The misallocation of driver visual attention has been suggested as a major contributing factor to vehicle accidents. One possible reason is that the relatively high cognitive demands of driving limit the ability to efficiently allocate gaze. We present an experiment that explores the relationship between attentional function and visual performance when driving. Drivers performed 2 variations of a multiple-object tracking task targeting aspects of cognition including sustained attention, dual-tasking, covert attention, and visuomotor skill. They also drove a number of courses in a driving simulator. Eye movements were recorded throughout. We found that individuals who performed better in the cognitive tasks exhibited more effective eye movement strategies when driving, such as scanning more of the road, and they also exhibited better driving performance. We discuss the potential link between an individual’s attentional function, effective eye movements, and driving ability. We also discuss the use of a visuomotor task in assessing driving behavior.

Differences in eye movement patterns are often found when comparing passive viewing paradigms to actively engaging in everyday tasks. Arguably, investigations into visuomotor control should therefore be most useful when conducted in settings that incorporate the intrinsic link between vision and action. We present a study that compares oculomotor behaviour and hazard reaction times across a simulated driving task and a comparable, but passive, video-based hazard perception task. We found that participants scanned the road less during the active driving task and fixated closer to the front of the vehicle. Participants were also slower to detect the hazards in the driving task. Our results suggest that the interactivity of simulated driving places increased demand upon the visual and attention systems than simply viewing driving movies. We offer insights into why these differences occur and explore the possible implications of such findings within the wider context of driver training and assessment.

Background: New population health community-based models of palliative care can result in more compassionate, affordable, and sustainable high-quality care.Objectives: We evaluated utilization and cost outcomes of a standardized, population health community-based palliative care program provided by nurses and social workers.Design: We conducted a retrospective propensity-adjusted study to quantify cost savings and resource utilization associated with a community-based palliative care program. We analyzed claims data from a Medicare Advantage (MA) plan and used a proprietary predictive model to identify 804 members at high risk for overmedicalized end-of-life care. We enrolled 204 members in the palliative care program and compared them with 600 who received standard, telephonic, health plan case management. We excluded members with fewer than two months of enrolled experience or those with insufficient data for analysis, leaving 176 members in the study group and 570 in the control group for evaluation. We compared differences in utilization and costs (medical and pharmacy), hospital admissions, bed days (acute and intensive care unit [ICU]), and emergency department visits.Setting/Subjects: A 30,000-member MA plan and a health system in Central Ohio between October 2015 and June 2016.Results: Members who received community-based palliative care showed a statistically significant 20% reduction in total medical costs ($619 per enrolled member per month), 38% reduction in ICU admissions, 33% reduction in hospital admissions, and 12% reduction in hospital days.Conclusion: A structured nurse and social work model of community-based palliative care using a predictive model to identify MA candidates for intervention can reduce utilization and medical costs.

Translational recognition memory research makes frequent use of the Novel Object Recognition (NOR) paradigm in which animals are simultaneously presented with one new and one old object. The preferential exploration of the new as compared to the old object produces a metric, the Discrimination Ratio (DR), assumed to represent recognition memory sensitivity. Human recognition memory studies typically assess performance using signal detection theory derived measures; sensitivity (d′) and bias (c). How DR relates to d′ and c and whether they measure the same underlying cognitive mechanism is, however, unknown. We investigated the correspondence between DR (eye-tracking-determined), d′ and c in a sample of 37 humans. We used dwell times during a visual paired comparison task (analogous to the NOR) to determine DR, and a separate single item recognition task to derive estimates of response sensitivity and bias. DR was found to be significantly positively correlated to sensitivity but not bias. Our findings confirm that DR corresponds to d′, the primary measure of recognition memory sensitivity in humans, and appears not to reflect bias. These findings are the first of their kind to suggest that animal researchers should be confident in interpreting the DR as an analogue of recognition memory sensitivity.

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