Literature DB >> 32387700

A systematic review of nudge theories and strategies used to influence adult health behaviour and outcome in diabetes management.

Y H Kwan1, T Y Cheng2, S Yoon3, L Y C Ho4, C W Huang5, E H Chew2, J Thumboo6, T Østbye7, L L Low8.   

Abstract

BACKGROUND: Diabetes is a chronic disease associated with a variety of complications, and nudging may be a potential solution to improve diabetes control. Since nudging is a new concept, no review of literature on nudging diabetic patients into improving their health behaviour has been done. Therefore, we aim to collate a list of nudge intervention and determine the context in which nudging is successful.
METHODS: We adopted a two-arm search strategy comprising the search of literature databases and snowballing using relevant search terms. We summarized patient characteristics, the nudge intervention, according to nudging strategies, delivery mode and their outcomes. The conditions present in effective nudge interventions were assessed and reported.
RESULTS: We retrieved 11,494 studies from our searches and included 33. An additional five studies were added through snowballing. Studies included utilized framing (n=5), reminders (n=10), gamification (n=2), social modelling (n=5) and social influence (n=16). Studies on reminders and gamification were more likely to have a statistically significant outcome. The targeted health behaviours identified were medication adherence, physical activity, diet, blood glucose monitoring, foot care, self-efficacy, HbA1c and quality of life. Of these, studies with adherence to medication, foot care practice and quality of life as targeted health behaviours were more likely to show a statistically significant outcome.
CONCLUSION: Nudging has shown potential in changing health behaviour of patients with diabetes in specific context. We identified two possible factors (delivery mode and patient characteristics) that may affect the effectiveness of nudge intervention.
Copyright © 2020 The Author(s). Published by Elsevier Masson SAS.. All rights reserved.

Entities:  

Keywords:  Choice architecture; Diabetes; Framing; Gamification; Nudge; Reminders; Social influence; Social modelling

Year:  2020        PMID: 32387700     DOI: 10.1016/j.diabet.2020.04.002

Source DB:  PubMed          Journal:  Diabetes Metab        ISSN: 1262-3636            Impact factor:   6.041


  6 in total

1.  Pharmacoadherence: An Opportunity for Digital Health to Inform the Third Dimension of Pharmacotherapy for Diabetes.

Authors:  David C Klonoff; Jennifer Y Zhang; Trisha Shang; Chhavi Mehta; David Kerr
Journal:  J Diabetes Sci Technol       Date:  2020-12-08

2.  A Nudge-Inspired AI-Driven Health Platform for Self-Management of Diabetes.

Authors:  Shane Joachim; Abdur Rahim Mohammad Forkan; Prem Prakash Jayaraman; Ahsan Morshed; Nilmini Wickramasinghe
Journal:  Sensors (Basel)       Date:  2022-06-19       Impact factor: 3.847

3.  Healthcare Professionals' Views of Factors Influencing Diabetes Self-Management and the Utility of a mHealth Application and Its Features to Support Self-Care.

Authors:  Sungwon Yoon; Jun Hao Ng; Yu Heng Kwan; Lian Leng Low
Journal:  Front Endocrinol (Lausanne)       Date:  2022-02-24       Impact factor: 5.555

4.  Types of health-related procrastination in patients with type-2 diabetes: a qualitative content analysis.

Authors:  Habib Shareinia; Shahrzad Ghiyasvandian; Zahra Rooddehghan; Alireza Esteghamati
Journal:  J Diabetes Metab Disord       Date:  2022-09-16

5.  Promoting the adoption of local governmental policy on the reimbursement of chronic disease medicines (PAPMed): study protocol of a field-based cluster randomized trial in rural Nantong, China.

Authors:  Zhengting He; Xin Cao; Duan Zhao; Zemin Tang; Jiayu Zhao; Mariel Beasley; Angela Renne; Lei Liu; Shengjie Zhu; Yuexia Gao; Lijing L Yan
Journal:  Trials       Date:  2022-09-15       Impact factor: 2.728

6.  Association between Grit Scales and adherence to regular hospital visits among Japanese patients with type 2 diabetes: Prospective observational study.

Authors:  Shuhei Nakanishi; Masashi Shimoda; Fuminori Tatsumi; Kenji Kohara; Atsushi Obata; Junpei Sanada; Yoshiro Fushimi; Tomoatsu Mune; Kohei Kaku; Hideaki Kaneto
Journal:  J Diabetes Investig       Date:  2021-06-19       Impact factor: 4.232

  6 in total

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