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Robot-Mediated Nudges for Workplace Health: Not a One-Size-Fits-All Modeling Problem.
Preston, Rhian C; Dinsdale, Kenna; Shippy, Madison R; Fitter, Naomi T.
Afiliación
  • Preston RC; CoRIS Institute, Oregon State University, P.O. Box 1212, Corvallis 97331, OR, USA.
  • Dinsdale K; CoRIS Institute, Oregon State University, P.O. Box 1212, Corvallis 97331, OR, USA.
  • Shippy MR; CoRIS Institute, Oregon State University, P.O. Box 1212, Corvallis 97331, OR, USA.
  • Fitter NT; CoRIS Institute, Oregon State University, P.O. Box 1212, Corvallis 97331, OR, USA.
Int J Soc Robot ; 16(5): 899-918, 2024 May.
Article en En | MEDLINE | ID: mdl-39239458
ABSTRACT
Prolonged sedentary behavior in the vast population of office and remote workers leads to increased cardiovascular and musculoskeletal health challenges, and existing solutions for encouraging breaks are either costly health coaches or notification systems that are easily ignored. A socially assistive robot (SAR) for promoting healthy workplace practices could provide the physical presence of a health coach along with the scalability of a notification system. To investigate the impact of such a system, we implemented a SAR as an alternative break-taking support solution and examined its impact on individual users' break-taking habits over relatively long-term deployments. We conducted an initial two-month-long study (N = 7) to begin to understand the robot's influence beyond the point of novelty, and we followed up with a week-long data collection (N = 14) to augment the dataset size. The resulting data was used to inform a robot behavior model and formulate possible methods of personalizing robot behaviors. We found that uninterrupted sitting time tended to decrease with our SAR intervention. During model formulation, we found participant responsiveness to the break-taking prompts could be classified into three archetypes and that archetype-specific adjustments to the general model led to improved system success. These results indicate that break-taking prompts are not a one-size-fits-all problem, and that even a small dataset can support model personalization for improving the success of assistive robotic systems.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Int J Soc Robot Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Int J Soc Robot Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos