The psychometric rigor of unsupervised, smartphone-based assessments and factors that impact remote protocol engagement is critical to evaluate prior to the use of such methods in clinical contexts. We evaluated the validity of a high-frequency, smartphone-based cognitive assessment protocol, including examining convergence and divergence with standard cognitive tests, and investigating factors that may impact adherence and performance (i.e., time of day and anticipated receipt of feedback vs. no feedback).

Cognitively unimpaired participants (N = 120, Mage = 68.8, 68.3% female, 87% White, Meducation = 16.5 years) completed 8 consecutive days of the Mobile Monitoring of Cognitive Change (M2C2), a mobile app-based testing platform, with brief morning, afternoon, and evening sessions. Tasks included measures of working memory, processing speed, and episodic memory. Traditional neuropsychological assessments included measures from the Preclinical Alzheimer’s Cognitive Composite battery.

Findings showed overall high compliance (89.3%) across M2C2 sessions. Average compliance by time of day ranged from 90.2% for morning sessions, to 77.9% for afternoon sessions, and 84.4% for evening sessions. There was evidence of faster reaction time and among participants who expected to receive performance feedback. We observed excellent convergent and divergent validity in our comparison of M2C2 tasks and traditional neuropsychological assessments.

This study supports the validity and reliability of self-administered, high-frequency cognitive assessment via smartphones in older adults. Insights into factors affecting adherence, performance, and protocol implementation are discussed.

Remote assessment for cognitive screening and monitoring in the elderly has many potential advantages, including improved convenience/access and ease of repeat testing. As remote testing becomes more feasible and common, it is important to examine what factors might influence performance and adherence with these new methods. Personal beliefs about one’s ability to remember effectively have been shown to impact memory performance, especially in older adults (Lineweaver & Hertzog, 1998). The perception of a low level of personal control over memory may impact a person’s use of memory strategies which might otherwise enhance performance, as well as their beliefs about the efficacy of those strategies (Lineweaver et al., 2021). The present study examined the relationship between perceived memory self-efficacy and performance and adherence on self-administered, smartphonebased remote cognitive assessments.

Participants were 123 cognitively unimpaired adults (ages 55-80, 68.3% female, 87% White, M= 16.5 years of education) recruited from the Butler Hospital Alzheimer’s Prevention Registry as part of an ongoing study evaluating novel cognitive assessment methods. A cutoff of score of ≥34 on the modified Telephone Interview for Cognitive Status (TICSm) was required for enrollment. Perceived memory self-efficacy was assessed using two subscales of the Personal Beliefs about Memory Instrument (PBMI; Lineweaver et al., 1998): “prospective control”, the perception of control one currently has to influence future memory functioning, and “future control”, the perception of the amount of control over memory function one will have in the future. Participants completed three brief self-administered cognitive testing sessions per day for 8 consecutive days using a mobile app-based platform developed as part of the National Institute of Aging’s Mobile Toolbox initiative. Cognitive tasks assessed visual working memory (WM), processing speed (PS), and episodic memory (EM)(see Thompson et al., 2022).

Statistical analyses were conducted using univariate ANOVA tests to look for main effects of each PBMI subscale score on remote assessment adherence and average performance on each task over 8 days. After adjusting for aging, we found a higher rate of false alarms (proportion of misidentified stimuli) on the WM task was associated with higher levels of both self-reported prospective control (F(2, 86) = 4.188, p = .018) and future control (F(2, 96) = 5.003, p = .009). Increased response time on the PS task was also associated with higher levels of future control when adjusted for aging (F(2, 96) = 6.075, p = .003). There was no main effect of memory self-efficacy ratings on EM. We found no main effects of memory self-efficacy ratings on assessment adherence.

These findings suggest perceptions of high prospective and future control are associated with positive response bias on a forced-choice WM task, and high perceptions of future control are also associated with slower response times on PS tasks. Future research should examine whether this is due to increased deliberation, cautiousness, or other factors. Limitations include the potentially limited generalizability of this largely White, highly educated, and motivated sample self-selected for AD research. Next steps for this research include comparing these results with the effects of perceived self-efficacy on in-person cognitive assessments.

Routine cognitive screening in the elderly may facilitate earlier diagnosis of neurodegenerative diseases and access to care and resources for patients and families. However, despite growing rates of Alzheimer's and related disorders (ADRD), the availability and implementation of cognitive screening for older adults in the US remains quite limited. Remote cognitive assessment via smartphone app may reduce several barriers to more widespread screening. We examined the validity of a remote app-based cognitive screening protocol in healthy older adults by examining remote task convergence with standard-person assessments and cerebral amyloid (Aß) status as an AD biomarker.

Participants (N =117) were cognitively unimpaired adults aged 60-80 years (67.5% female, 88% White, 75% education > 16 years). A portion had Aß PET imaging results available from prior research participation [(Aß positive (Aß+) n =26, and Aß negative (Aß-) n = 44]. A modified Telephone Interview for Cognitive Status (TICSm) cutoff score of >34 was used to establish unimpaired cognition. Participants completed 8 consecutive assessment days using Mobile Monitoring of Cognitive Change (M2C2), a smartphone app-based testing platform developed as part of the National Institute of Aging's Mobile Toolbox initiative. Brief (i.e., 3-4 minute) M2C2 sessions were assigned daily within morning, afternoon, and evening time windows. Tasks included measures of visual working memory (WM), processing speed (PS), and episodic memory (EM) (see Thompson et al., 2022). Participants then completed a battery of standard neuropsychological assessments in-person at a follow-up visit.

Participants completed 22.6 (SD = 2.6) out of 24 assigned sessions (3 sessions x 8 days) on average. Performance on all M2C2 tasks decreased significantly with age. Women performed significantly better on WM and EM tasks relative to men. There were no detectable significant differences in performance by race or education. Shorter mean reaction time on M2C2 PS trials predicted faster Trails A and B completion (ß = .26, p < .01, 95% CI [3.8, 23.3] and ß = .20, p < .05, 95% CI [.23, 6.8], respectively). Greater mean M2C2 WM accuracy predicted longer maximum backward digital span (ß = .24, p = .01, 95% CI [.02, .16]). Greater mean M2C2 EM accuracy predicted stronger Logical Memory delayed recall (ß = .33, p < .001, 95% CI [.004, .012]) and total immediate recall on the Free and Cued Selective Reminding Test (ß = .19, p < .05, 95% CI [.000, .006]). Moreover, EM significantly distinguished Aß- and Aß+ individuals (t (68) = 3.0, p < .01) with fair accuracy (AUC = .72).

Mean performance across 8-days on each M2C2 task predicted same-domain cognitive task performance on a standard assessment battery, with medium effect sizes. Performance on the EM task was also sensitive to cerebral Aß status, consistent with subtle memory changes implicated in the preclinical stage of AD. These findings support the validity of this remote testing protocol in healthy older adults, with implications for future efforts to facilitate accessible and sensitive cognitive screening for early detection of ADRD. Limitations include the restricted generalizability of this primarily white and college educated sample.

Sensitive and non-invasive methods of screening for early-stage Alzheimer’s disease (AD) are urgently needed. The digital clock drawing test (DCTclockTM) is an established and well-researched neuropsychological tool that can aid in early detection of dementia. Other simple, yet sensitive, neuropsychological measures able to detect early stages of AD include Trail Making Tests (TMT). We investigated the psychometric properties of DCTclockTM with TMT-A and TMT-B. We then sought to understand the degree to which neuropsychological tools (i.e., DCTclockTM, TMT-A, and B) versus the Montreal Cognitive Assessment (MoCA) predict beta-amyloid (Aß) positron emission tomography (PET) status (positive or negative) in cognitively normal individuals.

Participants included a sample of cognitively normal older adults (n= 59, M age = 69.2, F = 64%) recruited from the Butler Memory and Aging Program. The Linus Health DCTclockTM uses a digital pen to capture traditional clock drawing test performance and advanced analytics to evaluate the drawing process for indicators of cognitive difficulty. DCTclockTM may have overlapping cognitive properties with TMT measures, like efficiency, processing speed, and spatial reasoning. We compared latency measures (i.e., process efficiency, clock face speed, average latency, and processing speed) and spatial reasoning of the DCTclockTM to z-scores of TMT-A and TMT-B to detect any overlapping psychometric properties. Verbal fluency was included for discriminant validity. We then ran logistic regressions on a subset of the sample to compare neuropsychological tests (DCTclockTM total score [score that captures overall performance], TMT-A/B, and verbal fluency) to the MoCA, a commonly used cognitive screening tool, in determining PET status.

Highly correlated (r > .7) DCTclockTM variables were excluded. We found statistically significant correlations between some DCTclockTM measures and TMT-A/B, like DCTclockTM drawing process efficiency and TMT-A and TMT-B (r= .45, p< .001, r=.29, p< .026, respectively), and DCTclockTM average latency and TMT-A and TMT-B (r=.3, p< .024, r= .26, p< .044, respectively). No statistically significant associations were found between any DCTclockTM measures and verbal fluency, or between DCTclockTM spatial reasoning and TMT-A/B. We then investigated the effect of these neuropsychological tests (DCTclockTM total score, TMT-A/B, verbal fluency) and age on the likelihood of PET positivity (subset of sample, total PET, n=31). The model was statistically significant (x2 (5) = 15.35, p< .01). The model explained 53% (Nagelkerke R2) of the variance in PET status and correctly classified 74.2% of cases. DCTclockTM was the only significant predictor (p< .02), after controlling for TMT-A, TMT-B, verbal fluency, and age. Comparatively, there was no effect of MoCA and age (total PET, n= 29) on the likelihood of PET positivity.

Overall, these results suggest psychometric convergence on elements of DCTclockTM and TMT-A/B, while there was no association in spatial operations between DCTclockTM and TMT measures. Further, when compared to the MoCA, DCTclockTM and these commonly used neuropsychological tests (verbal fluency and TMT-A/B) were better predictors of PET status, primarily driven by the DCTclockTM. Digitized neuropsychological tools may provide additional metrics not captured by pen-and-paper tests that can detect AD-associated pathology.

To evaluate the potential superiority of donanemab vs. aducanumab on the percentage of participants with amyloid plaque clearance (≤24.1 Centiloids [CL]) at 6 months in patients with early symptomatic Alzheimer's disease (AD) in phase 3 TRAILBLAZER-ALZ-4 study. The amyloid cascade in AD involves the production and deposition of amyloid beta (Aβ) as an early and necessary event in the pathogenesis of AD.

Participants (n = 148) were randomized 1:1 to receive donanemab (700 mg IV Q4W [first 3 doses], then 1400 mg IV Q4W [subsequent doses]) or aducanumab (per USPI: 1 mg/kg IV Q4W [first 2 doses], 3 mg/kg IV Q4W [next 2 doses], 6 mg/kg IV Q4W [next 2 doses] and 10 mg/kg IV Q4W [subsequent doses]).

Baseline demographics and characteristics were well-balanced across treatment arms (donanemab [N = 71], aducanumab [N = 69]). Twenty-seven donanemab-treated and 28 aducanumab-treated participants defined as having intermediate tau.

Upon assessment of florbetapir F18 PET scans (6 months), 37.9% donanemab-treated vs. 1.6% aducanumab-treated participants achieved amyloid clearance (p < 0.001). In the intermediate tau subpopulation, 38.5% donanemab-treated vs. 3.8% aducanumab-treated participants achieved amyloid clearance (p = 0.008).

Percent change in brain amyloid levels were −65.2%±3.9% (baseline: 98.29 ± 27.83 CL) and −17.0%±4.0% (baseline: 102.40 ± 35.49 CL) in donanemab and aducanumab arms, respectively (p < 0.001). In the intermediate tau subpopulation, percent change in brain amyloid levels were −63.9%±7.4% (baseline: 104.97 ± 25.68 CL) and −25.4%±7.8% (baseline: 102.23 ± 28.13 CL) in donanemab and aducanumab arms, respectively (p ≤ 0.001).

62.0% of donanemab-treated and 66.7% of aducanumab-treated participants reported an adverse event (AE), there were no serious AEs due to ARIA in donanemab arm and 1.4% serious AEs (one event) due to ARIA were reported in aducanumab arm.

This study provides the first active comparator data on amyloid plaque clearance in patients with early symptomatic AD. Significantly higher number of participants reached amyloid clearance and amyloid plaque reductions with donanemab vs. aducanumab at 6 months.

Previously presented at the Clinical Trials on Alzheimer's Disease - 15th Conference, 2022.

Alzheimer’s disease (AD) is highly comorbid with idiopathic normal pressure hydrocephalus (iNPH) and may diminish the benefits of shunting; however, findings in this area are mixed. We examined postoperative outcomes, with emphases on cognition and utilization of novel scoring procedures to enhance sensitivity.

Using participant data from an iNPH outcome study at Butler Hospital, a mixed effect model examined main and interaction effects of time since surgery (baseline, 3 months, 12 months, and 24–60 months) and AD comorbidity (20 iNPH and 11 iNPH+AD) on activities of daily living (ADLs) and iNPH symptoms. Regression modeling explored whether baseline variables predicted improvements 3 months postoperatively.

There were no group differences in gait, incontinence, and global cognition over time, and neither group showed changes in ADLs. Cognitive differences were observed postoperatively; iNPH patients showed stable improvements in working memory (p = 0.012) and response inhibition (p = 0.010), while iNPH + AD patients failed to maintain initial gains. Regarding predicting postoperative outcomes, baseline AD biomarkers did not predict shunt response at 3 months; however, older age at surgery predicted poorer cognitive outcomes (p = 0.04), and presurgical Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) (p = 0.035) and Mini-Mental Status Examination (MMSE) scores (p = 0.009) predicted improvements incontinence.

iNPH + AD may be linked with greater declines in aspects of executive functioning postoperatively relative to iNPH alone. While baseline AD pathology may not prognosticate shunt response, younger age appears linked with postsurgical cognitive improvement, and utilizing both brief and comprehensive cognitive measures may help predict improved incontinence. These results illustrate the potential benefits of surgery and inform postoperative expectations for those with iNPH + AD.

Cognitive impairment and apathy are well-documented features of idiopathic normal pressure hydrocephalus (iNPH). However, research examining other neuropsychiatric manifestations of iNPH is scant, and it is unknown whether the neuropsychiatric presentation differs for iNPH patients with comorbid Alzheimer’s disease (AD) versus iNPH without AD. This study aims to advance our understanding of neuropsychiatric syndromes associated with iNPH.

Fifty patients from Butler Hospital’s Normal Pressure Hydrocephalus Clinic met inclusion criteria. Caregiver ratings on the Frontal Systems Behavior Scale (FrSBe) were examined to appraise changes in apathy, executive dysfunction, and disinhibition. Patients also completed cognitive tests of global cognition, psychomotor speed, and executive functioning. AD biomarker status was determined by either amyloid-beta (Aβ) positron emission tomography (PET) imaging or cerebrospinal fluid (CSF) total tau to Aβ-42 ratio.

Results revealed clinically significant elevations on the FrSBe’s apathy and executive dysfunction scales and modest correlations among these scales and cognitive measures. Of the 44 patients with available neuroimaging or CSF draw data, 14 presented with comorbid AD. Relative to the iNPH-only group, the iNPH + AD group showed a larger increase from pre-illness to current informant ratings on the executive dysfunction scale, but not the apathy or disinhibition scales.

These results replicate and extend prior research by identifying apathy and executive dysfunction as prominent neuropsychiatric symptoms of iNPH and suggest comorbid AD exacerbates dysexecutive behaviors. Future research is warranted to examine the effects of comorbid AD pathology in response to shunt surgery for iNPH, neuropsychiatric symptom changes, and resultant caregiver burden.

To develop and validate the Discrepancy-based Evidence for Loss of Thinking Abilities (DELTA) score. The DELTA score characterizes the strength of evidence for cognitive decline on a continuous spectrum using well-established psychometric principles for improving detection of cognitive changes.

DELTA score development used neuropsychological test scores from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort (two tests each from Memory, Executive Function, and Language domains). We derived regression-based normative reference scores using age, gender, years of education, and word-reading ability from robust cognitively normal ADNI participants. Discrepancies between predicted and observed scores were used for calculating the DELTA score (range 0–15). We validated DELTA scores primarily against longitudinal Clinical Dementia Rating-Sum of Boxes (CDR-SOB) and Functional Activities Questionnaire (FAQ) scores (baseline assessment through Year 3) using linear mixed models and secondarily against cross-sectional Alzheimer’s biomarkers.

There were 1359 ADNI participants with calculable baseline DELTA scores (age 73.7 ± 7.1 years, 55.4% female, 100% white/Caucasian). Higher baseline DELTA scores (stronger evidence of cognitive decline) predicted higher baseline CDR-SOB (ΔR2 = .318) and faster rates of CDR-SOB increase over time (ΔR2 = .209). Longitudinal changes in DELTA scores tracked closely and in the same direction as CDR-SOB scores (fixed and random effects of mean + mean-centered DELTA, ΔR2 > .7). Results were similar for FAQ scores. High DELTA scores predicted higher PET-Aβ SUVr (ρ = 324), higher CSF-pTau/CSF-Aβ ratio (ρ = .460), and demonstrated PPV > .9 for positive Alzheimer’s disease biomarker classification.

Data support initial development and validation of the DELTA score through its associations with longitudinal functional changes and Alzheimer’s biomarkers. We provide several considerations for future research and include an automated scoring program for clinical use.