The Perceived Danger (PD) Scale: Development and Validation

TL;DR

This paper introduces a new 12-item scale to measure perceived danger of robots, validated through multiple studies, showing it predicts safety perceptions better than existing tools and responds to robot speed changes.

Contribution

The study develops and validates the first psychometrically sound perceived danger scale for robots, including its factor structure and predictive validity.

Findings

The scale has four subdimensions: affective states, physical vulnerability, ominousness, and cognitive readiness.

The perceived danger scale outperforms the Godspeed perceived safety scale in predicting perceptions.

The scale is sensitive to robot speed manipulations, aligning with empirical expectations.

Abstract

There are currently no psychometrically valid tools to measure the perceived danger of robots. To fill this gap, we provided a definition of perceived danger and developed and validated a 12-item bifactor scale through four studies. An exploratory factor analysis revealed four subdimensions of perceived danger: affective states, physical vulnerability, ominousness, and cognitive readiness. A confirmatory factor analysis confirmed the bifactor model. We then compared the perceived danger scale to the Godspeed perceived safety scale and found that the perceived danger scale is a better predictor of empirical data. We also validated the scale in an in-person setting and found that the perceived danger scale is sensitive to robot speed manipulations, consistent with previous empirical findings. Results across experiments suggest that the perceived danger scale is reliable, valid, and an adequate predictor of both perceived safety and perceived danger in human-robot interaction contexts.