Background Effects of cannabis, the most commonly encountered non-alcohol drug in driving under the influence cases, are heavily debated. We aimed to determine how blood Δ9-tetrahydrocannabinol (THC) concentrations relate to driving impairment, with and without alcohol. Methods Current occasional (≥1×/last 3months, ≤3days/week) cannabis smokers drank placebo or low-dose alcohol, and inhaled 500mg placebo, low (2.9%)-THC, or high (6.7%)-THC vaporized cannabis over 10min ad libitum in separate sessions (within-subject design, 6 conditions). Participants drove (National Advanced Driving Simulator, University of Iowa) simulated drives (~0.8h duration). Blood, oral fluid (OF) and breath alcohol samples were collected before (0.17h, 0.42h) and after (1.4h, 2.3h) driving that occurred 0.5–1.3h after inhalation. We evaluated standard deviations of lateral position (lane weave, SDLP) and steering angle, lane departures/min, and maximum lateral acceleration. Results In N=18 completers (13 men, ages 21–37years), cannabis and alcohol increased SDLP. Blood THC concentrations of 8.2 and 13.1μg/L during driving increased SDLP similar to 0.05 and 0.08g/210L breath alcohol concentrations, the most common legal alcohol limits. Cannabis-alcohol SDLP effects were additive rather than synergistic, with 5μg/L THC+0.05g/210L alcohol showing similar SDLP to 0.08g/210L alcohol alone. Only alcohol increased lateral acceleration and the less-sensitive lane departures/min parameters. OF effectively documented cannabis exposure, although with greater THC concentration variability than paired blood samples. Conclusions SDLP was a sensitive cannabis-related lateral control impairment measure. During-drive blood THC ≥8.2μg/L increased SDLP similar to notably-impairing alcohol concentrations. Despite OF’s screening value, OF variability poses challenges in concentration-based effects interpretation. KEYWORDS: Cannabis, Alcohol, Driving, Lateral Control, THC, Oral Fluid

Although the last decade has witnessed mounting research on the development and evaluation of positive interventions, investigators still know little about the target population of such interventions: happiness seekers. The present research asked three questions about happiness seekers: (1) What are their general characteristics?, (2) What do they purposefully do to become happier?, and (3) How do they make use of self-help resources? In Study 1, we identified two distinct clusters of online happiness seekers. In Study 2, we asked happiness seekers to report on their use of 14 types of happiness-seeking behaviors. In Study 3, we tracked happiness seekers' usage of an iPhone application that offered access to eight different happiness-increasing activities, and assessed their resulting happiness and mood improvements. Together, these studies provide a preliminary portrait of happiness seekers' characteristics and naturalistic behaviors.

The present study examined age-related differences in multisensory integration and the role of attention in age-related differences in multisensory integration. The sound-induced flash illusion---the misperception of the number of visual flashes due to the simultaneous presentation of a different number of auditory beeps---was used to examine the strength of multisensory integration in older and younger observers. The effects of integration were examined when discriminating 1–3 flashes, 1–3 beeps, or 1–3 flashes presented with 1–3 beeps. Stimulus conditions were blocked according to these conditions, with baseline (unisensory) performance assessed during the multisensory block. Older participants demonstrated greater multisensory integration--a greater influence of the beeps when judging the number of visual flashes--than younger observers. In a second experiment, the role of attention was assessed using a go/no-go paradigm. The results of Experiment 2 replicated those of Experiment 1. In addition, the strength of the illusion was modulated by the sensory domain of the go/no-go task, though this did not differ by age group. In the visual go/no-go task we found a decrease in the illusion, while in the auditory go/no-go task we found an increase in the illusion. These results demonstrate that older individuals exhibit increased multisensory integration compared to younger individuals. Attention was also found to modulate the strength of the sound-induced flash illusion. However, the results also suggest that attention was not likely to be a factor in the age-related differences in multisensory integration.

Although evidence suggests cannabis impairs driving, its driving-performance effects are not fully characterized. We aimed to establish cannabis' effects on driving longitudinal control (with and without alcohol, drivers' most common drug combination) relative to psychoactive ∆(9) -tetrahydrocannabinol (THC) blood concentrations. Current occasional (≥1×/last 3 months, ≤3 days per week) cannabis smokers drank placebo or low-dose alcohol, and inhaled 500 mg placebo, low (2.9%), or high (6.7%) THC vaporized cannabis over 10 min ad libitum in separate sessions (within-subject, six conditions). Participants drove (National Advanced Driving Simulator, University of Iowa) simulated drives 0.5-1.3 h post-inhalation. Blood and breath alcohol samples were collected before (0.17 and 0.42 h) and after (1.4 and 2.3 h) driving. We evaluated the mean speed (relative to limit), standard deviation (SD) of speed, percent time spent >10% above/below the speed limit (percent speed high/percent speed low), longitudinal acceleration, and ability to maintain headway relative to a lead vehicle (headway maintenance) against blood THC and breath alcohol concentrations (BrAC). In N=18 completing drivers, THC was associated with a decreased mean speed, increased percent speed low and increased mean following distance during headway maintenance. BrAC was associated with increased SD speed and increased percent speed high, whereas THC was not. Neither was associated with altered longitudinal acceleration. A less-than-additive THC*BrAC interaction was detected in percent speed high (considering only non-zero data and excluding an outlying drive event), suggesting cannabis mitigated drivers' tendency to drive faster with alcohol. Cannabis was associated with slower driving and greater headway, suggesting a possible awareness of impairment and attempt to compensate. Copyright © 2016 John Wiley & Sons, Ltd.

Researchers often conduct visual world studies to investigate how listeners integrate linguistic information with prior context. Such studies are likely to generate anticipatory baseline effects (ABEs), differences in listeners' expectations about what a speaker might mention that exist before a critical speech stimulus is presented. ABEs show that listeners have attended to and accessed prior contextual information in time to influence the processing of the critical speech stimulus. However, further evidence is required to show that the information actually did influence subsequent processing. ABEs can compromise the validity of inferences about information integration if they are not appropriately controlled. We discuss four solutions: statistical estimation, experimental control, elimination of "on-target" trials, and neutral gaze. An experiment compares the performance of these solutions, and suggests that the elimination of on-target trials introduces bias in the direction of ABEs, due to the statistical phenomenon of regression toward the mean. We conclude that statistical estimation, possibly coupled with experimental control, offers the most valid and least biased solution.