Abstract
BackgroundIt is unclear why some physical activity (PA) mobile health (mHealth) interventions successfully promote PA whereas others do not. One possible explanation is the variety in PA mHealth interventions—not only do interventions differ in the selection of persuasive strategies but also the design and implementation of persuasive strategies can vary. However, limited studies have examined the different designs and technical implementations of strategies or explored if they indeed influenced the effectiveness of the intervention.ObjectiveThis scoping review sets out to explore the different technical implementations and design characteristics of common and likely most effective persuasive strategies, namely, goal setting, monitoring, reminders, rewards, sharing, and social comparison. Furthermore, this review aims to explore whether previous mHealth studies examined the influence of the different design characteristics and technical operationalizations of common persuasive strategies on the effectiveness of the intervention to persuade the user to engage in PA.MethodsAn unsystematic snowball and gray literature search was performed to identify the literature that evaluated the persuasive strategies in experimental trials (eg, randomized controlled trial, pre-post test). Studies were included if they targeted adults, if they were (partly) delivered by a mobile system, if they reported PA outcomes, if they used an experimental trial, and when they specifically compared the effect of different designs or implementations of persuasive strategies. The study methods, implementations, and designs of persuasive strategies, and the study results were systematically extracted from the literature by the reviewers.ResultsA total of 29 experimental trials were identified. We found a heterogeneity in how the strategies are being implemented and designed. Moreover, the findings indicated that the implementation and design of the strategy has an influence on the effectiveness of the PA intervention. For instance, the effectiveness of rewarding was shown to vary between types of rewards; rewarding goal achievement seems to be more effective than rewarding each step taken. Furthermore, studies comparing different ways of goal setting suggested that assigning a goal to users might appear to be more effective than letting the user set their own goal, similar to using adaptively tailored goals as opposed to static generic goals. This study further demonstrates that only a few studies have examined the influence of different technical implementations on PA behavior.ConclusionsThe different implementations and designs of persuasive strategies in mHealth interventions should be critically considered when developing such interventions and before drawing conclusions on the effectiveness of the strategy as a whole. Future efforts are needed to examine which implementations and designs are most effective to improve the translation of theory-based persuasive strategies into practical delivery forms.
Highlights
Physical activity (PA) mobile health interventions, such as interventions delivered by wearable technologies, SMS messages, and mobile apps, have potential for supporting physical activity (PA) behavior [1,2,3,4,5]
The effectiveness of rewarding was shown to vary between types of rewards; rewarding goal achievement seems to be more effective than rewarding each step taken
Studies comparing different ways of goal setting suggested that assigning a goal to users might appear to be more effective than letting the user set their own goal, similar to using adaptively tailored goals as opposed to static generic goals
Summary
Physical activity (PA) mobile health (mHealth) interventions, such as interventions delivered by wearable technologies, SMS messages, and mobile apps, have potential for supporting PA behavior [1,2,3,4,5]. Several taxonomies of persuasive strategies have been developed [8,9,10,11,12], including a taxonomy for PA and dietary interventions (ie, the CALO-RE taxonomy [9]) These taxonomies allow for a clear and consistent description of interventions [13], and they have been frequently adopted for designing and evaluating interventions for behavior change [14,15,16,17,18]. It is unclear why some physical activity (PA) mobile health (mHealth) interventions successfully promote PA whereas others do not. Limited studies have examined the different designs and technical implementations of strategies or explored if they influenced the effectiveness of the intervention
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