Modifying health behaviors such as physical activity, diet, stress, and mental activity can lower risk for Alzheimer’s disease (AD). Many people in mid-life find it difficult to sustain risk-modifying health behavior changes. As part of a larger intervention development project, qualitative methods were used to develop an explanatory method to convey AD risk and personal health belief factors that may impact adherence to brain health behaviors.

We conducted focus groups to develop a method of communicating 12 known modifiable dementia risk factors (Livingston et al, 2020) and personal health belief concepts identified from the Science of Behavior Change Research Network (future time perspective, considering future consequences, response inhibition, executive control, delay discounting, deferment of gratification and self-efficacy). We presented layperson-friendly descriptions of these concepts, which are important moderators of engagement in brain health-relevant behaviors. We also created images to convey this information. Participants were asked targeted questions about images and their components. Sessions were digitally recorded and transcribed. A framework matrix approach was used to analyze the results; individual participant comments were summarized and preferences and trends across the groups were identified.

We conducted 6 focus groups, (3-6 participants per group; aged 47-69, 73% women, 96% non-Hispanic white; 42% from an AD prevention registry and 58% from the RI community); all participants had at least a high school education with 35% obtaining a bachelor's degree. Participants had strong opinions and reactions to presented information. They responded most favorably to an image conveying AD risk factors color coded by risk magnitude (red, yellow, green). Many participants reflected that an individual's reaction could vary depending on their results. For instance, receiving health risk and health belief information where an individual scored low in many measures might be discouraging rather than motivating for behavior change. Some ways of presenting the information elicited confusion among various participants, and they provided suggestions and alternative language to clearly explain complex health beliefs. Health belief concepts were felt to be relevant to health behavior, with consideration of future consequences most frequently identified as personally relevant. Participants were able to articulate differences between the health belief concepts, though several were conceptually connected (i.e., consideration of future consequences and deferment of gratification; response inhibition and delay discounting). Preferences were incorporated for use in the next phase of the study. Overall, participants expressed enthusiasm and interest in learning about their own personal risk profiles to prevent AD and improve their lifestyles.

Using qualitative data from focus groups, we refined images and developed an explanatory framework for communicating about individual health beliefs important for AD risk modification. We clustered related health belief concepts conceptually as well as by strengths and weaknesses to improve clarity and accurately convey personalized information. We will use qualitative data generated from this phase to develop a personalized health education program and compare it to standard education in a randomized controlled trial. It is anticipated that this enhanced health education program will help mid-life individuals navigate barriers to AD-relevant health behavior change.