Work-related subjective experiences among community residents with schizophrenia or schizoaffective disorder

Objective: To develop a self-report scale of subjective experiences of illness perceived to impact on employment functioning, as an alternative to a diagnostic perspective, for anticipating the vocational assistance needs of people with schizophrenia or schizoaffective disorders. Method: A repeated measures pilot study (n1 = 26, n2 = 21) of community residents with schizophrenia identified a set of work-related subjective experiences perceived to impact on employment functioning. Items with the best psychometric properties were applied in a 12 month longitudinal survey of urban residents with schizophrenia or schizoaffective disorder (n1 = 104; n2 = 94; n3 = 94). Results: Construct validity, factor structure, responsiveness, internal consistency, stability, and criterion validity investigations produced favourable results. Work-related subjective experiences provide information about the intersection of the person, the disorder, and expectations of employment functioning, which suggest new opportunities for vocational professionals to explore and discuss individual assistance needs. Conclusion: Further psychometric investigations of test-retest reliability, discriminant and predictive validity, and research applications in supported employment and vocational rehabilitation, are recommended. Subject to adequate psychometric properties, the new measure promises to facilitate exploring: individuals' specific subjective experiences; how each is perceived to contribute to employment restrictions; and the corresponding implications for specialized treatment, vocational interventions and workplace accommodations.

Urban food futures : ICTs and opportunities

Food is a vital foundation of all human life. It is essential to a myriad of political, socio-cultural, economic and environmental practices throughout history. However, those practices of food production, consumption, and distribution have the potential to now go through immensely transformative shifts as network technologies become increasingly embedded in every domain of contemporary life. Information and communication technologies (ICTs) are one of the key foundations of global functionality and sustenance today and undoubtedly will continue to present new challenges and opportunities for the future. As such, this Symposium will bring together leading scholars across disciplines to address challenges and opportunities at the intersection of food and ICTs in everyday urban environment. In particular, the discussion will revolve around the question: What are the key roles that network technologies play in re-shaping the food systems at micro- to macroscopic level? The symposium will contribute a unique perspective on urban food futures through the lens of network society paradigm where ICTs enable innovations in production, organisation, and communication within society. Some of the topics addressed will include encouraging transparency in food commodity chains; value of cultural understanding and communication in global food sustainability; and technologies to social inclusion; all of which evoke and examine the question surrounding networked individuals as changes catalysts for urban food futures. The event will provide an avenue for new discussions and speculations on key issues surrounding urban food futures in the network era, with a particular focus on bottom-up micro actions that challenge the existing food systems towards a broader sociocultural, political, technological, and environmental transformations. One central area of concern is that current systems of food production, distribution, and consumption do not ensure food security for the future, but rather seriously threaten it. With the recent unprecedented scale of urban growth and rise of middle-class, the problem continues to intensify. This situation requires extensive distribution networks to feed urban residents, and therefore poses significant infrastructural challenges to both the public and private sectors. The symposium will also address the transferability of citizen empowerment that network technologies enable as demonstrated in various significant global political transformations from the bottom-up, such as the recent Egyptian Youth Revolution. Another key theme of the discussion will be the role of ICTs (and the practices that they mediate) in fostering transparency in commodity chains. The symposium will ask what differences these technologies can make on the practices of food consumption and production. After discussions, we will initiate an international network of food-thinkers and actors that will function as a platform for knowledge sharing and collaborations. The participants will be invited to engage in planning for the on-going future development of the network.

Produsage: a closer look at continuing developments

The concept of produsage developed from the realisation that new language was needed to describe the new phenomena emerging from the intersection of Web 2.0, user-generated content, and social media since the early years of the new millennium. When hundreds, thousands, maybe tens of thousands of participants utilise online platforms to collaborate in the development and continuous improvement of a wide variety of content – from software to informational resources to creative works –, and when this work takes place through a series of more or less unplanned, ad hoc, almost random cooperative encounters, then to describe these processes using terms which were developed during the industrial revolution no longer makes much sense. When – exactly because what takes place here is no longer a form of production in any conventional sense of the word – the outcomes of these massively distributed collaborations appear in the form of constantly changing, permanently mutable bodies of work which are owned at once by everyone and no-one, by the community of contributors as a whole but by none of them as individuals, then to conceptualise them as fixed and complete products in the industrial meaning of the term is missing the point. When what results from these efforts is of a quality (in both depth and breadth) that enables it to substitute for, replace, and even undermine the business model of long-established industrial products, even though precariously it relies on volunteer contributions, and when their volunteering efforts make it possible for some contributors to find semi- or fully professional employment in their field, then conventional industrial logic is put on its head.

Outlearning

Making the University Matter investigates how academics situate themselves simultaneously in the university and the world and how doing so affects the viability of the university setting. The university stands at the intersection of two sets of interests, needing to be at one with the world while aspiring to stand apart from it. In an era that promises intensified political instability, growing administrative pressures, dwindling economic returns and questions about economic viability, lower enrolments and shrinking programs, can the university continue to matter into the future? And if so, in which way? What will help it survive as an honest broker? What are the mechanisms for ensuring its independent voice? Barbie Zelizer brings together some of the leading names in the field of media and communication studies from around the globe to consider a multiplicity of answers from across the curriculum on making the university matter, including critical scholarship, interdisciplinarity, curricular blends of the humanities and social sciences, practical training and policy work. The collection is introduced with an essay by the editor and each section has a brief introduction to contextualise the essays and highlight the issues they raise.

Modelling port water collision risk using traffic conflicts

Navigational collisions are one of the major safety concerns for many seaports. Despite the extent of work recently done on collision risk analysis in port waters, little is known about the influencing factors of the risk. This paper develops a technique for modeling collision risks in port waterways in order to examine the associations between the risks and the geometric, traffic, and regulatory control characteristics of waterways. A binomial logistic model, which accounts for the correlations in the risks of a particular fairway at different time periods, is derived from traffic conflicts and calibrated for the Singapore port fairways. Estimation results show that the fairways attached to shoreline, traffic intersection and international fairway attribute higher risks, whereas those attached to confined water and local fairway possess lower risks. Higher risks are also found in the fairways featuring higher degree of bend, lower depth of water, higher numbers of cardinal and isolated danger marks, higher density of moving ships and lower operating speed. The risks are also found to be higher for night-time conditions.

Factors affecting pedestrian crossing behaviours at signalized crosswalks in urban areas in Beijing and Singapore

This paper reports an observation investigation of pedestrian crossing behaviors conducted at signalized crosswalks in urban areas in Singapore and Beijing on typical workdays. Each crosswalk was observed 3 times in different periods, i.e. normal hours, lunch hours, and rush hours. A total of 103,956 pedestrians were observed. The results showed that lane type, lane number, intersection type, and culture had significant effect on illegal pedestrian crossing in both cities; observation period had no significant effect on pedestrian violation in both cities; the violation rate in Singapore was lower than that in Beijing. However, observers reported that illegal crossing of vulnerable pedestrians, e.g. pregnant, the lame, old men and women, was more obvious in Singapore than that in Beijing. Evidence proved the hypothesis that the violations were related to pedestrians’ cognition of the definition of safety.

Examining Exposure of Motorcycles at Signalized Intersections

Crash statistics in Singapore from 2001 to 2005 have shown that motorcycles are involved in about 54% of intersection crashes. The overall involvement of motorcycles in crashes as the not-at-fault party is about 43% but at intersections, the corresponding percentage is increased to 57%. Quasi-induced exposure estimates show that the motorcycle exposure rate at signalized intersections is 41.7% even though motorcycles account for only 19% of the vehicle population. This study seeks to examine in greater details, the problem of motorcycle exposure at signalized intersections. In particular, the exposure arising from potential crashes with red light running vehicles from the conflicting stream at four signalized intersections is investigated. The results show that motorcycles are more exposed because they tend to accumulate near the stop-line during the red phase to facilitate an earlier discharge during the initial period of the green which is the more vulnerable period. At sites where there are more weaving opportunities because the lanes are wider or where there are exclusive right-turn lanes, the accumulation is higher and hence an increased exposure is observed. The analysis also shows that the presence of heavy vehicles tends to decrease motorcycle exposure as their weaving opportunities become restricted as well as there is a greater reluctance for them to weave past or queue alongside the heavy vehicles and their effects intensify for narrower lane width.

Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis

Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

Modeling fault among motorcyclists involved in crashes

Singapore crash statistics from 2001 to 2006 show that the motorcyclist fatality and injury rates per registered vehicle are higher than those of other motor vehicles by 13 and 7 times respectively. The crash involvement rate of motorcyclists as victims of other road users is also about 43%. The objective of this study is to identify the factors that contribute to the fault of motorcyclists involved in crashes. This is done by using the binary logit model to differentiate between at-fault and not-at-fault cases and the analysis is further categorized by the location of the crashes, i.e., at intersections, on expressways and at non-intersections. A number of explanatory variables representing roadway characteristics, environmental factors, motorcycle descriptions, and rider demographics have been evaluated. Time trend effect shows that not-at-fault crash involvement of motorcyclists has increased with time. The likelihood of night time crashes has also increased for not-at-fault crashes at intersections and expressways. The presence of surveillance cameras is effective in reducing not-at-fault crashes at intersections. Wet road surfaces increase at-fault crash involvement at non-intersections. At intersections, not-at-fault crash involvement is more likely on single lane roads or on median lane of multi-lane roads, while on expressways at-fault crash involvement is more likely on the median lane. Roads with higher speed limit have higher at-fault crash involvement and this is also true on expressways. Motorcycles with pillion passengers or with higher engine capacity have higher likelihood of being at-fault in crashes on expressways. Motorcyclists are more likely to be at-fault in collisions involving pedestrians and this effect is higher at night. In multi-vehicle crashes, motorcyclists are more likely to be victims than at fault. Young and older riders are more likely to be at-fault in crashes than middle-aged group of riders. The findings of this study will help to develop more targeted countermeasures to improve motorcycle safety and more cost-effective safety awareness program in motorcyclist training.

Empirical evaluation of alternative approaches in identifying crash hot spots

This study proposes a framework of a model-based hot spot identification method by applying full Bayes (FB) technique. In comparison with the state-of-the-art approach [i.e., empirical Bayes method (EB)], the advantage of the FB method is the capability to seamlessly integrate prior information and all available data into posterior distributions on which various ranking criteria could be based. With intersection crash data collected in Singapore, an empirical analysis was conducted to evaluate the following six approaches for hot spot identification: (a) naive ranking using raw crash data, (b) standard EB ranking, (c) FB ranking using a Poisson-gamma model, (d) FB ranking using a Poisson-lognormal model, (e) FB ranking using a hierarchical Poisson model, and (f) FB ranking using a hierarchical Poisson (AR-1) model. The results show that (a) when using the expected crash rate-related decision parameters, all model-based approaches perform significantly better in safety ranking than does the naive ranking method, and (b) the FB approach using hierarchical models significantly outperforms the standard EB approach in correctly identifying hazardous sites.

Bayesian hierarchical analysis on crash prediction models

Traditional crash prediction models, such as generalized linear regression models, are incapable of taking into account the multilevel data structure, which extensively exists in crash data. Disregarding the possible within-group correlations can lead to the production of models giving unreliable and biased estimates of unknowns. This study innovatively proposes a -level hierarchy, viz. (Geographic region level – Traffic site level – Traffic crash level – Driver-vehicle unit level – Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To properly model the potential cross-group heterogeneity due to the multilevel data structure, a framework of Bayesian hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is introduced and recommended. The proposed method is illustrated in an individual-severity analysis of intersection crashes using the Singapore crash records. This study proved the importance of accounting for the within-group correlations and demonstrated the flexibilities and effectiveness of the Bayesian hierarchical method in modeling multilevel structure of traffic crash data.

Factors affecting motorcycle crashes at signalized intersections

Singapore crash statistics show that motorcycles are involved in about 54% of crashes at intersections. Moreover, about 46% of fatal and 67% of injury motorcycle crashes occur at signalized intersections. The objective of this study is to identify causal factors affecting the motorcycle crashes at both four-legged and three-legged signalized intersections. Treating the data in time-series cross-section panels, this study explores different Hierarchical Poisson models and found that the model allowing autoregressive lag 1 dependent specification in the error term is the most suitable. Analysis of the results shows the number of lanes at the intersections significantly increases motorcycle crashes largely because of the higher exposure resulting from higher motorcycle accumulation at the stop line. Furthermore, the presence of a wide median at four-legged intersections and an exclusive right-turn lane and an uncontrolled left-turn lane at three-legged intersections exacerbate this potential hazard. Moreover, motorcycle crashes increase on high-speed roadways because of the vulnerability of the motorcyclists. The presence of red light cameras reduces motorcycle crashes significantly on the intersection roadways for both four-legged and three-legged intersections. With the red-light camera, motorcycles are less exposed to conflicts because it is observed that they are more disciplined in queuing at the stop line and less likely to jump start at the start of green.

Hotspot Identification: A Full Bayesian Hierarchical Modeling Approach

This study proposes a full Bayes (FB) hierarchical modeling approach in traffic crash hotspot identification. The FB approach is able to account for all uncertainties associated with crash risk and various risk factors by estimating a posterior distribution of the site safety on which various ranking criteria could be based. Moreover, by use of hierarchical model specification, FB approach is able to flexibly take into account various heterogeneities of crash occurrence due to spatiotemporal effects on traffic safety. Using Singapore intersection crash data(1997-2006), an empirical evaluate was conducted to compare the proposed FB approach to the state-of-the-art approaches. Results show that the Bayesian hierarchical models with accommodation for site specific effect and serial correlation have better goodness-of-fit than non hierarchical models. Furthermore, all model-based approaches perform significantly better in safety ranking than the naive approach using raw crash count. The FB hierarchical models were found to significantly outperform the standard EB approach in correctly identifying hotspots.

Effects of Mobile Phone Distraction at the Onset of Amber Light: Analysis of Driving Simulator Data

Distraction whilst driving on an approach to a signalized intersection is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. This study examines the decisions of distracted drivers during the onset of amber lights. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of IOWA - National Advanced Driving Simulator. Explanatory variables include age, gender, cell phone use, distance to stop-line, and speed. An iterative combination of decision tree and logistic regression analyses are employed to identify main effects, non-linearities, and interactions effects. Results show that novice (16-17 years) and younger (18-25 years) drivers’ had heightened amber light running risk while distracted by cell phone, and speed and distance thresholds yielded significant interaction effects. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Solutions are needed to combat the use of mobile phones whilst driving.

Perceived collision risks in anchorages : a hierarchical ordered probit analysis

Navigational collisions are a major safety concern in many seaports. Despite the recent advances in port navigational safety research, little is known about harbor pilot’s perception of collision risks in anchorages. This study attempts to model such risks by employing a hierarchical ordered probit model, which is calibrated by using data collected through a risk perception survey conducted on Singapore port pilots. The hierarchical model is found to be useful to account for correlations in risks perceived by individual pilots. Results show higher perceived risks in anchorages attached to intersection, local and international fairway; becoming more critical at night. Lesser risks are perceived in anchorages featuring shoreline in boundary, higher water depth, lower density of stationary ships, cardinal marks and isolated danger marks. Pilotage experience shows a negative effect on perceived risks. This study indicates that hierarchical modeling would be useful for treating correlations in navigational safety data.