AbstractBackgroundIn the United States alone, more than six million individuals are living with Alzheimer’s disease and related dementias (ADRDs), with minority groups disproportionately impacted. An estimated one‐third of ADRD cases is associated with eight modifiable risk factors: physical inactivity, smoking, depression, low education, diabetes, midlife obesity, midlife hypertension, and hearing loss. With the ADRD pandemic fast approaching, there is greater urgency to identify and adopt risk reduction behavior changes. Lifestyle interventions have shown efficacy in reducing risk for ADRDs and delaying the onset of symptoms. These interventions are often grounded in traditional theories of health behavior change; however, few intervention frameworks exist that combine constructs from multiple discrete theories, or incorporate concept of stigma, a powerful influence in setting the foundation of risk reduction behavior change.MethodsA review of the literature identified health behavior models from which risk reduction interventions are developed. Insights from these studies informed the development of a new framework to inform ADRD risk reduction interventions. This new framework seeks to leverage constructs from the Social Ecological Model (SEM), Health Belief Model (HBM), Transtheoretical Model (TTM), and the Health Stigma and Discrimination Framework (HSDF) to better inform and understand the factors that influence ADRD risk reduction behaviors.ResultThis framework contains several concepts that predict why individuals will take action to reduce risk of ADRDs: individual factors, social‐environmental factors, self and public stigma, and perceptions. Our model also includes stages of change to integrate processes and principles of change, offering a temporal dimension for understanding behavior change. This novel framework can be utilized to inform both individual and community‐level interventions.ConclusionThis new framework provides an innovative and alternative foundation for new ADRD risk reduction interventions. Applicable across a range of risk reduction behaviors, the model highlights the domains and pathways common across ADRD research and intervention implementation. This crosscutting approach will support a more efficient and effective response to addressing preventable risk factors for ADRDs, with the goal of application and realization. Further research is needed to assess the strengths and limitations of this framework in real‐world settings.
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