Introduction
Quantitative and qualitative data collection and study methods are distinct methods used in data analysis. While they differ in the type of data collected and approach, researchers must be aware of such techniques to develop their data collection and study methods (Hughes & Tarrant, 2019). Due to the varying nature of the data collected during quantitative and qualitative data studies, these methods of collection are significantly different. Qualitative data studies depend on personal documents or accounts indicating how people respond or think in society (Oflazoglu, 2017). In contrast, quantitative studies are reliant on measurable or numerical data.
Discussion
Qualitative research methods involve the collection and interpretation of non-numerical information. Various sources of such data include documents, observations, interviews, cultural records, personal papers or accounts, and focus groups. The researcher conducts focus groups or interviews to gather data not provided in existing records or existing documents. Focus groups and interviews are semi-structured or unstructured, allowing leeway for unexpected or varied answers (Oflazoglu, 2017). This format enables the researcher to develop open-ended questions while following the trail left by the responses. These answers offer an in-depth outlook on each person’s experiences compared to those provided by other participants involved in the study.
Quantitative studies involve researchers using varying forms of data collection. In this instance, these methods entail the compilation of numerical data that enables the examination of the causal relationships between these variables (Hughes & Tarrant, 2019). Various types of data collection include surveys, questionnaires, database reports, and experiments, which yield information that allows numerical analysis. For example, questionnaires exhibit a multiple-choice design to develop numerable answers compressed into yes or no. These formats can be directed into quantifiable data.
Quantitative and qualitative data collection methods have varying outcomes. Qualitative researchers look for insight based on the testimonies of individuals under study, considered informants. They draw conclusions by comparing, evaluating, and compiling informants, input, and feedback. Qualitative research seeks to determine the reason behind a phenomenon: behavior or correlation (Hughes & Tarrant, 2019). Conversely, quantitative data is numerically analyzed to create a statistical image of a connection or trend. Statistical results can illuminate the cause-and-effect associations by either disproving or confirming the researcher’s primary hypothesis. The outcome may spark action and awareness, whether positive or negative. Quantitative research deals with answers to questions such as how or what results are elicited by a study based on their behavior or correlation with the variables used.
Topic Outline and Factors that Impinge on the Variables
Covid-19 merged with one of the significant risk factors in the developed world, obesity. Children are primarily affected by this issue under normal circumstances. The emergence of a pandemic resulted in a stressful environment for adults, with the effects compounded in children (CDC, 2022). Stress eating is one major factor evidenced as a reason for obesity; coupled with lack of exercise due to lockdown and the unavailability of healthy food options for individuals with low income, obesity becomes a more probable outcome (Magge, 2021). Children experienced pandemic-level obesity during the COVID-19 period, leading to higher chances of developing illnesses, getting hospitalized, or dying.
Conclusion
However, while the COVID-19 pandemic elicited one of the worst prevalences of childhood obesity, determining its extent was a problem due to the lockdown. Many feared taking children to a hospital for fear of contracting the virus or exposing others to the illness (Browne et al., 2021). In this way, some children facing these problems did not access healthcare. Furthermore, the lockdown impeded research on the subject as those interested in the issue could not collect data from many people without access to a stable internet connection.
References
Browne, N. T., Snethen, J. A., Greenberg, C. S., Frenn, M., Kilanowski, J. F., Gance-Cleveland, B., Burke, P. J., & Lewandowski, L. (2021). When pandemics collide: The impact of covid-19 on childhood obesity. Journal of Pediatric Nursing, 56, 90–98. Web.
CDC. (2022). Children, obesity, and covid-19. Centers for Disease Control and Prevention. Web.
Hughes, K., & Tarrant, A. (2019). Qualitative secondary analysis. Sage.
Magge, S. N. (2021). Obesity in children and the impact of covid-19. Contemporary Pediatrics. Web.
Oflazoglu, S. (2017). Qualitative versus Quantitative Research. Books on Demand.