Interpreting Qualitative and Quantitative Research Studies

Introduction

Research has become necessary for finding information about things that have not been established truthfully through valid reasoning and experience. When an already available source of information exists, it becomes easier for a researcher to build rational results that are both valid and reliable. This paper examines the difference between continuous and categorical variables, as well as the difference between nominal data and interval data. It then interprets a qualitative and a quantitative research study in order to better understand both categories of research design.

Continuous vs. Categorical Variables and Data Types

Continuous variables have an infinite numeric value between any two points on a scale (Minitab, n.d.). For instance, a continuous variable can be a date or time between two days, such as the day a delivery parcel arrives. On the other hand, variables that do not have a logical order and are finite in number are called categorical variables. These can be sorted into distinct groups. Gender, payment method, and ethnic group are examples of categorical variables.

Nominal data involves the labeling of variables without assigning them any quantitative value (Corporate Finance Institute, n.d.). It is considered the simplest type of measurement scale, as it cannot be measured numerically or placed in any order. Interval data, by contrast, places each value at a definite and equal position on a scale (QuestionPro, n.d.). It is measured quantitatively with specific numbers, with the intervals between values assumed to be equal and standardized.

Qualitative Study: Loneliness and Social Isolation in Old Age

The qualitative article selected from the annotated bibliography was presented by Courtin and Knapp (2015). The qualitative research technique employed was a review of existing literature produced by various authors on the same subject. A total of 11,736 articles were initially considered, and the comprehensive literature review spanned from July to September 2013. Of these, 128 items from 15 countries were extracted for scoping review purposes. The two central concepts — social isolation and loneliness — were the focus of the selected studies, with the aim of analyzing their effects on mental and physical health in old age.

The study results indicated that the previous literature included for studying loneliness and social isolation in older adults was predominantly directed toward the United States. The studies also largely highlighted loneliness rather than social isolation. The documented health effects of loneliness, and to a lesser extent social isolation, were mainly limited to cardiovascular disease and depression. The authors concluded that broader research was needed to extend the investigation to other countries beyond the US population, and that future studies should examine health outcomes beyond cardiovascular problems and depression.

The method used for collecting data in this study was based on the five-stage methodological framework put forward by Arksey and O'Malley (2005). The main steps in this framework included: identifying the research question, selecting studies relevant to the research question and the issue at hand, charting the data from the selected studies, and summarizing the results extracted from the prior literature. Keywords were identified to locate relevant literature for the stated research questions, organized into three categories: population or target group, issue, and health outcome. Keywords for the population or target group included aged, aging, old people, older people, old age, and elderly people. Keywords for the issue category included isolation, loneliness, solitude, and social isolation. Keywords for the health outcome category included physical health, mental health, mental disorder, and depression.

Inclusion criteria required that papers be written in English; all research designs were accepted. Studies were excluded if they were based outside Europe and the United States, did not focus on the older population, did not address physical or mental health, or did not discuss loneliness or social isolation. Data analysis was conducted systematically using a chart that recorded the studies by year of publication and number of studies per year. The highest numbers of studies came from 2010 through 2013, while the fewest were from 2003, meaning the most recent data was prioritized. Further analysis was presented in a table showing variables, the number of studies associated with each variable, and the percentage of studies related to each variable. An additional table displayed the variables most frequently addressed by authors in relation to the year of publication.

A final analytical table provided a detailed overview of all outcomes and keywords, with the corresponding number of studies listed alongside each keyword. A concluding table summarized the characteristics of health outcomes related to depression and cardiovascular health.

Conclusion

Together, the qualitative scoping review by Courtin and Knapp (2015) and the quantitative cross-sectional study by Bahramnezhad et al. (2017) illustrate the distinct methodologies used in each type of research. The qualitative study synthesized a broad body of existing literature using a structured keyword and inclusion framework, while the quantitative study collected primary data and applied statistical tests to identify relationships between social isolation and health outcomes in elderly participants. Both studies converge on the conclusion that social connection plays a meaningful role in the health and well-being of older adults, while also pointing to gaps that future research should address — particularly regarding geographic diversity and the full range of health outcomes affected by loneliness and social isolation.

References

Bahramnezhad, F., Chalik, R., Bastani, F., Taherpour, M., & Navab, E. (2017). The social network among the elderly and its relationship with quality of life. Electronic Physician, 9(5), 4306–4311. https://doi.org/10.19082/4306

Corporate Finance Institute. (n.d.). Nominal data. Retrieved from https://corporatefinanceinstitute.com/resources/knowledge/other/nominal-data/

Courtin, E., & Knapp, M. (2015). Social isolation, loneliness, and health in old age: A scoping review. Health and Social Care in the Community, 25(3), 799–812.

Minitab. (n.d.). What are categorical, discrete, and continuous variables? Retrieved from https://support.minitab.com/en-us/minitab-express/1/help-and-how-to/modeling-statistics/regression/supporting-topics/basics/what-are-categorical-discrete-and-continuous-variables/

QuestionPro. (n.d.). Interval data: Definition, characteristics, and examples. Retrieved from https://www.questionpro.com/blog/interval-data/