Scale Analysis

The Opinion Scale is a measurement tool widely used to assess individuals’ opinions, attitudes, and preferences regarding various issues. This scale typically includes a series of statements or questions to which participants respond by selecting from an agreement–disagreement continuum, such as “Strongly Agree,” “Agree,” “Neutral,” “Disagree,” and “Strongly Disagree.” The Opinion Scale may also be numerical, allowing participants to choose a number that represents the intensity of their opinion. Through this scale, quantitative data are collected that enable the analysis and comparison of the opinions of a population sample. The results can be used to understand general trends and support decision-making in various fields, such as market research, sociology, and psychology.

Purpose of the Scale

The purpose of this scale is to provide a structured and objective method for measuring individuals’ opinions and attitudes on specific issues. By using a standardized set of statements and a rating scale, it enables the collection of quantitative data that allow for analysis and comparison of results. This helps researchers and analysts to identify general trends and differences within a population, detect patterns, and make evidence-based decisions. In addition, the Opinion Scale helps to reduce bias and subjective judgments, offering a more reliable and valid picture of public opinions.

Scale Scoring

The OS-80 consists of 80 items, which are rated as follows:
Strongly Disagree
Disagree Very Much
Disagree
Neither Agree nor Disagree
Agree
Agree Very Much
Strongly Agree

References

Rokeach, M. (1956). Political and religious dogmatism: An alternative to the authoritarian personality. Psychological Monographs, 43(18), 1–43.
Hood, Ralph W. (1968). An empirical test of the validity of Rokeach’s Opinionation Scale. The Journal of Psychology, 69(1), 47–52.
Robinson, John P., & Shaver, Phillip R. (1969). Measures of Political Attitudes. Institute for Social Research, University of Michigan, Ann Arbor, Michigan.