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Burnout and the Quantified Workplace: Tensions around Personal Sensing Interventions for Stress in Resident Physicians.
Adler, Daniel A; Tseng, Emily; Moon, Khatiya C; Young, John Q; Kane, John M; Moss, Emanuel; Mohr, David C; Choudhury, Tanzeem.
Afiliación
  • Adler DA; Cornell Tech, USA.
  • Tseng E; Cornell Tech, USA.
  • Moon KC; Zucker Hillside Hospital, USA.
  • Young JQ; Zucker School of Medicine at Hofstra/Northwell Health and Zucker Hillside Hospital, USA.
  • Kane JM; Zucker Hillside Hospital, USA.
  • Moss E; Cornell Tech and Data & Society Research Institute, USA.
  • Mohr DC; Northwestern University, USA.
  • Choudhury T; Cornell Tech, USA.
Proc ACM Hum Comput Interact ; 6(CSCW2)2022 Nov.
Article en En | MEDLINE | ID: mdl-36714170
Recent research has explored computational tools to manage workplace stress via personal sensing, a measurement paradigm in which behavioral data streams are collected from technologies including smartphones, wearables, and personal computers. As these tools develop, they invite inquiry into how they can be appropriately implemented towards improving workers' well-being. In this study, we explored this proposition through formative interviews followed by a design provocation centered around measuring burnout in a U.S. resident physician program. Residents and their supervising attending physicians were presented with medium-fidelity mockups of a dashboard providing behavioral data on residents' sleep, activity and time working; self-reported data on residents' levels of burnout; and a free text box where residents could further contextualize their well-being. Our findings uncover tensions around how best to measure workplace well-being, who within a workplace is accountable for worker stress, and how the introduction of such tools remakes the boundaries of appropriate information flows between worker and workplace. We conclude by charting future work confronting these tensions, to ensure personal sensing is leveraged to truly improve worker well-being.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Proc ACM Hum Comput Interact Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Proc ACM Hum Comput Interact Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos