Invisible work and unpredictable challenges in clinical practice: results from a participatory design case study

Abstract The shortage of professional caregivers and an aging population in Western countries contribute to high workloads in hospitals, which can negatively affect patient care and increase nurse turnover. Robotic assistance has the potential to alleviate these workloads. We conducted a design case study to identify application scenarios to reduce nurses’ administrative challenges. We found that tasks such as patient admissions and escorting patients to in-house medical appointments often constitute invisible work, which can be supported by a robot. Observations and follow-up semi-structured interviews with nursing staff highlight the potential of robots to reduce workload. At the same time, successful implementation requires considering the perspectives of multiple stakeholders, including nursing staff, patients, and bystanders. Moreover, our findings show that invisible human work by nurses was often needed to maintain the robot’s functionality.

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Publication Details

Journal
i-com
Published
2026-01-27
DOI
https://doi.org/10.1515/icom-2025-0041
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
0.00
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article

Invisible work and unpredictable challenges in clinical practice: results from a participatory design case study

Katharina Thiel, Lorin Lingl, Dominik Schulz, David Unbehaun et al.
i-com
Social Robot Interaction and HRI
article

Invisible work and unpredictable challenges in clinical practice: results from a participatory design case study

Katharina Thiel, Lorin Lingl, Dominik Schulz, David Unbehaun, Volker Wulf
article en

Abstract

Abstract The shortage of professional caregivers and an aging population in Western countries contribute to high workloads in hospitals, which can negatively affect patient care and increase nurse turnover. Robotic assistance has the potential to alleviate these workloads. We conducted a design case study to identify application scenarios to reduce nurses’ administrative challenges. We found that tasks such as patient admissions and escorting patients to in-house medical appointments often constitute invisible work, which can be supported by a robot. Observations and follow-up semi-structured interviews with nursing staff highlight the potential of robots to reduce workload. At the same time, successful implementation requires considering the perspectives of multiple stakeholders, including nursing staff, patients, and bystanders. Moreover, our findings show that invisible human work by nurses was often needed to maintain the robot’s functionality.

i-com
University of Siegen (DE), Clausthal University of Technology (DE)
Openalex Percentile: Top 81%
Social Robot Interaction and HRI
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