Research Paper Sample on Secondary Analysis of Existing Data

Introduction

This study shall use the secondary analysis of existing data methodology to examine the survey data from Wave Five of the Food and You Survey, 2018. Secondary analysis of existing data refers to the “analysis of data that was collected by someone else for another primary purpose” (Johnston, 2014: 619). Such an empirical analysis of data from a previously published research output has continued to gain scholarly attention for several reasons. The primary reasons for resorting to secondary analyses are time and resource-based factors. In adopting the secondary approach to the study of food safety and security in the UK, for instance, the author recognized the central positioning of the Food Standards Agency (FSA) as a primary research agency for food safety surveys. The author thereby appreciated the immense progress of the institution in food security and safety studies through the waves of Food and You Surveys. From a close evaluation of these surveys by the FSA, the author recognized that their findings could be used in analyzing the topic for this present analysis. The author thereby selected the most recent survey in the Food and You Surveys as the database for the secondary analysis of existing data.

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Dataset Evaluation

Before the data search from the selected primary survey started, the author evaluated the dataset. This evaluation of the Food and You Survey Wave Five dataset allowed the author to uncover the relevance of the dataset to the current research interest. From this evaluation, the author found that the original Wave Five report had a similar overlaying purpose as the present study. The aims of the Food and You Survey Wave Five study revolved around uncovering the demographic differences in understanding food safety and security trends. These differences in behavioral patterns among the UK demographics around food insecurity, safety, and eating patterns were also the target of the present study.

Furthermore, the original study uncovered the access and quality factors of the food and nutrition for the population. The original Wave Five study did not, however, explicitly relate the eating trends and food insecurity and safety patterns to the health of the target population. This secondary analysis thereby focused on examining perceptions of the sample population on food safety and security as a factor determining the health of the UK population. The strengths and weaknesses analysis of the dataset was also essential in the research evaluation process (Johnston, 2014). This evaluation process of the original study extended to analyzing the methodology and target population for the original research.

Study Design

As the original study was a descriptive quantitative study, this secondary search also employed a similar research design (Kneipp & Yarandi, 2002). However, in the present secondary survey, the author also intended to conduct an analytical investigation of the variables in the original study and relate the variables to an outcome variable (human health). This analytical research design requires the author to investigate the impacts of the independent variables (eating habits, food insecurity, and safety) on the dependent variable (human health). This secondary analytical analysis shall be solely observational and intended to expose the phenomenon (effect of eating habits and food safety on human health) (Kneipp & Yarandi, 2002). The author, as such, shall not intend to introduce any intervention to change the currently existing phenomenon. This present quantitative analysis is thus mainly a descriptive and correlational study of existing phenomena and causation to the suggested outcome (human health).

Sampling

The data for this study shared the properties of the original Wave Five Food and You Survey. As such, the sampling methodology may be described as a stratified sampling technique from populations in England, Wales, and Northern Ireland. From a randomized target of 7069 addresses from the three countries, a total of 3059 responses were received – representing a 48.2% response rate. Random probability sampling ensured that all the respondents had an equal chance of selection. This randomized sampling technique made the original study ideal for a secondary analysis because of its ease of generalizability (Kneipp & Yarandi, 2002).

The sampling frame included any citizen of the three countries aged 16years and above. 283 Primary Sampling Units (PSUs) were selected from the three countries, and the 7,075 addresses selected for the interviews. From the addresses, the authors listed the dwelling units and the occupants of the units using the Kish grid. Any citizens outside the Primary Sampling Unit (PSU) clusters were thereby excluded from the research. Furthermore, individuals below the age of 16 years who reside in these three countries were also excluded from the study. In the final data analysis, 2,241 interviews were used for the research investigation. These interviews were sufficiently appraised and passed the extensive list of eligibility tests. Interview data from each country was then weighted differently to present a fair representation of the realities in the three countries´ contexts (Boo & Froelicher, 2012).

Ethical Considerations

In a secondary analysis, the author is working with data from a different researcher or research organization (Irwin, 2013). As such, the ethical considerations present a complex range of factors that intend to protect the privacy of both the primary researcher and the study respondents. To start with, the author of the secondary analysis must gain express permission to use the dataset of the primary analysis. Such express permission must respect the rules and ethical codes of conduct for the intellectual property of the primary analysts. In this study, the author requested express and informed consent from the FSA to use their Food, and You Wave Five Survey. While using the dataset, the secondary analysis thereby commits to respecting the privacy and copyright provisions in the original study (Irwin, 2013).

In addition to the intellectual property rights considerations, the secondary analyst must also commit to respecting the confidentiality and consent agreement of the respondents of the original study (Irwin, 2013). The author of this secondary study must thereby review the Informed Consent Form used in the original Food and You Wave Five Survey. As the study involved a range of participant demographics of different ages and regions, the author must commit to treating their data with high commitment to the ethical codes and principles, including non-maleficence and beneficence. For underage participants, the parents must consent to the use and reuse of their private information. The author must, furthermore, agree to the anonymity agreements made before the primary data was collected from the respondents (Irwin, 2013).

Conclusion

The secondary analysis of data continues to be a popular research approach in the nationwide public health domain (Boo & Froelicher, 2012). The primary reason for such an increase in the secondary analysis approach to the national or international datasets relates to the cost-effectiveness of such approaches in a considerable breadth of research coverage. It is, for instance, a lot cheaper to analyze the data from FSA Survey data while aiming to uncover the correlation of food security and safety with human health. Such attractiveness of the methodology is furthermore increased through its time effectiveness. The author can access an extensive range of data that covers a large geographical and population expanse. Such a study allows the author to produce generalizable findings at the macro-level instead of highly contextualized data from a limited societal domain (Boo & Froelicher, 2012).

References

Boo, S. & Froelicher, E.S., 2012. Secondary analysis of national survey datasets. Japan Journal of Nursing Science, 10(1), pp.130–135.

Irwin, S., 2013. Qualitative secondary data analysis: Ethics, epistemology and context. Progress in Development Studies, 13(4), pp.295–306.

Johnston, M.P., 2014. Secondary Data Analysis: A Method of which the Time Has Come. Qualitative and Quantitative Methods in Libraries (QQML), 3(3), pp.619–626.

Kneipp, S.M. & Yarandi, H.N., 2002. Complex Sampling Designs and Statistical Issues in Secondary Analysis. Western Journal of Nursing Research, 24(5), pp.552–566.