Terms of Engagement: Understanding the Motivations, Preferences, and Attitudes of Older Adults Toward Mobile Cognitive Assessment and Training

BACKGROUND AND OBJECTIVES

The future of cognitive assessment is likely to involve mobile applications for smartphones and tablets; cognitive training is also often delivered in these formats. Unfortunately, low adherence to these programs can hinder efforts at the early detection of cognitive decline and interfere with examining cognitive training efficacy in clinical trials. We explored factors that increase adherence to these programs among older adults.

RESEARCH DESIGN AND METHODS

Focus groups were conducted with older adults (N = 21) and a younger adult comparison group (N = 21). Data were processed using reflexive thematic analysis with an inductive, bottom-up approach.

RESULTS

Three primary themes related to adherence were developed from the focus group data. Switches of engagement reflects factors that must be present; without them, engagement is unlikely. Dials of engagement reflects a cost-benefit analysis that users undergo, the outcome of which determines whether a person will be more or less likely to engage. Bracers of engagement reflects factors that nudge users toward engagement by minimizing barriers associated with the other themes. Older adults in general were more sensitive to opportunity costs, preferred more cooperative interactions, and were more likely to mention technology barriers.

DISCUSSION AND IMPLICATIONS

Our results are important for informing the design of mobile cognitive assessment and training apps for older adults. These themes provide guidance about ways apps could be modified to increase engagement and adherence, which in turn can more effectively facilitate the early detection of cognitive impairment and the evaluation of cognitive training efficacy.

Adherence Promotion With Tailored Motivational Messages: Proof of Concept and Message Preferences in Older Adults

This study examined the feasibility of using tailored text messages to promote adherence to longitudinal protocols and determined what facets of text message tone influence motivation. Forty-three older adults (Mage = 73.21, SD = 5.37) were recruited to engage in video-game-based cognitive training for 10 consecutive days. Participants received encouraging text messages each morning that matched their highest or lowest ranking reasons for participating in the study, after which they rated how effective each message was in motivating them to play the games that day. After 10 days, participants rated all possible messages and participated in semi-structured interviews to elicit their preferences for these messages. Results showed that messages matching participants' reasons for participating were more motivating than mismatched messages. Further, participants preferred messages that were personalized (i.e., use second person voice) and in formal tones. Messages consistent with these preferences were also rated as more motivating. These findings establish the feasibility of using message tailoring to promote adherence to longitudinal protocols and the relevance of tailoring messages to be personal and formal.

Components of navigation ability and their predictors in a community-dwelling sample of older adults

Introduction: Navigation, as a complex skill important for independent living, requires a variety of cognitive processes. Current scales tapping components are lengthy and can be burdensome for older adults. Methods: Community-dwelling older adults (n = 380, age 60-90 years) completed an online survey tapping wayfinding, being lost navigating, and needing help navigating. Participants then completed objective measures of navigation ability and self-reported memory ability. Cronbach's α was calculated for navigation subscales consisting of subsets of the Wayfinding Questionnaire and Santa Barbara Sense of Direction Questionnaire, and an exploratory factor analysis (EFA) was conducted. Regression analyses were used to test whether objective navigation, memory, and demographic information navigation predicted navigation subscale performance. Results: Each of the individual subscales demonstrated high reliability. EFA generated five unique factors: routing, mental mapping, navigation in near vicinities, feeling lost in far vicinities, and needing help in far vicinities. Across regression analyses, memory, gender, and performance on the Spatial Orientation Test were significant predictors. Discussion: Navigation is a multi-faceted construct that can be reliably measured using concise surveys. Further research is necessary to understand the intricacies of aging and navigation.

Financial Fraud of Older Adults During the Early Months of the COVID-19 Pandemic

BACKGROUND AND OBJECTIVES

Coronavirus disease 2019 (COVID-19) created a "perfect storm" for financial fraud targeting older adults. Guided by the Contextual Theory of Elder Abuse, we focused on individual and systemic contexts to examine how older adults became prey to financial fraud.

RESEARCH DESIGN AND METHODS

In July 2020, 998 adults who were 60-98 years of age (93% White; 64% female) completed an online survey about experiences with financial fraud. Participants were recruited from gerontology research registries at Florida State University, University of Pittsburg, Virginia Tech, and Wayne State University.

RESULTS

Over half (65.9%) of the respondents experienced a COVID-19-related scam attempt, with charity contributions (49%) and COVID-19 treatments (42%) being the most common. Perpetrators commonly contacted older adults electronically (47%) two or more times (64%). Although most respondents ignored the request (i.e., hung up the phone and deleted text/e-mail), 11.3% sent a requested payment, and 5.3% provided personal information. Predictors of vulnerability included contentment with financial situation, concern about finances in the aftermath of the pandemic, and wishing to talk to someone about financial decisions. Respondents targeted for a non-COVID-19 scam attempt were less likely to be targets of a COVID-19-related scam.

DISCUSSION AND IMPLICATIONS

Older adults who were financially secure, worried about their financial situation, or wished they could speak with someone about their financial decisions appeared susceptible to falling victim to a fraud attempt. The high number of attempts indicates a need for a measurable and concerted effort to prevent the financial fraud of older adults.

Individualistic Versus Collaborative Learning in an eHealth Literacy Intervention for Older Adults: Quasi-Experimental Study

BACKGROUND

Older adults tend to have insufficient health literacy, which includes eHealth literacy-the ability to access, assess, and use digital health information. Interventions using methods such as collaborative learning (CL) and individualistic learning (IL) may be effective in addressing older adults' low eHealth literacy, but little is known about the short- and long-term effects of CL versus IL on older adults' eHealth literacy.

OBJECTIVE

The objective of this study was to use a 3 × 2 × 3 mixed factorial design to examine older adults' learning with CL versus IL for eHealth literacy.

METHODS

Older adults (N=466; mean age 70.5, SD 7.2; range 60-96 years) from diverse racial and ethnic groups were randomly assigned to either the CL or IL group (233/466, 50% in each). The intervention consisted of 4 weeks of training in 2-hour sessions held twice a week. Using ANOVA and multiple regression, we focused on the main effects of learning condition and interaction between learning condition and previous computer experience. Learning method (CL or IL) and previous computer experience (experienced, new, or mixed) were between-subject variables, and time of measurement (pretest measurement, posttest measurement, and 6-month follow-up) was the within-subject variable. Primary outcome variables were eHealth literacy efficacy, computer and web knowledge, basic computer and web operation skills, information-seeking skills, and website evaluation skills. Control variables were age, sex, education, health status, race and ethnicity, income, primary language, and previous health literacy.

RESULTS

eHealth literacy efficacy, computer and web knowledge, basic computer and web operation skills, information-seeking skills, and website evaluation skills improved significantly (P<.001 in all cases) from before to after the intervention. From postintervention measurement to 6-month follow-up, there was a significant interaction between learning condition and previous computer experience based on 1 outcome measure, computer and web operation skills (F2,55=3.69; P=.03). To maintain computer and web operation skills 6 months after the intervention, it was more effective for people with little to no previous computer experience to learn individually, whereas for people with more previous computer experience, it was more effective to learn collaboratively. From postintervention measurement to 6-month follow-up, statistically significant decreases were found in 3 of the 5 outcome measures: eHealth literacy efficacy, computer and web knowledge, and basic computer and web operation skills (P<.001 for all 3 cases).

CONCLUSIONS

Older adults' eHealth literacy can be improved through effective intervention, and the IL or CL condition may have little effect on short-term outcomes. However, to maintain long-term benefits, it may be best to learn collaboratively with others who have similar previous computer experience. eHealth literacy is multidimensional, with some components retained better over time. Findings suggest a need for resources to provide continuous training or periodic boosting to maintain intervention gains.

RELIABILITY AND VALIDITY OF A REDUCED SET OF NAVIGATION ITEMS IN COMMUNITY-DWELLING OLDER ADULTS

Navigation is a complex skill that is used in everyday living, whether it be to travel across a country or to travel to a local store. How one successfully navigates through their environment involves many different processes, including spatial navigation, route generation, and orientation. An issue with investigating those separate constructs within navigation is the number of questions required to assess them reliably. As a part of a larger project, a large sample of community-dwelling older adults (ages 60–90) completed an online survey answering questions related to navigation. Among those were three subscales: a general wayfinding subscale, a subscale asking how often they felt lost when moving around near and far spaces, and a subscale asking how often they needed help navigating around near and far spaces. Each of these subscales contained fewer than eight items. The goal of the analysis was to determine the reliability and validity of these subscales, and this was accomplished through calculating Cronbach’s α and an exploratory factor analysis (EFA). Cronbach’s α for each of the individual subscales were above 0.8, indicating high reliability. EFA results output five unique factors. Noticeably, the wayfinding subscale was broken into two factors, one for route generation ability and one for mental mapping ability. while the “Feeling Lost” and “Needing Help” subscales produced a dichotomy between nearer distances (ex. Your immediate neighborhood) and farther distances (ex. Your state). This contrast, along with its implications, are discussed further.

CHARACTERISTICS OF LEADERS OF AGING CENTERS

In December of 2021 and January of 2022, current leaders of Centers on Aging belonging to the GSA Age Directors interest group were invited to fill out a survey inquiring about their backgrounds, training for leadership, and perceived needs for training via an online Qualtrics survey. Thirty-one responses were received though a few responses were missing for most questions. The sample mostly resided in the USA (86%), and identified mainly as female (63% female, 37% male). Most were married (90%). The average age of a respondent was 58 years (SD=9; range 37-74). Respondents were not diverse: 97% White. Most had doctoral level education (1 Master’s level). The results indicate that there is a need to enhance and develop leadership skills in diverse mid-career gerontologists in order to provide replacements for an aging cohort of directors. Results are also consistent with prior National Academies’ recommendations for training the gerontological workforce.

ACHIEVING DIGITAL EQUITY FOR OLDER PERSONS WITH EMERGING TECHNOLOGY: THE CASE OF NORTH AMERICA

The United Nations’ theme for the International Day of Older Persons 2021 was “Digital Equity for All Ages”. I define digital equity, then compare progress in North America, focusing on Canada, the USA, and Mexico for internet, smartphone, and broadband access. An age-related digital divide for internet and computer use, first identified in the USA in 1999, persists. Where year-to-year comparisons are available, I also discuss the impact of the pandemic on technology adoption. National data sets measuring internet use show that there are similarities and differences in the USA and Canada in factors influencing adoption. For smartphone ownership, Mexico showed gender differences favoring men, unlike the case in the USA and Canada. For broadband access in the USA inequity was seen as a function of age, race/ethnicity, education and income, and urban/rural residence. I discuss potential reasons for inequitable access and potential approaches to achieve greater equity.

TECHNOLOGY TO SUPPORT AGING ADULTS: FUTURE APPLICATIONS

The aging of the population is projected to continue for the upcoming decades. Thus, innovative strategies are needed to support current and future cohorts of older adults. In this regard, there are exciting developments in technology that have the potential to meet the needs of population aging. This summary presentation will discuss emerging technology applications such as developments in artificial intelligence, sensing technologies, and robotics that can be used to foster everyday activities, cognitive, physical, and emotional health. A framework will be provided to characterize current and emerging technology applications for older adults within life domains. Current research examining the efficacy, feasibility, and acceptability of these technologies with older adult populations will be also summarized. Recommendations for needed future research in the aging and technology domain will also be provided to ensure that the emerging technology applications are designed to meet the needs, abilities, and preferences of aging adults.

Motivation to Engage in Aging Research: Are There Typologies and Predictors?

BACKGROUND AND OBJECTIVES

Study recruitment and retention of older adults in research studies is a major challenge. Enhancing understanding of individual differences in motivations to participate, and predictors of motivators, can serve the dual aims of facilitating the recruitment and retention of older adults, benefiting study validity, economy, and power.

RESEARCH DESIGN AND METHODS

Older adults (N = 472) past and potential participants were surveyed about motivations to participate in research, demographic, and individual difference measures (e.g., health status, cognitive difficulties). Latent class and clustering analyses explored motivation typologies, followed by regression models predicting individual motivators and typologies.

RESULTS

Older adults endorsed a diversity of research motivations, some of which could be predicted by individual difference measures (e.g., older participants were more motivated by the desire to learn new technology, participants without a college education were more motivated by financial compensation, and participants with greater self-reported cognitive problems were more likely to participate to gain cognitive benefit). Clustering analysis revealed 4 motivation typologies: brain health advocates, research helpers, fun seekers, and multiple motivation enthusiasts. Cognitive difficulties, age, employment status, and previous participation predicted membership in these categories.

DISCUSSION AND IMPLICATIONS

Results provide an understanding of different participant motivations beyond differences between younger and older adults and begin to identify different classes of older adults motivated to participate in research studies. Results can provide guidance for targeted recruitment and retention strategies based on individual differences in stated or predicted motivations.

Deep learning-based predictions of older adults' adherence to cognitive training to support training efficacy

As the population ages, the number of older adults experiencing mild cognitive impairment (MCI), Alzheimer's disease, and other forms of dementia will increase dramatically over the next few decades. Unfortunately, cognitive changes associated with these conditions threaten independence and quality of life. To address this, researchers have developed promising cognitive training interventions to help prevent or reverse cognitive decline and cognitive impairment. However, the promise of these interventions will not be realized unless older adults regularly engage with them over the long term, and like many health behaviors, adherence to cognitive training interventions can often be poor. To maximize training benefits, it would be useful to be able to predict when adherence lapses for each individual, so that support systems can be personalized to bolster adherence and intervention engagement at optimal time points. The current research uses data from a technology-based cognitive intervention study to recognize patterns in participants' adherence levels and predict their future adherence to the training program. We leveraged the feature learning capabilities of deep neural networks to predict patterns of adherence for a given participant, based on their past behavior. A separate, personalized model was trained for each participant to capture individualistic features of adherence. We posed the adherence prediction as a binary classification problem and exploited multivariate time series analysis using an adaptive window size for model training. Further, data augmentation techniques were used to overcome the challenge of limited training data and enhance the size of the dataset. To the best of our knowledge, this is the first research effort to use advanced machine learning techniques to predict older adults' daily adherence to cognitive training programs. Experimental evaluations corroborated the promise and potential of deep learning models for adherence prediction, which furnished highest mean F-scores of 75.5, 75.5, and 74.6% for the Convolution Neural Network (CNN), Long Short-Term Memory (LSTM) network, and CNN-LSTM models respectively.

Technology obsolescence across the adult lifespan in a USA internet sample

We know that older adults are less likely to own certain technological devices, such as smartphones, a technology now integral to telehealth. However, for those older adults who do own devices, we know very little about how their devices may differ from those of younger adults. The age of a device can determine the types of programs it can run, as well as the level of protection it has against malicious code. The following study is an attempt to understand the ages of devices owned by different demographic groups. An electronic survey was sent to American adults from ages 19-97, querying the types of devices they own, how old those devices are, when they plan on replacing them, and demographic information. Regression models were employed to determine the factors that predict device ownership and the age of the devices owned. We replicate the finding that older adults are less likely to own certain devices, like smartphones and laptops. However, they may be more likely to own more dated devices, such as non-smart mobile phones. Models of device age showed that older adults are more likely to own older smartphones, as well as older desktop and laptop computers. Thus, older adults may be more susceptible to hacking, due to obsolete technology. In some cases, they also may not have devices modern enough for technology-based health interventions. Thus, obsolete devices may present an additional barrier for adoption of technology-based interventions by older adults.

A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training

Adequate adherence is a necessary condition for success with any intervention, including for computerized cognitive training designed to mitigate age-related cognitive decline. Tailored prompting systems offer promise for promoting adherence and facilitating intervention success. However, developing adherence support systems capable of just-in-time adaptive reminders requires understanding the factors that predict adherence, particularly an imminent adherence lapse. In this study we built machine learning models to predict participants' adherence at different levels (overall and weekly) using data collected from a previous cognitive training intervention. We then built machine learning models to predict adherence using a variety of baseline measures (demographic, attitudinal, and cognitive ability variables), as well as deep learning models to predict the next week's adherence using variables derived from training interactions in the previous week. Logistic regression models with selected baseline variables were able to predict overall adherence with moderate accuracy (AUROC: 0.71), while some recurrent neural network models were able to predict weekly adherence with high accuracy (AUROC: 0.84-0.86) based on daily interactions. Analysis of the post hoc explanation of machine learning models revealed that general self-efficacy, objective memory measures, and technology self-efficacy were most predictive of participants' overall adherence, while time of training, sessions played, and game outcomes were predictive of the next week's adherence. Machine-learning based approaches revealed that both individual difference characteristics and previous intervention interactions provide useful information for predicting adherence, and these insights can provide initial clues as to who to target with adherence support strategies and when to provide support. This information will inform the development of a technology-based, just-in-time adherence support systems.

Older Adults' concerns regarding Hurricane-Induced evacuations during COVID-19: Questionnaire findings

The COVID-19 pandemic has drastically affected our day-to-day life in the last few years. This problem becomes even more challenging when older adults are considered due to their less powerful immune system and vulnerability to infectious diseases, especially in Florida where 4.5 million people aged 65 and over reside. With its long coastline, large and rapidly growing of older adult population, and geographic diversity, Florida is also uniquely vulnerable to hurricanes, which significantly increases the associated risks of COVID-19 even further. This study investigates older adults' evacuation-related concerns during COVID-19 using statistical analysis of a questionnaire conducted among 389 older adult Florida residents. The questionnaire includes questions concerning demographic information and older adults' attitudes toward hurricane-induced evacuations during the COVID-19 pandemic. Ordered Probit regression models were developed to investigate the impacts of demographic parameters on older adults' tendencies toward evacuating as well as their preferences to stay at home or shelter during the pandemic. The model results reveal that male participants felt safer to evacuate compared to females. Also, any decrease in the level of income was associated with an increase in the need for help for evacuation by 18%. Findings indicated that the participants who found the evacuation safe normally also had a positive attitude toward staying in their vehicle, hotel, or even shelters if maintaining social distance was possible. Emergency management policies can utilize these findings to enhance hurricane preparations for dealing with the additional health risks posed by the pandemic for older adults, a situation that could be exacerbated by the upcoming hurricane season in Florida.

A Grand Challenge for Psychology: Reducing the Age-related Digital Divide

World-wide population aging and rapid diffusion of digital technology have converged to produce an age-related digital divide in technology adoption, as seen in use of the internet and ownership of smartphones. Given the centrality of these technologies for full participation in modern society, reducing that gap is an important challenge for psychologists. We outline more and less malleable factors associated with technology adoption. We argue that interventions that can change both the aging user and the design of products will be necessary. Adaptive technology systems that incorporate artificial intelligence and extended reality represent promising new approaches to reducing the age-related digital divide.

Relative effectiveness of general versus specific cognitive training for aging adults

In the present study, we examined three experimental cognitive interventions, two targeted at training general cognitive abilities and one targeted at training specific instrumental activities of daily living (IADL) abilities, along with one active control group to compare benefits of these interventions beyond expectation effects, in a group of older adults (N = 230). Those engaged in general training did so with either the web-based brain game suite BrainHQ or the strategy video game Rise of Nations, while those trained on IADL skills completed instructional programs on driving and fraud awareness. Active control participants completed sets of puzzles. Comparing baseline and postintervention data across conditions, none of the preregistered primary outcome measures demonstrated a significant interaction between session and intervention condition, indicating no differential benefits. Analysis of expectation effects showed differences between intervention groups consistent with the type of training. Those in the IADL training condition did demonstrate superior knowledge for specific trained information (driving and finances). Twelve months after training, significant interactions between session and intervention were present in the primary measure of fraud detection, as well as the secondary measures of the letter sets task and Rey's Auditory Verbal Learning Test. However, the specific source of these interactions was difficult to discern. At 1-year follow-up those in the IADL condition did not maintain superior knowledge of driving and finances gained through training, as was present immediately postintervention. Hence, the interventions, when compared to an active control condition, failed to show general or specific transfer in a meaningful or consistent way. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Digital transformation of everyday lives of older Swiss adults: use of and attitudes toward current and future digital services

Digital (consumer) services, such as ticket machines, self-checkout, and online reservations, have become increasingly important in modern society. Studies on adoption of these services and openness to using future public digital services (e.g., online voting, online taxes, electronic patient records) have mostly focused on younger adults or nonrepresentative samples among older adults. Therefore, two important questions remain that can best be addressed with representative sampling: To what extent do older adults use or are willing to use current and future digital services in their everyday lives? How do older adults evaluate the ease of use of these services?. The study included data on use of current and future digital services among a large Swiss sample of 1149 people age 65 years and older (mean age: 74.1 years, SD: 6.69). Descriptive and multivariate analyses showed that (a) established services such as cash machines were used more often than new services, such as self-checkout apps or machines. (b) Perceived ease of use is related to age, socioeconomic status, health, and interest in technology. (c) Only 8.9% had an overall positive attitude toward these digital services, and this attitude was predicted by age, gender, socioeconomic status, and interest in technology. (d) Participants were more often open to filing taxes online than voting online, and openness was predicted by age, income, and interest in technology. Today, mainly older adults with a high interest in technology use digital services. Nevertheless, potential for greater use is evident.

Temporal Subtyping of Alzheimer's Disease Using Medical Conditions Preceding Alzheimer's Disease Onset in Electronic Health Records

Subtyping of Alzheimer's disease (AD) can facilitate diagnosis, treatment, prognosis and disease management. It can also support the testing of new prevention and treatment strategies through clinical trials. In this study, we employed spectral clustering to cluster 29,922 AD patients in the OneFlorida Data Trust using their longitudinal EHR data of diagnosis and conditions into four subtypes. These subtypes exhibit different patterns of progression of other conditions prior to the first AD diagnosis. In addition, according to the results of various statistical tests, these subtypes are also significantly different with respect to demographics, mortality, and prescription medications after the AD diagnosis. This study could potentially facilitate early detection and personalized treatment of AD as well as data-driven generalizability assessment of clinical trials for AD.

Does Computer Use Improve Older Adults' Cognitive Functioning? Evidence From the Personal Reminder Information and Social Management Trial

BACKGROUND AND OBJECTIVES

Numerous longitudinal studies suggest that technology use in late adulthood is associated with cognitive benefits. Using data from a randomized controlled trial, the current study examined whether computer use improves cognition in older adults with little to no previous computer experience.

RESEARCH DESIGN AND METHODS

This study used data from the Personal Reminder Information and Social Management (PRISM) trial. Community-dwelling older adults with little previous computer experience (MAge = 76.15) were randomly assigned to learn and use a computer (the PRISM system, n = 150) or interact with parallel content delivered in a nondigital format (paper binder, n = 150) for 12 months. Objective and subjective cognitive outcomes were measured before (pretest) and after the intervention (posttest). Latent change score models and Bayesian analysis of variances were used to examine cognitive change at the ability and individual measure level.

RESULTS

Computer training and use for 12 months did not lead to cognitive improvements at the ability level. Strong evidence against cognitive benefits at the individual measure level was also observed.

DISCUSSION AND IMPLICATIONS

Casual computer use does not provide enough cognitive stimulation to improve cognition in late adulthood. Cognitive benefits observed in longitudinal studies may be mediated by other factors or influenced by confounding variables.

PRISM 2.0: A Technology System to Support Resource Access and Social and Cognitive Engagement

Social isolation and lack of engagement are common among older adults and present a risk for emotional, physical and cognitive decline. Technology offers the potential of remediating these risks and enhancing opportunities for connectivity. In this paper we present an overview of the PRISM 2.0 multi-site RCT, which evaluated a simple to use Personalized Reminder Information and Social Management System (PRISM) among a sample of two hundred and forty-eight adults age 65+ in diverse contexts (Rural Locations, Assisted Living Communities and Senior Housing). PRISM 2.0 is a tablet-based system, intended to provide support for access to resources and information, new learning, social and cognitive engagement, and memory. We describe the goals and content of PRISM, the user-centered design process, and measurement strategies. We also discuss the challenges of conducting the trial during the COVID-19 pandemic and the strategies used to adapt the trial protocol within the three contexts.

PRISM 2.0: Technical Challenges

PRISM 2.0 was designed to run on Android tablets and made use of both customized apps that relied on Google’s browser and e-mail functionality as well as commercial apps, such as Microsoft’s Skype for videoconferencing. We also made use of functionality provided by our partner AT&T, such as their sim cards to provide cell-based internet connectivity to participants who did not have access to Wi-Fi internet services to their home (cable, DSL), as well as tablet management software to deploy updates. The Miami site provided central management and tablet deployment and redeployment services and support as well as coordinating locally provided tech support at the three sites. We discuss some of the technical challenges associated with these arrangements. We focus on how changes to the operating system broke some of our apps necessitating substitution of other apps and provision of new training, and how Covid-19 affected technical support.

AUGMENT: Navigation Apps Instruction for Older Adults With Cognitive Impairment

Augmenting User Geocordinates and Mobility by ENhanced Tutorials (AUGMENT) is a development project in the ENHANCE Rehabilitation Engineering Research Center aiming to promote community engagement for aging adults with cognitive impairment (CI) from stroke, traumatic brain injury, and mild cognitive impairment. AUGMENT aims include 1) providing proof of concept that a robust instructional package can support successful use of existing, complex navigation apps, Google maps and rideshare app Uber, by a diverse set of people with CI; and 2) providing proof of product by testing performance with and without instruction. We discuss the needs assessment phase and development of new tests to assess wayfinding abilities and reported difficulties with navigation, using a control sample of 384 community-dwelling older adults. We found that self-reported navigation difficulties are predicted (R-square = .28) by gender, a spatial orientation test, self-reported memory ability, and severity of memory difficulty.

Aims of the Adherence Promotion With Person-Centered Technology (APPT) Project

The APPT project supports the early detection and treatment of age-related cognitive decline and dementia by 1) enhancing adherence to cognitive intervention and assessment protocols, 2) improving understanding of barriers to long-term adherence, and 3) developing algorithms for predicting and preventing adherence failures. Two randomized controlled trials will test an adaptive technology support system predicted to boost adherence to cognitive protocols over a period of six months within samples of older adults with and without cognitive impairment. These studies will provide insight into the benefits of adherence support, and individual difference factors that should shape the adherence protocol, informing the process of identifying individuals who would benefit from additional support and predicting and preventing extended adherence failures before they happen. These studies should improve early detection and treatment of cognitive decline, extend functional independence, and improve lives of those with cognitive impairment as well as the lives of their families.

Financial Exploitation of Older Adults During the Early Months of the COVID-19 Pandemic

COVID-19 created a “perfect storm” for financial exploitation directed at older adults. We invited adults aged 60 and older enrolled in gerontology research registries at Virginia Tech, Florida State University, Wayne State University, and University of Pittsburgh to complete an on-line survey about experiences with financial exploitation by strangers. The 997 respondents ranged in age from 60 to 98 (M = 71.3; SD = 6.8); most identified as White (93.4%), female (64.2%) and living with a spouse/partner (58%). Approximately one-half of respondents (56.87%) reported experiencing a scam attempt about COVID-19 issues. Most contact by scammers was electronic (49%) and frequently occurred two or more times (40%). Most respondents ignored the request (i.e., hung up phone, deleted text/email, threw away mail). However, 9% sent the requested payment, and 4% gave the scammer their personal information. Confidence in financial matters and having attended financial educational programs protected older adults from being scammed.

Everyday Needs Assessment for Cognitive Tasks: Challenges for Persons With Cognitive Impairment

ENACT (Everyday Needs Assessment for Cognitive Tasks) is an exploration and discovery project to gather information on challenges in daily and community living experienced by individuals aging with compromised cognition due to mild cognitive impairment, traumatic brain injury, or post-stroke. We are exploring their challenges through a longitudinal needs assessment study involving interviews with older adults with cognitive impairment and their care partners. We will describe the study development process wherein we interviewed subject matter experts, including persons with professional (neurology, rehabilitation, gerontology) or personal experience with individuals who have cognitive impairment. Based on their collective insights, we selected the following categories of activities for the ENACT in-depth interviews: health, social engagement, transportation, domestic life, and leisure/recreation. The ENACT longitudinal data will provide insights to guide development of adaptive, context-sensitive technology-based supports for the AUGMENT, DREAM, and STRUMM projects described in this symposium, as well as other initiatives.

Development of the DREAM System: Digital Reminders for Everyday Activity Memory

Prospective memory, the ability to remember to execute an intention in the future, is crucial for the performance of many everyday tasks important for independent living. Prospective memory abilities decline with age, and older adults living with mild cognitive impairment (MCI), cognitive impairment due to traumatic brain injury (TBI), and cognitive impairment due to stroke are especially susceptible to prospective memory failures. The goal of the Digital Reminders for Everyday Activity Memory (DREAM) project is first to establish proof of concept for an adaptive cognitive aid to support the prospective memory of older adults with various cognitive impairments, and then establish proof of product in studies examining the use of a working prototype within the lab and within participants’ homes. Data will be presented from initial work verifying product requirements through engagement with stakeholders, including subject matter experts, older adults with cognitive impairments, and their care partners.

Challenges of Quantifying PRISM 2.0 and Tablet Use

As with the PRISM 1.0 trial, an important outcome of the PRISM 2.0 trial is use of the PRISM system and use of the PRISM system compared to the control condition (a standard tablet without the PRISM software). Frequent use over time is an important measure of system success. Further, use data provide key measures of system usefulness and usability. What features do participants use most and how often? Within those features, what activities do they engage in? What are the patterns of use throughout the trial, and how does PRISM system use compare to the control condition? However, quantifying use is not an easy task. This talk presents the challenges of quantifying use of a complex, multi-faceted system, and of making meaningful comparisons in use between two very different systems. Analysis approaches and solutions are discussed.

STRUMM: An Intelligent, Adaptive Software Package for Older Adults With a Cognitive Impairment

Many older adults have a cognitive impairment (CI), which negatively impacts on their quality of life and threatens their independence. In this presentation, we provide an overview of the conceptual framework, structure, and processes of our multi-site Center, ENHANCE, which is focused on developing technology support for aging adults with a CI. ENHANCE has two cross-site research projects, two cross-site development projects, training, and dissemination components. A core battery of measures is collected across all projects. We also discuss the Supportive Technology Resources through Usability & Machine-learning Methods (STRUMM) research project, which focuses on an innovative intelligent adaptive software package aimed at providing cognitive and social support, and support for resource access to aging adults with a CI. STRUMM is designed to meet the user’s varying cognitive needs. Finally, we present preliminary data regarding the perceived usability and value of STRUMM from our clinical partners and potential user groups.

Investigating message framing to improve adherence to technology-based cognitive interventions

A cognitive intervention study was conducted with the purpose of exploring methods to improve adherence to a technology-based cognitive intervention and uncover individual differences that predict adherence (N = 120). The study was divided into two phases: Phase 1, in which participants were asked to follow a prescribed schedule of training that involved gamified neuropsychological tests administered via tablet, and Phase 2, in which participants were asked to play as frequently as they wished. Positive- and negative-framed messages about brain health were delivered via the software program, and measures of cognition, technology proficiency, self-efficacy, technology attitudes, and belief in the benefits of cognitive training were collected. Generalized linear mixed-effects models revealed that positive-framed messages encouraged greater adherence over negative-framed messages, but this effect was restricted to Phase 2 of the study in the absence of social pressure. Measures of memory and self-efficacy demonstrated some, but limited, ability to predict individual differences in adherence. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

How the clinical research community responded to the COVID-19 pandemic: an analysis of the COVID-19 clinical studies in ClinicalTrials.gov

OBJECTIVE

In the past few months, a large number of clinical studies on the novel coronavirus disease (COVID-19) have been initiated worldwide to find effective therapeutics, vaccines, and preventive strategies for COVID-19. In this study, we aim to understand the landscape of COVID-19 clinical research and identify the issues that may cause recruitment difficulty or reduce study generalizability.

METHODS

We analyzed 3765 COVID-19 studies registered in the largest public registry-ClinicalTrials.gov, leveraging natural language processing (NLP) and using descriptive, association, and clustering analyses. We first characterized COVID-19 studies by study features such as phase and tested intervention. We then took a deep dive and analyzed their eligibility criteria to understand whether these studies: (1) considered the reported underlying health conditions that may lead to severe illnesses, and (2) excluded older adults, either explicitly or implicitly, which may reduce the generalizability of these studies to the older adults population.

RESULTS

Our analysis included 2295 interventional studies and 1470 observational studies. Most trials did not explicitly exclude older adults with common chronic conditions. However, known risk factors such as diabetes and hypertension were considered by less than 5% of trials based on their trial description. Pregnant women were excluded by 34.9% of the studies.

CONCLUSIONS

Most COVID-19 clinical studies included both genders and older adults. However, risk factors such as diabetes, hypertension, and pregnancy were under-represented, likely skewing the population that was sampled. A careful examination of existing COVID-19 studies can inform future COVID-19 trial design towards balanced internal validity and generalizability.

Older Adults’ Adherence to Technology-Based Intervention: The Role of Messaging and Individual Differences

Adherence to health behaviors is often poor, including adherence to at-home technology-based interventions. This study (N=120) explored adherence to a cognitive training intervention delivered via computer tablet, assessed adherence over a 4.5 month period, explored how individual difference factors shaped adherence, and tested the efficacy of message framing manipulations (positive vs. negative framing) in boosting adherence. Individual difference factors predicted adherence, including variations in self-efficacy and belief in the efficacy of cognitive training. Overall message framing had little impact. However, during the final portion of the study in which participants were asked to play as much or as little as they wanted instead of following a schedule, participants who received positively framed messages engaged with the intervention more. Implications for predicting and boosting adherence to home delivered technology-based interventions will be discussed.

Acceptance of Transportation Technologies by Aging Adults

Older adults are at greater risk of death and serious injury in transportation crashes which have been increasing in older adult cohorts relative to younger cohorts. Can technology provide a safer road environment? Even if technology can mitigate crash risk, is it acceptable to older road users? We outline the results from several studies that tested 1) whether advanced driver assistance systems (ADAS) can improve older adult driving performance, 2) older adults’ acceptance of ADAS and Autonomous Vehicle (AV) systems, and 3) perceptions of value for ADAS systems, particularly for blind-spot detection systems. We found that collision avoidance warning systems improved older adult simulator driving performance, but not lane departure warning systems. In a young to middle-aged sample the factor “concern with AV” showed age effects with older drivers less favorable. Older drivers, however, valued an active blind spot detection system more than younger drivers.

Introducing the ENHANCE (Enhancing Neurocognitive Health, Abilities, Networks, & Community Engagement) Center

Cognitive impairment (CI) refers to changes in cognition that result in difficulties remembering, learning new things, concentrating, making decisions important to everyday life, responding to environmental demands, or understanding social cues, and these difficulties can result in disability (limiting one or more major life activities). Existing and emerging technology applications hold promise for providing everyday support for older adults with CI, promoting independence and community living. However, these solutions will only be viable if they consider the needs, preferences, and abilities of older adults experiencing cognitive impairment. This talk introduces a new center, funded by the National Institute on Disability, Living, and Rehabilitation Research (NIDILRR), with the aim of supporting older adults with CI (MCI, CI as a result of traumatic brain injury or stroke) through adaptive and individualized technology solutions.

An Introduction to the Adherence Promotion With Person-Centered Technology Project

The massive potential of cognitive training and longitudinal cognitive assessment to detect and prevent age-related cognitive decline and dementia will not be realized unless individuals are willing and able to engage with these protocols for an extended period of time. Unfortunately, similar to other health behaviors, adherence to home-based assessment and training is frequently poor. Addressing the gap between potential and realized benefits is an urgent goal as the population ages. APPT investigates these and related issues within samples of older adults with and without cognitive impairment. Ultimately, two randomized controlled trials will test whether an adaptive, tailored, and integrated technology-based adherence support system can boost adherence, with the ultimate goal being the early detection and treatment of age-related cognitive decline and dementia. Initial algorithm development and application to existing datasets will be presented that will inform the design of a smart reminder system that will later be assessed.

How the clinical research community responded to the COVID-19 pandemic: An analysis of the COVID-19 clinical studies in ClinicalTrials.gov

OBJECTIVE

The novel coronavirus disease (COVID-19), broke out in December 2019, and is now a global pandemic. In the past few months, a large number of clinical studies have been initiated worldwide to find effective therapeutics, vaccines, and preventive strategies for COVID-19. In this study, we aim to understand the landscape of COVID-19 clinical research and identify the gaps such as the lack of population representativeness and issues that may cause recruitment difficulty.

MATERIALS AND METHODS

We analyzed 3,765 COVID-19 studies registered in the largest public registry - ClinicalTrials.gov, leveraging natural language processing and using descriptive, association, and clustering analyses. We first characterized COVID-19 studies by study features such as phase and tested intervention. We then took a deep dive and analyzed their eligibility criteria to understand whether these studies: (1) considered the reported underlying health conditions that may lead to severe illnesses, and (2) excluded older adults, either explicitly or implicitly, which may reduce the generalizability of these studies to the older adults population.

RESULTS

Most trials did not have an upper age limit and did not exclude patients with common chronic conditions such as hypertension and diabetes that are more prevalent in older adults. However, known risk factors that may lead to severe illnesses have not been adequately considered.

CONCLUSIONS

A careful examination of existing COVID-19 studies can inform future COVID-19 trial design towards balanced internal validity and generalizability.

When Going Digital Becomes a Necessity: Ensuring Older Adults' Needs for Information, Services, and Social Inclusion During COVID-19

Older adults are in triple jeopardy during COVID-19: compared with younger people, older adults are (1) more likely to develop serious conditions and experience higher mortality; (2) less likely to obtain high quality information or services online; and (3) more likely to experience social isolation and loneliness. Hybrid solutions, coupling online and offline strategies, are invaluable in ensuring the inclusion of vulnerable populations. Most of these solutions require no new inventions. Finding the financial resources for a rapid, well-coordinated implementation is the biggest challenge. Setting up the requisite support systems and digital infrastructure is important for the present and future pandemics.

Clinical Trial Generalizability Assessment in the Big Data Era: A Review

Clinical studies, especially randomized, controlled trials, are essential for generating evidence for clinical practice. However, generalizability is a long‐standing concern when applying trial results to real‐world patients. Generalizability assessment is thus important, nevertheless, not consistently practiced. We performed a systematic review to understand the practice of generalizability assessment. We identified 187 relevant articles and systematically organized these studies in a taxonomy with three dimensions: (i) data availability (i.e., before or after trial (a priori vs. a posteriori generalizability)); (ii) result outputs (i.e., score vs. nonscore); and (iii) populations of interest. We further reported disease areas, underrepresented subgroups, and types of data used to profile target populations. We observed an increasing trend of generalizability assessments, but < 30% of studies reported positive generalizability results. As a priori generalizability can be assessed using only study design information (primarily eligibility criteria), it gives investigators a golden opportunity to adjust the study design before the trial starts. Nevertheless, < 40% of the studies in our review assessed a priori generalizability. With the wide adoption of electronic health records systems, rich real‐world patient databases are increasingly available for generalizability assessment; however, informatics tools are lacking to support the adoption of generalizability assessment practice.

Assessing the Validity of a a priori Patient-Trial Generalizability Score using Real-world Data from a Large Clinical Data Research Network: A Colorectal Cancer Clinical Trial Case Study

Existing trials had not taken enough consideration of their population representativeness, which can lower the effectiveness when the treatment is applied in real-world clinical practice. We analyzed the eligibility criteria of Bevacizumab colorectal cancer treatment trials, assessed their a priori generalizability, and examined how it affects patient outcomes when applied in real-world clinical settings. To do so, we extracted patient-level data from a large collection of electronic health records (EHRs) from the OneFlorida consortium. We built a zero-inflated negative binomial model using a composite patient-trial generalizability (cPTG) score to predict patients' clinical outcomes (i.e., number of serious adverse events, [SAEs]). Our study results provide a body of evidence that 1) the cPTG scores can predict patient outcomes; and 2) patients who are more similar to the study population in the trials that were used to develop the treatment will have a significantly lower possibility to experience serious adverse events.

Aging: Older Adults' Driving Behavior Using Longitudinal and Lateral Warning Systems

OBJECTIVE

This study assessed older drivers' driving behavior when using longitudinal and lateral vehicle warning systems together.

BACKGROUND

Advanced driver assistance systems (ADAS) can benefit drivers of all ages. Previous research with younger to middle-aged samples suggests that safety benefits are not necessarily additive with additional ADAS. Increases in following distance associated with the use of forward collision warning (FCW) decreased when drivers also used lane departure warning (LDW), likely due to attending to the LDW more than the FCW.

METHOD

The current study used a driving simulator to provide 128 older drivers experience with FCW and/or LDW system(s) during a ~25-min drive to gauge their usage's effects on driving performance and subjective workload.

RESULTS

There were no significant differences found in headway distance between older drivers who used different combinations of FCW and LDW systems, but those who used an FCW system showed significantly longer time-to-collision (TTC) when approaching the critical event than those who did not. Users of LDW systems did not show reductions in standard deviation of lane position. Analyses of subjective workload measures showed no significant differences between conditions.

CONCLUSION

Findings suggest that FCW could increase older drivers' TTC over the course of a drive. Contrary to previous findings in younger samples, concurrent use of FCW and LDW systems did not adversely affect older drivers' longitudinal driving performance and subjective workload.

APPLICATION

Potential applications of this research include the assessment of older drivers' use of vehicle warning systems and their effects on subjective workload.

Depressive Symptoms as a Predictor of Memory Complaints in the PRISM Sample

Objectives

The current study investigated baseline and longitudinal relationships between memory complaints, depressive symptoms, and cognition in older adults.

Method

Using the sample from the Personal Reminder Information and Social Management trial, we generated path models predicting self-rated memory complaints measured by the Memory Functioning Questionnaire (MFQ).

Results

Our baseline models showed that more depressive symptoms were associated with reporting more frequent forgetting incidents and a greater decline in memory function. The baseline models also revealed that higher scores in a latent cognitive function were associated with reporting a greater decline in memory functioning and a greater use of mnemonics. However, cognitive predictors did not mediate the baseline associations between the MFQ measures and depressive symptoms. Further, these predictors were not able to directly predict the 12-month MFQ measures over and above the baseline effects. Including personality traits (neuroticism and conscientiousness) did not significantly affect the models.

Discussion

Our results suggest that memory complaints about frequency of forgetting can be the most reliable indicator of depression risk among the four factors in the MFQ. We discuss theoretical implications for longitudinal relationships between memory complaints, depressive symptoms, and cognitive function in older adults.

Shaking Confidence in Technology: Effects of an Earthquake-Induced Nuclear Disaster on Technology Adoption in Middle-Aged and Older Adults

Using the coincidental timing of a national survey conducted in Japan before and after the Fukushima Daiichi nuclear disaster in 2011, this study reports a rare natural experiment that explored how the experience of a nuclear disaster influenced technology adoption in middle-aged and older adults. We conducted path analyses assessing how technology or nontechnology adoption intention and behavior changed before and after the nuclear disaster and whether age could moderate the potential change over and above other relevant factors. Our models supported that Japanese middle-aged to older adults reported fewer technology adoption behaviors after experiencing of the earthquake. However, the negative impact of the earthquake was not more pronounced in older adults. Our results suggest that researchers need to pay more attention to the issue of how loss of trust and/or perceived risk affect technology adoption interacting with other relevant factors, particularly, age-related factors and abilities.

THE POTENTIAL AND PITFALLS OF GAMIFICATION TO SUPPORT OLDER ADULTS' ADHERENCE TO HEALTHCARE INTERVENTIONS

The addition of video game-like elements to non-game activities, known as gamification, holds promise with respect to encouraging engagement with, and adherence to, health behaviors and healthcare interventions. Elements of gamification include the introduction of points systems, leaderboards, achievement badges, stories and themes, rewards, progress tracking, and challenges. However, a lack of enthusiasm for, and experience with, video game play by older adults has important implications for the effectiveness of these techniques across the lifespan. Specifically, the age-related “digital divide” must be considered before applying these approaches to improving the wellbeing, cognition, and health of older adults. This talk will build on the body of research conducted by the Center for Research and Education on Aging and Technology Enhancement (CREATE) focused on gaming and interventions to present best practice guidelines for implementing gamification with older adults.

INTEREST GROUP SESSION—TECHNOLOGY AND AGING: THE POTENTIAL AND PITFALLS OF EXTENDED REALITY SOLUTIONS FOR SUPPORTING AND ASSESSING OLDER ADULTS

Extended Reality (XR), which encompasses Virtual Reality (VR) and Augmented Reality (AR), holds a great deal of promise for improving the health and well-being of older adults. These opportunities include providing rehabilitation, physical exercise, skills training, leisure opportunities, and support for instrumental activities of daily living. Further, XR presents novel assessment opportunities. This session will explore the potential of XR solutions, and also crucial barriers to XR implementation, adoption, and engagement, particularly with respect to the “digital divide.” Some older adults, for a number of reasons, experience greater challenges adopting and using newer technologies. This session will start with a broad overview of issues related to XR solutions and will identify critical research needs, with an emphasis on the needs of older adults. This will be followed by a presentation of older adults’ perceptions of XR using data derived from a large, nationally representative sample. While some older adults reported not being ready for XR solutions, many older adults reported being willing to accept them to support optimal aging. Next, a study is presented that directly compares older adults’ perceptions of presence and immersion in virtual spaces. Using VR to assess wayfinding and navigation abilities of older adults is discussed next. The final talk will present VR usability issues derived from interview and focus group data. The session discussant will bring an interdisciplinary perspective to these important issues.

GERONTECHNOLOGY PERCEPTIONS AND POTENTIAL ROLE OF VR/AR IN OPTIMAL AGING

Technology presents opportunities to optimize whole person wellness and functioning. To understand tech readiness and the potential role of virtual (VR) and augmented reality (AR) to support optimal aging, we surveyed 604 participants from the nationally representative RAND American Life Panel. Participant age ranged from 50-90+, 51.5% were female, and 50% reported bachelor’s education or higher. Overall, 8% of the sample identified as Hispanic, with 15% of individuals also identifying as Black, Asian, or Asian Indian or Alaskan Native. Males reported greater optimism and technology innovation and adults aged 50-64 were the most optimistic. Overall, 80% of the sample reported VR familiarity compared to 33% AR. Regarding future needs, 75% of the participants expressed specific concerns about future ADL ability. Almost half of the respondents indicated willingness to use VR and AR to maintain or improve functioning with age and increased personalization of optimal aging emerged as a significant predictor.

A Framework for Choosing Technology Interventions to Promote Successful Longevity: Prevent, Rehabilitate, Augment, Substitute (PRAS)

Successful longevity is achieved when individuals can continue to plan, pursue, and reach their goals across the life-span. However, normative age-related impairments can make goal attainment more difficult, unless there are interventions to mitigate such changes. Behavioral interventions that use technology are increasing in frequency. I outline a hierarchy of approaches to mitigating impairments. The first strategy to promote successful longevity is prevention of normative age-related decline. When impairments develop, they can be addressed by rehabilitation, augmentation, and substitution approaches.

Effects of Extended Use of an Age-friendly Computer System on Assessments of Computer Proficiency, Attitudes, and Usability by Older Non--Computer Users

This study examined the impact of use of a computer software application designed specifically for older people known as PRISM—a Personal Reminder Information and Social Management system—which was installed on a computer that was placed in the homes of adults aged 65 to 98 years, who were at risk for social isolation and had minimal or no computer skills and no computers in their homes. Participants received face-to-face training on the system in their homes over several days and a variety of measures were collected at baseline and at 12 months. A growth mixture model applied to participants’ usage of the system over the course of 12 months revealed two distinct subpopulations of users—less-frequent users and more-frequent users—who after one year of exposure to the system differed in computer proficiency, attitudes toward computers, and ratings of system usability. These two groups did not differ on computer proficiency and computer attitude measures at baseline. The more-frequent user group, however, had significantly higher fluid cognitive abilities. Additional analytical models were used to further examine the relationships among the study measures. The implications of the findings are discussed in terms of the importance of usability for promoting initial engagement with a system and that increased engagement with the system can instill beliefs in these older adults that they can successfully transition to other computer-based technologies and applications. The results also underscore the importance of the user-centered design approach and designing highly usable systems for older adults with low technology proficiency.

A Spanish Adaptation of the Computer and Mobile Device Proficiency Questionnaires (CPQ and MDPQ) for Older Adults

Technology can help support the goal of many older adults to live independently, though cognitive, attitudinal, and other barriers often result in a “digital divide” in which older adults use and adopt new technology at a lower rate compared to younger adults. Due to the many potential benefits of technology it is not surprising that interest in tools that assess technology proficiency among older adults has increased. These tools can help support older adult technology research and training. However, to understand these issues more broadly, especially cross-cultural determinants of technology proficiency, translated, validated, and standardized measures of proficiency are necessary. For example, according to the last Eurobarometer (European Commission, 2015), Spain has experienced the largest increase in technology adoption among European Union nations in the past few years, indicating potential cultural mediation of technology adoption and use. To benefit the investigation of cross-cultural differences and their causes, we adapted the Mobile Device Proficiency Questionnaire (MDPQ) and Computer Proficiency Questionnaire (CPQ) for older adults in Spain, including the full and brief forms of each measure. Consistent with English versions of the questionnaires, the scales and their subscales were found to be reliable and valid measures of mobile device and computer proficiency in Spanish older adults. However, in contrast to earlier studies, the factor structure for both questionnaires simplified into two factors for the population under study. We conclude that the Spanish versions of the MDPQ and CPQ can be employed as useful tools for measuring mobile device and computer proficiency in the Spanish older adult population for research and training purposes.

A Modest Proposal for Solving the Older Worker Productivity Problem

Following the satirist Jonathan Swift (https://www.gutenberg.org/files/1080/1080-h/1080-h.htm), I outline a "modest proposal" for managing the older worker productivity problem. Although meta-analyses by psychologists have consistently shown little or no relationship between age and worker productivity, older workers are clearly less productive from an economic perspective, given their average higher salary and, in the United States, their higher health care premiums. Building on Swift's satire, I propose that to satisfy profit-hungry capitalist firms, older worker contracts should include an automatic salary deflator past age 50. This would improve older worker productivity from an economic perspective by reducing the denominator in their productivity index (output/input costs) and add to the stock of the common good.

The Impact of Domain-Specific Experience on Chess Skill: Reanalysis of a Key Study

How important are training and other forms of domain-relevant experience in predicting individual differences in expertise? To answer this question, we used structural equation modeling to reanalyze data from a study of chess by Charness, Tuffiash, Krampe, Reingold, and Vasyukova (2005). Latent variables reflecting serious chess activity and formal instruction, along with a manifest variable indexing serious starting age, accounted for 63% of the variance in peak rating. Serious starting age had a significant negative effect on peak rating (β = –.15), even after we controlled for domain-specific experience, indicating an advantage for starting earlier. We also tested the prediction that formal instruction increases the effectiveness of serious study (Ericsson & Charness, 1994) using moderated regression. This claim was not supported. Overall, the results affirm that serious study and other forms of domain-specific experience are important pieces of the expertise puzzle, but other factors must matter too.

Supplemental materials are available at https://www.press.uillinois.edu/journals/ajp/media/chess_skill