bluuebunny/crossref_metadata_2025_split huggingface dataset:
RACIAL RESIDENTIAL SEGREGATION AND SUICIDAL BEHAVIOR ACROSS THE LIFECOURSE AMONG BLACK AMERICANS
Authors: Kahsay Eskira , Mezuk Briana 
Published: January 2025

Abstract
Residential segregation is a well-studied contextual factor with adverse impacts on physical health. However, the neighborhood is both a material and social space. Given hypothesized mechanisms of increased social support and reduced discrimination, racial/ethnic homogeneity may not be necessarily harmful to mental health. Still, little is known about its implications for suicidality among Black Americans, particularly older adults. This study investigated the associations between residential segregation and suicidal behavior using the National Survey of American Life (N = 5,191; mean age: 42.5). Lifetime suicidal behavior (ideation [10.4%] and attempt [3.6%]) were self-reported. The Getis-Ord Gi* statistic was used to measure the spatial segregation of Black residents at the census-tract level (low, medium, high). Weighted mixed-effects models were fit, adjusting for demographics and tract-level poverty and stratified by age group (early [18-29], middle [30-49], older adulthood [50+]). The prevalence of ideation and attempt did not significantly differ across segregation levels. Odds of ideation were not significantly different in high vs low segregation areas though were significantly lower in medium vs low segregation areas (OR = 0.70, 95% CI: 0.49, 0.99). Findings for suicide attempt were non-significant. Among older adults, the odds of attempt were significantly lower for high vs low segregation areas (0.98, 95% CI: 0.97, 0.99) only. No significant findings were found for other age groups, except ideation in medium vs low segregation in early adults (OR = 0.33, 95% CI: 0.15, 0.74). Despite economic disadvantage in racially segregated areas, findings suggest higher segregation is not associated with increased suicidality.
RACIAL DIFFERENCES IN PREDICTORS OF CARDIOMETABOLIC RISK FOR OLDER US WOMEN
Authors: Erving Christy , Davidson-Turner K J , Frazier Cleothia , Coats Jacquelyn 
Published: January 2025

Abstract
Though cardiovascular disease is the leading cause of death among women, significant racial disparities in cardiovascular disease persist. This study investigated psychosocial predictors of cardiometabolic risk (CMR), a count of high-risk cardiovascular and metabolic biomarkers, among older U.S women and whether predictors differed for Black, and Hispanic, and White respondents. Data were from the Health and Retirement Study (HRS; age 50 years+). Predictors including health behaviors, socioeconomic status, psychological factors, and relational demands (with spouse, children, relatives, friends) were drawn from the 2010/2012 waves. CMR, drawn from the 2014/2016 waves, was assessed using six biomarkers: pulse pressure, resting heart rate, C-reactive protein, waist glycosylated hemoglobin A1c, and total and high-density lipoprotein cholesterol. The sample comprised 6707 women (1197 Black, 672 Hispanic, 4838 White). Linear regression analyses were conducted to assess the association between the predictors and CMR in race-stratified models. Preliminary results revealed that predictors of CMR were distinct for different racialized groups. Specifically, for Black women, obesity and former smoking status were associated with increased CMR while working part-time was associated with decreased CMR. Among Hispanic women, having a GED or high school diploma (compared to less than a high school education) was associated with decreased CMR. Among White women, obesity, smoking, depressive symptoms, and having no spouse were associated with increased CMR while higher education, working part-time, and mastery were associated with decreased CMR. Surprisingly, no one factor was a predictor of CMR for all women; moreover, relational demands did not emerge as a significant predictor of CMR.
A LONGITUDINAL ANALYSIS OF EVERYDAY DISCRIMINATION
Authors: Wheaton Felicia 
Published: January 2025

Abstract
Experiences of everyday discrimination are associated with poorer mental and physical health in later life. However, most studies examine discrimination at a single time point. There is a need to better understand how experiences of everyday discrimination change over time, change with age, and differ by cohort. This study examined longitudinal change in everyday discrimination using data from the 2006-2020 waves of the Health and Retirement Study (HRS), a nationally-representative study of Americans 50+ (N=23,523). Frequency of everyday discrimination was summed across 5 items: you are treated with less courtesy or respect than other people, receive poorer service than other people at restaurants or stores, are threatened or harassed, people act as if the think you are not smart, and act as if they are afraid of you (1=never, 6=almost every day). Overall, everyday discrimination discrimination decreased from 2006 until 2016 when it peaked again, then fell through 2020. Average everyday discrimination increased across cohorts, with the oldest cohort (born before 1924) having the lowest average discrimination and the late Baby Boomers (born 1960-1965) experiencing the highest average discrimination. Across waves, as people aged, their discrimination scores decreased. The adjusted linear mixed model confirmed these trends: age was negatively associated with everyday discrimination and younger cohorts reported higher everyday discrimination. These findings indicate that age, period and cohort differences exist in experiences of everyday discrimination, and this has important implications for health across the life course.
NAVIGATING REAL-WORLD BARRIERS IN NURSING HOME PRAGMATIC TRIALS
Authors: Snow A Lynn , Snow A Lynn 
Published: January 2025

Abstract
Nursing homes (NHs) are an important setting for the use of pragmatic clinical trial (PCT) approaches, particularly due to the challenging implementation environments since the COVID-19 pandemic. NHs have well documented, long-standing quality challenges, staffing shortages, and substantial time gaps between the development of new evidence and innovations and their wide-spread industry adoption. Thus, NHs are an opportune setting for the development of pragmatic methods to accelerate the adoption of efficacious interventions into practice. In this symposium we explore successful approaches used in current NH PCTs to address five common challenges: organizational partnerships, intervention adaptation, use of technology in PCTs, pragmatic measurement of outcomes, and evaluating intervention-related staff competencies. We will explore each topic through an example from one or two recent NH PCTs, sharing challenges and successes. The discussant and panel will then examine the topics across all four represented PCTs and consider applications to future PCTs.
PATIENT-CENTERED OUTCOME MEASUREMENT IN NURSING HOME-BASED PRAGMATIC TRIALS: CAPTURING WHAT COUNTS
Authors: McCreedy Ellen , Sisti Anthony , Gutman Roee , Baier Rosa , Reddy Ann , Mor Vincent 
Published: January 2025

Abstract
Embedded pragmatic randomized controlled trials (ePCTs) rely on routinely collected data to evaluate study outcomes. Using data from Music & MEmory: A Pragmatic TRial for Nursing Home Residents With ALzheimer’s Disease (METRIcAL), we highlight the strengths and weaknesses of using routinely collected data to evaluate agitated behaviors in nursing home (NH) residents with dementia. We conducted two National Institute on Aging-funded ePCTs, one enrolled 976 residents (483 treatment, 493 control) from 54 NHs between June, 2019 and March, 2020, and the other enrolled 850 residents (431 Treatment, 419 control) from 54 NHs between May, 2021 and September, 2022. In both trials, there was no effect of the intervention on agitated behaviors, as measured by the Minimum Data Set (MDS), a routinely collected, pragmatic source of data in NHs. The intervention also did not affect behaviors as reported by staff using the Cohen-Mansfield Agitation Inventory (CMAI). However, we found a reduction in the frequency of nonaggressive agitated behaviors in response to the personalized music intervention, using the Agitation Behavior Mapping Instrument to conduct structured observations of residents, at standardized times of day, in treatment and control NHs. A personalized music intervention for NH residents with dementia reduced nonaggressive agitation, but these changes were not captured in the routinely collected administrative data (MDS) or by interviewing staff using the CMAI. Temporary reprieve from agitated behaviors may improve the quality of life for persons living with dementia, but these effects are not captured using pragmatic data or tools that rely on staff recall.
SYSTEMATIC EVALUATION OF ADAPTATIONS AND FIDELITY IN PRAGMATIC NURSING HOME CLINICAL TRIALS
Authors: Hilgeman Michelle , Madrigal Caroline , Curyto Kimberly , Ott Corilyn , Geisser Sophia , Hartmann Christine , Snow A Lynn 
Published: January 2025

Abstract
Adaptation of interventions to local contexts is often required for sustainable implementation. Yet maintaining and measuring fidelity to an intervention’s core components is necessary during pragmatic clinical trials. We systematically addressed this inherent tension across two studies of Montessori approaches for person-centered care in Department of Veterans Affairs (VA) nursing homes. We first conducted a 3-phase pre-implementation study (2018-2021) to adapt Montessori for VA with input from operations partners, frontline clinical teams, long-term care residents, implementation scientists, and intervention developers. We used the Framework for Reporting Adaptations and Modifications-Enhanced (FRAME) to track changes in real-time using qualitative and quantitative data at eight VAs. Primary motivators for adaptation were expanding reach of the intervention and engagement with staff training/delivery. Next, the adapted Montessori intervention was tested in a pragmatic, randomized stepped-wedge clinical trial at eight additional VAs (2021-2023). Diverse frontline staff (e.g., nursing assistants, nurses, therapists) delivered the intervention to all residents. Low burden methods were used to gather reach, implementation, and fidelity data over 12-months (i.e., 15-minute weekly neighborhood check-ins, individual staff surveys, organizational-level fidelity tools completed by the clinical team). Adherence to and delivery of the intervention remained high at most sites over time across all measures. Evidence of fidelity and sustained use across sites in the trial may be attributed to the fit of the adapted Montessori intervention with the needs, resources, and clinical priorities of VA long-term care residents and staff.
PILOT FEASIBILITY STUDY OF EMR-BASED IDENTIFICATION OF PSYCHOLOGICAL DISTRESS AROUND RECENT DEMENTIA DIAGNOSES
Authors: Bannon Sarah , Divecha Ayushi , Dams-O’Connor Kristen , Federman Alex 
Published: January 2025

Abstract
ADRDs have a significant impact on individuals, families, and systems. Though technological advances have enabled earlier diagnoses, early psychological distress experienced around the time diagnosis is largely overlooked. Psychological distress is an important early intervention target given its pronounced negative impact on ADRD adjustment. Interventions are limited by our insufficient understanding of psychological distress experienced around the time of ADRD diagnoses. Our primary objective was to investigate the feasibility of identifying EMR-based psychological distress in a diverse sample of individuals with recent ADRD diagnoses. We conducted secondary data analysis of EMR records obtained from the Mount Sinai Data Warehouse (MSDW) and identified N=12249 individuals with recent ADRD diagnoses after age 65. ICD-10 diagnoses of depression and anxiety were identified in (32.73%) and (27.58%) of the sample, respectively. We also examined scores above the standard cut-offs for clinically elevated distress using self-report measures of depression [PHQ-9 (&gt;=10)] and anxiety [GAD-7 (&gt;=10)]. Unfortunately, these measures were assessed in a very small proportion of the sample at the visit of dementia diagnosis. Out of 509 (4.1%) individuals with self-report measures available, 113 (22%) indicated clinically elevated distress.. Structured data elements can be used to identify distress in the context of dementia diagnosis, though they are limited in their administration and may only offer the potential to identify distress in a subset of individuals. Our findings emphasize the importance of further exploration of unstructured data elements to identify distress.
USING SUPERVISED MACHINE LEARNING METHODS TO IDENTIFY INDIVIDUALS AT RISK OF DEMENTIA
Authors: Divecha Ayushi , Bannon Sarah , Dams-O’Connor Kristen 
Published: January 2025

Abstract
There has been an increased interest in AI and machine learning based models in early detection and diagnosis of Alzheimer’s disease (AD) and Alzheimer’s disease related dementia (ADRD). However, there is a need for feasible tools to identify individuals at risk of AD/ADRD using machine learning methods that can be validated. Early identification of risk of AD/ADRD can be valuable for building a monitoring system and planning of care. The aim of the study is to identify individuals at risk of developing dementia at baseline visit using machine learning models. Clinical and cognitive data from 5 of the largest NIH-funded studies of aging across the US (ACT, ROS, MAP, MARS, FHS) will be used to predict all-cause dementia in cognitively normal individuals at baseline using random forest models with competing risk of death. Cognitive elements like executive functioning, language, memory, visuospatial ability will be included. Since cognitive function was assessed using different measures across cohorts (MMSE and CASI), co-calibrated cognitive factor scores will be used in the trained models to allow for direct comparison of cognition across cohorts and joint analyses. We examined 3 out of 5 cohorts. From ROS/MAP/MARS cohorts, 2235 individuals qualified for the study and had a mean follow-up of 8.6 ± 5.3 years. AOC will be used to assess sensitivity and specificity of the trained models (75% training set, 25% testing set) with each of the 5 cohorts. The models will also identify features important in predicting dementia.
PRESIDENTIAL SYMPOSIUM: EMBRACING ENGAGED TEACHING, RESEARCH, SERVICE, AND POLICY TO STRENGTHEN GERONTOLOGICAL EDUCATION
Authors: Fruhauf Christine , Newsham Tina 
Published: January 2025

Abstract
It takes fortitude for GSA members to embrace engagement in their academic roles. Engagement is the opportunity for informing and enhancing research, teaching, and service, and policy by actively participating in activities that connect students with external partners and the community. In this AGHE Presidential Symposium, leading scholars whose grit and determination to embrace engagement will address the important role engagement has in uplifting gerontology and geriatrics education. Elinor Schoenfeld and colleagues will provide insights into their innovative, multidisciplinary approach to teaching students about community engagement, technology, and data security as it relates to supporting older adults living in their homes. Taylor Jansen will discuss incorporating Geographic Information Systems (GIS) Mapping into gerontology research and teaching both undergraduate and graduate students, as she works closely with community partners in several states across the U.S. to uplift their programming and policy work. José Carrión-Baralt will describe the process he and his colleagues embraced as they coordinated efforts across several universities and health professions to support older adults after hurricanes Irma and Maria hit Puerto Rico in 2017, through the development of a team called Brigadas Salubristas (Public Health Brigades). Shannon Jarrott will highlight ways to engage students in local, state, and federal aging policy through decades of engaged work addressing intergenerational programming. AGHE Chair Tina Newsham will serve as discussant, sharing how AGHE will continue to embrace fortitude and support educational efforts and opportunities through engaged teaching, research, service, and policy.
PREDICTION OF FINANCIAL FRAUD RISKS AMONG OLDER ADULTS: THE APPLICATION OF GA-XGBOOST MODEL
Authors: Zhao Jin , Li Yuanyuan , Jin Hao , Zhang Xuemin 
Published: January 2025

Abstract
The importance of crime prevention can be more profound than correction efforts after crime occurs, highlighting the necessity to develop an early risk warning model that can accurately identify financial fraud risks among older adults. Utilizing data from the fourth Urban and Rural Survey on the Living Conditions of Older Adults conducted in 2015 in China, this study leverages a genetic algorithm (GA) to optimize the parameters of the XGBoost model, resulting in the creation of a GA-XGBoost-based financial fraud risk prediction model tailored for older adults. The efficiency of this novel model is evaluated against established machine learning algorithms, including LightGBM, Random Forest, Decision Tree, and SVM. Furthermore, SHAP values are employed for a detailed visual analysis of the factors most influential in predicting and understanding financial fraud risks among this demographic. We found that variables such as lower education level, older age, and loneliness increased risks for financial fraud. In contrast, increased awareness of rights protection and better sleep quality appear to have protective effects. A comparative assessment at both domestic and international levels, with references to the United States, Germany, and South Korea, highlights psychological vulnerability, cognitive functioning, age, and loneliness as financial fraud risks among older adults. This study offers recommendations for mitigating financial fraud risks from three angles: enhancing public awareness and education; implementing effective regulatory frameworks; and strengthening intergenerational connections. These suggestions will help lay the groundwork for more robust protective measures against financial fraud targeting older adults.
RISK FACTORS FOR FINANCIAL FRAUD AMONG OLDER CHINESE: AN ANALYSIS BASED ON CHARLS DATA
Authors: Li Yuanyuan , Cao Yunqi , Wu Yuxia , Mi Hong 
Published: January 2025

Abstract
Financial fraud targeting older adults in China is a growing concern, resulting in both financial losses and adverse effects on their physical and mental health. Despite its prevalence, there remains a scarcity of research focused on the victims of these frauds. Leveraging the 2018 China Health and Retirement Longitudinal Study (CHARLS) database and applying structural equation modeling (SEM), this study delves into the factors that place older adults in China at risk of financial fraud, examining the issue through the lens of the victims themselves. The frameworks typically used in Western contexts like the United States and Britain only focused on individual level factors, such as age and living arrangement, physical functioning, and individual capital (i.e., levels of education, cognition, and social activities). This study integrates unique social models, including factors related to family relationships, to reflect the Chinese cultural setting. It offers a comprehensive view of the elements that heighten the risk of financial fraud among older Chinese. The analysis uncovered that factors such as age and living arrangement, physical functioning, family relationship, and individual capital play a direct role in increasing the vulnerability of older adults to financial scams. Furthermore, psychological vulnerability and material wealth were identified as mediators among physical functioning, family relationships, and fraud risks. Based upon these findings, the study proposes targeted strategies to mitigate the risk of financial fraud to include promoting healthier living habits, enhancing individual capital, and reinforcing family connections.
WHO EXPERIENCES MASS MARKETING FRAUD IN AMERICA? A SURVEY OF KNOWN VICTIMS
Authors: DeLiema Marguerite , Gao Siyu , Brannock M Daniel , Langton Lynn 
Published: January 2025

Abstract
Significant research has attempted to understand the characteristics of older adult fraud victims, yet most surveys rely on participants’ self-reports of victimization. This approach can lead to biased estimates because older victims are less likely to disclose victimization experiences relative to younger victims. We avoid underreporting bias by surveying a population of victims identified by the US Postal Inspection Service. All respondents mailed money in response to fraudulent solicitations between 2022 and 2023 (range = 1 to 168 victimization incidents). Victims’ payment envelopes were detained by Postal Inspectors as part of the agency’s law enforcement efforts. Victim addresses were securely shared with the research team. The survey response rate was 23% (N=934); 84% of participants responded by mail and 16% responded online. Average age was 74 (standard deviation = 13.2; range= 20 to 98). Mass marketing mail fraud victims were racially and economically diverse: 22% of victims were Black, 10% were Latino/a, and 6% were Asian or Pacific Islander. A quarter reported an annual household income of less than $20,000; 27% reported a household income between $20,000 and $50,000. Rates of widowhood and divorce were high—31% and 20%, respectively. Nearly half of fraud victims reported that they live alone. These results suggest that diverse, lower income and isolated older adults are targeted by mass marketing fraud. Given the relatively robust response rate, consumer fraud education materials should be mailed to victim households and include information on how to identify fake solicitations and report scams.
FINANCIAL EXPLOITATION PREVENTION AMONG OLDER ADULTS WITH DEMENTIA IN RURAL MICHIGAN: A PILOT RANDOM CONTROL TRIAL
Authors: Sun Fei , Guo Yu , Zhang Zhenmei , Wang Xia , Kim Haneul , Tucker Brittany , Smith Eleanor 
Published: January 2025

Abstract
Dementia increases the susceptibility of older adults to financial exploitation, including abuse by relatives or acquaintances and fraud by strangers. This study evaluated the effectiveness of a novel community-based financial exploitation prevention model for older adults with dementia residing in rural Michigan. Drawing from the routine activity theory, the study focused on mitigating financial exploitation risks linked to family caregivers. While family caregivers might potentially engage in such exploitation, they also play a crucial role in detecting and preventing fraudulent activities. Employing a randomized control design, 32 family caregivers in intervention groups and 23 in control groups received an education session on dementia, financial exploitation, and community resources. In addition, intervention groups received 6 sessions of case management service tailored to mitigate identified risk factors for financial exploitation. Linear mixed modeling (LMM) was applied to assess changes before and post intervention and between groups on the following outcomes: attitude towards financial exploitation, competence in addressing financial exploitation, caregiver stress, and dementia knowledge and stigma. No significant differences were found on dementia knowledge and attitude towards financial exploitation. However, caregivers in the intervention groups exhibited significantly greater confidence in addressing financial exploitation and reported lower levels of dementia-related stigma (p &lt;.05) compared to the control group. Both groups reported a decrease in caregiver stress, but no group difference was observed. The study highlights the integral role of family caregivers as a protective shield against financial exploitation, and the need for policy and practice efforts to educate and support family caregivers.