VARIABLES OPERATIONALIZATION: PROCESS AND EXAMPLES - SCIENCE - 2025

The operationalization of variables consists of a logical process through which the concepts that are part of an investigation are decomposed with the intention of making them less abstract and more useful for the investigative process. When each variable can be collected, valued and observed it becomes an indicator.

According to the author Mercedes Reguant, the process of operationalization of variables is one in which some variables are replaced by more specific ones that represent those substituted. An example of this process can be school grades, which act as necessary indicators to calculate the variable of academic success.

Through the operationalization of variables, it is sought to break down a concept to the maximum to increase its usefulness within a research process. Source: pixabay.com

A variable is operationalized with the aim of converting an abstract concept into an empirical one through the application of an instrument. This process is important as it guides a researcher with little experimentation during the preparation of his work and protects him from making frequent mistakes in the investigative processes.

Some variables are so specific that they do not require operationalization; for example, such is the case of those that determine the sex of individuals or the colors of the traffic light as traffic signals. Neither do the variables that define the structure and location of organs in the human body require operationalization.

The operationalization of variables becomes necessary when their conceptualization is more difficult, usually because they are related to abstract definitions such as education, quality of life and authority. These concepts can have different meanings depending on the type of study to be carried out or the discipline of the researcher.

The need to operationalize a variable must be established by the researcher, who must take into account the scale of variables to determine whether or not the operationalization process will be required during the investigation.

The scale of variables is made up of a comparative table in which the fundamental characteristics of each variable are established, such as what type it belongs to, what is its definition, and what are its dimensions and unit of measurement. This information allows establishing which variables are essential to carry out the investigative work.

What are variables?

Taking into account the definition of Linton Freeman, it can be established that the variables are the characteristics or observable elements of a given object that are susceptible to adopting different values ​​and that can be expressed in different categories.

A simple example of a variable can be color, which in turn can be categorized as black, white, blue, green or purple, among others. The weight of a person can also be a variable: for example, it can be presented in the values ​​of 80, 70, 60 kilograms.

Quantitative and qualitative variables

Variables are qualitative by nature when they cannot be quantified. For example, this occurs in variables of abstract concepts such as justice as value, work as dignity, equal opportunities or corruption present in public officials.

On the other hand, the variables can be quantitative when their elements have a quantitative or numerical character, as occurs, for example, with the average age of the murderers in the main capital cities, the financial level of the people who are engaged in craft trades or the average of third-year students, among other cases.

Importance of variables in scientific and sociological methods

The importance of variables within scientific and sociological methods is undeniable, since all scientific research revolves around them.

In fact, some authors affirm that the purpose of scientific work is to discover the variables and their magnitude through tests that test the relationships that exist between them.

Consequently, it can be said that the variables are used in the main phases of scientific research because they permeate all the terms or operational methods of the work, such as description, analysis, classification and explanation.

It is necessary to bear in mind that the concept of variable is initially endowed with the maximum generality; therefore, all the realities and things of the world (considered as objects of science) can be a variable.

To define a variable as an element, it must have the following aspects:

- A name.

- Some kind of verbal definition.

- A series of categories.

- A procedure that involves the classification into categories of what is observed.

The following example explains the above:

- Name: preference regarding political parties.

- Verbal definition: specific predilection for any of the organizations that promote citizen participation within the framework of the democratic system.

- Categories: matches PPC, APRA, PPT, PSU, other, none.

- Category classification procedure: determine the preference regarding political parties through the responses of those surveyed to the following question: "In favor of which political party will you vote in the next elections?"

Types of variables

Variables can be cataloged as follows:

-Depending on the level of measurement

These can be nominal, ordinal, ratio or proportion, or interval. The most outstanding characteristics of each are described below:

Nominal

Nominal variables only allow objects to be classified; that is, they catalog a single relationship between the objects that have been assigned a number. These variables maintain an equivalence relationship.

For example, in the variable "sex" the numeral "1" is assigned to designate men, while "2" is used to refer to women. This means that all the members of numeral 1 will be men, so they maintain an equivalent condition.

Consequently, the equivalence relation is reflexive (a = a), symmetric (a = b then b = a) and transitive (if a = b and b = c, then a = c).

Ordinals

Ordinal variables allow classifying and ordering, so they establish a logical sequence that considers the intensity of the attribute itself.

An example of this can be the following: if the level of satisfaction of people in the execution of a service related to health is measured, the scales "full satisfaction", "average satisfaction", "little satisfaction" and " dissatisfaction".

This type of classification differs from the nominal one because it allows establishing a graduation or order in the observations.

Of reason or proportion

In the variables of proportion or ratio are the previous properties such as ordering and classifying; however, the possibility of absolute or true zero is added.

This means that if an object that is being measured has the value zero, that object does not have the property that is being measured.

This variable corresponds to the highest level of measurement. To analyze it, it is possible to apply all the techniques of the previous levels, and it also admits the geometric mean and the necessary tests to establish the zero point of the scale.

Interval

Interval variables make it possible to measure aspects taking into account the notion of equality. Unlike the ratio variable, it does not accept absolute zero; however, it allows measuring the distances between the values ​​as well as the order that governs them.

-Depending on the type of study

Scientific studies that analyze the cause-effect relationship of a phenomenon have the following variables: independent, dependent or intervening.

Independent

The independent variables represent the eventual cause.

Dependents

This type of variable represents the possible effect.

Interveners

It corresponds to the one that raises a third variable that acts between the dependent and the independent one. The intervening variable can facilitate the understanding of this relationship.

-According to the origin of the variable

A variable can be active or attributive.

Active

A variable is considered to be active when the researcher designs or creates it.

Attributive

If the variable in question was already set (that is, it was pre-existing), it is considered to be attributive.

-According to the number of values ​​it represents

In this case the variables can be continuous, discrete, dichotomous or polytomous.

Continuous

Continuous variables represent values ​​progressively and admit fractionation, such as age.

Discreet

Discrete variables are those that only take values ​​that do not admit fractionation, such as the number of children or the number of pregnancies. These values ​​must belong to a specific numerical set so that they can be considered within the discrete variables.

Dichotomous

When the variable takes only two values, such as sex, it is defined as dichotomous.

Politics

In cases where the variable takes more than two values, it is called polytomous.

-According to the control by the researcher of the variable

They can be controllable or controlled and uncontrolled.

Controlled

The controlled variable is the dependent variable that requires control by the researcher, such as the number of cigarettes a smoker consumes per day and its relationship with lung disease.

Not controlled

Unlike the previous one, the uncontrolled variable is evident when it is not considered during the analysis by the researcher.

-According to the degree of abstraction

According to this categorization, the variables can be divided into general, intermediate or empirical.

General

General variables are those that refer to realities that cannot be directly measured empirically.

Intermediate

Variables are intermediate when they express partial dimensions. As a consequence of this, they are closer to the empirical reality.

Empirical

Regarding the empirical variables (also known as indicators), these represent observable and measurable aspects or dimensions in a direct and experimental way.

Variables operationalization process

According to the sociologist Paul Lazarsfeld, the operation of the variables requires the following phases to be carried out:

First phase

In this first stage the concept of the variable is determined. This has the purpose of expressing the main features in empirical reality through a theoretical notion.

Second stage

In this phase, very direct specifications are made about the concept that has been previously found. This process is carried out through an analysis of the dimensions and practical aspects of this concept.

These aspects are included in the conceptual representation of the variable or derive empirically from the understanding of the different relationships between its values.

For example, Lazarsfeld establishes that in the variable "performance" three dimensions can be distinguished: product quality, work rate and team profitability.

Third phase

During this phase, the indicators or specific empirical circumstances that reach the greatest dimension in the investigative units should be selected.

In order to comply with this phase, it is necessary to take the operationalization to the maximum possible limit. This is achieved by searching for all the clues that can be used in empirical reality as a sample of the dimension.

For example, a dimension of the variable “social class” could be “economic level”; In this case, the indicators would be the following: yields from urban and rustic properties, salaries, dividends from shares, capital interests, obtaining loans and paying debts, among others.

Fourth phase

It consists of the construction of the indices after having selected the most important and appropriate indicators for the investigation.

In some cases it may happen that each indicator is not assigned the same importance. For this reason, an index must be constructed that gathers in a common measure all the indicators that refer to a specific dimension; This is achieved by assigning a value to each of these according to its importance.

It is important to remember that the operationalization of variables is generally about substituting some variables for others that are more specific. Therefore, for the operation to be valid, the variables that are going to replace the others must be representative of the latter.

For this reason, the operationalization is based on the implicit or explicit formulation of probable assumptions or auxiliary hypotheses about the correct representation of the general variables by the indicators.

In summary, to operationalize a variable it is necessary to comply with the following:

1- State or define the variable.

2- Deduce its dimensions and main aspects.

3- Find the appropriate indicators for each dimension.

4- Form the index for each case.

Examples

If we take the variable "school achievement" as an example, we can define the following indicators:

- Number of approved and disapproved.

- Average of marks obtained.

- School dropout.

- Loss of class.

Another widely used example is the variable “socio-economic level”. In this case the indicators can be the following:

- Level of studies.

- Income level.

- Place of residence.

- Work activity.

- Monthly salary.

- Outstanding debts.

A third example may be the variable “gender violence”. In this case, the researcher can find the following indicators:

- Physical abuse.

- Psychological abuse.

- Control through physical force.

- Control through words.

- Violent manipulation.

- Verbal manipulation.

Another example can be the variable “family time”, which includes these indicators:

- Eat together.

- Shopping.

- Social meetings.

- Go to the movies.

- Travel to another city.

- Go to the beach.

- Camp in the woods.

- Visit relatives.

- Celebrate the Christmas festivities.

Finally, in the variable “couple conflict” we find the following indicators:

- You fight for friends.

- You fight for the children.

- Fights related to the sexual sphere.

- Non-conformities regarding the home.

- Non-conformities regarding finances.

- Appearance of a third party.

- Elaboration of lies.

References

1. Baray, H. (sf) Introduction to the research methodology. Retrieved on July 23, 2019 from Eumed: eumed.net
2. Betancurt, S. (2019) Operationalization of variables. Retrieved on July 23, 2019 from FCA online: fcaenlinea.unam.mx
3. Reguant, M. (2014) Operationalization of concepts / variables. Retrieved on July 23, 2019 from: Dipósit Digital: diposit.ub.edu
4. SA (sf) Operationalization: dimensions, indicators and variables. Retrieved on July 23, 2019 from Google Sites: sites.google.com
5. SA (sf) T ypes of variables in statistics and research. Retrieved on July 23, 2019 from Statistics how to: statisticshowto.datasciencecentral.cm
6. SA (sf) Types of variables. Retrieved on July 23, 2019 from Laerd Dissertation: dissertation.laerd.com