for HLT 362 Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis

for HLT 362 Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis

Hypothesis testing is a systematic statistical approach to identify if substantial evidence supports a specific claim about the research topic. Hypothesis testing in research is anchored on five steps: stating the null and alternative hypotheses. The other steps include data collection, identifying a statistical test to conduct, calculating the p-value, and deciding based on the value and the critical value (Keysers et al., 2020). There are specific examples of how research uses hypothesis testing to determine the efficacy of an intervention to improve health outcomes. For instance, in a study of the effectiveness of a new medication to relieve pain, researchers can use hypothesis testing to evaluate whether the medication is significantly better than a placebo. The null hypothesis for this research will state that there is no difference in pain reduction between the medication and the placebo.

On the other hand, the alternative hypothesis will be the medication is indeed more effective. Testing the hypothesis, the researchers would collect data on a sample of randomly selected to receive the drug. They will then utilize statistical analysis tests such as t-tests to evaluate if the groups significantly differ in pain reduction. The p-value will be calculated, and if it is below the predetermined threshold, such as 0.05, it could indicate that the observed result is unlikely to have occurred by chance alone. Therefore, the null hypothesis can be rejected.

In assessing the impact of a population-tailored health education program on diabetes and self-management, hypothesis testing can be effective in determining change in behavior between individuals enrolled in the program compared to the central group. The null hypothesis would state that there is no difference in self-care behaviors between the two groups. On the other hand, the alternative hypothesis would state that the education program leads to improved self-care behaviors. Data collection will be conducted through surveys and questionnaires before and after the program’s implementation (Tang et al., 2022). Statistical tests such as paired t-tests or chi-square tests are conducted to assess the difference. Additionally, the value will be calculated. If it is below the predetermined threshold, it indicates the observed change was unlikely to occur due to chance alone, hence rejecting the null hypothesis.

In nursing practice, hypothesis testing is fundamental in assessing the effectiveness of interventions, treatments, and educational programs. It provides evidence of the intervention’s importance and guides healthcare professionals to care for patients effectively (Dang et al., 2021). The nurses can utilize the information to implement various evidence-based approaches to empower patients to manage their health. Additionally, via hypothesis testing, nurses can be guaranteed that the interventions they advocate for patients are proven to be effective and data-driven. Overall, it improves patient health outcomes and advances a better evidence-based and patient-centered practice in nursing care.

References

Dang, D., Dearholt, S. L., Bissett, K., Ascenzi, J., & Whalen, M. (2021). Johns Hopkins evidence-based practice for nurses and healthcare professionals: Model and guidelines. Sigma Theta Tau.