Customizing wellness programs to patients' lives improves outcomes

Treating chronic diseases such as obesity can involve intensive programs designed to change people’s diet, exercise, and other health behaviors. But a typical program, while packed with information and advice, may overlook a fundamental reality: people’s lives can contain a variety of barriers to behaviors that can improve their health. 

“The assumption is that if people follow these programs, their health will improve,” says Emily Fu, PhD, MPH. “However, when you consider people’s real lives—busy schedules, different environments, mental health, social determinants of health, and life circumstances affect whether they can engage in recommended behaviors. For example, you might recommend that someone walk for 30 minutes a day, but if they live somewhere without sidewalks or where they don’t feel safe walking, that’s not realistic.” 

Fu, a clinical psychologist and first year in the Primary care Investigators Training in Chronic disease & Health disparities (PITCH) Fellowship at the University of Chicago, studies how psychosocial factors and behaviors such as physical activity, sleep, and eating patterns influence long-term health. Key to effectively changing patient behaviors is tailoring interventions to their particular needs and circumstances. Yet while the importance of tailoring treatments is broadly accepted, it is neither a standardized practice nor well-understood. “People often say they’re tailoring interventions, especially in behavioral medicine, but they rarely define what that means,” she notes.

Now, in a paper recently published in Prevention Science, Fu proposes a new way to measure whether health interventions are truly tailored to individuals, and shows that personalization can make a measurable difference in how people engage with treatment. 

Scoring how well programs are tailored

The new framework describes tailoring as a structured process in which providers assess a participant’s health behaviors, mental health, and social circumstances using validated questionnaires and discussions. Providers then work collaboratively with participants to create a plan that addresses the most relevant barriers.

Fu applied her new Observational Assessment Tool for Tailoring (OATT) to data from two trials of the Family Check-Up 4® Health intervention, an adaptation of the internationally-recognized Family Check-Up®, designed to support families to promote positive child outcomes. Families periodically met with a trained FCU4Health coordinator to develop strategies for improving health, and completed multiple surveys about family, parent, and child health behaviors, mental health, and social needs, including at the beginning of the intervention and a year later. 

Using video recordings of feedback sessions with the FCU4Health coordinator and the parent, Fu and collaborators developed an observation-based scoring system to evaluate how well coordinators tailored their recommendations. Coders watched nearly 200 recorded sessions across two trials, examining whether coordinators accurately identified the family’s needs and collaborated with them to develop personalized goals.

The scale ranged from zero to five, with higher scores reflecting stronger tailoring. A mid-range score indicated that the coordinator followed expected practices, while higher scores reflected especially thorough personalization and collaboration. “Good tailoring means the coordinator accurately understands the family’s needs and collaborates with them to develop an appropriate plan,” she explains. “For example, if a parent says mental health is the main barrier and the coordinator connects them to a therapist, that’s good tailoring. If the parent says mental health is the issue but the coordinator focuses only on exercise, that’s poor tailoring.”

Personalized plans make a difference

The results showed that personalizing treatments made a difference. “We found that better tailoring led to higher engagement during the intervention, which in turn predicted improvements in parents’ health behaviors after 12 months,” says Fu. Moreover, she points out that the findings suggest that starting interventions on a strong personal note can help patients invest long-term in following the treatment.

“The tailoring session we analyzed was only the first session,” she says. “Even that initial session predicted later engagement. The key takeaway is the importance of thorough assessments and collaborative prioritization. Even if a program can’t perfectly tailor every element, focusing on participants’ main needs can improve engagement and outcomes.”

The work also addresses a practical challenge in health care: intensive programs can be expensive and difficult to implement widely. By identifying which elements of personalization matter most, Fu hopes future programs can deliver more efficient interventions that still maintain strong patient engagement.

In the future, Fu hopes to adapt OATT into simpler checklists or self-assessment tools that clinicians can use in everyday practice. Ultimately, her research aims to shift the focus of behavioral health interventions away from standardized prescriptions and toward a more collaborative model—one that recognizes that improving health behaviors often starts with understanding the complexities of people’s lives.

“Many health problems seen in primary care have behavioral components,” says Fu. “Clinicians and researchers work very hard to help patients change behaviors–often by adding more and more interventions. I’m interested in creating shorter, efficient, tailored behavioral interventions that fit into that setting.”