Objectives: The accuracy of self-reported driving exposure has questioned the validity of using self-reported mileage to inform research questions. Studies examining the accuracy of self-reported driving exposure compared to objective measures find low validity, with drivers overestimating and underestimating driving distance. The aims of the current study were to (1) examine the discrepancy between self-reported annual mileage and driving exposure the following year and (2) investigate whether these differences depended on age and annual mileage.
Methods: Two estimates of drivers’ self-reported annual mileage collected during vehicle installation (obtained via prestudy questionnaires) and approximated annual mileage driven (based upon Global Positioning System data) were acquired from 3,323 participants who participated in the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study.
Results: A Wilcoxon signed rank test showed that there was a significant difference between self-reported and annual driving exposure during participation in SHRP 2, with the majority of self-reported responses overestimating annual mileage the following year, irrespective of whether an ordinal or ratio variable was examined. Over 15% of participants provided self-reported responses with over 100% deviation, which were exclusive to participants underestimating annual mileage. Further, deviations in reporting differed between participants who had low, medium, and high exposure, as well as between participants in different age groups.
Conclusions: These findings indicate that although self-reported annual mileage is heavily relied on for research, such estimates of driving distance may be an overestimate of current or future mileage and can influence the validity of prior research that has utilized estimates of driving exposure. 相似文献
This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The
methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model
input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population
or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership
functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4)
defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy
membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment
of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the
subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology
are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility,
in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the
inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through
the procedures of ‘fuzzification’ and ‘defuzzification’. 相似文献
Observations of air temperature changes in a steppe marmot burrow were performed from late July to mid-October. Until early September, temperature in the burrow remained relatively constant, but then it began to decrease rapidly. This occurred after air temperature above the ground became equal to the temperature in the burrow. Supposedly, it is in this particular period that marmots begin to plug the entrance to the burrow with earth, thus reducing heat exchange between the increasingly cold aboveground air and the air in the burrow. 相似文献
The main purpose of this study is to assess economic vulnerability of small island development regions as part of their sustainability constraints. By combining economic and environmental time series data, we assessed a composite index of economic vulnerability which is constructed from three exogenous variables, namely economic exposure, economic remoteness, and economic impact of environmental and natural disasters. We used the Amami Islands, Kagoshima Prefecture, Japan as the case studies for this paper.The results indicated that using a gross island products based valuation index, Kikaijima is the most vulnerable island in the Amami Islands with a composite economic vulnerability index (CEVI) value of 0.678, while by using a per capita based index, Okinoerabujima is considered the most vulnerable island with a CEVI value of 0.680. From the results we also revealed that smaller islands have relative higher vulnerability than the bigger one, which also confirms some previous country-level vulnerability studies.However, it is matter of fact that some islands that have relatively high vulnerability also have good economic performance as shown by their per capita income. In this regard, it can be argued that the success of these small islands could have been achieved in spite of and not because of their inherent vulnerability conditions as an indicator of sustainability constraint. Regarding these findings, we also examined a comparison between vulnerability results and the preliminary concept of an island's resilience in order to capture another perspective on sustainability assessment in a small island region. 相似文献