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Smartphone App-Based Survey Deployment Patterns and Longitudinal Response Rate: Randomized Controlled Trial.

Yuankai Zhang1, Jian Rong2, Xuzhi Wang1

  • 1Department of Biostatistics, School of Public Health, Boston University, Boston, MA, United States.

Journal of Medical Internet Research
|October 10, 2025
PubMed
Summary
This summary is machine-generated.

To combat survey fatigue in longitudinal studies, delivering smaller survey batches more frequently (biweekly) improved participant response rates compared to less frequent, larger batches (every 4 weeks). This digital health strategy enhances data quality over time.

Keywords:
digital device useinterventionlongitudinal engagementmobile app–based surveymobile healthmobile phonerandomized controlled trialsurvey deployment

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Area of Science:

  • Digital Health
  • Longitudinal Studies
  • Survey Methodology

Background:

  • Survey fatigue is a significant challenge in longitudinal studies, particularly those utilizing smartphone applications for data collection.
  • There is a need for evidence-based strategies to effectively maintain participant engagement and response rates over extended study periods.

Purpose of the Study:

  • To evaluate the impact of a more frequent smartphone-administered survey deployment strategy, using smaller survey batches, on participant response rates.
  • To assess the effectiveness of this strategy over an extended duration in a longitudinal study setting.

Main Methods:

  • A randomized controlled trial (NCT04752657) was conducted within the Framingham Heart Study cohorts (June 2021-December 2023).
  • Participants were randomized to receive either a full survey set every 4 weeks (control) or half the set biweekly (experimental), completing the full set every 4 weeks in both arms.
  • The primary outcome was the longitudinal proportion of surveys returned per participant across four assessment periods, analyzed using mixed-effects regression models.

Main Results:

  • The experimental group demonstrated higher sustained response rates over time compared to the control group (P=.003 for interaction).
  • While initial response rates were similar (75% vs 76%), the experimental group showed progressively higher returns in subsequent periods (e.g., 58% vs 50% in weeks 24-32).
  • The proportion of non-responding participants increased from 3% to 38% in the control group versus 1% to 28% in the experimental group.

Conclusions:

  • Deploying half the survey set biweekly, compared to the full set every 4 weeks, significantly improved maintained longitudinal survey response rates.
  • This strategy shows promise in mitigating survey fatigue and enhancing data quality within digital health research.