Introduction: Why the Fogg Behavior Model matters for health
Behavior change is central to public health, yet turning intentions into sustained healthy actions remains challenging. Among the models designed to guide behavior change, the Fogg Behavior Model (FBM) stands out for its concise, actionable framework: behavior occurs when motivation, ability, and prompts converge in the same moment. This scoping review surveys how the FBM has been applied in health interventions and what we can learn about its effectiveness, feasibility, and equity across contexts.
What the FBM brings to health interventions
The FBM emphasizes three core elements—motivation, ability, and prompts—as a designing lens for health programs. Motivation can be built through anticipation, sensation, and belonging; ability is enhanced by reducing effort, increasing accessibility, and integrating behaviors into routines; prompts trigger action through reminders, calls to action, and environmental cues. Unlike more complex theories, the FBM offers a practical, scalable approach particularly suited to digital health tools and public health programs with broad reach.
Scope of the body of evidence
The scoping review identified six studies (2016–2024) spanning sexual and reproductive health, vaccination, chronic disease management, general wellness, and healthcare adherence. Most research originated in the United States, with additional work from Iran and China. The interventions varied in duration—from a single session to several months—and were delivered in clinical, workplace, or hybrid formats that commonly incorporated digital components such as SMS reminders or mobile apps.
How FBM components were applied
Motivation. Interventions leveraged anticipation (benefits of healthy behavior) and fear or risk framing to motivate change, alongside elements of sensation (positive reinforcement) and sense of belonging (social norms and family support). For example, HPV vaccination and vaginal birth decision interventions used social and culturally tailored messaging to foster engagement.
Ability. Programs reduced cognitive and logistical barriers by offering time flexibility, financial accessibility, simplified information, and routine integration. Some studies provided devices or tech support to ensure equal access, while others broke complex guidance into actionable steps to lower mental effort.
Prompts. Prompts included reminders (texts or messages), calls to action (schedule appointments or set goals), and environmental cues within participants’ social or physical environments. Timely prompts were designed to align with moments of receptivity, such as post-visit reminders or family discussions.
Effectiveness across health domains
Across studies, FBM-informed strategies showed statistically meaningful gains in targeted outcomes: increased intention or uptake of vaginal birth after cesarean, higher HPV vaccine initiation, improved diabetes self-management behaviors, and enhanced parental engagement in child health. Gestational weight management was associated with reductions in gestational diabetes risk, hypertension, and cesarean deliveries in some contexts. However, outcome heterogeneity and small sample sizes limit broad generalizations about long-term impact.
Gaps and limitations
The review highlights several gaps. Notably, most studies report short- to medium-term outcomes with limited long-term follow-up. Sex- and gender-disaggregated analyses were seldom conducted, reducing insight into differential responses by gender. The majority of evidence comes from high-income country settings, raising questions about cultural adaptability in low- and middle-income contexts. A lack of direct comparison with other behavior change models (e.g., COM-B) means we know less about relative advantages or contexts where FBM may be most effective.
Implications for practice and policy
FBM offers a practical blueprint for designing scalable health interventions. For policy and program planners, weaving motivation, ability, and prompts into digital and hybrid interventions can enhance engagement, reduce barriers, and support sustained behavior change. Importantly, future work should prioritize longitudinal follow-ups, gender-aware analyses, equitable access considerations (digital literacy and device availability), and cross-model comparisons to determine where the FBM best complements existing frameworks.
Future directions
Researchers should test FBM-driven interventions in diverse settings, including LMICs, with rigorous designs that enable causal inferences and long-term assessment. Incorporating habit formation principles and evaluating the durability of behavior change after prompts taper off will be critical to determining lasting impact.
