Damon Berridge

A population-based investigation of behavioural and emotional problems and maternal mental health: associations with autism spectrum disorder and intellectual disability

BACKGROUND While research indicates elevated behavioural and emotional problems in children with autism spectrum disorders (ASD) and decreased well-being in their parents, studies do not typically separate out the contribution of ASD from that of associated intellectual disabilities (ID). We investigated child behavioural and emotional problems, and maternal mental health, among cases with and without ASD and ID in a large population-representative sample. METHODS Cross-sectional comparison of child behavioural and emotional problems and maternal mental health measures among 18,415 children (5 to 16 years old), of whom 47 had an ASD, 51 combined ASD with ID, 590 had only ID, and the remainder were the comparison group with no ASD or ID. RESULTS The prevalence of likely clinical levels of behavioural and emotional problems was highest among children with ASD (with and without ID). After controlling for age, gender, adversity, and maternal mental health, the presence of ASD and ID significantly and independently increased the odds for hyperactivity symptoms, conduct, and emotional problems. Emotional disorder was more prevalent in mothers of children with ASD (with or without ID). The presence of ASD, but not ID, significantly increased the odds for maternal emotional disorder. As has been found in previous research, positive maternal mental health was not affected by the presence of ASD or ID. CONCLUSIONS ASD and ID are independent risk factors for behavioural and emotional problems. ASD (but not ID) is positively associated with maternal emotional disorder. Approaches to diagnosing hyperactivity and conduct problems in children with ASD may need to be reconsidered.

Young People's Entry into Higher Education: Quantifying influential factors

The government has recently raised the issue of differential rates of participation in higher education. The overall aim of this paper is to present an example of the kind of detailed research necessary to identify factors associated with low rates of participation in higher education by some groups of young people. A number of studies have suggested that in addition to educational attainment, issues such as social class, gender and parental education also influence a young persons likelihood of entering higher education. In this paper we undertake exploratory analysis of a series of nationally representative data and through statistical modelling we then identify the factors that influence a young persons chances of entry into higher education and participating on a degree level course. Through sample enumeration, an innovative statistical methodology, we were then able to quantify the substantive effects of these factors. We found that net of educational attainment a number of factors (e.g. gender and social background variables) influence the likelihood of a young person entering higher education and participating on a degree level course. In addition our analysis highlights the interwoven effects of parental education and schooling and we discuss the complex nature of the effects of ethnicity.

Poverty transitions among families supporting a child with intellectual disability

Abstract Background Little is known about child disability and dynamic aspects of poverty. Method Analysis of data collected over a 12-month period for families (a) supporting a child with intellectual disability (n = 370), (b) supporting a child with other disability (n = 1,418), and (c) supporting a child with no disability (n = 7,215). Results When compared to families not supporting a child with disability, families supporting a child with intellectual disability were (a) more likely to be poor, (b) more likely to become poor, (c) less likely to escape from being poor. Half of poverty transitions were associated with identifiable potential trigger events. Conclusions There were few differences between families supporting or not supporting a child with disability with regard to either levels of exposure to potential trigger events or to the strength of the association between exposure and poverty transitions.

Is there a bidirectional relationship between maternal well-being and child behavior problems in autism spectrum disorders? Longitudinal analysis of a population-defined sample of young children.

The aim of this study was to examine whether the relationship between maternal psychological well‐being and behavior problems in children with an autism spectrum disorder (ASD) is bidirectional. Data were available at 9 months, 3 years, and 5 years old for 132 children with ASD, identified from a population‐representative sample of UK children. Three‐wave cross‐lagged models examined reciprocal effects between child behavior and maternal well‐being (psychological distress, physical health functioning, and life satisfaction). Results indicated that the relationships between maternal well‐being and child problem behaviors were not bidirectional. Specifically, findings suggested that while early behavior problems are not a risk factor for later maternal well‐being, maternal psychological distress, physical health limitations, and lower life satisfaction are risk factors for later child behavior problems. Autism Res 2013, 6: 201–211.

Child Disability and the Dynamics of Family Poverty, Hardship and Financial Strain: Evidence from the UK

Disabled children are significantly more likely to grow up in poverty than their non-disabled peers. We used longitudinal data from Waves 3–7 (2001–2005) of the UK Families and Children Study to explore the relationship between the presence of a disabled child in the family and poverty transitions. When compared to other families, families supporting a disabled child are more likely to be exposed to persistent or recurrent poverty, less likely to escape from an episode of poverty and more likely to descend into poverty. However, statistically controlling for the effects of salient family characteristics either attenuates, eliminates or reverses these associations. That is, when compared to other families with similar levels of personal and social resources, families supporting a disabled child are no more likely to escape from or descend into poverty than other families. Results are discussed in relation to the need for social policy to invest in strengthening the broader capabilities of families of disabled children.

Fitting a random effects model to ordinal recurrent events using existing software

The continuation ratio model is a direct generalisation of the more familiar binary logistic model. In this paper, it is proposed to model ordinal recurrent events by generalising the logistic-normal model for binary recurrent events in a similar manner. This new model is implemented in the statistical software package SABRE.

Changing Attitudes to Gender Roles A Longitudinal Analysis of Ordinal Response Data from the British Household Panel Study

This article examines changes in attitudes to gender roles in contemporary Britain by using a first-order Markov process in which cumulative transition probabilities are logistic functions of a set of personal and socioeconomic characteristics of respondents. The data are taken from the British Household Panel Study (BHPS). The attitudinal responses examined take the form of ordinal responses concerning gender roles in 1991 and 2003. The likelihood function is partitioned to make possible the use of existing software for estimating model parameters. For the BHPS data, it was found that, depending on the value of the response in 1991, a variety of factors were important determinants of attitudes to gender roles by 2003.

Predictors of early numeracy : Is there a place for mistakes when learning about number?

It is one thing to be able to count and share items proficiently, but it is another thing to know how counting and sharing establish and identify quantity. The aim of the study was to identify which measures of numerical knowledge predict childrens success on simple number problems, where counting and set equivalence are at issue. Seventy-two 5-year-olds were given a battery of nine tasks on each of three sessions (at 3-monthly intervals). Tasks measured procedural proficiency, conceptual understanding (using an error-detection paradigm) and the ability to compare sets using number knowledge. Procedural skills remained fairly stable over the 6-month period, and preceded childrens ability to detect anothers violations to those procedures. Regression analysis revealed that children who are sensitive to procedural errors in anothers counting and sharing are more likely to recognize the significance of cardinal numbers for set comparisons. We suggest that although childrens conceptual understanding of well-rehearsed routines is often limited, conceptual insight might be achieved by setting tasks that require reflection rather than practice.

Robust joint modeling of longitudinal measurements and time to event data using normal/independent distributions: A Bayesian approach

Joint modeling of longitudinal data and survival data has been used widely for analyzing AIDS clinical trials, where a biological marker such as CD4 count measurement can be an important predictor of survival. In most of these studies, a normal distribution is used for modeling longitudinal responses, which leads to vulnerable inference in the presence of outliers in longitudinal measurements. Powerful distributions for robust analysis are normal/independent distributions, which include univariate and multivariate versions of the Students t, the slash and the contaminated normal distributions in addition to the normal. In this paper, a linear-mixed effects model with normal/independent distribution for both random effects and residuals and Coxs model for survival time are used. For estimation, a Bayesian approach using Markov Chain Monte Carlo is adopted. Some simulation studies are performed for illustration of the proposed method. Also, the method is illustrated on a real AIDS data set and the best model is selected using some criteria.

Joint modeling of multivariate longitudinal mixed measurements and time to event data using a Bayesian approach

In many longitudinal studies multiple characteristics of each individual, along with time to occurrence of an event of interest, are often collected. In such data set, some of the correlated characteristics may be discrete and some of them may be continuous. In this paper, a joint model for analysing multivariate longitudinal data comprising mixed continuous and ordinal responses and a time to event variable is proposed. We model the association structure between longitudinal mixed data and time to event data using a multivariate zero-mean Gaussian process. For modeling discrete ordinal data we assume a continuous latent variable follows the logistic distribution and for continuous data a Gaussian mixed effects model is used. For the event time variable, an accelerated failure time model is considered under different distributional assumptions. For parameter estimation, a Bayesian approach using Markov Chain Monte Carlo is adopted. The performance of the proposed methods is illustrated using some simulation studies. A real data set is also analyzed, where different model structures are used. Model comparison is performed using a variety of statistical criteria.