Relationship Between Concepts, Constructs, and Variables

Introduction

When research is performed in any field, scientists must develop a conceptual framework for their studies to have a clear vision for themselves and articulate it to others. It is built prior to the experimental part to help researchers answer specific questions (“Conceptual framework vs. theoretical framework,” 2022). However, to develop the conceptual framework, it is crucial to define the concept, constructs, and variables and understand their similarities, differences, and application in healthcare research. These three terms are essential for studies since they help operationalize and conceptualize measures.

Discussion

The three foundational aspects of a theory are concepts, constructs, and variables. A concept can be defined as a phenomenon that serves as a building block for developing hypotheses in research (“Introduction to nursing theories,” 2020). A construct, which can be unidimensional or multidimensional, is an abstract idea used for explaining various events (Bhattacherjee, 2021). To elucidate the abovementioned terms, variables are used, which are measurable characteristics of constructs that can be dependent, independent, moderating, and controlling (Bhattacherjee, 2021). For example, a person’s weight is a concept, while one’s body mass index is a multidimensional construct that comprises a specific ratio of weight to height squared. In the last case, height and weight are variables used to measure the indicated construct.

As incomparable as they may seem, these three terms have some similarities. Indeed, unidimensional constructs and concepts represent one specific abstract idea (Bhattacherjee, 2021). For instance, gravitation is a concept, but it can also be viewed as a construct since it explains the phenomenon of objects staying on the ground on Earth. Moreover, concepts and variables are similar in the way that they represent one particular idea or measure.

The concept, variable, and construct differ from each other in several dimensions. Firstly, a concept is always one idea, while a construct can incorporate multiple abstractions (Bhattacherjee, 2021). Furthermore, the distinction between construct and variable is that the former cannot be directly measured while the latter is purposefully used for measuring constructs (Bhattacherjee, 2021). The difference between concept and variable is in their purpose. The latter serves as a measure, whereas the former represents a phenomenon.

The ultimate goal of these three conceptions is to operationalize and explain a variety of healthcare measures. For example, describing healthcare workers’ satisfaction, engagement, motivation, and burnout is conceptualized as job morale to simplify research in that field (Sabitova et al., 2020). It is sometimes challenging to explain such phenomenon as public health acceptance; hence, researchers formulate the construct of acceptability of medical interventions to be able to qualitatively or quantitatively measure it (Sekhon et al., 2018). In fact, statistical tools like logistic regression analysis are frequently used to determine the association between independent and dependent variables that constitute a health-related construct (Bodur & Atsa’am, 2019). As these examples demonstrate, the three terms under discussion can be utilized in multiple ways to understand an idea or test a theory in healthcare research.

In summary, variables, concepts, and constructs are essential elements of scientific studies that allow the development of a theoretical framework and produce a measurable outcome. Indeed, concepts and constructs represent one or several abstract ideas that may explain a specific event or phenomenon. These ideas are usually measured with the help of variables that may be constant or dynamic. Overall, all three terms are crucial for healthcare research since they are implemented in measuring and elucidating certain behaviors and attitudes of people regarding public health.

Assignment 2

Table 1: Examples of Concepts and Constructs

Concept/
Construct
Variables Operational Definition Data Category* Measure**
Concept example (Insulin resistance): Waist-to-hip ratio

More than 1 (male) and 0.8 (female) = Abdominal obesity

Less than 1 (male) and 0.8 (female) = Normal

What is your waist-to-hip ratio? Continuous Ordinal
Glycemic level
2 = Normal
1 = Lower than normal
0 = Elevated
How do you rate your blood glucose level? Please provide your last two readings of glucose concentration. Continuous Ratio
Body mass index (BMI)
Less than 18.5 = Underweight
18.5-24.9 = Normal
25-29.9 = Overweight
More than 30 = Obese
What is your BMI? Continuous Ordinal
Construct example (attitude to the chosen health plan): Annual check-ups
1 = Yes
0 = No
Do you undergo annual health check-ups? Categorical Ordinal
Adherence to treatment
1 = Compliant
0 = Not compliant
Do you consider yourself generally adherent to a doctor’s prescribed treatment plan? Categorical Ordinal
Satisfaction with the current health plan
5 = Fully satisfied
4 = Satisfied
3 = Neutral
2 = Not satisfied
1 = Completely dissatisfied
How satisfied are you with your current health plan? Categorical Ordinal

Conclusion

Measurement in healthcare research can be done in various ways, but it requires a clear definition of variables. Indeed, defining measures is critical for developing a robust methods section and attaining the study objectives (Jensen & Laurie, 2017). For example, the outcomes research may measure morbidity and mortality after a specific surgical procedure or therapeutic intervention (Kane & Radosevich, 2011). However, not all phenomena can easily be measured; hence, operationalization, the process of translating abstract ideas into measurable components, is required (Greenstein, 2006). The measurement process involves determining the level of variable assessment, which can be nominal, ordinal, interval, and ratio (Greenstein, 2006). Table 2 shows examples of concepts and constructs that were converted to different measures to estimate the outcome. Specifically, the concept being analyzed in Table 2 is insulin resistance, while the construct is the overall attitude to the chosen health plan.

References

Bhattacherjee, A. (2021). Concepts, constructs, and variables. Libre Texts. Web.

Bodur, E. K., & Atsa’am, D. D. (2019). Filter variable selection algorithm using risk ratios for dimensionality reduction of healthcare data for classification. Processes, 7(4), 1-14. Web.

Conceptual framework vs. theoretical framework – And constructing each. (2022). Charlesworth Author Services. Web.

Greenstein, T. N. (2006). How do we measure concepts? In Methods of family research (pp. 51-62). SAGE Publications, Inc.

Introduction to nursing theories. (2020). Current Nursing. Web.

Jensen, E., & Laurie, C. (2017). An introduction to research design [Video file]. Sage Methods Database.

Kane, R., & Radosevich, D. (2011). Conducting health outcomes research. Jones & Bartlett Learning.

Sabitova, A., Hickling, L. M., & Priebe, S. (2020). Job morale: A scoping review of how the concept developed and is used in healthcare research. BMC Public Health, 20(1), 1-9. Web.

Sekhon, M., Cartwright, M., & Francis, J. J. (2018). Acceptability of health care interventions: A theoretical framework and proposed research agenda. British Journal of Health Psychology, 23(3), 519-531. Web.

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