What is it about?
This paper explores whether digital health interventions (DHIs; e.g., mobile health apps, web-based programmes) are effective in improving health behaviours and reducing risk of noncommunicable diseases. Specifically, we identify the most promising features and components in DHIs that can unlock behaviour change and be prioritized for future interventions, with the goal of accelerating the advancement of effective digital health for all.
Why is this important?
Noncommunicable diseases (NCDs) such as cardiovascular diseases, cancers, respiratory diseases, and diabetes are the leading causes of death and disability worldwide. The combined health, societal, and economic burden of NCDs and mental disorders is tremendous, therefore tackling NCDs and their risk factors is a major public health challenge.
What makes a digital health intervention effective?
DHIs have become increasingly popular in recent years, offering a convenient and accessible way to promote behaviour change, improve health outcomes, and prevent or treat NCDs. However, not all interventions are created equal. Some are more effective than others, and understanding the key components that contribute to their success is crucial. By understanding and implementing the most effective features and components, DHIs have the potential to make a significant impact on improving people’s lives.
Summary of the research
The aim of this research study was to conduct an umbrella review of the scientific evidence to answer the question; which intervention components used in DHIs are the most effective in changing behaviour and improving health?
We reviewed 85 systematic reviews published between 2007 – 2022, spanning 12 health domains, and including more than 865,000 individuals to find the answer.
What did we find?
DHIs are effective in improving health outcomes for patients with cardiovascular disease, cancer, type 2 diabetes, and asthma. Furthermore, DHIs are effective in improving health-related behaviors, including physical activity, sedentary behavior, diet, weight management, medication adherence, and abstinence from substance use in both general and clinical populations.
Specific intervention components that are effective and should be prioritized for inclusion in future DHIs include:
- using a credible source (e.g. communication with a health care professional)
- social support (e.g. peer support, community connections)
- prompts and cues (e.g. in the form of notifications or nudges)
- graded tasks (e.g. building progress over time)
- self-regulatory techniques ( e.g. goals and planning, feedback and monitoring)
- human coaching (e.g. helping people to overcome ambivalence to change)
- personalization (e.g. data-driven guidance and feedback)
Social Support
Research has consistently shown that social support is associated with better health outcomes and increased engagement in DHIs. DHIs can leverage social support in various ways, such as through online communities, peer-to-peer communication, or virtual health coaching. By providing opportunities for users to connect with others who have similar health goals or challenges, DHIs can create a sense of community and mutual support. This can help users stay motivated, share experiences and tips, and overcome obstacles together – and may even have a positive spill-over effect on others.
Self-regulatory techniques
Self-regulatory behaviour change techniques are evidence-based strategies that aim to promote behavior change and help individuals adopt healthier habits. By incorporating these techniques into DHIs, users are provided with the tools and support they need to make lasting changes in their behavior. For example, setting specific and achievable goals helps users stay motivated and focused, while self-monitoring enables them to track their progress and make adjustments as needed. The combination of these techniques has been shown to significantly improve health outcomes and increase the likelihood of sustained behavior change.
Personalization
People have unique needs and preferences when it comes to their health, and one-size-fits-all approaches often don’t work. Effective interventions take into account individual characteristics, such as age, gender, lifestyle, and health conditions, to tailor the program to each person’s specific needs. Personalization can be achieved through various means, such as adaptive algorithms that adjust the intervention based on user feedback and progress, or the inclusion of interactive features that allow users to customize their experience. By personalizing the intervention, users are more likely to engage with the program and adhere to the recommended behaviors, ultimately leading to better health outcomes.
Conclusion
In conclusion, personalised coaching (from a professional, peer, or digital entity), self-regulatory behavioral change techniques, and social support are key components that contribute to the effectiveness of DHIs. By tailoring the intervention to an individual’s evolving needs, incorporating evidence-based strategies for behavior change, and fostering a sense of community and support, these interventions have the potential to make a significant impact on improving health outcomes. As the field of digital health continues to evolve, understanding and implementing these components will be crucial in developing interventions that truly make a difference in people’s lives.
Read the paper
Jacqueline Louise Mair, PhD, Alicia Salamanca-Sanabria, PhD, Mareike Augsburger, PhD, Bea Franziska Frese, MBA, Stefanie Abend, BA, Robert Jakob, MSc, Tobias Kowatsch, PhD, Severin Haug, PhD
Annals of Behavioral Medicine, Volume 57, Issue 10, October 2023, Pages 817-835, https://doi.org/10.1093/abm/kaad041
Published: 25 August 2023
