Perception of risk, feelings of vulnerability and effects on driving behaviour in women drivers across the lifespan.

Sustained driving in older age has implications for quality of life and mental health. Studies have shown that despite the recognised importance of driving in maintaining health and social engagement, many women give up driving prematurely or adopt self-imposed restrictive driving practices. Emotional responses to driving have been implicated in these decisions. This research examined the effect of risk perception and feelings of vulnerability on women’s driving behaviour across the lifespan. It also developed and tested a modified theory of planned behaviour intervention to positively affect driving habits. The first two studies (N=395) used quantitative analysis to model driving behaviours affected by risk perception and feelings of vulnerability, and established that feelings of vulnerability do indeed affect women’s driving behaviour, specifically resulting in increases in driving avoidance and the adoption of maladaptive driving styles. Further, that self-regulation, conceptualised as avoidance, is used by drivers across the lifespan. Qualitative analysis of focus group data (N=48) in the third study provided a deeper understanding of the variations in coping behaviours adopted by sub-groups of drivers and extended the definition of self-regulation to incorporate adaptive coping strategies. The next study (N=64) reported the construction and preliminary validation of the novel self-regulation index (SRI) to measure wider self-regulation behaviours using an objective measure of driving behaviour, a simulated driving task. The understanding gained from the formative research was used in the final study, an extended theory of planned behaviour intervention to promote wider self-regulation behaviour, measured using the previously validated self-regulation index. The intervention achieved moderate success with changes in affective attitude and normative beliefs as well as self-reported behaviour. The results offer promise for self-regulation, incorporating a spectrum of planning and coping behaviours, to be used as a mechanism to assist drivers in achieving their personal mobility goals whilst promoting safe driving.

Feelings of vulnerability and effects on driving behaviour:a qualitative study

Feelings of vulnerability in driving can be considered an emotional response to risk perception and the coping strategies adopted could have implications for continued mobility. In a series of focus groups with 48 licensed drivers aged 18-75 years, expressions of vulnerability in driver coping behaviours were examined. Despite feelings of vulnerability appearing low, qualitative thematic analysis revealed a complex array of coping strategies in everyday driving including planning, use of 'co-pilots', self-regulation, avoidance and confrontive coping, i.e. intentional aggression toward other road users. The findings inform future intervention studies to enable appropriate coping strategy selection and prolong independent mobility in older adults. © 2014 Elsevier Ltd. All rights reserved.

Partnering with governments and other institutions:driving change in diabetes care

The human and material cost of type 2 diabetes is a cause of increasing concern for health professionals, representative organisations and governments worldwide. The scale of morbidity and mortality has led the United Nations to issue a resolution on diabetes, calling for national policies for prevention, treatment and care. There is clearly an urgent need for a concerted response from all interested parties at the community, national and international level to work towards the goals of the resolution and create effective, sustainable treatment models, care systems and prevention strategies. Action requires both a 'bottom-up' approach of public awareness campaigns and pressure from healthcare professionals, coupled with a 'top-down' drive for change, via partnerships with governments, third sector (non-governmental) organisations and other institutions. In this review, we examine how existing collaborative initiatives serve as examples for those seeking to implement change in health policy and practice in the quest to alleviate the health and economic burden of diabetes. Efforts are underway to provide continuous and comprehensive care models for those who already have type 2 diabetes; in some cases, national plans extend to prevention strategies in attempts to improve overall public health. In the spirit of partnership, collaborations with governments that incorporate sustainability, long-term goals and a holistic approach continue to be a driving force for change. It is now critical to maintain this momentum and use the growing body of compelling evidence to educate, inform and deliver a long-term, lasting impact on patient and public health worldwide. © 2007 The Authors.

Driving licensing renewal policy using neural network-based probabilistic decision support system

This paper investigates neural network-based probabilistic decision support system to assess drivers' knowledge for the objective of developing a renewal policy of driving licences. The probabilistic model correlates drivers' demographic data to their results in a simulated written driving exam (SWDE). The probabilistic decision support system classifies drivers' into two groups of passing and failing a SWDE. Knowledge assessment of drivers within a probabilistic framework allows quantifying and incorporating uncertainty information into the decision-making system. The results obtained in a Jordanian case study indicate that the performance of the probabilistic decision support systems is more reliable than conventional deterministic decision support systems. Implications of the proposed probabilistic decision support systems on the renewing of the driving licences decision and the possibility of including extra assessment methods are discussed.

Progmosis:evaluating risky individual behavior during epidemics using mobile network data

The possibility to analyze, quantify and forecast epidemic outbreaks is fundamental when devising effective disease containment strategies. Policy makers are faced with the intricate task of drafting realistically implementable policies that strike a balance between risk management and cost. Two major techniques policy makers have at their disposal are: epidemic modeling and contact tracing. Models are used to forecast the evolution of the epidemic both globally and regionally, while contact tracing is used to reconstruct the chain of people who have been potentially infected, so that they can be tested, isolated and treated immediately. However, both techniques might provide limited information, especially during an already advanced crisis when the need for action is urgent. In this paper we propose an alternative approach that goes beyond epidemic modeling and contact tracing, and leverages behavioral data generated by mobile carrier networks to evaluate contagion risk on a per-user basis. The individual risk represents the loss incurred by not isolating or treating a specific person, both in terms of how likely it is for this person to spread the disease as well as how many secondary infections it will cause. To this aim, we develop a model, named Progmosis, which quantifies this risk based on movement and regional aggregated statistics about infection rates. We develop and release an open-source tool that calculates this risk based on cellular network events. We simulate a realistic epidemic scenarios, based on an Ebola virus outbreak; we find that gradually restricting the mobility of a subset of individuals reduces the number of infected people after 30 days by 24%.