Impact of community-based technology training with low-income older adults.

OBJECTIVES: Compared with younger and middle-aged adults, older adults are less likely to adopt new computer technology, potentially limiting access to healthcare and many other important resources available online. This limitation could impact cognitive abilities, well-being, and mental health outcomes of older adults. The aims of the present study were to increase access to online county and healthcare resources, while also assessing the impact of technology access on cognitive functioning and multiple well-being domains. METHODS: A pilot community collaboration provided a two-month tablet training intervention, focused on increasing digital independence via tablet navigation, resources access, and fraud and scam prevention, to 20 low-income older adult participants (75% female, Mage = 70.85). Pre- and post-test phone interviews were conducted to measure any changes in digital independence, cognitive abilities, well-being, mental health, and mindset. RESULTS: Linear mixed effects models revealed no significant changes in outcome measures from pre- to post-test. However, we found effects of digital independence on several well-being measures, providing important information for the impact of technology access and training for low-income older adults. CONCLUSION: This pilot intervention offers limited but promising results, inspiring further investigations that may inform public health and policy services to address barriers to access and potentially improve psychological health.

Long-Term Effects of a Real-World Multi-Skill Intervention on Older Adults' Growth Mindset.

Although there have been interventions to increase growth mindset, little is known about their effectiveness over a longer period, especially for older adults. This study with older adults investigated the long-term effects of a learning intervention that included growth mindset lectures and discussions on growth mindset. In Study 1 (n = 27), participants were tracked for one year after a 12-week intervention. We found that an increased growth mindset did not last beyond the intervention. In Study 2 (n = 71), the COVID-19 pandemic interrupted the intervention after only two months. Participants were followed up for two years, and their growth mindset at one year was greater than at the pretest (Week 0) but declined from the 1- to 2-year follow-up. Taken together, interventions incorporating growth mindset messages can increase growth mindset in the short term but may require booster sessions to retain effects, especially during disruptive life events.

Multivariate spatiotemporal functional principal component analysis for modeling hospitalization and mortality rates in the dialysis population.

Dialysis patients experience frequent hospitalizations and a higher mortality rate compared to other Medicare populations, in whom hospitalizations are a major contributor to morbidity, mortality, and healthcare costs. Patients also typically remain on dialysis for the duration of their lives or until kidney transplantation. Hence, there is growing interest in studying the spatiotemporal trends in the correlated outcomes of hospitalization and mortality among dialysis patients as a function of time starting from transition to dialysis across the United States Utilizing national data from the United States Renal Data System (USRDS), we propose a novel multivariate spatiotemporal functional principal component analysis model to study the joint spatiotemporal patterns of hospitalization and mortality rates among dialysis patients. The proposal is based on a multivariate Karhunen-Loéve expansion that describes leading directions of variation across time and induces spatial correlations among region-specific scores. An efficient estimation procedure is proposed using only univariate principal components decompositions and a Markov Chain Monte Carlo framework for targeting the spatial correlations. The finite sample performance of the proposed method is studied through simulations. Novel applications to the USRDS data highlight hot spots across the United States with higher hospitalization and/or mortality rates and time periods of elevated risk.

The Impact of Learning Multiple Real-World Skills on Cognitive Abilities and Functional Independence in Healthy Older Adults.

OBJECTIVES: The natural learning experience from infancy to emerging adulthood, when considerable cognitive and functional growth is observed, mandates learning multiple real-world skills simultaneously. The present studies investigated whether learning multiple real-world skills simultaneously is possible in older adults and also whether it improves both their cognitive abilities (working memory, episodic memory, and cognitive control) and functional independence. METHODS: Over two studies (15 and 27 participants), older adults learned at least three new skills (e.g., Spanish, drawing, music composition) simultaneously for 3 months. Participants completed cognitive and functional assessments before, during, and after the intervention in both studies. Participants were recruited sequentially for an intervention or no-contact control group in Study 1, and Study 2 included only an intervention group, who also completed assessments 4-6 weeks prior to the start of the intervention (i.e., they served as their own control group). RESULTS: Results from both studies show that simultaneously learning multiple skills is feasible and potentially beneficial for healthy older adults. Learning multiple skills simultaneously increased cognitive abilities in older adults by midpoint of the intervention, to levels similar to performance in a separate sample of middle-aged adults. DISCUSSION: Our findings demonstrate the feasibility and potential of conducting a real-world skill-learning intervention involving learning three novel skills with older adults. Our multiskill intervention may provide broad cognitive gains, akin to the benefits experienced earlier in the life span.

One-year cognitive outcomes from a multiple real-world skill learning intervention with older adults.

OBJECTIVES: Novel skill learning has been shown to have cognitive benefits in the short-term (up to a few months). Two studies expanded on prior research by investigating whether learning multiple novel real-world skills simultaneously (e.g. Spanish, drawing, music composition), for a minimum of six hours a week, would yield 1-year cognitive gains. METHOD: Following a 3-month multi-skill learning intervention, Study 1 (N = 6, Mage = 66 years, SDage = 6.41) and Study 2 (N = 27, Mage = 69 years, SDage = 7.12) participants completed follow-up cognitive assessments 3 months, 6 months, and one year after the intervention period. Cognitive assessments tested executive function (working memory and cognitive control) and verbal episodic memory. RESULTS: Linear mixed-effects models revealed improvements in multiple cognitive outcomes from before the intervention to the follow-up timepoints. Specifically, executive function increased from pre-test to the 1-year follow-up for both studies (an effect driven mostly by cognitive control scores). DISCUSSION: Our findings provide evidence that simultaneously learning real-world skills can lead to long-term improvements in cognition during older adulthood. Future work with diverse samples could investigate individual differences in gains. Overall, our findings promote the benefits of lifelong learning, namely, to improve cognitive abilities in older adulthood.

Growth Mindset Predicts Cognitive Gains in an Older Adult Multi-Skill Learning Intervention.

Growth mindset (belief in the malleability of intelligence) is a unique predictor of young learners' increased motivation and learning, and may have broader implications for cognitive functioning. Its role in learning in older adulthood is unclear. As part of a larger longitudinal study, we examined growth mindset and cognitive functioning in older adults engaged in a 3-month multi-skill learning intervention that included growth mindset discussions. Before, during, and after the intervention, participants reported on their growth mindset beliefs and completed a cognitive battery. Study 1 indicated that intervention participants, but not control participants, increased their growth mindset during the intervention. Study 2 replicated these results and found that older adults with higher preexisting growth mindsets showed larger cognitive gains at posttest compared to those with lower preexisting growth mindsets. Our findings highlight the potential role of growth mindset in supporting positive learning cycles for cognitive gains in older adulthood.

Social Mobility and Sense of Purpose From Midlife to Old Age: Examining the Role of Major Life Events.

Purpose in life (PIL) has been linked with numerous health benefits and adaptive aging, yet it diminishes with age, possibly due to loss of social or familial roles through life transitions. Drawing from the longitudinal surveys of the Midlife in the US study (n = 3418), we use time-varying coefficient models to investigate how the trajectory of PIL differs across cumulatively (dis)advantaged, upwardly mobile, and downwardly mobile groups and the role of major life events in shaping these trajectories. We found the upwardly mobile group exhibits higher PIL than the cumulatively disadvantaged and downwardly mobile groups. The consistently disadvantaged group experiences more adverse events at non-normative times. Socioeconomic status disparities in PIL during old age decrease after controlling for life events. We discuss how and why well-being changes and the role of structural and social factors in facilitating or impeding the development or maintenance of PIL over the life course.

A Bayesian multilevel time-varying framework for joint modeling of hospitalization and survival in patients on dialysis.

Over 782 000 individuals in the United States have end-stage kidney disease with about 72% of patients on dialysis, a life-sustaining treatment. Dialysis patients experience high mortality and frequent hospitalizations, at about twice per year. These poor outcomes are exacerbated at key time periods, such as the fragile period after transition to dialysis. In order to study the time-varying effects of modifiable patient and dialysis facility risk factors on hospitalization and mortality, we propose a novel Bayesian multilevel time-varying joint model. Efficient estimation and inference is achieved within the Bayesian framework using Markov chain Monte Carlo, where multilevel (patient- and dialysis facility-level) varying coefficient functions are targeted via Bayesian P-splines. Applications to the United States Renal Data System, a national database which contains data on nearly all patients on dialysis in the United States, highlight significant time-varying effects of patient- and facility-level risk factors on hospitalization risk and mortality. Finite sample performance of the proposed methodology is studied through simulations.

Spatial Analysis of Neural Cell Proteomic Profiles Following Ischemic Stroke in Mice Using High-Plex Digital Spatial Profiling.

Stroke is ranked as the fifth leading cause of death and the leading cause of adult disability in the USA. The progression of neuronal damage after stroke is recognized to be a complex integration of glia, neurons, and the surrounding extracellular matrix, therefore potential treatments must target the detrimental effects created by these interactions. In this study, we examined the spatial cellular and neuroinflammatory mechanisms occurring early after ischemic stroke utilizing Nanostring Digital Spatial Profiling (DSP) technology. Male C57bl/6 mice were subjected to photothrombotic middle cerebral artery occlusion (MCAO) and sacrificed at 3 days post-ischemia. Spatial distinction of the ipsilateral hemisphere was studied according to the regions of interest: the ischemic core, peri-infarct tissues, and peri-infarct normal tissue (PiNT) in comparison to the contralateral hemisphere. We demonstrated that the ipsilateral hemisphere initiates distinct spatial regulatory proteomic profiles with DSP technology that can be identified consistently with the immunohistochemical markers, FJB, GFAP, and Iba-1. The core border profile demonstrated an induction of neuronal death, apoptosis, autophagy, immunoreactivity, and early degenerative proteins. Most notably, the core border resulted in a decrease of the neuronal proteins Map2 and NeuN; an increase in the autophagy proteins BAG3 and CTSD; an increase in the microglial and peripheral immune invasion proteins Iba1, CD45, CD11b, and CD39; and an increase in the neurodegenerative proteins BACE1, APP, amyloid ß 1-42, ApoE, and hyperphosphorylated tau protein S-199. The peri-infarct region demonstrated increased astrocytic, immunoreactivity, apoptotic, and neurodegenerative proteomic profiles, with an increase in BAG3, GFAP, and hyperphosphorylated tau protein S-199. The PiNT region displayed minimal changes compared to the contralateral cortex with only an increase in GFAP. In this study, we showed that mechanisms known to be associated with stroke, such as apoptosis and inflammation, occur in distinct spatial domains of the injured brain following ischemia. We also demonstrated the dysregulation of specific autophagic pathways that may lead to neurodegeneration in peri-infarct brain tissues. Taken together, these data suggest that identifying post-ischemic mechanisms occurring in a spatiotemporal manner may lead to more precise targets for successful therapeutic interventions to treat stroke.

Multilevel Varying Coefficient Spatiotemporal Model.

Over 785,000 individuals in the U.S. have end-stage renal disease (ESRD) with about 70% of patients on dialysis, a life-sustaining treatment. Dialysis patients experience frequent hospitalizations. In order to identify risk factors of hospitalizations, we utilize data from the large national database, United States Renal Data System (USRDS). To account for the hierarchical structure of the data, with longitudinal hospitalization rates nested in dialysis facilities and dialysis facilities nested in geographic regions across the U.S., we propose a multilevel varying coefficient spatiotemporal model (M-VCSM) where region- and facility-specific random deviations are modeled through a multilevel Karhunen-Loéve (KL) expansion. The proposed M-VCSM includes time-varying effects of multilevel risk factors at the region- (e.g., urbanicity and area deprivation index) and facility-levels (e.g., patient demographic makeup) and incorporates spatial correlations across regions via a conditional autoregressive (CAR) structure. Efficient estimation and inference is achieved through the fusion of functional principal component analysis (FPCA) and Markov Chain Monte Carlo (MCMC). Applications to the USRDS data highlight significant region- and facility-level risk factors of hospitalizations and characterize time periods and spatial locations with elevated hospitalization risk. Finite sample performance of the proposed methodology is studied through simulations.

Investigating Longitudinal Associations Between Racial Microaggressions, Coping, Racial/Ethnic Identity, and Mental Health in Black Girls and Women.

Racial microaggressions pose significant risk to health and well-being among Black adolescents and adults. Yet, protective factors (i.e., coping, racial/ethnic identity) can moderate the impact of racial microaggressions over time. Unfortunately, few studies have evaluated the role of these protective factors longitudinally or specifically among Black girls and women. In the current study, we focused on the experiences of Black girls and women and investigated the longitudinal links between racial microaggressions and mental health symptoms over 1 year. We then explored the role of two key protective factors as moderators-coping with racial discrimination and racial/ethnic identity-for mental health. Participants included 199 Black adolescent girls (Mage = 16.02) and 199 Black women (Mage = 42.82) who completed measures on two types of racial microaggressions, three types of coping strategies, racial/ethnic identity, and mental health symptomology. Girls and women completed measures at three time points over 1 year. Results indicated both types of microaggressions predicted increased mental health symptoms in Black women. Among Black girls, assumptions of criminality predicted increased externalizing symptoms only when protective factors were included in the model. Analysis of the protective factors indicated a potential direct benefit rather than a moderating role of coping with racial discrimination through positive thinking for mental health in both Black girls and women. Evidence suggests that coping may have had a direct rather than an indirect effect on Black girls' mental health over time. We conclude with future directions for research and considerations for practice.

The Use of Putative Dialysis Initiation Time in Comparative Outcomes of Patients with Advanced Chronic Kidney Disease: Methodological Aspects.

The latest data from the United States Renal Data Systems show over 134,000 individuals with end-stage kidney disease (ESKD) starting dialysis in the year 2019. ESKD patients on dialysis, the default treatment strategy, have high mortality and hospitalization, especially in the first year of dialysis. An alternative treatment strategy is (non-dialysis) conservative management (CM). The relative effectiveness of CM with respect to various patient outcomes, including survival, hospitalization, and health-related quality of life among others, especially in elderly ESKD or advanced chronic kidney disease patients with serious comorbidities, is an active area of research. A technical challenge inherent in comparing patient outcomes between CM and dialysis patient groups is that the start of follow-up time is "not defined" for patients on CM because they do not initiate dialysis. One solution is the use of putative dialysis initiation (PDI) time. In this work, we examine the validity of the use of PDI time to determine the start of follow-up for longitudinal retrospective and prospective cohort studies involving CM. We propose and assess the efficacy of estimating PDI time using linear mixed effects model of kidney function decline over time via simulation studies. We also illustrate how the estimated PDI time can be used to effectively estimate the survival distribution.

Multilevel modeling of spatially nested functional data: Spatiotemporal patterns of hospitalization rates in the US dialysis population.

End-stage renal disease patients on dialysis experience frequent hospitalizations. In addition to known temporal patterns of hospitalizations over the life span on dialysis, where poor outcomes are typically exacerbated during the first year on dialysis, variations in hospitalizations among dialysis facilities across the US contribute to spatial variation. Utilizing national data from the United States Renal Data System (USRDS), we propose a novel multilevel spatiotemporal functional model to study spatiotemporal patterns of hospitalization rates among dialysis facilities. Hospitalization rates of dialysis facilities are considered as spatially nested functional data (FD) with longitudinal hospitalizations nested in dialysis facilities and dialysis facilities nested in geographic regions. A multilevel Karhunen-Loéve expansion is utilized to model the two-level (facility and region) FD, where spatial correlations are induced among region-specific principal component scores accounting for regional variation. A new efficient algorithm based on functional principal component analysis and Markov Chain Monte Carlo is proposed for estimation and inference. We report a novel application using USRDS data to characterize spatiotemporal patterns of hospitalization rates for over 400 health service areas across the US and over the posttransition time on dialysis. Finite sample performance of the proposed method is studied through simulations.

Fixed Effects High-Dimensional Profiling Models in Low Information Context.

Profiling or evaluation of health care providers, including hospitals or dialysis facilities, involves the application of hierarchical regression models to compare each provider's performance with respect to a patient outcome, such as unplanned 30-day hospital readmission. This is achieved by comparing a specific provider's estimate of unplanned readmission rate, adjusted for patient case-mix, to a normative standard, typically defined as an "average" national readmission rate across all providers. Profiling is of national importance in the United States because the Centers for Medicare and Medicaid Services (CMS) policy for payment to providers is dependent on providers' performance, which is part of a national strategy to improve delivery and quality of patient care. Novel high dimensional fixed effects (FE) models have been proposed for profiling dialysis facilities and are more focused towards inference on the tail of the distribution of provider outcomes, which is well-suited for the objective of identifying sub-standard ("extreme") performance. However, the extent to which estimation and inference procedures for FE profiling models are effective when the outcome is sparse and/or when there are relatively few patients within a provider, referred to as the "low information" context, have not been examined. This scenario is common in practice when the patient outcome of interest is cause-specific 30-day readmissions, such as 30-day readmission due to infections in patients on dialysis, which is only about ~ 8% compared to the > 30% for all-cause 30-day readmission. Thus, we examine the feasibility and effectiveness of profiling models under the low information context in simulation studies and propose a novel correction method to FE profiling models to better handle sparse outcome data.

Categorization in infancy based on novelty and co-occurrence.

categories (i.e., groups of objects that do not share perceptual features, such as food) abound in everyday situations. The present looking time study investigated whether infants are able to distinguish between two abstract categories (food and toys), and how this ability may extend beyond perceived information by manipulating object familiarity in several ways. Test trials displayed 1) the exact familiarized objects paired as they were during familiarization, 2) a cross-pairing of these same familiar objects, 3) novel objects in the same category as the familiarized items, or 4) novel objects in a different category. Compared to the most familiar test trial (i.e., Familiar Category, Familiar Objects, Familiar Pairings), infants looked longer to all other test trials. Although there was a linear increase in looking time with increased novelty of the test trials (i.e., Novel Category as the most novel test trial), the looking times did not differ significantly between the Novel Category and Familiar Category, Unfamiliar Objects trials. This study contributes to our understanding of how infants form object categories based on object familiarity, object co-occurrence, and information abstraction.

Profiling dialysis facilities for adverse recurrent events.

Profiling analysis aims to evaluate health care providers, such as hospitals, nursing homes, or dialysis facilities, with respect to a patient outcome. Previous profiling methods have considered binary outcomes, such as 30-day hospital readmission or mortality. For the unique population of dialysis patients, regular blood works are required to evaluate effectiveness of treatment and avoid adverse events, including dialysis inadequacy, imbalance mineral levels, and anemia among others. For example, anemic events (when hemoglobin levels exceed normative range) are recurrent and common for patients on dialysis. Thus, we propose high-dimensional Poisson and negative binomial regression models for rate/count outcomes and introduce a standardized event ratio measure to compare the event rate at a specific facility relative to a chosen normative standard, typically defined as an "average" national rate across all facilities. Our proposed estimation and inference procedures overcome the challenge of high-dimensional parameters for thousands of dialysis facilities. Also, we investigate how overdispersion affects inference in the context of profiling analysis. The proposed methods are illustrated with profiling dialysis facilities for recurrent anemia events.

Nerve Blocks Prior to Microfocused Ultrasound Treatment are Safe and Reduce Patient Discomfort.

BACKGROUND: Microfocused ultrasound with visualization has become one of the more popular nonsurgical facial rejuvenation therapies available. Although the treatment has gained wide acceptance, providing adequate pain relief during the procedure can be challenging. OBJECTIVES: The aim of this study was to test our hypothesis that nerve blocks prior to treatment would be well tolerated and significantly reduce patient discomfort. METHODS: Subjects undergoing microfocused ultrasound were offered the choice of participating in a split face nerve block, bilateral block, or a control group. Nerves targeted included infraorbital, supratrochlear, supraorbital, zygomaticofrontal, mental, great auricular, and cervical plexus. Pain assessment was based on a 10-point Wong-Backer FACES Pain score. RESULTS: A total of 65 patients were included in the study: 28 in the split face group, 19 in the bilateral block group, and 18 without a block. The mean [standard deviation] pain score of the bilateral block cohort was 3.9 [1.2], and that of the control group was 5.1 [1.7] (P = 0.001). Patients in the split face cohort reported a higher pain score on the unblocked side of the face (7.5 [1.3]) than on the blocked side (2.9 [1.0]) (P < 0.001). The mean pain score for local anesthetic injection was 2.7 and 1.4 for the split face and the bilateral groups, respectively. There were no adverse events. CONCLUSIONS: Nerve blocks are well tolerated and significantly improve patient comfort during microfocused ultrasound treatment without compromising outcomes or increasing adverse events.

The Relationship Between Physical Examination and Ultrasonography of Large Entheses of the Achilles Tendon and Patellar Tendon Origin.

OBJECTIVE: To investigate the relationship between physical examination (PE) and sonographic features of enthesitis, based on anatomical sites. METHODS: The analysis was done using merged raw data of 3 studies on 2298 entheses. RESULTS: Patients with clinical Achilles enthesitis had more abnormalities on ultrasound (US): hypoechogenicity, p < 0.001; thickening, p = 0.001; Doppler signals, p = 0.002; and erosions, p = 0.02. The patellar tendon origin also correlated with PE but distal patellar tendon insertion and plantar aponeurosis were uncoupled from the US. CONCLUSION: The relationship between clinical and sonographic findings for large entheses is dependent on the anatomical site. For the patellar tendon origin and Achilles entheses, PE is significantly linked to US findings.

The Impact of Learning Multiple Real-World Skills on Cognitive Abilities and Functional Independence in Healthy Older Adults.

OBJECTIVE: The natural learning experience from infancy to emerging adulthood, when considerable cognitive and functional growth is observed, mandates learning multiple real-world skills simultaneously. The present studies investigated whether learning multiple real-world skills simultaneously is possible in older adults and also whether it improves both their cognitive abilities (working memory, episodic memory, and cognitive control) and functional independence. METHOD: Over two studies (15 and 27 participants), older adults learned at least three new skills (e.g., Spanish, drawing, music composition) simultaneously for 3 months. Participants completed cognitive and functional assessments before, during, and after the intervention in both studies. Participants were recruited sequentially for an intervention or no-contact control group in Study 1, and Study 2 included only an intervention group, who also completed assessments 4-6 weeks prior to the start of the intervention (i.e., they served as their own control group). RESULTS: Results from both studies show that simultaneously learning multiple skills is feasible and potentially beneficial for healthy older adults. Learning multiple skills simultaneously increased cognitive abilities in older adults by midpoint of the intervention, to levels similar to performance in a separate sample of middle-aged adults, 30 years younger. DISCUSSION: Our findings demonstrate the feasibility and potential of conducting a real-world skill-learning intervention involving learning three novel skills with older adults. Our multiskill intervention may provide broad cognitive gains, akin to the benefits experienced earlier in the life span.

A multilevel mixed effects varying coefficient model with multilevel predictors and random effects for modeling hospitalization risk in patients on dialysis.

For patients on dialysis, hospitalizations remain a major risk factor for mortality and morbidity. We use data from a large national database, United States Renal Data System, to model time-varying effects of hospitalization risk factors as functions of time since initiation of dialysis. To account for the three-level hierarchical structure in the data where hospitalizations are nested in patients and patients are nested in dialysis facilities, we propose a multilevel mixed effects varying coefficient model (MME-VCM) where multilevel (patient- and facility-level) random effects are used to model the dependence structure of the data. The proposed MME-VCM also includes multilevel covariates, where baseline demographics and comorbidities are among the patient-level factors, and staffing composition and facility size are among the facility-level risk factors. To address the challenge of high-dimensional integrals due to the hierarchical structure of the random effects, we propose a novel two-step approximate EM algorithm based on the fully exponential Laplace approximation. Inference for the varying coefficient functions and variance components is achieved via derivation of the standard errors using score contributions. The finite sample performance of the proposed estimation procedure is studied through simulations.