Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic...

Area of Science:

• Digital Health
• Behavioral Science
• Systems Engineering

Background:

• Traditional psychological theories are insufficient for optimizing smartphone interventions for physical activity (PA) and sedentary behavior (SB) change.
• Dynamic models from engineering, such as control systems, offer potential for more effective PA and SB interventions.
• The integration of these dynamic models into smartphone-based interventions remains largely unexplored.

Purpose of the Study:

• To systematically review and quantify studies using dynamic models in smartphone-based interventions for PA promotion and SB reduction.
• To describe the characteristics of these interventions, including the dynamic models and psychological theories employed.
• To evaluate the effectiveness of these interventions where possible.

Main Methods:

• A comprehensive literature search was conducted across multiple databases (PubMed, PsycINFO, IEEE Xplore, Cochrane, Scopus) up to May 15, 2019.
• Studies included were randomized controlled trials (RCTs), pilot RCTs, quasi-experimental, and pre-post designs involving adult PA or SB interventions delivered via smartphone.
• Data on general characteristics, dynamic models, theory integration, and behavioral outcomes were narratively synthesized due to study variability.

Main Results:

• Eleven publications representing 8 studies were included, primarily focusing on PA, with 4 also addressing SB.
• Various dynamic models were used, including control systems and behavioral analytic algorithms, often integrated with Social Cognitive Theory.
• Effectiveness varied, with some studies showing significant reductions in SB and increases in light and moderate-to-vigorous PA, while others showed non-significant results.

Conclusions:

• This review highlights a scarcity of smartphone-based interventions integrating dynamic models for PA and SB.
• Despite the limited number of studies, preliminary findings suggest promising effectiveness.
• Further research is essential to fully assess and leverage the potential of dynamic models in mobile health for behavior change.