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.

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.

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.

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 four 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.

The authors replicated and extended a test of Epstein's cognitive-experiential self-theory (CEST; S. Epstein, 1973, 1980, 1985, 1994, 2003) regarding subjective estimates of the relationship between freedom and responsibility. CEST predicts that information in the form of sexually provocative images is likely to be processed by the experiential system. The authors' hypothesis was that such experiential processing would cause an increase in the likelihood of participants endorsing as true a statement that proposed a negative correlation between freedom and responsibility. University students (N = 97) in introductory psychology classes viewed 25 images of either men or women in provocative clothing, or a control consisting of academic journal covers, after which they responded to 24 statements proposing either a positive, negative, or noncontingent relationship between freedom and responsibility. Judgments were analyzed according to perceiver gender and target gender, as well as the framing of the proposition and its contingency category. The hypothesis was supported for the men and to a lesser extent for the women. Although priming the experiential system by exposing participants to sexually provocative images did not change endorsement rates of positive contingencies, it did lead to an increase in the likelihood of simultaneously endorsing negative contingencies.