Background: Persons with profound intellectual and multiple disabilities (PIMD) are vulnerable when it comes to experiencing pain. Reliable assessment of pain-related behaviour in these persons is difficult. Aim To determine how pain items can be reliably scored in adults with PIMD.Methods: We developed an instruction protocol for the assessment of pain-related behaviour in four phases. We used videos of 57 adults with PIMD during potentially painful situations. The items were assessed for inter-rater reliability (Cohen's kappa or percentage of agreement).Results: The developed instruction protocol appeared to be adequate. Twelve items had satisfactory inter-rater reliability (n = 9: .30–1.00; n = 3: 85%–100%).Discussion: Calibrating and adjustments to the instructions and item set appeared to be crucial to reliably score 12 items in adults with PIMD. Further research should focus on creating an assessment instrument based on these reliably scored items.
Objectives: To investigate immediate changes in walking performance associated with three implicit motor learning strategies and to explore patient experiences of each strategy. Design: Participants were randomly allocated to one of three implicit motor learning strategies. Within-group comparisons of spatiotemporal parameters at baseline and post strategy were performed. Setting: Laboratory setting. Subjects: A total of 56 community-dwelling post-stroke individuals. Interventions: Implicit learning strategies were analogy instructions, environmental constraints and action observation. Different analogy instructions and environmental constraints were used to facilitate specific gait parameters. Within action observation, only videotaped gait was shown. Main measures: Spatiotemporal measures (speed, step length, step width, step height) were recorded using Vicon 3D motion analysis. Patient experiences were assessed by questionnaire. Results: At a group level, three of the four analogy instructions (n=19) led to small but significant changes in speed (d=0.088m/s), step height (affected side d=0.006m) and step width (d=–0.019m), and one environmental constraint (n=17) led to significant changes in step width (d=–0.040m). At an individual level, results showed wide variation in the magnitude of changes. Within action observation (n=20), no significant changes were found. Overall, participants found it easy to use the different strategies and experienced some changes in their walking performance. Conclusion: Analogy instructions and environmental constraints can lead to specific, immediate changes in the walking performance and were in general experienced as feasible by the participants. However, the response of an individual patient may vary quite considerably.
This quasi-experimental study examines the effect of short instruction videos on students’ business statistics learning. Two hundred and thirty-one Dutch students attended 6-week online seminars on Business Statistics. One hundred and nineteen students were in an experimental group, and 112 in a control group. Students in the experimental group watched short instructional videos and studied online quizzes at their own pace. In the control group, students followed teachers’ instructions throughout the seminars. It was found students watching short videos significantly outperformed those following teachers’ virtual instruction. Short videos were especially useful for those who were good at math. The research sheds light on the design of hybrid learning, particularly for business statistics education at the university level.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
