Key facets to build up eHealth and mHealth interventions to enhance physical activity, sedentary behavior and nutrition in healthy subjects – an umbrella review

Abstract

Background Electronic (eHealth) and mobile (mHealth) health interventions can provide a large coverage, and are promising tools to change health behavior (i.e. physical activity, sedentary behavior and healthy eating). However, the determinants of intervention effectiveness in primary prevention has not been explored yet. Therefore, the objectives of this umbrella review were to evaluate intervention effectiveness, to explore the impact of pre-defined determinants of effectiveness (i.e. theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions), and to provide recommendations for future research and practice in the field of primary prevention delivered via e/mHealth technology. Methods PubMed, Scopus, Web of Science and the Cochrane Library were searched for systematic reviews and meta-analyses (reviews) published between January 1990 and May 2020. Reviews reporting on e/mHealth behavior change interventions in physical activity, sedentary behavior and/or healthy eating for healthy subjects (i.e. subjects without physical or physiological morbidities which would influence the realization of behaviors targeted by the respective interventions) were included if they also investigated respective theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions. Included studies were ranked concerning their methodological quality and qualitatively synthesized. Results The systematic search revealed 11 systematic reviews and meta-analyses of moderate quality. The majority of original research studies within the reviews found e/mHealth interventions to be effective, but the results showed a high heterogeneity concerning assessment methods and outcomes, making them difficult to compare. Whereas theoretical foundation and behavior change techniques were suggested to be potential positive determinants of effective interventions, the impact of social context remains unclear. None of the reviews included just-in-time adaptive interventions. Conclusion Findings of this umbrella review support the use of e/mHealth to enhance physical activity and healthy eating and reduce sedentary behavior. The general lack of precise reporting and comparison of confounding variables in reviews and original research studies as well as the limited number of reviews for each health behavior constrains the generalization and interpretation of results. Further research is needed on study-level to investigate effects of versatile determinants of e/mHealth efficiency, using a theoretical foundation and additionally explore the impact of social contexts and more sophisticated approaches like just-in-time adaptive interventions. Trial registration The protocol for this umbrella review was a priori registered with PROSPERO: CRD42020147902.

The Tridirectional Relationship among Physical Activity, Stress, and Academic Performance in University Students: A Systematic Review and Meta-Analysis

“…Following the Okanagan Charter for Health Promoting Universities and Colleges [ 69 ], this approach can strengthen student health by forming long term health habits [ 70 ]. There are plenty of opportunities to implement PA habits in university students for example by offering sports courses during the examination period or by providing mobile health interventions, which are promising new tools in the area of primary prevention [ 71 ].…”

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

“…Instead, personalized approaches should focus on responding appropriately to the realities of everyday life and addressing the diversity of modern societies [ 16 ]. Key facets of effective mHealth interventions depict the integration of behavior change techniques (BCTs) [ 17 ] and the foundation upon existing theoretical approaches [ 18 ]. Furthermore, there is empirical evidence that just-in-time interventions [ 19 , 20 ], individualized or tailored interventions [ 21 ], and interventions that incorporate multiple BCTs [ 22 ] show large potential in this respect.…”

Comparison of Self-Reported and Device-Based Measured Physical Activity Using Measures of Stability, Reliability, and Validity in Adults and Children

“…Here, it needs to be stressed that everyone working with PA values (e.g., scientists planning and conducting PA studies, practitioners giving detailed health-related PA advice, and consumers trying to estimate if they are sufficiently active compared to the guidelines) should carefully consider the measurement tool to be suitable for the purpose in question because considerable discrepancies in results can be detected. Furthermore, it is crucial to use standardized reporting to enhance the comparability of the data (e.g., for future meta-analyses) [ 60 ]. Finally, self-reported measures can offer additional contextual information of PA in a timely manner by using e.g., ecological momentary assessments [ 17 , 61 ] to further refine our understanding of PA and may lay the foundation for personalized intervention approaches as with just-in-time adaptive interventions [ 10 ] in the future.…”