Overview of Land Use Transport Models

The previous chapters in this Handbook have shown that spatial development, or land use, determines the need for spatial interaction, or transport, but that transport, by the accessibility it provides, also determines spatial development. However, it is difficult to empirically isolate impacts of land use on transport and vice versa because of the multitude of concurrent changes of other factors. This poses a problem if the likely impacts of integrated land-use and transport policies to reduce the demand for travel are to be predicted. There are principally three methods to predict those impacts. The first is to ask people how they would change their location and mobility behaviour if certain factors, such as land use regulations or transport costs, would change ('stated preference'). The second consists of drawing conclusions from observed decision behaviour of people under different conditions on how they would be likely to behave if these factors would change ('revealed preference'). The third method is to simulate human decision behaviour in mathematical models. All three methods have their advantages and disadvantages. Surveys can reveal also subjective factors of location and mobility decisions, however, their respondents can only make conjec-tures about how they would behave in still unknown situations, and the validity of such con

Relationship of neuroimaging to typical sleep times during a clinical reasoning task: a pilot study

Item does not contain fulltextBACKGROUND: Sleep deprivation and fatigue have been associated with medical errors, clinical performance decrements, and reduced quality of life for both practicing physicians and medical students. Greater understanding of the impact of sleep quantity on clinical reasoning could improve patient care. The purpose of our pilot study was to examine relationships between clinical reasoning (assessed by functional magnetic resonance imaging) and sleep time (measured in different ways by actigraphy) while answering multiple-choice questions (MCQs) from licensing agencies. METHODS: Residents and faculty were administered a clinical reasoning exercise (MCQs from licensing bodies) during functional magnetic resonance imaging. Usual sleep patterns were sampled with actigraphy. Covariate analysis was used to examine the relationship between sleep duration (mean sleep, minimum sleep, maximum sleep) and brain activity during clinical reasoning (solving MCQs from licensing bodies). RESULTS: The mean sleep time over the duration of monitoring for the group was 7.19 hours (SD 0.66) with a range of 6.1 to 8.1 hours (internal medicine faculty 7.1 hours, SD 0.41; internal medicine residents 7.27 hours, SD 0.92). There was a negative relationship between activation in the prefrontal cortex and minimum sleep time while reflecting on MCQs. CONCLUSION: Our findings provide evidence that the quantity of sleep can modulate brain activity while completing a clinically meaningful task that should be confirmed in larger studies. Our findings suggest that the construct of sleepiness may be more complex than appreciated by many and that the most important of these sleep measures in terms of outcomes remains to be determined