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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.
Background:
Survey fatigue is a common challenge in longitudinal studies, particularly when using smartphone apps to collect survey data. Evidence-based strategies are needed to maintain longitudinal response rates.
Objective:
This study aims to evaluate the effect of a more frequent smartphone-administered survey deployment strategy with smaller survey batches on participant response rates over an extended period.
Methods:
We conducted a randomized controlled trial (NCT04752657) embedded in the electronic Framingham Heart Study cohorts between June 2021 and December 2023. Participants were randomly allocated to receive a full set of surveys every 4 weeks (control group) or half of the survey set biweekly, such that the full set is completed every 4 weeks (experimental group). Randomization was stratified by age (≤75 y vs >75 y) and phone type (Android vs iPhone). Married couples were assigned to the same group using a blocked randomization approach. The primary outcome was the proportion of surveys returned per participant assessed longitudinally across four periods (baseline to wk 8, wk 8-16, wk 16-24, and wk 24-32), with 19, 17, 16, and 15 unique surveys deployed, respectively. We used mixed-effects regression models with random intercepts to compare the repeated outcome between groups. Stratified analyses by age and sex were performed.
Results:
Among 492 participants (mean age 74, SD 6.3 y; 58%, n=284 women, 84%, n=413 non-Hispanic White), there was evidence that the experimental group had higher response rates over time compared to the control group (P=.003 for interaction between deployment pattern and time). Both groups showed similar proportions of surveys returned during the first period (75% vs 76%). The experimental group had higher response rates than the control group in subsequent periods (70% vs 67% in wk 8-16, 64% vs 59% in wk 16-24, and 58% vs 50% in wk 24-32). The proportion of participants not returning any surveys increased from 3% to 38% in the control group compared to 1% to 28% in the experimental group across the four time periods. Stratified analyses revealed that among younger participants (≤75 y), the experimental group showed 12% higher survey response rates compared to the control group in the final period, while the difference was minimal among older participants (>75 years). The effect of the deployment pattern was similar for men and women. Three-way interaction analyses revealed no significant differences in the deployment pattern effect over time by age group (P=.95) or sex (P=.65).
Conclusions:
Administering half of the surveys every 2 weeks, as compared to all surveys every 4 weeks, was associated with higher maintained longitudinal survey response rates. This strategy may help mitigate survey fatigue and improve data quality in digital health studies.
Trial Registration:
ClinicalTrials.gov NCT04752657; https://clinicaltrials.gov/study/NCT04752657.
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