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Abstract AimsTo examine how perceived balance problems are associated with self‐reported falls in the past month after controlling for known correlates of falls among older adults. BackgroundApproximately 30% of adults age 65 and older fall each year. Most accidental falls are preventable, and older adults' engagement in fall prevention is imperative. Limited research suggest that older adults do not use the term ‘fall risk’ to describe their risk for falls. Instead, they commonly use the term ‘balance problems’. Yet, commonly used fall risk assessment tools in both primary and acute care do not assess older adults' perceived balance. Design and MethodThe Health Belief Model and the concept of perceived susceptibility served as the theoretical framework. A retrospective, cross‐sectional secondary analysis using data from the National Health and Aging Trends Study from year 2015 was conducted. The outcome variable was self‐reported falls in the last month. ResultsA subsample of independently living participants (N = 7499) was selected, and 10.3% of the sample reported a fall. Multiple logistic regression analysis revealed that the odds of reporting a fall in the past month was 3.4 times (p < .001) greater for participants who self‐reported having a balance problem compared to those who did not. In contrast, fear of falling and perceived memory problems were not uniquely associated with falls. Using a mobility device, reporting pain, poor self‐rated health status, depression and anxiety scores were also associated with falling. Conclusion and ImplicationsOlder adults' perceived balance problem is strongly associated with their fall risk. Perceived balance may be important to discuss with older adults to increase identification of fall risk. Older adults' perceived balance should be included in nursing fall risk assessments and fall prevention interventions. A focus on balance may increase older adults' engagement in fall prevention. 

BackgroundAlzheimer's disease affects 55 million people worldwide. As the disease progresses, these individuals require a devoted caregiver, often a family member, who provides evolving complex care. Caregivers can experience a variety of ongoing stressors, resulting in reductions in caregiver emotional well-being (and other quality-of-life indicators). Information and communication technologies provide an excellent opportunity to train caregivers remotely and help them to manage these stressors and related distress. ObjectiveThis protocol describes the theoretical rationale, study design, and methods of a new, technologically enhanced psychoeducational skill-building intervention for caregivers of people with dementia that includes a virtual reality component. MethodsThrough Alzheimer’s Eyes is a 4-week, single-arm, pre-post test pilot study consisting of 4 sessions of 90 minutes each that are delivered by videoconferencing. These sessions include a weekly virtual reality experience characterizing the journey of an older Latina with Alzheimer's disease from her perspective to help caregivers see through the eyes of a person with dementia. The 4 sessions cover the skill-training topics of communication, managing challenging behaviors and unhelpful thoughts, the importance of self-care, and mindfulness—all of which are key components designed to reduce stress and distress in family caregivers. Individual interviews conducted before and after the intervention gather participant insights into the intervention, evaluate its feasibility and acceptability, and assess its impact on key outcomes. ResultsData collection for the study started in January 2022, and the results are expected to be submitted for publication in the second half of 2023. Twenty caregivers from the United States have completed the workshop to date. Preliminary data gathered from these participants support the intervention’s feasibility and acceptability. ConclusionsThrough Alzheimer’s Eyes leverages existing technology combined with psychoeducational skill building to help caregivers manage their stress, regardless of their location. International Registered Report Identifier (IRRID)DERR1-10.2196/42655 

Persistent memory (PM) brings important opportunities for improving data storage including the widely used hash tables. However, PM is not friendly to small writes, which causes existing PM hashes to suffer from high hardware write amplification. Hybrid memory offers the performance and concurrency of DRAM and the durability and capacity of PM, but existing hybrid memory hashes cannot deliver high performance, low DRAM footprint, and fast recovery at the same time. This paper proposes WALSH, a flat hash with novel log-structured separate chaining designs to optimize the performance while ensuring low DRAM footprint and fast recovery. To address the overhead of hash resizing and garbage collection (GC), WALSH further proposes partial resizing/GC mechanisms and a 4-phase protocol for concurrent hash operations. As a result, WALSH is the first flat index for hybrid memory with embedded write aggregation ability. A comprehensive evaluation shows that WALSH substantially outperforms state-of-the-art hybrid memory hashes; e.g., its insert throughput is up to 2.4X that of related works while saving more than 87% of DRAM. WALSH also provides efficient recovery; e.g., it can recover a dataset with 1 billion objects in just a few seconds. 

Alzheimer’s disease (AD) affects Latinos disproportionately. One of the reasons underlying this disparity may be type 2 diabetes (T2D) that is a risk factor for AD. The purpose of this study was to examine the associations of T2D and AD blood biomarkers and the differences in these associations between Mexican Americans and non-Hispanic Whites. This study was a secondary analysis of baseline data from the observational Health and Aging Brain Study: Health Disparities (HABS-HD) that investigated factors underlying health disparities in AD in Mexican Americans in comparison to non-Hispanic Whites. HABS-HD participants were excluded if they had missing data or were large outliers (z-scores >|4|) on a given AD biomarker. Fasting blood glucose and glycosylated hemoglobin (HbA1c) levels were measured from clinical labs. T2D was diagnosed by licensed clinicians. Plasma amyloid-beta 42 and 40 (Aβ_42/42) ratio, total tau (t-tau), and neurofilament light (NfL) were measured via ultra-sensitive Simoa assays. The sample sizes were 1,552 for Aβ_42/40ratio, 1,570 for t-tau, and 1,553 for NfL. Mexican Americans were younger (66.6±8.7 vs. 69.5±8.6) and had more female (64.9% female vs. 55.1%) and fewer years of schooling (9.5±4.6 vs. 15.6±2.5) than non-Hispanic Whites. Mexican Americans differed significantly from non-Hispanic Whites in blood glucose (113.5±36.6 vs. 99.2±17.0) and HbA1c (6.33±1.4 vs. 5.51±0.6) levels, T2D diagnosis (35.3% vs. 11.1%), as well as blood Aβ_42/40ratio (.051±.012 vs. .047±.011), t-tau (2.56±.95 vs. 2.33±.90), and NfL levels (16.3±9.5 vs. 20.3±10.3). Blood glucose, blood HbA1c, and T2D diagnosis were not related to Aβ_42/40ratio and t-tau but explained 3.7% of the variation in NfL (p< .001). Blood glucose and T2D diagnosis were not, while HbA1c was positively (b= 2.31,p< .001,β =0.26), associated with NfL among Mexican Americans. In contrast, blood glucose, HbA1c, and T2D diagnosis were negatively (b =-0.09,p< .01,β =-0.26), not (b =0.34,p= .71,β =0.04), and positively (b= 3.32,p< .01,β =0.33) associated with NfL, respectively in non-Hispanic Whites. To conclude, blood glucose and HbA1c levels and T2D diagnosis are associated with plasma NfL levels, but not plasma Aβ and t-tau levels. These associations differ in an ethnicity-specific manner and need to be further studied as a potential mechanism underlying AD disparities. 

This paper discusses three points inspired by Skraaning and Jamieson’s perspective on automation failure: (a) the limitations of the automation failure concept with expanding system boundaries; (b) parallels between the failure to grasp automation failure and the failure to grasp trust in automation; (c) benefits of taking a pluralistic approach to definitions in sociotechnical systems science. While a taxonomy of automation-involved failures may not directly improve our understanding of how to prevent those failures, it could be instrumental for identifying hazards during test and evaluation of operational systems. 

Virtual humans are on-screen characters that are often embedded in learning technologies to deliver educational content. Little research has investigated how virtual humans can be used to correct common misconceptions. In this study, we explored how different types of narrative structures, refutation text and expository text, influence perceptions of trust, credibility, and learning outcomes. In addition, we conducted exploratory analyses examining how different measures of trust and credibility are related to each other and how these measures may mediate learning outcomes. Results showed that the type of narrative used did not influence any measure. However, the trust and credibility measures, while related to one another, were measurably distinct. In addition, only perceptions of message trust were significantly related to learning. Perceptions of message trust did not mediate learning outcomes, but were significantly predictive of learning at nearly the same effect as prior knowledge.