Data Analysis, Reliability, Validity, and Statistical Tests in Health-Related Research

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

Type of the article Title of the article Type of analysis Applicability of test Reliability and validity
Qualitative systematic literature review What enables older people to continue with their falls prevention exercises? A qualitative systematic review A comprehensive search of qualitative and mixed methods studies focused on fall prevention of older adults was conducted in the next databases (MEDLINE, PSYCHinfo, AMED, ASSIA, CINAHL, and EMBASE). Thematic synthesis was used to generate three descriptive and one analytical theme, each of which was extracted and checked independently. Apart from thematic synthesis, researchers could use qualitative analysis to obtain a deeper understanding of fall prevention among geriatrics, as well as a phenomenology to discuss fall prevention as a medical phenomenon. No measurements of reliability and validity are present in the study. Techniques used to enhance reliability and validity are randomized sample and controlled variables.
A quasi-experimental retrospective cohort study Beneficial falls in stroke patients: Evaluation using a mixed-method design In this mixed-method study, data was collected with the help of open-ended interviews (qualitative) and close-ended checklists (quantitative). A grounded theory approach was taken to analyze the information obtained. In addition to the grounded theory approach, researchers could use statistical analysis to interpret quantitative data. No measurements of reliability and validity are present in the study. The technique used to enhance reliability and validity is a randomly stratified sample.
A systematic review and quantitative meta-analysis Comparisons of interventions for preventing falls in older adults Researchers conducted pairwise random-effects meta-analysis and statistical analysis of the scholarly journals on randomized clinical trials. Apart from the analysis taken, researchers could apply the computational method, observing the dynamics of data in the larger sample. Inter-rater reliability and internal consistency reliability strategies were used. No mentioned techniques to enhance validity.
A quantitative cluster-randomized controlled trial Fall rates in hospital rehabilitation units after individualized patient and staff education programs: A pragmatic, stepped-wedge, cluster-randomized controlled trial. The primary approach taken to analyze data is statistical analysis. Information collected from the randomly assigned units during 50 weeks was subjective to computational analysis. Potentially, researchers could expand the controlled trial through the introduction of close-ended surveys to collect quantitative opinions from healthcare professionals. Random assignment and test-to-test reliability were used as techniques to enhance the reliability and validity of the research.
Qualitative phenomenological study “The right way at the right time”: Insights on the uptake of falls prevention strategies from people with dementia and their caregivers. This qualitative study uses qualitative analysis with a phenomenological approach to report on the data collected through interviews. The 6-month intervention was introduced to put the identified fall factors to test. Other applicable approaches to this study include content analysis and focus groups. In-depth interviews could be substituted with developed group discussions. The study applies inter-rater reliability and predictive validity to enhance the accuracy of the research.
Mixed-methods exploratory study Lessons learned from implementing CDC’s STEADI falls prevention algorithm in primary care This mixed-methods exploratory study utilizes descriptive statistics and retrospective analysis to interpret the data collected through open and close-ended surveys. This study would benefit from an in-depth content analysis of the verbatim transcribed interviews and statistical analysis of the close-ended questions. Parallel forms of reliability are used in the study. No validity measurements are listed.
A prospective qualitative explanatory study “My independent streak may get in the way”: How older adults respond to falls prevention education in the hospital. Data collected with the help of a prospective qualitative survey was interpreted with the content analysis. Other types of analysis included descriptive statistics and conceptual framework analysis. This study’s methodology could be improved with the help of the grounded theory approach because interpretations of the content analysis lack current theoretical evidence. No measurement or techniques to enhance validity and reliability are identified.

References

Casey, C., Parker, E., Winkler, G., Liu, X., Lambert, G., & Eckstrom, E. (2017). Lessons learned from implementing CDC’s STEADI falls prevention algorithm in primary care. The Gerontologist, 57(4), 787–796. 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.

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StudyCorgi. 2022. "Data Analysis, Reliability, Validity, and Statistical Tests in Health-Related Research." January 21, 2022. https://studycorgi.com/data-analysis-reliability-validity-and-statistical-tests-in-health-related-research/.

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