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The need to have a clear procedure for recruiting participants in a study remains to be one of the most significant procedures in research designing. The study will apply probability sampling to select its participants from the sampling frame. The paper begins with exploring the sample plan, target population, sample frame, and the recruitment strategy.

Sampling Plan

A sampling plan is a comprehensive outline of which measurements will be taken at specific periods, on which subjects, in what ways and by whom (Brink et al, 2007). The sampling plan is outlined in such a way that it addresses the research question fully taking into account the representative sample. In a study that involves establishing the relationship between obesity and diabetes, the researcher has the role to choose categorically his/her target population, sampling frame and sample.

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Target Population

Brink et al. (2007) explains that the target population refers to the entire or total number of units for which the sampling survey data is to be used in order to make conclusions. It is clear therefore, that the target population defines units for which the findings will be generalized in regard to the research question. Moreover, in a study that involves establishing the relationship between obesity and diabetes, the target population would consist of patients in a specific hospital including those who diagnosed with obesity and are under treatment. To take into account the issues of geographic and temporal features of the target population, several other hospitals in different locations will be selected for the study. In each hospital, the researcher has the role to identify the total number of patients including those diagnosed with obesity to monitor the likelihood of contracting diabetes after certain period.

Sample Frame

The elementary units that form the basis of sampling process are defined as sampling units. This list of sampling units defining the target population from which the sample will be drawn is called the sample frame (Kumar, 2011). A finite target population guarantees a sample frame that is identical with it. In this study, the sample frame would be drawn from the list of patients tested and diagnosed with obesity in various hospitals. The patient’s register will serve to help the researcher to sort out those diagnosed with obesity. In the event that there is no clear register specific to patients that are obese, the researcher has the role to construct the sample frame from the main patient’s register. Clear and well established sample frame would help in probability sampling that would later be employed.

Sample

Kothari (2005) cites that a sample is a section of a large body selected specifically to represent the whole target population. The sample is selected through sampling from the sample frame. Therefore a sample should reflect the features found in the target population. The sample studied thus represents the actual people who participate in the study (Kothari, 2005). In the study seeking relationship between obesity and diabetes, the sample shall consist of those diagnosed with obesity selected randomly from the sample frame prepared. Each hospital have a sample of the obese people under study in order to determine whether they can later be diagnosed with diabetes. This would help make inference about the larger target population.

Recruitment Strategy for the Participants

The recruitment strategy for the participants in the study will be done by probability sampling also referred to us random sampling. Under this sampling design, every item will have an equal chance of being selected from the whole population (Brink et al, 2007).  Since the sample prepared from the sample frame in regard to the study of obesity in relation to diabetes is finite, the best recruitment method would be random sampling. This gives each possible sample combination an equal opportunity to be picked up and analyzed.

Since the list of elementary units to be used in the study is available for each hospital and regarded as sample frame, the best way to come up with each sample would be systemic random sampling. The names of patients with obese recorded down for each sample frame is numbered. Then every item on the list is selected. Then researcher uses an element of randomness to pick up the number to begin within the systemic sampling among the first elements. This is then followed by systemic sampling maintaining interval between the selections to obtain the desired sample size.

Once a sample has been produced for once hospital, the procedure is repeated to other hospitals too. The systemic random sampling would be considered if the lists of patients diagnosed with obesity are considerably long. If the list is not long, then simple writing of the names on papers, mixing them and then choosing randomly from a basket would be used.

The samples selected would then be subjected to further scrutiny to check suitability for the study. The research question is to find out whether patients diagnosed with obesity are likely to contract diabetes, thus those earlier diagnosed with diabetes before being obese are disqualified.

Conclusion

From the brief discussion above, it is clear that making a sample plan is very important in any study such as the one to be undertaken. A proper target population, sample frame and sample have to be outlined as described. This shall be finalized by the systemic random recruitment strategy explained.

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