# General corruption scale: development and psychometric properties

## TL;DR

This paper introduces a new scale to measure individual support for corruption and validates its reliability and effectiveness.

## Contribution

The paper presents the first-ever General Corruption Scale with empirical validation of its psychometric properties.

## Key findings

- The scale has a two-factor model with 26 items showing good fit indices.
- The scale correlates with related constructs like jeitinho and trust propensity.
- The scale demonstrates satisfactory validity and reliability for measuring corruption support.

## Abstract

Corruption is a pervasive phenomenon that erodes institutional structures and undermines social relations. Despite its widespread impact, little attention has been given to developing and providing empirical evidence of the construct validity and reliability of measures assessing individual differences in support for corruption. This study seeks to address this gap by introducing, for the first time, the General Corruption Scale and presenting the results of a research program designed to provide robust empirical evidence for the quality of its psychometric properties.

In the first study, content validity was assessed by three experts using the Content Validity Coefficient, confirming the adequacy of the scale’s content. Subsequent studies employed both exploratory (n = 308) and confirmatory (n = 840) factor analyses to evaluate its factorial structure.

Results supported a two-factor model comprising 26 items, organized into Perception of Corruption and Support for Corruption. The model demonstrated satisfactory fit indices and performed better than alternative measurement models. Evidence of nomological validity was established through associations with measures of jeitinho and propensity to trust.

The scale is theoretically aligned with its foundational model and demonstrates evidence of validity and reliability. Further research is recommended to assess its psychometric performance across diverse contexts.