Abstract
Objectives
Early diagnosis of Alzheimer’s disease (AD) using brain scans and other biomarker tests will be essential to increasing the benefits of emerging disease-modifying therapies, but AD biomarkers may have unintended negative consequences on stigma. We examined how a brain scan result affects AD diagnosis confidence and AD stigma.
Methods
The study used a vignette-based experiment with a 2 × 2 × 3 factorial design of main effects: a brain scan result as positive or negative, treatment availability and symptom stage. We sampled 1,283 adults ages 65 and older between June 11and July 3, 2019. Participants (1) rated their confidence in an AD diagnosis in each of four medical evaluations that varied in number and type of diagnostic tools and (2) read a vignette about a fictional patient with varied characteristics before completing the Modified Family Stigma in Alzheimer’s Disease Scale (FS-ADS). We examined mean diagnosis confidence by medical evaluation type. We conducted between-group comparisons of diagnosis confidence and FS-ADS scores in the positive versus negative brain scan result conditions and, in the positive condition, by symptom stage and treatment availability.
Results
A positive versus negative test result corresponds with higher confidence in an AD diagnosis independent of medical evaluation type (all p < .001). A positive result correlates with stronger reactions on 6 of 7 FS-ADS domains (all p < .001).
Discussion
A positive biomarker result heightens AD diagnosis confidence but also correlates with more AD stigma. Our findings inform strategies to promote early diagnosis and clinical discussions with individuals undergoing AD biomarker testing.
Keywords: Alzheimer’s stigma, Biomarker testing, Diagnosis confidence
Alzheimer’s disease (AD) affects more than 5 million people in the United States. AD is the most common cause of dementia, accounting for an estimated 60% to 80% of dementia cases (Alzheimer’s Association, 2023). The U.S. Food and Drug Administration (FDA) recently approved two therapies, with more pending review, for persons with AD biomarkers who have mild cognitive impairment or mild-stage dementia (Alzheimer’s Association, 2023). Additionally, multiple clinical trials are underway testing therapies in biomarker-positive persons who do not yet have symptoms (Hoffmann-La Roche, 2022; VA Office of Research and Development, 2022). The goal of these therapies, whether for cognitively normal or cognitively impaired persons, is to modify the underlying biology of the disease (Alzheimer’s Association, 2023). Advances in biomarkers are moving AD diagnosis and treatment toward a tertiary or even a secondary prevention model of AD (Dubois et al., 2016; Jack et al., 2018). To understand the effects of advances in biomarker diagnosis and treatment and inform efforts promoting a prevention model of AD, our study examines how AD biomarker-informed diagnosis may affect public perceptions related to diagnosis confidence and stigma.
Currently, a diagnosis of AD is typically made by a clinician using data from multiple sources, including a clinical history interview, physical exam, and memory tests (Knopman et al., 2021). Diagnostic criteria guide interpretation of clinical data to arrive at a diagnosis (McKhann et al., 1984). There is no single test that can definitively diagnose AD (Khoury & Ghossoub, 2019). Diagnosis can take months, or even years, and patients are sometimes misdiagnosed (Hunter et al., 2015). The journey to acquiring an AD diagnosis can be difficult and uncertain for patients and their families. To the best of our knowledge, there are no studies examining older adults’ confidence in an AD diagnosis.
Public confidence in an AD diagnosis may increase when biomarker testing is used in the medical evaluation. Brain scans and blood tests for AD-specific pathologies may radically improve accuracy and timeliness of diagnosis. Brain scans, for example, can measure amyloid and tau burden (Betthauser et al., 2020; Jack et al., 2010). Prior studies suggest brain scans increase physicians’ diagnosis confidence and have diagnostic qualities superior to cognitive testing (Boccardi et al., 2016; Fantoni et al., 2018; Jagust et al., 2007; Ossenkoppele et al., 2013; Zamrini et al., 2004). A positive brain scan may help guide the prescribing of therapies that slow disease progression (Blennow & Zetterberg, 2018a), which may, by means of expectations for improved treatment outcomes, also increase diagnosis confidence.
Higher confidence in an AD diagnosis may be beneficial. Individuals and their families may not seek out multiple clinical evaluations to feel confident that they received the correct diagnosis. Instead, patients and families may begin to address current care needs and future life planning. Fewer diagnostic visits may, in turn, reduce health care spending (Hunter et al., 2015). Higher diagnosis confidence may also influence health behaviors, such as lifestyle changes (Bensaïdane et al., 2016; Largent et al., 2020), as well as patient management and treatment adherence (Fantoni et al., 2018). Moreover, improved diagnosis confidence may help ameliorate the most common reason given by patients for not discussing cognitive issues during medical visits: incorrect diagnosis (Alzheimer’s Association, 2023).
Alzheimer’s disease stigma—negative perceptions, attitudes, emotions, and reactions related to AD (Corner & Bond, 2004; Werner & Heinik, 2008)—is a known barrier to early diagnosis (Corner & Bond, 2004; Werner & Giveon, 2008). A positive brain scan test has been shown to be associate with higher AD stigma (Stites et al., 2022). If a positive brain scan test also leads to higher confidence in an AD diagnosis, it would identify an intuitive but novel association between AD diagnosis and AD stigma. Consequently, AD stigma would need to be addressed not only in efforts to encourage individuals to seek diagnosis but also directly in the delivery of a diagnosis.
We conducted a vignette-based experiment in a sample of adults aged 65 and older to examine how a brain scan test result (positive or negative) affects AD diagnosis confidence and AD stigma; in the positive brain scan condition, we examine how availability of disease-modifying treatment and dementia symptom stage affect each diagnosis confidence and stigma. We hypothesized that (1) use of AD biomarker testing—that is, a brain scan or blood tests—in a medical evaluation would lead to higher confidence in an AD diagnosis, and that individuals randomized to the positive brain scan condition would (2) have higher AD diagnosis confidence when a brain scan was used in a medical evaluation, and (3) report higher AD stigma. Findings from our study may inform strategies to promote early diagnosis and clinical discussions among individuals undergoing AD biomarker testing.
Method
Study Design
The study was a vignette-based experiment that used a 2 × 2 × 3 factorial design of main effects. Data collection occurred between June 11 and July 3, 2019. Study flow is shown in Supplementary Figure 1.
Study Sample
Adults who could read English and were ages 65 and older were randomly invited from a large Qualtrics research panel. Screener questions were used to verify age eligibility. Panel members who consented to participate were asked to provide demographic data. The response rate was 56.0% and the completion rate was 98.8% (n = 16 participants discontinued the study).
To ensure the ability to comprehend the vignettes, participants completed a comprehension check. They read an educational paragraph about AD biomarker testing and then answered a fact-based question (Appendix A of Stites et al., 2022). Participants had up to two opportunities to answer correctly or they were excluded from the study (n = 0 participants excluded). Participants who completed the study were financially compensated by Qualtrics for their time.
No prior study has been published with this sample. Some participants in this sample (n = 427, 33%) were included in samples reported on in prior studies (Stites et al., 2022, 2024). The current study is the first to report on older adults and the first to test whether reading about a positive versus negative biomarker result affects an individual’s AD diagnosis confidence.
Vignettes
Simple randomization was used to assign participants to one vignette describing a fictional patient attending a new patient visit at a memory center. The vignette described the patient undergoing a “brain scan test” for an AD biomarker to determine if AD was the cause of memory issues. The patient was accompanied by an adult daughter. Similar proportions of vignettes described the fictional patient as aged 60, 70, or 80 years old and as a man or woman. Race was not mentioned, and the patient’s name in the vignette was selected to be ambiguous.
Vignettes varied by the following three factors: AD biomarker test result (positive or negative), status of AD disease-modifying treatment (unavailable or available), and clinical symptom severity (no dementia symptoms, mild-stage symptoms, or moderate stage symptoms). The scan result was reported in the vignette as either “positive” or “negative” for an AD biomarker, which conforms to FDA labels for positron emission tomography biomarker tests measuring brain amyloid. Symptoms were described consistent with the Clinical Dementia Rating (CDR) Scale (Hughes et al., 1982), a validated informant and patient interview assessing a patient’s cognition and functioning, with global scores of 0 (none), 1 (mild), or 2 (moderate). The CDR covers six domains: memory, orientation, judgment and problem-solving, community affairs, home and hobbies, and personal care. The physician explained whether a disease-modifying treatment that “could slow the progression of (AD)” was or was not available. Vignette samples are shown in Appendix A of Stites et al. (2022).
Measures
Alzheimer’s disease diagnosis confidence was evaluated using an instrument from Baumann et al. (2011). We modified the diagnostic approaches for relevance in current clinical practices in diagnosing AD and research-only methods for identifying AD. Participants rated the confidence that they would have if given an AD diagnosis based on a medical evaluation that included: (i) only a clinical history interview and physical exam; (ii) a clinical history interview, physical exam, and memory tests; (iii) a clinical history interview, physical exam, memory tests, and blood tests; or (iv) a clinical history interview, physical exam, memory tests, blood tests, and a brain scan. Participants rated their confidence for each evaluation on a scale of 0–100 on a visual analog scale, with higher scores indicating more confidence. No additional anchors or narrative instructions were given.
Alzheimer’s disease stigma was assessed using a modified Family Stigma in Alzheimer’s Disease Scale (FS-ADS), a validated scale that measures AD public stigma across a range of cognitive, emotional, and behavioral attributions (Werner et al., 2011). These attributions align with Link and Phelan’s theory of stigma (Link & Phelan, 2001), the modified labeling theory (Link et al., 1989), and the social-cognitive model of stigma (Corrigan, 2007). Items on the original assessment were adapted for relevance to the vignettes (Johnson et al., 2015). The overall internal consistency of the adapted form appeared similar to that of the original scale (Cronbach’s alpha = 0.91; Werner et al., 2011). Cronbach alphas for all individual domains were above 0.80, suggesting “better than good” internal reliability, except for the Pity scale, which had a score of 0.77, suggesting “good” internal reliability.
The modified FS-ADS is comprised of 41 items that load onto seven empirically derived domains. Items asked the extent to which the participant believed that the person described in the vignette: (a) should worry about encountering discrimination by insurance companies or employers and being excluded from voting or medical decision-making (Structural Discrimination); (b) would be expected to have certain symptoms like speaking repetitively or suffering incontinence (Negative Severity Attributions); (c) should be expected to have poor hygiene, neglected self-care, and appear in other ways that provoke negative judgments (Negative Aesthetic Attributions); (d) would evoke feelings of disgust or repulsion (Antipathy); (e) would evoke feelings of concern, compassion, or willingness to help from others (Support); (f) would evoke feelings of sympathy, sadness, or pity from others (Pity); and (g) would be ignored or have social relationships limited by others (Social Distance). We framed items on domains that pertained to negative or unpleasant attributes to be about the actions of “others” in order to minimize social desirability bias (Bazinger & Kühberger, 2012; Fisher, 1993). Responses were recorded on a 5-point Likert scale arranged on the screen horizontally from left to right, and analyzed by domain using established methods (Johnson et al., 2015), with higher scores indicating stronger endorsement.
Basic demographic data were collected using U.S. Census categories of White, African-American, or Other (including American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, and Other). The Institutional Review Board of the University of Pennsylvania (IRB #828348) approved all procedures.
Statistical Analysis
A power calculation using data on the smallest between-group mean difference on the FS-ADS and a Type I error rate (alpha) of 0.05 (two-sided) showed that a sample of 1,200 participants would be sufficient to maintain at least 95% statistical power in estimations of main study effects (Stites, Johnson, et al., 2018). Means and proportions were used to characterize the sample. Normal 95% confidence intervals (95% CI) and Fisher’s exact test of proportions were used to compare the sample to the general population (Bureau, 2021). We also compare differences in AD diagnosis confidence ratings between groups and quantify them as both point differences and standard deviations (Cohen’s d). Standard deviations of 1.2 and higher are considered large differences (Lipsey & Wilson, 2001).
In this study, pairs of 95% CI that do not overlap are statistically significant at p < .05. Analysis of variance (ANOVA), Kruskal–Wallis, and ordered logistic regression (OLR) were used to test for between-group mean differences in diagnosis confidence and FS-ADS domains by study condition. These three approaches produced similar results. Cohen’s d and common odds ratios (ORs) from OLR were used to report association sizes.
Analyses control for participant age, gender, and race and for the age and gender of the person described in the vignette to adjust for effects that could be attributed to these characteristics. Statistical analyses were performed in 2022–2023. Statistical tests were two-sided. p Values were corrected for multiple comparisons in the ANOVA using Tukey honestly significant difference. Those ≤.002 were considered statistically significant. Analyses were performed in Stata 16 (College Station, TX, USA).
Results
Study Sample Characteristics
In the sample of 1,283 older adults, mean age was 70.7 years (95% CI: 70.4 to 71.1; Table 1). Most participants self-identified as women (61.2% [95% CI: 57.9% to 64.4%]) and White (84.4% [95% CI: 81.9% to 86.7%]). About a quarter of participants had a high school education or less (24.7% [95% CI: 21.9% to 27.7%]).
Table 1.
Characteristics of Study Sample and Similarly Aged American Population
Characteristic | 65+ sample (N = 1,283) |
U.S. 65+ adult populationa,b |
---|---|---|
Age, mean (95% CI) | 70.7 (70.4 to 71.1) | 86.4 (86.3 to 86.4)a |
Women, % (95% CI) | 61.2 (57.9 to 64.4) | 54.9 (54.8 to 55.0)b |
Race, % (95% CI) | ||
White | 84.4 (81.9 to 86.7) | 75.6 (75.5 to 75.7)b |
African-American | 6.6 (5.0 to 8.4) | 9.2 (9.1 to 9.3)b |
Other | 9.0 (7.3 to 11.1) | 6.7 (3.4 to 6.9)a |
Hispanic or Latina/o/x | 3.7 (2.2 to 6.4) | 9.0 (8.9 to 9.1)b |
Education, % (95% CI) | ||
High school/GED or less | 24.7 (21.9 to 27.7) | 56.2 (55.7 to 56.7)a |
Some college or 2-year degree | 39.8 (36.5 to 43.1) | 27.0 (26.9 to 27.1)b |
4-Year college degree | 20.7 (18.1 to 23.6) | 13.1 (12.5 to 13.7)a |
Professional degree | 14.9 (12.6 to 17.4) | 9.4 (8.8 to 9.9)a |
Notes: Characteristics of a sample of adults (N = 1,283) ages 65 and older; survey conducted between June 11 and July 3, 2019. Column percentages may not total 100 due to rounding.
aData from the U.S. 2010 Census.
bData from the U.S. 2021 American Community Survey (ACS) Table S0103.
On average, participants were younger, more likely to identify as women, more likely to identify as White, and reported higher educational attainment than the general U.S. population 65 years and older.
Participant Confidence in an Alzheimer’s Diagnosis by Medical Evaluation Type
Participant confidence in an AD diagnosis that was based on a clinical interview and physical examination had an average rating of 32.04 points (95% CI: 30.57 to 33.52; Table 2).
Table 2.
Older Adults’ Confidence in an Alzheimer’s Disease Diagnosis by Evaluation Type and Brain Scan Result (N = 1,283)
Evaluation type | Overall mean (95% CI) |
Estimate name | Positive test result conditiona (n = 636) |
In the positive brain scan result conditionb | ||
---|---|---|---|---|---|---|
Treatment unavailablec (n = 314) |
Mild stage ADd (n = 223) |
Moderate stage ADd (n = 205) |
||||
Clinical history interview and physical exam only | 32.04 (30.57 to 33.52) |
OR (95% CI) |
1.48***
(1.80 to 1.23) |
1.04 (1.26 to 0.86) |
1.13 (1.42 to 0.89) |
1.08 (1.36 to 0.85) |
N/Ae | Significance (p, Cohen’s d) | <0.001, 0.20 | 0.70, 0.001 | 0.31, 0.007 | 0.53, 0.033 | |
Clinical history interview, physical exam, and memory tests | 42.10 (40.66 to 43.54) |
OR (95% CI) |
1.60***
(1.94 to 1.32) |
1.02 (1.23 to 0.84) |
1.14 (1.44 to 0.91) |
1.07 (1.35 to 0.84) |
N/Ae | Significance (p, Cohen’s d) | <0.001, 0.28 | 0.83, 0.00024 | 0.26, 0.033 | 0.59, 0.08 | |
Clinical history interview and physical exam, memory tests, and blood tests | 50.93 (49.47 to 52.38) |
OR (95% CI) |
1.58***
(1.91 to 1.30) |
0.96 (0.79 to 1.16) |
1.15 (1.44 to 0.91) |
1.14 (1.45 to 0.90) |
N/Ae | Significance (p, Cohen’s d) | <0.001, 0.27 | 0.67, 0.021 | 0.24, 0.077 | 0.27, 0.091 | |
Clinical history interview and physical exam, memory tests, blood tests, and brain scan | 77.97 (76.79 to 79.14) |
OR (95% CI) |
1.64***
(1.99 to 1.36) |
1.05 (1.27 to 0.87) |
1.04 (1.31 to 0.83) |
1.05 (1.33 to 0.83) |
N/Ae | Significance (p, Cohen’s d) | <0.001, 0.22 | 0.61, 0.02 | 0.71, 0.05 | 0.68, 0.03 |
Notes: AD = Alzheimer’s disease; OR = odds ratio from ordered logistic regression; 95% CI = 95% confidence interval.
Data gathered from a survey of adults ages 65 and older (n = 1,283) conducted between June 11 and July 3, 2019.
aNegative test result is reference group.
bIncludes only those participants that were randomized to read about a patient who learned a positive brain scan test result.
cTreatment available is reference category.
dCognitively unimpaired condition is reference category.
eIndicates no p values were calculated for the control condition.
Boldface indicates statistical significance (*p < .05, **p < .01, ***p < .001).
When an AD diagnosis was based on memory tests in addition to clinical interview and physical examination, participant AD diagnosis confidence had an average rating of 42.10 points (95% CI: 40.66 to 43.54), which was 10.06 points (95% CI: 7.14 to 12.97) higher than a clinical interview and physical examination alone. Histograms of confidence ratings by each evaluation type are shown in Supplementary Figure 2.
Participant AD diagnosis confidence that was based on blood tests in addition to a clinical interview, physical examination, and memory tests had an average rating of 50.93 points (95% CI: 49.47 to 52.38), which was higher by 18.89 points (95% CI: 15.95 to 21.81) than a clinical interview and physical examination alone. Participant AD diagnosis confidence that was based on a brain scan in addition to the other four assessments was an average rating of 77.97 points (95% CI: 76.79 to 79.14), which was higher by 45.93 points (32.04 [95% CI: 30.57 to 33.52]) than a clinical interview and physical examination alone.
Participant Confidence in an Alzheimer’s Diagnosis by Study Condition
On average, participants randomized to the positive versus negative brain scan result condition gave higher confidence ratings in an AD diagnosis for each of the four types of medical evaluations (all p < .001, Table 2). These effect sizes were small, ranging from 0.20 to 0.28; about 60% of participants in the positive brain scan result condition endorsed higher confidence in each evaluation than those in the negative condition. No statistically significant differences were observed based on treatment availability or clinical symptom stage.
Participant Ratings of Alzheimer’s Stigma by Brain Scan Result Condition
Participants endorsed greater worries about structural discrimination (OR: 3.47 [95% CI: 4.24 to 2.84]) and social distance (OR: 1.52 [95% CI: 1.85 to 1.25]) in the positive brain scan condition than in the negative condition. They also endorsed greater symptom severity (OR: 1.46 [95% CI: 1.77 to 1.21]) in the positive brain scan result condition. Participants endorsed stronger emotional reactions, including greater antipathy (OR: 1.44 [95% CI: 1.75 to 1.19]), pity (OR: 2.10 [95% CI: 2.55 to 1.73]), and support (OR: 1.55 [95% CI: 1.88 to 1.27]), in the positive as compared to the negative brain scan result condition. Analyses control for treatment availability and clinical symptom severity.
Participant Ratings of Alzheimer’s Stigma by Availability of Disease-Modifying Treatment in the Positive Brain Scan Result Condition
In the positive brain scan result condition, participants endorsed greater worries about structural discrimination when a disease-modifying treatment was unavailable versus available (OR: 1.34 [95% CI: 1.02 to 1.76], Table 3). This finding did not meet the criterion for statistical significance that was adjusted for multiple comparisons. No other differences based on treatment availability were observed (p > .05). Analyses were balanced for clinical symptom severity.
Table 3.
Alzheimer’s Disease Stigma by Brain Scan Test Result Condition and in the Positive Test Result Condition (N = 1,283)
FS-ADS domain | Estimate name |
Positive test result conditiona (n = 636) |
In the positive brain scan test conditionb | ||
---|---|---|---|---|---|
Treatment unavailablec (n = 314) |
Mild stage ADd (n = 223) |
Moderate stage ADd (n = 205) |
|||
Structural discrimination | OR (95% CI) |
3.47***
(4.24 to 2.84) |
1.34*
(1.02 to 1.76) |
2.33***
(3.25 to 1.67) |
2.75***
(3.87 to 1.95) |
Significance (p, Cohen’s d) | <0.001, 0.72 | 0.034, 0.15 | <0.001, 0.46 | <0.001, 0.56 | |
Negative severity attributions | OR (95% CI) |
1.46***
(1.77 to 1.21) |
0.88 (0.67 to 1.16) |
43.81***
(70.14 to 27.36) |
48.13***
(77.75 to 29.79) |
Significance (p, Cohen’s d) | <0.001, 0.25 | 0.36, −0.07 | <0.001, 1.41 | <0.001, 1.44 | |
Negative aesthetic attributions | OR (95% CI) | 1.13 (1.42 to 0.89) |
0.83 (0.60 to 1.16) |
18.07***
(32.38 to 10.08) |
5.22***
(9.54 to 2.86) |
Significance (p, Cohen’s d) | 0.31, 0.23 | 0.28, −0.02 | <0.001, 0.83 | <0.001, 0.34 | |
Antipathy | OR (95% CI) |
1.44***
(1.75 to 1.19) |
1.04 (0.79 to 1.37) |
4.44***
(6.31 to 3.12) |
3.33***
(4.76 to 2.33) |
Significance (p, Cohen’s d) | <0.001, 0.15 | 0.78, −0.02 | <0.001, 0.69 | <0.001, 0.55 | |
Support | OR (95% CI) |
1.55***
(1.88 to 1.27) |
0.92 (0.71 to 1.21) |
1.74**
(2.42 to 1.24) |
2.10***
(2.94 to 1.50) |
Significance (p, Cohen’s d) | <0.001, 0.23 | 0.57, −0.03 | 0.001, 0.32 | <0.001, 0.45 | |
Pity | OR (95% CI) |
2.10***
(2.55 to 1.73) |
0.98 (0.75 to 1.28) |
5.55***
(7.91 to 3.90) |
6.43***
(9.28 to 4.45) |
Significance (p, Cohen’s d) | <0.001, 0.43 | 0.88, −0.02 | <0.001, 0.95 | <0.001, 0.99 | |
Social distance | OR (95% CI) |
1.52***
(1.85 to 1.25) |
1.02 (0.78 to 1.35) |
6.16***
(8.87 to 4.27) |
5.40***
(7.80 to 3.73) |
Significance (p, Cohen’s d) | <0.001, 0.19 | 0.86, 0.00 | <0.001, 0.91 | <0.001, 0.83 |
Notes: AD = Alzheimer’s disease; FS-ADS = Modified family stigma in Alzheimer’s disease scale; OR = odds ratio from ordered logistic regression; 95% CI = 95% confidence interval.
Data gathered from a survey of adults ages 65 and older (N = 1,283) conducted between June 11 and July 3, 2019.
aNegative test result is reference group.
bIncludes only those participants that were randomized to read about a patient who learned a positive brain scan test result.
cTreatment available is reference category.
dCognitively unimpaired condition is reference category.
Boldface indicates statistical significance (*p < .05, **p < .01, ***p < .001).
Participant Ratings of Alzheimer’s Stigma by Clinical Symptom Severity in the Positive Brain Scan Result Condition
Compared to participants in the positive brain scan condition that described a cognitively unimpaired patient, participants in the positive brain scan condition that described a patient with moderate stage dementia endorsed more worries about structural discrimination (OR: 2.75 [95% CI: 3.87 to 1.95]), greater severity of symptoms (OR: 48.13 [95% CI: 77.75 to 29.79]), harsher aesthetic judgments (OR: 5.22 [95% CI: 9.54 to 2.86]), more antipathy (OR: 3.33 [4.76 to 2.33]), more support (OR: 2.10 [95% CI: 2.94 to 1.50]), more pity (OR: 6.43 [95% CI: 9.28 to 4.45]), and more concerns about social distance (OR: 5.40 [95% CI: 7.80 to 3.73], Table 3).
Results were similar for the comparisons of the condition describing mild-stage dementia to the cognitively unimpaired condition. Results were also similar for comparisons in the full sample versus those in the positive brain scan result condition (Supplementary Table 1). All analyses statistically control for treatment availability.
Discussion
We conducted a study in a sample of 1,283 older adults to examine how a brain scan test result affected confidence in an AD diagnosis and AD stigma. Our findings showed that individuals randomized to a positive brain scan condition reported both higher confidence in an AD diagnosis and more AD stigma. In this section, we discuss details of our findings, first, related to diagnosis confidence, and second, to AD stigma. We also consider their implications.
Our findings support our hypothesis that inclusion of AD biomarker testing in a medical evaluation would lead to higher confidence in an AD diagnosis. Confidence was more than a standard deviation higher (Cohen’s d = 1.12 [95% CI: 1.0 to 1.2]) when a brain scan was used in the medical evaluation, as compared to an otherwise similar evaluation without a brain scan. This effect size is large. Inclusion of a blood-based test showed a smaller effect size (Cohen’s d = 0.33), compared to a medical evaluation that did not use blood tests but was otherwise similar, which is notable given the study’s biomarker education explained that AD biomarkers could be derived from lab tests and brain scans. Our finding may reflect the salience of a test result to participants, as a brain scan was paired with a specific test result in the vignette, while blood tests were described as part of assessment. It could also reflect the salience of the brain as the afflicted organ in AD (vs blood).
We found partial support for our second hypothesis; when a brain scan was used in the medical evaluation, individuals in the positive result condition were more confident in an AD diagnosis than those in the negative result condition. However, this finding was not unique to a brain scan. Individuals in the positive test result condition expressed more confidence in an AD diagnosis across all evaluation types, independent of the specific assessments.
This finding is unexpected and novel as there is no prior literature on the role of psychological priming, which refers to passive activation of internal mental representations (Bargh, 2016), in diagnosis confidence. The presence of the priming effect, also called environmental cueing, may suggest the importance of the content being primed, which we interpret in this case as relating to concerns about health and AD risk (Bargh, 2016).
As AD biomarkers allow for earlier diagnosis, even before memory and other cognitive symptoms, these findings suggest a priming effect could occur for some patients when they learn a positive AD biomarker result, possibly influencing their subsequent interactions (Erber et al., 1997). The priming effect of a positive biomarker result could have consequences for clinical discussions with patients during pretest counseling, post-test return of result sessions, or both. Priming effects can affect treatment outcomes, both facilitating or impeding better outcomes (Sliwinski & Elkins, 2013). For example, priming effects can stimulate adaptive mindsets (Papies, 2016). Clinicians may be able to connect these ideas in clinical discussions; priming discussion of an AD diagnosis with the benefits of knowing a positive biomarker result could aid patients in making behavioral or lifestyle changes.
We found that confidence in AD diagnosis was higher with each additional test included in the medical evaluation. In fact, the magnitude of difference in participants’ confidence about doubled with each addition. Thus, the number of tests in a medical evaluation may affect patient confidence. This warrants further investigation. Could clinicians’ efforts to meet the needs of patient confidence contribute to over-utilization of medical tests (Kip et al., 2019; Lillo et al., 2022; Miyakis et al., 2006)? The finding may also suggest that the expansion of AD biomarker tests might increase health care costs while also heightening patient diagnosis confidence in ways that might lower health care costs (Blennow & Zetterberg, 2018b, 2018a).
Consistent with a prior study in the public (Stites et al., 2022) and studies with individuals in AD prevention trials (Largent et al., 2021; Mozersky et al., 2021), we found support for our hypothesis that a positive brain scan test would correlate with higher AD stigma. The moderate effect size of 0.72 is similar to effect sizes observed in the comparisons of clinical symptom stages, which is notable as clinical symptoms are a driver of AD stigma (Stites, Rubright, et al., 2018).
Alzheimer’s disease stigma reduction strategies often rely heavily on education and contact-based interventions to normalize and demystify symptoms (Bacsu et al., 2022; Kim et al., 2021). Yet, a positive AD biomarker result can occur independent of clinical symptoms. Thus, efforts to mitigate AD stigma for individuals who are positive for AD biomarkers may require approaches other than those focused on symptoms, such as those that emphasize dispelling misbeliefs about AD and using person-centered language because personal dignity is the antithesis of stigma (Stites & Karlawish, 2018).
Availability of a disease-modifying treatment might offset some worries about structural discrimination attributable to a positive AD biomarker test. We observed a reduction of 34% in the difference in structural discrimination between the biomarker conditions when treatment was available. However, replication studies are needed, as this difference did not persist after adjustment for multiple comparisons.
Overall, we find that an AD biomarker result presents a double-edged sword, increasing both diagnosis confidence and stigma. Thus, advances in AD biomarkers, which aim to improve sensitivity and specificity of an AD diagnosis, may also pose barriers to early diagnosis via stigma. The present study extends our current understanding, suggesting the need to consider psychological and contextual factors in the clinical use of AD biomarkers. In part, the findings show a differential effect of priming a positive versus negative result, which suggests that older adults may demonstrate a predisposition to believe in disease presence, and, potentially, make stronger attributions about the precision of positive versus negative results. These ideas warrant further study, particularly as they may be unfounded drivers of AD stigma.
Limitations
Our study had several limitations. Our sample was not representative of the U.S. older adult population; on average, sample participants were younger, more educated, and more likely to be White and women. Discrepancies between the sample and general U.S. population limit the generalizability of the study results. Additional studies are needed to examine how findings may differ in subgroups with varying characteristics. Although the analyses controlled for fictional patient age and gender, the analyses did not control for all possible characteristics of the person in the vignette that may have influenced participants’ response patterns. In our assessment of measured covariates, we found no evidence that any effects attributable to potential confounding were not randomly distributed across the study groups. Our results are based on a fictional scenario and future in vivo studies may need to be conducted. In addition, our measure of diagnosis confidence does not have established clinical thresholds; future studies to establish these thresholds and their connections to clinical endpoints could be useful metrics for clinicians delivering AD diagnoses.
Conclusion
We conducted a study in a sample of older adults to examine how a brain scan result affects AD diagnosis confidence and AD stigma. We found that including a brain scan test in a medical evaluation heightens older adults’ confidence in an AD diagnosis. Notably, a positive brain scan result heightens confidence in an AD diagnosis but also correlates with more AD stigma. Our findings have the potential to inform the design of population-level interventions to reduce AD stigma.
Supplementary Material
Contributor Information
Shana D Stites, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Brian N Lee, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Emily A Largent, Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Kristin Harkins, Division of Geriatric Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Pamela Sankar, Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Abba Krieger, Department of Statistics, Wharton School of Business, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Rebecca T Brown, Division of Geriatric Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Rodlescia S Sneed, (Psychological Sciences Section).
Funding
This work was supported by the National Institutes of Health (grant numbers NIA P30 AG 072979, 1K23AG065442, 1K23AG065442-03S1, K01AG064123); the Alzheimer’s Association (grant number AARF-17-528934); the Centers for Disease Control and Prevention (grant number U48 DP—005053); the Alzheimer’s Foundation of America (no grant number); and the Greenwall Faculty Scholars Program (no grant number).
Conflict of Interest
None.
Data Availability
The de-identified data, analytic code, and materials on which the study conclusions are based are available for purposes of replication. Written requests may be made to the corresponding author. The data have not been made publicly available as the research team has not completed planned analyses for publications. Reasoning for the sample size, any data exclusions, all manipulations, and all measures are included in this publication. The study design, hypotheses, and analytic plan were not preregistered.
Author Contributions
S.D.S. and B.N.L. wrote the first draft. S.D.S., E.A.L., K.H., P.S., and A.K. contributed to the concept and design of the parent study. S.D.S. and R.B. contributed to the design of the current analyses. R.B. contributed content-specific expertise. All authors contributed to the writing of the paper. All authors approved the final version of this manuscript submitted.
Disclaimer
The views of this publication are those of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The de-identified data, analytic code, and materials on which the study conclusions are based are available for purposes of replication. Written requests may be made to the corresponding author. The data have not been made publicly available as the research team has not completed planned analyses for publications. Reasoning for the sample size, any data exclusions, all manipulations, and all measures are included in this publication. The study design, hypotheses, and analytic plan were not preregistered.