Sensitivity of the lane change test as a measure of in-vehicle system demand

The Lane Change Test (LCT) is one of the growing number of methods developed to quantify driving performance degradation brought about by the use of in-vehicle devices. Beyond its validity and reliability, for such a test to be of practical use, it must also be sensitive to the varied demands of individual tasks. The current study evaluated the ability of several recent LCT lateral control and event detection parameters to discriminate between visual-manual and cognitive surrogate In-Vehicle Information System tasks with different levels of demand. Twenty-seven participants (mean age 24.4 years) completed a PC version of the LCT while performing visual search and math problem solving tasks. A number of the lateral control metrics were found to be sensitive to task differences, but the event detection metrics were less able to discriminate between tasks. The mean deviation and lane excursion measures were able to distinguish between the visual and cognitive tasks, but were less sensitive to the different levels of task demand. The other LCT metrics examined were less sensitive to task differences. A major factor influencing the sensitivity of at least some of the LCT metrics could be the type of lane change instructions given to participants. The provision of clear and explicit lane change instructions and further refinement of its metrics will be essential for increasing the utility of the LCT as an evaluation tool.

Does the acid hydrolysis-incubation method measure meaningful soil organic carbon pools?

The literature was reviewed and analyzed to determine the feasibility of using a combination of acid hydrolysis and CO2-C release during long-term incubation to determine soil organic carbon (SOC) pool sizes and mean residence times (MRTs). Analysis of 1100 data points showed the SOC remaining after hydrolysis with 6 M HCI ranged from 30 to 80% of the total SOC depending on soil type, depth, texture, and management. Nonhydrolyzable carbon (NHC) in conventional till soils represented 48% of SOC; no-till averaged 56%, forest 55%, and grassland 56%. Carbon dates showed an average of 1200 yr greater MRT for the NHC fraction than total SOC. Longterm incubation, involving measurement of CO2 evolution and curve fitting, measured active and slow pools. Active-pool C comprised 2 to 8% of the SOC with MRTs of days to months; the slow pool comprised 45 to 65% of the SOC and had MRTs of 10 to 80 yr. Comparison of field C-14 and (13) C data with hydrolysis-incubation data showed a high correlation between independent techniques across soil types and experiments. There were large differences in MRTs depending on the length of the experiment. Insertion of hydrolysis-incubation derived estimates of active (C-a), slow (C-s), and resistant Pools (C-r) into the DAYCENT model provided estimates of daily field CO2 evolution rates. These were well correlated with field CO2 measurements. Although not without some interpretation problems, acid hydrolysis-laboratory incubation is useful for determining SOC pools and fluxes especially when used in combination with associated measurements.

Benchmarking framework to measure extent of ICT adoption for building project management

This project discusses a component of the research study conducted to provide construction organizations with a generic benchmarking framework to assess their extent of information communication technology (ICT) adoption for building project management processes. It defines benchmarking and discusses objectives of the required benchmarking framework and development of the framework. The study focuses on ICT adoption by small and medium enterprises (SMEs) in the construction industry and with respect to SMEs it is important to understand processes, their indicators, and measures in the local context. Structure of the suggested benchmarking framework has been derived after extensive literature survey and a questionnaire survey conducted in the Indian construction industry. The suggested benchmarking process is an iterative process divided into four stages. It can be implemented at organization and industry levels for rating the construction organizations for ICT adoption and performance measurement. The framework has a generic structure and can be generalized and applied for other countries with due considerations.

Validation of the MEASURE automobile emissions model : a statistical analysis

The Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) model provides an external validation capability for hot stabilized option; the model is one of several new modal emissions models designed to predict hot stabilized emission rates for various motor vehicle groups as a function of the conditions under which the vehicles are operating. The validation of aggregate measurements, such as speed and acceleration profile, is performed on an independent data set using three statistical criteria. The MEASURE algorithms have proved to provide significant improvements in both average emission estimates and explanatory power over some earlier models for pollutants across almost every operating cycle tested.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

Psychometric analysis of the Brisbane Practice Environment Measure (B-PEM)

Purpose: To undertake rigorous psychometric testing of the newly developed contemporary work environment measure (the Brisbane Practice Environment Measure [B-PEM]) using exploratory factor analysis and confirmatory factor analysis. Methods: Content validity of the 33-item measure was established by a panel of experts. Initial testing involved 195 nursing staff using principal component factor analysis with varimax rotation (orthogonal) and Cronbach's alpha coefficients. Confirmatory factor analysis was conducted using data from a further 983 nursing staff. Results: Principal component factor analysis yielded a four-factor solution with eigenvalues greater than 1 that explained 52.53% of the variance. These factors were then verified using confirmatory factor analysis. Goodness-of-fit indices showed an acceptable fit overall with the full model, explaining 21% to 73% of the variance. Deletion of items took place throughout the evolution of the instrument, resulting in a 26-item, four-factor measure called the Brisbane Practice Environment Measure-Tested. Conclusions: The B-PEM has undergone rigorous psychometric testing, providing evidence of internal consistency and goodness-of-fit indices within acceptable ranges. The measure can be utilised as a subscale or total score reflective of a contemporary nursing work environment. Clinical Relevance: An up-to-date instrument to measure practice environment may be useful for nursing leaders to monitor the workplace and to assist in identifying areas for improvement, facilitating greater job satisfaction and retention.

An extended measure of work-life balance culture : development and confirmation of the measure

This paper extends the work of Thompson, Beauvais and Lyness (1999) to develop a more comprehensive measure of work-life balance culture. Thompson et al. developed a survey based on three sub-dimensions which examine work-family culture. We have extended this to incorporate extra dimensions, and to broaden the measure to encompass life aspects beyond the family. Two studies were conducted in order to test and refine the measure. Over 700 participants in the first study completed the survey, and the Confirmatory Factor Analysis results show that the extended measure is robust. Further, a second study with a sample of 629 participants confirmed the general measure, with slight adaptations. The results are discussed in relation to the use of the measure for work-life balance research.

Psychometric validation of the growth and empowerment measure (GEM) applied with Indigenous Australians

Objective: Empowerment is a complex process of psychological, social, organizational and structural change. It allows individuals and groups to achieve positive growth and effectively address the social and psychological impacts of historical oppression, marginalization and disadvantage. The Growth and Empowerment Measure (GEM) was developed to measure change in dimensions of empowerment as defi ned and described by Aboriginal Australians who participated in the Family Well Being programme.---------- Method: The GEM has two components: a 14-item Emotional Empowerment Scale (EES14) and 12 Scenarios (12S). It is accompanied by the Kessler 6 Psychological Distress Scale (K6), supplemented by two questions assessing frequency of happy and angry feelings. For validation, the measure was applied with 184 Indigenous Australian participants involved in personal and/or organizational social health activities.---------- Results: Psychometric analyses of the new instruments support their validity and reliability and indicate two-component structures for both the EES (Self-capacity; Inner peace) and the 12S (Healing and enabling growth, Connection and purpose). Strong correlations were observed across the scales and subscales. Participants who scored higher on the newly developed scales showed lower distress on the K6, particularly when the two additional questions were included. However, exploratory factor analyses demonstrated that GEM subscales are separable from the Kessler distress measure.---------- Conclusion: The GEM shows promise in enabling measurement and enhancing understanding of both process and outcome of psychological and social empowerment within an Australian Indigenous context.

The obsessive compulsive drinking scale is a valid measure of alcohol craving in young adults

Background: Alcohol craving is associated with greater alcohol-related problems and less favorable treatment prognosis. The Obsessive Compulsive Drinking Scale (OCDS) is the most widely used alcohol craving instrument. The OCDS has been validated in adults with alcohol use disorders (AUDs), which typically emerge in early adulthood. This study examines the validity of the OCDS in a nonclinical sample of young adults. Methods: Three hundred and nine college students (mean age of 21.8 years, SD = 4.6 years) completed the OCDS, Alcohol Use Disorders Identification Test (AUDIT), and measures of alcohol consumption. Subjects were randomly allocated to 2 samples. Construct validity was examined via exploratory factor analysis (n = 155) and confirmatory factor analysis (n = 154). Concurrent validity was assessed using the AUDIT and measures of alcohol consumption. A second, alcohol-dependent sample (mean age 42 years, SD 12 years) from a previously published study (n = 370) was used to assess discriminant validity. Results: A unique young adult OCDS factor structure was validated, consisting of Interference/Control, Frequency of Obsessions, Alcohol Consumption and Resisting Obsessions/Compulsions. The young adult 4-factor structure was significantly associated with the AUDIT and alcohol consumption. The 4 factor OCDS successfully classified nonclinical subjects in 96.9% of cases and the older alcohol-dependent patients in 83.7% of cases. Although the OCDS was able to classify college nonproblem drinkers (AUDIT <13, n = 224) with 83.2% accuracy, it was no better than chance (49.4%) in classifying potential college problem drinkers (AUDIT score ≥13, n = 85). Conclusions: Using the 4-factor structure, the OCDS is a valid measure of alcohol craving in young adult populations. In this nonclinical set of students, the OCDS classified nonproblem drinkers well but not problem drinkers. Studies need to further examine the utility of the OCDS in young people with alcohol misuse.

The development of the extended adolescent injury checklist (E-AIC) : a measure for injury prevention program evaluation

The Extended Adolescent Injury Checklist (E-AIC), a self-report measure of injury based on the model of the Adolescent Injury Checklist (AIC), was developed for use in the evaluation of school-based interventions. The three stages of this development involved focus groups with adolescents and consultations with medical staff, pilot testing of the revised AIC in a high school context, and use of the finalised checklist in pre- and post-questionnaires to examine its utility. Results revealed that responses to the final version of the E-AIC were meaningful and remained consistent over time. The E-AIC appears to be a promising measure of adolescent injury that is simple, time-efficient and appropriate for use in the evaluation of school-based injury prevention programs.

Participation index : a measure to identify rural transport disadvantage?

This paper develops a composite participation index (PI) to identify patterns of transport disadvantage in space and time. It is operationalised using 157 weekly activity-travel diaries data collected from three case study areas in rural Northern Ireland. A review of activity space and travel behaviour research found that six dimensional indicators of activity spaces were typically used including the number of unique locations visited, distance travelled, area of activity spaces, frequency of activity participation, types of activity participated in, and duration of participation in order to identify transport disadvantage. A combined measure using six individual indices were developed based on the six dimensional indicators of activity spaces, by taking into account the relativity of the measures for weekdays, weekends, and for a week. Factor analyses were conducted to derive weights of these indices to form the PI measure. Multivariate analysis using general linear models of the different indicators/indices identified new patterns of transport disadvantage. The research found that: indicator based measures and index based measures are complement each other; interactions between different factors generated new patterns of transport disadvantage; and that these patterns vary in space and time. The analysis also indicates that the transport needs of different disadvantaged groups are varied.

Participation index : improved measure of transport related social exclusion?

Although transport related social exclusion has been identified through zonal accessibility measures in the recent past, the debate has shifted from zonal to individual level measures. One way to identify disadvantaged individuals is to measure their size of participation in society (activity spaces). After reviewing existing literature, this paper has found two approaches to measure the activity spaces. One approach is based on the time-geographic potential path area (PPA) concept. The size of the PPA has largely been used as an indicator to the size of potential activity spaces and consequently individual accessibility. The limitations of the PPA concept have been identified in this paper and it is argued cannot be applied as a measure of social exclusion. The other approach is based on individuals’ actual travel activity participation called actual activity spaces. The size of actual activity spaces possesses a good potential measure of social exclusion. However, the indicators to measure the size of actual activity spaces are multidimensional representing the different aspects of social exclusion. The development of a unified approach has therefore been found to be important. This paper has developed a participation index (PI) using the different dimensions of actual activity spaces encountered. A framework has also been developed to operationalise the concept in GIS. The framework, on the one hand, will visualize individuals’ actual travel behaviour in real geographic space; on the other hand, it will calculate the size of their participation in society.