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This week, you will receive feedback from your instructor on your rough draft assignment. You will edit, revise, and add any additional information to your literature review based on your instructor feedback and additional research and reading. This submission should be more polished than your previous version. As you continue to read about your chosen research topic, feel free to add to your literature review and make it even more meaningful for your research proposal. The following requirements should be met in your literature review: Include a minimum of six scholarly sources Organize in logical sections Include an overview of the literature Be unbiased in your presentation of information Include sources and content relevant to your research questions and hypothesis; state the relevance in your literature review Include a critical assessment of the sources. Do not simply include a summary of what you have read A strong introduction and conclusion, including further questions for research Research Questions What are the perceived effects of mindfulness-based interventions (MBIs) on stress levels among nurses working in Intensive Care Units (ICUs)? How do ICU nurses perceive the feasibility and acceptability of integrating MBIs into their daily routine? What are the potential barriers and facilitators to successfully implementing MBIs for stress reduction in ICU nursing staff?

Discussion  MEASURES USED IN EPIDEMIOLOGY 

   Discussion DATA SCIENCE APPLICATIONS AND PROCESSES

Using CDC Wonder databases: write about Childhood cancer in VA. what you learned from the data, and how aggregate population data impacts nursing practice.

  How does the nursing metaparadigm impact the implementation of culturally proficient nursing care?  Your initial post should be at least 500 words, formatted, and cited in current APA style with support from at least 2 academic sources. Submit your initial post as a Word document

PLEASE NOTE: WEEK 3 AND 4 DISCUSSIONS ARE A PART OF YOUR STATISTICAL APPLICATION PRESENTATION AND ARE WEIGHED MORE THAN A TYPICAL DISCUSSION (see syllabus for details) Instructions for Initial Post This Week 1.) Visit the following page: https://www.cdc.gov/DataStatistics/Links to an external site. 2.) Under "Data and Stats by Topic", pick a topic you find interesting. Click on the topic. After you choose a topic be sure to put in that information in the previous page title PICK YOUR TOPIC HERE. Do not delete anyone else's information on that page. Do not select a topic that has already been selected. 3.) Here, you will find a lot of data and information concerning your topic. You will pick a set of data and create a graphical representation for it, (i.e. a line graph, bar graph, pie chart). Make note: you MUST create your OWN graphical representation. Copied graphs DO NOT COUNT. You must cite the source of this data set in your initial post, using proper APA formatting. 4.) In your initial post, due by Day 4, you will introduce your topic and its importance along with discussing methodology and numerical findings in the data. You will also include your graphical representation and give a summary of it. You may post your graphical representation as an image directly into the textbox, copied from Excel or another program/website

Replies 1: When there is an uptick in illness, it is important to find out the cause and source of origin to prevent further spread. The first step is to collect data on who is getting sick and where they are located. Patterns may be seen by the locations of those affected. Through interviews with those who are ill, a hypothesis will begin to form about the root cause of the outbreak.  Below is a bar chart of the location and number of people hospitalized from E.coli 0157:H7. The CDC investigated this outbreak and found a total of 109 cases with symptom onset from July 26th until August 24 2022. Although the carrier item of the E.coli was not specifically found due to cross-contamination among ingredients and possible food handler complications, the fast-food chain was identified.  Replies 2: Overweight & Obesity Obesity is a common, serious, and costly chronic disease of adults and children that continues to increase in the United States (CDC.govLinks to an external site.). Obesity affects our health by slowing down our mobility and may lead to more serious complications such as diabetes and heart disease which can result in death. The cost of healthcare is also affected by overweight and obese individuals as costly medications and unnecessary hospital visits become common. The below bar graph is of a study that was conducted on 10,636 individuals, 5,223 Men and 5,413 Women of different races to determine the prevalence of obesity on that race. According to the statistical numbers women of combined races had the highest prevalence of obesity than men. Non-Hispanic Black women had the highest prevalence of all the races and women. What is already known about this topic? Studies have suggested that obesity prevalence varies by income or education, although patterns might differ in high and low income countries (CDC.govLinks to an external site.). Replies 3: This week for my discussion I chose to research Tuberculosis Cases vs Deaths in the United States. I work in an infectious disease office, and we recently discussed new cases and the increase in the number of patients being referred to the office.  I began looking into exposure cases, treatment, and deaths. According to the CDC "In 2022, reported TB cases and incidence rates (number of TB cases per 100,000 persons) in the United States increased for the second year in a row, but remained lower than levels reported prior to the COVID-19 pandemic." (CDC, 2023). The CDC reports that "Ending TB will require a dual approach of maintaining and strengthening efforts to diagnose and treat TB disease and latent TB infection, especially in populations at increased risk for TB disease." (CDC,2023). Treatment and prevention will help combat the growing number of cases. Healthcare workers must complete annual screening and mask fitting testing for proper mask type and size.  Replies 4: Tobacco use remains the leading cause of preventable death and disease in the US. Different communities are disproportionally affected by cigarette smoking and tobacco use. Data for this graph was taken from the webpage Center for Disease Control and Prevention. This graph illustrates the current smoking rates among different population groups. Adults with lower levels of education smoke at higher rates than the general population. People living in poverty smoke cigarettes more heavily compared to people with a family income three times higher. Tobacco companies often target advertising campaigns towards low-income communities and a higher density of tobacco retailers can often be found in low-income neighborhoods. Research shows that gaining insurance coverage increases the odds of quitting smoking due to more primary care visits (American Lung Association, 2024). Cigarette smoking is considered a very important problem for several significant reasons besides being a leading cause of preventable diseases such as lung cancer, heart disease, stroke, and chronic obstructive pulmonary disease (COPD). Smoking-related illnesses result in substantial economic costs to healthcare systems and society as a whole. Exposure to secondhand smoke also poses health risks, especially for non-smokers who are exposed to tobacco smoke in indoor or enclosed environments. Cigarette production, packaging, and disposal contribute to environmental pollution, including deforestation, water pollution, and littering. The initiation of smoking among youth is a significant concern as it can lead to lifelong addiction and increased health risks over time.

Reply to both. Use 2 sources  1. Health Information Technology (HIT) Framework:  The Health Information Technology (HIT) Framework prioritizes data security and privacy, encourages interoperability for smooth information interchange, and incorporates technology into the delivery of healthcare (Neame et al., 2020). Healthcare organizations can use Electronic Health Records (EHR) systems for complete patient data management to support these goals. To guarantee consistent data representation, established coding systems like SNOMED and LOINC can also be used. It is crucial to implement strong security protocols for both data transmission and storage to protect patient privacy. Nursing Informatics Framework: The Nursing Informatics Framework is based on the integration of information science and nursing science, the management and communication of data through the use of ICTs, and the support of nursing practice, education, administration, and research (Conte, 2023). To fully utilize this framework, healthcare institutions should integrate decision support systems that improve clinical decision-making. It is also essential to implement telehealth and mobile technology for remote patient monitoring and communication. The effective application of this paradigm is facilitated by healthcare workers' ongoing education and training in nursing informatics. Data-Driven Healthcare Quality Improvement Model: Neame et al. (2020) state that the Data-Driven Healthcare Quality Improvement Model is centered on measuring results to pinpoint areas that need improvement, creating feedback loops for continuous quality improvement, and continuously collecting and analyzing data to improve performance. Key Performance Indicators (KPIs) are used in this model's best practices to track and assess healthcare results. Predictive modeling in particular, a type of data analytics, helps to identify possible problems. Developing a culture of learning and continual development is necessary for this technique to be applied successfully. Clinical Decision Support Systems (CDSS):  According to Wang et al. (2019), CDSS function by offering evidence-based data to assist clinical decision-making, facilitating a seamless integration with Electronic Health Record (EHR) systems, and improving patient safety and care quality. Healthcare organizations should modify CDSS to fit nursing workflows and decision-making procedures to use it to its full potential. To represent the most recent evidence-based procedures, knowledge bases must be updated regularly (Sipes, 2020). Furthermore, ensuring that healthcare personnel are proficient in the use of CDSS guarantees that it will contribute as much as possible to nursing practice. Telehealth and Telemedicine Model: The Telehealth and Telemedicine Model seeks to increase patient satisfaction and engagement, improve overall healthcare accessibility, and provide remote access to healthcare services (Conte, 2023). One of this model's best practices is to put in place safe and convenient telehealth systems. Ensuring adherence to privacy and regulatory requirements is critical. In keeping with the tenets of this paradigm, telehealth integration into nursing care plans is essential for efficient monitoring and follow-up. Healthcare organizations and nursing professionals can leverage technology to boost productivity, improve patient care, and raise the standard of healthcare by implementing these frameworks and the related best practices. Sustaining success in this dynamic profession requires keeping up with emerging technologies and modifying processes to conform to changing norms   2. The informatics frameworks and models apply to healthcare organizations and nursing practice. The American Nurse Association (ANA) defines nursing informatics as a specialty that integrates nursing, information, and computer science. Informatics is critical in meeting the needs of consumers, patients, and healthcare providers and influencing their decision-making capacities (Booth et al., 2021). Some of the relevant frameworks and models of nursing informatics include the informatics research organizing model (IROM), which mainly compares and contrast the technical and scientific approaches and considers the contexts under which the obtained information can be applied (Wang et al., 2019). Furthermore, the other models are associated with the change process and include the systems development life cycle (SDLC), which is critical in guiding the project, change development, and implementation. The SDLC is commonly used in health information technologies. The model believes that effective health information technology development involves the systematic diffusion of knowledge and preparing all the needed elements for change development. Fundamental Principles and Best Practices That You Can Leverage from These Frameworks To Support Your Practice The fundamental principles and best practices to leverage the frameworks include continuous research processes and integration of data analytics to influence clinical decision-making. In addition, collaboration is another best practice and principle that should be integrated into the informatics and change process. All the stakeholders within an institution ought to be engaged to ensure that they fully understand the development or change scope and embrace it fully (Wang et al., 2019). Furthermore, the collaborative change process eliminates the potential non-compliance gaps. It improves how the parties or stakeholders within a healthcare institution embrace and apply the change proposal.

reply to both  1. Research Question: How effective is virtual reality (VR) therapy in reducing anxiety levels during medical procedures in young patients compared to traditional drug-based treatments? Independent Variable: The independent variable in this study is the type of treatment administered to children during medical procedures. Specifically, it includes two levels: VR therapy (non-drug approach) and traditional drug-based treatments. Level of Measurement for Independent Variable: The independent variable is categorical with two levels: VR therapy and traditional drug-based treatments. This categorical nature allows for easy comparison between the two types of treatments. Considerations for Analyzing Data: When analyzing data related to the independent variable (type of treatment), researchers may use inferential statistical techniques such as chi-square tests or logistic regression to assess the association between the type of treatment and anxiety reduction (Gao et al., 2022). One advantage of analyzing categorical data is the straightforward interpretation of results in terms of treatment effectiveness. However, challenges may arise in ensuring that the groups receiving different treatments are comparable in terms of other relevant factors that could influence anxiety levels (Ferraz-Torres et al., 2023). Dependent Variable: The dependent variable in this study is anxiety levels experienced by children during medical procedures. These levels are measured using a recognized anxiety measurement tool. Level of Measurement for Dependent Variable: The dependent variable (anxiety levels) is measured on an interval or ratio scale, depending on the specific anxiety measurement tool used. Interval scales assign numerical values to anxiety levels with equal intervals between them, while ratio scales include a true zero point, allowing for ratios to be calculated. Considerations for Analyzing Data: Analyzing data related to the dependent variable (anxiety levels) may involve using descriptive statistics such as means and standard deviations to summarize the data (Addab et al., 2022). Additionally, inferential statistical techniques like t-tests or analysis of variance (ANOVA) may be used to compare anxiety levels between the VR therapy group and the traditional treatment group. One advantage of analyzing interval or ratio data is the ability to conduct more sophisticated statistical analyses and derive meaningful conclusions about the magnitude of differences in anxiety levels between groups. However, challenges may include ensuring the reliability and validity of the anxiety measurement tool and controlling for potential confounding variables that could impact anxiety levels. 2. How can increase insight into illness and medication, improve adherence of psychotropic medications among individuals with serious and persistent mental illness? Variables and brief rationale for your classification of each variable.  -Dependent variable: the dependable variable in researchable question is medication adherence in mental health patients. This can be assessed using medication adherence rating scale (MARS) (Buchman-Wildbaum, T. et al. ,2020). -Level of measurement: This can typically be measured as a ratio or proportion, indicating the percentage of prescribed medications taken by the individuals. -Independent variables: The independent variables in the research question are insight into illness and medication. -Level of measurement: insight into illness and medication can measured using qualitative assessments like interviews, self-reports of patients or with a quantitative scale like a standardized questionnaires) to assess patients understanding, awareness, and acceptance of their illness and prescribed medication (De Las Cuevas, C., & de Leon, J. ,2020). Consideration for analyzing data.        Analyzing data related to independent variables and dependent variables can be done by considering the relationship between insight into illness and medication and adherence to psychotropic medications using correlation coefficients (Buchman-Wildbaum, T. et al. ,2020). Data can be analyzed using regression analysis to examine the extent to which improved insight into illness and medication may improve adherence to psychotropic medications, while controlling the variables. Adherence rates can be reported as mean or median scores or as percentages of complete doses taken or assessment of the tool scores. The ratio rating   can be used to categorize and rank data from the most compliant to list compliant.

   An understanding of the respiratory system is a critically important component of disease diagnosis and treatment. This importance is magnified by the fact that oftentimes, the respiratory system works closely with the cardiovascular system.  A variety of factors and circumstances that impact the emergence and severity of issues in one system can have a role in the performance of the other. Effective disease analysis often requires an understanding that goes beyond these systems and their capacity to work together. The impact of patient characteristics, as well as racial and ethnic variables, can also have an important impact. An understanding of the symptoms of alterations in the respiratory system is a critical step in diagnosis and treatment of many diseases. For APRNs, this understanding can also help educate patients and guide them through their treatment plans.