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Related Experiment Video

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Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and

Curtis Lee Petersen1,2, Ryan Halter3, David Kotz4

  • 1The Dartmouth Institute for Health Policy, Dartmouth, Hanover, NH, United States.

JMIR Mhealth and Uhealth
|June 17, 2020
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Summary
This summary is machine-generated.

This study developed a user-friendly mobile app for resistance exercise to combat sarcopenia, improving patient compliance. Positive sentiment during app development was linked to higher usability scores, demonstrating the value of user-centered design.

Keywords:
aged adultsmobile phoneremote sensing technologysarcopeniatelemedicine

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Area of Science:

  • Gerontology
  • Biomedical Engineering
  • Health Informatics

Background:

  • Sarcopenia, the age-related loss of muscle mass and strength, is a significant health concern for older adults.
  • Resistance exercise is effective for mitigating sarcopenia, but adherence to home-based programs remains low (approx. 40%).
  • Remote sensing systems and user-centered mobile app design can enhance patient engagement and compliance with exercise regimens.

Purpose of the Study:

  • To develop a user-centered mobile application for a novel resistance exercise device.
  • To involve older adults and clinicians in the app's design process.
  • To explore the utility of natural language processing (NLP) and sentiment analysis on data collected during user-centered design.

Main Methods:

  • A user-centered design approach was employed, including semistructured interviews with patients and clinicians at multiple development stages.
  • Interviews incorporated heuristic evaluations, cognitive walkthroughs, and observations.
  • Sentiment analysis (Bing sentiment library) and NLP topic modeling (LDA) were applied to transcripts; usability was assessed using SUS and USE questionnaires.

Main Results:

  • The study included 22 participants (mean age 68 years, 77% female).
  • Overall System Usability Scale (SUS) and Usefulness, Satisfaction, and Ease of use (USE) scores indicated moderate usability.
  • Positive sentiment during interviews correlated positively with SUS scores (ß=1.38, P=.01), but not USE scores; LDA revealed no topic overlap between patients and clinicians.

Conclusions:

  • Co-designing a mobile app with patients and clinicians resulted in a user-friendly application that supports adherence to resistance exercise for older adults.
  • This study is the first to integrate NLP and usability questionnaires for quantifying the user-centered design of technology for the geriatric population.
  • The findings highlight the importance of user involvement in technology development to improve health outcomes and compliance.