bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factors associated with the cognitive performance of healthy older adults and persons living with Alzheimer’s disease from a middle‐income country in Latin America
Authors: Palma Leticia Fernanda , Pulgatti Karen Letícia , Victoriano Pedro Henrique Moreira , Rebecchi Laís , de Sousa Danilo Barroso , Grigoli Marina Mantellatto , Popolin Cecilia Patricia , da Silva Vanessa Alexandre , de Oliveira Sabrina Dorta , Manzine Patricia Regina , Cominetti Márcia Regina , Pelegrini Lucas Nogueira de Carvalho 
Published: January 2025

AbstractBackgroundLow‐ and middle‐income countries (LMIC) share characteristics, such as low education, that increase the risk of dementia among their population. Critically, around 70% of the cases of dementia in LMICs are underdiagnosed. Understanding factors contributing to older adults’ cognitive performance may support healthcare professionals from these countries in their decision‐making process when screening for cognitive decline in their communities. This study aims to analyze factors associated with the cognitive performance of older adults from a Latin American country.MethodThis is a cross‐sectional and analytical study whose participants (n = 92) were healthy older adults (n = 74) and persons living with Alzheimer’s disease (PLwAD) (n = 18) who lived in a middle‐income Latin American country (Brazil). For assessment, the following instruments were used: a sociodemographic questionnaire, the Addenbrooke’s Cognitive Examination‐Revised (ACE‐R), the Mini‐Mental State Examination (MMSE), Geriatric Depressive Scale (GDS‐15), and the Pfeffer Functional Activity Questionnaire (FAQ). Descriptive, linear regression and mediation analyses were performed on SPSS (version 29.0) and PROCESS for SPSS (version 4.1). The significance level was set at p<0.05.ResultPLwAD were older (t = ‐5.27; p<0.001; 95%CI [‐13.12 to ‐5.75]), had less years of formal education (t = 4.16; p<0.001; 95%CI [2.94 to 8.60]), worse cognitive performance (ACE‐R‐ t = 8.41; p<0.001; 95%CI [31.84 to 52.78] / MMSE‐ t = 9.32; p<0.001; 95%CI [8.96 to 13.82]), and worse functionality (FAQ‐ t = ‐14.31; p<0.001; 95%CI [‐20.25 to ‐15.31]). GDS‐15 scores did not differ between groups (t = ‐0.81; p = 0.423; 95%CI [‐2.27 to 0.93]). Age (B = ‐0.575; t = ‐2.96; p = 0.004), years of education (B = ‐1.073; t = 5.44; p<0.001), and functionality (B = ‐1.593; t = ‐9.99; p<0.001), were significantly associated with cognitive performance, as per ACE‐R scores (R2 = 0.799; F = 102.27; p<0.001). Finally, mediation analysis suggested that years of education mediate the effect of FAQ on ACE‐R scores (total effect = ‐2.15; p<0.001 / direct effect = ‐1.78; p<0.001 / indirect effect = ‐0.3558; 95%BCaCI [‐0.61 to ‐0.18]).ConclusionThese findings align with existing literature, yet they present a novel perspective within this population. Results demonstrate that age, education, and functionality are associated with cognitive performance, emphasizing their relevance in the screening/assessment. Our data also suggests that years of education mediate the relationship between functionality and cognitive performance.
Feasibility of Older Adult Remote Self‐Installation of Passive Sensor Assessment Technologies
Authors: Gothard Sarah , Rodrigues Nathaniel , Irish Stephanie , Kaye Jeffrey A , Beattie Zachary T , Lindauer Allison 
Published: January 2025

AbstractBackgroundConducting research remotely in aging and Alzheimer’s disease related (ADRD) populations using multiple passive sensing technologies (e.g., activity watches, electronic pillboxes, bed‐mats, wall‐mounted sensors) provides opportunities for greater inclusiveness and more ecologically valid data capture. A challenge to this approach has been the need to enter homes to deploy and/or maintain devices or technologies. To overcome this limitation, we developed and tested a novel protocol for entirely remote self‐deployment of technologies.MethodResearch participants in 14 households (age = 70.8±7.2 years; 61.5% female; education = 16.5±2 years; telephone MoCA = 21±1.6, days of follow‐up = 834.9±604.7) in an aging and dementia study were sent an online accessible Remote Installation Manual to guide independent installation of technologies in their homes. The manual included technology overviews, video installation tutorials, and written step‐by‐step instructions for each device. Eight separate sensing technologies could be deployed in each home (PIR motion sensors, contact door sensors, activity watches, wireless body composition scale, bed mats, driving sensors, and a data hub aggregating computer). Participants could request installation support, if necessary. The success of self‐deployment was compared to 22 study homes, which were installed in‐person by study field technicians.ResultFour of 14 participants deployed the technologies entirely using only supplied instructions: 10/14 participants required assistance with at least one aspect of installation; all issues were resolved through remote contact. Data recovery and maintenance issues between the participant‐installed homes and the 22 technician‐installed homes were not different. The median percentage of days with technical issues were similar (volunteer = 2.3%; technician = 1.4%). The percentage of days of captured data for watches, bed‐mats, and electronic pillbox use were similar or better for volunteer‐installed homes (watch: volunteer = 72.9%, technician = 70.6%; bed‐mat: volunteer = 72.0%, technician = 67.2%; pillbox: volunteer = 72.0%, technician = 68.5%).ConclusionOlder adults are readily able to deploy remote assessment technologies without study personnel needing to travel to or enter a residence. Data generation and technical issues related to the research technologies are comparable between study participant self‐deployment and technician‐deployment, demonstrating feasibility and effectiveness of remote older adult self‐deployment of study technologies. The ability to deploy digital technologies for continuous, objective and ecologically valid assessments anywhere with internet access may greatly broaden the inclusiveness of ADRD research.
What does it take to assess dementia in community‐dwelling immigrant older adults with limited English proficiency? – A case of Korean Americans
Authors: Han Hae‐Ra 
Published: January 2025

AbstractBackgroundCurrently, there is no national consensus on how to identify individuals with probable dementia in community‐based settings. With the rapid increase of aging populations—particularly ethnic minorities—there is an urgent need to create a process to effectively identify individuals with probable dementia to adequately plan for dementia care. The aim of this study was to evaluate a dementia screening approach applied to a recent immigrant community, Korean Americans.MethodPLAN—Preparing for healthy aging through dementia Literacy education And Navigation—is an ongoing trial involving community‐dwelling Korean older adults with probable dementia and their care partners in the greater Washington and metropolitan New York areas. Data for the current analysis came from: community coordinator logs, recruitment tracking notes, and participant enrollment database.ResultThe study team developed a two‐phase screening process to ensure accurate assessment of dementia status: (1) Mini‐Mental Status Exam (MMSE) and (2) Clinical Dementia Rating (CDR). The screening protocol was written so once the first‐phase screening meets the pre‐established criterion (MMSE<24), the older adult‐caregiver dyad is invited to a CDR interview to confirm the dementia status. Given lack of bilingual/bicultural geriatric workforce in the community, bilingual community health workers (CHWs) were trained to conduct both screenings. As of January 19, 2024, trained CHWs screened 2,693 older adults using MMSE; 584 of them (21.7%) were screened positive and invited to the second‐phase screening using CDR. More than two thirds (n = 392 or 67.1%) agreed and participated in CDR assessment; 309 of them (or 78.8%) received a score of 1+, indicating probable dementia.ConclusionWe were able to train bilingual CHWs to conduct dementia screenings in one of the most understudied and underserved Asian immigrant communities. The prevalence of dementia was more than 20% in the screened sample, compared to 6%∼13% in the general US older population. Nearly four of five among the MMSE positive sample were confirmed to have a substantial functional decline based on CDR, indicative of probable dementia. When working with resource‐poor communities, our approach of mobilizing community assets (CHWs) and combining a brief cognitive screener with a refined functional measure can help identify older adults with probable dementia.
Importance of digital skills in attitude towards the use of smartphones and usage behavior in ederly population
Authors: Benitez Estela , Sarmiento Elsa Araceli Revollo , Moreno Maria Celeste López , Vera Rocio Micaela , Vivas Leticia 
Published: January 2025

AbstractBackgroundThe use of technology in elderly population has increased in the past years due to COVID‐19. Therefore it is relevant to identify the factors that contribute and limit the effective use of technology by older people. In particular, digital skills have shown to be relevant to determine the attitude toward the use of technology and consequently to have an effect on usage behavior. The aim of the current poster is to analyze the relations between this variable and the use of smartphones.MethodWe employed a correlational design with a non‐probabilistic for convenience sample including 139 elderly (56.9% women). The age ranged from 60 to 90 years, with a mean of 71.1 (DS = 6.62). Participants were administered the Digital Competencies Questionnaire (Heredia & Garcia, 2017), the acceptance questionnaire for the STAM model smartphone (Chen & Chan, 2014) and questionnaire to assess usage behavior called SAMCOP (Ma et al., 2016)ResultFirst, a correlation analysis was performed between digital competencies (DC) and the variables of the STAM and it indicated a positive correlation between DC and self‐efficacy in use (r = .456; p < .001), facilitating conditions (r = .434; p < .001), perceived usefulness in use(r = .508; p < .001), perceived ease of use (r = .425; p < .001), attitude towards use (r = .594; p < .001), and a negative correlation with anxiety towards use with the use of technology (r = ‐.323; p < .01). Furthermore, a linear regression analysis was performed to identify the influence of DC on SAMCOP. The results indicated an influence of DC on frequency of smartphone use (p < .001; R2 = .245); experience in smartphone use(p < .001; R2 = .175); and most frequently used apps (p < .01; R2 = .0801), but no influence on number of installed apps (p = .491).ConclusionThe results demonstrate a direct relationship between digital competencies and smartphone acceptance variables. This indicates that greater digital competencies lead to higher smartphone acceptance and reduced anxiety in the elderly. These competencies also influence smartphone usage behavior in old age, highlighting the importance of promoting digital skills among the elderly.
Designing a Comprehensive Family Caregiver Assessment: Insights from a Multidisciplinary Professional Panel
Authors: Gholizadeh Shadi , Neal Matthew , Hayes Kirk , Geiss John Mark 
Published: January 2025

AbstractBackgroundThe imminent launch of the Guiding an Improved Dementia Experience (GUIDE) Model necessitates a nuanced understanding of family caregiver needs to support the implementation of family‐centered dementia care plans. Recognizing the multifaceted role of family caregivers, a preliminary working session was convened to outline the foundational elements of a family caregiver assessment, ensuring these assessments are equipped to guide effective interventions.MethodA multidisciplinary panel consisting of a clinical psychologist, two health care executives, and a physician with geriatric expertise convened to delineate components of a caregiver assessment tool to supplement the Zarit Burden Interview. The panel, representing diverse expertise within the elder care setting, engaged in discussions focused on the challenges caregivers face, the support they require, and the pivotal information that could enhance care delivery. The session aimed to consolidate professional insights in order to develop a focus group interview guide as a precursor to engaging with the broader caregiver community.ResultThe panel identified essential domains for the caregiver assessment, including caregiver’s understanding of dementia, behavioral modification strategies, navigation of healthcare systems, and caregiver health behaviors. It was determined that each of these domains should be developed after literature review and insights from family caregivers. Five areas that were highlighted as often missed but crucial to include in an assessment were 1) the caregiver’s understanding of anosognosia as a dementia symptom, 2) a plan and goal setting for what the caregiver would do during respite times, 3) caregiver health behaviors, 4) cultural considerations around caregiver roles and identity and 5) learning preferences. Failing to consider language/cultural preferences and preferred modalities of support modalities emerged as a common barrier to caregiver engagement, affecting care plan acceptance.ConclusionRecognizing the preliminary nature of this professional panel’s insights, the next phase will involve conducting extensive focus groups with family caregivers to validate and expand upon these findings. This subsequent step is pivotal in ensuring the assessment tool captures the authentic voice, needs, and preferences of caregivers, thereby facilitating the delivery of comprehensive, person and family‐centered dementia care.
Using Natural Language Processing to identify text for qualitative research into the lived experience of people with dementia
Authors: Shapiro Lily N. , Bowers William I , Ehrlich Kelly , Maripuu Tiina , Peterson Jenna Mae , Gray Marlaine Figueroa , Sankaran Sundary , Crane Paul K. , Taylor Janelle S , Penfold Robert B 
Published: January 2025

AbstractBackgroundMedical records present a rich potential source of information on the lived experiences of people with dementia. These records are extensive and the work of extracting relevant data is labor‐intensive. We sought to determine whether we could use natural language processing (NLP) approaches to sift through medical records to prioritize an enriched subset of notes illuminating the lived experiences of people with dementia.MethodsWe identified an analytic cohort of adults aged ≥ 65 years from the Adult Changes in Thought (ACT) Study, a prospective cohort study of dementia in Seattle, WA. We collected a corpus of 254,532 notes from the electronic medical records (2003‐present) of these participants. The corpus included a range of clinical encounters from five years prior to dementia onset to most recent visit. We implemented an NLP algorithm, pytakes, which extracted concepts from notes in our corpus. The concepts were codes adapted from a prior qualitative study, which we further refined for this study. We used these concepts to curate smaller sub‐corpora for manual, qualitative review.ResultsStarting with 32 unique concepts, pytakes extracted over 1.7 million concepts. 178,042 notes (69.94% of the original corpus) had at least one associated concept. Preliminary review of notes extracted showed acceptable concurrence between the text retrieved and the target concepts. Leveraging the extracted concepts, we curated, then randomly sampled 500 notes for three sub‐corpora, each aimed at a different research question. The first investigates the topics and timings of patient‐ or caregiver‐initiated communications with the healthcare system. The second relates to caregiving needs and networks of people with dementia and how these shift over time. The third revolves around housing situations and transitions of people with dementia. Our qualitative team is examining these sub‐corpora to investigate the lived experience of people with dementia.ConclusionsNLP tools may be a productive method for identifying materials suited to qualitative inquiry into the lives of people with dementia. This innovative approach can provide access to data that would otherwise be difficult to obtain, offering insight into the lived experiences, care needs, living situations, and social networks of people living with dementia.
Electronic Health Record‐Embedded Dementia Screening Toolkit Tailored for Bilingual and Bicultural Needs
Authors: Shah Samantha , Huerta Gabriela Islas , Wang Kevin , Wadhwa Satpal S. , Diaz‐Santos Mirella , Vossel Keith , Chang Timothy S 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is a significant health concern affecting at least 10% of individuals aged 65 and older, with heightened risk in Black and Hispanic/Latino populations. Despite this prevalence, our analysis of University of California Los Angeles (UCLA) electronic health records (EHR) indicates that only 4% of patients aged 65 or older receive an AD diagnosis, with underdiagnosis more prevalent among Black and Hispanic/Latino patients compared to their white counterparts. To address this issue, we propose implementing a concise dementia screening tool (DST) in real‐world clinical settings.MethodThe DST, developed through collaborative efforts among multiple University of California AD Centers and the California Department of Public Health, is a brief (<5 minutes) screening tool. It includes a three‐question questionnaire for patients and, if available, their informants, followed by the Mini‐Cog assessment if applicable. The questions address changes in language, memory, and personality. A positive DST result is defined as any “Yes” response by the patient or informant to any question or a Mini‐Cog score below 3 out of 5 points. We have also created a Spanish version of the questionnaire tailored to the Hispanic/Latino cultural context.ResultIntegration of the DST into the EHR system facilitates a seamless implementation. Patients receive questionnaire through the EHR messaging system before appointments, with the Spanish version available for those who prefer it. Responses and Mini‐Cog results are easily accessible in the EHR. Additionally, a documentation link automatically populates DST results, final scores, and recommendations into provider notes.The DST is currently in use at a large, diverse UCLA family medicine clinic serving Hispanic/Latino and Black patients. In the first fourteen months, 1,963 patients (Table 1) were seen, with 28% self‐identifying as Hispanic or Latino. Among them, 1,070 patients answered at least one question, and 340 completed the Mini‐Cog (Table 2). Notably, 31 patients received a new dementia diagnosis, and 81 were referred to Neurology.ConclusionOur implementation of the DST in a diverse clinical setting has successfully screened 1,070 participants, with future research comparing data from the DST period with a pre‐time period.
Exploring Semantic Topics in Dementia Caregiver Tweets
Authors: Feng Yanbo , Hou Bojian , Klein Ari , O'Connor Karen , Chen Jiong , Mondragón Andrés , Yang Shu , Gonzalez‐Hernandez Graciela , Shen Li 
Published: January 2025

AbstractBackgroundCaring for family caregivers of dementia patients has grown to an important topic. Social media platforms, like Twitter, provide great resources for studying the needs of caregivers. It would be beneficial to understand the caregivers’ interested or concerned topics from their tweets. Meanwhile, topic modeling has become an efficient NLP tool for analyzing semantic themes within texts. Thus, in this study, we perform a novel topic model leveraging weighting strategies to analyze dementia‐caregiver‐related twitter data.MethodThe information about the twitter data collection is available at: https://aging.jmir.org/2022/3/e39547. In our analysis, we first performed quality control, as shown in Figure 1. Then, we deployed two word‐frequency weighting strategies, Log weighting and Balanced Distributional Concentration (BDC) weighting, on the Dirichlet Multinomial Mixture (DMM) model to obtain 4 DMM variants and used them to mine semantic topics within the tweets. We compared the performance of DMM variants, LDA variants, and BERTopic variants. Topic numbers of 5, 10, 15, 20 were picked to achieve comprehensive comparison. The coherence score C_V was applied to evaluate the model performance. We then leveraged the GPT‐4 to summarize the bag of words in each topic from the best model to generate interpretable themes.Result224,862 tweets passed the quality control and were analyzed in our study. As shown in Figure 2, the performance evaluation demonstrated that the Log‐BDC DMM has the best general performance among traditional and BERT‐based models, with an averaged coherence score of 0.5648. The bags of words from the Log‐BDC DMM with 10 topics were interpreted using GPT‐4 due to the highest coherence score of 0.6054. The interpretation yielded 10 semantic themes, as shown in Figure 3.ConclusionOur investigation of the twitter data shows that the DMM model with Log and BDC strategies has promising power for mining meaningful semantic topics from short and noisy tweets. The model outperforms LDA models and the BERTopic models while maintaining high model interpretability. This initial study on twitter data provides interesting findings that can provide better care to family caregivers and demonstrates the promise and interpretability of traditional topic modeling methods.
Attitudes and Perceptions of Caregivers of person with Frontotemporal Dementia in Peru: Preliminary results
Authors: Castro‐Suarez Sheila , Illanes‐Manrique Maryenela Z. , Meza‐Vega Maria , Cuenca José , Lanata Serggio , Cornejo‐Olivas Mario 
Published: January 2025

AbstractBackgroundFrontotemporal dementia (FTD) is a clinical syndrome characterized by progressive changes in behavior, executive function, or language. In Latin America, persons with FTD are underrecognized or diagnosed late. There is a lack of knowledge about the experiences have on families.MethodWe used a mixed methods approach consisting of qualitative, semi‐structured interviews that were recorded, transcribed, and analyzed using thematic analysis. Local IRB approval was obtained for this study.ResultWe interviewed fourteen family caregivers of persons with FTD, ten of them (71.4%) were caregivers of persons with behavioral variant FTD (bvFTD). There was female predominance (78.5%). The average of education was 14.5±2,3 years. Half were sole caregivers, seven were children, five were spouses, and two were sisters. The key themes emerging from qualitative interviews were difficulties surrounding the diagnostic process, the impact of knowing the diagnosis, and challenges surrounding caregiving. Caregivers stressed how tedious it is to access health services and obtain specialized care and the lack of knowledge of the disease among health professionals. Caregivers commented on the perceived lack of skills of some professionals when informing about the diagnosis and prognosis of a neurodegenerative disease. Knowledge of FTD prognosis generates anguish, hopelessness, and frustration among caregivers. Caregivers who are sons or daughters often adopt leadership roles within the family, especially from financial and caregiving point of view. They also often change or postpone life/professional plans. On the other hand, if the caregiver is the wife or husband, the absence of their partner in the home stands out as a main stressor, even though they remain together.ConclusionOur preliminary results highlight the importance of providing accessible, plain‐language education and support to caregivers of persons with FTD, as well as the opportunity to improve training on healthcare professionals. The impact of caring for patients with FTD appears to be dependent on the parental relationship.