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A Comparison of Different Modeling Techniques in Predicting Mortality With the Tilburg Frailty Indicator

Background: Modern modeling techniques may potentially provide more accurate predictions of dichotomous outcomes than classical techniques. Objective: In this study, we aimed to examine the predictive performance of eight modeling techniques to predict mortality by frailty. Methods: We performed a longitudinal study with a 7-year follow-up. The sample consisted of 479 Dutch community-dwelling people, aged 75 years and older. Frailty was assessed with the Tilburg Frailty Indicator (TFI), a self-report questionnaire. This questionnaire consists of eight physical, four psychological, and three social frailty components. The municipality of Roosendaal, a city in the Netherlands, provided the mortality dates. We compared modeling techniques, such as support vector machine (SVM), neural network (NN), random forest, and least absolute shrinkage and selection operator, as well as classical techniques, such as logistic regression, two Bayesian networks, and recursive partitioning (RP). The area under the receiver operating characteristic curve (AUROC) indicated the performance of the models. The models were validated using bootstrapping. Results: We found that the NN model had the best validated performance (AUROC=0.812), followed by the SVM model (AUROC=0.705). The other models had validated AUROC values below 0.700. The RP model had the lowest validated AUROC (0.605). The NN model had the highest optimism (0.156). The predictor variable “difficulty in walking” was important for all models. Conclusions: Because of the high optimism of the NN model, we prefer the SVM model for predicting mortality among community-dwelling older people using the TFI, with the addition of “gender” and “age” variables. External validation is a necessary step before applying the prediction models in a new setting.

Transforming Clinical Practice Guideline Usage Through the Use of a Clinical Decision Support System: An explorative study at the University Medical Centre Utrecht

Personally perceived publication pressure: revising the Publication Pressure Questionnaire (PPQ) by using work stress models

Background: The emphasis on impact factors and the quantity of publications intensifies competition between researchers. This competition was traditionally considered an incentive to produce high-quality work, but there are unwanted side-effects of this competition like publication pressure. To measure the effect of publication pressure on researchers, the Publication Pressure Questionnaire (PPQ) was developed. Upon using the PPQ, some issues came to light that motivated a revision.Method: We constructed two new subscales based on work stress models using the facet method. We administered the revised PPQ (PPQr) to a convenience sample together with the Maslach Burnout Inventory (MBI) and the Work Design Questionnaire (WDQ). To assess which items best measured publication pressure, we carried out a principal component analysis (PCA). Reliability was sufficient when Cronbach's alpha > 0.7. Finally, we administered the PPQr in a larger, independent sample of researchers to check the reliability of the revised version.Results: Three components were identified as 'stress', 'attitude', and 'resources'. We selected 3 × 6 = 18 items with high loadings in the three-component solution. Based on the convenience sample, Cronbach's alphas were 0.83 for stress, 0.80 for attitude, and 0.76 for resources. We checked the validity of the PPQr by inspecting the correlations with the MBI and the WDQ. Stress correlated 0.62 with MBI's emotional exhaustion. Resources correlated 0.50 with relevant WDQ subscales. To assess the internal structure of the PPQr in the independent reliability sample, we conducted the principal component analysis. The three-component solution explains 50% of the variance. Cronbach's alphas were 0.80, 0.78, and 0.75 for stress, attitude, and resources, respectively.Conclusion: We conclude that the PPQr is a valid and reliable instrument to measure publication pressure in academic researchers from all disciplinary fields. The PPQr strongly relates to burnout and could also be beneficial for policy makers and research institutions to assess the degree of publication pressure in their institute.

Telemonitoring for independently living elderly

In this paper we investigate the precise focus required of a telemonitoring system for the domain of independently living elderly. Particularly, we investigate (1) the needs of telemonitoring for this particular domain, and (2) the requirements for such a telemonitoring system. For our investigation, we performed an extensive study of the literature, as well as performed interviews with 36 individuals active in the field. As a result, we established numerous needs to be considered, being foremost information need on safety, with regard to care response on emergencies (e.g., falling incidents, wandering), as well information need on dependence on care, with regard to inactivity, self-neglect and loneliness. Subsequently, we established numerous requirements to be addressed, being foremost the use of non-wearable sensors, unobtrusiveness, durability, reliability, privacy, and ubiquitousness. In our discussion of the requirements, we detailed specifically the topics of focus, functionality, and form of a telemonitoring system for this domain.

Estimated impact of CO2 and NOx emission reduction targets on car ownership and car use in The Netherlands

Densely populated areas are major sources of air, soil and water pollution. Agriculture, manufacturing, consumer households and road traffic all have their share. This is particularly true for the country featured in this paper: the Netherlands. Continuous pollution of the air and soil manifests itself as acification, decalcification and eutrofication. Biodiversity becomes lower and lower in nature areas. Biological farms are also under threat. In case of mobility, local air pollution may have a huge health impact. Effective policy is called for, after high courts blocked construction projects, because of foreseen building- and transport-related NOx emissions. EU law makers are after Dutch governments, because these favoured economics and politics over environmental and liveability concerns. But, people in the Netherlands are strongly divided. The latest provincial elections were dominated by environmental concerns, next to many socio-economic issues. NOx and CO2 emissions by passenger cars are in focus. Technical means and increasing fuel economy norms strongly reduced NOx emissions to a still too high level. A larger number of cars neutralized a technological reduction of CO2 emissions. The question is: What would be the impact of a drastic mandatory reduction in CO2, NOx, and PM10 emissions on car ownership and use in the Netherlands? The authors used literature, scenario analysis and simulation modelling to answer this question. Electric mobility could remove these emissions. Its full impact will only be achieved if the grid-mix, which is still dominated by fossil fuels, becomes green(er), which is a gradual, long-term, process. EVs compete with other consumers of electricity, as many other activities, such as heating, are also electrifying. With the current grid-mix, it is inevitable that the number of km per vehicle per year is reduced to reach the scenario targets (−25% resp. −50% CO2 emissions by cars). This calls for an individual mobility budget per car user.

Longitudinal residential ambient monitoring

Wireless sensor networks are becoming popular in the field of ambient assisted living. In this paper we report our study on the relationship between a functional health metric and features derived from the sensor data. Sensor systems are installed in the houses of nine people who are also quarterly visited by an occupational therapist for functional health assessments. Different features are extracted and these are correlated with a metric of functional health (the AMPS). Though the sample is small, the results indicate that some features are better in describing the functional health in the population, but individual differences should also be taken into account when developing a sensor system for functional health assessment.