Driver self-regulation and depressive symptoms in cataract patients awaiting surgery: a cross-sectional study

Background: Cataract is an extremely common visual condition of ageing. Evidence suggests that visual impairment influences driving patterns and self-regulatory behavior among older drivers. However, little is known about the psychological effects of driver self-regulation among older drivers. Therefore, this study aimed to describe driver self-regulation practices among older bilateral cataract patients and to determine the association between self-regulation and depressive symptoms. Methods: Ninety-nine older drivers with bilateral cataract were assessed the week before first eye cataract surgery. Driver self-regulation was measured via the Driving Habits Questionnaire. Depressive symptoms were assessed using the 20-item Center for Epidemiological Studies Depression Scale. Visual, demographic and cognitive data were also collected. Differences between self-regulators and non self-regulators were described and linear regression modeling used to determine the association between driver self-regulation and depressive symptoms score. Results: Among cataract patients, 48% reported self-regulating their driving to avoid at least one challenging situation. The situations most commonly avoided were driving at night (40%), on the freeway (12%), in the rain (9%) and parallel parking (8%). Self-regulators had significantly poorer contrast sensitivity in their worse eye than non self-regulators (p = 0.027). Driver self-regulation was significantly associated with increased depressive symptoms after controlling for potential confounding factors (p = 0.002).Conclusions: Driver self-regulation was associated with increased depressive symptoms among cataract patients. Further research should investigate this association among the general older population. Self-regulation programs aimed at older drivers may need to incorporate mental health elements to counteract unintended psychological effects

A psycho-Geoinformatics approach for investigating older adults’ driving behaviours and underlying cognitive mechanisms

Introduction: Safe driving constantly challenges the driver’s ability to respond to the dynamic traffic scene under space and time constraints. It is of particular importance for older drivers to perform sufficient visual and motor actions with effective coordination due to the fact of age-related cognitive decline. However, few studies have been able to integrate drivers’ visual-motor behaviours with environmental information in a spatial-temporal context and link to the cognitive conditions of individual drivers. Little is known about the mechanisms that underpin the deterioration in visual-motor coordination of older drivers. Development: Based on a review of driving-related cognitive decline in older adults and the context of driver-vehicle-environment interactions, this paper established a conceptual framework to identify the parameters of driver’s visual and motor behaviour, and reveal the cognitive process from visual search to vehicle control in driving. The framework led to a psycho-geoinformatics approach to measure older drivers’ driving behaviours and investigate the underlying cognitive mechanisms. The proposed data collection protocol and the analysis and assessments depicted the psycho-geoinformatics approach on obtaining quantified variables and the key means of analysis, as well as outcome measures. Conclusions: Recordings of the driver and their interactions with the vehicle and environment at a detailed scale give a closer assessment of the driver’s behaviours. Using geoinformatics tools in driving behaviours assessment opens a new era of research with many possible analytical options, which do not have to rely on human observations. Instead, it receives clear indicators of the individual drivers’ interactions with the vehicle and the traffic environment. This approach should make it possible to identify lower-performing older drivers and problematic visual and motor behaviours, and the cognitive predictors of risky driving behaviours. A better targeted regulation and tailored intervention programs for older can be developed by further research

Aging and Visual Counting

Much previous work on how normal aging affects visual enumeration has been focused on the response time required to enumerate, with unlimited stimulus duration. There is a fundamental question, not yet addressed, of how many visual items the aging visual system can enumerate in a "single glance", without the confounding influence of eye movements.We recruited 104 observers with normal vision across the age span (age 21-85). They were briefly (200 ms) presented with a number of well- separated black dots against a gray background on a monitor screen, and were asked to judge the number of dots. By limiting the stimulus presentation time, we can determine the maximum number of visual items an observer can correctly enumerate at a criterion level of performance (counting threshold, defined as the number of visual items at which ≈63% correct rate on a psychometric curve), without confounding by eye movements. Our findings reveal a 30% decrease in the mean counting threshold of the oldest group (age 61-85: ∼5 dots) when compared with the youngest groups (age 21-40: 7 dots). Surprisingly, despite decreased counting threshold, on average counting accuracy function (defined as the mean number of dots reported for each number tested) is largely unaffected by age, reflecting that the threshold loss can be primarily attributed to increased random errors. We further expanded this interesting finding to show that both young and old adults tend to over-count small numbers, but older observers over-count more.Here we show that age reduces the ability to correctly enumerate in a glance, but the accuracy (veridicality), on average, remains unchanged with advancing age. Control experiments indicate that the degraded performance cannot be explained by optical, retinal or other perceptual factors, but is cortical in origin