Abstract

Delay, probability and social discounting refer to the decrease in the subjective value of a reward as a function of its delay of delivery, probability or social distance, respectively. One question in the area is whether the three types of discounting share the same process or whether they are held by different processes. This question has been investigated by looking at the correlations between the three types of discounting. Moreover, it has been suggested that the method used to obtain the indifference points could modulate the discounting rates. However, the search of a common process underlying the three types of discounting should not be influenced by the method used to obtain the indifference points. Therefore, the purpose of this study was to determine whether the method used to obtain the indifference points contributes to the correlation between the three types of discounting. Forty-four college students responded tasks of delay, probability and social discounting —which used a hypothetical monetary reward— with two different methods: Binary choice and adjusting amount. We found significant correlations between binary-choice and adjusting-amount methods for the three types of discounting. Albeit, a significantly higher delay discounting rate was found with the adjusting-amount method rather than with the binary-choice method, but there were no significant differences between the probability and social discounting rates obtained with both methods. In addition to the previous results, with the binary-choice method it was found that social discounting correlated with delay and probability discounting, but the last two did not correlate between them. In contrast, with the adjusting-amount method, it was only found a correlation between delay and probability discounting. The latter result suggests that the method used to obtain the indifference points contributes to the search of a common process between the three types of discounting. Actually a common decision-making process underlying the three types of discounting could depend on the context in which the choice is made.

Abstract

Background São Paulo city, Brazil, faces challenges caused by rapid urbanization. We illustrate how future travel patterns could lead to different health consequences in the city. Methods We evaluated the health impacts of different travel pattern scenarios for the São Paulo adult population by comparing the travel patterns of São Paulo in 2012 with counterfactual scenarios in which the city adopted travel patterns of i) those living in the city's expanded centre; ii) London (2012); iii) a highly motorized São Paulo (SP California); and iv) a visionary São Paulo (SP 2040), with high levels of walking and cycling and low levels of car and motorcycle use. For each scenario we estimated changes in exposure to air pollution, road injury risk, and physical activity. Health outcomes were estimated using disability adjusted life years (DALYs) and premature deaths averted. Sensitivity analyses were performed to identify the main sources of uncertainty. Results We found considerable health gains in the SP 2040 scenario (total 63.6 k DALYs avoided), with 4.7% of premature deaths from ischemic heart disease avoided from increases in physical activity alone. Conversely, we found substantial health losses in the scenario favouring private transport (SP California, total increase of 54.9 k DALYs), with an increase in road traffic deaths and injuries among pedestrians and motorized vehicles. Parameters related to air pollution had the largest impact on uncertainty. Conclusions Shifting travel patterns towards more sustainable transport can provide major health benefits in São Paulo. Reducing the uncertainties in the findings should be a priority for empirical and modelling research on the health impacts of such shifts. Highlights • There is scarce evidence of transportation impacts on health in developing cities • Comparative risk assessment used to assess impacts on three major risk factors • We found large net health gains in sustainable transport scenario for Sao Paulo, Brazil • We also found large net health losses in a car dependent scenario for Sao Paulo • Physical activity provided the largest health impacts, similar to previous studie Document type: Article

Abstract

Background Road transport workers (RTWs) are at high risk of exposure to several occupational carcinogens. However, there are gaps in knowledge regarding the extent and the circumstances of exposure. As a sub-study of the Australian Work Exposures Study, this study investigated the prevalence of occupational exposure in Australian RTWs. Methods A random sample of Australian working population was invited to a telephone interview regarding their current jobs. An automated expert-assessment procedure was applied to self-reported job-related tasks using a web-based application. 162 RTWs were included in this study. Results RTWs were exposed to diesel exhaust (97%), solar ultraviolet radiation (78%), environmental tobacco smoke (55%), benzene (29%), silica (15%), and asbestos (10%) at work. Besides driving on roads, vehicle maintenance-related tasks were the major source of carcinogen exposures among RTWs. Discussion Most RTWs are exposed to at least one carcinogen at work. We have identified tasks where the use of control measures could potentially reduce exposures. Am. J. Ind. Med. 59:31–41, 2016. © 2015 Wiley Periodicals, Inc.

Abstract

Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis (NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients’ symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network. Document type: Article