Falling Off Track with Health Goals? Science Points to a Better Way
Researchers are using wearable technology to bring a more personalized approach to nutrition and health. By integrating tools like activity trackers and mobile apps into their studies, they are developing strategies that adapt to individual behaviors, helping make health guidance more responsive to real life.
People don’t all use health apps the same way—and that may matter for weight loss.
A recent study published in Digital Health, led by doctoral trainee JM Power under the mentorship of UNC Nutrition Research Institute’s Interim Director, Deborah Tate, PhD, followed 363 adults enrolled in a digital weight management program delivered through primary care over one year. The research offers a closer look at how patients engage with digital tools in real-world clinical settings.
Researchers found that participants tended to engage in four different ways: some never used the program, some started out active but tapered off, some engaged early and then declined, and a smaller group stayed consistently engaged throughout the year.
The key findings: Participants who stayed consistently engaged lost the most weight overall. However, individuals who engaged early—even if their use later dropped—lost more weight than those who used the program very little or not at all.
Why do these patterns matter?
Because engagement is not just about logging into an app—it is closely tied to outcomes. But the takeaway is not simply “stay engaged.” It is that engagement itself is dynamic and personal.
This is where personalized recommendations come in.
Rather than designing one-size-fits-all interventions, this research points toward a more tailored approach: understanding how individuals engage, when they are most likely to struggle, and what support they need at different points in a program is key—especially in primary care settings, where patients are balancing competing health priorities and limited time.
For example, someone who tends to disengage after a few weeks may benefit from early reinforcement or adaptive coaching. Another person who cycles in and out may need flexible, intelligent tools that allow them to re-engage without starting over completely.
By identifying these patterns, researchers can begin to design interventions that respond to real human behavior, which often fluctuates and is rarely perfectly consistent.
“At the NRI, we are working to understand not just what people should eat to improve their health, but how they are able to follow those recommendations over time and what help they may need,” said Tate. “This research shows that engagement doesn’t follow the same pattern for everyone, even among people who are initially motivated to improve their health. And when we reliably recognize and predict those patterns, we can design more personalized, effective strategies that help people become healthier.”
The takeaway is not simply “use digital programs or apps more.” It is that different people engage in different ways and have different needs—and digital programs may be more effective when they adapt to those patterns.
Power JM, Hurley L, O’Shea NG, Nezami BT, Sciamanna C, Tate DF. Examining latent trajectories of participant engagement in a 12-month eHealth weight management intervention. Digit Health. 2026 Mar 20;12:20552076261434062. doi: 10.1177/20552076261434062. PMID: 41883553; PMCID: PMC13009811.