I’m working on a nursing discussion question and need an explanation and answer to help me learn

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Learning Goal: I’m working on a nursing discussion question and need an explanation and answer to help me learn. answer port #1 and prompt #2 prompt #1: Reflecting on research you’ve performed, can you provide a clear example from your personal experience as a professional nurse of why statistically significant results in a study do not always mean that the study is clinically significant? What has this looked like within the clinical setting in which you’ve worked? I look forward to your response. INITIAL POST: Clinically relevant interventions mainly justify the effects, which primarily overcome the harm, costs, and the various adverse effects to the target population. Thus, the leading difference between the two is that the latter examines the dissimilarities between two treatment modalities or groups. Conversely, statistical significance assesses whether any mathematical analysis is necessary for the results. Different research can have the same statistical result but differ majorly in their clinical significance (Amrhein et al., 2019). As a result, has always been varied scientific opinions on the accuracy and relevance of statistical significance. In addition, the phenomenon is the primary reason why scientists always refute differences that people are not in their fields consider exist. Besides, scientists have been cautioned that statistically insignificant findings do not necessarily affirm the null hypothesis (Amrhein et al., 2019). These claims affirm that the statistical and clinical significance are distinct in nature and application.Furthermore, the statistical significance does not prove the accuracy of and relevance of clinical results but primarily aims at improving the quality of life. Sharma (2021) posits that clinically significant results enhance medical care, ultimately enhancing physical functions and mental and social status. Quality of life in medical care refers to objective and subjective terms. In this case, the objective deals with aspects that improve the performance, duration of disease remission, and prolonged lifespan. Contrarily, subjective term deals with improving the quality of life in terms of attitude, feelings, social and physical activities, and general wellbeing.However, statistical significance aims at affirming the research hypothesis. Research shows that most studies that rely on these aspects are more concerned with the accuracy of the findings than their application in improving the quality of life (Sevelius et al., 2021). Due to this reason, scientists and health care professionals claim that statistical significance does not necessarily imply that the results are valid. Besides, the rationale behind the reasoning of the proponents of this aspect proves that they are more concerned with the mathematical than other underlying factors that change the results of a finding. These assumptions deviate from the best practice requiring clinical researchers and clinicians to focus more on clinically significant changes. Further, the evidence-based practice requires healthcare professionals to stay current with the most clinically relevant literature (Sevelius et al., 2021). Therefore the uncertainty of statistical significance, not necessarily clinically relevant, makes them less helpful to the sector. The best example explaining the phenomenon is that studies can share statistical significance but differ more in their clinical relevance. Considering two distinct cancer chemotherapy- the first case examines the survival rates of patients on drug A treatment. Similarly, the second study on the same principles using drug B. the first drug increases survival by ten years, P = 0.01while the second achieves the same objective but only offers patients four months to live, P = 0.01. The two tests are significant in both instances, but the second drug can only increase survival by four months, which is not clinically viable compared to the first medication.In conclusion, the main dissimilarity between the statistical and clinical significance is that the latter examines the dissimilarities between two treatment modalities or groups. Conversely, statistical significance assesses whether any mathematical analysis is necessary for the results. Further, it is justifiable to claim that statistically significant results do not always mean that the study is clinically significant.ReferencesAmrhein, V., Greenland, S., & McShane, B. (2019). Scientists rise against statistical significance, https://www.nature.com/articles/d41586-019-00857-9 (Links to an external site.).Sevelius, J., Chakravarty, D., Neilands, T. B., Keatley, J., Shade, S. B., Johnson, M. O., & Rebchook, G. (2021). Evidence for the model of gender affirmation: the role of gender affirmation and healthcare empowerment in viral suppression among transgender women of color living with HIV. AIDS and Behavior, 25(1), 64-71, https://doi.org/10.1007/s10461-019-02544-2 (Links to an external site.).Sharma, H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi Journal of Anaesthesia, 15(4), 431, https://doi.org/10.4103%2Fsja.sja_158_21 (Links to an external site.).Prompt #2: Provide a positive feedback to this comment Statistical significance asks the question of whether or not results of a statistical study or test meet the standard levels, which is measured by the probability value being less than 0.05. (Schmidt & Brown, 2017) Clinical significance is loosely defined as a treatment or research experiment to help patients return to ‘normal’ functioning from a dysfunctional state. (Schmidt & Brown, 2017) Statistical significance and clinical significance are not synonymous; statistical significance can be unrelated to clinical significance. For example, if you have a large enough study and enough participants even small differences can be reported as statistically significant. However, just because a study has been shown to be statistically significant does not mean that these results are meaningful to patients. (Schmidt & Brown, 2017)An example of both statistically and clinically significant findings can be found in a study on the effectiveness of antimicrobial agents in hospital settings to reduce the number of HAI’s on acute care units. (Abushaheen et al., 2020) It was determined that antimicrobial agents must be used with caution, as over or underusage can result in microbial mutation that can render the pathogenic agent resistant to treatments. (Abushaheen et al., 2020) As nurse researchers we must carefully review and analyze research studies, especially as they relate to EBP, in order to enhance our knowledge and implement better nursing practices. (Schmidt & Brown, 2017)References:Abushaheen, M. A., Muzaheed, Fatani, A. J., Alosaimi, M., Mansy, W., George, M., Acharya, S., Rathod, S., Divakar, D. D., Jhugroo, C., Vellappally, S., Khan, A. A., Shaik, J., & Jhugroo, P. (2020). Antimicrobial resistance, mechanisms and its clinical significance. Disease-a-Month, 66(6), 100971. https://doi.org/10.1016/j.disamonth.2020.100971 (Links to an external site.)Schmidt, N. A., & Brown, J. M. (2017). Evidence-Based Practice for Nurses: Appraisal and Application of Research (4th ed.). Jones & Bartlett Learning.

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