Feature-specific terrain park-injury rates and risk factors in snowboarders : a case–control study

Background : Snowboarding is a popular albeit risky sport and terrain park (TP) injuries are more severe than regular slope injuries. TPs contain man-made features that facilitate aerial manoeuvres. The objectives of this study were to determine overall and feature-specific injury rates and the potential risk factors for TP injuries. Methods : Case–control study with exposure estimation, conducted in an Alberta TP during two ski seasons. Cases were snowboarders injured in the TP who presented to ski patrol and/or local emergency departments. Controls were uninjured snowboarders in the same TP. κ Statistics were used to measure the reliability of reported risk factor information. Injury rates were calculated and adjusted logistic regression was used to calculate the feature-specific odds of injury. Results : Overall, 333 cases and 1261 controls were enrolled. Reliability of risk factor information was κ>0.60 for 21/24 variables. The overall injury rate was 0.75/1000 runs. Rates were highest for jumps and half-pipe (both 2.56/1000 runs) and lowest for rails (0.43/1000 runs) and quarter-pipes (0.24/1000 runs). Compared with rails, there were increased odds of injury for half-pipe (OR 9.63; 95% CI 4.80 to 19.32), jumps (OR 4.29; 95% CI 2.72 to 6.76), mushroom (OR 2.30; 95% CI 1.20 to 4.41) and kickers (OR 1.99; 95% CI 1.27 to 3.12). Conclusions : Higher feature-specific injury rates and increased odds of injury were associated with features that promote aerial manoeuvres or a large drop to the ground. Further research is required to determine ways to increase snowboarder safety in the TP

Comparing the characteristics of snowboarders injured in a terrain park who present to the ski patrol, the emergency department or both

Ski patrol report forms are a common data source in ski/snowboard research, but it is unclear if those who only present to the emergency department (ED) are systematically different from those who see the ski patrol. To determine the proportion and characteristics of injured snowboarders who bypass the ski patrol before presenting to the ED, three groups of injured snowboarders were compared: presented to the ED only, ski patrol only and ski patrol and ED. Data were collected from ski patrol Accident Report Forms (ARFs), ED medical records and telephone interviews. There were 333 injured snowboarders (ED only: 34, ski patrol only: 107, both: 192). Ability, time of day, snow conditions or drugs/alcohol predicted ED only presentation. Concussions (RRR: 4.66; 95% CI: 1.83, 11.90), sprains/strains (RRR: 4.22; 95% CI: 1.87, 9.49), head/neck (RRR: 2.90; 95% CI: 1.48, 5.78), trunk (RRR: 4.17; 95% CI: 1.92, 9.09) or lower extremity (RRR: 3.65; 95% CI: 1.32, 10.07) injuries were significantly more likely to present to ski patrol only versus ski patrol and ED. In conclusion, snowboarders who presented to the ED only had similar injuries as those who presented to both

Characteristics of injuries sustained by snowboarders in a terrain park

Abstract OBJECTIVE: To determine injured body regions and injury type resulting from snowboarding on aerial and nonaerial terrain park features and the accuracy of ski patrol assessments compared with physician diagnoses. DESIGN: Case series study. SETTING: An Alberta terrain park during the 2008-2009 and 2009-2010 seasons. PATIENTS: There were 333 snowboarders injured on features (379 injuries). ASSESSMENT OF RISK FACTORS: Aerial or nonaerial terrain park feature used at injury, injured body region, injury type, and additional risk factors were recorded from ski patrol Accident Report Forms, emergency department medical records, and telephone interviews. MEASURES: Odds of injury to body regions and injury types on aerial versus nonaerial features were calculated using multinomial logistic regression. Accuracy of ski patrol injury assessments was examined through sensitivity, specificity, and kappa (κ) statistics. RESULTS: The wrist was the most commonly injured body region (20%), and fracture was the most common injury type (36%). Compared with the upper extremity, the odds of head/neck [odds ratio (OR), 2.58; 95% confidence interval (CI), 1.37-4.85] and trunk (OR, 3.65; 95% CI, 1.68-7.95) injuries were significantly greater on aerial features. There was no significant association between aerial versus nonaerial feature and injury type. The accuracy of ski patrol injury assessment was higher for injured body region (κ = 0.65; 95% CI, 0.54-0.75) than for injury type (κ = 0.29; 95% CI, 0.22-0.37). CONCLUSIONS: Snowboarders were significantly more likely to sustain head/neck or trunk injuries than upper extremity injuries on aerial features. Investigators should acknowledge potential misclassification when using ski patrol injury assessments

Interventions to increase attendance for diabetic retinopathy screening

BACKGROUND: Despite evidence supporting the effectiveness of diabetic retinopathy screening (DRS) in reducing the risk of sight loss, attendance for screening is consistently below recommended levels.OBJECTIVES: The primary objective of the review was to assess the effectiveness of quality improvement (QI) interventions that seek to increase attendance for DRS in people with type 1 and type 2 diabetes.Secondary objectives were:To use validated taxonomies of QI intervention strategies and behaviour change techniques (BCTs) to code the description of interventions in the included studies and determine whether interventions that include particular QI strategies or component BCTs are more effective in increasing screening attendance;To explore heterogeneity in effect size within and between studies to identify potential explanatory factors for variability in effect size;To explore differential effects in subgroups to provide information on how equity of screening attendance could be improved;To critically appraise and summarise current evidence on the resource use, costs and cost effectiveness.SEARCH METHODS: We searched the Cochrane Library, MEDLINE, Embase, PsycINFO, Web of Science, ProQuest Family Health, OpenGrey, the ISRCTN, ClinicalTrials.gov, and the WHO ICTRP to identify randomised controlled trials (RCTs) that were designed to improve attendance for DRS or were evaluating general quality improvement (QI) strategies for diabetes care and reported the effect of the intervention on DRS attendance. We searched the resources on 13 February 2017. We did not use any date or language restrictions in the searches.SELECTION CRITERIA: We included RCTs that compared any QI intervention to usual care or a more intensive (stepped) intervention versus a less intensive intervention.DATA COLLECTION AND ANALYSIS: We coded the QI strategy using a modification of the taxonomy developed by Cochrane Effective Practice and Organisation of Care (EPOC) and BCTs using the BCT Taxonomy version 1 (BCTTv1). We used Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital (PROGRESS) elements to describe the characteristics of participants in the included studies that could have an impact on equity of access to health services.Two review authors independently extracted data. One review author entered the data into Review Manager 5 and a second review author checked them. Two review authors independently assessed risks of bias in the included studies and extracted data. We rated certainty of evidence using GRADE.MAIN RESULTS: We included 66 RCTs conducted predominantly (62%) in the USA. Overall we judged the trials to be at low or unclear risk of bias. QI strategies were multifaceted and targeted patients, healthcare professionals or healthcare systems. Fifty-six studies (329,164 participants) compared intervention versus usual care (median duration of follow-up 12 months). Overall, DRS attendance increased by 12% (risk difference (RD) 0.12, 95% confidence interval (CI) 0.10 to 0.14; low-certainty evidence) compared with usual care, with substantial heterogeneity in effect size. Both DRS-targeted (RD 0.17, 95% CI 0.11 to 0.22) and general QI interventions (RD 0.12, 95% CI 0.09 to 0.15) were effective, particularly where baseline DRS attendance was low. All BCT combinations were associated with significant improvements, particularly in those with poor attendance. We found higher effect estimates in subgroup analyses for the BCTs 'goal setting (outcome)' (RD 0.26, 95% CI 0.16 to 0.36) and 'feedback on outcomes of behaviour' (RD 0.22, 95% CI 0.15 to 0.29) in interventions targeting patients, and 'restructuring the social environment' (RD 0.19, 95% CI 0.12 to 0.26) and 'credible source' (RD 0.16, 95% CI 0.08 to 0.24) in interventions targeting healthcare professionals.Ten studies (23,715 participants) compared a more intensive (stepped) intervention versus a less intensive intervention. In these studies DRS attendance increased by 5% (RD 0.05, 95% CI 0.02 to 0.09; moderate-certainty evidence).Fourteen studies reporting any QI intervention compared to usual care included economic outcomes. However, only five of these were full economic evaluations. Overall, we found that there is insufficient evidence to draw robust conclusions about the relative cost effectiveness of the interventions compared to each other or against usual care.With the exception of gender and ethnicity, the characteristics of participants were poorly described in terms of PROGRESS elements. Seventeen studies (25.8%) were conducted in disadvantaged populations. No studies were carried out in low- or middle-income countries.AUTHORS' CONCLUSIONS: The results of this review provide evidence that QI interventions targeting patients, healthcare professionals or the healthcare system are associated with meaningful improvements in DRS attendance compared to usual care. There was no statistically significant difference between interventions specifically aimed at DRS and those which were part of a general QI strategy for improving diabetes care. This is a significant finding, due to the additional benefits of general QI interventions in terms of improving glycaemic control, vascular risk management and screening for other microvascular complications. It is likely that further (but smaller) improvements in DRS attendance can also be achieved by increasing the intensity of a particular QI component or adding further components.</p

Buildings behaving badly:A behavioral experiment on how different motivational frames influence residential energy label adoption in the Netherlands

Heating buildings contributes to approximately 36% of Europe’s energy demand and several EU member states have adopted mandatory energy labels to improve energy efficiency by promoting home weatherization investments. This paper focuses on the perception of the energy label for residential buildings in the Netherlands and the role of different frames (egoistic, biospheric and social norms and neutral frames) in motivating adoption of energy labels for housing. We used a behavioral email experiment and an online survey to investigate these motivational factors. We find that biospheric frames are weaker than the other three motivational frames in terms of engaging interest in the energy label, but that the biospheric frame results in higher willingness to pay (WTP) for the energy label. We also find that age (rather than income) correlates with higher willingness to pay for home energy labels

Modeling the uptake of plug-in vehicles in a heterogeneous car market using a consumer segmentation approach

There is broad agreement on the need for substantial use of low carbon vectors in the long term in the transport sector. Electrification, via mass market adoption of plug-in vehicles (i.e. battery electric and plug-in hybrid electric vehicles), has emerged as a front runner for road transport across the globe, but there are concerns that the pace and extent implied by many modelling studies is problematic and that assessment of (a) the heterogeneity in the market, (b) other low carbon vectors (e.g. conventional hybrids, hydrogen fuel cell) and (c) life cycle energy and environmental impacts have been relatively neglected. This paper aims to fill these gaps by examining the timing, scale and impacts of the uptake of plug-in vehicles in the heterogeneous UK car market from a consumer perspective. To achieve this aim it (a) brings together a bespoke disaggregated model of the transport-energy-environment system (the UK Transport Carbon Model) with previous work by the authors on heterogeneity in the demand for and supply of plug-in vehicles and (b) applies the improved model to develop future low carbon scenarios that assess the potential impact of different investment pathways and policy approaches to the electrification of cars with the view to meeting the UK’s legally binding carbon budgets to 2050. The results show the importance of accounting for the heterogeneity in and dynamic nature of the car market in terms of new technology adoption by private consumers, so called ‘user choosers’ and fleet managers, as well as accounting for potential effects on wider life cycle emissions resulting from different uptake pathways. It allows an assessment of the effectiveness of different policy instruments, market conditions (vehicle supply, private vs fleet market, vehicle segments) and social factors (consumer awareness, range “anxiety”, perceived charging requirements) on different consumer segments, thus providing more policy-focused conclusions on the likely pathways to high penetration of plug-in vehicles that may be required to meet future carbon and air quality targets

Data-driven staging of genetic frontotemporal dementia using multi-modal MRI

Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high-dimensional large-scale population datasets to obtain individual scores of disease stage. We used cross-sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting-state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI-obtained disease scores to the estimated years to onset (age—mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre-dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data-driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics

Assessing the importance of car meanings and attitudes in consumer evaluations of electric vehicles

This paper reports findings from a research study which assesses the importance of attitudinal constructs related to general car attitudes and the meanings attached to car ownership over evaluations of electric vehicles (EVs). The data are assessed using principal component analysis to evaluate the structure of the underlying attitudinal constructs. The identified constructs are then entered into a hierarchical regression analysis which uses either positive or negative evaluations of the instrumental capabilities of EVs as the dependent variable. Results show that attitudinal constructs offer additional predictive power over socioeconomic characteristics and that the symbolic and emotive meanings of car ownership are as, if not more, effective in explaining the assessment of EV instrumental capability as compared to issues of cost and environmental concern. Additionally, the more important an individual considers their car to be in their everyday life, the more negative their evaluations are of EVs whilst individuals who claim to be knowledgeable about cars in general and EVs in particular have a lower propensity for negative EV attitudes. However, positive and negative EV attitudes are related to different attitudinal constructs suggesting that it is possible for someone to hold both negative and positive assessments at the same time

Lifestyle, efficiency and limits: modelling transport energy and emissions using a socio-technical approach

It is well-known that societal energy consumption and pollutant emissions from transport are influenced not only by technical efficiency, mode choice and the carbon/pollutant content of energy but also by lifestyle choices and socio-cultural factors. However, only a few attempts have been made to integrate all of these insights into systems models of future transport energy demand or even scenario analysis. This paper addresses this gap in research and practice by presenting the development and use of quantitative scenarios using an integrated transport-energy-environment systems model to explore four contrasting futures for Scotland that compare transport-related ‘lifestyle’ changes and socio-cultural factors against a transition pathway focussing on transport electrification and the phasing out of conventionally fuelled vehicles using a socio-technical approach. We found that radical demand and supply strategies can have important synergies and trade-offs between reducing life cycle greenhouse gas and air quality emissions. Lifestyle change alone can have a comparable and earlier effect on transport carbon and air quality emissions than a transition to EVs with no lifestyle change. Yet, the detailed modelling of four contrasting futures suggests that both strategies have limits to meeting legislated carbon budgets, which may only be achieved with a combined strategy of radical change in travel patterns, mode and vehicle choice, vehicle occupancy and on-road driving behaviour with high electrification and phasing out of conventional petrol and diesel road vehicles. The newfound urgency of ‘cleaning up our act’ since the Paris Agreement and Dieselgate scandal suggests that we cannot just wait for the ‘technology fix’

Data-driven staging of genetic frontotemporal dementia using multi-modal MRI.

Funder: Fondation Brain Canada; Id: http://dx.doi.org/10.13039/100009408Funder: Fonds de Recherche du Québec ‐ Santé; Id: http://dx.doi.org/10.13039/501100000156Funder: Health Canada; Id: http://dx.doi.org/10.13039/501100000008Funder: Brain Canada Foundation; Id: http://dx.doi.org/10.13039/100009408Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high-dimensional large-scale population datasets to obtain individual scores of disease stage. We used cross-sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting-state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI-obtained disease scores to the estimated years to onset (age-mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre-dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data-driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics