There is a new study out of the Netherlands, published in the Journal of Medical Internet Research, which examines how fully-automated lifestyle interventions are creating new opportunities for more effective personal health management.
In short, the combination of self-tracking and persuasive eCoaching is a promising modern and accessible methodology. We’re particularly interested in this work because a better understanding of how digital programs can improve health outcomes, and how humans like to interact with them, helps us design better software. We’re also pleased that we’re already using, and refining, many of the most important techniques identified in the study.
The JMIR study asks these two fundamental questions:
1) What are the key components of self-tracking and persuasive eCoaching that affect health outcomes, usability, and adherence to automated healthy lifestyle interventions?
2) How should digital programs and technology be designed to improve health outcomes, usability, and/or adherence?
The study concludes that healthcare apps designed with a focus on the following components saw the greatest positive influence on health outcomes.
· Reduction – training time & information
· Personalization – self-tracking data & interface
· Simulation – health technique & behavior
· Suggestion/Praise – positive encouragement
· Goal-setting – set your objective
· Reminders – daily reminders to users
· Integration – self-tracking & persuasive eCoaching
· Face-to-face instruction – during implementation.
Most important among these were found to be reduction, personalization, simulation, praise, and reminders. However, it’s clear to us that how all of these items are combined into an intuitive program drives the best results, meaning, it’s important to have a healthy mix of these components in any product.
The study also suggests something else that interests us: objective measurements of people’s lifestyle patterns (i.e. data) are usually more reliable than their own estimations, which are based on biased memories and biological sensing. This suggests that more reliable measurements will become an even more essential component in lifestyle behavior change, enabling users to develop a greater awareness of their actual lifestyle, not the one they think they have.