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The Effectiveness of Smartphone Apps for Lifestyle Improvement in Noncommunicable Diseases: Systematic Review and Meta-Analyses

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Lunde, Pernille, Nilsson, Birgitta Blakstad, Bergland, Astrid, Kværner, Kari Jorunn, Bye, Asta·2018·Journal of Medical Internet Research
DOI 10.2196/jmir.9751PMC PMC5960039

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Abstract

Background: Noncommunicable diseases (NCDs) account for 70% of all deaths in a year globally. The four main NCDs are cardiovascular diseases, cancers, chronic pulmonary diseases, and diabetes mellitus. Fifty percent of persons with NCD do not adhere to prescribed treatment; in fact, adherence to lifestyle interventions is especially considered as a major challenge. Smartphone apps permit structured monitoring of health parameters, as well as the opportunity to receive feedback. Objective: The aim of this study was to review and assess the effectiveness of app-based interventions, lasting at least 3 months, to promote lifestyle changes in patients with NCDs. Methods: In February 2017, a literature search in five databases (EMBASE, MEDLINE, CINAHL, Academic Research Premier, and Cochrane Reviews and Trials) was conducted. Inclusion criteria was quantitative study designs including randomized and nonrandomized controlled trials that included patients aged 18 years and older diagnosed with any of the four main NCDs. Lifestyle outcomes were physical activity, physical fitness, modification of dietary habits, and quality of life. All included studies were assessed for risk of bias using the Cochrane Collaboration`s risk of bias tool. Meta-analyses were conducted for one of the outcomes (glycated hemoglobin, HbA1c) by using the estimate of effect of mean post treatment with SD or CI. Heterogeneity was tested using the I2 test. All studies included in the meta-analyses were graded. Results: Of the 1588 records examined, 9 met the predefined criteria. Seven studies included diabetes patients only, one study included heart patients only, and another study included both diabetes and heart patients. Statistical significant effect was shown in HbA1c in 5 of 8 studies, as well in body weight in one of 5 studies and in waist circumference in one of 3 studies evaluating these outcomes. Seven of the included studies were included in the meta-analyses and demonstrated significantly overall effect on HbA1c on a short term (3-6 months; P=.02) with low heterogeneity (I2=41%). In the long term (10-12 months), the overall effect on HbA1c was statistical significant (P=.009) and without heterogeneity (I2=0%). The quality of evidence according to Grading of Recommendations Assessment, Development and Evaluation was low for short term and moderate for long term. Conclusions: Our review demonstrated limited research of the use of smartphone apps for NCDs other than diabetes with a follow-up of at least 3 months. For diabetes, the use of apps seems to improve lifestyle factors, especially to decrease HbA1c. More research with long-term follow-up should be performed to assess the effect of smartphone apps for NCDs other than diabetes.

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  • Lack of adherence to behavioral changes is the most significant modifiable factor compromising therapeutic outcomes in diabetes management.

    “The lack of adherence to behavioral changes represents an important challenge in diabetes management, identified as the most significant modifiable factor compromising therapeutic outcomes [20,21].”

    From Evaluation of the Impact of Mobile Health App Vitadio in Patients With Type 2 Diabetes: Randomized Controlled Trial (2025) · cites this paper as [21]

    The Introduction (page not provided in our copy) calls adherence to treatment the most important modifiable factor compromising treatment outcomes and says adherence includes behavioral changes, which are a major challenge in treating noncommunicable diseases. It does not identify lack of adherence to behavioral changes specifically as the most significant factor in diabetes management. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Current literature suggests that user factors such as high levels of engagement with an mHealth app are frequently associated with better outcomes.

    “Current literature suggests that user factors such as a high levels of engagement with an mHealth app are frequently associated with better outcomes and clinicians may be able to support patients by setting goals that are achievable for the individual in a defined time frame with scheduled follow-up.”

    From What is the clinical value of mHealth for patients? (2020) · cites this paper as [43]

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Research works printed but not linked: 1

  1. [24]Cochrane Community 2014 Copenhagen The Nordic Cochrane Centre, The Cochrane Collaboration RevMan 5 http://community.cochrane.org/tools/review-production-tools/revman-5

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Authors
Lunde, P., Nilsson, B. B., Bergland, A., Kværner, K. J., & Bye, A.
Affiliations
  • OsloMet – Oslo Metropolitan University (NO)
  • Oslo University Hospital (NO)
Corresponding author
Lunde, Pernille
ORCID
Venue
Journal of Medical Internet Research
Publisher
JMIR Publications Inc.
Published
2018-05-04
Volume
20
Issue
5
Pages
e162
ISSN
1438-8871 (ISSN-L)
DOI
10.2196/jmir.9751
PMC
PMC5960039
OpenAlex
W2802822747
Cited by
214
References
42
Citations by year
2026: 11 · 2025: 20 · 2024: 22 · 2023: 29 · 2022: 43 · 2021: 34 · 2020: 22 · 2019: 26 · 2018: 6
FWCI
4.01
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
  • NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
Keywords
mobile application, non-communicable diseases, lifestyle intervention, diabetes mellitus, HbA1c, physical activity, dietary habits, quality of life, body weight, waist circumference, cardiovascular disease, chronic lung disease, medication adherence, mobile health, digital health interventions, cardiovascular risk factors, blood pressure, cholesterol, blood glucose monitoring, exercise adherence
MeSH terms
Smartphone, Noncommunicable Diseases, Humans, Life Style, Quality of Life, Mobile Applications

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