Hypertension intervention study design in men over thirty

¶ … blended study, both qualitative and quantitative in nature. The blend between numbers-based data and analysis and more abstract and conceptual work is necessary because of the totality of what is being looked at and how the research will be done (Lund, 2012).

Rationale for Study Type Selection

While the before and after results of hypertension of patients in this case will be strictly numerical and statistical in scope, the formulation and tracking of the interventions, education and so forth that will form the control for the experiment will certainly be based more on concepts, evidence-based practice and the ostensibly proper ways to enforce and impose interventions on patients (McDonald & Blackwell, 2006). After all, the behaviors and changes under way are not something more detached and simple like whether a medication is take or not or whether a therapy is administered. The people involved will be instructed on what to do but they will have to be the ones to do it then the results of the intervention will be measured. The depth, breadth and scope of how far the people with doing the intervention will matter a great deal. At the very least, there needs to be homogeneity and sameness from patient to patient so that the results are usable across the board.

Rationale for Sample Selection Strategy

There is not a huge amount of chance or riddle to the sample size, but it was selected for a reason. With that being said, the strategy shall be shown in the remainder of this brief section.

Sample Size

• A sample of 50 to 100 would be best with half of the group, at random, being the control group and the other half being a test bed for the interventions to be levied.

• The use of random selection helps avoid selection bias and helps make the sample as pure as possible. However, there are some reasons that selected people might later be removed from the sample, albeit for a good reason (Hanley, 2017).

Exclusion Criteria

• People that are unable to reasonable do the interventions and lifestyle changes should also be excluded. This would include people that are bound to a wheelchair or otherwise physically restricted, as their ability to do lifestyle exercise changes centering on physical activity would be restricted.

• Similarly, people with inordinate diet restrictions should also probably be excused. Easy example would include people with gluten and dairy allergies or intolerance.

• People that would be intentionally and knowingly excluded from the sample would be people that are clearly exceptions and outliers.

• For example, there are some people that just have naturally high blood pressure even if they have a healthy lifestyle. Such an outlier would cause statistical variation that is not due to lifestyle and diet choices and thus that person should not be part of the sample.

• Furthermore, people that have high blood pressure due to diseases or disorders that are not controllable in the form of lifestyle choices should also be excluded. Indeed, the intervention may or may not have any effect but the blood pressure being high (i.e. hypertension) is at least in part due to patterns and issues that are not within the control of the patient.

Conclusion

Overall, the ability to find a sample that is free from results-skewing participants and that are male should not be that hard to pull off. Indeed, the age range in question is rather high and most people with hypertension are in their situation because of lifestyle and diet issues, although there are surely are at least some exceptions. Indeed, those outliers and exceptions are actively being accounted and prepared for and this is by design. That being said, catching every person that would skew results like that is unlikely but that is what sample size is meant to smooth out and blunt.