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Guttman Scale

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What is the Guttman Scale

The Guttman Scale, also known as the cumulative scale, is one of the methods used for scale construction in sociological and psychological research. The scale is used to measure respondents’ attitudes toward a phenomenon or concept through a sequence of questions ordered by intensity or difficulty. The key feature of the Guttman Scale is that respondents’ answers must follow a certain logic: if a respondent agrees with a more “difficult” statement, they should also agree with the “simpler” statements.

What is the Guttman Scale used for

The Guttman Scale is used to measure sequential or cumulative attitudes, opinions, or behaviors of respondents on a specific topic. Its main application is to reveal the structure of people’s opinions on an issue and to determine the intensity of their positions.

Main purposes and uses of the Guttman Scale:

  • Measuring opinions and attitudes. The scale helps rank respondents according to the strength of their opinions or positions. This is useful for understanding how strongly people support a particular viewpoint.
  • Diagnosing response consistency. Since the questions are arranged by increasing difficulty or intensity, it allows identifying how logically and consistently respondents answer them.
  • Predicting responses. Using the Guttman Scale, one can predict respondents’ answers to “weaker” questions if it is known they agreed with the “stronger” statements.
  • Evaluating cumulative properties. The questions are organized so that agreement with a stronger statement implies agreement with weaker ones. This reveals the cumulative nature of attitudes, where a person moves from more general to more specific.
  • Sociological and psychological research. In these fields, the scale is used to assess things like the level of agreement with various social norms, attitudes toward specific issues (e.g., human rights, politics, ecology, etc.).

Thus, the Guttman Scale allows researchers to gain a deeper understanding of the structure of respondents’ attitudes and relationships, as well as obtain more accurate and logically consistent data for analysis.

General methodology of the Guttman Scale

The methodology for constructing a Guttman Scale includes several steps that help organize statements or questions in a sequence so that respondents’ answers follow a certain logic. The main goal is to create a scale where agreement with more complex or radical statements implies agreement with simpler ones.

Main steps in building the Guttman Scale:

  1. Selecting the research area. Define the specific topic or phenomenon to measure, for example, the level of support for certain political or social positions.
  2. Formulating statements. Develop a series of statements or questions covering different levels of intensity or difficulty. These statements should be related and ranked by the degree of expression of the phenomenon. The questions should be worded so that agreement with one statement logically implies agreement with weaker statements.
  3. Pilot testing. Conduct a survey with these statements among a small group of respondents to test how consistent their answers are and whether the wording is understood correctly.
  4. Consistency analysis. After data collection, analyze how well the answers conform to the cumulative model. Usually, a coefficient of reproducibility (or consistency coefficient) is used to show how well respondents’ answers fit the scale. If a respondent agrees with a more complex statement, their answers should include agreement with previous, simpler statements.
  5. Checking reproducibility. If the scale corresponds to the cumulative logic, the reproducibility level should be above 0.90. This means there is a 90% probability of predicting a respondent’s answer to simpler statements if their answer to more complex ones is known.
  6. Adjusting the scale. If inconsistencies are found (e.g., respondents do not always follow the cumulative logic), either revise the wording of the questions or exclude incorrect statements.
  7. Creating the final scale. Based on the analysis, create the final scale including only those statements that clearly follow the principles of cumulativeness.

Important points:

  • Reproducibility — the main goal of the Guttman Scale. It measures how predictable respondents’ answers are based on their “strongest” responses.
  • Cumulativeness — a key characteristic. Respondents must logically agree with each simpler statement if they agreed with a more complex one.

The Guttman Scale methodology is effective for measuring cumulative opinions and positions where respondents’ answers follow a sequence and can be applied in social sciences, psychology, marketing, and other fields.

Example:

A researcher wants to measure respondents’ level of support for various smoking bans. For this purpose, questions are formulated, each representing stricter ban measures.

Example statements:

  1. I support a smoking ban in schools.
  2. I support a smoking ban in restaurants.
  3. I support a smoking ban in public places.
  4. I support a complete smoking ban.

If a respondent agrees with statement 4 (complete smoking ban), this should logically mean they also agree with the previous, less strict statements (1, 2, and 3). That is, a respondent who supports a complete ban also supports bans in schools, restaurants, and public places.

Using the Guttman Scale, the researcher can rank respondents by the level of their support for different bans, from minimal (only schools) to maximal (complete ban).

How to improve the Guttman Scale

To improve the Guttman Scale and increase its reliability and accuracy, several methods and strategies can be used. Here are some of them:

  • Clear and unambiguous wording. Statements should be understandable and avoid ambiguity.
  • Logical sequence. Statements should be arranged in increasing intensity so respondents can logically agree with less complex statements if they agree with more complex ones.
  • Pilot testing. Conduct pilot studies to check the scale structure and identify problems with wording or sequence.
  • Reproducibility analysis. Calculate the reproducibility coefficient to verify how well respondents’ answers fit the cumulative model (preferably above 90%).
  • Eliminating inconsistencies. If respondents give illogical answers (e.g., agreeing with a more complex but disagreeing with a simpler statement), review or remove such questions.
  • Using a consistency coefficient. Analyze the degree of consistency in answers to ensure questions reflect true cumulative logic.
  • Adding intermediate questions. Include more intermediate statements for more precise ranking of opinions.
  • Splitting complex statements. If one statement covers multiple aspects, split it into two or more simpler statements for accuracy.
  • Controlling bias. Ensure statement wording does not mislead respondents or create bias.

Constantly update the scale. Review and adapt the scale as new information arises or the research topic changes to maintain its relevance and accuracy.

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