Cited by 66Mobile Health and mHealth ApplicationsCancer survivorship and careMobile Learning in Education

Evidence on the Use of Mobile Apps During the Treatment of Breast Cancer: Systematic Review

Open access
Cruz, Flávia Oliveira Almeida Marques, Vilela, Ricardo Alencar, Ferreira, Elaine Barros, Melo, Nilce Santos, Reis, Paula Elaine Diniz Dos·2019·JMIR mHealth and uHealth

Published version of a preprint

Abstract

Background: Cancer is a major cause of morbidity, disability, and mortality worldwide, and breast cancer is the most common cause of death in women. Different modalities of cancer treatment can have adverse effects that reduce the quality of life of patients and lead to treatment interruptions, if not managed properly. The use of mobile technologies has brought innovative possibilities for improving health care. Mobile apps can help individuals manage their own health and well-being and may also promote healthy lifestyles and information access. Objective: The aim of this study was to identify available evidence on the use of mobile apps to provide information and facilitate communication regarding self-care management related to the adverse effects of toxicities owing to breast cancer therapy. Methods: This systematic review includes studies which were identified using a search strategy adapted for each electronic database: CINAHL, Cochrane Library, LILACS, LIVIVO, PubMed, SCOPUS, and Web of Science. In addition, a gray literature search was performed using Google Scholar. All the electronic database searches were conducted on April 17, 2019. Two investigators independently reviewed the titles and abstracts of the studies identified and then read the full text of all selected papers. The quality of the included studies was analyzed by the Cochrane Collaboration Risk of Bias Tool and the Methodological Index for Non-Randomized Studies. Results: A total of 9 studies which met the eligibility criteria—3 randomized clinical trials and 6 nonrandomized studies published in English from 2010 to 2018—were considered for this systematic review; 396 patients with breast cancer, as well as 40 experts in the medical and nursing fields, and 3 software engineers were included. Conclusions: The evidence from the studies included in this systematic review is currently limited but suggests that mobile apps for women with breast cancer might be an acceptable information source that can improve patient well-being; they can also be used to report symptoms and adverse treatment-related effects and promote self-care. There is a need to test more evidence-based apps in future randomized clinical trials.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/13245

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Breast cancer survivors are open to technology-based support.

    “breast cancer survivors are open to technology-based support [27,28].”

    From Co-Designing the MOSAIC mHealth App With Breast Cancer Survivors: User-Centered Design Approach (2024) · cites this paper as [28]

    The Results > Synthesis of Results (page not available) reports that women undergoing chemotherapy found a support app useful and would recommend it to others, supporting openness to technology-based support during treatment. The review says its included studies evaluated apps during breast cancer treatment; it does not establish the same finding for survivors after treatment. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 27 · Cited by 66

Research works printed but not linked: 1

  1. [16]Higgins JP Green S Cochrane Handbook for Systematic Reviews of Interventions. Version 5.1.0 2011 Hoboken, New Jersey Wiley-Blackwell

Authors
Cruz, F. O. A. M., Vilela, R. A., Ferreira, E. B., Melo, N. S., & Reis, P. E. D. D.
Affiliations
Universidade de Brasília (BR)
Venue
JMIR mHealth and uHealth
Published
2019-08-27
Volume
7
Issue
8
Pages
e13245
ISSN
2291-5222 (ISSN-L)
OpenAlex
W2947382798
Cited by
66
References
27
Citations by year
2026: 5 · 2025: 7 · 2024: 15 · 2023: 6 · 2022: 16 · 2021: 11 · 2020: 5 · 2019: 1
FWCI
1.52
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Oncology › Cancer survivorship and care
  • Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
Keywords
mobile health apps, breast cancer, cancer treatment side effects, self-care management, symptom reporting, patient well-being, health information access, patient-provider communication, quality of life
MeSH terms
Breast Neoplasms, Female, Humans, Patient Acceptance of Health Care, Quality of Life, Mobile Applications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review