400418 | Health Promotion | Assessment Answer

Answer:

Background, brief literature and rationale

Cardiovascular disease (CVD) is concerned with the disease of the heart (cardio) and blood vessels (vascular). The affected blood vessels may be in various parts of the body. They may comprise of peripheral vascular disease and the brain manifested as a stroke. Some of the types of CVD are most common in Australia such as coronary heart diseases, heart failure, hypertension and cerebrovascular disease.

CVD is amongst the major causes of death and disability in Australia. It accounts for 17% of the overall diseases in Australia in the year 2003. Almost $5.9 Billion of direct healthcare expenditure is spent on the prevention of CVD . It represents 11% of the total allotted health system expenditure  in Australia.

This research proposal is conducted with the intention to introduce public intervention which sets the goals and objectives, planning strategies for accomplishing these goals and identification of the means to evaluate the objectives for prevention of CVD in Australia (Yang et al., 2012).

There are certain risk factors for CVD. Chronic diseases such as chronic kidney diseases, CVD and Diabetes are the risk factors for each other. Diabetes is known to be a common risk factor for CVD. There should be a framework for the prevention of these diseases. According to the Australian Institute of Health and Welfare (AIHW), the prevention of the disease or ill health pertains to the action to mitigate the reasons, factors, complexities or recurrence of ill health or diseases.

A public intervention should be developed for monitoring the actions taken and creating awareness amongst the people of Australia for mitigating the effects of these diseases. The framework should be based upon the rationale of prevention followed by the major areas in which the prevention is crucial for the health care system (Rice, 2012). 

It should be followed by prevention of the disease and the progression, complexities and reoccurrence amongst the people suffering from these diseases. There are two crucial aspects of monitoring for each of the components. These aspects pertain to the outcomes which can be prevented and the provisions of prevention services (Masters & Hooker, 2013).

In terms of monitoring of the outcomes, the public intervention would include the evaluation of the prevalence of the disease in each of the areas viz. risk factors, the disease along with their complexities comprising with their reoccurrence. These areas are required to be evaluated for analyzing the magnitude of the problem which would help in determining if the prevention activities can create the desired impact.

>So, it becomes crucial to monitor the results over time for the population in question, especially for the high-risk population groups. They comprise of Aboriginal and Torres Strait Islander people and various other socio-economic groups. It becomes helpful for comparing Australia with other countries in this context (Nghiem, Blakely, Cobiac, Pearson & Wilson, 2015).

The prevention services comprise of two activities. The first activity pertains to the promotion of health aiming to provide the best chance to maintain good health and prevention of ill health to individuals and groups. The health promotion emphasizes working with people so that they can make decisions about their needs.

Health promotion is the procedure of enabling people so that they can improve their health. The individuals and communities can control over the determinants of the health. The targets for health promotion pertain to the dietary habits of people and their physical activity patterns along with the use of tobacco and alcohol (Australian Institute of Health, 2012). 

The second activity pertains to the more therapeutic type of health care which is usually provided under the supervision of a medical practitioner. It comprises of regular health checkups, vaccinations and prescription of medications. In order to prevent the risk factors, there is a large role for promotion of health and smaller yet crucial role for health care, taxes and school-based intervention( O’Mara-Eves et al.,2015).

Monitoring of health is often associated with the care at the individual level. In order to prevent the disease, it is crucial to monitor the services and interventions at the population level. It comprises conducting campaigns through television advertisements. Evaluating the interventions at the population level proves to be a new challenge for the policymakers (Kim et al., 2016).

The various services and outcomes should be analyzed for various parts of the population. Furthermore, the specific aspects related to an environment like transport and urban design should also be considered in this behalf.

Moreover, in the context of the development of a public intervention for mitigating the effects of CVD, it has been analyzed that these diseases are highly preventable. It makes them an ideal group for monitoring in order to prevent them.  The public intervention framework comprises of evaluation of risk factors of the preventable disease and prevention of complexities in the people suffering from these diseases.

The rationale for conducting this research is to identify the information about the risk factors which need to be monitored for the prevention of CVD. These can be individual risk factor frequency, the prevalence of multiple risk factors and presence of absolute risk. The individual risk factor frequency comprises of evaluation of incidences and prevalence of the main risk factors including behaviors such as physical inactivity, obesity, high blood pressure and smoking (O'Hara et al. 2012).

This research proposal outlines the goals and strategies for the accomplishment of these goals along with identifying the means for evaluating the objectives. It also aims at justifying the public health importance of the health outcome.

The population-level interventions and services are the more relevant for prevention of risk factors. The framework of public health intervention is based on the approaches used by the World Health Organization (WHO). It covers the laws, regulations, taxation mechanisms, creating awareness through campaigns and approaches to build the environment and intervention through community, school and workplace.

In this regard, the programs for preventing and detecting CVD could comprise of organized screening or risk assessment programs along with clinical guidelines. The clinical guidelines for prevention of complications is a population-based initiative (Dombrowski et al.,2012).

Aims and objectives

The research proposal is aimed at prevention of the risk factors for CVD. The research is intended to evaluate the position of Australia in the prevention of risk factors along with informing the future monitoring for prevention of these conditions and tracking their progress.

The research questions pertain to the following aims and objectives of the study:

• What is the national prevalence of the risk factors for CVD?
• What kind of individual-level services are used for the prevention of the risk factors in the people suffering from this disease?
• What population level initiatives are being implemented for the prevention of the risk factors in people suffering from this disease?

Study method

A survey is conducted for studying the various risk factors for CVD. The study further analyses the collection of data from January 2018 to October 2018. The survey is intended to develop a framework for the prevention of CVD on the basis of the data collected from the sample of Australian adults aged between 30 and 65 years.

The name of the survey is Heart Watch and it is an online survey which is a Computer Assisted Phone Survey. It would be reported from the data retrieved from the cross-sectional samples amongst the Australian adults who are aged between 30 years and 65 years ( O’Neil et al.,2013).

In this regard, mixed research methods are used. Mixed research methods comprise qualitative and quantitative methods. Qualitative methods comprise of literature review and a scientific method of gathering non numeric data which has been stated at the beginning of this research proposal. Quantitative methods are the process of gathering numeric data. In this research proposal, information is collected through an online sample survey (Cabassa et al., 2013).

Sampling Methods

The non-probability sampling methodology was used with all the members of the panel qualifying for the completion of the survey regarding their quotas for age, gender and areas of residence so that the responses of the population of Australia can be reflected on the basis of Australian Demographic Census. This survey considers the understanding about the heart diseases and their associated factors along with health behaviors and conditions of the Australian people (Smith, 2015).

The sample took an average of 30 minutes for its completion. The participation was voluntary and the participants were notified about the protection of their information and responses. They would be treated as strictly confidential ( Hoare, Stavreski,  Kingwell  & Jennings, 2017).

Sample size and power

A total number of 50 participants aged about 30-60 years had completed the survey and they were included in the subsequent analysis. They also represented the population of Australia in terms of age, areas of residence and sex ( Davis et al.,2015).

Intervention

The interventions are aimed at preventing CVD from Australia and they have a great potential to improve their health and reduction of inequalities. The research intervention can pertain to economic evaluations which can assist the policy makers for determining a value for money methods for improving the health of Australians ( Nghiem, Blakely, Cobiac, Pearson & Wilson,2015).

There is a need for allocating additional resources for addressing the health of Australians particularly the indigenous population. it should be widely reflected in policy recommendations of Australia. So, the more economic evidence is required for decision making in an appropriate manner( Lee, Lee, Kim & Kang, 2012).

Data collection methods

Both quantitative and qualitative methods were used for collection of data. The non-probability sampling methodology was used regarding the survey regarding their quotas for age, gender and areas of residence as quantitative data. Furthermore, the responses of the population of Australia can be reflected on the basis of Australian Demographic Census.

Qualitative data comprises of retrieval of data from relevant literature and peer review articles by various scholars (Balagopal, Kamalamma, Patel & Misra, 2012).

Quantitative data related to the weight, height and consumption methods was analyzed through  Stata release V.14.1. Random tests were conducted for checking the status of weights of the participants. The missing and non-missing data in this regard was evaluated with the help of logistic regression models and the chi-square test.

The weight status of the participants was retrieved on the basis of criteria prescribed by the World Health Organization (WHO) in which BMI>25kg/m² is considered to be overweight. The weight which equals to or > 30 kg/ m² is considered to be obese ( Aikins, Kushitor, Koram, Gyamfi  & Ogedegbe, 2014).

Ethical approval

In this research proposal, the researchers have applied the Data Safety and Security Act 1988 so that the information provided by the participants is secured and kept confidential. It is further intended to make a robust relationship with them. Some of the factors such as manipulation of data and university regulation and reference are also considered by the researchers. It would help in avoiding ethical issues from the research (Antman & Harrington, 2012).

Data analyses

As discussed above, the data were analyzed using the Stata release V.14.1. All the variables are verified for the missing data. Apart from the status of weight, there were less than 5% values for the other factors, so the case-wise deletion was applied accordingly.

The missing and non-missing weight status was analyzed with the help of chi-square tests and logistic regression models. They were used as a subset of predictor variables viz. gender, age and education were found associated with the missing data regarding the status of weight.

The case wise deletion was considered proper as unbiased estimates. The predictor variables in the final regression model were included. They were further based on the previous recommendations that the missing data less than 10% should not be expected for introducing biases ( Lewis, 2015).

The participant characteristics and descriptive data were calculated with 95% confidence intervals. The correlation between a variety of health and demographic characteristics with respective genetic, lifestyle, clinical and psychological risk factors were assessed with the help of logistic regression models. They were expressed as odds ratios using 95% confidence intervals.

Every risk factor which was a dependent variable is examined in different models with the identified predictor variables such as age, gender, level of education, weight, the area of residence, diagnostic status and medication. It is also assessed if the participant has  experienced a heart attack recently.

The aim of this analysis was to evaluate the variations in the level of knowledge associated with the risk factors for heart diseases which are based on health and demographic factors ( Klasnja  & Pratt, 2012).

Proposed action plan

With the reference of the proposed action plan, the first step in the preparation of the research proposal would be setting of objectives, strategies and interventions for conducting of the research (Santschi, Chiolero, Paradis, Colosimo & Burnand, 2012).  

The objective of the research is to develop a framework for monitoring the strategies adopted for the prevention of CVD from Australia. The timeline is from January 2018 to February 2018.

The second step is to identify the resources needed for conducting of research. The resources can be acquiring equipment   which would help in retrieval of appropriate data required for conducting the research. The timeline is March   2018 to April   2018.

The third step would be the preparation of budget required for conducting research. The time line would be from May   2018 to June    2018. The budget of $200 K is approved for each year and the research is intended to be completed in 2 years. So the total budget would be $400K.

The fourth step would be the acquisition of additional resources required for conducting research. The timeline is July 2018.

The fifth step is the collection of data. It would require 3 months from August   2018 to October   2018.

The sixth step would analyze the data. The time required for it would be 3 months from November 2018 to January   2019.

The seventh step would be to evaluate the data. The time required for it would be 3 months from February 2019 to April 2019.

The eight-step would be a declaration of its outcomes. The time required for it would be 3 months from May 2019-July 2019.

The ninth step would be report writing. It would require 3 months from August 2019- October 2019. The last step would be a final submission of the report. It would require two months from November 2019 to December 2019.

Anticipated outcomes and significance

Out of 50 participants, a quarter of males had been taking medications for high blood pressure and heart diseases as compared to females of the same number. About one-tenth of them are being anticipated to be diagnosed with heart disease. About 2% of females and 4% of males are anticipated to be suffering from heart attacks during the past 2 years (Kripalani et al., 2012).

The health characteristics of this sample are similar to the Heath Survey Findings of 2014-2015 conducted on the wider population of Australia.  It is anticipated that about 47% of the sample will identify the leading cause of death among males as a heart attack. About 26% of women will agree that the leading cause of death amongst them is a heart attack (Cobiac et al.,2012).

About 58% of the respondents believe that poor diet is the main risk factor for heart attack. About 49% of them believe that physical inactivity causes CVD, 39% believe it is smoking and 31% are of the opinion that it is obesity.

About 6% nominated high blood pressure and 10% believed that high cholesterol levels are the less frequent clinical risk factors for heart attacks. Out of the risk factors for heart attacks,  more females recognize the risk factors for heart attacks as compared to males. However, both groups identify poor diet as a major risk factor for heart attack (Brownson,2017). 

The significance of these outcomes would be to create awareness amongst both the groups to mitigate the impact of CVD in Australia. The research is aimed at creating a framework which would help the people to transform their lifestyles and eating habits so that they do not suffer from CVD.

The study also analyses that an improved awareness of the clinical risk factors for the CVD is required.

Strategies to evaluate outcomes

Several implications for evaluating the outcomes were adopted. It has been made clear from this study that lifestyle factors are the major causes of the CVD. The analytical method adopted in this study is likely to have a bias amongst the participants who were interested in participating in lieu of payments.

About half of the sample identified that heart disease is the main cause of death among men. It appears that there are misconceptions that the proportion of deaths are directly attributed to heart diseases amongst Australian adults (Widmer et al., 2015).

The findings here reveal that further investigation is required for evaluating the misconceptions regarding health and potential behavior along with the health outcomes amongst men and women in Australian.

According to the knowledge of the author, it is the first comprehensive analysis of the population level representations regarding the beliefs about the causes of death in the people of Australia. They further reveal the awareness about the risk factors causing heart diseases (Craig et al., 2012).

Proposed timeline

The proposed budget, and justification of budget

Budget

For this research, a budget of $400K for two years is estimated to attain the research objectives systematically .

The researcher would require a budget of $100 K for literature review as data would be collected for research. The data collection would require $200 K as the researchers would require resources for collecting of data. The analysis of data requires $100 K as data would be analyzed prior to the declaration of outcomes ( Waldstein & Elias, 2015). 

References

Aikins, A. D. G., Kushitor, M., Koram, K., Gyamfi, S. & Ogedegbe, G. (2014). Chronic non-communicable diseases and the challenge of universal health coverage: insights from community-based cardiovascular disease research in urban poor communities in Accra, Ghana. BMC Public Health, 14(2), S3.

Antman, E. M. & Harrington, R. A. (2012). Transforming clinical trials in cardiovascular disease: mission critical for health and economic well-being. Jama, 308(17), 1743-1744.

Australian Institute of Health (2012). Australia's Health 2012: In Brief. Retrieved 29^th October ,2018 from https://www.aihw.gov.au/reports/australias-health/australias-health-2012-in-brief/contents/table-of-contents

Balagopal, P., Kamalamma, N., Patel, T. G. & Misra, R. (2012). A community-based participatory diabetes prevention and management intervention in rural India using community health workers. The Diabetes Educator, 38(6), 822-834.

Brownson, R. C. (2017). Dissemination and implementation research in health: translating science to practice. Oxford : Oxford University Press. 1-100.

Cabassa, L. J., Parcesepe, A., Nicasio, A., Baxter, E., Tsemberis, S. & Lewis-Fernández, R. (2013). Health and wellness photovoice project: engaging consumers with serious mental illness in health care interventions. Qualitative Health Research, 23(5), 618-630.

Cobiac, L. J., Magnus, A., Lim, S., Barendregt, J. J., Carter, R. & Vos, T. (2012). Which interventions offer best value for money in primary prevention of cardiovascular disease?. PloS one, 7(7), e41842.

Craig, P., Cooper, C., Gunnell, D., Haw, S., Lawson, K., Macintyre, S. & Thompson, S. (2012). Using natural experiments to evaluate population health interventions: new Medical Research Council guidance. J Epidemiol Community Health, jech-2011.66(12),1182-1186.

Davis, C. R., Bryan, J., Hodgson, J. M., Wilson, C., Dhillon, V. & Murphy, K. J. (2015). A randomised controlled intervention trial evaluating the efficacy of an Australianised Mediterranean diet compared to the habitual Australian diet on cognitive function, psychological wellbeing and cardiovascular health in healthy older adults (MedLey study): Protocol paper. BMC Nutrition, 1(1), 35.

Dombrowski, S. U., Sniehotta, F. F., Avenell, A., Johnston, M., MacLennan, G. & Araújo-Soares, V. (2012). Identifying active ingredients in complex behavioural interventions for obese adults with obesity-related co-morbidities or additional risk factors for co-morbidities: a systematic review. Health Psychology Review, 6(1), 7-32.

Hoare, E., Stavreski, B., Kingwell, B. A. & Jennings, G. L. (2017). Australian adults' behaviors, knowledge and perceptions of risk factors for heart disease: A cross-sectional study. Preventive medicine reports, 8(2017), 204-209

Kim, K., Choi, J. S., Choi, E., Nieman, C. L., Joo, J. H., Lin, F. R. & Han, H. R. (2016). Effects of community-based health worker interventions to improve chronic disease management and care among vulnerable populations: a systematic review. American journal of public health, 106(4), e3-e28.

Klasnja, P. & Pratt, W. (2012). Healthcare in the pocket: mapping the space of mobile-phone health interventions. Journal of biomedical informatics, 45(1), 184-198.

Kripalani, S., Roumie, C. L., Dalal, A. K., Cawthon, C., Businger, A., Eden, S. K. & Huang, R. L. (2012). Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial. Annals of internal medicine, 157(1), 1-10.

Lee, T. W., Lee, S. H., Kim, H. H. & Kang, S. J. (2012). Effective intervention strategies to improve health outcomes for cardiovascular disease patients with low health literacy skills: a systematic review. Asian Nursing Research, 6(4), 128-136.

Lewis, S. (2015). Qualitative inquiry and research design: Choosing among five approaches. Health promotion practice, 16(4), 473-475.

Masters, K. S. & Hooker, S. A. (2013). Religiousness/spirituality, cardiovascular disease, and cancer: Cultural integration for health research and intervention. Journal of Consulting and Clinical Psychology, 81(2), 206.

Nghiem, N., Blakely, T., Cobiac, L. J., Pearson, A. L. & Wilson, N. (2015). Health and economic impacts of eight different dietary salt reduction interventions. PLoS One, 10(4), e0123915.

Nghiem, N., Blakely, T., Cobiac, L. J., Pearson, A. L. & Wilson, N. (2015). Health and economic impacts of eight different dietary salt reduction interventions. PLoS One, 10(4), e0123915.

O’Mara-Eves, A., Brunton, G., Oliver, S., Kavanagh, J., Jamal, F. & Thomas, J. (2015). The effectiveness of community engagement in public health interventions for disadvantaged groups: a meta-analysis. BMC public health, 15(1), 129.

O’Neil, A., Stevenson, C. E., Williams, E. D., Mortimer, D., Oldenburg, B. & Sanderson, K. (2013). The health-related quality of life burden of co-morbid cardiovascular disease and major depressive disorder in Australia: findings from a population-based, cross-sectional study. Quality of life research, 22(1), 37-44.

O'Hara, B. J., Phongsavan, P., Venugopal, K., Eakin, E. G., Eggins, D., Caterson, H . & Bauman, A. E. (2012). Effectiveness of Australia's Get Healthy Information and Coaching Service®: translational research with population wide impact. Preventive medicine, 55(4), 292-298.

Rice, V. H.  (2012). Handbook of stress, coping, and health: Implications for nursing research, theory, and practice. Melbourne : Sage. 1-100.

Santschi, V., Chiolero, A., Paradis, G., Colosimo, A. L. & Burnand, B. (2012). Pharmacist interventions to improve cardiovascular disease risk factors in diabetes: a systematic review and meta-analysis of randomized controlled trials. Diabetes care, 35(12), 2706-2717.

Smith, J. A. (2015). Qualitative psychology: A practical guide to research methods. Melbourne  : Sage. 1-100.

Waldstein, S. R.  & Elias, M. F.  (2015). Neuropsychology of cardiovascular disease. UK: Psychology Press. 1-100.

Widmer, R. J., Collins, N. M., Collins, C. S., West, C. P., Lerman, L. O. & Lerman, A. (2015). Digital health interventions for the prevention of cardiovascular disease: a systematic review and meta-analysis. In Mayo Clinic Proceedings, 90( 4), 469-480.

Yang, Q., Cogswell, M. E., Flanders, W. D., Hong, Y., Zhang, Z., Loustalot, F. & Hu, F. B. (2012). Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults. Jama, 307(12), 1273-1283.