Het Studieloopbaanbegeleidingsinstrument Master Ecologische Pedagogiek (SLB-MEP) is een web-based zelfassessment voor (potentiële) studenten, dat de mate van overeenstemming tussen opleidingswaarden en studentvoorkeuren inventariseert. Het instrument biedt de mogelijkheid om de keuzeprocessen van studenten en de studieloopbaanbegeleiding op afstand te ondersteunen. Dit kan daarom ook voor initiële lerarenopleidingen van belang zijn. Het ontwikkelproces combineerde een gecontextualiseerde, kwalitatieve benadering met een kwantitatieve validatiestudie 1. Het bleek dat de betrouwbaarheid en validiteit voldoende zijn. Tevens zijn de gebruikerservaringen positief.
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STUDY OBJECTIVE: Endotracheal suctioning in intubated patients is routinely applied in most ICUs but may have negative side effects. We hypothesised that on-demand minimally invasive suctioning would have fewer side effects than routine deep endotracheal suctioning, and would be comparable in duration of intubation, length of stay in the ICU, and ICU mortality.DESIGN: Randomised prospective clinical trial.SETTING: In two ICUs at University Hospital Groningen, the Netherlands.PATIENTS: Three hundred and eighty-three patients requiring endotracheal intubation for more than 24 h.INTERVENTIONS: Routine endotracheal suctioning (n=197) using a 49-cm suction catheter was compared with on-demand minimally invasive airway suctioning (n=186) using a suction catheter only 29 cm long.MEASUREMENTS AND RESULTS: No differences were found between the routine endotracheal suctioning group and the minimally invasive airway suctioning group in duration of intubation [median (range) 4 (1-75) versus 5 (1-101) days], ICU-stay [median (range) 8 (1-133) versus 7 (1-221) days], ICU mortality (15% versus 17%), and incidence of pulmonary infections (14% versus 13%). Suction-related adverse events occurred more frequently with RES interventions than with MIAS interventions; decreased saturation: 2.7% versus 2.0% (P=0.010); increased systolic blood pressure 24.5% versus 16.8% (P<0.001); increased pulse pressure rate 1.4% versus 0.9% (P=0.007); blood in mucus 3.3% versus 0.9% (P<0.001).CONCLUSIONS: This study demonstrated that minimally invasive airway suctioning in intubated ICU-patients had fewer side effects than routine deep endotracheal suctioning, without being inferior in terms of duration on intubation, length of stay, and mortality.
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Background: The diffusion of telehealth into hospital care is still low, partially because of a lack of telehealth competence among nurses. In an earlier study, we reported on the knowledge, skills, and attitudes (KSAs) nurses require for the use of telehealth. The current study describes hospital nurses' confidence in possessing these telehealth KSAs. Method: In a cross-sectional study, we invited 3,543 nurses from three hospitals in the Netherlands to rate their self-confidence in 31 telehealth KSAs on a 5-point Likert scale, using an online questionnaire. Results: A total of 1,017 nurses responded to the survey. Nine KSAs were scored with a median value of 4.0, 19 KSAs with a median value of 3.0, and three KSAs with a median value of 2.0. Conclusion: Given that hospital nurses have self-confidence in only nine of the 31 essential telehealth KSAs, continuing education in additional KSAs is recommended to support nurses in gaining confidence in using telehealth.
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Theme: Quality Assurance in Higher Education An online tool was developed for (potential) students to assess the congruence between the characteristics of an educational program and student preferences (Butter & Van Raalten, 2010)
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This pilot study explores the possibility of cognitive training software Neurotracker (NT), to have potential beneficial effects for Traumatic Brain Injury patients with Sensory Processing Disorder. Five subjects with TBI and SPD trained for 5 weeks/21 sessions with Neurotracker. Pre-post training cognitive tests (WAIS TMTA, TMTB, LNS) and surveys were conducted to measure possible cognitive differences with no statistical significant results. However, significant improvement in Neurotracker scores were found. =2.73, SD = 0.55) and positive changes associated with attention attention span, divided attention, (multiple) object tracking and motion sickness. LinkedIn: https://www.linkedin.com/in/bernard-de-roosz-28b96b125/
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Completeness of data is vital for the decision making and forecasting on Building Management Systems (BMS) as missing data can result in biased decision making down the line. This study creates a guideline for imputing the gaps in BMS datasets by comparing four methods: K Nearest Neighbour algorithm (KNN), Recurrent Neural Network (RNN), Hot Deck (HD) and Last Observation Carried Forward (LOCF). The guideline contains the best method per gap size and scales of measurement. The four selected methods are from various backgrounds and are tested on a real BMS and meteorological dataset. The focus of this paper is not to impute every cell as accurately as possible but to impute trends back into the missing data. The performance is characterised by a set of criteria in order to allow the user to choose the imputation method best suited for its needs. The criteria are: Variance Error (VE) and Root Mean Squared Error (RMSE). VE has been given more weight as its ability to evaluate the imputed trend is better than RMSE. From preliminary results, it was concluded that the best K‐values for KNN are 5 for the smallest gap and 100 for the larger gaps. Using a genetic algorithm the best RNN architecture for the purpose of this paper was determined to be Gated Recurrent Units (GRU). The comparison was performed using a different training dataset than the imputation dataset. The results show no consistent link between the difference in Kurtosis or Skewness and imputation performance. The results of the experiment concluded that RNN is best for interval data and HD is best for both nominal and ratio data. There was no single method that was best for all gap sizes as it was dependent on the data to be imputed.
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Completeness of data is vital for the decision making and forecasting on Building Management Systems (BMS) as missing data can result in biased decision making down the line. This study creates a guideline for imputing the gaps in BMS datasets by comparing four methods: K Nearest Neighbour algorithm (KNN), Recurrent Neural Network (RNN), Hot Deck (HD) and Last Observation Carried Forward (LOCF). The guideline contains the best method per gap size and scales of measurement. The four selected methods are from various backgrounds and are tested on a real BMS and metereological dataset. The focus of this paper is not to impute every cell as accurately as possible but to impute trends back into the missing data. The performance is characterised by a set of criteria in order to allow the user to choose the imputation method best suited for its needs. The criteria are: Variance Error (VE) and Root Mean Squared Error (RMSE). VE has been given more weight as its ability to evaluate the imputed trend is better than RMSE. From preliminary results, it was concluded that the best K‐values for KNN are 5 for the smallest gap and 100 for the larger gaps. Using a genetic algorithm the best RNN architecture for the purpose of this paper was determined to be GatedRecurrent Units (GRU). The comparison was performed using a different training dataset than the imputation dataset. The results show no consistent link between the difference in Kurtosis or Skewness and imputation performance. The results of the experiment concluded that RNN is best for interval data and HD is best for both nominal and ratio data. There was no single method that was best for all gap sizes as it was dependent on the data to be imputed.
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Background: Non-technical errors, such as insufficient communication or leadership, are a major cause of medical failures during trauma resuscitation. Research on staffing variation among trauma teams on teamwork is still in their infancy. In this study, the extent of variation in trauma team staffing was assessed. Our hypothesis was that there would be a high variation in trauma team staffing. Methods: Trauma team composition of consecutive resuscitations of injured patients were evaluated using videos. All trauma team members that where part of a trauma team during a trauma resuscitation were identified and classified during a one-week period. Other outcomes were number of unique team members, number of new team members following the previous resuscitation and new team members following the previous resuscitation in the same shift (Day, Evening, Night). Results: All thirty-two analyzed resuscitations had a unique trauma team composition and 101 unique members were involved. A mean of 5.71 (SD 2.57) new members in teams of consecutive trauma resuscitations was found, which was two-third of the trauma team. Mean team members present during trauma resuscitation was 8.38 (SD 1.43). Most variation in staffing was among nurses (32 unique members), radiology technicians (22 unique members) and anesthetists (19 unique members). The least variation was among trauma surgeons (3 unique members) and ER physicians (3 unique members). Conclusion: We found an extremely high variation in trauma team staffing during thirty-two consecutive resuscitations at our level one trauma center which is incorporated in an academic teaching hospital. Further research is required to explore and prevent potential negative effects of staffing variation in trauma teams on teamwork, processes and patient related outcomes.
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Background Objective gait analysis that fully captures the multi-segmental foot movement of a clubfoot may help in early identification of a relapse clubfoot. Unfortunately, this type of objective measure is still lacking in a clinical setting and it is unknown how it relates to clinical assessment. Research question The aim of this study was to identify differences in total gait and foot deviations between clubfoot patients with and without a relapse clubfoot and to evaluate their relationship with clinical status. Methods In this study, Ponseti-treated idiopathic clubfoot patients were included and divided into clubfoot patients with and without a relapse. Objective gait analysis was done resulting in total gait and foot scores and clinical assessment was performed using the Clubfoot Assessment Protocol (CAP). Additionally, a new clubfoot specific foot score, the clubFoot Deviation Index (cFDI*), was calculated to better capture foot kinematics of clubfoot patients. Results Clubfoot patients with a relapse show lower total gait quality (GDI*) and lower clinical status defined by the CAP than clubfoot patients without a relapse. Abnormal cFDI* was found in relapse patients, reflected by differences in corresponding variable scores. Moderate relationships were found for the subdomains of the CAP and total gait and foot quality in all clubfoot patients. Significance A new total foot score was introduced in this study, which was more relevant for the clubfoot population. The use of this new foot score (cFDI*) besides the GDI*, is recommended to identify gait and foot motion deviations. Along with clinical assessment, this will give an overview of the overall status of the complex, multi-segmental aspects of a (relapsed) clubfoot. The relationships found in this study suggest that clinical assessment might be indicative of a deviation in total gait and foot pattern, therefore hinting towards personalised screening for better treatment decision making.
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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.
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