bluuebunny/crossref_metadata_2025_split huggingface dataset:
SYNTHESIZING LIFESTYLE MEDICINE AND SUCCESSFUL AGING: A PERFECT PAIRING FOR THEORIZING OPTIMAL AGING?
Authors: Undem Teri , Fuller Heather 
Published: January 2025

Abstract
Within gerontology, various theoretical perspectives on what it means to age successfully have emerged over recent decades (e.g. Rowe & Kahn, etc.) and garnered empirical support. Within medicine and related healthcare fields, research is prolific regarding engaging in healthy living in terms of physical health, mental health, and well-being. In recent years, a theoretical perspective of Lifestyle Medicine has emerged to describe the role of such lifestyle factors on health. The present work includes a scoping review of both literatures with the ultimate goal of determining overlaps and distinctions between theoretical concepts of successful aging and lifestyle medicine. We take a holistic approach to develop a model that identifies linkages between the principles of successful aging and lifestyle medicine. The resultant ‘Lifestyle Model of Optimal Aging’ merges the core pillars of Lifestyle Medicine (nutrition, physical activity, stress management, restorative sleep, social connection, and avoidance of risky substances) with the core principles of successful aging from the models put forth by Rowe and Kahn (1997) and expanded upon by Urtamo et.al., (2019). This new, holistic approach to exploring the linkages between the principles of LM and the essential components of successful aging highlights how proactive behavioral health strategies related to nutrition, exercise, sleep, stress, and substances can foster optimal aging in cognitive and physical functioning and disease prevention, thereby potentially yielding more positive outcomes for aging well. Discussion explores how concepts underlying successful aging may be enhanced by incorporating a lifestyle medicine approach.
THEORETICAL ANALYSIS OF THE DISABLEMENT PROCESS MODEL IN THE CONTEXT OF VISION LOSS IN LATE LIFE
Authors: Suzuki Haruno , Wallhagen Margaret 
Published: January 2025

Abstract
Vision loss experienced by older adults is associated with poor biopsychosocial health, yet the mechanisms underpinning adjustment to this disability are poorly understood. One framework that may facilitate the exploration of the adjustment is the disablement process model (DPM) (Verbrugge & Jette, 1994), which describes how a chronic condition leads to disability. However, limited studies have evaluated the model’s applicability to older adults living with vision loss. This study critically appraises the theoretical assumptions of DPM for its applicability to studying vision loss acquired in late life. We utilized the criteria adapted from Chinn and Kramer (2011), which include 6-items of description of theory and 5-items of critical reflection. The central pathway of the DPM describes moving from pathology to impairments, functional limitations, and disability with intra- and extra-individual factors influencing the experience of disability. Definitions of each concept and subconcept are explicit yet general enough to use in various populations with disabilities, increasing the model’s generalizability. However, the magnitude of the effects of each subconcept on disability and health outcomes is unclear. Furthermore, it is based on a medical model of disability, focusing on preventing disability. It lacks the nuance of social models that include strengths and capacities, thus limiting its use in developing inclusive communities that reinforce intrinsic capability and extrinsic environmental supports, such as age-friendly community. The findings imply the necessity of modifying the model to improve its utility in exploring the lived experience of disability among older adults living with vision loss in late life.
TOPIC CLUSTERS OF SUCCESSFUL AGING STUDIES: RESULTS OF A TOPIC MODELING APPROACH
Authors: Kim Ha Neul , Freddolino Paul 
Published: January 2025

Abstract
Literature regarding successful aging reflects a wide variety of fields and perspectives. Given the range of definitions and approaches found in the published literature, it is important to investigate clusters of topics studied over time. This study aimed to show the change of topic clusters within successful aging studies. The study used topic modeling methodology to analyze vast amounts of abstract data. Among publications collected from Scopus (4,458) and Web of Science (5,187), 5,610 publications were analyzed. Topic clusters were analyzed in two ways: by a) division of time (1960s – 1990s, 2000s, 2010s, 2020s) and b) all years combined. In the 1960s – 1990s, 11 topic clusters ranging from health to emotional well-being emerged without any dominant domain. In the 2000s, two clusters related to social support and health appeared as major clusters. In the 2010s, one topic cluster that included words related to health and social participation was the biggest. In the 2020s, emotional health and social participation appeared again as one of the major clusters and health-related topics started to diverge into subgroups like physical health and mental health. In all years of publications combined, the major cluster involved words that are related to either health or social domains. Results revealed that successful aging has been studied in many fields using multidimensional perspectives. The dominant categories were health and social domains. These findings suggest interprofessional practice, an interdisciplinary approach in research, and multi-sector involvement in policy.
EFFECTS OF A GAIT TRAINING PROGRAM USING A WALKING-ASSIST WEARABLE ROBOT ON COMMUNITY-DWELLING OLDER ADULTS
Authors: Hwang Sinwoo , Cho Eunhee 
Published: January 2025

Abstract
Two-thirds of people aged 65 and older require help with daily activities such as eating, bathing, and getting in and out of bed or a chair. Walking-assist wearable robots have shown significant improvements in physical function in controlled settings for patients. In this study, we aimed to determine the feasibility and evaluate the effectiveness of a gait assistance and gait resistance training program using a walking-assist wearable robot for community-dwelling older adults. A total of 23 community-dwelling older adults aged 65 and older (30 participants recruited, 7 dropped out) enrolled in a 12-session, 6-week gait assistance and gait resistance training program using a walking-assist wearable robot. A single-group, pre- and post-test design was employed to evaluate effectiveness. Paired t-tests and linear mixed model analysis reveal that the functional performance (assessed using the 10-Meter Walk Test, Timed Up-and-Go, and Four Square Step Test) and leg muscle strength of the participants improved significantly at the end of the program compared to the baseline values (P &lt; 0.01). This study stands out for applying gait assistance and resistance training across various terrains, unlike previous studies that only tested gait assistance in controlled environments. The results demonstrated significant improvements in functional performance and muscle strength in older adults, suggesting the effectiveness of preventive healthcare services utilizing a walking-assist wearable robot as an intervention that can contribute to improving independent functioning and frailty among community-dwelling older adults.
EXPLORING BED SENSOR SLEEP TECH: INSIGHTS FROM INTERDISCIPLINARY TEAM IN A GERIATRIC ASSESSMENT INPATIENT SETTING
Authors: Acosta Cromwell , Zhao Yong , Lawrence Joanna , Towell Michelle , MacKay-Dunn Marion , D’Oyley Heather , Chow Bryan , Hung Lillian 
Published: January 2025

Abstract
Poor sleep can affect cognitive function and decrease overall quality of life. Evaluating sleep is critical in the care of hospitalized older adults. This study compared the use of traditional paper-based logs charted by nurses to record sleep patterns with smart sensors offering continuous monitoring and analysis of sleep patterns. The goal was to investigate the perspectives of staff members in an interdisciplinary team on sleep monitoring methods. We also asked participants about barriers and facilitators in implementing bed sensor technology in an Inpatient setting. Employing Interpretive Descriptive methodology, we conducted interviews and focus groups involving 29 staff members with diverse roles in one inpatient setting. The Consolidated Framework for Implementation Research (CFIR) guided our data analysis. Our findings indicate that while the traditional paper-based method, somnolog, is prone to inaccuracies from subjective estimates and sleep disturbances, bed sensor sleep technology is perceived as efficient, data-driven, and evidence-supported. Barriers to technology adoption include resistance to change, consent issues, patient comfort and safety concerns, and familiarity with the technology. On the other hand, facilitating factors comprise orientation and training, trial integration, effective communication, and evidence-based incentives. Utilizing the CFIR framework provides valuable insights into the challenges and aids in incorporating technology into care settings. Future research should focus on practical strategies involving interdisciplinary teams to facilitate innovative practices.
FACTORS ASSOCIATED WITH PERCEPTION OF PATIENT-GENERATED HEALTH DATA AMONG OLDER PATIENTS POST LUNG CANCER SURGERY
Authors: Choi Mona , Cho Hyeonmi , Kim Yesol , Kim Yeonju 
Published: January 2025

Abstract
This study examines factors related to the perceived usefulness of patient-generated health data (PGHD) among older patients who underwent lung cancer surgery. This descriptive cross-sectional study involved individuals aged ≥65 years who had lung cancer surgery at least 4 weeks prior. Participants were recruited from an outpatient clinic, and survey data from 102 patients were analyzed. Thirty-seven PGHD items were categorized into 7 groups: Environmental Factors (EF), Lifestyle Factors (LF), Body Composition and Activity Level (BCAL), Medication-related Factors (MF), Physiological Parameters (PP), Physical and Mental Well-being Factors (PMWF), and Digital Engagement (DE). Stepwise linear regression models were used to identify factors associated with patients’ perceptions of PGHD. Higher digital literacy was associated with greater perceived usefulness in EF and DE categories. Older individuals perceived PGHD in LF and BDAL categories as less useful. Unemployed individuals found PGHD less useful in LF compared to employed individuals. Higher household income was associated with greater perceived usefulness in PMWF category. Non-smartphone users perceived PGHD as less useful in BCAL and PP categories. Patients who underwent surgery more than 5 years ago found PGHD less useful in MF and PP categories than those with more recent surgeries. Individuals with lower education levels and those living alone showed lower perceived usefulness in PP compared to their counterparts. Understanding patients’ personal characteristics, digital literacy, and technology access is crucial for utilizing PGHD effectively for health promotion among older patients with lung cancer surgery. This understanding can assist healthcare providers in identifying and addressing potential challenges.
FAMILY EXPERIENCE IN USING TELEPRESENCE ROBOTS WITH RESIDENTS IN LONG-TERM CARE
Authors: Hung Lillian , Hu Grace , Wong Joey , Ren Haopu (Lily) , Mann Jim , Wong Lily 
Published: January 2025

Abstract
Informal care, most often provided by family or friends, remains a hidden and underrecognized undertaking within long-term care (LTC) settings. As care recipients transition into LTC, informal care partners experience a parallel shift in their caregiving roles: transitioning from primary care partner to visitor. Many care partners report this transition to be difficult, as they must surrender an unpredictable level of control and involvement over their loved one’s care. The COVID-19 pandemic intensified this experience by introducing new challenges: individual health concerns, fluctuating care home protocols, and isolating government policies. Telepresence robots are emerging as a tool that can ease the care partner transition. The main aim of this study is to examine the experiences of care partners who used telepresence robots with loved ones living in LTC settings, during the COVID-19 pandemic. This study took place between May 2021 and August 2023 in five urban LTC homes located in British Columbia, Canada. A total of 20 care partners were recruited through purposive sampling. The care partners participated in semi-structured interviews, in-person or virtually, and thematic analysis was employed to identify four key themes characterizing their experiences using the robot: 1) Decreases care partner burden, 2) Facilitates care partner-staff relationship, 3) Creates relational autonomy, and 4) Expands the scope of what is possible. Findings capture the ability of the robot to enhance the caregiving experience for informal care partners. Further research on the sustainability of robot implementation amongst diverse geographic regions and care home compositions is needed.
LEVELING UP ADHERENCE PREDICTION: MOTIVATION’S INFLUENCE ON ENGAGEMENT WITH TECH-BASED COGNITIVE INTERVENTIONS
Authors: Shaleha Rinanda , Roque Nelson , Harrell Erin 
Published: January 2025

Abstract
In this study, comprising a sample size of N=118 older adults with an age range of 65 years and above, we investigated the impact of individual motivation on adherence behavior within a technology-based cognitive training intervention. Despite previous research indicating limited effects of framing conditions (negative, positive, and disabled) on adherence (Harrell et al., 2021), we hypothesized that individual motivation levels would significantly influence adherence behavior. Motivation is operationally defined based on participants’ performance in cognitive training games, where high motivation is indicated by a pattern of low failure rates and successful game performance. Utilizing advanced multilevel modeling techniques, we compared adherence models with and without motivation as a predictor. Our findings supported our hypothesis. The linear mixed model analysis revealed a significant effect of motivation on adherence (Estimate = 1.35939, SE = 0.24490, t (1422.78) = 5.551, p &lt;.001), indicating that for each unit increase in motivation, there is a significant increase in adherence. Likelihood ratio tests (LRTs) comparing the model fit showed significantly divergent log-likelihoods between the two models (Δχ² (1) = 27.559, p &lt;.001). These findings suggest that high levels of motivation play a crucial role in driving adherence behavior within the context of technology-based cognitive training interventions. By leveraging motivational factors and harnessing the power of gamification, researchers and practitioners can design more effective interventions that promote adherence, facilitate behavior change, and ultimately improve outcomes for participants.
NAMING AND STORYTELLING IN SOCIAL ROBOT INTERACTIONS: A NARRATIVE ANALYSIS OF ENGAGEMENT AND PERSONAL CONNECTIONS
Authors: Cheng Clio Yuen Man , Lou Vivian Weiqun 
Published: January 2025

Abstract
Social robots have emerged as promising tools with gerontology, offering the potential to enhance human-computer interaction and improve the well-being of older adults. This study employs narrative analysis approach to examine the impact of naming and storytelling in social robot interactions among older singletons. A total of 17 participants, aged between 60 to 73, engaged in 15-minute interaction sessions with a social robot (LOVOT), during which they provided a name for the robot and crafted a story around it. Through a comprehensive narrative analysis, this study uncovers the intricate dynamics of naming and storytelling in shaping older adults’ engagement and personal connections within social robot interactions. The analysis reveals that naming and storytelling serve as powerful vehicles for expressing expectations, personal experiences, and emotional connections. Participants drew upon their individual backgrounds, memories, and cultural references to create narratives that reflected their unique perspectives and desires. The narratives showcased the participants’ desires for intelligent and emotionally responsive robots while evoking nostalgia through connections to past experiences. Additionally, the narratives revealed a longing for companionship and emotional support, exemplified by associations of robot naming with deceased pets. Understanding the role of naming and storytelling in social robot interactions is crucial for designing robots that effectively cater to the needs and desires of older adults, ultimately enhancing their engagement and overall well-being. This study contributes to the field of human-robot interaction in gerontology by shedding light on the significance of personal narratives in fostering meaningful connections between older adults and social robots.
PREDICTING ACCIDENTS OF OLDER ADULTS LIVING WITH DEMENTIA USING ASSISTIVE TECHNOLOGIES AND MACHINE LEARNING
Authors: Lee Kyung Hee , Yang Eunjin , Lee Ji Yeon , Cho Aeyoung 
Published: January 2025

Abstract
Although older adults living with dementia prefer to age in their own homes, they face many challenges such as falls, injuries, and night-time disturbances. Predicting and preventing those challenges could help both older adults and their caregivers to maintain aging in place. This study aimed to develop and validate machine learning models in predicting accident subgroups among individuals with dementia using assistive technologies (i.e., in-home motion sensors and actigraphy). Data were collected from 75 older adults living with dementia and their family caregivers in South Korea. Utilizing 966 days of data on sensors, sleep, and survey from dyads, various machine learning models were developed to predict three accident subgroups—physical impact, night-time behaviors/wandering, and risky behaviors. The performances of five machine learning classification models were compared and important features were extracted. Python 3.9 was used for all analyses. The Gradient Boosting Model excelled in predicting physical impact and night-time behaviors, while CatBoost performed best for risky behaviors, achieving F1-scores of 0.50, 0.71, and 0.87, respectively. Important features were different by type of accidents. For physical impact, caregiver’s age, comorbidity severity, and total sleep time were the three top features; for night-time behaviors/wandering, cognitive function and number of medications were the most important features; neuropsychiatric and depressive symptoms were the most important features for risk behaviors. In addition, activity patterns recorded by in-home motion sensors emerged as important features. The findings highlight the potential of these assistive technologies to identify high-risk individuals, provide a safer environment, and support family caregivers.
PREFERENCE FOR DIGITAL DEVICES AND PATIENT-GENERATED HEALTH DATA UTILITY IN OLDER PATIENTS AFTER LUNG CANCER SURGERY
Authors: Choi Mona , Kim Yeonju , Cho Hyeonmi , Kim Yesol 
Published: January 2025

Abstract
This study aimed to investigate the preference for digital devices and the utility of patient-generated health data (PGHD) among older patients who have undergone lung cancer surgery. A cross-sectional descriptive study included patients at least four weeks after lung cancer surgery and excluded those with cognitive impairments. Participants in this study were recruited from a tertiary hospital outpatient clinic and conducted using a structured questionnaire: 1) patient’s general characteristics; 2) experience and duration of use of digital devices; 3) preference for wearable or attachable digital devices for PGHD collection; and 4) PGHD usability. Descriptive and bivariate analyses were performed. 135 patients were analyzed (age = 70.19 ± 11.80 years; 47.0% female). Smartphones (94.1%) were the most experienced digital devices, and the period of use varied from 4 months to 15 years. The wristwatch type was the most preferred wearable digital device (61.5%), and men preferred the belt type. Depending on the level of education, there was a difference in preference between the watch type and the skin patch type, and there was a difference in preference for the glasses type depending on the quality of sleep. The most informative PGHDs were lung function (91.1%), blood pressure (83.7%), and step count (83.7%). The usefulness of PGHD, such as drug side effects and social relationships, differed depending on the number of drugs taken. This study may help healthcare providers select appropriate digital health devices and utilize useful PGHD to improve health outcomes among older patients after lung cancer surgery.
ADVANCING CULTURALLY INCLUSIVE RESEARCH AND TOOLS IN ALZHEIMER’S DISEASE AND RELATED DEMENTIAS (ADRD)
Authors: Magid Maryam Abdel , Taylor Jean , Turner Anne 
Published: January 2025

Abstract

Background and Significance
Existing research underscores cultural norms’ influence on healthcare decisions but lacks depth in exploring their impact on dementia care transitions, critical for improving ADRD care outcomes. Research Aims include (1) Analyze interviews with dementia care providers and staff to better understand how cultural norms influence the decision-making processes for care transitions. (2) Explore methods used to facilitate inclusive and engaging discussions regarding care transitions.

Methods
Nested in the NIA-funded Decision Making in Alzheimer’s Research (DMAR) study, we examined interviews with 18 providers and staff on dementia care transitions. Prioritizing inclusivity, we leveraged the Alzheimer’s Disease Research Center (ADRC) registry and community partnerships coupled with tailored methods including diversifying the team and targeted outreach efforts. We’re employing a novel framework to analyze dementia care transitions, integrating societal and cultural aspects for nuanced understanding. This approach accounts for intergenerational culture, cognition perception, and care expectations, evolving to capture cultural nuances. Qualitative findings will be enriched with quantitative sentiment analysis, validated manually for accuracy.

Key findings
Novel framework will allow us to identify and analyze cultural norms affecting care transitions, as perceived by ADRD providers.

Implications
The study’s findings advocate for inclusive decision-making tools in ADRD care to accommodate diverse patient preferences. Future steps involve applying this framework to patients and caregivers and integrating findings into diverse settings involved in care decision-making. Funding statement: Funded in part by NIA grant #R01 AG066957 and the NLM T15 training grant #5T155LM007442-22. Content responsibility lies with authors, not representing NIH views.