bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of caregiver tele‐health support and education intervention on the relationship between caregiver grief and quality‐of‐life
Authors: Gothard Sarah , Mooney Aimee , Tupper Emily , Lindauer Allison 
Published: January 2025

AbstractBackgroundCurrent research around caregiving for person’s with dementia (PWD) has historically emphasized caregiver burden. This leaves a gap of knowledge around other contributors to caregiving’s long‐term effects, including grief. The current analysis explores the relationship between caregiver grief and quality‐of‐life.MethodThe Tele‐STELLA study is a multi‐component, telehealth‐based intervention that teaches caregivers strategies to manage upsetting behaviors related to dementia in 8 weekly, 1‐hour sessions with professionals. The caregivers in this analysis (n = 138) cared for a family member with moderate to late‐stage dementia. A multilinear analysis was used to explore the relationship between grief and quality‐of‐life for 138 caregivers of PWD. Caregivers were women (73.2%) and white (87.0%), with 82.6% reporting financial security. On average, caregivers were engaged in their roles for 4.64 years (SD 3.69); 87.0% of the PWDs were in the moderate stage of dementia. Pre and post questionnaires queried caregivers about frequency of problematic behaviors and their reactions to the behaviors, grief, and household quality‐of‐life.ResultOf the 138 caregivers who started the 8‐week intervention, 98 (71%) completed both pre/post self‐reported data. Scatterplot visualization demonstrated a linear negative relationship between grief/quality‐of‐life at both pre and post intervention timepoints. Controlling for sex and care recipient dementia severity, a multilinear regression was performed and showed, at alpha 0.05, a significant negative relationship between quality‐of‐life and grief (p‐value: 0.00, B1: ‐0.17) at the pre‐intervention timepoint. Post‐intervention analysis of the same model showed the magnitude of the B1 coefficient of grief changed to ‐0.22 and an increased significance (p‐value: 0.00).ConclusionThis analysis found that grief in dementia caregiving had a strong negative relationship with quality‐of‐life and that this relationship became stronger after intervention. This may be due to caregivers' increased awareness of grief, or to the progressive nature of dementia over the 8‐week intervention period, but still highlights grief’s impact on caregiver quality‐of‐life. Future longitudinal studies will be necessary to evaluate if grief can serve as a predictor of quality‐of‐life and long‐term health outcomes for caregivers, and how best to leverage that knowledge for interventions in this population.
APOE‐ε4 associations with smartphone‐based cognitive markers
Authors: Rosická Anna M , Fittipaldi Sol , Gallagher Eoghan , Hanlon Anna K , Ibáñez Agustín , Bridgeman Katie , Muniz‐Terrera Graciela , Ritchie Karen , Ritchie Craig W , O'Brien John T , Koychev Ivan , Lawlor Brian , Naci Lorina , Gillan Claire M 
Published: January 2025

AbstractBackgroundSmartphone‐based assessments are a promising tool for early detection of cognitive decline in midlife. Previous research has shown such cognitive markers can be sensitive to a range of potentially modifiable dementia risk factors even in healthy adults. However, their sensitivity to genetic risk factors like APOE‐e4 is likely to differ by cognitive domain, with evidence of strong negative effects on wayfinding tasks but mixed for other domains. We investigated the associations between a set of previously validated smartphone‐based cognitive markers and APOE‐e4.MethodN = 87 cognitively unimpaired, APOE‐genotyped participants (aged 44‐67, 57.5% female) of the PREVENT study completed a self‐administered module in the smartphone application Neureka, including gamified cognitive tasks and memory self‐evaluation (completion rates: 81%–99%). Controlling for age, gender, education, and parental history of dementia, we compared APOE‐e4 carriers (n = 35) with non‐carriers in their performance on five cognitive measures: model‐based planning, visual working memory, processing speed (∼Trails A), cognitive flexibility (∼Trails B), and subjective memory problems. We conducted receiver operating characteristic (ROC) analysis to assess if APOE‐e4 status can be predicted from norm‐adjusted cognitive scores, i.e., the difference between observed cognitive performance and what we would predict for given demographics based on an additional benchmark sample (N = 3,376, aged 18‐84, 65% female).ResultIn univariate analyses, APOE‐e4 carriers did not significantly differ from non‐carriers in their demographic characteristics or cognitive scores except for visual working memory, which was better in carriers (t(63.226) = 2.245; p = .028). After controlling for covariates, APOE‐e4 status was not significantly linked to, which was better in APOE‐e4 carriers (ß[bootstrapped 95% CI] = ‐0.29[‐0.53,‐0.06]; t = ‐2.30; p = .025). In ROC‐analysis, norm‐adjusted visual working memory scores modestly differentiated between carriers and non‐carriers (AUC(SE) = .648(0.067); bootstrapped 95% CIs = 0.515–0.774).ConclusionThe non‐significant associations between APOE‐e4 and most cognitive markers suggest limited sensitivity to genetic risk. Interestingly, APOE‐e4 carriers outperformed non‐carriers in visual working memory, which could be due to antagonistic pleiotropy effects, but needs to be replicated in larger samples. The current study shows limited evidence for the clinical utility of our cognitive markers as indicators of genetic risk in middle‐aged cognitively unimpaired adults.
A Brief Digital Neuropsychological Protocol – II: Using Artificial Intelligence to Assess Verbal Serial List Learning Recognition Latency
Authors: Libon David J. , Swenson Rodney , Tobyne Sean E , Price Catherine C. , Lamar Melissa , Cosentino Stephanie , Banks Russell , Jannati Ali , Showalter John , Bates David , Pascual‐Leone Alvaro 
Published: January 2025

AbstractBackgroundDigital neuropsychological assessment easily captures behavior previously not obtainable by traditional pencil‐and‐paper tests. Verbal serial list learning tests are commonly used to assess for putative neurogenerative syndromes. Recognition test performance is often expressed compiling simple ‘yes/ no' responses, but fail to assess process metrics such as the latency to respond to individual recognition test items.MethodMemory clinic patients were assessed with the a digital neuropsychological protocol where cluster analysis of traditional metrics classified patients into normal (nl = 23), amnestic MCI (aMCI = 17), dysexecutive MCI (dMCI = 23), and dementia (dem = 14) groups. Verbal episodic memory was assessed with a 6‐word Philadelphia (repeatable) Verbal Learning Test. P(r)VLT delayed recognition memory was assessed using a forced multiple‐choice format where the iPad both displayed and verbally administered six trials containing the target word, a prototypic semantic foil (e.g., “apple”) and a generic semantic foil (e.g., “pear”). The patient was asked to touch the word that was part of the original word list as quickly as possible.ResultaMCI and dementia groups endorsed more recognition foils that other groups (Table 1; dementia > all groups, p< 0.001; aMCI > dMCI & nl groups, p< 0.001). Serial list learning recognition latency was slower for aMCI versus dMCI and nl groups; p< 0.005); and dementia versus dMCI and nl groups (p< 0.001). Regression analysis (dv = recognition latency; block 1 = age, education, sex; block 2 = recognition prototypic & generic foils) was significant (R2 = 0.463, p< 0.001); and found slower recognition latency was associated with greater numbers of prototypic recognition foils (beta = 0.551; p< 0.001). Regression analysis (dv = recognition latency; block 1 = age, education, sex; block 2 = all free recall cluster responses, all free recall extra‐list intrusion errors) also found slower recognition latency was associated with fewer semantic cluster responses (beta = ‐0.252, p< 0.021), but greater numbers of extra‐list intrusion errors (beta = 0.266, p< 0.017).ConclusionWhen brought to scale, automated analysis of recognition latency along with other serial list learning process metrics could help identify early, emergent neurodegenerative illness.
A Brief Digital Neuropsychological Protocol: III ‐ Using Artificial Intelligence to Measure Semantic Memory with the ‘Animal’ Fluency Test
Authors: Libon David J. , Swenson Rodney , Tobyne Sean , Price Catherine C. , Lamar Melissa , Cosentino Stephanie , Banks Russell , Jannati Ali , Showalter John , Bates David , Pascual‐Leone Alvaro 
Published: January 2025

AbstractBackgroundSemantic memory refers to knowledge of attributes associated with common objects. Quantifying the strength of semantic association between successive ‘animal' fluency responses can be challenging. The current research assessed between‐group differences for ‘animal' fluency total output and selected verbal serial list learning, episodic memory measures.MethodMemory clinic patients were assessed with a digital neuropsychological protocol. Cluster analysis classified patients into normal (nl = 23), amnestic MCI (aMCI = 17), dysexecutive MCI (dMCI = 23), and dementia (dementia = 14) groups. During the protocol, patients were given 60secs to provide animal exemplars. Memory was assessed with the P(r)VLT, a 6‐word verbal serial list learning test. Using artificial intelligence assisted scoring all ‘animal' fluency and P(r)VLT outcome variables including the ‘animal' Association Index (AI), where the mean number of shared attributes between successive responses were automatically tallied.ResultThe nl group generated more animal exemplars than all other groups (p< 0.001; Table 1). aMCI and dMCI patients generated more responses than dementia patients (p< 0.043, both analyses). NL and dMCI patients produced a higher, more semantically connected, ‘animal' AI than dementia patients (nl > dem; p< 0.025, both analyses). Regression analysis (dv = ‘animal’ AI; block 1 = age, education, sex; block 2 = recognition prototypic & generic foils) was significant (R2 = 0.145, p< 0.023); and found that a reduced, more impaired ‘animal' AI was associated with increasing numbers of P(r)VLT prototypic recognition foils (beta = ‐0.276; p< 0.024). Regression analysis (dv = ‘animal’ AI; block 1 = age, education, sex; block 2 = P(r)VLT semantic cluster responses, P(r)VLT extra‐list intrusion errors) was not significant.ConclusionIn addition to commonly used outcome measures such as total ‘animal' responses, this digital neuropsychological protocol scores a number of process variables, including the ‘animal' AI. The association between reduced ‘animal' AI and greater numbers of list learning prototypic recognition foils suggests combined episodic memory and semantic‐related impairment in selected patients. When brought to scale, automated analysis of neuropsychological process variables may aide in identifying emergent neurodegenerative illness.
Media Contribution to Dementia Awareness in Recruitment and Retention of Alzheimer’s Disease Diversity Genetic Cohorts‐ Alzheimer’s disease Sequencing Project in Africa
Authors: Farombi Temitope Hannah , Arulogun Oyedunni , Nichols Michelle , Olorunsogbon Olorunyomi F , Kumolu Timilehin , Ogunronbi Mayowa , Sanni Taofeek Adedayo , Mutiso Victoria , Uthman Muhammed , Sule Abdullateef , Assey Emmanuel , Mwombeki Innocent , Onoria Joy , Onunka Godspower Chibuke , Tagoe Benedict , Melkamu Selem K , Adigwe Ifeoma , Ogunyemi Adedoyin O , Gyabaah Solomon , Byrd Goldie S. , Ogunniyi Adesola , Pericak‐Vance Margaret A , Akinyemi Rufus O. 
Published: January 2025

AbstractBackgroundThe escalating prevalence of dementia in Africa, propelled by rapidly ageing population, necessitates innovative approaches to raise awareness and address associated challenges. The prevalent misconception of dementia as a result of witchcraft or wizardry is a challenge, and the media acts as a key agent in dispelling such myths. By reaching divers audiences, the media reinforces the notion that dementia is not confined to Africa alone but it is a global concern. It also aids in overcoming the shame and stigma associated with dementia, encouraging individuals to seek consultation.MethodA comprehensive analysis of media initiatives used by the African Dementia Consortium (AfDC) during the World Alzheimer’s Month and subsequently was conducted. Digital Platforms (Instagram, LinkedIn, Facebook), print and traditional media (publications, journals, newspaper, radio and television stations) were examined for their effectiveness in achieving recruitment objectives, destigmatizing and promoting early diagnosis. Quality tools, such as cameras and recorders, were utilized to capture relevant information, while the outcome was evaluated based on their impact on target audience assessed by greater participation.ResultMedia Platforms have proven instrumental in recruitment efforts by disseminating information that reaches diverse demographic groups in Africa. Through compelling visual and textual content, the media has played a key role in destigmatizing dementia, challenging prevalent misconceptions, and fostering a more inclusive understanding of the condition. In addition, media initiatives have contributed significantly to the promotion of early diagnosis by disseminating educational content that empowers individuals to recognize early signs and seek timely medical intervention.ConclusionBoth the digital and traditional media play vital roles in visually and textually representing dementia, correcting misconceptions, and fostering understanding. Allocating increased resources to media initiatives hold immense benefit for Africa, contributing to a more positive perspective on dementia and dispelling negative attitudes.
A longitudinal real‐world study in patients with Alzheimer’s Disease dementia using frequent multi‐domain digital measurements performed at‐home on the Cumulus Neuroassessment Platform: usability and feasibility findings
Authors: Diggin Shannon , Alexander‐Sefre Azar , Murphy Brian , Nolan Hugh , Rowe James B , Rueda‐Delgado Laura M , Buick Alison R 
Published: January 2025

AbstractBackgroundMany outcome measures used in AD clinical trials require clinic visits and are paper based, making them infrequent and burdensome ‘snapshots', subject to rater bias. A consortium of 10 pharma companies came together with Cumulus Neuroscience to design a solution for frequent, objective, real‐world measurement across a range of domains. We present a study that examined the feasibility of asking patients with mild dementia to use the neuroassessment platform repeatedly at home for one year.MethodSeven UK sites recruited Alzheimer’s type mild dementia patients (n = 59, ACE‐III scores >60 and = 88) and a matched cohort of controls (n = 60). Participants had 2 weeks of at‐home familiarisation to become comfortable with the 8 assessments presented on a mobile tablet and EEG headsets, one for wake and another for sleep. A staggered longitudinal protocol followed (Figure 1), with burst sampling tapering to periodic sampling over the year. Benchmark paper‐based assessments (including ADAS‐Cog) and self‐reported usability were collected at months 0, 6 and 12. Additionally, plasma was collected at months 6 and 12 for later biomarker analysis.ResultPreliminary results are available, with <1% expected at‐home sessions still outstanding (last patient out is scheduled for March 2024). Feedback collected at baseline (Figure 2) showed differences in technology usage. Patients felt they required more technology support than controls (49% vs 17%). Nonetheless, they were successful in using the study technology at home on a regular basis and maintained a high level of adherence to the protocol (Figure 3). Overall compliance was 72.9% for dementia, 87.5% for controls and was highest in the latter stages of the study during periodic sampling (Stage 4: 80.1% dementia, 92.6% controls). System Usability Scale results indicated controls rated usability higher (63.8) than dementia participants (54.5) at baseline, increasing for both groups by Week 26 (71.8 controls; 62.2 dementia).ConclusionWith appropriate technology design, and provision of training and support, patients with Alzheimer’s disease dementia are capable and willing to provide repeated, real‐world samples of a broad range of objective digital endpoints for clinical research.
Assessing a Digital Lifestyle Intervention to Reduce Dementia Risk in Older Adults
Authors: Bunyan Maria , Irving Jessica , Barnett Jennifer H , Kawadler Jamie , Bauermeister Sarah , Vassilev Philip , Gallacher John , Koychev Ivan 
Published: January 2025

AbstractBackgroundAn estimated ∼40% of dementia cases are due to modifiable risk factors which can be targeted in lifestyle interventions. Effective interventions employ face‐to‐face delivery, making them resource‐intensive and burdensome. Digital interventions offer scalability, accessibility and cost‐effectiveness. Engagement and efficacy of digital interventions are unknown, as is whether the ‘human component' of these interventions must be retained.MethodThe Five Lives app is a digital health solution that combines a CE‐marked dementia risk assessment with a digital coaching programme (DC) to facilitate behaviour changes which could lead to eventual reduced dementia risk. Three groups were compared: DC‐only, DC and access to brief 1‐to‐1 virtual clinician services (DC+VC) and no intervention (control). The study spanned 12 weeks and participants (n = 154) were aged 50‐69 with normal cognition. A lifestyle score was conducted at baseline and exit, which scores participants on behaviour relating to sleep, physical activity, diet, stress & mood and mental stimulation. Engagement was measured as the total number of app activities (brain games, articles, quizzes and lifestyle log) completed during the intervention period.ResultParticipant engagement was high (mean participant activities = 35/week). There was a significantly greater change in lifestyle score between intervention group (DC‐only and DC+VC pooled) and control (F(1,81) = 3.10, p = 0.049), and a trend for significance for a greater change in DC‐only versus control (F(1,24) = 3.96, p = 0.058). The change in lifestyle score between DC‐only and DC+VC was not significant, nor was the difference in app engagement. Total engagement was not predictive of lifestyle score change.ConclusionParticipant engagement indicates the intervention is feasible in older adults. Results suggest the Five Lives app is a promising tool to facilitate behaviour change to potentially reduce dementia risk, and the VC does not provide significant additional benefits. This study provides initial data to warrant further development of DC interventions to reduce dementia risk. Future analyses should investigate which participants respond best to the intervention, barriers to change, and how engagement interplays with sustained dementia‐targeted lifestyle change.
Evaluating Sociodemographic Bias in an Artificial Intelligence Algorithm to Detect Cognitive Impairment in Electronic Health Records
Authors: Magdamo Colin G. , He Yignan , Dickson John R , Tyagi Tanish , Westover M. Brandon , Mukerji Shibani , Ritchie Christine S , Hyman Bradley T. T , Blacker Deborah , Das Sudeshna 
Published: January 2025

AbstractBackgroundUnderdiagnosis of Alzheimer’s disease and related dementias (ADRD) leads to lost opportunities for timely intervention, increased healthcare costs, and underestimation of the true burden of disease. To address this problem, we developed an AI algorithm, Decipher‐AI (DEtection of Cognitive Impairment PHenotypes in EHR), to screen primary care patients for undiagnosed cognitive impairment (CI). We evaluated performance across sociodemographic groups using 3 years of EHR data before the first diagnosis or most recent visit.MethodDecipher‐AI employs a two‐level hierarchical model, consisting of a large language model (LLM) to generate latent representations from unstructured clinical text and a patient‐level model that combines these representations with structured EHR data to predict the probability of CI (AUC: 0.98, 95% CI: 0.94, 1.00). Decipher‐AI was evaluated on a test set comprising 22,000 Mass General Brigham primary care patients aged 65 years or older. The selection process involved stratified random sampling across distinct racial/ethnic strata to ensure representation of diverse sociodemographic factors (Table 1). Cognitive status labels were determined based on the presence of dementia‐related diagnosis codes, while sociodemographic status was measured using the Area Deprivation Index (ADI).ResultThe AUC on the validation dataset was 0.80 [95% CI: 0.79, 0.81]; sensitivity was 0.75 [0.74, 0.77] and specificity 0.68 [0.67, 0.69], at the threshold of maximum accuracy. There were no significant differences in AUCs across sex or race/ethnic subgroups, but AUC was lower for patients under 75 years. (Figure 1A). Notably, Decipher‐AI exhibited diminished performance in patients from more disadvantaged neighborhoods (Figure 1B). Further analysis revealed that these disparities were associated with fewer encounters, outpatient visits, and notes containing cognition‐related keywords in patients from disadvantaged neighborhoods (Table 2).ConclusionOur study highlights the potential of Decipher‐AI for screening undiagnosed cognitive impairment in primary care. Nevertheless, disparities in algorithm performance underscore the importance of addressing sociodemographic inequities in EHR data. In the future, systematic tailored screening in primary care via standardized questionnaires coupled with AI‐assisted chart reviews, has the potential to address the underdiagnosis of ADRD in an equitable manner.