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Accepted for/Published in: JMIR Formative Research

Date Submitted: May 11, 2024
Date Accepted: Sep 20, 2024

The final, peer-reviewed published version of this preprint can be found here:

Exploring the Perspectives of Older Adults on a Digital Brain Health Platform Using Natural Language Processing: Cohort Study

Ding H, Gifford K, Shih LC, Ho K, Rahman S, Igwe A, Low S, Popp Z, Searls E, Li Z, Madan S, Burk A, Hwang PH, Anda-Duran ID, Kolachalama VB, Au R, Lin H

Exploring the Perspectives of Older Adults on a Digital Brain Health Platform Using Natural Language Processing: Cohort Study

JMIR Form Res 2024;8:e60453

DOI: 10.2196/60453

PMID: 39556805

PMCID: 11612578

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Exploring Perspectives of Older Adults on Digital Brain Health Platform with Natural Language Processing: A Pilot Cohort Study

  • Huitong Ding; 
  • Katherine Gifford; 
  • Ludy C. Shih; 
  • Kristi Ho; 
  • Salman Rahman; 
  • Akwaugo Igwe; 
  • Spencer Low; 
  • Zachary Popp; 
  • Edward Searls; 
  • Zexu Li; 
  • Sanskruti Madan; 
  • Alexa Burk; 
  • Phillip H. Hwang; 
  • Ileana De Anda-Duran; 
  • Vijaya B Kolachalama; 
  • Rhoda Au; 
  • Honghuang Lin

ABSTRACT

Background:

Although digital technology represents a growing field aiming to revolutionize early Alzheimer's disease (AD) risk prediction and monitoring, the perspectives of older adults on an integrated digital brain health platform have not been investigated.

Objective:

This study aims to understand the perspectives of older adults on a digital brain health platform by conducting semi-structured interviews and analyzing their transcriptions by natural language processing (NLP).

Methods:

The study included 28 participants from the Boston University Alzheimer’s Disease Research Center (BU ADRC), all of whom engaged with a digital brain health platform over an initial assessment period of 14 days. Semi-structured interviews were conducted to collect data on participants' experiences with the digital brain health platform. The transcripts generated from these interviews were analyzed using NLP techniques. The frequency of positive and negative terms was evaluated through word count analysis. A sentiment analysis was used to measure the emotional tone and subjective perceptions of the participants towards the digital platform.

Results:

Word count analysis revealed a generally positive sentiment towards the digital platform, with "like", "well", and "good" being the most frequently mentioned positive terms. However, terms such as "problem" and "hard" indicated certain challenges faced by participants. Sentiment analysis showed a slightly positive attitude with a median polarity score of 0.13 on a scale from -1 (completely negative) to 1 (completely positive), and a median subjectivity score of 0.51, ranging from 0 (completely objective) to 1 (completely subjective). These results suggested an overall positive attitude among the study cohort.

Conclusions:

The study highlights the importance of understanding older adults' attitudes toward digital health platforms amidst the comprehensive evolution of the digitalization era. Future research should focus on refining digital solutions to meet the specific needs of older adults, fostering a more personalized approach to brain health.


 Citation

Please cite as:

Ding H, Gifford K, Shih LC, Ho K, Rahman S, Igwe A, Low S, Popp Z, Searls E, Li Z, Madan S, Burk A, Hwang PH, Anda-Duran ID, Kolachalama VB, Au R, Lin H

Exploring the Perspectives of Older Adults on a Digital Brain Health Platform Using Natural Language Processing: Cohort Study

JMIR Form Res 2024;8:e60453

DOI: 10.2196/60453

PMID: 39556805

PMCID: 11612578

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