# Use of Digital Health Interventions Among Forcibly Displaced People: A Systematic Review and Meta-Analysis

## TL;DR

Digital health interventions show high recruitment and retention rates among forcibly displaced people, suggesting they are a feasible way to deliver health care in this population.

## Contribution

This study provides the first systematic review and meta-analysis on recruitment and retention rates of digital health interventions in forcibly displaced populations.

## Key findings

- Recruitment rates ranged from 16% to 100%, with a pooled estimate of 91%.
- Retention rates ranged from 28% to 91%, with a pooled estimate of 68%.
- Digital health interventions are feasible and scalable for delivering health care to forcibly displaced people.

## Abstract

What are the recruitment and retention rates for digital health interventions among forcibly displaced people?

In this systematic review and meta-analysis of 9 randomized clinical trials with 2858 participants, recruitment and retention rates were highly variable, ranging from 16% to 100% and 28% to 91%, respectively. The pooled estimates were high at 91% for recruitment and 68% for retention.

These findings suggest that digital technologies—thanks to their low cost, accessibility, and scalability—may provide a feasible way to deliver health interventions in forcibly displaced populations.

This systematic review and meta-analysis examines the recruitment and retention rates of forcibly displaced people in randomized clinical trials using digital health interventions.

Forcibly displaced people face significant biopsychosocial barriers to accessing health care. Digital health interventions have emerged as tools to bridge care gaps and have been successfully implemented in other disadvantaged populations to improve health care access and outcomes. However, the feasibility and practicality of digital health interventions among forcibly displaced individuals cannot be fully evaluated without characterizing recruitment and retention rates for these interventions in this unique population.

To evaluate the recruitment rate and retention rate for digital health interventions in forcibly displaced people.

A comprehensive search was conducted in PubMed, Web of Science, and SocINDEX in January 2023, with an updated search in February 2024. The search strategy followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The protocol was registered in PROSPERO.

Only randomized clinical trials evaluating digital health interventions in forcibly displaced populations were included. Non–peer reviewed studies, reviews, and studies lacking recruitment or retention data were excluded. Two independent reviewers screened and selected studies, and conflicts were resolved by a third reviewer.

Data were extracted independently by 2 reviewers using Covidence, and a third reviewer resolved discrepancies. Meta-analysis was conducted using a random-effects model to estimate the pooled recruitment rate and retention rate. Study quality was assessed using the Downs and Black Checklist.

Recruitment rate (percentage of prospective participants who were successfully randomized) and retention rate (percentage of randomized participants who completed the intervention).

A total of 9 randomized clinical trials with 2858 participants were analyzed. The most frequently investigated technology was mobile applications (4 trials), followed by mobile phones (3 trials), with 1 study utilizing tablets and another using wearables. Recruitment rates varied widely across studies (16% to 100%), as did retention rates (28% to 91%). The pooled recruitment rate was 91% (95% CI, 57%-99%; I2 = 99%), and the pooled retention rate was 68% (95% CI, 48%-84%; I2 = 98%).

In this systematic review and meta-analysis of 9 randomized clinical trials, forcibly displaced populations exhibited variable recruitment and retention rates, although pooled estimates were high. These findings suggest that digital technologies provide a unique opportunity for scalable health interventions in this population, which may mitigate the negative health consequences arising from the many biopsychosocial barriers to in-person care.