Literature DB >> 33774008

Personalized mobile technologies for lifestyle behavior change: A systematic review, meta-analysis, and meta-regression.

Huong Ly Tong1, Juan C Quiroz2, A Baki Kocaballi3, Sandrine Chan Moi Fat4, Kim Phuong Dao5, Holly Gehringer6, Clara K Chow7, Liliana Laranjo8.   

Abstract

Given that the one-size-fits-all approach to mobile health interventions have limited effects, a personalized approach might be necessary to promote healthy behaviors and prevent chronic conditions. Our systematic review aims to evaluate the effectiveness of personalized mobile interventions on lifestyle behaviors (i.e., physical activity, diet, smoking and alcohol consumption), and identify the effective key features of such interventions. We included any experimental trials that tested a personalized mobile app or fitness tracker and reported any lifestyle behavior measures. We conducted a narrative synthesis for all studies, and a meta-analysis of randomized controlled trials. Thirty-nine articles describing 31 interventions were included (n = 77,243, 64% women). All interventions personalized content and rarely personalized other features. Source of data included system-captured (12 interventions), user-reported (11 interventions) or both (8 interventions). The meta-analysis showed a moderate positive effect on lifestyle behavior outcomes (standardized difference in means [SDM] 0.663, 95% CI 0.228 to 1.10). A meta-regression model including source of data found that interventions that used system-captured data for personalization were associated with higher effectiveness than those that used user-reported data (SDM 1.48, 95% CI 0.76 to 2.19). In summary, the field is in its infancy, with preliminary evidence of the potential efficacy of personalization in improving lifestyle behaviors. Source of data for personalization might be important in determining intervention effectiveness. To fully exploit the potential of personalization, future high-quality studies should investigate the integration of multiple data from different sources and include personalized features other than content.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Fitness trackers[MeSH]; Health behavior[MeSH]; Mobile applications[MeSH]; Personalization; Tailoring

Year:  2021        PMID: 33774008     DOI: 10.1016/j.ypmed.2021.106532

Source DB:  PubMed          Journal:  Prev Med        ISSN: 0091-7435            Impact factor:   4.018


  10 in total

Review 1.  A Scoping Review of Digital Health Interventions to Promote Healthy Romantic Relationships in Adolescents.

Authors:  Amanda Emerson; Michelle Pickett; Shawana Moore; Patricia J Kelly
Journal:  Prev Sci       Date:  2022-08-17

2.  Tailoring Can Improve Consumers' Hygienic Food-Handling Behavior to Reduce the Transmission Risk of Antimicrobial-Resistant Bacteria through Food.

Authors:  Claudia Freivogel; Sarah H Lehmann; Vivianne H M Visschers
Journal:  Eur J Investig Health Psychol Educ       Date:  2022-02-01

Review 3.  Personalization of Intervention Timing for Physical Activity: Scoping Review.

Authors:  Saurabh Chaudhari; Suparna Ghanvatkar; Atreyi Kankanhalli
Journal:  JMIR Mhealth Uhealth       Date:  2022-02-28       Impact factor: 4.947

Review 4.  The Use of Mobile Apps for Heart Failure Self-management: Systematic Review of Experimental and Qualitative Studies.

Authors:  Clara Chow; Liliana Laranjo; Leticia Bezerra Giordan; Huong Ly Tong; John J Atherton; Rimante Ronto; Josephine Chau; David Kaye; Tim Shaw
Journal:  JMIR Cardio       Date:  2022-03-31

Review 5.  mHealth Interventions to Reduce Physical Inactivity and Sedentary Behavior in Children and Adolescents: Systematic Review and Meta-analysis of Randomized Controlled Trials.

Authors:  Hannes Baumann; Kathrin Wunsch; Alexander Woll; Bettina Wollesen; Janis Fiedler
Journal:  JMIR Mhealth Uhealth       Date:  2022-05-11       Impact factor: 4.947

6.  Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach.

Authors:  Sofia Balula Dias; Yannis Oikonomidis; José Alves Diniz; Fátima Baptista; Filomena Carnide; Alex Bensenousi; José María Botana; Dorothea Tsatsou; Kiriakos Stefanidis; Lazaros Gymnopoulos; Kosmas Dimitropoulos; Petros Daras; Anagnostis Argiriou; Konstantinos Rouskas; Saskia Wilson-Barnes; Kathryn Hart; Neil Merry; Duncan Russell; Jelizaveta Konstantinova; Elena Lalama; Andreas Pfeiffer; Anna Kokkinopoulou; Maria Hassapidou; Ioannis Pagkalos; Elena Patra; Roselien Buys; Véronique Cornelissen; Ana Batista; Stefano Cobello; Elena Milli; Chiara Vagnozzi; Sheree Bryant; Simon Maas; Pedro Bacelar; Saverio Gravina; Jovana Vlaskalin; Boris Brkic; Gonçalo Telo; Eugenio Mantovani; Olga Gkotsopoulou; Dimitrios Iakovakis; Stelios Hadjidimitriou; Vasileios Charisis; Leontios J Hadjileontiadis
Journal:  Front Nutr       Date:  2022-07-01

7.  Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA).

Authors:  Sarah Martine Edney; Su Hyun Park; Linda Tan; Xin Hui Chua; Borame Sue Lee Dickens; Salome A Rebello; Nick Petrunoff; Andre Matthias Müller; Cheun Seng Tan; Falk Müller-Riemenschneider; Rob M van Dam
Journal:  Digit Health       Date:  2022-06-30

8.  A personalized mobile app for physical activity: An experimental mixed-methods study.

Authors:  Huong Ly Tong; Juan C Quiroz; Ahmet Baki Kocaballi; Kiran Ijaz; Enrico Coiera; Clara K Chow; Liliana Laranjo
Journal:  Digit Health       Date:  2022-07-21

9.  What Are We Measuring When We Evaluate Digital Interventions for Improving Lifestyle? A Scoping Meta-Review.

Authors:  Rodolfo Castro; Marcelo Ribeiro-Alves; Cátia Oliveira; Carmen Phang Romero; Hugo Perazzo; Mario Simjanoski; Flavio Kapciznki; Vicent Balanzá-Martínez; Raquel B De Boni
Journal:  Front Public Health       Date:  2022-01-03

Review 10.  Continuous Glucose Monitoring in Healthy Adults-Possible Applications in Health Care, Wellness, and Sports.

Authors:  Roman Holzer; Wilhelm Bloch; Christian Brinkmann
Journal:  Sensors (Basel)       Date:  2022-03-05       Impact factor: 3.576

  10 in total

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