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.

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.

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.

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.

Prevalence of Multiple Chronic Conditions Among Older Adults in Florida and the United States: Comparative Analysis of the OneFlorida Data Trust and National Inpatient Sample.

BACKGROUND: Older patients with multiple chronic conditions are often faced with increased health care needs and subsequent higher medical costs, posing significant financial burden to patients, their caregivers, and the health care system. The increasing adoption of electronic health record systems and the proliferation of clinical data offer new opportunities for prevalence studies and for population health assessment. The last few years have witnessed an increasing number of clinical research networks focused on building large collections of clinical data from electronic health records and claims to make it easier and less costly to conduct clinical research. OBJECTIVE: The aim of this study was to compare the prevalence of common chronic conditions and multiple chronic conditions in older adults between Florida and the United States using data from the OneFlorida Clinical Research Consortium and the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS). METHODS: We first analyzed the basic demographic characteristics of the older adults in 3 datasets-the 2013 OneFlorida data, the 2013 HCUP NIS data, and the combined 2012 to 2016 OneFlorida data. Then we analyzed the prevalence of each of the 25 chronic conditions in each of the 3 datasets. We stratified the analysis of older adults with hypertension, the most prevalent condition. Additionally, we examined trends (ie, overall trends and then by age, race, and gender) in the prevalence of discharge records representing multiple chronic conditions over time for the OneFlorida (2012-2016) and HCUP NIS cohorts (2003-2013). RESULTS: The rankings of the top 10 prevalent conditions are the same across the OneFlorida and HCUP NIS datasets. The most prevalent multiple chronic conditions of 2 conditions among the 3 datasets were-hyperlipidemia and hypertension; hypertension and ischemic heart disease; diabetes and hypertension; chronic kidney disease and hypertension; anemia and hypertension; and hyperlipidemia and ischemic heart disease. We observed increasing trends in multiple chronic conditions in both data sources. CONCLUSIONS: The results showed that chronic conditions and multiple chronic conditions are prevalent in older adults across Florida and the United States. Even though slight differences were observed, the similar estimates of prevalence of chronic conditions and multiple chronic conditions across OneFlorida and HCUP NIS suggested that clinical research data networks such as OneFlorida, built from heterogeneous data sources, can provide rich data resources for conducting large-scale secondary data analyses.

Remote Health Monitoring for Older Adults and Those with Heart Failure: Adherence and System Usability.

BACKGROUND: Remote health monitoring technology has been suggested as part of an early intervention and prevention care model. Older adults with a chronic health condition have been shown to benefit from remote monitoring but often have challenges with complex technology. The current study reports on the usability of and adherence with an integrated, real-time monitoring system over an extended period of time by older adults with and without a chronic health condition. MATERIALS AND METHODS: Older adults 55 years of age and over with and without heart failure participated in a study in which a telehealth system was used for 6 months each. The system consisted of a wireless wristwatch-based monitoring device that continuously collected temperature and motion data. Other health information was collected daily using a weight scale, blood pressure cuff, and tablet that participants used for health surveys. Data were automatically analyzed and summarized by the system and presented to study nurses. RESULTS: Forty-one older adults participated. Seventy-one percent of surveys, 75% of blood pressure readings, and 81% of daily weight measurements were taken. Participants wore the watch monitor 77% of the overall 24/7 time requested. The weight scale had the highest usability rating in both groups. The groups did not otherwise differ on device usage. CONCLUSIONS: The findings indicate that a health monitoring system designed for older adults can and will be used for an extended period of time and may help older adults with chronic conditions reside longer in their own homes in partnership with the healthcare system.

Predicting Older Adults' Perceptions about a Computer System Designed for Seniors.

PURPOSE: Although computer technology may be particularly useful for older adults (e.g., for communication, information access), they have been slower adopters than their younger counterparts. Perceptions about computers such as perceived usefulness and perceived ease of use can pose barriers to acceptance and universal access [1]. Therefore, understanding the precursors to these perceptions for older adult non-computer users may provide insight into the reasons for their non-adoption. METHODS: We examined the relationship between perceived usefulness and perceived ease of use of a computer interface designed for older users and demographic, technology experience, cognitive abilities, personality, and attitudinal variables in a sample of 300 non-computer using adults between the ages of 64 and 98, selected for being at high risk for social isolation. RESULTS: The strongest correlates of perceived usefulness and perceived ease of use were: technology experience, personality dimensions of agreeableness and openness to experience, and attitudes. The emotional stability personality dimension was significantly correlated with perceived ease of use but not perceived usefulness. Hierarchical regression analysis revealed that attitudes (i.e., self-efficacy, comfort, interest) remained predictive of perceptions of usefulness and ease of use when technology experience and personality variables were accounted for. CONCLUSION: Given that attitudes are more malleable than other variables, such as demographic and cognitive abilities, these findings highlight the potential to increase technology acceptance through positive experiences, appropriate training, and educational campaigns about the benefits of computers and other technologies.

Dutch nurses' willingness to use home telehealth: implications for practice and education.

Home telehealth (HT) refers to the use of videoconferencing to provide care to patients remotely and can help older adults age in place. However, these technologies are unlikely to impact care unless health care providers are motivated to use them. Education may play a key role in increasing motivation to use and competence regarding HT. To help guide the development of nursing education to facilitate adoption and use, the current study examined predictors of Dutch nurses' willingness to use HT, based on a survey of 67 Dutch nurses with and 126 without HT experience. Nurses' willingness to use this technology was predicted by HT's (a) perceived usefulness to the client, (b) effort expectancy, (c) social influence, and (d) cost expectations. These observed relationships are anticipated to help with the development of effective educational programs to increase HT use and, therefore, improve older adults' quality of life. [Journal of Gerontological Nursing, 41(4), 47-56.].

Improving the safety of aging road users: a mini-review.

Older drivers are at greatest risk for injury or death as a result of a car crash. In this mini-review, we outline the normative age-related changes to perceptual, cognitive, and motor abilities that contribute to increased crash risk and decreased comfort with driving, and highlight specific driving scenarios and conditions that are particularly challenging for aging road users. Adopting a person-environment fit framework, we discuss how the roadway environment can be modified to better match the abilities of the aging driver. We also review evidence for the efficacy of training interventions that aim to change the abilities and strategies of the aging driver to better match the demands of the driving environment. Evidence suggests that specific changes to the roadway and driver training strategies can bring the abilities of the older driver back into alignment with the demands of the driving task. A focus on both approaches will help ensure the safety of all road users as the number of aging drivers greatly increases over the next few decades.

Utilizing technology to improve older adult health.

Health care costs in the USA have been increasing, with the largest percentage of revenues accruing to hospitals, health care professionals, and the pharmaceutical industry. Increases are likely associated with increases in care costs for chronic conditions, attributable in part to the aging of the population. Technology in the form of telehealth is one important tool to improve the efficiency of health care delivery. However, complex telehealth systems, particularly those relying on remote detection of health status, can also introduce challenges for management, due to system unreliability and particularly the cost of false alarms. A case study is used to illustrate these phenomena.

Are Virtual Assistants Trustworthy for Medicare Information: An Examination of Accuracy and Reliability.

BACKGROUND AND OBJECTIVES: Advances in artificial intelligence (AI)-based virtual assistants provide a potential opportunity for older adults to use this technology in the context of health information-seeking. Meta-analysis on trust in AI shows that users are influenced by the accuracy and reliability of the AI trustee. We evaluated these dimensions for responses to Medicare queries. RESEARCH DESIGN AND METHODS: During the summer of 2023, we assessed the accuracy and reliability of Alexa, Google Assistant, Bard, and ChatGPT-4 on Medicare terminology and general content from a large, standardized question set. We compared the accuracy of these AI systems to that of a large representative sample of Medicare beneficiaries who were queried twenty years prior. RESULTS: Alexa and Google Assistant were found to be highly inaccurate when compared to beneficiaries' mean accuracy of 68.4% on terminology queries and 53.0% on general Medicare content. Bard and ChatGPT-4 answered Medicare terminology queries perfectly and performed much better on general Medicare content queries (Bard = 96.3%, ChatGPT-4 = 92.6%) than the average Medicare beneficiary. About one month to a month-and-a-half later, we found that Bard and Alexa's accuracy stayed the same, whereas ChatGPT-4's performance nominally decreased, and Google Assistant's performance nominally increased. DISCUSSION AND IMPLICATIONS: LLM-based assistants generate trustworthy information in response to carefully phrased queries about Medicare, in contrast to Alexa and Google Assistant. Further studies will be needed to determine what factors beyond accuracy and reliability influence the adoption and use of such technology for Medicare decision-making.

The Benefits of Technology for Engaging Aging Adults: Findings From the PRISM 2.0 Trial.

Background and Objectives: Technology has potential for providing support for aging adults. This study evaluated the Personal Reminder Information and Social Management 2.0 (PRISM 2.0) software, in terms of enhancing social engagement and quality of life, and decreasing loneliness among older adults. Research Design and Methods: The randomized field trial conducted in diverse living contexts (rural locations, senior housing, and assisted living communities [ALC]). Two hundred and forty-five adults, aged 64 to 99 years, were randomly assigned to the PRISM 2.0 (integrated software system designed for aging through an iterative design process) or a Standard Tablet (without PRISM) Control condition, where participants received the same amount of contact and training as those in the PRISM 2.0 condition. Primary outcomes included measures of loneliness, social support, social connectedness, and quality of life. Secondary outcomes included measures of social isolation, mobile device proficiency, and technology readiness. Data were collected at baseline and 6 and 9 months postrandomization. This article focuses on the 6-month outcomes due to coronavirus disease 2019-related data challenges at 9 months. Results: Contrary to our hypothesis, participants in rural locations and senior housing in both conditions reported less loneliness and social isolation, and greater social support and quality of life at 6 months, and an increase in mobile device proficiency. Participants in the ALCs in both conditions also evidenced an increase in mobile device proficiency. Improvements in quality of life and health-related quality of life were associated with decreases in loneliness. Discussion and Implications: This study provides compelling evidence about the benefits of technology for older adults in terms of enhancing social outcomes and quality of life. However, the findings also underscore that for technology applications to be successful, they need to be adapted to the abilities and needs of the user group and instructional support needs to be provided. Clinical Trials Registration #: NCT03116399.

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.

Metrics for assessing the reliability of a telemedicine remote monitoring system.

OBJECTIVE: The goal of this study was to assess using new metrics the reliability of a real-time health monitoring system in homes of older adults. MATERIALS AND METHODS: The "MobileCare Monitor" system was installed into the homes of nine older adults >75 years of age for a 2-week period. The system consisted of a wireless wristwatch-based monitoring system containing sensors for location, temperature, and impacts and a "panic" button that was connected through a mesh network to third-party wireless devices (blood pressure cuff, pulse oximeter, weight scale, and a survey-administering device). To assess system reliability, daily phone calls instructed participants to conduct system tests and reminded them to fill out surveys and daily diaries. Phone reports and participant diary entries were checked against data received at a secure server. RESULTS: Reliability metrics assessed overall system reliability, data concurrence, study effectiveness, and system usability. Except for the pulse oximeter, system reliability metrics varied between 73% and 92%. Data concurrence for proximal and distal readings exceeded 88%. System usability following the pulse oximeter firmware update varied between 82% and 97%. An estimate of watch-wearing adherence within the home was quite high, about 80%, although given the inability to assess watch-wearing when a participant left the house, adherence likely exceeded the 10 h/day requested time. In total, 3,436 of 3,906 potential measurements were obtained, indicating a study effectiveness of 88%. CONCLUSIONS: The system was quite effective in providing accurate remote health data. The different system reliability measures identify important error sources in remote monitoring systems.

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.

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.

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.

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.