Description

The Ascription of Responsibility Questionnaire (ARQ) is an important tool for assessing how individuals attribute responsibility for various events and situations. The proper design, analysis, and calibration of the scale ensure the reliability and validity of the results, providing valuable insights into individuals’ perceptions of responsibility and how these perceptions influence their behavior.

Objective

The primary goal of the ARQ is to evaluate how individuals attribute responsibility for different events and circumstances. The questionnaire examines personal and external attributions of responsibility and their effects on behavior and decision-making. It aims to: Assess individuals’ perceptions of responsibility in various situations. Understand how responsibility attribution influences decision-making and behavior. Explore differences in responsibility attribution across demographics (e.g., gender, age, profession).

Analysis

Data collected from the ARQ is analyzed using various statistical methods: Descriptive Statistics: Measures such as means, variances, and percentages to identify general trends in responsibility attribution. Frequency Analysis: Examining response distributions for each question. Comparative Analysis: Comparing responses between different participant groups (e.g., gender, age groups, professional background). Correlation Analysis: Exploring relationships between responsibility attribution and other psychological factors (e.g., anxiety levels, self-esteem, job performance). Factor Analysis: Investigating the structure of the questionnaire to verify the theoretical construct of the tool.

Calibration

The ARQ scale undergoes rigorous calibration to ensure its reliability and validity: Preliminary Testing: Pilot testing on a small sample to identify and correct issues. Reliability Analysis: Statistical methods (e.g., Cronbach’s alpha) to assess internal consistency. Validity Analysis: Assessing content validity, criterion validity, and construct validity to ensure the scale measures what it is intended to measure. Cross-Validation: Using data from different samples to confirm the reliability and validity of the results.

Bibliography

Heider, F. (1958). The Psychology of Interpersonal Relations. Wiley.
DeVellis, R. F. (2016). Scale Development: Theory and Applications (4th ed.). Sage Publications.
Fowler, F. J. (2013). Survey Research Methods (5th ed.). Sage Publications.
Weiner, B. (1985). “An Attributional Theory of Achievement Motivation and Emotion.” Psychological Review, 92(4), 548-573.
Kelley, H. H., & Michela, J. L. (1980). “Attribution Theory and Research.” Annual Review of Psychology, 31, 457-501.