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Nudging to move: a scoping review of the use of choice architecture interventions to promote physical activity in the general population.

ABSTRACT: BACKGROUND:Nudges are used to alter lifestyles and thus curb the rise of non-communicable diseases. Physical activity is a core prevention strategy to reduce the burden of non-communicable diseases. This paper aims to (1) give an overview of the scope of interventions using choice architecture techniques to promote physical activity at the population levels and (2) identify research gaps by analysing the different approaches in terms of class and type of intervention used. METHODS:A systematic electronic database search was combined with snowball citation sampling of a starter set of publications to search for studies published through October 2018 reporting interventions to promote physical activity at the population level using choice architecture techniques. The methodology of the Joanna Briggs Institute for Scoping Reviews was applied. RESULTS:In all, 35 publications were included. Most of the interventions used point-of-choice prompts tested at railway stations, shopping malls and airports (N?=?27). Eight studies were online studies. While all studies were aimed at the general population, details, if reported at all, were vague and basic. All studies focused on individual-level lifestyle behaviour. None of the studies attempted to alter population-based lifestyle behaviour. Online and "real-world" approaches were rarely combined. Neither, interventions targeting meso- and macro-level structures nor combinations of individual-level and specific meso- or macro-level interventions were found. CONCLUSION:Nudging is in principle an effective approach to promote physical activity within the general population. However, there are large gaps in research. Available opportunities have not yet been exhausted. Further research is needed that is explicitly based on behavioural insights and covering the full range of nudging approaches, particularly focussing on theoretical developments, practical feasibility tests and scale-up activities.

SUBMITTER: Forberger S

PROVIDER: S-EPMC6724306 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Nudging to move: a scoping review of the use of choice architecture interventions to promote physical activity in the general population.

Forberger S S Reisch L L Kampfmann T T Zeeb H H

The international journal of behavioral nutrition and physical activity 20190903 1

<h4>Background</h4>Nudges are used to alter lifestyles and thus curb the rise of non-communicable diseases. Physical activity is a core prevention strategy to reduce the burden of non-communicable diseases. This paper aims to (1) give an overview of the scope of interventions using choice architecture techniques to promote physical activity at the population levels and (2) identify research gaps by analysing the different approaches in terms of class and type of intervention used.<h4>Methods</h4 ...[more]

PMID: 31481090

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Project description:BackgroundHealth-monitoring smart homes are becoming popular, with experts arguing that 9-to-5 health care services might soon become a thing of the past. However, no review has explored the landscape of smart home technologies that aim to promote physical activity and independent living among a wide range of age groups.ObjectiveThis review aims to map published studies on smart home technologies aimed at promoting physical activity among the general and aging populations to unveil the state of the art, its potential, and the research gaps and opportunities.MethodsArticles were retrieved from 6 databases (PubMed, CINAHL, Scopus, IEEE Xplore, ACM Library, and Web of Science). The criteria for inclusion were that the articles must be user studies that dealt with smart home or Active Assisted Living technologies and physical activity, were written in English, and were published in peer-reviewed journals. In total, 3 researchers independently and collaboratively assessed the eligibility of the retrieved articles and elicited the relevant data and findings using tables and charts.ResultsThis review synthesized 20 articles that met the inclusion criteria, 70% (14/20) of which were conducted between 2018 and 2020. Three-quarters of the studies (15/20, 75%) were conducted in Western countries, with the United States accounting for 25% (5/20). Activities of daily living were the most studied (9/20, 45%), followed by physical activity (6/20, 30%), therapeutic exercise (4/20, 20%), and bodyweight exercise (1/20, 5%). K-nearest neighbor and naïve Bayes classifier were the most used machine learning algorithms for activity recognition, with at least 10% (2/20) of the studies using either algorithm. Ambient and wearable technologies were equally studied (8/20, 40% each), followed by robots (3/20, 15%). Activity recognition was the most common goal of the evaluated smart home technologies, with 55% (11/20) of the studies reporting it, followed by activity monitoring (7/20, 35%). Most studies (8/20, 40%) were conducted in a laboratory setting. Moreover, 25% (5/20) and 10% (2/20) were conducted in a home and hospital setting, respectively. Finally, 75% (15/20) had a positive outcome, 15% (3/20) had a mixed outcome, and 10% (2/20) had an indeterminate outcome.ConclusionsOur results suggest that smart home technologies, especially digital personal assistants, coaches, and robots, are effective in promoting physical activity among the young population. Although only few studies were identified among the older population, smart home technologies hold bright prospects in assisting and aiding older people to age in place and function independently, especially in Western countries, where there are shortages of long-term care workers. Hence, there is a need to do more work (eg, cross-cultural studies and randomized controlled trials) among the growing aging population on the effectiveness and acceptance of smart home technologies that aim to promote physical activity.

Project description:BackgroundFitness devices have spurred the development of apps that aim to motivate users, through interventions, to increase their physical activity (PA). Personalization in the interventions is essential as the target users are diverse with respect to their activity levels, requirements, preferences, and behavior.ObjectiveThis review aimed to (1) identify different kinds of personalization in interventions for promoting PA among any type of user group, (2) identify user models used for providing personalization, and (3) identify gaps in the current literature and suggest future research directions.MethodsA scoping review was undertaken by searching the databases PsycINFO, PubMed, Scopus, and Web of Science. The main inclusion criteria were (1) studies that aimed to promote PA; (2) studies that had personalization, with the intention of promoting PA through technology-based interventions; and (3) studies that described user models for personalization.ResultsThe literature search resulted in 49 eligible studies. Of these, 67% (33/49) studies focused solely on increasing PA, whereas the remaining studies had other objectives, such as maintaining healthy lifestyle (8 studies), weight loss management (6 studies), and rehabilitation (2 studies). The reviewed studies provide personalization in 6 categories: goal recommendation, activity recommendation, fitness partner recommendation, educational content, motivational content, and intervention timing. With respect to the mode of generation, interventions were found to be semiautomated or automatic. Of these, the automatic interventions were either knowledge-based or data-driven or both. User models in the studies were constructed with parameters from 5 categories: PA profile, demographics, medical data, behavior change technique (BCT) parameters, and contextual information. Only 27 of the eligible studies evaluated the interventions for improvement in PA, and 16 of these concluded that the interventions to increase PA are more effective when they are personalized.ConclusionsThis review investigates personalization in the form of recommendations or feedback for increasing PA. On the basis of the review and gaps identified, research directions for improving the efficacy of personalized interventions are proposed. First, data-driven prediction techniques can facilitate effective personalization. Second, use of BCTs in automated interventions, and in combination with PA guidelines, are yet to be explored, and preliminary studies in this direction are promising. Third, systems with automated interventions also need to be suitably adapted to serve specific needs of patients with clinical conditions. Fourth, previous user models focus on single metric evaluations of PA instead of a potentially more effective, holistic, and multidimensional view. Fifth, with the widespread adoption of activity monitoring devices and mobile phones, personalized and dynamic user models can be created using available user data, including users' social profile. Finally, the long-term effects of such interventions as well as the technology medium used for the interventions need to be evaluated rigorously.

Dataset Information

Nudging to move: a scoping review of the use of choice architecture interventions to promote physical activity in the general population.

Publications

Nudging to move: a scoping review of the use of choice architecture interventions to promote physical activity in the general population.

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