SLP - TYPES OF VARIABLES AND DATA ANALYSIS

Types of Variables and Data Analysis

Before any study can be undertaken, the researcher must determine what exactly will constitute the study’s target population, sample frame, and sample (if any of these terms is unfamiliar to you, I strongly encourage you to revisit the discussion of sampling in Module 3 as this information provides the foundation necessary to complete this SLP assignment) I paste the Module 3 below for your review to review and pull from as well. Also to be considered how he will go about recruiting subjects into his study.

Your Task for this Assignment

Discuss the following as it pertains to your study in 3-4 pages; incorporate this discussion into a 12- to 15-page final paper consisting of all prior SLP components.

1. A sampling plan for your study to address the research question you chose in Module 1. Be sure to outline clearly your study’s

a. target population

b. sampling frame

c. sample

2. A recruitment strategy for enlisting prospective research subjects in your study.

SLP Assignment Expectations

1. You are expected to consult the scholarly literature in preparing your paper; you are also expected to incorporate relevant background readings.

2. Your paper should be written in your own words. This will enable me to assess your level of understanding.

3. In order to earn full credit, you must clearly show that you have read all required background materials.

4. Cite your references in the text of all papers and on the reference list at the end. For examples, look at the way the references are listed in the modules and on the background reading list.

5. Proofread your paper to be sure grammar and punctuation are correct and that each part of the assignment has been addressed clearly and completely.

6. Your assignment will not be graded until you have submitted an Originality Report with a Similarity Index (SI) score <20% (excluding direct quotes, quoted assignment instructions, and references). Papers not meeting this requirement by the end of the session will receive a score of 0 (grade of F). Do keep in mind that papers with a lower SI score may be returned for revisions.  For example, if one paragraph accounting for only 10% of a paper is cut and pasted, the paper could be returned for revision, despite the low SI score.  Please use the report and your SI score as a guide to improve the originality of your work.

Length: 12-15 pages typed, double-spaced.

Note: Wikipedia is not an acceptable source of information.

RES 500 Research Methods for the Health Sciences

August 2017

Module 3: SLP Sampling

Trident University International

Professor: Dr.

The suitable design for this study will be a Cross-sectional study design (Yin, 2013). This is because the situation at hand is to find out if obesity increases the risk factor of individuals getting diabetes in a particular population. In other words, what is the prevalence of diabetes among the obese population will be the question the study is addressing. This study will use the existing data and also observation and therefore, data will be randomly collected from two populations that were purposively selected observing the criteria of being obese and being diabetic separately. The components of the design therefore will include variables, population, sample, sample size and the parameters measured (Merriam & Tisdell, 2015).

The independent variable will be obese while the dependent variable will be diabetes risk factor. The population will be the patients that have been diagnosed with diabetes and the people that are obese. The population sample size considered will be 200 individuals form each group so as to increase accuracy of the results obtained. Each group will be classified into three subgroups considering the age (school age -5-16; young adults, 16-26; adults, 27-70) of the individuals. The quantitative parameters that will be measured will be the heights of the individuals, body weight and age of the individuals. The qualitative parameters will be the medical status of the obese and diabetic individuals. This design will be used to test the hypothesis that “Obesity increases body’s insulin resistance and thus increases the risk of developing diabetes” (Dabelea et al., 2014).

The study design here will be considered observation rather than experimental. This is because the data collection will be based on the recoded data and what can be observed in the population. For instance, the obesity individuals will be observed and identified before being sampled for testing. The diabetic individuals on the other hand will be sampled from the clinical data for research with their consent. It will not be possible to experimentally induce obesity in the individuals so that their resistance to insulin is determined by time as they are monitored because this will be un-ethical practice is stipulated in the ethics of medical researches. The causal of diabetes is commonly known to be the individuals’ body to become resistant to the functions of insulin and therefore there will be no need of inducing insulin in individuals with diabetes to monitor their condition. The data collected will aid in the correlation of the obesity prevalence with the prevalence of diabetes in the population identified. This can be done using existing data and few measurements of natural phenomenon like height, age and body weight of the sample population. Going the experimental way may be detrimental because individuals may suffer the residual impact of being induced with insulin and or being caused to become obese so that their resistance to insulin in their body is monitored. Therefore, the study will base on observational approaches.

I chose on this study because the study would need a one chance contact with the patients and therefore will take a short time and will be ease in terms of financial spending and applicability. Cross-sectional observational study design is used to examining the relationship of one aspect and the other in a population at one time and the prevalence of the outcome in a population that is defined for a particular time. This kind of a study is very vital in proving or disapproving a certain observation or assumption using data obtained in the population. The study design is very instrumental in capturing a certain point over an aspect in a particular population in time. The data collected can be used in many other areas or to develop new theories or define a trend in a population. The advantages above fit well for the research problem at hand thus a cross-sectional observational study will be the best (Sedgwick, 2014).

However, the design as some inherent disadvantages though which do not cancel its applicability in this study. These include the inability of the study to conclusively determine the cause of obese and diabetes but will just point that the risk of developing diabetes is high in obese individuals than the normally weighing individuals in a particular population (Haider et al., 2014). The study may also be influenced by the irrepresentativity of the sample selected because the specific samples are selected not giving equal change to all individuals in the population so as to be representative. The result may therefore be biased or may fail to identify other correlations in the issue at hand (Patten, 2017).

This kind of research is vulnerable to various kinds of biasness. For instance, the choosing of the study sample may be unrepresentative due to sampling error thus resulting in biased conclusions or results that cannot be obtained in another population if the same design and methods were applied on a different population with similar conditions. Using individuals from the healthcare facility as the sample population and not considering the other people in the entire population with the same condition may cause a self-selection factor in the sample which may affect one of the variable in the research thus resulting into internal validity issue of the data (Hassett et al., 2015). This will also yield a coverage error in that the population intended for generalization was not inclusively included in the sample due to systemic sampling which considered the individuals with obesity or over weight that attend healthcare attentions and not the other individuals that do not attend healthcare facilities. During measurement of the height, and weight, instrumental errors may also cone in. the instrument zero error or incorrect reading may mislead the results. This will result into wrong interpretation and conclusions thus missing the real phenomenon in the population (Patten, 2017).

References

Dabelea, D., Mayer-Davis, E. J., Saydah, S., Imperatore, G., Linder, B., Divers, J., ... & Liese, A. D. (2014). Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. Jama, 311(17), 1778-1786.

Haider, A., Saad, F., Doros, G., & Gooren, L. (2014). Hypogonadal obese men with and without diabetes mellitus type 2 lose weight and show improvement in cardiovascular risk factors when treated with testosterone: an observational study. Obesity research & clinical practice, 8(4), e339-e349.

Hassett, L., Moseley, A., Harmer, A., & van der Ploeg, H. P. (2015). The reliability, validity, and feasibility of physical activity measurement in adults with traumatic brain injury: an observational study. The Journal of head trauma rehabilitation, 30(2), E55-E61.

Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation. John Wiley & Sons.

Patten, M. L. (2017). Understanding research methods: An overview of the essentials. Taylor & Francis.

Sedgwick, P. (2014). Cross sectional studies: advantages and disadvantages. BMJ: British Medical Journal, 348.

Yin, R. K. (2013). Case study research: Design and methods. Sage publications.