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.

It is well documented that interacting with a mobile phone is associated with poorer performance on concurrently performed tasks because limited attentional resources must be shared between tasks. However, mobile phones generate auditory or tactile notifications to alert users of incoming calls and messages. Although these notifications are generally short in duration, they can prompt task-irrelevant thoughts, or mind wandering, which has been shown to damage task performance. We found that cellular phone notifications alone significantly disrupted performance on an attention-demanding task, even when participants did not directly interact with a mobile device during the task. The magnitude of observed distraction effects was comparable in magnitude to those seen when users actively used a mobile phone, either for voice calls or text messaging.

Autonomous vehicles (AVs) hold considerable promise for maintaining aging adults’ mobility as they develop impairments in driving skill. Nonetheless, attitudes can be a significant barrier to adoption as has been shown for other technologies. We investigated how different introductions to AV, video with a driver in the front seat, the rear seat, and a written description, affected attitudes, as well as how individual difference variables such as age, gender, prior knowledge, and personality traits predict attitudes within a middle-aged (Median age = 34, IQR = 20, n = 441) Amazon Mechanical Turk sample. The 16-item attitude survey uncovered three factors: Concern with AV, Eagerness to Adopt AV technology, and Willingness to Relinquish Driving Control. ANOVAs showed that only age (younger less concerned) and gender, (females more concerned) were significant factors in Concern with AV. Only gender affected Willingness to Relinquish Driving Control, with males more willing. Multiple regressions that included previous knowledge level and personality traits showed a different pattern. Female gender and greater conscientiousness were associated with greater Concern about AV. Prior knowledge of AV was associated with less concern. Emotional stability and openness to experience were positive predictors of Eagerness to Adopt AV, whereas conscientiousness was a negative predictor. Prior knowledge and openness to experience, positively, and extraversion, negatively, were associated with being willing to relinquish driving control. These results suggest that different information dissemination campaigns are needed to persuade consumers to adopt AV technology. We discuss potential approaches.

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.