Diabetic Patients in Saudi Arabia - Research Paper Example

? Research Proposal: Health Sciences and Medicine Table of Contents Introduction 2. Literature review 3. Research Methodology 3.1. Design 3.2. Materials 3.3. Sample 3.4. Procedure 4. Ethical issues 4.1. The approach and recruitment of subjects 4.2. Informed consent procedures 4.3. Data management/storage 4.4. Confidentiality/anonymity 4.5. Potential negative effects, Risks and safety 4.5.1. Negative Effects 4.5.2. Potential Risks 4.5.3. Safety Measures 4.6. Sources of data/records 5. Plans for data analysis 5.1. Qualitative Analysis 5.2. Limitations of the data analysis 6. Time Schedule Abstract Objectives: To investigate the effects of Low Socioeconomic Status on diabetic nephropathy type of complication in patients suffering from diabetes. The target group for this research is a group of diabetic patients in Saudi Arabia undergoing treatment in the Diabetic Center in Riyadh. Design and methods: Qualitative data collection and analysis with the use of fully structured questionnaires distributed among the patients followed by critical analysis to test the hypothesis. Setting and subjects: A random selection of diabetic patients in Riyadh, from different economic backgrounds and presently undergoing diagnosis and treatment at the Riyadh Diabetic Centre. Sample: A random sample of patients who have been diagnosed of Diabetes with special respect to cases of complication of diabetic nephropathy. Main issues: Elements of low socioeconomic affairs and their effects on the rate of diabetic nephropathy. 1. Introduction This study investigates the impacts of low socioeconomic class status on the rates of occurrence of diabetic complication popularly known as diabetic nephropathy. In this study, the hypothesis will be measures and tested by conduction a qualitative data collection and analysis on the sample population that has been randomly selected. With a special focus on Riyadh, we are interested in studying the proportionality of the numbers of tested cases, to make conclusive remarks concerning the entire population in Saudi Arabia. The proportion will provide for this study, a wider picture of the relationship that exists between the socioeconomic conditions of the population to the number of cases of complication. Our study is to discover whether poverty leads to increased number of diabetic nephropathy cases or not. Riyadh Centre for Diabetes will be a direct beneficiary of this project because it will be able to use its recommendations to improve its services to the diabetic patients, especially those in the poor families. The centre will be able to provide access of information and vital resources. This study will guide the centre in providing necessary medical attentions to the patients. 2. Literature review In Saudi Arabia, certain scholars have claimed that there is no proper standard way to classify patients in order to determine the relationship between social and economic status to diabetic morbidity. Secondly, there is no specific study that has undertaken to look at various classes in the society in the line of their economic status, and how they influence the numbers and extents of diabetic complication in the Saudi Arabia population. There have been studies about Diabetes but with different objectives and at different scopes. Scholars have long known socio-economic status (SES) together with its related parameters as the major determinant factors for health. Some studies have shown far-reaching proofs to illustrate their claims that that poverty reduces human life expectancies and hence increases mortality rates. Recent discoveries of the behaviour of Diabetes nephropathy in Riyadh, Saudi Arabia shows a greater effect to be among the low income earning families. However, the observation has not been carried out to great details in a structured research to prove it validity. Very important socio-economic factors have been exhibited in the measure of prevalence of many complicated diabetic conditions as major risk factors (Winkleby & Cubbin, 2003). Of course the realization comes amidst multiple studies of cardiovascular diseases, one of which is diabetes. The impact study shows that approximately 60 percent of the population in Riyadh, Saudi Arabia that have Diabetes and suffer from the complication of diabetic nephropathy originate from the low income class (Brancati et al., 1992). The remaining 40 per cent forms the middle class and the rich families in Riyadh on average. This observation proves the claim that several studies have shown in the relation that manifests between socioeconomic factors and diabetic nephropathy. The studies have varied in scope to cover the global domain, but this study narrows down to the case of Riyadh for the purpose of consistency to the aims and objectives of the qualitative research. Socio economic status (SES) presents an extremely complicated scenario and a construct using different variables to measure (Winkleby & Cubbin, 2003). The socio economic factors that have been explored by the previous studies include financial incomes, education, population growth, public resource allocation and availability of jobs. The effect of these factors reflects in various explicit exposures. Economic income is a direct parameter related to the trend of the complication, but one that has not been completely covered. Measures of economic positions of the low income classes in the society often reflect in the resultant feedback of the effects according to observation (Larranaga et al., 2005). There is an intriguing relationship between poor health and income, which presents a mutual interconnectivity (Brown et al., 2004). Whereas poor income earning prevents patients from accessing health services, it is also true that poor health limit the ability of the population to access income. Poor income limits acquisition of vital information and awareness of the diabetic complications. Low income of course, implies that the poor families in Saudi Arabia cannot access sufficient food supply and medication. This tends to provide an inherent meaning of the model that relates socio-economic status (SES) of the target group to the rate of diabetes spread and morbidity. Once there is limited awareness, preventive measures do not find application. Studies have shown that the level of education and exposure are adequately higher among the younger generations, including adolescents and teenagers, who cannot apply them in the real life. Adults who are the custodians incidentally lack the significant exposure (Stelmach et al., 2005). The poor in the society live in oblivion of the dangers that are constantly looming around them. In the Preliminary studies and analysis, scholars have discovered that several diseases and conditions are purely related to the socio-economic status (SES) of the societies. The researchers in the field of health science and medicine have had almost similar experiences in their investigators, relating the financial position to disease prevalence. A population study conducted in Saudi Arabia in 2010 on diabetic renal conditions discovered that among the low income earners, socioeconomic status and the resultant indication in the lack of tertiary education was greater than among the wealthy families. In a separate structured questionnaire study conducted in 2002 among 770 people suffering from diabetes among forty practitioner in Saudi Arabia to find out the role of socio-economic relations to diabetic incidents and complications, the practitioners looked at the inequality that exists between the people with the highest possible education and least educated. The same they applied on the richest in the society and the lowest income earners among the patients undergoing treatment. The survey made a conclusion that less educated people and the poor patients with diabetes suffer a greater effect of diabetic morbidity and have limited access to medical attention. Analytical studies in the recent times have revealed that the cases of diabetes complications are constantly on the rise among the Saudi Arabian population. Currently, the effect has been felt to be covering between 23 to 30 per cent of the entire population of Saudi Arabia (Mufti, 2000). This project will be very essential to the target group because it will add value by minimizing the already existing knowledge disparities between diabetic nephropathy and the effects of socioeconomic factors among the Saudi Arabian population. The studies leave room for further investigations to perfect the measures of the different in the level of education as well as the level of adherence to their medication between the two groups. 3. Research Methodology 3.1. Design The research will use data from the Case Study conducted from the Diabetic Registry centre in Riyadh, Saudi Arabia. It will use structured questionnaires to explore two cases of diabetic conditions. There will be two categories of tests in conducting the methodology; the test case and the control case. The test case will be branded “Diabetic Nephropathy”. It will consist of diagnostic test for diabetes with complication. The second case will be the control case branded ‘Diabetic’. It will consist of diagnostic tests for diabetes without complications. This diagnosis will be conducted on the basis of the results from the analysis and representation of the information that we will receive from data analysis. Both case test and control test will compare other vital parameters such as the age, sex and the duration in which the patient suffered from diabetes. The questionnaire will take care of the case as well as the control study. It will compare the factors as they appear in the two situations to compare the effects, of course deriving the measures from the responses in the questionnaire. The research has opted to use questionnaires as the most reliable tool for data collection, because questionnaire has a documented evidence of the respondents, making the results of data analysis valid. Interviews could be effective, but does not easily indemnify the research teams in cases that involve ethical matters and require protection from legal risks. Secondly, questionnaire enables our research team to collect data from a large sample, because interview and observation does not reveal hidden factors. Interview can only work in a smaller sample set, and observation is based on individual prejudices. The table below will represent the responses and the measures of socio-economic parameters affecting the rate of diabetes incidents in a tabulated comparison. Serial No Parameters Diabetes Diabetes with Nephropathy 1 Income 2 Level of education 3 Number of Children 4 Cost of Housing 5 Gender Table 1: Comparing diabetes and diabetes with nephropathy. The data the tabulated results will be used to make analysis and conclusion that will be used as practical tool for testing the hypothesis. This is where we will be able to identify the case that has greater influence of socio-economic status (SES) on diabetes and diabetes with nephropathy (Edmonds et al., 2008). The questionnaire contains a list of open ended-questions that require voluntary response. They test the socio-economic status of the patient including their financial status and the level of awareness of diabetes. After data collection, the next stage of the analytical research is data analysis. This will involve the use of professional data analysis tools such as SPSS or STATA to perform data analysis on the data that have been collected. The analysis is supposed to provide aggregate results of the functions and parameters of significance to the study of socio-economic factors and diabetes complications in Saudi Arabia. The aggregate functions will provide measurable information resulting from qualitative data. The measurable aggregate values include averages, maximum, minimum, sums, variances, standard errors, standard deviations, correlations and regression coefficients. The data analysis will lead to appropriate interpretation of the results. It will be easy to derive interpretations in form of inferences such as “60 percent of the diabetes patients are from poor families”, or “the Riyadh Centre for Diabetes receives an average of 200 diabetes patients, out of whom 65 percent is illiterate”. The interpretation will enable us to present the aggregate functions in simple professional forms such as graphs, pie charts, tables and histograms. Out of data presentation, we will be able to make conclusions and possible recommendations that stakeholders will make use of in order to improve the socio-economic status (SES) of the Saudi Arabia population. This entirely depends on the result of the conclusion, because the conclusion is the real test of the research hypothesis (Twaddle, 2002). Our recommendations will be of great significance to the stakeholders whether we qualify the hypothesis or the hypothesis fails the validity test (Alqurashi et al., 2011). The challenge will only be in the accuracy of the data that the respondents provide. To take care of the errors that may exist in the data we have collected, we create a provision for errors, which we can tolerate within our calculations. Our areas of interest will narrow down to the aggregate functions of socio-economic status. 3.2. Materials This study uses primary data from the questionnaire that we will distribute to the respondents in the Centre for Diabetes in Riyadh, Saudi Arabia. For the purpose of detailed study of diabetes complication, we will use professional academic materials from various sources including recent research works. The materials will provide this study with an appropriate way to use the case-control study in evaluating the disparities between the group considering the social-demographic properties, information and compliance of the diabetic patients in Riyadh Diabetic Center to the recommended guidelines (AL-Nonzha et al., 2004). They will further suggest valid attributes of diabetes-related information apart from the information that the questionnaires will provide. The questionnaire mainly extracts bio data information from the respondents with socio-economic parameters. Both of the two separate questionnaires will have to be interpreted into Arabic, since it is the main language in Saudi Arabia, to eliminate the limitation of language barrier. The data in socio-economic information mainly will be derived from various gulf nations. We are also going to use the periodic journals that the Center for Diabetes in Riyadh releases, to observe the past behavioral attribute of the disease complication in Saudi Arabia, and compare the results along the line of social and economic status of various classes. 3.3. Sample This research will use random sampling by selecting two sample sets for the test of hypothesis. One of the sample sets is the source of information for the control case study. The next sample is the bio data and socio-economic information for the case study from the Centre of Diabetes in Riyadh (AL-Maskari et al., 2013). In the survey, we will gather the samples of information and perform analysis from which we will conclude on the whole set. In this case, the whole sample set refers to the entire population of Saudi Arabia. Random sampling is more reliable because it represents the actual situation of socio economic factors in a typical society (AL-Adsani et al., 2009). The strength of random sampling is that it is a quick selection of a holistic representation of the entire population. The people who are going to be selected are going to represent the whole country, Saudi Arabia. The weakness is that the sample selected may not guarantee an accurate approximation of the actual information. Random sampling suffers from uncertainties and non uniform factors. This is because the sample may have experienced an unusual interfering factor that could lead to wrong conclusions (Agardh et al., 2011). 3.4. Procedure This is a qualitative research that will follow the usual procedure of conducting research works. It begins from the preliminary studies out of which we create hypothesis and the research questions. The next stage is to prepare data collection tools, of course after deciding on the data collection method of choice. In this study, we have prepared a well structured questionnaire that we will distribute to our respondent groups. From the data collected, we can move to the stage of data analysis, data interpretation, presentation and conclusion. The analysis stage demands that we convert all qualitative data into quantitative data. In the entire procedure, the end result will be the preparation of the research paper in a professionally recommendable way. Respondents to the questionnaires will simply be issued with the papers and left to fill according to their own judgments. Whenever a person does not respond to any question, it will be important to skip that response and exclude it from the valid data. 4. Ethical issues The process of conducting this research expects to encounter certain ethical issues, which demand a lot of caution. 4.1. The approach and recruitment of subjects We have to conduct a title check from all sources to ensure that the subject of our study is a unique one to avoid falling into possibility of plagiarism and resultant legal challenges. It covers even the contents of the research documentation. Of course plagiarism is a matter of ethics and needs to be avoided in every section of this research. Secondly, the research contents have to be relevant and consistent to the topic being studied. Finally, the information presented in this study has to be of utmost honesty. This is why we opted for questionnaire instead of other methods of data collection to provide documented evidence to support our raw data. We also reference sources of our secondary data to prove the honesty of our claims. 4.2. Informed consent procedures We avoid ethical community issues by informing our target groups prior to our visit about our intended action and dire need of their cooperation in the procedure. We have to inform the Riyadh Diabetes Centre in writing and wait for their acceptance before we begin data collection. We then allow them to sign a consent page as a proof of their awareness of the procedure. In the questionnaire, we avoid asking sensitive questions, especially the personal details that could possibly deprive the respondents of their rights to privacy. When we finally publish our research document, we present an acknowledgement page, where we recognize with due respect, the contributors to our project at various capacities. 4.3. Data management/storage This project will have data both in hard print outs, questionnaires and in electronic copy. We will have a common database in which all our external data are backed up. We then have to create at least 3 back up storages other than the database server, in which we periodically transfer our information and to be able to perform data recovery and audit trail in the event of a disaster leading to data loss. We will create high level security protection requiring approval, verification and authentication before a user can gain access to our data base. This is to deter unauthorized users from gaining access to our data, to protect the integrity and confidentiality of the users. We will protect the data in all back up locations from any external entities, and disconnect any existing links to external networks to prevent the possibilities of hacking and malware attacks. 4.4. Confidentiality/anonymity We promise to keep our information confidential, by first, restricting the respondents identity to anonymity. Of course our questionnaires do not have any space for personal identification by use of names. Any questionnaire where a respondent decides to input his or her names is not rejected but we countercheck to make sure he or she has signed against the names as a sign of voluntary decision to indemnify our research team from the responsibility of protecting the names. Failure to countersign means we have to nullify the questionnaire and issue a blank copy to the respondent. Our research team will have to be professionals who have practiced confidentiality and a detailed understanding of the consequences of legal breaches and unprofessional behaviours. With this assurance, we will be confident that our team will be able to maintain high level of confidentiality. 4.5. Potential negative effects, Risks and safety 4.5.1. Negative effects The process of data collection has to experience certain negative effects either from the respondents, from the prevailing government authorities or from natural features. Such situations include the challenges with uncooperative respondents, lack of honesty among the respondents and language barrier, since we have to hire interpreters before we can decipher the responses from Arabic to English. The Riyadh Diabetic Centre may not easily accept our request so we have to express the request in a way to present the dire need of their acceptance. Out of observation and experiences in research, there is usually a practice by respondents to overstate or understate their details as they fill the questionnaires (Ward & Younis, 2013). In extreme cases, respondents fill in malicious responses including insults. Majority especially in the low income earning class may not be able to fill in the questionnaires due to illiteracy. With many blank questionnaires, it may be impossible to make accurate data analysis and interpretation. 4.5.2. Potential Risks Data collection experience expects certain inherent risks such as violation of hospital regulations, hostility among the respondent and the entire target groups, natural factors such as unfavourable weather and insecurity. Of course we don’t anticipate these occurrences, but there is a possibility of their occurrences. We have to prepare on how we can respond to such events whenever they occur. The community may be suspicious of our actions and hence may totally refuse to provide the required information. 4.5.3. Safety measures To minimize the probability and prevent the impact of for such risks, we have to prepare by preparing strategies for mitigating the risks. At the inherent stage, we have to conduct ground work prior to the data collection, to understand the policies of the hospital as we familiarize ourselves with the nature of the community we are approaching. During the ground work, we will be able to seek sufficient authority from the government agencies and the authorities controlling Riyadh Centre for Diabetes (AL-Adsani et al., 2009). We also have to prepare for unfavourable weather conditions through proper dressing and accessing umbrella. Ground work will enable us to identify unexpected challenges such as the cultural and social factors within the community that may need special care. We will be able to observe the terrain and possibly prepare well for transportation and logistics. We conduct ground work to confirm whether there is a risk of violating the cultural values of the Saudi Arabia people in the process of data collection. 4.6. Sources of data/records The sources of data are from the society of real people living with the complicated case of diabetic nephropathy. This is an actual raw data that reflects the situation on the ground. There are also sources of historical information that informs the readers about the impacts of diabetes and the extent to which its complication relates to the socio-economic status (SES) of the society in Riyadh. We therefore have a mandate to protect the sources of our primary data in form of backups in electronic form. For our secondary data, we will prepare a bibliographic list of references as to aid the stakeholders in accessing full information. The records will be used to enable the target groups and all stakeholders to implement the recommendations effectively. 5. Plans for data analysis 5.1. Qualitative Analysis The plan that we have for data analysis takes consideration of the fact that majority of the data from the questionnaires are of qualitative nature and have to be converted to qualitative data so that they can be measured. Without this conversion, it may be difficult to do data analysis. We entirely depend on the results of data analysis for the purpose of making conclusion and relevant recommendations. Some of the responses of the patients on the questionnaires are in the form of “Yes” and “No”. This means that we have to convert them into quantitative data by assigning measurable values to the Yes and no responses, or to use aggregate values reflected by the overall responses for example, counting the number of Yes responses and observing the implication (AL-Maskari et al., 2013). After the conversion, we have to decide on the most appropriate data analysis method and tools to use. We propose to use either STATA or SPSS among many statistical applications. The method that we plan to use is the application of aggregate functions and values. We intend to use a combination of aggregate functions to interpret the relationship of the parameters to the current socio economic status (SES). Consequently, we will use the status of social and economic factors to interpret their implication on the trend of diabetes nephropathy. From there, we will be able to make recommendation to the stakeholders, proposing effective actions that they can carry out to improve the status of social and economic factors that affect the trend of diabetes and related complications. We will identify the relevant aggregate functions that will make meanings to our model that relates the two parameters. 5.2. Limitations of the data analysis The analysis has got a number of limitations in the sense that it depends mainly on the data from the questionnaires. The respondents may not have been accurate in the way they presented their responses. There is a risk of exaggeration of responses based on personal prejudices and observations. On another perspective, some respondents may possibly understate their responses of omit certain vital parameters. It is possible that the analysis may lead to inaccurate conclusion and misleading recommendations. This may eventually lead the research team into making irrational decisions. Since this analysis is not quantitative, it consumes a lot of efforts to convert the raw data into quantitative data before doing the actual data analysis. This kind of data analysis is limited to English, yet the data collection materials will be in Arabic. The challenge of language barrier takes a lot of efforts to overcome. Even after interpretation into English, there is a possibility of losing the meaning of certain aspects of the data owing to misunderstanding or the raw data and the explanation. 6. Time Schedule Time factor is a very vital factor for a research work. This study proposes a time schedule that guides the way we conduct our activities. This is because each activity is a prerequisite of the subsequent activity. At the same time, there are activities that can be executed concurrently, so that the research work can move on smoothly. The research will have a number of activities that require a well structured plan of implementation. The research will begin from preliminary studies followed by ground work, data collection, data analysis plan, data interpretation, data presentation, conclusion, recommendation and decision making. This will eventually culminate into the actual implementation of the recommendations by the relevant stakeholders. The recommendations are the collective action plans that the stakeholders have to make references to. Because of our recommendation for the translation of the questionnaire into Arabic language, the research work may take longer than we had expected. We have to find a qualified translator and wait for the interpretation for about 2 months. It means we have to begin our questionnaire in the early stages, probably during the preliminary studies. The work schedule for our project will have to follow the sequence of activities in the time schedule presented below. Tasks Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Preliminary Studies Ground Work Questionnaire preparation Data Collection Data Analysis Data Interpretation Data presentation Conclusion Recommendation and decision making Implementation of Action Plans Table2: Activity schedule for our project The schedule shows that our research will be able to take a period of 7 months, including the commencement of the implementation of the action plans by the various stakeholders. 7. Appendices 7.1. Consent Form I ....................................................... have voluntarily decided to fill in the questionnaire. I confirm by my signature that the information provided in the questionnaire is accurate and honest. Signature.....................................................Date............................................................. References Agardh, E., Allebeck, P., Hallqvist, J., Moradi, T., & Sidorchuk, A., 2011. Type 2 diabetes incidence and socio-economic position: a systematic review and meta-analysis. Int J Epidemiol, 40, pp. 804-18. AL-Adsani, A. M., Moussa, M. A., AL-Jasem, L. I., Abdella, N. A., & AL-Hamad, N. M., 2009. The level and determinants of diabetes knowledge in Kuwaiti adults with type 2 diabetes. Diabetes Metab, 35, pp. 121-8. AL-Maskari, F., EL-Sadig, M., AL-Kaabi, J. M., Afandi, B., Nagelkerke, N., & Yeatts, K. B., 2013. Knowledge, attitude and practices of diabetic patients in the United Arab Emirates. London: Sage. AL-Nonzha, M. M., AL-Maatouq, M. A., AL-Mazrou, Y. Y., AL-Harthi, S. S., Arafah, M. R., Khalil, M. Z., Khan, N. B., AL-Khadra, A., AL-Marzouki, K., Nouth, M. S., Abdullah, M., Attas, O., AL-Shahid, M. S., & AL-Mobeireek, A., 2004. Diabetes mellitus in Saudi Arabia. Saudi Med J, 25, pp. 1603-10. Alqurashi, K. A., Aijabri, K. S., & Bokhari, S. A., 2011. Prevalence of diabetes mellitus in a Saudi community. Ann Saudi Med, 31, pp. 19-23. Brancati, F. L., Whittle, J. C., Whelton, P. K., Seidler, A. J., & Klag, M. J., 1992. The excess incidence of diabetic end-stage renal disease among blacks. A population-based study of potential explanatory factors. JAMA, 268, pp. 3079-84. Brown, A. F., Ettner, S. L., Piette, J., Weinbergger, M., Gregg, E., Shapiro, M. F., Karter, A. J., Safford, M., Watzfelder, B., Prata, P. A. & Beckles, G. L., 2004. Socioeconomic position and health among persons with diabetes mellitus: a conceptual framework and review of the literature. Epidemiol Rev, 26, pp. 63-77. Edmonds, E. M., Foster, A. V. M., & Sanders, L., 2008. A Practical Manual of Diabetic Foot Care. London: John Wiley & Sons. Larranaga, I., Arteagoitia, J. M., Rodriguez, J. L., Gonzalez, F., Esnaola, S., Pinies, J. A., & Sentinel Practice Network of the Basque, C., 2005. Socio-economic inequalities in the prevalence of Type 2 diabetes, cardiovascular risk factors and chronic diabetic complications in the Basque Country, Spain. Diabet Med, 22, pp. 1047-53. Mufti, M. H., 2000. Healthcare Development Strategies in the Kingdom of Saudi Arabia. New York: Springer. Stelmach, W., Kaczmarczyk-Chalas, K., Bielecki, W., & Drygas, W., 2005. How education, income, control over life and life style contribute to risk factors for cardiovascular disease among adults in a post-communist country. Public Health, 119, pp. 498-508. Twaddle, A. C., 2002. Health Care Reform Efforts Around the World. Greenwood: Greenwood Publishing Group. Winkleby, M. A., & Cubbin, C., 2003. Influence of individual and neighbourhood socioeconomic status on mortality among black, Mexican-American, and white women and men in the United States. J Epidemiol Community Health, 57, pp. 444-52. Ward, W. B., & Younis, M. Z., 2013. Steps Toward a Planning Framework for Elder Care in the Arab World. New Yok: Springer. Read More