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Y. Wang1, D. Ren1, J.S. Roberts2, L.K. Tamres1, J.H. Lingler1


1. University of Pittsburgh, School of Nursing, USA; 2. University of Michigan, School of Public Health, USA

Corresponding Author: J.H. Lingler, University of Pittsburgh, School of Nursing, USA,

J Prev Alz Dis 2024;
Published online March 6, 2024,



BACKGROUND: Growing evidence supports the clinical utility of amyloid PET, however, whether patients at risk for dementia use knowledge of their brain amyloid status to alter their health behaviors remains unclear.
OBJECTIVES: To explore the effect of amyloid PET results disclosure on self-reported health behaviors in patients with mild cognitive impairment.
DESIGN: Self-reported health behaviors were a secondary outcome of the Return of Amyloid Imaging Scan Results (RAISR) randomized clinical trial of amyloid PET results disclosure for individuals with mild cognitive impairment.
SETTING: Academic medical center.
PARTICIPANTS: RAISR study participants included 82 patients with mild cognitive impairment who were 92% non-Hispanic white, 59% male, and, on average, 73 ± 8.61 years old with 16.25 ± 2.49 years of education.
INTERVENTION: Participants were assigned to a scan group with the opportunity to have an amyloid PET scan and learn their results or to a control group consisting only of a mild cognitive impairment education session and no opportunity for an amyloid PET scan.
MEASUREMENTS: A 14-item health behavior questionnaire supplemented with qualitative data from the open-ended text entries to describe “other” health behaviors and follow-up semi-structured interviews. Baseline assessments were conducted prior to group assignment. For the present analysis, 71 participants had available data and scan group participants were divided by amyloid status, creating three groups for comparison: amyloid positive, amyloid negative, and control (no scan).
RESULTS: Over 12 months of follow-up, no significant differences were observed in lifestyle, vitamin/supplement use, stress reduction activities, cognitive stimulation, or advance directive completion. Amyloid-negative participants were less likely than controls to consider long-term care insurance (63.6% vs. 89.2%; P = .025), and to endorse behaviors classified as “other” (36.4% vs. 64.9%; P = 0.037). After adjusting for education level, gender, and Mini-Mental State Exam score, logistic regression showed that amyloid-negative patients were 74% less likely than controls to report “other” behaviors (OR = 0.26, 95% CI [0.08, 0.85], P = 0.025), and 78% less likely to consider long-term care insurance (OR= 0.22, 95% CI [0.06, 0.86], P = 0.03). Qualitative analysis of open-ended questionnaire data and supplemental interviews with scan group participants revealed “other” activities to include changes in areas like employment, driving, and residential status, and engagement in other non-medical activities (e.g., pursuing bucket lists).
CONCLUSIONS: This exploratory analysis of health-related behavior changes following amyloid PET disclosure suggests that the value of knowing one’s brain amyloid status may differ by scan result and encompass actions that focus more on maximizing quality of life than promoting cognitive health.

Key words: Mild cognitive impairment, amyloid imaging, results disclosure, behavior response, value of knowing.



A diagnosis of mild cognitive impairment (MCI) confers a high 5-year risk for progression to dementia and is widely viewed as an intermediate state between normal cognitive aging and dementia (1-5). As a potential clinical precursor to dementia, MCI represents a critical window of opportunity to employ secondary preventive strategies for dementia, introduce interventions to promote cognitive health more generally, and offer counseling and support services for those affected (1, 6). Health-related activities that may be undertaken following an MCI diagnosis span a range of behaviors including, lifestyle changes, cognitive stimulation, and the conduct of advance planning. Although only symptom modifying agents were available at the time this research was completed, most recently, the U.S. Food and Drug Administration has granted approval to two anti-amyloid monoclonal therapies, aducanumab and lecanemab, both of which carry appropriate use recommendations for persons with MCI who are amyloid positive upon biomarker testing (7, 8).
Despite robust evidence supporting the prognostic utility of fluid and imaging biomarker tests of Alzheimer’s disease (AD) pathology for persons with MCI (9, 10), uptake in clinical practice has been constrained by numerous factors including limited access to dementia care specialists who order such testing, inconsistencies in insurance coverage, especially for amyloid positron emission tomography (PET), and clinicians’ concerns about the unintended social, legal and psychological consequences of documenting and disclosing an individual’s brain amyloid status (11, 12).
Efforts to quantify the frequency and extent of such risks have been underway for nearly a decade and are increasingly referred to in working groups like AGREEDementia (13) as “disclosure science.” While a published definition of disclosure science is lacking, the phrase may be understood as the systematic investigation of the psychological, behavioral, social, and legal implications of learning the results of one’s own or a family member’s biomarker testing for AD or related disorders.
A growing body of studies in the emerging field of disclosure science has demonstrated the psychological safety of disclosing AD biomarker results (14, 15), and a handful of studies have found that both cognitively healthy older adults and patients with MCI can comprehend the purpose, results and limitations of amyloid PET scans when disclosed in research settings (16-18). Complementing this line of research, qualitative analyses from both cognitively unimpaired and symptomatic samples suggest that individuals and their family members or study partners find inherent value in opportunities to learn the results of a research participant’s brain amyloid scan (19-20). Building on these reports, we sought to determine whether and in what ways knowledge of one’s brain amyloid status influences subsequent health behaviors, broadly defined, among cognitively symptomatic individuals.




This analysis involved patients with MCI from the Return of Amyloid PET Scan Results (RAISR) Study (; NCT03121118). RAISR is a randomized controlled trial investigating the effect of receiving amyloid PET scan results on understanding, and perceived self-efficacy to cope with MCI (21). Secondary outcomes included behavioral responses (health management behaviors, change of will, and insurance purchase) to amyloid PET results disclosure. The RAISR study rationale, design, and main results are described elsewhere (21). The objective of this secondary outcomes analysis is to describe the frequency and nature of MCI-related health behavior changes implemented after the receipt of amyloid PET scan results. We limit our definition of health behavior changes to those that were newly adopted by the patient for the explicit purpose of promoting cognitive health or planning ahead, above and beyond any medication changes instituted by providers.

Setting and Sample

RAISR participants were recruited from the University of Pittsburgh Alzheimer Disease Research Center (ADRC). Participants had been diagnosed with MCI for an average of 29.6 months (S.D. = 38.3) at the time of enrollment into RAISR. We included patients with consensus-based diagnoses of all subtypes of MCI and excluded patients with prior biomarker-derived knowledge of their risk for AD and those with active untreated mood disorders. Eligible participants (n = 82) were allocated in a 1:1 ratio to a scan group or control group. Scan group participants received pre-test counseling for amyloid PET and the option to proceed with undergoing an amyloid PET scan (22). Participants in the control group received an MCI education session and did not have the option of amyloid PET. Descriptions of the RAISR protocols for MCI education (control group) and pre-testing counseling (scan group), amyloid PET results disclosure, and adverse event monitoring have been previously reported (21-23). Briefly, both the MCI education session and pre-test counseling included general overviews of lifestyle measures and other non-pharmacologic strategies to promote cognitive health. The current analysis focuses on 71 participants with complete health behavior assessment data at each time point.


A 14-item health behavior checklist was administered at baseline (pre-randomization) and at six- and twelve-months post-disclosure (scan group) or MCI education session (controls) (24). At baseline participants were instructed to indicate whether (yes/no) they were performing any of 8 activities on the checklist in order to prevent worsening of their memory or thinking problems and whether they had any of 5 types of legal and medical planning documents in place. An option to endorse performing “other” activities was provided and research staff recorded participants’ open-ended descriptions of such activities during administration of the assessment. At follow-up, participants were instructed to indicate whether, since baseline, they had made changes in their performance of each checklist activity. Reminders of previously endorsed items were provided and participants were asked to verify whether they were still engaging in each behavior or not. As part of the RAISR protocol, follow-up assessments for the Amyloid PET participants also included audio-recorded qualitative interviews during which participants were invited to describe how learning their brain amyloid status has impacted their lives. To enhance the current analysis, responses detailing changes in health-related activities were pulled from those interviews, supplementing health behavior checklist data.
This study employed an explanatory sequential mixed methods approach (25) to enrich our description of the impact of learning one’s brain amyloid status on participant behaviors. Initially, we conducted statistical analyses to quantify the influence of brain amyloid status on participant behaviors. Subsequently, qualitative analysis was employed to elucidate behavioral changes and to understand how knowledge of one’s scan results shapes their adoption.

Statistical Analysis

Scan group participants were divided by scan result (amyloid positive or negative) for the purpose of the current analysis. Descriptive statistics were conducted to characterize the overall sample and each subgroup (amyloid positive, amyloid negative, and control group). Demographic differences by group were examined using one-way ANOVA and chi-square tests (Table 1). Responses to health-related behavior questions at each time point were analyzed with descriptive and inferential statistics (Table 2 and 3). The percentage of patients within each of the three follow-up groups was calculated and the differences in the percentage endorsing each behavior were compared using chi-square tests. Multivariable logistic regression analyses were conducted to predict health-related behaviors at follow-up adjusting for age, years of education, sex, and Mini-Mental State Exam (MMSE) (26) scores (Table 2 and 3). All statistical analyses were conducted using SAS version 9.4 (SAS Institute). Significance level is set at 0.05.

Table 1. Demographic characteristics by randomization and amyloid status (n=71)

Note: Eleven of the 82 enrolled participants were excluded from the analysis due to dropping out prior to scan result disclosure or missing data health behavior questionnaire data.


Qualitative analysis

Qualitative methods were applied to analyze open-ended text descriptions of “other” health-related behaviors as endorsed on the health behavior checklist by participants in all three subgroups. For scan group participants, these data were supplemented by qualitative interview transcripts from follow-up visits. The standard qualitative approach of content analysis was performed using NVivo qualitative analysis software, version 12 (27). First, three trained researchers from the team conducted a preliminary analysis to develop the coding structure. Second, the first author (YW) reviewed interview transcripts and questionnaires to create initial codes for “other” behaviors as described in the open text field for this item in REDCap. A senior researcher (JL) reviewed and revised the codes. In an iterative process, the codes were sorted into subcategories based on similarities and combined into overarching categories based on content. The same coding system was applied to analyze supplemental data on health-related behavior changes as described in qualitative interviews conducted with scan group dyads at follow-up visits. During analysis, coders met regularly to discuss and find consensus in instances of uncertainty or discrepancy.



Sample Characteristics

The patients’ basic characteristics are outlined in Table 1. No significant differences were observed by age, years of education, race, sex, or MMSE.

Behaviors for dementia prevention

Most patients endorsed performing at least one behavior specific to brain health at baseline and across T2, T3, and T4 (Table 2). On average, patients with positive amyloid PET scans endorsed 4.67 behaviors and patients with negative amyloid PET scans endorsed 3.72, a difference that was not statistically significant. No statistically significant differences were observed across the three groups, at follow-up, in performing behaviors related to diet, physical activity, medication, vitamins, herbal supplements, activities to reduce stress, and mental activities. Amyloid-negative patients endorsed significantly fewer “other” behaviors than those in the control group (P = 0.037). Amyloid-negative patients also reported fewer “other” behaviors than those in the amyloid-positive group, though this trend did not reach statistical significance (36.4% vs. 66.7%; P = 0.097). After adjusting for age years of education, sex, and MMSE, logistic regression showed that amyloid-negative patients were 74.4% with 95% confidence (0.077, 0.846) less likely to endorse “other” behaviors at follow-up than those in the control group (P = 0.025).

Table 2. Endorsement of health behavior assessment items

Note: Eleven of the 82 enrolled participants were excluded from the analysis due to dropping out prior to scan result disclosure or missing data health behavior questionnaire data. Statistical comparisons focused on between-group differences at follow-up. Follow-up health behavior was defined as endorsement at one or more of time points T2 (Week 4), T3 (Week 24), or T4 (Week 52). *Amyloid negative vs. comparison group, P=0.037. Abbreviation: AD: Alzheimer’s Disease


Given the relatively high levels of brain health behaviors performed at baseline, we extended this analysis conducting a longitudinal examination with post-disclosure health behavior as the dependent variable at three time points (4 weeks, 24 weeks, and 52 weeks). Baseline health behavior served as the independent variable, while controlling for covariates such as age, sex, education, scan result disclosure group (scan positive, scan negative, and comparison group), and time. Given the binary nature of health behavior change (Yes vs. No), we employed the Generalized Estimating Equation (GEE) model. Our analysis revealed that there was no significant interaction between baseline health behavior and group. However, we did find a statistically significant association between baseline health behavior and post-disclosure health behavior performance [Adjusted Odds Ratio (OR) = 4.64, 95% Confidence Interval (CI): 1.00, 21.5; p = 0.0497]. This suggests that individuals who had exhibited a health behavior change at baseline were substantially more likely to continue this behavior during post-disclosure follow-ups, irrespective of their group, including amyloid status.

Future Planning Behaviors

Our analysis of changes in the execution of a last will, living will, power attorney for health care and finances, and purchase of long-term care insurance found no significant differences by the group. However, statistically significant differences in changes regarding considering (not purchase of) long-term care insurance were observed across the 3 groups (Table 3). Significantly more patients from the control group considered purchasing long-term care insurance than amyloid negative patients (P = 0.025). More amyloid positive patients considered long-term care insurance than those in the negative group, but this trend did not reach statistical significance (P = 0.1). After adjusting for age years of education, sex, and MMSE, logistic regression showed that amyloid negative patients were 78.2% less likely [OR = 0.055; 95% CI (0.055, 0.863); P=0.03] to consider long-term care insurance than those in the control group.

Table 3. Future Planning by Study Group

Note: Eleven of the 82 enrolled participants were excluded from the analysis due to dropping out prior to scan result disclosure or missing data health behavior questionnaire data. Frequencies reflect endorsement of future planning behavior at any time point. *Scanned negative vs. comparison group, P=0.025.


Qualitative description of “other” behavior changes

To understand the nature of “other” changes in behavior, we analyzed open-ended responses to the health behavior questionnaire item “other” as well as transcripts of audio-recorded interviews with patient and caregiver participants. Other behavior changes fell into the following categories: driving, employment, financial planning, residential status, alcohol moderation, management of medical comorbidities, and other non-medical activities (pursuit of social, leisure and bucket list activities, and mending strained personal relationships). Example quotes for each category from the three groups are listed in Table 4. Changes in the categories of driving, employment, alcohol moderation, and self-management of comorbid medical conditions were qualitatively similar across the three subgroups of participants and consistently reflected an orientation toward promoting either safety or cognitive health. Scrutiny of the examples provided in the remaining categories of behavior change (i.e., financial planning, residential status, and other non-medical activities) suggest that perceptions of time remaining in relative cognitive health may influence individuals’ priorities for the use of resources following amyloid PET results disclosure. This phenomenon is exemplified in the phrasing “I’ve got time,” by an amyloid negative participant discussing plans to refrain from spending down investment income, and mention of a desire to “get it all in” by an amyloid positive participant discussing travel pursuits. Similarly, an amyloid-negative dyad who was considering relocation to a long-term care setting described pausing such plans, stating “all of that has changed” in light of what was perceived as favorable amyloid imaging results.

Table 4. Example quotes from participants and their caregivers from amyloid positive, negative, and control groups



Building on a growing literature describing psychological responses to and subjective perceptions of AD biomarker disclosure (14-15), the current analysis sought to quantify the extent to which learning one’s brain amyloid status influences behavior. We found that regardless of scan result, all participants with MCI reported changing at least one health-related behavior in the 12-month period following the return of amyloid PET results. Our between-group comparisons of post-disclosure performance of cognitive health-related behaviors revealed no significant differences. Additionally, the mean number of total changes implemented (4.13±1.86), while highest in the amyloid positive group, did not differ statistically differ across the three groups (amyloid positive, amyloid negative and control). Post-hoc analysis revealed that baseline performance of cognitive health behaviors was a strong driver of such behaviors over the twelve-month follow-up period.
Our findings have implications for both amyloid-positive and amyloid-negative individuals as MCI represents a heightened risk state for dementia regardless of etiology. The health behavior questionnaire employed in this study includes items consistent with guidelines for the secondary prevention of dementia (1). Even as disease-modifying therapies for AD become available, comprehensive approaches to dementia prevention and management will continue to include non-pharmacologic measures including those targeting lifestyle factors like physical activity and diet (28). This applies to patients with MCI due to both AD and non-AD pathologies, and is particularly relevant to those who may have a vascular contribution to their clinical presentation. In RAISR, disclosing clinicians informed participants with non-elevated amyloid levels that their results “…suggest that Alzheimer’s disease (AD) may not be the underlying cause of the changes in memory or thinking that you are experiencing. Keep in mind that there are other causes of memory decline and changes in thinking besides AD (for example, stroke and Parkinson’s disease).” Participants were further advised that amyloid PET scans do not provide information about these non-Alzheimer’s types of dementia and offered general recommendations about activities to promote cognitive health.
Published reports of patient-initiated changes in health behaviors following amyloid PET disclosure are limited and focus almost exclusively on cognitively unimpaired individuals. For example, a survey of anticipated reactions to AD biomarker disclosure among cognitively unimpaired research volunteers found over 80% of respondents to endorse informing lifestyle changes, like diet and exercise, to be a “very” or “extremely” important reason to learn one’s results (29). In that study, arranging personal, legal and financial affairs was also endorsed as a strong motivator for learning one’s AD biomarker status by the majority of participants surveyed regarding the hypothetical option of learning such results. Another team conducted a qualitative analysis of reactions described by cognitively unimpaired older adults who learned their brain amyloid status as candidates for an anti-amyloid clinical trial (30). They found that more amyloid positive clinical trial candidates reported both contemplating and making changes to health behaviors and plans, than those who were amyloid negative. These findings are consistent with seminal research on APO-E genotype disclosure, as conducted in the Risk Evaluation and Education for Alzheimer’s Disease (REVEAL) Study. The REVEAL team has reported that asymptomatic offspring of dementia patients who learned of carrying the APOE 4 allele were more likely to pursue one or more health behavior changes relative to noncarriers and controls (24) and were nearly 6 times more likely than controls to alter their long-term care insurance status (31).
While there is reason to positively view our finding that amyloid-negative patients were just as likely as other participants to pursue most activities on the health behavior questionnaire, our findings that amyloid-negative individuals were 74% less likely to make “other” health-related behavior changes and 78% less likely to consider long-term care insurance warrant further investigation. These results raise the possibility of a misconception that ruling out AD pathology necessarily suggests a more favorable prognosis.
Our qualitative examination of the “other” behaviors implemented by RAISR participants post-disclosure points to the need for a broad definition of the value of knowing one’s AD biomarker status and importance of recognizing that the value of knowing may differ based on biomarker result type. Acknowledging the multidimensional value of learning one’s brain amyloid status is especially important as the field enters an era where the chief indication of AD biomarker testing will be to determine eligibility for anti-amyloid agents (7, 8). Amyloid PET results were returned in RAISR under the condition of a research study focused on understanding the psychological and behavioral implications of learning one’s AD biomarker status in the absence of an approved disease-modifying treatment. In addition to activities to promote cognitive health, participants consistently described activities undertaken to promote physical health and quality of life. As the subfield of disclosure science moves toward more clearly defining and assessing the so-called value of knowing, it will be important to capture activities like pursuing bucket list items and promoting social well-being, including the repair of strained relationships, as such undertakings speak to the person-specific nature of the value of learning one’s AD biomarker status. In addition, as the subfield moves toward post-disclosure interventions, it will be important to explore approaches that extend beyond the provision of information to test strategies grounded in theories of behavior change (32).


RAISR was a single-site RCT that was powered for the primary outcomes of understanding and perceived self-efficacy to cope with MCI, which required a minimum sample size of 80 dyads (patient + care partner), irrespective of amyloid status. Our approach to measuring health-related behavior performance and did not account for subtleties such as increasing the frequency or intensity of a given behavior. The relatively small number of individuals scanning positive for beta amyloid may have underpowered the current analysis. Small subsample sizes also constrained opportunities for within-group analyses. Statistical findings should be interpreted with caution because, as an exploratory analysis, we did not correct for multiple comparisons. Follow-up longitudinal studies are indicated and should strive not only for larger samples but for greater representation of persons from historically minoritized communities. RAISR participants were primarily non-Hispanic white with high levels of education, limiting generalizability to the diverse population of older adults for whom AD biomarker testing may be indicated. Finally, these interviews were conducted prior to the approval of potentially disease modifying therapies for AD, a development which could have profound implications for the value of knowing one’s brain amyloid status.



Building on a growing body of studies that describe how individuals feel following AD biomarker disclosure, this analysis focused on how cognitively symptomatic individuals act in response to learning their brain amyloid status. Findings suggest that the value of knowing one’s brain amyloid status, as a basis for action, may differ by scan result and encompass a broad range of behaviors that may be more related to maintaining quality of life than enhancing cognition.


Funding: The RAISR (Return of Amyloid PET Scan Results) Study (; NCT03121118) was supported by a grant from the National Institutes of Health, National Institute on Aging (NIA) R01AG046906-01 (JHL, PI) and by grants P50 AG005133 and P30 AG066468. Partial research support was provided by Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly, Inc. JSR is supported by NIA grant P30 AG072931.

Acknowledgements: We would like to express our sincere gratitude to two trained researchers from the team, Uchenna J. Mbawuike, Melissa L. Knox for their valuable contributions to the preliminary analysis of developing the coding structure. We also extend our immense appreciation to all the patients and their care partners who participated in this trial.

Conflict of interest disclosure: JHL has provided consultation to Genentech and Biogen.

Ethical standards: This study was approved by the University of Pittsburgh IRB. This manuscript is an original work and all authors contributed substantively to its development and have verified the accuracy of its content.



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