulation in patients with renal insufficiency, especially during the stress of hospitalization.

The theory posits that as renal function declines, systemic physiological disturbances compromise muscle function, cognitive clarity, and energy levels, thereby reducing propensity and ability to ambulate without external support or encouragement (Kumar & Kanaparthy, 2014). Understanding this physiological framework clarifies why interventions aimed at correcting metabolic imbalances may improve mobility outcomes.

Statistical Analysis for the Second Research Question

The second research question seeks to explore the relationships among renal insufficiency, ambulation, and family presence. When the data are suitable for parametric testing—assuming the data meet requirements such as normal distribution, interval or ratio scaling, and homogeneity of variances—the appropriate statistical analysis is the Pearson correlation coefficient.

Pearson’s r allows researchers to quantify the strength and direction of the linear relationship between two continuous variables, such as levels of renal impairment and degree of ambulation, or family presence and mobility scores (Schober et al., 2018). If the study examines multiple pairwise relationships simultaneously, a multiple regression analysis could be employed to assess the influence of renal insufficiency and family presence on ambulation, controlling for potential confounders.

Moreover, the use of regression analysis would provide insight into how much variance in ambulation can be explained by changes in renal function and family support, thus offering practical implications for targeted interventions (Tabachnick & Fidell, 2013). Ensuring assumptions are met, such as linearity, Independence of errors, Homoscedasticity, and Normality, is crucial for deriving valid inferences from such analyses.

References

• Himmelfarb, J., Ikizler, T. A., & Kaysen, G. A. (2017). Uremic neurotoxins: A new dimension in renal failure. Seminars in Nephrology, 37(3), 271-278.
• Kasiske, B. L., Canda, A., Epstein, R., et al. (2012). Impact of renal function on patient activity after kidney transplantation. Nephrology Dialysis Transplantation, 27(7), 2808-2815.
• Kumar, V., & Kanaparthy, R. (2014). Pathophysiology of muscle weakness in chronic renal failure. Journal of Clinical & Diagnostic Research, 8(12), 1504-1506.
• Leung, J., Stuard, S., & Johnson, C. (2019). Cognitive impairment in patients with chronic kidney disease: Pathophysiology and management. American Journal of Kidney Diseases, 74(1), 132-139.
• Schober, P., Boer, C., & Schwarte, L. A. (2018). Correlation coefficients: Appropriate use and interpretation. Anesthesia & Analgesia, 126(5), 1763–1768.
• Tabachnick, B. G., & Fidell, L. S. (2013). Using Multivariate Statistics (6th ed.). Pearson Education.