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Design Guidelines for Improving Mobile Sensing Data Collection: Prospective Mixed Methods Study.

Christopher Slade1,2, Roberto M Benzo3,4, Peter Washington2

  • 1Computer Science Department, Brigham Young University-Hawaii, Laie, HI, United States.

Journal of Medical Internet Research
|November 18, 2024
PubMed
Summary
This summary is machine-generated.

Mobile sensing apps can improve data collection for machine learning models. Contextual prompting is better for background events, while setup prompting is recommended for ecological momentary assessments (EMA).

Keywords:
active data collectioncollegedata consistencyecological momentary assessmentmHealthmachine learningmixed methodmobile datamobile health sensingmobile phonepassive data collectionreal-world settingstudentuser data

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Area of Science:

  • Mobile sensing
  • Machine learning
  • Data collection

Background:

  • Machine learning models utilize sensor data streams for predictions via ecological momentary assessments (EMA).
  • Challenges persist in mobile data collection, particularly obtaining authorization for background tasks and notifications.

Purpose of the Study:

  • To investigate mobile sensing app challenges and develop design guidelines.
  • To compare setup vs. contextual prompting for active data collection (EMA).
  • To evaluate scheduled background tasks vs. persistent reminders for passive data collection.

Main Methods:

  • Developed iOS and Android mobile sensing apps for a 30-day study with 145 college students.
  • Tested active data collection via daily EMA questions.
  • Assessed passive data collection through background location events, persistent reminders, and scheduled background tasks.

Main Results:

  • Setup and contextual prompting showed no significant difference in EMA compliance (23.4/30 assessments completed).
  • Contextual prompting was 55.5% more effective for authorizing background events.
  • Persistent reminders, despite initial user resistance, completed 226.5% more background sessions than scheduled tasks.

Conclusions:

  • Contextual prompting is more efficient for authorizing background events in passive sensing.
  • Setup prompting is recommended for EMA due to more consistent notification delivery on Android.
  • Persistent reminders offer a viable method to enhance sensor and user data collection for adaptive interventions.