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Objective: To examine the use of the term ‘metric’ in health and social sciences’ literature, focusing on the interval scale implication of the term in Modern Test Theory (MTT).
Materials and methods: A systematic search and review on MTT studies including ‘metric’ or ‘interval scale’ was performed in the health and social sciences literature. The search was restricted to 2001–2005 and 2011–2015. A Text Mining algorithm was employed to operationalize the eligibility criteria and to explore the uses of ‘metric’. The paradigm of each included article (Rasch Measurement Theory (RMT), Item Response Theory (IRT) or both), as well as its type (Theoretical, Methodological, Teaching, Application, Miscellaneous) were determined. An inductive thematic analysis on the first three types was performed.
Results: 70.6% of the 1337 included articles were allocated to RMT, and 68.4% were application papers. Among the number of uses of ‘metric’, it was predominantly a synonym of ‘scale’; as adjective, it referred to measurement or quantification. Three incompatible themes ‘only RMT/all MTT/no MTT models can provide interval measures’ were identified, but ‘interval scale’ was considerably more mentioned in RMT than in IRT.
Conclusion: ‘Metric’ is used in many different ways, and there is no consensus on which MTT metric has interval scale properties. Nevertheless, when using the term ‘metric’, the authors should specify the level of the metric being used (ordinal, ordered, interval, ratio), and justify why according to them the metric is at that level.
The open and cooperative nature of Cyber-Physical Systems (CPS) poses new challenges in assuring dependability. The DEIS project (Dependability Engineering Innovation for automotive CPS. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732242, see http://www.deis-project.eu) addresses these challenges by developing technologies that form a science of dependable system integration. In the core of these technologies lies the concept of a Digital Dependability Identity (DDI) of a component or system. DDIs are modular, composable, and executable in the field facilitating (a) efficient synthesis of component and system dependability information over the supply chain and (b) effective evaluation of this information in-the-field for safe and secure composition of highly distributed and autonomous CPS. The paper outlines the DDI concept and opportunities for application in four industrial use cases.
BACKGROUND: Active performance is crucial for motor learning, and, together with motivation, is believed to be associated with a better rehabilitation outcome. Virtual reality (VR) is an innovative approach to engage and motivate patients during training. There is promising evidence for its efficiency in retraining upper limb function. However, there is insufficient proof for its effectiveness in gait training.
AIM: To evaluate the acceptability of robot-assisted gait training (RAGT) with and without VR and the feasibility of potential outcome measures to guide the planning of a larger randomized controlled trial (RCT).
DESIGN: Single-blind randomized controlled pilot trial with two parallel arms.
SETTING: Rehabilitation hospital.
POPULATION: Twenty subacute stroke patients (64±9 years) with a Functional Ambulation Classification (FAC) ≤2.
METHODS: Twelve sessions (over 4 weeks) of either VR-augmented RAGT (intervention group) or standard RAGT (control group). Acceptability of the interventions (drop-out rate, questionnaire), patients’ motivation (Intrinsic Motivation Inventory [IMI], individual mean walking time), and feasibility of potential outcome measures (completion rate and response to interventions) were determined.
RESULTS: We found high acceptability of repetitive VR-augmented RAGT. The drop-out rate was 1/11 in the intervention and 4/14 in the control group. Patients of the intervention group spent significantly more time walking in the robot than the control group (per session and total walking time; P<0.03). In both groups, motivation measured with the IMI was high over the entire intervention period. The felt pressure and tension significantly decreased in the intervention group (P<0.01) and was significantly lower than in the control group at the last therapy session (r=-0.66, P=0.005). The FAC is suggested as a potential primary outcome measure for a definitive RCT, as it could be assessed in all patients and showed significant response to interventions (P<0.01). We estimated a sample size of 44 for a future RCT.
CONCLUSIONS: VR-augmented RAGT resulted in high acceptability and motivation, and in a reduced drop-out rate and an extended training time compared to standard RAGT. This pilot trial provides guidance for a prospective RCT on the effectiveness of VR-augmented RAGT.
CLINICAL REHABILITATION IMPACT: VR might be a promising approach to enrich and improve gait rehabilitation after stroke.
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