The quantitative research plan being conducted is on the prevalence of diabetes in the local community. This particular design is significant in the sense that diabetes is becoming more prevalent as the health of populations decline and there is greater dependence on technology and other means of supporting society and populations in the 21st century. Part of the research plan is on the sampling method that will be used to determine the prevalence of diabetes as well as the exposure of society to particular aspects of diabetes such as abnormal blood pressure, bad eating habits and how often people frequent fast food restaurants where unhealthy food is served. The most effective means of determining the prevalence of diabetes in a local population is by a consensus however in this particular instance, it is simply not possible. Diabetes can have tremendous and rather horrific impacts on the health of populations as well as the abilities of local health departments to treat patients and ensure that its resources can necessitate the spread of diabetes.
The population under analysis for the prevalence of diabetes has a size of close to 10,000 people, all of which can not be sampled within this particular research plan. The population is also widely diverse with a large majority of white Caucasians, estimated to be close to 70% of the population size along with 20% for Hispanic populations and 10% accounting for other minorities within the general population such as Black Africans, Canadians and foreigners including some Chinese and Indonesians (Parker, 2015). For the purposes of this research plan, these population sectors will not be scrutinized in terms of which population type has a greater prevalence of diabetes however the results of the sampling plan will be noted and used for future reference. The main focus of this research plan is on the prevalence of diabetes in the general, local population.
The type of sampling design used in this research plan and most suitable considering its main focus (the prevalence of diabetes in the general population) is “Systematic Sampling”. Systematic sampling is effective for cases or research plans where the incidence of one common factor needs to be determined amongst a large population. It is more detailed than others and can allow a ratio to be determined based on the sampling size out of the entire population size. This ratio can then be used to determine the accuracy and validity of the results. In regards to how sampling is conducted, after a ratio has been determined based on the population size, that sampling size is then used in small groups (WISC, 2016). Each group within the large sampling size is selected throughout a number of different locations within the area and this allows for a very diverse sampling size to be collected, which can further improve the validity and accuracy of the results being collected throughout the research plan. In regards to which sample size is surveyed first, random selection is conducted and each sample size is eventually surveyed. The results are then collected and compared to one another and most significantly, aligned with the ratio calculated prior to the commencement of sampling.
The sample size pre-determined in this research plan is 100 people from a total population of 10,000. This equates to a ratio of 1% or 0.01 and is used to magnify or otherwise multiply numbers collected from each sample collection of people (Parker, 2015). Each sample size will be 10 individuals allowing for 10 random samples to be collected from 10 different locations. As previously stipulated, this improves the accuracy and validity of the results further.
In determining the prevalence of diabetes in the general population, this sample design will be most effective as a result of its high level of accuracy, reliability and validity. Furthermore, diabetes is the only requirement in this research plan and allows for the systematic sample design to make it more accurate and effective overall and with a high possibility of the results being very valid and relevant to the main hypothesis of the plan. The disadvantages of choosing such a sample design focus on its lack of flexibility and inability to focus on a number of different variables and requirements. In this case, it is an effective choice because of the one sampling requirement however if the prevalence of diabetes in certain populations and ethnic groups of society was required, then it would be generally ineffective. In terms of other available sample designs, simple random sampling is not advisable as certain populations within society are being targeted and random sampling may provide very inaccurate results and show up a 0% prevalence of diabetes (Parker, 2015). Additionally, stratified sampling and over sampling methods may be perceived to be accurate in this case however are more basic and general in nature and may provide results on other aspects of society rather than simply on diabetes. For example, if someone wanted to find out a wide range of diseases and their prevalence in society, then these methods would be highly advisable and effective in achieving this requirement.
There are a number of considerations associated with the chosen sample design and being able to accurately determine the prevalence of diabetes in the particular population. The first is that surveys will be conducted within each particular sampling group to be able to collect information from a random group of people, but who live within different areas of society. For example, one of the groups will be located in the central area of the general population and be able to provide accurate information on the prevalence of diabetes in that area and when the total number of diabetes cases is multiplied by the pre-determined ratio. In this particular area, if there are 3 people with diabetes, then this number will be multiplied by the stipulated ratio. This will continue for other sample collections in other areas of the general population. The western and northern areas will be sampled and the number of diabetes cases further magnified and multiplied by the ratio number (Parker, 2015).
Other considerations focus on the fact that some sampling collections may have no prevalence of diabetes whatsoever and it may be an instance where there is no evidence or existence of diabetes in the general populations. Similar results to this must be considered seriously and not blamed on the sampling design. If the overall population happens to have a very small prevalence of diabetes then perhaps it is healthier or there are other factors that are influencing its health and respective medical programs overall. It must also be considered that this sample design could be used to highlight the prevalence of other diseases and health concerns within each area of the population and this may rely solely on additional questions being added to the survey that each individual is asked to fill out (WISC, 2016). This can expand the research plan further and provide some other factors, which may be causing the prevalence of diabetes to be either very high or very low. This could be very relevant to the current research plan if the survey remains restrictive and only asks target samples one or two questions and no other social requirements.
- Parker, M. (2015). Types of Sampling. UT Mathematics, Retrieved from https://www.ma.utexas.edu/users/parker/sampling/srs.htm Accessed on 7th April, 2016.
- WISC. (2016). Sampling Designs. Retrieved from
http://www.ssc.wisc.edu/~jraymo/links/soc357/class8_F09.pdf Accessed on 7th April, 2016.