Evidence map›Paper›PMID 41727706›Full record

Trial reportFrontiers in digital health2025

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

Dominique G Stuijt, Igor Radanovic, Vasileios Exadaktylos, Ellen Kapiteijn, Tom van der Hulle, Jorg R Oddens, Erik van Gennep, Lois A Daamen, Marieke A R Bak, M Corrette Ploem and 3 more

Abstract readClinical Trial
In one paragraph

Trial report in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Dominique G StuijtDepartment of Medical Oncology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.
Igor RadanovicCentre for Human Drug Research, Leiden, Netherlands.
Vasileios ExadaktylosCentre for Human Drug Research, Leiden, Netherlands.
Ellen KapiteijnDepartment of Medical Oncology, Leiden University Medical Center, Leiden, Netherlands.
Tom van der HulleDepartment of Medical Oncology, Leiden University Medical Center, Leiden, Netherlands.
Jorg R OddensDepartment of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.
Erik van GennepDepartment of Urology, Leiden University Medical Center, Leiden, Netherlands.
Lois A DaamenDivision of Imaging & Oncology, University Medical Center Utrecht, Utrecht, Netherlands.
Marieke A R BakDepartment of Ethics, Law and Humanities, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
M Corrette PloemDepartment of Ethics, Law and Humanities, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
Martijn G H van OijenDepartment of Medical Oncology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.
Adriaan D Bins *Department of Medical Oncology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.
Jacobus J Bosch *Centre for Human Drug Research, Leiden, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Indexed as

challengesmHealthoncologyremote monitoringsmartphonewearable

Identifiers

PMID41727706
PMCPMC12917771

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.