AAC Technologies with Visual Scene Displays and "Just in Time" Programming and Symbolic Communication Turns Expressed by Students with Severe Disability.

Background: The current study investigated the impact of an intervention that included aided augmentative and alternative communication (AAC) technologies on the frequency of symbolic communication turns of school-age children, adolescents, and young adults with severe disability.

Method: Nine students ages 8-20 were engaged in interactive activities using an aided AAC system with visual scene displays (VSDs; concepts embedded within a photograph of a naturally occurring event), and "just-in-time" (JIT) programming (the capability to add new contexts "on the fly"). Effectiveness was evaluated using a single subject multiple probe across participants design.

Statistics: general linear models (a flexible approach).

This article moves on to discuss a type of statistical testing different from those we have discussed previously, namely a General Linear Model. This system incorporates a number of other statistical models and is a powerful tool used widely in modern statistics.

Statistics: more regression models.

In a previous article, we tackled the question "How are we related?" for the simple case of one explanatory variable or covariate. Now we can move onto a natural extension, with still only one response variable, but more than one explanatory variable.

Statistics: using regression models.

In a previous article, we asked the simple question "Are we related?" and used scatterplots and correlation coefficients to provide an answer. In this article, we will take this question and reword it to "How are we related?" and will demonstrate the statistical techniques required to reach a conclusion.

Statistics: are we related?

This short addition to our series on clinical statistics concerns relationships, and answering questions such as "are blood pressure and weight related?" In a later article, we will answer the more interesting question about how they might be related. This article follows on logically from the previous one dealing with categorical data, the major difference being here that we will consider two continuous variables, which naturally leads to the use of a Pearson correlation or occasionally to a Spearman rank correlation coefficient.

Statistics: dealing with categorical data.

This, the fifth of our series of articles on statistics in veterinary medicine, moves onto modelling categorical data, in particular assessing associations between variables. Some of the questions we shall consider are widely discussed in many clinical research publications, and we will use the ideas of hypothesis tests and confidence intervals to answer those questions.

Statistics: how many?

The fourth in our series of articles on statistics for clinicians focuses on how we determine the appropriate number of subjects to include in an experimental study to provide sufficient statistical "power".

Statistics: more than pictures.

This, the third of our series of articles on statistics in veterinary medicine, moves onto the more complex concepts of hypothesis testing and confidence intervals. As these two areas are widely discussed in many clinical research publications, an awareness of the underlying methodology behind their use is essential to appreciate the information they convey.

Statistics: making sense of what we see.

Dealing with numerical results from a research study can be a daunting task for the non-statistician. This article highlights some of the ways in which such data can be expressed to facilitate subsequent analysis.

A statistics primer.

Statistical input into an experimental study is often not considered until the results have already been obtained. This is unfortunate, as inadequate statistical planning 'up front' may result in conclusions which are invalid. This review will consider some of the statistical considerations that are appropriate when planning a research study.

A transferable programme of nutritional counselling for rehabilitation following myocardial infarction: a randomised controlled study.

Objective: To evaluate the response to simple innovative dietary counselling in post myocardial infarction patients.

Design: Randomised controlled trial.

Setting: Cardiac rehabilitation programmes of two acute hospitals in Lanarkshire, Scotland.

Evaluation of a dietary targets monitor.

Objective: To evaluate a two-page food frequency list for use as a Dietary Targets Monitor in large scale surveys to quantify consumptions of the key foods groups targeted in health promotion.

Design: Intakes of fruit and vegetables, starchy foods and fish estimated from a validated food frequency questionnaire (FFQ) were compared with a short food frequency list (the Dietary Targets Monitor) specifically designed to assess habitual frequency of consumption of foods in relation to dietary targets which form the basis of a National (Scottish) Food and Health Policy.

Subjects: A total of 1085 adults aged 25-64 y from the Glasgow MONICA Study.

Weight change after myocardial infarction: statistical perspectives for future study.

Objectives: Survivors of acute myocardial infarction (MI) often experience weight changes and weight management is often appropriate. Estimates of the sample size required in intervention weight loss studies are essential to the success of future evaluations. The aims of this study were therefore two-fold: (1) to describe pilot data on the effectiveness of advice for weight loss; (2) to provide information on the sample size required for future research to assess weight management in similar patients.

The influences of height and age on waist circumference as an index of adiposity in adults.

Objectives: To assess the influences of height and age on the differences in waist circumference between individuals of different stature.

Subjects: 3319 males and 4358 females from four studies in the UK and the Netherlands.

Measurements: Waist circumference, body weight, height, and age.

The influence of fat free mass on prediction of densitometric body composition by bioelectrical impedance analysis and by anthropometry.

Objective: To examine the effect of varying size of fat free mass (FFM) on the precision and bias of body composition prediction by bioelectrical impedance analysis (BIA) from four equations of Segal et al (BIA-Segal), Gray et al (BIA-Gray, Lukaski et al (BIA-Lukaski) and those from a manufacturer (BIA-EZC), by body mass index (BMI), and by skinfold methods with reference to estimation by densitometry.

Subjects: 73 men and 77 women aged 17-71 years, were measured for height, weight, FFM, bioelectrical impedance and age.

Results: BIA-Segal gave the highest precision (men: R2 = 83%, women: R2 = 75%) and the least bias (men: slope = 0.