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Why are older adults reluctant to adopt new technology, such as the Internet, given its potential to improve the quality of their lives? We review evidence indicating that attitudes and abilities are among the most powerful predictors of technology use. We conclude that normative age-related changes in ability must be taken into account when designing products and training programs for aging adults, and we discuss new tools to support designers. The most promising emerging technologies likely lie in training cognitive abilities and augmenting or substituting for impaired abilities. We discuss reasons to expect that the lag in technology adoption between younger and older adults may lessen but will not disappear in future generations.

To draw causal conclusions about the efficacy of a psychological intervention, researchers must compare the treatment condition with a control group that accounts for improvements caused by factors other than the treatment. Using an active control helps to control for the possibility that improvement by the experimental group resulted from a placebo effect. Although active control groups are superior to \"no-contact\" controls, only when the active control group has the same expectation of improvement as the experimental group can we attribute differential improvements to the potency of the treatment. Despite the need to match expectations between treatment and control groups, almost no psychological interventions do so. This failure to control for expectations is not a minor omission—it is a fundamental design flaw that potentially undermines any causal inference. We illustrate these principles with a detailed example from the video-game-training literature showing how the use of an active control group does not eliminate expectation differences. The problem permeates other interventions as well, including those targeting mental health, cognition, and educational achievement. Fortunately, measuring expectations and adopting alternative experimental designs makes it possible to control for placebo effects, thereby increasing confidence in the causal efficacy of psychological interventions.

This study aims to develop a machine learning-based approach to predict adherence to gamified cognitive training using a variety of baseline measures (demographic, attitudinal, and cognitive abilities) as well as game performance data. We aimed to: (1) identify the cognitive games with the strongest adherence prediction and their key performance indicators; (2) compare baseline characteristics and game performance indicators for adherence prediction, and (3) test ensemble models that use baseline characteristics and game performance data to predict adherence over ten weeks. Using machine learning algorithms including logistic regression, ridge regression, support vector machines, classification trees, and random forests, we predicted adherence from weeks 3 to 12. Predictors included game performance metrics in the first two weeks and baseline measures. These models' robustness and generalizability were tested through five-fold cross-validation. The findings indicated that game performance measures were superior to baseline characteristics in predicting adherence. Notably, the games \"Supply Run,\" \"Ante Up,\" and \"Sentry Duty\" emerged as significant adherence predictors. Key performance indicators included the highest level achieved, total game sessions played, and overall gameplay proportion. A notable finding was the negative correlation between initial high achievement levels and sustained adherence, suggesting that maintaining a balanced difficulty level is crucial for long-term engagement. Conversely, a positive correlation between the number of sessions played and adherence highlighted the importance of early active involvement. The insights from this research inform just-in-time strategies to promote adherence to cognitive training programs, catering to the needs and abilities of the aging population. It also underscores the potential of tailored, gamified interventions to foster long-term adherence to cognitive training.

In 2014, two groups of scientists published open letters on the efficacy of brain-training interventions, or \"brain games,\" for improving cognition. The first letter, a consensus statement from an international group of more than 70 scientists, claimed that brain games do not provide a scientifically grounded way to improve cognitive functioning or to stave off cognitive decline. Several months later, an international group of 133 scientists and practitioners countered that the literature is replete with demonstrations of the benefits of brain training for a wide variety of cognitive and everyday activities. How could two teams of scientists examine the same literature and come to conflicting \"consensus\" views about the effectiveness of brain training? In part, the disagreement might result from different standards used when evaluating the evidence. To date, the field has lacked a comprehensive review of the brain-training literature, one that examines both the quantity and the quality of the evidence according to a well-defined set of best practices. This article provides such a review, focusing exclusively on the use of cognitive tasks or games as a means to enhance performance on other tasks. We specify and justify a set of best practices for such brain-training interventions and then use those standards to evaluate all of the published peer-reviewed intervention studies cited on the websites of leading brain-training companies listed on Cognitive Training Data (www.cognitivetrainingdata.org), the site hosting the open letter from brain-training proponents. These citations presumably represent the evidence that best supports the claims of effectiveness. Based on this examination, we find extensive evidence that brain-training interventions improve performance on the trained tasks, less evidence that such interventions improve performance on closely related tasks, and little evidence that training enhances performance on distantly related tasks or that training improves everyday cognitive performance. We also find that many of the published intervention studies had major shortcomings in design or analysis that preclude definitive conclusions about the efficacy of training, and that none of the cited studies conformed to all of the best practices we identify as essential to drawing clear conclusions about the benefits of brain training for everyday activities. We conclude with detailed recommendations for scientists, funding agencies, and policymakers that, if adopted, would lead to better evidence regarding the efficacy of brain-training interventions.

Some have explained large sex differences in visuospatial abilities by genetic adaptations to different roles in primitive hunter-gatherer societies and the interaction of innate biological differences and environmental factors. We explored the extent to which variations in behavior and acquired skills can provide alternative accounts for sex differences in the performance of a complex spatially-demanding video game (Space Fortress). Men and women with limited video game experience were given 30 hours of training, and latent curve analyses examined the development of their ship control performance and behavior. Men had significantly better control performance than women before and after training, but differences diminished substantially over the training period. An analysis of participants' joystick behaviors revealed that initially men and women relied on different patterns of control behaviors, but changes in these behaviors over time accounted for the reduced sex differences in performance. When we controlled for these differences in behavior, sex effects after training were no longer significant. Finally, examining the development of control performance and control behaviors of men and women categorized as initially high and low performers revealed the lower-performing women may have been controlling their ship using an approach that was very different from the men and higher-performing women. The potential problems of analyzing men and women's spatial performance as homogenous groups are discussed, as well as how these issues may account for sex differences in skilled video game performance and perhaps other domains involving spatial abilities.

To what extent are low-level visual and attentional phenomena related to higher-level personality traits? Trait self-control is thought to modulate behavior via two separate mechanisms: 1) by preventing initial temptation and, 2) by inhibiting temptation when it occurs (disengagement). Similarly, the control of visual attention often entails preventing initial distraction by irrelevant but tempting (goal-similar) objects, and disengaging attention when it has been inappropriately captured. Given these similarities, we examined whether individuals higher versus lower in trait self-control would differ in their susceptibility to attention capture using mouse-tracking as a sensitive, online measure of how attentional dynamics resolve over time and space in response to a distracting visual cue. Using a variety of metrics of attention capture, we found that differences among people in trait self-control did not predict initial selection of visual information nor subsequent disengagement. Overall, these results suggest that trait self-control and attention capture operate via separate mechanisms.

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.

Abstract Background and Objectives Exposure to nature and nature-based imagery has been shown to improve mood states and stave off cognitive decline in older adults. Even “micro-doses” of natural scenery can provide beneficial effects in situations where more extensive interactions with nature are not feasible. In the current study, we evaluated the use of virtual reality (VR) for delivering interactive nature-based content with the goal of prompting active engagement and improving mood states in older adults. Research Design and Methods The researchers developed a novel VR environment that combined 360-degree videos of natural areas and botanical gardens with interactive digital features that allowed users to engage with aspects of the environment. We recruited 50 older adults to try out this VR environment and measured changes in mood states and attitudes toward VR from before versus after the sessions. We controlled for variables such as age, education level, and exposure to nature in everyday life, and we looked for differences in responses to the VR among participants with cognitive impairments (CIs) versus without, and participants with physical disabilities versus without. Results The findings indicated significant improvements in “good” mood and “calm” mood dimensions after exposure to the VR, as well as improvements in attitudes toward the technology. These positive outcomes were significantly greater for participants with physical disabilities compared to those without disabilities. No differences were found in the responses of participants with CIs versus those without. Exit interviews provided a variety of helpful suggestions about ways to improve the VR equipment design and content to meet the needs of an older adult population. Discussion and Implications The study demonstrates that VR can provide a cost-effective, noninvasive, and nonpharmaceutical approach for improving the lives of older adults in both clinical and recreational settings, particularly when real-world access to nature is limited.

A number of studies and meta-analyses conclude that aerobic fitness (walking) interventions improve cognition. Such interventions typically compare improvements from these interventions to an active control group in which participants engage in non-aerobic activities (typically stretching and toning) for an equivalent amount of time. However, in the absence of a double-blind design, the presence of an active control group does not necessarily control for placebo effects; participants might expect different amounts of improvement for the treatment and control interventions. We conducted a large survey to explore whether people expect greater cognitive benefits from an aerobic exercise intervention compared to a control intervention. If participants expect greater improvement following aerobic exercise, then the benefits of such interventions might be due in part to a placebo effect. In general, expectations did not differ between aerobic and non-aerobic interventions. If anything, some of the results suggest the opposite (e.g., respondents expected the control, non-aerobic intervention to yield bigger memory gains). These results provide the first evidence that cognitive improvements following aerobic fitness training are not due to differential expectations.

Abstract Background and Objectives Sustained computer and internet use have the potential to help older adults in various aspects of their lives, making predicting sustained use a critical goal. However, some factors related to adoption and use (e.g., computer attitudes) change over time and with experience. To understand these dynamics, the current study modeled changes in constructs related to computer use after initial computer adoption and examined whether these changes predict continued use. Research Design and Methods We used data from the computer arm (N = 150, MAge = 76.15) of a 12-month field trial examining the potential benefits of computer use in older adults. Individual differences identified in the technology acceptance literature (perceived usefulness, ease of use, computer interest, computer self-efficacy, computer anxiety, quality of life, social isolation, and social support) were measured before (baseline), during (Month 6), and after the intervention (post-test). Univariate and bivariate latent change score models examined changes in each predictor and their potential causal relationship with use. Results Results demonstrated large interindividual differences in the change patterns of individual difference factors examined. Changes in perceived usefulness, perceived ease of use, computer interest, computer self-efficacy, and computer anxiety were correlated with but not predictive of change in use. Discussion and Implications Our findings demonstrate the limitation of popular constructs in technology acceptance literature in predicting continued use and point out important gaps in knowledge to be targeted in future investigations.