The Warwick-Edinburgh Mental Well-Being Scale

Background There is increasing international interest in the concept of mental well-being and its contribution to all aspects of human life. Demand for instruments to monitor mental well-being at a population level and evaluate mental health promotion initiatives is growing. This article describes the development and validation of a new scale, comprised only of positively worded items relating to different aspects of positive mental health: the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). Methods WEMWBS was developed by an expert panel drawing on current academic literature, qualitative research with focus groups, and psychometric testing of an existing scale. It was validated on a student and representative population sample. Content validity was assessed by reviewing the frequency of complete responses and the distribution of responses to each item. Confirmatory factor analysis was used to test the hypothesis that the scale measured a single construct. Internal consistency was assessed using Cronbach’s alpha. Criterion validity was explored in terms of correlations between WEMWBS and other scales and by testing whether the scale discriminated between population groups in line with pre-specified hypotheses. Test-retest reliability was assessed at one week using intra-class correlation coefficients. Susceptibility to bias was measured using the Balanced Inventory of Desired Responding. Results WEMWBS showed good content validity. Confirmatory factor analysis supported the single factor hypothesis. A Cronbach’s alpha score of 0.89 (student sample) and 0.91 (population sample) suggests some item redundancy in the scale. WEMWBS showed high correlations with other mental health and well-being scales and lower correlations with scales measuring overall health. Its distribution was near normal and the scale did not show ceiling effects in a population sample. It discriminated between population groups in a way that is largely consistent with the results of other population surveys. Test–retest reliability at one week was high (0.83). Social desirability bias was lower or similar to that of other comparable scales. Conclusions WEMWBS is a measure of mental well-being focusing entirely on positive aspects of mental health. As a short and psychometrically robust scale, with no ceiling effects in a population sample, it offers promise as a tool for monitoring mental well-being at a population level. Whilst WEMWBS should appeal to those evaluating mental health promotion initiatives, it is important that the scale’s sensitivity to change is established before it is recommended in this context.

Investigating output accuracy for a discrete event simulation model and an agent based simulation model

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study. We had to determine an efficient implementation of management policy in the store’s fitting room using DES and ABS. Overall, we have found that both simulation models were a good representation of the real system when modelling human reactive behaviour.

Modelling and analysing cargo screening processes: a project outline

The efficiency of current cargo screening processes at sea and air ports is unknown as no benchmarks exists against which they could be measured. Some manufacturer benchmarks exist for individual sensors but we have not found any benchmarks that take a holistic view of the screening procedures assessing a combination of sensors and also taking operator variability into account. Just adding up resources and manpower used is not an effective way for assessing systems where human decision-making and operator compliance to rules play a vital role. For such systems more advanced assessment methods need to be used, taking into account that the cargo screening process is of a dynamic and stochastic nature. Our project aim is to develop a decision support tool (cargo-screening system simulator) that will map the right technology and manpower to the right commodity-threat combination in order to maximize detection rates. In this paper we present a project outline and highlight the research challenges we have identified so far. In addition we introduce our first case study, where we investigate the cargo screening process at the ferry port in Calais.