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research-article

Designing personalised mHealth solutions: : An overview

Published: 01 October 2023 Publication History

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Abstract

Introduction

Mobile health, or mHealth, is based on mobile information and communication technologies and provides solutions for empowering individuals to participate in healthcare. Personalisation techniques have been used to increase user engagement and adherence to interventions delivered as mHealth solutions. This study aims to explore the current state of personalisation in mHealth, including its current trends and implementation.

Materials and Methods

We conducted a review following PRISMA guidelines. Four databases (PubMed, ACM Digital Library, IEEE Xplore, and APA PsycInfo) were searched for studies on mHealth solutions that integrate personalisation. The retrieved papers were assessed for eligibility and useful information regarding integrated personalisation techniques.

Results

Out of the 1,139 retrieved studies, 62 were included in the narrative synthesis.
Research interest in the personalisation of mHealth solutions has increased since 2020. mHealth solutions were mainly applied to endocrine, nutritional, and metabolic diseases; mental, behavioural, or neurodevelopmental diseases; or the promotion of healthy lifestyle behaviours. Its main purposes are to support disease self-management and promote healthy lifestyle behaviours. Mobile applications are the most prevalent technological solution. Although several design models, such as user-centred and patient-centred designs, were used, no specific frameworks or models for personalisation were followed. These solutions rely on behaviour change theories, use gamification or motivational messages, and personalise the content rather than functionality. A broad range of data is used for personalisation purposes. There is a lack of studies assessing the efficacy of these solutions; therefore, further evidence is needed.

Discussion

Personalisation in mHealth has not been well researched. Although several techniques have been integrated, the effects of using a combination of personalisation techniques remain unclear. Although personalisation is considered a persuasive strategy, many mHealth solutions do not employ it.

Conclusions

Open research questions concern guidelines for successful personalisation techniques in mHealth, design frameworks, and comprehensive studies on the effects and interactions among multiple personalisation techniques.

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  • (2024)Analyzing Use Intentions for Health-Diagnostic Chatbots: An Extended Technology Acceptance Model ApproachProceedings of the 2024 The 6th World Symposium on Software Engineering (WSSE)10.1145/3698062.3698093(208-217)Online publication date: 13-Sep-2024
  • (2024)Unlocking the Potential of mHealth for Smoking Cessation: An Expert ViewpointHuman-Centered Design, Operation and Evaluation of Mobile Communications10.1007/978-3-031-60458-4_5(59-79)Online publication date: 29-Jun-2024

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Published In

cover image Journal of Biomedical Informatics
Journal of Biomedical Informatics  Volume 146, Issue C
Oct 2023
168 pages

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Elsevier Science

San Diego, CA, United States

Publication History

Published: 01 October 2023

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  1. Personalisation
  2. mHealth
  3. Design methods
  4. Behavioral change
  5. Review

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View all
  • (2024)Analyzing Use Intentions for Health-Diagnostic Chatbots: An Extended Technology Acceptance Model ApproachProceedings of the 2024 The 6th World Symposium on Software Engineering (WSSE)10.1145/3698062.3698093(208-217)Online publication date: 13-Sep-2024
  • (2024)Unlocking the Potential of mHealth for Smoking Cessation: An Expert ViewpointHuman-Centered Design, Operation and Evaluation of Mobile Communications10.1007/978-3-031-60458-4_5(59-79)Online publication date: 29-Jun-2024

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