Order from us for quality, customized work in due time of your choice.
Understanding critical components of research, such as data analysis, validity, and reliability is central to the in-depth synthesis of the information reviewed. They analyzed seven articles that constitute only a small portion of the bigger research, aimed at exploring accessible measures of fall prevention. Close examination of the analysis types, factors of reliability, validity, and statistical tests allow predicting the application of the studies for the cornerstone project this semester.
Systematic tests lay at the core of health-related research with methods differing to a great extent depending on the nature of the study. In their qualitative systematic literature review, Finnegan, Bruce, and Seers (2019) use Wilcoxon sign-rank test to test for the differences between two related variables. Meyer, Dow, Hill, Tinney, and Hill (2016) apply the same type of statistical test in their qualitative phenomenological study. Both teams choose this approach, considering the direction and magnitude of influence of the factors that could not otherwise be interpreted quantitatively. Unlike the aforementioned researchers, Hill et al. (2016) chose to use Wilcoxon rank-sum test, since he investigated the differences between two independent variables in their qualitative explanatory study.
Quantitative studies applied substantially different statistical tests that proved to be effective in interpreting the obtained data. Both Hill et al. (2015) and Tricco et al. (2017) utilized Spearman correlation, checking for the strength of the association between ordinal variables in their quantitative meta-analysis and cluster-randomized controlled trial. Mixed-methods research by Watabe et al. (2018) and Casey et al. (2017) also apply Pearson correlation since they are testing for the strength of the association between two continuous variables. Though Watabe et al. (2018) conducted a quasi-experimental cohort study and Casey et al. (2017) did an exploratory study, their statistical methods were similar.
Apart from observable distinctions in statistical testing, studies had different approaches when it came to parametric and non-parametric tests. All of the qualitative and mixed methods research utilized non-parametric tests, while quantitative studies focused on parametric methods only. The reasoning behind such a finding is that non-parametric tests do not rely on the distribution of data. While some might argue that parametric tests are more reliable and accurate, non-parametric methods allow assessing factors in a wider array of situations, especially when the data obtained is not quantifiable.
The factors of reliability and validity remained ambiguous in the vast majority of the articles chosen. Only three out of seven scholarly sources explicitly mentioned measurement tools that evaluate reliability and validity in the research. Most techniques utilized to enhance reliability and validity included random stratification of the research sample, controlled variables, and introduction of the inter-rated reliability strengthened with parallel forms reliability and predictive validity.
The chosen articles lay a basic foundation for the cornerstone project focused on fall prevention. Findings from the quantitative, qualitative, and mixed methods studies provide a holistic approach for the research where both parametric and non-parametric factors are taken into consideration when building an argument. Empirical evidence from the statistical analysis of the quantitative research would specifically inform the part related to major attitudes of healthcare practitioners on fall prevention. Meanwhile, results of the qualitative and mixed methods studies are expected to be effective in creating protocols, outlining critical strategies for general nurses, supporting geriatric patients.
Appendix 1
References
Casey, C., Parker, E., Winkler, G., Liu, X., Lambert, G., & Eckstrom, E. (2017). Lessons learned from implementing CDCs STEADI falls prevention algorithm in primary care. The Gerontologist, 57(4), 787796. Web.
Finnegan, S., Bruce, J., & Seers, K. (2019). What enables older people to continue with their falls prevention exercises? A qualitative systematic review. BMJ Open, 9(4), 1-7. Web.
Hill, A. M., McPhail, S. M., Waldron, N., Etherton-Beer, C., Ingram, K., Flicker, L.,& Haines, T. P. (2015). Fall rates in hospital rehabilitation units after individualised patient and staff education programmes: A pragmatic, stepped-wedge, cluster-randomised controlled trial. The Lancet, 385(9987), 2592-2599. Web.
Hill, A. M., Francis-Coad, J., Haines, T. P., Waldron, N., Etherton-Beer, C., Flicker, L.,& McPhail, S. M. (2016). My independent streak may get in the way: How older adults respond to falls prevention education in hospital. BMJ Open, 6(7), e012363. Web.
Meyer, C., Dow, B., Hill, K., Tinney, J., & Hill, S. (2016). The right way at the right time: Insights on the uptake of falls prevention strategies from people with dementia and their caregivers. Frontiers in Public Health, 4, 1-10. Web.
Tricco, A. C., Thomas, S. M., Veroniki, A. A., Hamid, J. S., Cogo, E., Strifler, L.,& Riva, J. J. (2017). Comparisons of interventions for preventing falls in older adults. JAMA, 318(17), 1687-1699. Web.
Watabe, T., Suzuki, H., Konuki, Y., Aoki, K., Nagashima, J., & Sako, R. (2018). Beneficial falls in stroke patients: Evaluation using a mixed method design. Topics in Stroke Rehabilitation, 25(2), 137-144. Web.
Order from us for quality, customized work in due time of your choice.