Attitudes of mental health professionals towards the use of coercion are highly relevant concerning its use coercion in mental healthcare, as mental health professionals have to weigh ethical arguments and decide within a legal frame in which situations to use coercion or not. Therefore, assessment of those attitudes is relevant for research in this field. A vital instrument to measure those attitudes towards the use of coercion is the Staff Attitude to Coercion Scale. This scoping review aims to provide a structured overview of the advantages and limitations in the assessment of attitudes toward coercion. We conducted a scoping review in Medline, PsycINFO, CINAHL, and Web of Science, based on the PRISMA-ScR. Inclusion criteria were empirical studies on the attitudes of mental health professionals. We included 80 studies and systematically mapped data about the main results and limitations in assessing attitudes toward coercion. The main results highlighted the relevance and increased interest in staff attitudes towards coercion in mental healthcare. Still, the majority of the included studies relied on a variety of different concepts and definitions concerning attitudes. The data further indicated difficulties in developing new and adapting existing assessment instruments because of the equivocal definitions of underlying concepts. To improve the research and knowledge in this area, future studies should be based on solid theoretical foundations. We identified the need for methodological changes and standardized procedures that take into account existing evidence from attitude research in social psychology, nursing science, and other relevant research fields. This would include an update of the Staff Attitude to Coercion Scale based on the limitations identified in this review.
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We developed an application which allows learners to construct qualitative representations of dynamic systems to aid them in learning subject content knowledge and system thinking skills simultaneously. Within this application, we implemented a lightweight support function which automatically generates help from a norm-representation to aid learners as they construct these qualitative representations. This support can be expected to improve learning. Using this function it is not necessary to define in advance possible errors that learners may make and the subsequent feedback. Also, no data from (previous) learners is required. Such a lightweight support function is ideal for situations where lessons are designed for a wide variety of topics for small groups of learners. Here, we report on the use and impact of this support function in two lessons: Star Formation and Neolithic Age. A total of 63 ninth-grade learners from secondary school participated. The study used a pretest/intervention/post-test design with two conditions (no support vs. support) for both lessons. Learners with access to the support create better representations, learn more subject content knowledge, and improve their system thinking skills. Learners use the support throughout the lessons, more often than they would use support from the teacher. We also found no evidence for misuse, i.e., 'gaming the system', of the support function.
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This article deals with automatic object recognition. The goal is that in a certain grey-level image, possibly containing many objects, a certain object can be recognized and localized, based upon its shape. The assumption is that this shape has no special characteristics on which a dedicated recognition algorithm can be based (e.g. if we know that the object is circular, we could use a Hough transform or if we know that it is the only object with grey level 90, we can simply use thresholding). Our starting point is an object with a random shape. The image in which the object is searched is called the Search Image. A well known technique for this is Template Matching, which is described first.
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