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I-Corps: Digital Phenotyping to Predict and Prevent Burnout in the Workplace

Project: Research

Abstract & Details

Description

Award ID: 2131399

The broader impact/commercial potential of this I-Corps project is the development of prediction software to prevent young adult burnout in the workplace. Currently, digital lives play a major role in mental health. This project aims to develop technology to analyze online behavior to predict and address burnout in the workplace. Burnout is cited as a primary source of disability in the workplace. Burnout prediction and prevention enabled with artificial intelligence may allow companies to be more productive and may allow better employee mental wellness. The proposed technology is focused on the young workforce due to the higher impact of mobile technology on their mental health. The proposed technology is based on analyzing mobile phone user interactions and behaviors and correlating them to mental health. The initial application of the technology is the game development industry where burnout is common due to the high cognitive demand on development teams to produce video games and to meet deadlines. This I-Corps project is based on the development of a software platform using digital phenotyping and artificial intelligence to measure behavior, cognition, and mood to design effective clinical mental health interventions for young professionals working in highly stressful environments. Digital phenotyping is a process that involves collecting sensor and sociability parameters, as well as keyboard, voice and speech data from off-the-shelf smartphones. Predictors of anxiety and depressive relapses include disrupted sleep, reduced sociability and physical activity, and changes in mood. Intonation in language and cognitive function may be measured via digital phenotyping and analyzed. The proposed technology may deliver metrics to predict possible burnout and other mental health problems, and propose artificial intelligence-based solutions for prevention of burnout in the young workforce. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Ruth Shuman
StatusClosed
Effective start/end date06/01/2105/31/22

Funding

  • I-Corps Teams: $50,000.00

Active Fiscal Year

  • FY2022

Start Fiscal Year

  • FY2021

TIP Programs

  • I-Corps Teams

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 100%)

Technology Foci

  • Artificial Intelligence (Broad)
  • (confidence score: 100%)

Congressional District at Award

  • District n. 07 of Massachusetts

Current Congressional District

  • District n. 07 of Massachusetts

United States

  • Massachusetts

Core Based Statistical Area (CBSA)

  • Boston-Cambridge-Newton, MA-NH

County

  • County: Middlesex, MA

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