Too old for risk? Enhancing effects between risk assessment and age on the perceived usefulness of cyborg technologies

This cross-sectional study (N = 572) examined how chronological age and individual risk perceptions influence the perceived usefulness of disruptive implant and wearable technologies, controlling for sex. Previous research has frequently examined age effects in technology acceptance but rarely employed differentiated measures of perceived risk, especially for body-integrated technologies. To address this gap, we developed and validated the Implant Risk Scale (IRS) to assess specific risk dimensions associated with implantable technologies. Ten potential risk dimensions were identified from prior research, and 50 items were developed based on the relevant scientific literature. Exploratory factor analysis of this item pool identified four distinct risk factors: ethical, physiological, psychological, and data hacking risk, accounting for 85 % of the total variance. Each risk could reliably be assessed with three items. In addition to age (β = -0.22, p < .01), physiological risk (β = -0.27, p < .01) and psychological risk (β = -0.16, p < .01) had independent negative effects on perceived usefulness. Moreover, moderation analyses indicated that each implant risk dimension enhanced the negative effect of age on perceived usefulness (ΔR²s between 0.01 and 0.02, ps < 0.01). Differentiated risk dimensions should be considered when examining technology adoption behavior. The validated IRS provides a concise framework for capturing these risk assessments. Different demographic groups seem to be affected to varying degrees by these risk dimensions. Social inequalities between demographic groups due to the use of disruptive technologies might be widened by perceived risk.