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The article describes an analysis of the use of e-learning to improve the learning transfer to practice in continuing education. Therefore an e-learning offer has been developed as a part between two attendance periods of a training course in the field of Ambient Assisted Living (AAL). All participants of the course were free to use the e-learning offer. After the end of the e-learning part we compared the e-learning users to the other participants. Using an online questionnaire we explored if there are differences in the activities in the field AAL after the training course. The results show that e-learning is beneficial especially for communication processes. Due to the fact that the possibility to talk about the learning content is an essential factor for the learning transfer, e-learning can improve the learning success.
Due to the emerging evidence of health IT as opportunity and risk for clinical workflows, health IT must undergo a continuous measurement of its efficacy and efficiency. IT-benchmarks are a proven means for providing this information. The aim of this study was to enhance the methodology of an existing benchmarking procedure by including, in particular, new indicators of clinical workflows and by proposing new types of visualisation. Drawing on the concept of information logistics, we propose four workflow descriptors that were applied to four clinical processes. General and specific indicators were derived from these descriptors and processes. 199 chief information officers (CIOs) took part in the benchmarking. These hospitals were assigned to reference groups of a similar size and ownership from a total of 259 hospitals. Stepwise and comprehensive feedback was given to the CIOs. Most participants who evaluated the benchmark rated the procedure as very good, good, or rather good (98.4%). Benchmark information was used by CIOs for getting a general overview, advancing IT, preparing negotiations with board members, and arguing for a new IT project.
Background:
One of the main problems of Internet-delivered interventions for a range of disorders is the high dropout rate, yet little is known about the factors associated with this. We recently developed and tested a Web-based 6-session program to enhance motivation to change for women with anorexia nervosa, bulimia nervosa, or related subthreshold eating pathology.
Objective:
The aim of the present study was to identify predictors of dropout from this Web program.
Methods:
A total of 179 women took part in the study. We used survival analyses (Cox regression) to investigate the predictive effect of eating disorder pathology (assessed by the Eating Disorders Examination-Questionnaire; EDE-Q), depressive mood (Hopkins Symptom Checklist), motivation to change (University of Rhode Island Change Assessment Scale; URICA), and participants’ age at dropout. To identify predictors, we used the least absolute shrinkage and selection operator (LASSO) method.
Results:
The dropout rate was 50.8% (91/179) and was equally distributed across the 6 treatment sessions. The LASSO analysis revealed that higher scores on the Shape Concerns subscale of the EDE-Q, a higher frequency of binge eating episodes and vomiting, as well as higher depression scores significantly increased the probability of dropout. However, we did not find any effect of the URICA or age on dropout.
Conclusions:
Women with more severe eating disorder pathology and depressive mood had a higher likelihood of dropping out from a Web-based motivational enhancement program. Interventions such as ours need to address the specific needs of women with more severe eating disorder pathology and depressive mood and offer them additional support to prevent them from prematurely discontinuing treatment.
Multiple-group confirmatory factor analysis (MG-CFA) is among the most productive extensions of.structural equation modeling. Many researchers conducting cross-cultural or longitudinal studies are interested in testing for measurement and structural invariance. The aim of the present paper is to provide a tutorial in MG-CFA using the freely available R-packages lavaan, semTools, and semPlot. The combination of these packages enable a highly efficient analysis of the measurement models both for normally distributed as well as ordinal data. Data from two freely available datasets – the first with continuous the second with ordered indicators - will be used to provide a walk-through the individual steps.
Handovers need a common ground on the clinical cases between the members of the successive shifts to establish continuity of care. Conventional electronic patient record systems (EHR) proved to be only insufficiently suitable for supporting the grounding process. Against this background we proposed a basic concept for a handover EHR that extends general EHRs in particular openEHR based systems. The resulting handover information model was implemented in a database and evaluated based on 120 clinical cases. The information items of these cases could be mapped successfully to the model, however, the new class “anticipatory guidance” needed to be introduced. The evaluation also demonstrated the importance of highly aggregated information on the clinical case, opinions and meta-information such as the relevance of an item during handovers. Based on these findings, in particular the handover database, handover EHR applications are currently developed to support the grounding process.