# Digital solutions, real-world challenges: lessons from mHealth trials in oncology

## TL;DR

This paper discusses challenges in using mobile health technologies for cancer care and offers practical solutions based on three ongoing studies.

## Contribution

The paper provides new insights and recommendations for designing and implementing mHealth trials in oncology.

## Key findings

- Key challenges in mHealth trials include planning, technology setup, adherence, and data reliability.
- Practical recommendations are proposed to address these challenges in future studies.
- Three ongoing mHealth studies in oncology were analyzed to identify common obstacles.

## Abstract

The use of mobile health (mHealth) technologies in oncology, such as wearable devices and smartphone applications, is gaining momentum due to their potential to improve quality of life, enhance treatment adherence, and positively impact survival outcomes for cancer patients. However, as a relatively new and evolving field, mHealth research faces a set of challenges in both study design and implementation. This article identifies key obstacles by drawing on preliminary experience from three mHealth studies in oncology: the eBladder study, the CHOPIN study, and the LAPSTAR study (ongoing studies at publication date). The topics covered are clustered into four categories: (1) planning and design (e.g., determining appropriate follow-up durations and inclusion criteria, defining digital support as an endpoint, developing response windows for digital questionnaires, establishing active measurement frequency); (2) technology set-up and study execution (e.g., aligning treatment and mHealth schedules, managing treatment heterogeneity and changes, establishing device configuration, scheduling data checks, determining end-of-study visits); (3) adherence (e.g., developing integrated platforms, balancing passive and active measurements, considering treatment goals as motivators, evaluating mHealth literacy); and (4) data reliability (capturing adverse events in real-time, ensuring device accuracy, and privacy considerations). This article also contains some practical recommendations in response to these challenges, meant to inspire researchers who are embarking on future mHealth studies in oncology.

https://onderzoekmetmensen.nl/en, identifiers NL81928.029.22 (eBladder trial), NL69508.058.19 (CHOPIN trial), and NL85622.041.24 (LAPSTAR trial).