Preclinical Dementia Research Articles

Exploring the Association Between Loneliness, Subjective Cognitive Decline, and Quality of Life Among Older Thai Adults: A Convergent Parallel Mixed-Method Study.

Examining the rising prevalence of subjective cognitive decline as an early indicator of dementia in adults, this study investigates its complex interaction with loneliness and quality of life in individuals with preclinical dementia. Using a convergent parallel mixed-method approach, we employed Structural Equation Modeling on a cohort of 149 older adults. Qualitative insights were derived from focused group discussions and in-depth semi-structured interviews with a cohort of 23 older adults. Loneliness emerges as a pivotal contributor, exerting a discernible partial indirect effect on quality of life through subjective cognitive decline (indirect effect = -0.145, p = .006). Noteworthy differentials surfaced, with the impact of subjective cognitive decline on quality of life heightened in those with chronic diseases (△χ2 = 6.139, p = .013). Loneliness, wielding a palpable impact, intricately interlaces with quality of life, the nexus of which is intricately mediated by subjective cognitive decline.

Incremental validity of the test of practical judgment (TOP-J) in the prediction of diagnosis in preclinical dementia

ABSTRACT The Test of Practical Judgment (TOP-J) has not been thoroughly investigated in terms of its incremental validity. In the current study, we explored whether the TOP-J adds unique and meaningful information to the neuropsychological assessment beyond other executive functioning tests that are often used as proxies for practical judgment. Ninety-seven older adults who were classified as cognitively unimpaired, with subjective cognitive decline, or with mild cognitive impairment completed a comprehensive neuropsychological evaluation. Incremental validity was assessed through hierarchical ordinal regression analysis by modeling the TOP-J (Forms A and B, 15-item and 9-item versions), in addition to widely used tests of executive function, with participant classification/diagnosis as the outcome. The addition of the TOP-J (both 15-item versions) added incremental validity beyond traditional executive functioning measures to predict diagnosis. Including the TOP-J within neuropsychological evaluations of older adults may enhance differentiation of preclinical dementia diagnoses and provide clinically valuable information to the exam.

Two-Year Longitudinal Outcomes of Subjective Cognitive Decline in Hispanics Compared to Non-hispanic Whites.

Subjective cognitive decline (SCD), considered a preclinical dementia stage, is less understood in Hispanics, a high-risk group for dementia. We investigated SCD to mild cognitive impairment (MCI) progression risk, as well as baseline and longitudinal features of depressive symptoms, SCD complaints, and objective cognitive performance among Hispanics compared to non-Hispanic Whites (NHW). Hispanic (n = 23) and NHW (n = 165) SCD participants were evaluated at baseline and 2-year follow-up. Evaluations assessed function, depressive symptoms, SCD, and objective cognitive performance. Hispanics were at increased risk of progression to MCI (OR: 6.10, 95% CI 1.09-34.20, P = .040). Hispanic participants endorsed more depressive symptoms at baseline (P = .048) that worsened more longitudinally (OR: 3.16, 95% CI 1.18-8.51, P = .023). Hispanic participants had increased SCD complaints on the Brief Cognitive Rating Scale (BCRS) (β = .40 SE: .17, P = .023), and in specific BCRS domains: concentration (β = .13, SE: .07, P = .047), past memory (β = .13, SE: .06, P = .039) and functional abilities (β = .10, SE: .05, P = .037). In objective cognitive performance, Hispanic ethnicity associated with decline in MMSE (β = -.27, SE: .13, P = .039), MoCA (β = -.80 SE: .34, P = .032), Trails A (β = 2.75, SE: .89, P = .002), Trails B (β = 9.18, SE: 2.71, P = .001) and Guild Paragraph Recall Delayed (β = -.80 SE: .28, P = .005). Conclusions: Hispanic ethnicity associated with a significantly increased risk of 2-year progression of SCD to MCI compared to NHW. This increased risk associated with increased depressive symptoms, distinctive SCD features, and elevated amnestic and non-amnestic objective cognitive decline. This supports further research to refine the assessment of preclinical dementia in this high-risk group.

Stimulating leisure-time activities and the risk of dementia: a multi-cohort study.

Stimulating activities are associated with a decreased risk of dementia. However, the extent to which this reflects a protective effect of activity or non-participation resulting from dementia is debated. We investigated the association of stimulating leisure-time activity in late adulthood with the risk of dementia across up to two decades' follow-up. We used data from five prospective cohort studies from Finland and Sweden. Mental, social, outdoor, consumptive and physical leisure-time activities were self-reported. Incident dementia was ascertained from clinical diagnoses or healthcare and death registers. Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Of the 33 263 dementia-free individuals aged ≥50years at baseline, 1408 had dementia during a mean follow-up of 7.0years. Active participation in mental (HR: 0.52, 95% CI: 0.41 to 0.65), social (HR: 0.56 95% CI: 0.46 to 0.72), outdoor (HR: 0.70, 95% CI: 0.58 to 0.85), consumptive (HR: 0.67, 95% CI: 0.53 to 0.94) and physical (HR: 0.62, 95% CI: 0.51 to 0.75) activity, as well as variety (HR: 0.54, 95% CI: 0.43 to 0.68) and the overall frequency of activity (HR: 0.41, 95% CI: 0.34 to 0.49) were associated with a reduced risk of dementia in <10years' follow-up. In ≥10years' follow-up all associations attenuated toward the null. Stimulating leisure-time activities are associated with a reduced risk of dementia in short-term but not long-term follow-up. These findings may reflect a reduction in leisure-time activity following preclinical dementia or dilution of the association over time.

Unveiling metabolic patterns in dementia: Insights from high-resolution quantitative blood-oxygenation-level-dependent MRI.

Oxygen extraction fraction (OEF) and deoxyhemoglobin (DoHb) levels reflect variations in cerebral oxygen metabolism in demented patients. Delineating the metabolic profiles evident throughout different phases of dementia necessitates an integrated analysis of OEF and DoHb levels. This is enabled by leveraging high-resolution quantitative blood oxygenation level dependent (qBOLD) analysis of magnitude images obtained from a multi-echo gradient-echo MRI (mGRE) scan performed on a 3.0 Tesla scanner. Achieving superior spatial resolution in qBOLD necessitates the utilization of an mGRE scan with only four echoes, which in turn limits the number of measurements compared to the parameters within the qBOLD model. Consequently, it becomes imperative to discard non-essential parameters to facilitate further analysis. This process entails transforming the qBOLD model into a format suitable for fitting the log-magnitude difference (L-MDif) profiles of the four echo magnitudes present in each brain voxel. In order to bolster spatial specificity, the log-difference qBOLD model undergoes refinement into a representative form, termed as r-qBOLD, particularly when applied to class-averaged L-MDif signals derived through k-means clustering of L-MDif signals from all brain voxels into a predetermined number of clusters. The agreement between parameters estimated using r-qBOLD for different cluster sizes is validated using Bland-Altman analysis, and the model's goodness-of-fit is evaluated using a -test. Retrospective MRI data of Alzheimer's disease (AD), mild cognitive impairment (MCI), and non-demented patients without neuropathological disorders, pacemakers, other implants, or psychiatric disorders, who completed a minimum of three visits prior to MRI enrolment, are utilized for the study. Utilizing a cohort comprising 30 demented patients aged 65-83 years in stages 4-6 representing mild, moderate, and severe stages according to the clinical dementia rating (CDR), matched with an age-matched non-demented control group of 18 individuals, we conducted joint observations of OEF and DoHb levels estimated using r-qBOLD. The observations elucidate metabolic signatures in dementia based on OEF and DoHb levels in each voxel. Our principal findings highlight the significance of spatial patterns of metabolic profiles (metabolic patterns) within two distinct regimes: OEF levels exceeding the normal range (S1-regime), and OEF levels below the normal range (S2-regime). The S1-regime, accompanied by low DoHb levels, predominantly manifests in fronto-parietal and perivascular regions with increase in dementia severity. Conversely, the S2-regime, accompanied by low DoHb levels, is observed in medial temporal (MTL) regions. Other regions with abnormal metabolic patterns included the orbitofrontal cortex (OFC), medial-orbital prefrontal cortex (MOPFC), hypothalamus, ventro-medial prefrontal cortex (VMPFC), and retrosplenial cortex (RSP). Dysfunction in the OFC and MOPFC indicated cognitive and emotional impairment, while hypothalamic involvement potentially indicated preclinical dementia. Reduced metabolic activity in the RSP suggested early-stage AD related functional abnormalities. Integrated analysis of OEF and DoHb levels using r-qBOLD reveals distinct metabolic signatures across dementia phases, highlighting regions susceptible to neuronal loss, vascular involvement, and preclinical indicators.

Linking Dementia Pathology and Alteration in Brain Activation to Complex Daily Functional Decline During the Preclinical Dementia Stages: Protocol for a Prospective Observational Cohort Study.

Progressive difficulty in performing everyday functional activities is a key diagnostic feature of dementia syndromes. However, not much is known about the neural signature of functional decline, particularly during the very early stages of dementia. Early intervention before overt impairment is observed offers the best hope of reducing the burdens of Alzheimer disease (AD) and other dementias. However, to justify early intervention, those at risk need to be detected earlier and more accurately. The decline in complex daily function (CdF) such as managing medications has been reported to precede impairment in basic activities of daily living (eg, eating and dressing). Our goal is to establish the neural signature of decline in CdF during the preclinical dementia period. Gait is central to many CdF and community-based activities. Hence, to elucidate the neural signature of CdF, we validated a novel electroencephalographic approach to measuring gait-related brain activation while participants perform complex gait-based functional tasks. We hypothesize that dementia-related pathology during the preclinical period activates a unique gait-related electroencephalographic (grEEG) pattern that predicts a subsequent decline in CdF. We provide preliminary findings showing that older adults reporting CdF limitations can be characterized by a unique gait-related neural signature: weaker sensorimotor and stronger motor control activation. This subsample also had smaller brain volume and white matter hyperintensities in regions affected early by dementia and engaged in less physical exercise. We propose a prospective observational cohort study in cognitively unimpaired older adults with and without subclinical AD (plasma amyloid-β) and vascular (white matter hyperintensities) pathologies. We aim to (1) establish the unique grEEG activation as the neural signature and predictor of decline in CdF during the preclinical dementia period; (2) determine associations between dementia-related pathologies and incidence of the neural signature of CdF; and (3) establish associations between a dementia risk factor, physical inactivity, and the neural signature of CdF. By establishing the clinical relevance and biological basis of the neural signature of CdF decline, we aim to improve prediction during the preclinical stages of ADs and other dementias. Our approach has important research and translational implications because grEEG protocols are relatively inexpensive and portable, and predicting CdF decline may have real-world benefits. DERR1-10.2196/56726.

A Strategy for Allowing Earlier Diagnosis and Rigorous Evaluation of BACE1 Inhibitors in Preclinical Alzheimer's Disease.

Given continued failure of BACE1 inhibitor programs at symptomatic and prodromal stages of Alzheimer's disease (AD), clinical trials need to target the earlier preclinical stage. However, trial design is complex in this population with negative diagnosis of classical hippocampal amnesia on standard memory tests. Besides recent advances in brain imaging, electroencephalogram, and fluid-based biomarkers, new cognitive markers should be established for earlier diagnosis that can optimize recruitment to BACE1 inhibitor trials in presymptomatic AD. Notably, accelerated long-term forgetting (ALF) is emerging as a sensitive cognitive measure that can discriminate between asymptomatic individuals with high risks for developing AD and healthy controls. ALF is a form of declarative memory impairment characterized by increased forgetting rates over longer delays (days to months) despite normal storage within the standard delays of testing (20-60 min). Therefore, ALF may represent a harbinger of preclinical dementia and the impairment of systems memory consolidation, during which memory traces temporarily stored in the hippocampus become gradually integrated into cortical networks. This review provides an overview of the utility of ALF in a rational design of next-generation BACE1 inhibitor trials in preclinical AD. I explore potential mechanisms underlying ALF and relevant early-stage biomarkers useful for BACE1 inhibitor evaluation, including synaptic protein alterations, astrocytic dysregulation and neuron hyperactivity in the hippocampal-cortical network. Furthermore, given the physiological role of the isoform BACE2 as an AD-suppressor gene, I also discuss the possible association between the poor selectivity of BACE1 inhibitors and their side effects (e.g., cognitive worsening) in prior clinical trials.

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study.

The relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults. We leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults. We analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease. During the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged <70 and >70 years, and in non-shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase. Based on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults.

Preclinical Dementia and Economic Well-Being Trajectories of Racially Diverse Older Adults.

ObjectivesThis study examined the magnitude, changes, and racial/ethnic disparities in the economic costs of the 16-year preclinical phase of dementia-a period of cognitive decline without significant impact on daily activities. Methods: The study utilized two dementia algorithms to classify individuals with incident dementia in the Health and Retirement Study. These cases were compared to matched controls in terms of poverty status, labor force participation, and unsecured debts. Results: Older adults classified with dementia were more likely to drop out of the labor force and become poor than similar older adults without dementia. Racial/ethnic disparities in poverty persisted during the preclinical period, with non-Hispanic Black older adults more likely to leave the labor force and Hispanic older adults more likely to have unsecured debt. Discussion: Findings highlight the economic costs during prodromal phase of dementia, emphasizing need for early interventions to reduce financial strain across diverse older adults.

Cardiovascular health and rate of cognitive decline in preclinical dementia: A 12-year population-based study.

We investigated whether vascular risk factors (VRFs), assessed with Life's Simple 7 (LS7), are associated with the rate of cognitive decline in the years preceding a dementia diagnosis. This study included 1,449 stroke-free participants aged ≥60 years from the Swedish National Study on Aging and Care in Kungsholmen, who underwent repeated neuropsychological testing (episodic memory, semantic memory, verbal fluency, perceptual speed) across 12 years. The LS7 score, assessed at baseline, included smoking, diet, physical activity, body mass index, plasma glucose, total cholesterol, and blood pressure. Preclinical dementia was defined as being dementia-free at baseline and diagnosed with dementia during follow-up. Level and change in cognitive performance as a function of LS7 category (poor vs. intermediate to optimal) and future dementia status were estimated using linear mixed-effect models. Participants who later developed dementia had, on average, a poorer LS7 score compared to those who remained dementia-free. For individuals aged 60-72 years, poor diet was associated with accelerated decline in perceptual speed (β = -0.05, 95% CI [-0.08, -0.02]), and a poor glucose score was associated with faster rates of verbal fluency (β = -0.019, 95% CI [-0.09, -0.01]) and global cognitive (β = -0.028, 95% CI [-0.06, 0.00]) decline in the preclinical dementia group. VRFs exacerbate rate of cognitive decline in the years preceding a dementia diagnosis. This effect was most pronounced in young-old age and primarily driven by diet and glucose. The effect of VRFs may be especially detrimental for cognitive decline trajectories of individuals with impending dementia. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Altered cerebellar and caudate gray-matter volumes and structural covariance networks preceding dual cognitive and mobility impairments in older people.

The neuroanatomical changes driving both cognitive and mobility impairments, an emerging preclinical dementia syndrome, are not fully understood. We examined gray-matter volumes (GMVs) and structural covariance networks (SCNs) abnormalities in community-based older people preceding the conversion to physio-cognitive decline syndrome (PCDS). Voxel-wise brain GMV and established SCNs were compared between PCDS and non-PCDS converters. The study included 343 individuals (60.2±6.9 years, 49.6% men) with intact cognitive and mobility functions. Over an average 5.6-year follow-up, 116 transitioned to PCDS. Identified regions with abnormal GMVs in PCDS converters were over cerebellum and caudate, which served as seeds for SCNs establishment. Significant differences in cerebellum-based (to right frontal pole and left middle frontal gyrus) and caudate-based SCNs (to right caudate putamen, right planum temporale, left precentral gyrus, right postcentral gyrus, and left parietal operculum) between converters and nonconverters were observed. This study reveals early neuroanatomic changes, emphasizing the cerebellum's role, in dual cognitive and mobility impairments. Neuroanatomic precursors of dual cognitive and mobility impairments are identified. Cerebellar GMV reductions and increased right caudate GMV precede the onset of PCDS. Altered cerebellum- and caudate-based SCNs drive PCDS transformation. This research establishes a foundation for understanding PCDS as a specific dementia syndrome.

Associations of body habitus and its changes with incident dementia in older adults.

This study examined the associations of body mass index (BMI) and waist circumference (WC), as well as their short- and long-term changes over time, with incident dementia in older individuals. Data came from 18,837 community-dwelling individuals aged 65+ years from Australia and the United States, who were relatively healthy without major cognitive impairment at enrolment. Anthropometric measures were prospectively assessed at baseline, as well as change and variability from baseline to year two (three time-points). In a subgroup (n = 11,176), self-reported weight at age 18 and 70+ years was investigated. Dementia cases satisfied DSM-IV criteria. Cox regression was used to examine the associations between anthropometric measures and incident risk of dementia. Compared to normal weight, an overweight (HR: 0.67, 95%CI: 0.57-0.79, p < 0.001) or obese BMI (HR: 0.73, 95%CI: 0.60-0.89, p = 0.002), or a larger WC (elevated, HR: 0.71, 95%CI: 0.58-0.86, p < 0.001; highly elevated, HR: 0.65, 95%CI: 0.55-0.78, p < 0.001; relative to low) at baseline was associated with lower dementia risk. In contrast, substantial increases in BMI (>5%) over 2 years after baseline were associated with higher dementia risk (HR: 1.49, 95% CI: 1.17-1.91, p = 0.001). Increased dementia risk was also seen with an underweight BMI at baseline and a 2-year BMI decrease (>5%), but these associations appeared only in the first 4 years of follow-up. Compared to normal weight at both age 18 and 70+ years, being obese at both times was associated with increased dementia risk (HR: 2.27, 95%CI: 1.22-4.24, p = 0.01), while obesity only at age 70+ years was associated with decreased risk (HR: 0.70, 95%CI: 0.51-0.95, p = 0.02). Our findings suggest that long-term obesity and weight gain in later life may be risk factors for dementia. Being underweight or having substantial weight loss in old age may be early markers of pre-clinical dementia.

An IoT-based cognitive impairment detection device: A newly proposed method in older adults care-choice reaction time-device development and data-driven validation.

Research shows that older adults' performance on choice reaction time (CRT) tests can predict cognitive decline. A simple CRT tool could help detect mild cognitive impairment (MCI) and preclinical dementia, allowing for further stratification of cognitive disorders on-site or via telemedicine. The primary objective was to develop a CRT testing device and protocol to differentiate between two cognitive impairment categories: (a) subjective cognitive decline (SCD) and non-amnestic mild cognitive impairment (na-MCI), and (b) amnestic mild cognitive impairment (a-MCI) and multiple-domain a-MCI (a-MCI-MD). A pilot study in Italy and Romania with 35 older adults (ages 61-85) assessed cognitive function using the Mini-Mental State Examination (MMSE) and a CRT color response task. Reaction time, accuracy, and demographics were recorded, and machine learning classifiers analyzed performance differences to predict preclinical dementia and screen for mild cognitive deficits. Moderate correlations were found between the MMSE score and both mean reaction time and mean accuracy rate. There was a significant difference between the two groups' reaction time for blue light, but not for any other colors or for mean accuracy rate. SVM and RUSBoosted trees were found to have the best preclinical dementia prediction capabilities among the tested classifier algorithms, both presenting an accuracy rate of 77.1%. CRT testing with machine learning effectively differentiates cognitive capacities in older adults, facilitating early diagnosis and stratification of neurocognitive diseases and can also identify impairments from stressors like dehydration and sleep deprivation. This study highlights the potential of portable CRT devices for monitoring cognitive function, including SCD and MCI.

Supplemental Material for Cardiovascular Health and Rate of Cognitive Decline in Preclinical Dementia: A 12-Year Population-Based Study

Supplemental Material for Cardiovascular Health and Rate of Cognitive Decline in Preclinical Dementia: A 12-Year Population-Based Study

Trajectory of multimorbidity before dementia: A 24-year follow-up study.

Although the multimorbidity-dementia association has been widely addressed, little is known on the long-term trajectory of multimorbidity (TOM) in preclinical dementia. Based on the Health and Retirement Study, burden of multimorbidity was quantified with the total number of eight long-term conditions (LTC). Patterns of TOM before dementia diagnosis were investigated with mixed-effects models. In 1752 dementia cases and 5256 matched controls, cases showed higher and faster increasing predicted number of LTC than controls, with a significant case-control difference from 20 years prior to dementia diagnosis. Larger increases in number of LTC during preclinical phase of dementia were found in White participants, females, those whose age at dementia onset was younger, and those who were less educated. Our findings emphasize the faster accumulation of multimorbidity in prodromal dementia than in natural aging, as well as effect modifications by age and sex. TOM increased faster in prodromal dementia than in natural ageing.Patterns of TOM by dementia status diverged at 20 years before dementia diagnosis.Patterns of TOM were modified by age and sex.

Association of neuropathological lesions with body mass index by the time of death

AbstractBackgroundThe association between moderate/severe dementia and lower Body Mass Index (BMI) is well described, but the weight decline seems to also occur in cognitively normal individuals with preclinical dementia. Considering that up to one‐fifth of individuals with normal cognition might meet the criteria for a neuropathological diagnosis, autopsy studies are key detecting neurodegenerative and cerebrovascular diseases that could be underlining weight changes during the life course. Therefore, we investigated the association between dementia‐related brain lesions and BMI and evaluated whether cognitive function was a mediator of this association.MethodNeuropathological study in a population‐based sample of 1,170 Brazilians. Clinical variables and cognition evaluation were obtained through a post mortem interview with a proxy. Linear regression adjusted models were used to investigate the association between each neuropathologic lesion (independent variable) and the BMI (dependent variable). The direct and indirect (considering a mediation by cognitive abilities) effects of each neuropathologic lesion on BMI were evaluated through a mediation model.ResultIndividuals with lower body weight were more likely to have a higher burden of neuropathological lesions and worse cognitive abilities. Neurofibrillary tangles (NFT) and neuropathological comorbidity were associated with low BMI. Mediation analyses showed these lesions were directly associated with BMI and indirectly through cognitive abilities. Despite having normal cognitive abilities, 25% of the sample had at least one neuropathologic diagnosis. High NFT burden was associated with lower BMI even in these participants.ConclusionNeurofibrillary tangles were associated with lower BMI independent of cognitive abilities.

Digital biomarker co‐design with people with preclinical or prodromal dementia

AbstractBackgroundLanguage markers can serve screening and early detection in Alzheimer’s disease (AD). Using artificial intelligence (AI) approaches enables automated assessment and analysis of speech biomarkes using chatbot technology. Reliable digital speech biomarkers require an easy‐to‐use chatbot which is adopted to the users’ needs. Currently, chatbots often are unsuitable for people with cognitive impairment and rather frustrating for their users. Here, we implemented a user centred design approach to iteratively evaluate usability of a chatbot system for automated speech assessments for people with prodromal or preclinical dementia.MethodWithin the study PROSPECT‐AD, participants (n = 53 by January 2023, 300 planned) are automatically called for six times every three months by our chatbot “Mili”. Each call takes about 15 minutes and consists of three cognitive tasks (Wordlist, Semantic Verbal Fluency, Story Telling). We applied a six stage usability check to improve Mili iteratively (see Figure 1). For deeper insights, we conduct semi‐structured interviews (n = 20). During the interviews, we focus on affinity for technology, usability, and participants’ attitude towards chatbots and artificial intelligence in medicine.ResultsTo date, Mili has completed 54 assessments (see Figure 2). Drop‐outs (11.3%) occcur around the first assessment. Reasons were e.g., lack of accessibility of participants, excessive demands through cognitive tasks or through Mili. Participants reported problems due to Mili’s high speaking pace and hangs of Mili. Additionally, Mili struggled in automatically retrieving appointments and missed calling. All problems were quickly resolved. The speaking pace was reduced and the time‐out time extented by 2 seconds. Results of the system usability scale revealed a high user‐friendliness of the calls (see Table 1). Participants (n = 6) evaluated the calls as quick to learn and easy to use. Two participants wished for more technical support for the calls. Two participants felt uncomfortable in using Mili.ConclusionOur results revealed a high usability and feasibility of the automated phone calls by Mili. Due to close colaboration, problems with Mili were solved qickly and further drop‐outs prevented. This underlines the benefit of close cooperation between participants, scientists, and IT specialists. Interviews are needed for further improvement of Mili and to understand uncertainty with Mili.

Increased worry associated with self‐reported, but not informant‐reported, subjective cognitive decline predicts risk of incident dementia

AbstractBackgroundSubjective cognitive decline (SCD), in the absence of impaired testing, may be an indicator of early Alzheimer’s disease (AD) and other dementias. However, not all individuals with SCD have cognitive decline. ‘SCD plus’ criteria were proposed in an effort to increase the likelihood of identifying preclinical dementia in individuals with SCD. Two of these criteria include the expression of concern (worry) about the SCD and confirmation of the SCD by an observer (informant). This study investigates whether longitudinal changes in self‐ and informant‐reported SCD‐worry are associated with increased risk of incident dementia over time.MethodParticipants were 873 older adults (M = 78.65‐years; 55% female) and 849 informants from the Sydney Memory and Ageing Study. SCD‐worry was defined as responding “Yes” to the following: “Have you noticed growing difficulties with your/their memory?” and “Have you been concerned about your/their memory getting worse?”. Changes in SCD‐worry over time were modelled using latent growth curve analyses with logit transformation. Participants’ and informants’ propensity to report SCD‐worry at baseline and change over time were analysed using Cox regressions to determine associations with incident dementia risk over 10‐years.Results32% of participants who reported noticing memory difficulties at baseline also reported worry associated with this, where only 19% of informants reported worry associated with SCD at baseline. Controlling for demographics, APOE4, mood and personality, participants’ initial level (p &lt; .001) and change in SCD‐worry over time (p = .002), were associated with dementia risk. Controlling for the same covariates, informants’ initial SCD‐worry (p &lt; .001) was associated with dementia risk, though SCD‐worry change was not (p = .862). When modelled together, participants’ initial level of, and longitudinal change in, SCD‐worry were still independently associated with increased dementia risk (p’s &lt; .001); informants’ initial SCD‐worry remained significant (see Table 1).ConclusionOur findings highlight the need to factor in concerns held by individuals that go beyond just recognising cognitive changes have occurred, as the latter is a common phenomenon in older adults. Our results suggest that worries about perceived cognitive changes may characterise individuals at greater dementia risk.

Can Changes in Older Adults' Technology Use Patterns Be Used to Detect Cognitive Decline?

The number of older adults diagnosed with dementia is expected to more than double by mid-century. Monitoring older adults' cognitive functioning is essential for the early detection of dementia, which can increase treatment efficacy and slow the disease progression. Current approaches to detect preclinical dementia are expensive, invasive, and are not accessible to everyone. This study aimed to determine whether technology use patterns could be used as an indicator of cognitive change. Using 6 waves (2015-2020) from the National Health and Aging Trends Study, we examined within-person and between-person effects of stopping 4 types of technology use on 4 cognitive outcomes. Our analyses showed that stopping the use of the Internet, computers, and tablets, and sending texts and e-mails were related to cognitive decline. These results suggest that monitoring technology use patterns may be an innovative approach that is economical and efficient to identify individuals at risk of cognitive decline.

81 Assessment of Functional Capacity Interview (AFCI): A New Informant- Report Measure to Detect Disability Risk in Older Adults

Objective:Functional disability is a foreseeable consequence of neurodegenerative diseases affecting cognition, yet there are few validated instruments that assess functional capacity for use in pre-clinical and clinical dementia conditions. To our knowledge, the existing instruments do not comprehensively assess decision-making capacity across the numerous functional domains of daily life. We developed and evaluated the utility of an informant-report measure, the Assessment of Functional Capacity Interview (AFCI), within a sample of cognitively unimpaired and preclinical dementia groups.Participants and Methods:Based on a comprehensive literature review, analysis of existing measures, and clinical experience, we generated &gt;40 items consisting of open-ended questions assessing crucial aspects of daily functioning. These items were presented to 12 experts in the field of geriatrics and neuropsychology, through a graded approach (4 rounds of feedback and alterations), resulting in item modification or rejection, as well as addition of new items. The remaining items were piloted on three informants at the time of outpatient clinical evaluations, leading to further item refinement. The final version of the AFCI evaluated capacity across domains of financial affairs and management, medical affairs and healthcare management, home and personal safety, and social behaviors and community functioning. The AFCI contained 6 items per domain with response items that ranged from 0=no difficulty to 3=severe difficulty (scores ranged from 0 to 72).Results:Participants (N = 58; Agemean = 76; Educationmean = 16) were classified as cognitively unimpaired (CU, n = 17), subjective cognitive decline (SCD, n = 24), or mild cognitive impairment (MCI, n = 17) based on established criteria. All participants had a knowledgeable informant who completed the AFCI. We found statistically significant moderate to large correlations between the AFCI total score and an informant report measure of cognitive functioning (Brief Informant Form of Neurobehavioral Symptomatology total score), rs(42) = .73, p &lt; .001, Test of Practical Judgment-informant total score rs(42) = .87, p &lt; .001, and Montreal Cognitive Assessment total score rs(41) = -.34, p = .027. A Kruskal-Wallis H test revealed significant differences in AFCI total score between the three diagnostic groups, H(2) = 12.30, p = .002. Pairwise post-hoc analysis with Bonferroni correction showed a significant difference between CU and MCI (p = .001). The difference in AFCI total score between SCD and MCI was in the expected direction, but did not achieve statistical significance with correction, (p = .068). As expected, there was no statistically significant difference between CU and SCD (p =.353).Conclusions:In this pilot sample (data collection is ongoing), the AFCI showed promise as a brief, clinically useful functional capacity instrument that is easily administered during a clinical interview or completed by knowledgeable informants. Results can help identify compromised decision-making in at-risk older adults to aid the prevention of common safety issues within this vulnerable population. Ongoing research will extend preliminary investigation of validity and further inform the utility of AFCI in both diagnostic and interventional contexts