[ANSWERED 2023] Search the GCU Library and find three different health care articles that use quantitative research. Do not use articles that appear in the Topic Materials or textbook Do not use articles that appear in the Topic Materials or textbook

Search the GCU Library and find three different health care articles that use quantitative

Search the GCU Library and find three different health care articles that use quantitative research. Do not use articles that appear in the Topic Materials or textbook. Complete an article analysis for each using the “Article Analysis 1” template.

Refer to the “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial,” in conjunction with the “Article Analysis Example 1,” for an example of an article analysis.

Expert Answer and Explanation

Article Analysis-Quantitative Research in Healthcare

References

Kumar, S., Syed, N., Jaykumar, S., Prem, V., Karvannan, H., Karthikbabu, S., & Sisodia, V. (2012). Study of nurses′ knowledge about palliative care: A quantitative cross-sectional survey. Indian Journal of Palliative Care, 18(2), 122. https://doi.org/10.4103/0973-1075.100832

Solvik, E., & Struksnes, S. (2018). Training Nursing Skills: A Quantitative Study of Nursing Students’ Experiences before and after Clinical Practice. Nursing Research and Practice, 2018, 1–9. https://doi.org/10.1155/2018/8984028

Wong, H., Karaca, Z., & Gibson, T. B. (2018). A Quantitative Observational Study of Physician Influence on Hospital Costs. INQUIRY: The Journal of Health Care Organization, Provision, and Financing, 55, 004695801880090. https://doi.org/10.1177/0046958018800906

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FAQs

What are the different types of quantitative research articles?

Quantitative research articles can take various forms, but they generally fall into several common categories. Here are some of the main types of quantitative research articles:

1. Experimental Research Articles:
   • Description: Experimental studies involve the manipulation of an independent variable to observe its effect on a dependent variable. These articles often follow a structured format, including sections on hypothesis, methods, results, and conclusions.
   • Example: A study testing the impact of a new drug on blood pressure levels.
2. Descriptive Research Articles:
   • Description: Descriptive studies aim to provide an accurate and detailed portrayal of a phenomenon or group without manipulating variables. They may include surveys, observational studies, or case studies.
   • Example: An article describing the prevalence of a particular disease in a specific population.
3. Correlational Research Articles:
   • Description: Correlational studies examine the relationships between two or more variables to determine if they are associated. However, correlation does not imply causation.
   • Example: Investigating the relationship between smoking habits and the incidence of lung cancer.
4. Longitudinal Research Articles:
   • Description: Longitudinal studies involve the collection of data over an extended period, allowing researchers to examine changes or trends over time.
   • Example: Tracking the academic performance of a group of students from kindergarten through high school.
5. Cross-Sectional Research Articles:
   • Description: Cross-sectional studies collect data at a single point in time to analyze and compare variables within a specific population.
   • Example: Assessing the relationship between income levels and access to healthcare services in a community.
6. Quasi-Experimental Research Articles:
   • Description: Quasi-experimental studies share similarities with experimental research but lack full control over variables. They often involve pre-existing groups or conditions.
   • Example: Evaluating the effectiveness of an educational intervention in different schools without random assignment.
7. Causal-Comparative Research Articles:
   • Description: Causal-comparative studies compare different groups to identify possible causes or factors contributing to observed differences.
   • Example: Investigating the impact of teaching methods on student achievement by comparing performance in classrooms with different instructional approaches.
8. Survey Research Articles:
   • Description: Survey studies collect data through questionnaires or interviews to gather information about people’s attitudes, opinions, behaviors, or characteristics.
   • Example: Conducting a national survey to understand public attitudes towards a specific social or political issue.

Remember that these categories are not mutually exclusive, and some research articles may combine elements from multiple types of quantitative research methodologies. The choice of the research design depends on the research question, objectives, and practical considerations.

How do I find quantitative research articles?

Finding quantitative research articles involves utilizing various academic databases, library resources, and search engines. Here’s a step-by-step guide on how to find quantitative research articles:

1. Identify Keywords and Concepts:
   • Define the specific topic or research question you are interested in.
   • Identify keywords and related concepts that represent your topic.
2. Use Academic Databases:
   • Access academic databases such as PubMed, Google Scholar, JSTOR, ScienceDirect, and IEEE Xplore.
   • Enter your keywords into the search bar.
3. Filter for Quantitative Studies:
   • After performing a search, use filters or advanced search options to specify the type of study you’re looking for (e.g., empirical studies, quantitative research).
   • Some databases allow you to filter by study design or methodology.
4. Check Library Catalogs:
   • Explore your university or local library catalog for books, journals, and articles related to your topic.
   • Library catalogs often provide links to electronic resources.
5. Explore Institutional Repositories:
   • Check if academic institutions or organizations have repositories where researchers share their work.
   • Examples include university repositories and governmental databases.
6. Review Research Journals:
   • Look for journals that specialize in publishing quantitative research articles in your field of interest.
   • Browse recent issues or use the journal’s search feature to find relevant articles.
7. Use Citations from Existing Articles:
   • Check the reference lists of articles you have already found. Often, researchers cite relevant quantitative studies.
   • Follow the citation trail to discover more articles on your topic.
8. Set up Alerts:
   • Set up alerts or notifications for new articles in your area of interest.
   • Many databases allow you to create alerts based on specific search criteria.
9. Consult Subject-Specific Databases:
   • Explore databases that are specific to your academic discipline or field.
   • Examples include PsycINFO for psychology or EconLit for economics.
10. Ask Librarians for Assistance:
    • Librarians are valuable resources. Consult with them for assistance in finding quantitative research articles.
    • They can provide guidance on database selection, search strategies, and accessing full-text articles.
11. Use Search Engines:
    • Google Scholar is a powerful tool for finding scholarly articles. Enter your keywords and explore the results.
    • Use specific search terms like “quantitative research,” “empirical study,” or “statistical analysis” in combination with your topic.
12. Check Open Access Journals:
    • Explore open access journals that make their articles freely available.
    • Directories like the Directory of Open Access Journals (DOAJ) can help you find open access publications.

Remember to critically evaluate the articles you find, considering factors such as the study design, methodology, sample size, and the credibility of the authors. Additionally, ensure you have access to the full text of the articles through your institution’s library or other means.

What is an example of quantitative data in public health?

In public health, quantitative data often involve numerical measurements and statistical analyses to provide a quantitative understanding of health-related phenomena. Here’s an example of quantitative data in the context of public health:

Example: Incidence Rate of a Disease

Imagine a public health study focused on the incidence rate of a specific infectious disease, such as influenza, in a particular region over a one-year period. The researchers collect data on the number of new cases of influenza diagnosed during that time frame.

Quantitative Data:

• Number of new influenza cases reported each month: January (25), February (30), March (20), April (15), May (10), June (5), July (8), August (12), September (18), October (30), November (40), December (22).

To analyze this quantitative data, researchers might calculate the monthly incidence rate by dividing the number of new cases by the total population or the at-risk population for each month. The overall incidence rate for the year could also be calculated.

For instance, if the population of the region is 100,000, the incidence rate for January would be calculated as follows:

Incidence Rate=Number of new cases in January/Total population×100,000

Incidence Rate=Total population/Number of new cases in January​×100,000

This quantitative data can then be further analyzed to identify trends, seasonal variations, or clusters of cases. It provides a numeric representation of the disease’s impact, aiding public health officials in making informed decisions regarding prevention, intervention, and resource allocation.

Role of quantitative methods in public health

Quantitative methods play a crucial role in public health research and practice, providing a systematic and numeric approach to studying health-related phenomena. Here are key roles of quantitative methods in public health:

1. Epidemiological Studies:
   • Role: Quantitative methods are fundamental in epidemiology, helping researchers study the distribution and determinants of diseases in populations. Epidemiological studies, such as cohort and case-control studies, use quantitative data to identify risk factors, incidence rates, and prevalence of diseases.
2. Surveillance and Monitoring:
   • Role: Quantitative methods enable the systematic collection, analysis, and interpretation of health data for ongoing surveillance and monitoring. This helps public health officials track trends, identify outbreaks, and allocate resources effectively.
3. Program Evaluation:
   • Role: Quantitative methods are essential for evaluating the effectiveness of public health interventions and programs. Researchers use statistical analyses to assess outcomes, measure impact, and determine whether interventions achieve their intended objectives.
4. Risk Assessment:
   • Role: Quantitative methods assist in assessing and quantifying risks associated with various health factors, behaviors, or environmental exposures. This information is critical for developing evidence-based strategies to mitigate risks and promote public health.
5. Policy Development:
   • Role: Quantitative data provide a solid foundation for evidence-based policymaking. Policymakers use statistical analyses to understand the impact of health policies, predict potential outcomes, and make informed decisions to improve public health.
6. Health Services Research:
   • Role: Quantitative methods are employed to analyze healthcare utilization, access, and quality. Researchers use statistical tools to assess healthcare delivery models, evaluate disparities, and inform improvements in health services.
7. Behavioral Research:
   • Role: Quantitative approaches are valuable in studying health behaviors, attitudes, and outcomes. Surveys, experiments, and observational studies help researchers quantify and analyze patterns of behavior, aiding in the development of targeted health interventions.
8. Health Economics:
   • Role: Quantitative methods are applied in health economics to assess the economic impact of health policies, healthcare interventions, and the overall health of populations. Cost-effectiveness analyses and economic evaluations help inform resource allocation.
9. Data-driven Decision Making:
   • Role: Quantitative data facilitate evidence-based decision-making in public health. Policymakers, practitioners, and researchers use statistical analyses to identify trends, assess health disparities, and prioritize interventions based on data-driven insights.
10. Public Health Informatics:
    • Role: Quantitative methods are integral to the field of public health informatics, where data from various sources, including electronic health records and surveillance systems, are analyzed to support public health decision-making and planning.

How to analyze quantitative data

Analyzing quantitative data involves applying statistical methods and techniques to draw meaningful conclusions from numerical information. Here is a general guide on how to analyze quantitative data:

1. Data Preparation:

• Cleaning Data:
  • Check for missing values, outliers, and errors in the data.
  • Address any issues by imputing missing values or removing outliers as appropriate.
• Data Coding and Labeling:
  • Ensure that variables are correctly coded and labeled.
  • Convert categorical variables into numerical codes if necessary.

2. Descriptive Statistics:

• Measures of Central Tendency:
  • Calculate the mean, median, and mode to understand the central value of the data.
• Measures of Dispersion:
  • Compute measures such as standard deviation and range to assess the spread of the data.
• Frequency Distributions:
  • Create frequency tables and histograms to display the distribution of values.

3. Inferential Statistics:

• Hypothesis Testing:
  • Formulate null and alternative hypotheses.
  • Choose an appropriate statistical test (e.g., t-test, ANOVA, chi-square) based on the study design and data distribution.
• Significance Levels:
  • Determine the significance level (e.g., 0.05) to assess the probability of obtaining results by chance.
• Conduct Statistical Tests:
  • Perform the chosen statistical test using statistical software.
  • Evaluate p-values and compare them to the significance level to make decisions about hypotheses.

4. Correlation and Regression Analysis:

• Correlation:
  • Assess relationships between variables using correlation coefficients (e.g., Pearson’s r).
  • Interpret the strength and direction of correlations.
• Regression:
  • Use regression analysis to model the relationship between a dependent variable and one or more independent variables.
  • Interpret coefficients and assess the model’s fit.

5. Data Visualization:

• Graphs and Charts:
  • Create visual representations (scatter plots, bar charts, box plots) to illustrate patterns and trends in the data.
  • Enhance the presentation of findings for better communication.

6. Interpretation of Results:

• Contextualize Findings:
  • Relate statistical results to the research question or hypothesis.
  • Consider practical significance and relevance to the study’s objectives.
• Draw Conclusions:
  • Summarize key findings and draw conclusions based on the results.
  • Discuss limitations and implications for further research or practical applications.

7. Peer Review and Validation:

• Validation:
  • Share data and methods for validation by peers or experts.
  • Consider replication studies to confirm results.
• Peer Review:
  • Submit findings for peer review in academic or professional journals.
  • Address feedback and refine analyses if necessary.

8. Document the Analysis:

• Documentation:
  • Provide a clear and detailed description of the analysis process.
  • Include information about data transformations, statistical tests used, and software/tools employed.

9. Continuous Learning:

• Stay Informed:
  • Keep abreast of new statistical methods and tools.
  • Consider advanced techniques as appropriate for future analyses.

Tools for Analysis:

• Utilize statistical software such as R, Python (with libraries like NumPy and Pandas), SPSS, SAS, or Excel for conducting quantitative analyses.