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.
DOCUMENT
Abstract BackgroundFrailty is a syndrome that is defined as an accumulation of deficits in physical, psychological, and social domains. On a global scale, there is an urgent need to create frailty-ready healthcare systems due to the healthcare burden that frailty confers on systems and the increased risk of falls, healthcare utilization, disability, and premature mortality. Several studies have been conducted to develop prediction models for predicting frailty. Most studies used logistic regression as a technique to develop a prediction model. One area that has experienced significant growth is the application of Bayesian techniques, partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. ObjectiveWe compared ten different Bayesian networks as proposed by ten experts in the field of frail elderly people to predict frailty with a choice from ten dichotomized determinants for frailty. MethodsWe used the opinion of ten experts who could indicate, using an empty Bayesian network graph, the important predictors for frailty and the interactions between the different predictors. The candidate predictors were age, sex, marital status, ethnicity, education, income, lifestyle, multimorbidity, life events, and home living environment. The ten Bayesian network models were evaluated in terms of their ability to predict frailty. For the evaluation, we used the data of 479 participants that filled in the Tilburg Frailty indicator (TFI) questionnaire for assessing frailty among community-dwelling older people. The data set contained the aforementioned variables and the outcome ”frail”. The model fit of each model was measured using the Akaike information criterion (AIC) and the predictive performance of the models was measured using the area under the curve (AUC) of the receiver operator characteristic (ROC). The AUCs of the models were validated using bootstrapping with 100 repetitions. The relative importance of the predictors in the models was calculated using the permutation feature importance algorithm (PFI). ResultsThe ten Bayesian networks of the ten experts differed considerably regarding the predictors and the connections between the predictors and the outcome. However, all ten networks had corrected AUCs 0.700. Evaluating the importance of the predictors in each model, ”diseases or chronic disorders” was the most important predictor in all models (10 times). The predictors ”lifestyle” and ”monthly income” were also often present in the models (both 6 times). One or more diseases or chronic disorders, an unhealthy lifestyle, and a monthly income below 1,800 euro increased the likelihood of frailty. ConclusionsAlthough the ten experts all made different graphs, the predictive performance was always satisfying (AUCs 0.700). While it is true that the predictor importance varied all the time, the top three of the predictor importance consisted of “diseases or chronic disorders”, “lifestyle” and “monthly income”. All in all, asking for the opinion of experts in the field of frail elderly to predict frailty with Bayesian networks may be more rewarding than a data-driven forecast with Bayesian networks because they have expert knowledge regarding interactions between the different predictors.
LINK
This paper presents the results of an evaluation of a technology-supported leisure game for people with dementia in relation to the stimulation of social behavior.
DOCUMENT
Background: Blended physiotherapy, in which physiotherapy sessions and an online application are integrated, might support patients in taking an active role in the management of their chronic condition and may reduce disease related costs. The aim of this study was to evaluate the cost-effectiveness of a blended physiotherapy intervention (e-Exercise) compared to usual physiotherapy in patients with osteoarthritis of hip and/or knee, from the societal as well as the healthcare perspective. Methods: This economic evaluation was conducted alongside a 12-month cluster randomized controlled trial, in which 108 patients received e-Exercise, consisting of physiotherapy sessions and a web-application, and 99 patients received usual physiotherapy. Clinical outcome measures were quality-adjusted life years (QALYs) according to the EuroQol (EQ-5D-3 L), physical functioning (HOOS/KOOS) and physical activity (Actigraph Accelerometer). Costs were measured using self-reported questionnaires. Missing data were multiply imputed and bootstrapping was used to estimate statistical uncertainty.
DOCUMENT
Adaptive survey design has attracted great interest in recent years, but the number of case studies describing actual implementation is still thin. Reasons for this may be the gap between survey methodology and data collection, practical complications in differentiating effort across sample units and lack of flexibility of survey case management systems. Currently, adaptive survey design is a standard option in redesigns of person and household surveys at Statistics Netherlands and it has been implemented for the Dutch Health survey in 2018. In this article, the implementation of static adaptive survey designs is described and motivated with a focus on practical feasibility.
DOCUMENT
In general, people are poorly protected against cyberthreats, with the main reason being user behaviour. For the study described in this paper, a ques-tionnaire was developed in order to understand how people’s knowledge of and attitude towards both cyberthreats and cyber security controls affect in-tention to adopt cybersecure behaviour. The study divides attitude into a cog-nitive and an affective component. Although only the cognitive component of attitude is usually studied, the results from a questionnaire of 300 respond-ents show that both the affective and cognitive components of attitude have a clearly positive, albeit varying, influence on behavioural intention, with the affective component having an even greater effect on attitude than the cog-nitive aspect. No correlation was found between knowledge and behavioural intention. The results indicate that attitude is an important factor to include when developing behavioural interventions, but also that different kinds of attitude should be addressed differently in interventions.
DOCUMENT
Objectives This paper is the first multidisciplinary study into the impact of new skill requirements in the job on absenteeism. The aim of this study was to investigate whether economic skills obsolescence (ESO) increased both absence frequency and average duration mediated by burnout and/or work engagement.Methods A longitudinal study was conducted on data from the Dutch Study on Transitions in Employment, Ability and Motivation (N=4493). Structural equation modelling was used to test the specific direct and indirect effects of ESO on absence frequency and average duration, followed by bootstrapping to compute the confidence intervals.Results ESO at baseline had a positive relationship with burnout at follow-up. In turn, burnout was positively related to both absence frequency and average absence duration at follow-up. The bootstrap indirect effect test showed that ESO had a significant positive indirect effect, via burnout and (lower) work engagement, on absence frequency and average duration. Furthermore, ESO at baseline was negatively related to work engagement at follow-up. Work engagement, in turn, was negatively related to absence frequency and average duration at follow-up. The bootstrap test showed that ESO had a significant indirect effect, via work engagement, on absence frequency.Conclusion ESO is associated with subsequent absence frequency and average duration of workers, both mediated by burnout and decreased work engagement.
MULTIFILE
Crowdfunding is gaining popularity as a viable means to raise financial capital for good causes, cultural goods, new products, and ventures. Little empirical research has been done to understand crowdfunding and basic academic knowledge of its dynamics is still lacking. By data mining the crowdfunding platform Kickstarter.com and Facebook we collected a large dataset of crowdfunding projects and the ego networks of the entrepreneurs. We study the relation of the success of the Kickstarter project to his social network and to media activities and find a scaling law that predicts the number of clicks on the project website required for a successful project. Examining the results of the social network analysis we concluded that successful initiators on Kickstarter have more friends but a sparser network. Unsuccessful entrepreneurs on the other hand have a higher average degree suggesting a denser network. Our analyses suggest that sparse, and thus diverse networks are beneficial for the success of a project.
DOCUMENT
OBJECTIVE: This study aimed to examine the prevalence and predictors of reconstructive surgery among pediatric burn patients in the Netherlands.METHODS: Pediatric burn patients were identified through the Dutch Burn Repository R3. Eligibility criteria included a burn requiring hospital admission or surgical treatment at one of the Dutch burn centers in 2009-2019. First, patient, burn, and treatment characteristics were summarized using descriptive statistics. Second, time to the first reconstructive surgery was modelled using Kaplan Meier curves. Third, a prediction model was developed using univariate and multivariate logistic regression. The model's performance was assessed using calibration, discrimination, and explained variance. Fourth, internal validation was performed using bootstrapping.RESULTS: Approximately three percent (n = 84) of pediatric patients (n = 3072) required reconstructive surgery between the initial burn-related hospital admission and September 2021. Median time to the first reconstructive surgery was 1.2 (0.7-1.6) years. Most surgeries were performed on the face, arm, neck, hand, or anterior trunk, owing to contractures or hypertrophic scarring. Predictors of reconstruction included the etiology, anatomical site, extent of full-thickness burn, surgical treatment in the acute phase, and length of hospital stay.CONCLUSION: Our study provided an overview of the prevalence and independent predictors of reconstructive surgery in the pediatric burn population.
DOCUMENT
A public sector that adequately makes use of information technology can provide improved government services that not only stimulates business development it also intensifies citizen participation and economic growth. However, the effectiveness of IT and its governance at both national as well as on municipality level leaves much to be desired. It is often stated that this is due to a lack of digital skills needed to manage the IT function and alignment with business. Therefore, the aim of this study is to determine the effect that digital leadership competences and IT capabilities have on digital transformation readiness within Dutch municipalities. Based on an analyses of survey data from 178 respondents we recommend municipalities to implement a range of activities that all are related to realize the ability to constantly apply strategic thinking and organizational leadership to exploit the capability of Information Technology to improve the business.
MULTIFILE
