Assessing Moral Reasoning, Cognitive Distortions and Driving Style in the Context of Post-License Young Driver Coaching

As part of the Dutch post-license young driver coaching program, Drive Xperience (DX), the level of moral reasoning was explored in relation to self-reported violating driving behaviors. Drawing from literature in the field of juvenile crime, three online assessments were developed to measure: a) social driving behavior; b) moral justification for rule compliance, and: c) cognitive distortions in relation to socially undesirable driving behavior. The assessments were administered between fall 2014 and fall 2016 to1660 participants in the DXprogram. The results show that immature levels of moral reasoning and prevalence of cognitive distortions are strongly associated with self-reported speed choice, space competition and traffic law violations

A Coaching Program for Recently Licensed Young Drivers in the Netherlands: Which Drivers are Attracted?

In line with European developments, a Dutch second phase coaching program was developed for young novice drivers to counteract their high accident risk. In this paper the design principles of the program are described. The empirical study focused on the entry characteristics of the participating young drivers (n=3117) as compared to a reference group of young drivers (n=345). Results show that the DX program attracted young drivers that in some respects showed a more risky profile than average young drivers in terms of speed violations, anger and the number of fines. In addition, four groups of participants with sharply differing driving styles could be distinguished

Developing Driving Task Scenarios for Developmentally Tailored Driving Assessments: Using an Evidence-Centered Design Model

A systematic procedure was described by which task scenarios can be derived as a basis for educationally informative and developmentally tailored driving assessments. To this end, Mislevy´s evidence centered design model for assessment was applied to the driving context. Borrowing from recent theories on driving and driving errors, task environment attributes were derived which may complicate the sub processes of driving and thus may result in varying task difficulty. A universe of assessment tasks was defined by combining basic driving tasks and critical task environment attributes. A collection of 55 critical driving task scenarios was selected from 39 video recorded driving lessons, throughout different stages of driving education. Results of a difficulty rating study pertaining to these scenarios including experienced driving instructors show that the scenarios discriminate well between beginning and advanced learner drivers. Successful scenario solution can be predicted by using an IRT function, where solution probability is a function of driver ability and task difficulty. Implications for assessment design activities are discussed

Validity of an On-Road Driver Performance Assessment Within an Initial Driver Training Context

Based on a competence-oriented view of driving a driver performance assessment (DPA) has been developed to inform learner drivers about their progress in acquiring driving proficiency. An initial validation study was carried out to evaluate the adequacy of inferences based on DPA-scores assigned by driving instructors. The results of two pilots are presented. Implications for driving performance assessment within driver training programs are discussed

Development and evaluation of an online three-level proton vs photon decision support prototype for head and neck cancer - Comparison of dose, toxicity and cost-effectiveness

AbstractTo quantitatively assess the effectiveness of proton therapy for individual patients, we developed a prototype for an online platform for proton decision support (PRODECIS) comparing photon and proton treatments on dose metric, toxicity and cost-effectiveness levels. An evaluation was performed with 23 head and neck cancer datasets

'Rapid Learning health care in oncology' – An approach towards decision support systems enabling customised radiotherapy' ☆ ☆☆

AbstractPurposeAn overview of the Rapid Learning methodology, its results, and the potential impact on radiotherapy.Material and resultsRapid Learning methodology is divided into four phases. In the data phase, diverse data are collected about past patients, treatments used, and outcomes. Innovative information technologies that support semantic interoperability enable distributed learning and data sharing without additional burden on health care professionals and without the need for data to leave the hospital. In the knowledge phase, prediction models are developed for new data and treatment outcomes by applying machine learning methods to data. In the application phase, this knowledge is applied in clinical practice via novel decision support systems or via extensions of existing models such as Tumour Control Probability models. In the evaluation phase, the predictability of treatment outcomes allows the new knowledge to be evaluated by comparing predicted and actual outcomes.ConclusionPersonalised or tailored cancer therapy ensures not only that patients receive an optimal treatment, but also that the right resources are being used for the right patients. Rapid Learning approaches combined with evidence based medicine are expected to improve the predictability of outcome and radiotherapy is the ideal field to study the value of Rapid Learning. The next step will be to include patient preferences in the decision making

A cancer drug atlas enables synergistic targeting of independent drug vulnerabilities.

Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value

Prognostic factors for perceived recovery or functional improvement in non-specific low back pain: secondary analyses of three randomized clinical trials

The objective of this study was to report on secondary analyses of a merged trial dataset aimed at exploring the potential importance of patient factors associated with clinically relevant improvements in non-acute, non-specific low back pain (LBP). From 273 predominantly male army workers (mean age 39 ± 10.5 years, range 20–56 years, 4 women) with LBP who were recruited in three randomized clinical trials, baseline individual patient factors, pain-related factors, work-related psychosocial factors, and psychological factors were evaluated as potential prognostic variables in a short-term (post-treatment) and a long-term logistic regression model (6 months after treatment). We found one dominant prognostic factor for improvement directly after treatment as well as 6 months later: baseline functional disability, expressed in Roland–Morris Disability Questionnaire scores. Baseline fear of movement, expressed in Tampa Scale for Kinesiophobia scores, had also significant prognostic value for long-term improvement. Less strongly associated with the outcome, but also included in our final models, were supervisor social support and duration of complaints (short-term model), and co-worker social support and pain radiation (long-term model). Information about initial levels of functional disability and fear-avoidance behaviour can be of value in the treatment of patient populations with characteristics comparable to the current army study population (e.g., predominantly male, physically active, working, moderate but chronic back problems). Individuals at risk for poor long-term LBP recovery, i.e., individuals with high initial level of disability and prominent fear-avoidance behaviour, can be distinguished that may need additional cognitive-behavioural treatment