Exoskeletons in Care: A Video-Based Online-Experiment on Dehumanization and Gender Stereotypes in the Perception of Caregivers

Research output: ThesisMaster's / Diploma thesis

Abstract

As assistive wearable devices, exoskeletons are increasingly recognized for their potential in preventing and alleviating work-related musculoskeletal disorders. However, their implementation may pose challenges, notably the risk of mechanistic dehumanization. This presents a particularly pressing concern in socially demanding fields such as caregiving, where individuals are subjected daily to both their own experiences with the technology as well as the view of those they interact
with. Despite its relevance, the social reception of exoskeleton use in caregiving remains largely unexplored. This experimental online study investigates whether and how the presence of an exoskeleton affects the external perception of caregivers by drawing on established theories such as the Stereotype Content Model and mechanistic dehumanization. It further incorporates the highly relevant issue of gender-stereotyping in care work, examining the intersection of technology
and gender in a stereotype-laden field. 223 participants in total viewed one of four videos depicting a female or male caregiver, either wearing or not wearing an exoskeleton, in an eldercare interaction. Caregivers were then rated on their perceived warmth, competence and machine-likeness. It was assumed that the use of an exoskeleton would be associated with increased dehumanization, particularly for the female caregiver. While no overall effects of the exoskeleton by itself were observed, the interaction between gender and technology yielded significant results. The female caregiver – but not the male – was perceived as less warm and more machine-like
when wearing an exoskeleton. These findings offer early insights into the social reception of exoskeletons in care settings and underscore how gendered expectations shape the perceptions of wearable technology-assisted work in socially demanding fields.
Original languageEnglish
QualificationMaster
Awarding Institution
  • Johannes Kepler University Linz
Supervisors/Reviewers
  • Siedl, Sandra Maria, Supervisor
Award date29 Apr 2025
Publication statusPublished - 12 Jun 2025

Fields of science

  • 102013 Human-computer interaction
  • 501002 Applied psychology
  • 501012 Media psychology
  • 202035 Robotics

JKU Focus areas

  • Digital Transformation

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