Capturing Voluntary, Involuntary, and Habitual Components of Driver Distraction in a Self-Reported Questionnaire

To maximize the effectiveness of strategies for mitigating driver distraction, it is crucial to understand the factors underlying drivers’ engagement in distractions. This article describes a step toward an improved version of the Susceptibility to Driver Distraction Questionnaire (SDDQ), namely the development of an exploratory questionnaire based on findings from the original SDDQ. In this exploratory questionnaire, the Theory of Planned Behaviour continues to serve as the framework for investigating voluntary distractions, relating intentional actions to attitudes, perceived behavioural control, and perceived social norms regarding distractions. Involuntary distractions are captured by investigating the difficulty associated with ignoring information that is not critical for safe driving. A new component of habitual behaviours is also added to measure distractions that involve minimal conscious control, yet were once intentional and goal-driven. The resulting exploratory questionnaire will be used in an upcoming online survey study to determine the items that most effectively capture voluntary, involuntary, and habitual distraction. An improved SDDQ will be generated based on analyses of this pending study

Interface Design for Sonobuoy System

Modern sonar systems have greatly improved their sensor technology and processing techniques, but little effort has been put into display design for sonar data. The enormous amount of acoustic data presented by the traditional frequency versus time display can be overwhelming for a sonar operator to monitor and analyze. The recent emphasis placed on networked underwater warfare also requires the operator to create and maintain awareness of the overall tactical picture in order to improve overall effectiveness in communication and sharing of critical data. In addition to regular sonar tasks, sonobuoy system operators must manage the deployment of sonobuoys and ensure proper functioning of deployed sonobuoys. This thesis examines an application of the Ecological Interface Design framework in the interface design of a sonobuoy system on board a maritime patrol aircraft. Background research for this thesis includes a literature review, interviews with subject matter experts, and an analysis of the decision making process of sonar operators from an information processing perspective. A work domain analysis was carried out, which yielded a dual domain model: the domain of sonobuoy management and the domain of tactical situation awareness address the two different aspects of the operator's work. Information requirements were drawn from the two models, which provided a basis for the generation of various unique interface concepts. These concepts covered both the needs to build a good tactical picture and manage sonobuoys as physical resources. The later requirement has generally been overlooked by previous sonobuoy interface designs. A number of interface concepts were further developed into an integrated display prototype for user testing. Demos created with the same prototype were also delivered to subject matter experts for their feedback. While the evaluation means are subjective and limited in their ability to draw solid comparisons with existing sonobuoy displays, positive results from both user testing and subject matter feedback indicated that the concepts developed here are intuitive to use and effective in communicating critical data and supporting the user’s awareness of the tactical events simulated. Subject matter experts also acknowledged the potential for these concepts to be included in future research and development for sonobuoy systems. This project was funded by the Industrial Postgraduate Scholarships (IPS) from Natural Science and Engineering Research Council of Canada (NSERC) and the sponsorship of Humansystems Inc. at Guelph, Ontario

Quality Evaluation of Some Combinations of Unit Uniform Random Number Generators and Unit Normal Transformation Algorithms.

Due to the wide applications of normal random variates and the fact that applications are usually affected by their accuracy, an extensive study of the quality evaluation of unit uniform random number generators and unit normal transformation algorithms that are applications specific is recommended. In most simulation applications it is implicitly assumed that if any good unit uniform random number generator is used in combination with any good transformation algorithm. The resulting random variates will have good properties of randomness and will have the desired fit. The results of this research shows that this assumption is false. Use of good, theoretically exact transformation in conjunction with a theoretically good unit uniform generator does not necessary guarantee that the resulting variates have good statistical properties. In addition, a generator is good for one type of transformations, but it is not necessarily good for the other type of transformations. Hence, the simulation practitioner must be cautious in the selection of both the unit uniform generator and the transformation algorithm to be used. This study is concerned with the empirical study of quality evaluations of several different combinations of unit uniform random number generators and unit normal transformation algorithms for practical applications, and with procedures for determining if a given generator or a given combination is good or bad . Major emphasis of this study is placed upon selection of the appropriate statistical tests for this evaluation, and development of the pertinent procedures as well as the corresponding computer programs for these tests. The statistical tests selected as appropriate for evaluating and comparing the quality of various generators are: chi-square goodness of fit tests for testing the desired distribution fits and other goodness of fits procedures for use in conjunction with other tests, runs up and down, runs above and below the median, autocorrelation tests, and spectral tests for randomness and independence. The corresponding procedures and the computer programs are set up for each test. Seven widely used unit uniform random number generators (ADRAND, RANDU, L & L, M & M, R. Shore, URAND and GGUBS) and three well known normal transformation algorithms (Box-Muller partial inverse, Box-Muller rejection, and Hasting inverse routine) are investigated here. For each generator and each combination, a large sample size series is generated which contains 50 independent samples with 50 different initial seed numbers. Each sample contains 50 sets, and each set contains 1200 generated numbers. Each selected generator and each selected combination is assessed by statistically testing the quality, both locally and globally, of the corresponding generated sequence. In total, we empirically evaluate (at significance levels 0.01, 0.05 and 0.2 respectively), the quality of seven generators, twenty-one combinations, and two IBM IMSL library unit normal generators: GGNML and GGNPM. In addition, the statistics selected and the procedures developed as well as the corresponding computer programs established here are not restricted to use in this study. They can also be applied in assessing other generators and other combinations

Self-reported illness among Boston-area international travelers: A prospective study

This is the Accepted Manuscript version and was published in final edited form as: Travel Med Infect Dis. 2016 ; 14(6): 604–613. doi:10.1016/j.tmaid.2016.09.009.BACKGROUND: The Boston Area Travel Medicine Network surveyed travelers on travel-related health problems. METHODS: Travelers were recruited 2009-2011 during pre-travel consultation at three clinics. The investigation included pre-travel data, weekly during-travel diaries, and a post-travel questionnaire. We analyzed demographics, trip characteristics, health problems experienced, and assessed the relationship between influenza vaccination, influenza prevention advice, and respiratory symptoms. RESULTS:Of 987 enrolled travelers, 628 (64%) completed all surveys, of which 400 (64%) reported health problems during and/or after travel; median trip duration was 12 days. Diarrhea affected the most people during travel (172) while runny/stuffy nose affected the most people after travel (95). Of those with health problems during travel, 25% stopped or altered plans; 1% were hospitalized. After travel, 21% stopped planned activities, 23% sought physician or other health advice; one traveler was hospitalized. Travelers who received influenza vaccination and influenza prevention advice had lower rates of respiratory symptoms than those that received influenza prevention advice alone (18% vs 28%, P = 0.03). CONCLUSIONS:A large proportion of Boston-area travelers reported health problems despite pre-travel consultation, resulting in inconveniences. The combination of influenza prevention advice and influenza immunization was associated with fewer respiratory symptoms than those who received influenza prevention advice alone

Cerebral small vessel disease burden is associated with poststroke depressive symptoms: A 15-month prospective study

Objective: All types of cerebral small vessel disease (SVD) markers including lacune, white matter hyperintensities (WMH), cerebral microbleeds, and perivascular spaces were found to be associated with poststroke depressive symptoms (PDS). This study explored whether the combination of the four markers constituting an overall SVD burden was associated with PDS. Methods: A cohort of 563 patients with acute ischemic stroke were followed over a 15-month period after the index stroke. A score of _7 on the 15-item Geriatric Depression Scale was defined as clinically significant PDS. Scores of the four SVD markers ascertained on magnetic resonance imaging were summed up to represent total SVD burden. The association between SVD burden and PDS was assessed with generalized estimating equation models. Results: The study sample had a mean age of 67.0 _ 10.2 years and mild-moderate stroke [National Institutes of Health Stroke Scale score: 3, interquartile, 1–5]. PDS were found in 18.3%, 11.6%, and 12.3% of the sample at 3, 9, and 15 months after stroke, respectively. After adjusting for demographic characteristics, vascular risk factors, social support, stroke severity, physical and cognitive functions, and size and locations of stroke, the SVD burden was associated with an increased risk of PDS [odds ratio = 1.30; 95% confidence interval = 1.07–1.58; p = 0.010]. Other significant predictors of PDS were time of assessment, female sex, smoking, number of acute infarcts, functional independence, and social support. Conclusion: SVD burden was associated with PDS examined over a 15-month follow-up in patients with mild to moderate acute ischemic stroke

An Uncertainty Aided Framework for Learning based Liver T1ρT_1\rho Mapping and Analysis

Objective: Quantitative $T_1\rho$ imaging has potential for assessment of biochemical alterations of liver pathologies. Deep learning methods have been employed to accelerate quantitative $T_1\rho$ imaging. To employ artificial intelligence-based quantitative imaging methods in complicated clinical environment, it is valuable to estimate the uncertainty of the predicated $T_1\rho$ values to provide the confidence level of the quantification results. The uncertainty should also be utilized to aid the post-hoc quantitative analysis and model learning tasks. Approach: To address this need, we propose a parametric map refinement approach for learning-based $T_1\rho$ mapping and train the model in a probabilistic way to model the uncertainty. We also propose to utilize the uncertainty map to spatially weight the training of an improved $T_1\rho$ mapping network to further improve the mapping performance and to remove pixels with unreliable $T_1\rho$ values in the region of interest. The framework was tested on a dataset of 51 patients with different liver fibrosis stages. Main results: Our results indicate that the learning-based map refinement method leads to a relative mapping error of less than 3% and provides uncertainty estimation simultaneously. The estimated uncertainty reflects the actual error level, and it can be used to further reduce relative $T_1\rho$ mapping error to 2.60% as well as removing unreliable pixels in the region of interest effectively. Significance: Our studies demonstrate the proposed approach has potential to provide a learning-based quantitative MRI system for trustworthy $T_1\rho$ mapping of the liver

A qualitative, network-centric method for modeling socio-technical systems, with applications to evaluating interventions on social media platforms to increase social equality

We propose and extend a qualitative, complex systems methodology from cognitive engineering, known as theabstraction hierarchy, to model how potential interventions that could be carried out by social media platforms might impact social equality. Social media platforms have come under considerable ire for their role in perpetuating social inequality. However, there is also significant evidence that platforms can play a role inreducingsocial inequality, e.g. through the promotion of social movements. Platforms’ role in producing or reducing social inequality is, moreover, not static; platforms can and often do take actions targeted at positive change. How can we develop tools to help us determine whether or not a potential platform change might actually work to increase social equality? Here, we present the abstraction hierarchy as a tool to help answer this question. Our primary contributions are two-fold. First, methodologically, we extend existing research on the abstraction hierarchy in cognitive engineering with principles from Network Science. Second, substantively, we illustrate the utility of this approach by using it to assess the potential effectiveness of a set of interventions, proposed in prior work, for how online dating websites can help mitigate social inequality

A systematic review of chronic disease management interventions in primary care

Background: Primary and community care are key settings for the effective management of long term conditions. We aimed to evaluate the pattern of health outcomes in chronic disease management interventions for adults with physical health problems implemented in primary or community care settings. Methods: The methods were based on our previous review published in 2006. We performed database searches for articles published from 2006 to 2014 and conducted a systematic review with narrative synthesis using the Cochrane Effective Practice and Organisation of Care taxonomy to classify interventions and outcomes. The interventions were mapped to Chronic Care Model elements. The pattern of outcomes related to interventions was summarized by frequency of statistically significant improvements in health care provision and patient outcomes. Results: A total of 9589 journal articles were retrieved from database searches and snowballing. After screening and verification, 165 articles that detailed 157 studies were included. There were few studies with Health Care Organization (1.9% of studies) or Community Resources (0.6% of studies) as the primary intervention element. Self-Management Support interventions (45.8% of studies) most frequently resulted in improvements in patient-level outcomes. Delivery System Design interventions (22.6% of studies) showed benefits in both professional and patient-level outcomes for a narrow range of conditions. Decision Support interventions (21.3% of studies) had impact limited to professional-level outcomes, in particular use of medications. The small number of studies of Clinical Information System interventions (8.9%) showed benefits for both professional- and patient-level outcomes. Conclusions: The published literature has expanded substantially since 2006. This review confirms that Self-Management Support is the most frequent Chronic Care Model intervention that is associated with statistically significant improvements, predominately for diabetes and hypertension