# Indicators of retention in remote digital health studies: A cross-study evaluation of 100,000 participants

arXiv: https://arxiv.org/abs/1910.01165 · HTML: https://mlsanity.com/paper/1910.01165/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Oct 2019.

## Built on by (most cited first, 3 of 3)

- [A General Framework for Off-Policy Learning with Partially-Observed Reward](https://mlsanity.com/paper/2506.14439/) (2025)
- [Human Activity Recognition from Smartphone Sensor Data for Clinical Trials](https://mlsanity.com/paper/2508.05175/) (2025)
- [Curriculum-Aware Interpolate-then-Refine: Learned Physiological Time-Series Imputation under Realistic Missingness](https://mlsanity.com/paper/2608.21207/) (2026)

## Abstract (arXiv)

Digital technologies such as smartphones are transforming the way scientists conduct biomedical research using real-world data. Several remotely-conducted studies have recruited thousands of participants over a span of a few months. Unfortunately, these studies are hampered by substantial participant attrition, calling into question the representativeness of the collected data including generalizability of findings from these studies. We report the challenges in retention and recruitment in eight remote digital health studies comprising over 100,000 participants who participated for more than 850,000 days, completing close to 3.5 million remote health evaluations. Survival modeling surfaced several factors significantly associated(P < 1e-16) with increase in median retention time i) Clinician referral(increase of 40 days), ii) Effect of compensation (22 days), iii) Clinical conditions of interest to the study (7 days) and iv) Older adults(4 days). Additionally, four distinct patterns of daily app usage behavior that were also associated(P < 1e-10) with participant demographics were identified. Most studies were not able to recruit a representative sample, either demographically or regionally. Combined together these findings can help inform recruitment and retention strategies to enable equitable participation of populations in future digital health research.