The assessment of mental health in children with intellectual disability

Aim: Individuals with intellectual disability (ID) have higher rates of mental health problems than the general population. Assessment tends to rely heavily on self-report, but persons with ID often have difficulties in identifying and describing their own thoughts and feelings. Measures that are psychometrically sound with typically developing populations may not be as robust in samples with ID. The aim of the current study was to examine a range of self-report measures for assessing the mental health of children with ID, and to consider the appropriateness of minor modifications to those instruments. Method: The participants were 58 children with ID (mean 11.7 years) attending Year 6 in mainstream primary schools. At the first time point they completed four established measures of depression, anxiety and mood. Minor modifications were made to wording and format at re-administration six months later. Results: Internal consistency varied considerably across measures. Modifications resulted in small or no improvements, but the results were relatively consistent over time and across similar measures. Some gender differences were evident. Conclusions: The findings confirm the difficulties that children with ID may have when responding to self-report measures of mental health, and suggest that care should be taken in choice of instruments. While modifications can produce small improvements, it is clear that more robust measures of mental health are needed for persons with ID.

Strategy use of children with Down syndrome in a delay of gratification situation

Background: The capacity to delay gratification has been shown to be a very important developmental task for children who are developing typically. There is evidence that children with Down syndrome have more difficulty with a delay of gratification task than typically developing children of the same mental age. This study focused on the strategies children with Down syndrome use while in a delay of gratification situation to ascertain if these contribute to the differences in delay times from those of typically developing children. Method: Thirty-two children with Down syndrome (15 females) and 50 typically developing children participated in the study. Children with Down syndrome had a mental age, as measured by the Stanford-Binet IV, between 36 and 66 months (M = 45.66). The typically developing children had a mean chronological age of 45.76 months. Children participated in a delay of gratification task where they were offered two or one small treats and asked which they preferred. They were then told that they could have the two treats if they waited for the researcher to return (an undisclosed time of 15 min). If they did not want to wait any longer they could call the researcher back but then they could have only one treat. Twenty-two of the children with Down syndrome and 43 of the typically developing children demonstrated understanding of the task and their data are included here. Sessions were videotaped for later analysis. Results: There were significant differences in the mean waiting times of the two groups. The mean of the waiting times for children with Down syndrome was 181.32 s (SD = 347.62) and was 440.21 s (SD = 377.59) for the typically developing children. Eighteen percent of the group with Down syndrome waited for the researcher to return in comparison to 35% of the typically developing group. Sixty-four percent of children with Down syndrome called the researcher back and the remainder (18%) violated. In the typically developing group 37% called the researcher back and 28% violated. The mean waiting time for the group of children with Down syndrome who called the researcher back was 24 s. Examination of strategy use in this group was therefore very limited. There appeared to be quite similar strategy use across the groups who waited the full 15 min. Conclusions: These results confirm the difficulty children with Down syndrome have in delaying gratification. Teaching strategies for waiting, using information drawn from the behaviours of children who are developing typically may be a useful undertaking. Examination of other contributors to delay ability (e.g., language skills) is also likely to be helpful in understanding the difficulties demonstrated in delaying gratification.

Four years on – are the Gazelles still running? A longitudinal study of firm performance after a period of rapid growth

Gazelles, or very rapidly growing firms, are important because they contribute disproportionately to economic growth. There is a concern that some of these firms pursue growth too aggressively resulting in lower subsequent performance. We investigate the relationship between growth and subsequent profitability for gazelle firms, and how this is moderated by firm strategy. Previous empirical research regarding the growth-profitability relationship for firms in general is rather inconclusive, with only one study specifically investigating gazelle firms. Likewise, there are theoretical arguments both for and against growth leading to profitability that equally apply to gazelle firms. Further, while contingency theory might suggest the relationship depends on the firm’s strategy, earlier studies have not investigated this relationship. We address these questions using longitudinal data (seven years) for a sample of 964 Danish Gazelle firms. Our study finds a clear positive relationship between growth and subsequent profitability among gazelle firms. Moreover, this relationship is stronger for firms pursuing a broad market strategy rather than a focus or niche strategy. An important managerial implication is that the growth strategy should be clearly integrated with the general strategic orientation of the firm.

Mixed-dimensional consistent coupling by multi-point constraint equations for efficient multi-scale modeling

Finding an appropriate linking method to connect different dimensional element types in a single finite element model is a key issue in the multi-scale modeling. This paper presents a mixed dimensional coupling method using multi-point constraint equations derived by equating the work done on either side of interface connecting beam elements and shell elements for constructing a finite element multiscale model. A typical steel truss frame structure is selected as case example and the reduced scale specimen of this truss section is then studied in the laboratory to measure its dynamic and static behavior in global truss and local welded details while the different analytical models are developed for numerical simulation. Comparison of dynamic and static response of the calculated results among different numerical models as well as the good agreement with those from experimental results indicates that the proposed multi-scale model is efficient and accurate.

Too sleepy to drive : self-perception and regulation of driving when sleepy

Background: Sleepiness is a direct contributor to a substantial proportion of fatal and severe road cashes. A number of technological solutions designed to detect sleepiness have been developed, but self-awareness of increasing sleepiness remains a critical component in on-road strategies for mitigating this risk. In order to take appropriate action when sleepy, drivers’ perceptions of their level of sleepiness must be accurate. Aims: This study aimed to assess capacity to accurately identify sleepiness and self-regulate driving cessation during a validated driving simulator task. Participants: Participants comprised 26 young adult drivers (20-28 years). The drivers had open licenses but no other exclusion criteria where used. Methods: Participants woke at 5am, and took part in a laboratory-based hazard perception driving simulation, either at mid-morning or mid-afternoon. Established physiological measures (including EEG) and subjective measures (sleepiness ratings) previously found sensitive to changes in sleepiness levels were utilised. Participants were instructed to ‘drive’ until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 39 minutes (±18 minutes). Almost all (23/26) of the participants then achieved sleep during the nap opportunity. These data suggest that the participants’ perceptions of sleepiness were specific. However, EEG data from a number of participants suggested very high levels of sleepiness prior to driving cessation, suggesting poor sensitivity. Conclusions: Participants reported high levels of sleepiness while driving after very moderate sleep restriction. They were able to identify increasing sleepiness during the test period, could decide to cease driving and in most cases were sufficiently sleepy to achieve sleep during the daytime session. However, the levels of sleepiness achieved prior to driving cessation suggest poor accuracy in self-perception and regulation. This presents practical issues for the implementation of fatigue and sleep-related strategies to improve driver safety.

Not a dirty word : arts entrepreneurship and higher education

While the majority of creative, performing, and literary artists are self-employed, relatively few tertiary arts schools attempt to develop capabilities for venture creation and management (and entrepreneurship more broadly) and still fewer do so effectively. This article asks why this is the case. It addresses underlying conceptual and philosophical issues encountered by arts educators, arguing that in all three senses of the term: new venture creation; career self-management; and being enterprising, entrepreneurship is essential to career success in the arts. However, the practice of entrepreneurship in the arts is significantly different from the practice of entrepreneurship in business, in terms of the artist’s drivers and aims, as well as the nature of entrepreneurial opportunities, contexts and processes. These differences mean that entrepreneurship curricula cannot simply be imported from Business schools. This article also examines the arts-idiosyncratic challenge of negotiating distinctive and potentially conflicting entrepreneurial aims, using career identity theory. It concludes by suggesting strategies by which adaptive entrepreneurial artist identities can be developed through higher education programs.

The utilization of waste date seed as bio-oil and activated carbon by pyrolysis process

The renovation of biomass waste in the form of date seed waste into activated carbon and biofuel by fixed bed pyrolysis reactor has been focused in this study to obtain gaseous, liquid, and solid products. The date seed in particle form is pyrolysed in an externally heated fixed bed reactor with nitrogen as the carrier gas. The reactor is heated from 400◦C to 600◦C. A maximum liquid yield of 50wt.% and char of 30wt.% are obtained at a reactor bed temperature of 500◦C with a running time of 120 minutes. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 28.636 MJ/kg which is significantly higher than other biomass derived. Decolonization of 85–97% is recorded for the textile effluent and 75–90% for the tannery effluent, in all cases decreasing with temperature increase. Good adsorption capacity of the prepared activated carbon in case of diluted textile and tannery effluent was found.

Fixed bed pyrolysis of date seed waste for liquid oil production

The conversion of biomass waste in the form of date seed into pyrolysis oil by fixed bed pyrolysis reactor has been taken into consideration in this study. A fixed bed pyrolysis has been designed and fabricated for obtaining liquid fuel from these date seeds. The major component of the system are fixed bed pyrolysis reactor, liquid condenser and liquid collector. The date seed in particle form is pyrolysed in an externally heated 7.6 cm diameter and 46 cm high fixed bed reactor with nitrogen as the carrier gas. The reactor is heated by means of a biomass source cylindrical heater from 4000C to 6000C. The products are oil, char and gas. The reactor bed temperature, running time and feed particle size are considered as process parameters. The parameters are found to influence the product yield significantly. A maximum liquid yield of 50 wt.% is obtained at a reactor bed temperature of 5000 C for a feed size volume of 0.11- 0.20 cm3 with a running time of 120 minutes. The pyrolysis oil obtained at this optimum process conditions are analyzed for some fuel properties and compared with some other biomass derived pyrolysis oils and also with conventional fuels. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 28.636 MJ/kg which is significantly higher than other biomass derived pyrolysis oils.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Estimating the effects of environmental exposures using a weighted mean of monitoring stations

The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.

Pyrolysis decomposition of mahogony seeds (Swietenia macrophylla) for alternative fuel oil

A fixed bed pyrolysis has been designed and fabricated for obtaining liquid fuel from Mahogany seeds. The major components of the system are fixed bed pyrolysis reactor, liquid condenser and liquid collectors. The Mahogany seed in particle form is pyrolysed in an externally heated 10 cm diameter and 36 cm high fixed bed reactor with nitrogen as the carrier gas. The reactor is heated by means of a biomass source cylindrical heater from 450oC to 600oC. The products are oil, char and gas. The reactor bed temperature, running time and feed particle size are considered as process parameters. A maximum liquid yield of 54wt% of biomass feed is obtained with particle size of 1.18 mm at a reactor bed temperature of 5500C with a running time of 90 minutes. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 39.9 MJ/kg which is higher than other biomass derived pyrolysis oils.