Findings Used For Public Health Planning And Policy

Findings Used To Make Public Health Planning And Policy

Findings Used to Make Public Health Planning and Policy Decisions Unit 4 - HA560 March 28, 2016 There has been increased concern among policy makers, scientists and communities that health is greatly affected by a number of factors that occur in a person’s lifetime and in multi levels. Prevention is sententious to curb occurrence of any disease within the population, and it has to come first even if access to quality healthcare services is provided. To adequately promote health and prevent diseases, certain policies and factors need to be addressed mostly factors that are related to health behaviors. Social psychology is all about understanding individuals’ behavior specifically in a social setting.

Basically, social psychology focuses on factors that influence people to behave in certain ways in presence of others. The two greatest contributors in the field of social psychology were Allport (1920) and Bandura (1963). To begin with, according to Allport; he argued that the interaction of individuals with others or the presence of social groups can encourage the development of certain behaviors (Kassin, 2014). This is what Allport referred to as social facilitation, in his research he identified that an audience will facilitate the performance of an actor in a well learnt and understood task; however the performance of the same actor will decrease in performance on difficult tasks which are newly learnt, and this is contributed by social inhibition.

The second contributor in the field of social psychology is Bandura (1963), in his work he developed a notion that behavior in the social world could be possibly modeled, and this is what he referred to as social learning theory. He gave his explanation with three groups of children who were watching a video where in the video an adult showed aggressiveness towards a “bobo doll” and the adults who displayed such behavior were awarded by another adult or were just punished. Therefore Bandura found that children who saw the adult being rewarded were found to be more likely to imitate that adult’s behavior. Certain theories play important roles in health assessment, and a theory is defined as a collection of concepts in specific area of concern or interest in the world that need explanations, intervening and prediction.

Theories need to be backed up with evidence that tend to explain why things will happen in relation to current situations, and followed with some actions to turn situations in certain desirable ways. Health assessment can be defined as a plan of care that recognizes specific person’s health needs and how such needs will be addressed by healthcare system or any other health institutions (Jarvis, 2008). Generally, health assessment is the evaluation of health status through examination of physical and psychological concerns after looking at the health history of the victim assessed. The main purpose of health assessment is early detection of diseases on individuals who might seem to be well. Theories can be applied during health assessment to explain why individuals display certain behaviors or why some people are likely to develop certain illnesses.

Physicians also use general theoretical concepts to prescribe the right course of treatments for their patients. Theories such as social learning theories and health belief models play a great role in health assessment, the two theories together with self-efficacy and locus of control have both been applied to explain, predict and influence behaviors. Theories can also help in shaping advocacy and public policy, advocacy is the act of influencing public policy and practices and it entails a point of view or a taken action to influence. Theory of change has been widely used to advocate for change in public policies, this theory is defined as a specific type of methodology used in planning, participation, and evaluating what is actually used in philanthropy not for profit gains or government sectors but to bring about change.

Therefore theory of change can be applied to advocate for changes in undesirable public health policies and substitute them with policies which are desirable. Collection of empirical data is essential in science. Basically, scientific methods entail observing a phenomenon and coming up with an idea of what is observed and finally testing the idea to determine whether it is correct. In addition, the results of the test have to be recorded, analyzed and conclusion written. Therefore the result from the experiment which has been found to be true is the empirical data, empirical means that the information is based on experience.

Empirical data is the information gathered by scientists through observations and experiments (Holcomb, 2007). Empirical data will actually lead to empirical evidence once the research is tested and concluded, therefore empirical evidence can be used in community health assessment. The empirical evidence can be used to determine community health needs and possible solutions to address these needs, in most cases there are no standard procedures for conducting community health assessment, however, the best proposed practices are like application of empirical evidence. Once empirical data is collected within the community and proved, the data can be used as evidence to determine the policy weakness areas in planning and policy.

Evidence obtained from community practices, programs and policies is used to suggest potential policy impacts, the data can be used to plan for the community in terms of their health needs and change or modify policies which are unfavorable for the community. 1. Name of your county and state . Miami, Florida

2. Population of your county with racial and gender breakdowns

Population estimates, July 1, 2015, (V2015) – 321,418, 820 Female persons, percent, July 1, 2014, (V2014) – N/A 50.8% Female persons, percent, April 1, 2010 – 50.2% 50.8% White alone, percent, July 1, 2014, (V2014) – 77.4% Black or African American alone, percent, July 1, 2014, (V.2%) American Indian and Alaska native alone, percent, July 1, 2014 – 0.2% Asian alone, percent, July 1, 2014 (V2014) – 5.4% Native Hawaiian and other Pacific Islander alone, percent, July 2014 – 0.2% Hispanic or Latino, percent, July 1 2014, (V2014) – 17.4%

3. Number of senior citizens

Persons 65 years and over, percent July 1, 2014, (V.4%) – data missing, Persons 65 years and over, percent, April 1, 2010 – 0.0%

4. Number of disabled individuals

With a disability, under age 65 years, percent, April 1, 2010 – 7.6%; With a disability, under age 65 years, percent, July 1, 2014 – 8.5%

5. Number of children

Persons under 5 years, percent, July 1, 2014 – data missing; Persons under 18 years, percent, July 1, 2014 – data missing

The chosen population is senior citizens above 65 years of age, referred to as the aging population. This group faces various health concerns impacting their daily lives, notably heart disease and cancer. According to the CDC, heart disease is the leading cause of death among adults over 65, with nearly 488,156 deaths in 2013. In Miami, Florida, data indicates that heart disease affects more men than women in this age group, with 37% of men and 26% of women affected. Increased age-related risk factors such as hypertension and hyperlipidemia contribute to this prevalence.

Furthermore, cancer ranks as the second leading cause of death among seniors, with approximately 407,558 deaths recorded in 2013. The CDC reports that roughly 28% of men and 21% of women over 65 are diagnosed with cancer. Lung cancer, in particular, presents significant health challenges, often linked to risk factors like smoking, environmental carcinogens, and genetic predisposition. From a risk assessment perspective, individuals who avoid smoking, secondhand smoke exposure, and environmental carcinogens tend to have a lower risk of developing lung cancer. Preventive measures, including early screening, lifestyle modifications, and reducing exposure to carcinogens, are crucial for minimizing incidence rates.

To maintain optimal health and reduce the risk of lung cancer, recommended strategies include abstaining from smoking, testing for radon exposure at home, limiting contact with known carcinogens, and adopting a balanced diet rich in proteins, fruits, and vegetables. These measures are supported by health experts and evidence-based public health practices (Jarvis, 2008). Epidemiological data underscores the importance of targeted health interventions for high-risk groups, specifically the aging population, to decrease morbidity and mortality associated with chronic diseases such as heart disease and cancer.

Paper For Above instruction

Public health planning and policy decision-making are fundamentally driven by the analysis of empirical data and theoretical frameworks that elucidate health behaviors. Understanding the factors influencing health-related behaviors, particularly among vulnerable populations like seniors, is critical to developing effective interventions. Social psychology, with its foundational contributions from Allport and Bandura, provides vital insights into the social determinants of health behaviors, which are essential components in shaping public health policies.

Allport’s concept of social facilitation and social inhibition emphasizes the influence of social environments on individual behaviors. In public health, this translates to understanding how social contexts, peer groups, and societal norms can either promote or hinder healthy behaviors. Bandura’s social learning theory further elucidates how observing and modeling behaviors—especially through media or peer interactions—can influence health practices. For example, children and adults observe behaviors, such as smoking or exercising, and adopt these based on perceived rewards or punishments, shaping health outcomes over time.

Applying these psychological principles within community health assessments enables health professionals to identify environmental and social factors that contribute to health behaviors. This underscores the importance of evidence-based practices, as empirical data collected from communities can reveal behaviors linked to chronic diseases, thereby guiding policy formation. Empirical data serves as a backbone for evaluating community needs, identifying gaps, and tailoring intervention programs that are culturally and socially appropriate.

In the context of aging populations, such as in Miami, Florida, empirical data highlight specific health challenges, including heart disease and cancer. The demographic profile of Miami’s senior citizens illustrates the intersection of various social determinants, such as racial and socioeconomic disparities, which influence health outcomes. For instance, cardiovascular disease remains the leading cause of death among seniors, with risk factors aggravated by lifestyle, environmental, and genetic components. Preventive strategies including lifestyle modifications, screening programs, and health education are vital for mitigating these risks.

Research suggests that targeted public health policies focusing on behavioral modification can significantly reduce the burden of chronic diseases. For example, promoting smoking cessation and improving access to screenings for early cancer detection are proven interventions that can decrease mortality rates among seniors. Policy development should incorporate theoretical models such as the Health Belief Model and Self-Efficacy Theory, which address psychological factors influencing health behaviors. The Health Belief Model emphasizes perceived susceptibility and benefits of action, guiding messaging for health promotion. Self-efficacy, or confidence in one’s ability to perform a health behavior, predicts adherence to health interventions.

Additionally, health advocacy plays a crucial role in translating empirical evidence into policy change. The Theory of Change provides a structured methodology for planning, participating, and evaluating interventions aimed at health improvement. It helps stakeholders understand the pathways through which behavioral, social, and policy changes lead to better health outcomes. For instance, advocating for policies that promote smoke-free environments or increase funding for community health clinics can directly influence health behaviors among seniors.

Collecting high-quality empirical data involves systematic observation, experimentation, and evaluation, which underpin sound policy decisions. Community-based participatory research (CBPR) methods foster engagement with community members, ensuring data relevance and cultural sensitivity. Such approaches have been demonstrated to improve the effectiveness of public health interventions by ensuring they resonate with local populations and address specific needs.

In conclusion, leveraging findings from social psychology, empirical data collection, and theoretical models advances public health planning. These strategies enhance our understanding of health behaviors, especially within vulnerable communities like the elderly in Miami. Policymakers who integrate evidence-based insights can craft targeted interventions that promote health, prevent disease, and ultimately improve quality of life for aging populations.

References

• Holcomb, Z. C. (2007). Real data: A statistics workbook based on empirical data. Pyrczak Publishing.
• Jarvis, C. (2008). Physical examination & health assessment. Saunders Elsevier.
• Kassin, S. M., Fein, S., & Markus, H. R. (2014). Social psychology. Wadsworth.
• Centers for Disease Control and Prevention (CDC). (2014). Heart Disease Facts. CDC.
• Centers for Disease Control and Prevention (CDC). (2014). Cancer Data & Statistics. CDC.
• Bandura, A. (1963). Social learning and personality development. Holt, Rinehart & Winston.
• Allport, G. W. (1920). Social psychology. Houghton Mifflin.
• Holcomb, Z. C. (2007). Real data: A statistics workbook based on empirical data. Pyrczak Publishing.
• Jarvis, C. (2008). Physical examination & health assessment. Elsevier.
• Waidmann, T. A., & Rajan, S. (2001). Race and sex disparities in mortality. Journal of Health Economics, 20(3), 391–408.