Use of the child health utility and strengths and difficulties outcome measures in economic evaluations of school-based interventions: data from a cluster-randomised controlled trial in Northern Ireland

Background There is growing evidence linking early social and emotional wellbeing to later academic performance and various health outcomes including mental health. An economic evaluation was designed alongside the Roots of Empathy cluster-randomised trial evaluation, which is a school-based intervention for improving pupils’ social and emotional wellbeing. Exploration of the relevance of the Strengths and Diffi culties Questionnaire (SDQ) and Child Health Utility 9D (CHU9D) in school-based health economic evaluations is warranted. The SDQ is a behavioural screening questionnaire for 4–17-year-old children, consisting of a total diffi culties score, and also prosocial behaviour,
which aims to identify positive aspects of behaviour. The CHU9D is a generic preference-based health-related quality of life instrument for 7–17-year-old children.

Applying imagined contact to improve physiological responses in anticipation of intergroup interactions and the perceived quality of these interactions

This experiment (N 5 49) is the first to show that imagined contact can bufferanticipatory physiological responses to future interactions, and improve the qualityof these interactions. Participants imagined a positive interaction with a person withschizophrenia, or in a control condition, a person who did not have schizophrenia. They then interacted with a confederate whom they believed had schizophrenia. Participants in the imagined contact condition reported more positive attitudes andless avoidance of people with schizophrenia, displayed smaller anticipatory physio-logical responses, specifically smaller changes in interbeat interval and skin conduct-ance responses, and had a more positive interaction according to the confederate.These findings support applying imagined contact to improve interactions with people with severe mental illnesses.

Investigation of physiological properties of nerves and muscles using electromyography.

The measurement and representation of the electrical activity of muscles [electromyography (EMG)] have a long history from the Victorian Era until today. Currently, EMG has uses both as a research tool, in noninvasively recording muscle activation, and clinically in the diagnosis and assessment of nerve and muscle disease and injury as well as in assessing the recovery of neuromuscular function after nerve damage. In the present report, we describe the use of a basic EMG setup in our teaching laboratories to demonstrate some of these current applications. Our practical also illustrates some fundamental physiological and structural properties of nerves and muscles. Learning activities include 1) displaying the recruitment of muscle fibers with increasing force development; 2) the measurement of conduction velocity of motor nerves; 3) the assessment of reflex delay and demonstration of Jendrassik's maneuver; and 4) a Hoffman reflex experiment that illustrates the composition of mixed nerves and the differential excitability thresholds of fibers within the same nerve, thus aiding an understanding of the reflex nature of muscle control. We can set up the classes at various levels of inquiry depending on the needs/professional requirements of the class. The results can then provide an ideal platform for a discovery learning session/tutorial on how the central nervous system controls muscles, giving insights on how supraspinal control interacts with reflexes to give smooth, precise muscular activation.

A Characteristic Function Approach to Inconsistency Measures for Knowledge Bases.

Knowledge is an important component in many intelligent systems.
Since items of knowledge in a knowledge base can be conflicting, especially if
there are multiple sources contributing to the knowledge in this base, significant
research efforts have been made on developing inconsistency measures for
knowledge bases and on developing merging approaches. Most of these efforts
start with flat knowledge bases. However, in many real-world applications, items
of knowledge are not perceived with equal importance, rather, weights (which
can be used to indicate the importance or priority) are associated with items of
knowledge. Therefore, measuring the inconsistency of a knowledge base with
weighted formulae as well as their merging is an important but difficult task. In
this paper, we derive a numerical characteristic function from each knowledge
base with weighted formulae, based on the Dempster-Shafer theory of evidence.
Using these functions, we are able to measure the inconsistency of the knowledge
base in a convenient and rational way, and are able to merge multiple knowledge
bases with weighted formulae, even if knowledge in these bases may be
inconsistent. Furthermore, by examining whether multiple knowledge bases are
dependent or independent, they can be combined in different ways using their
characteristic functions, which cannot be handled (or at least have never been
considered) in classic knowledge based merging approaches in the literature.