A prospective longitudinal study of the impact of early postnatal vs. chronic maternal depressive symptoms on child development

Background Few studies of the effects of postnatal depression on child development have considered the chronicity of depressive symptoms. We investigated whether early postnatal depressive symptoms (PNDS) predicted child developmental outcome independently of later maternal depressive symptoms. Methods In a prospective, longitudinal study, mothers and children were followed-up from birth to 2 years; repeated measures of PNDS were made using the Edinburgh Postnatal Depression Scale (EPDS); child development was assessed using the Bayley Scales II. Multilevel modelling techniques were used to examine the association between 6 week PNDS, and child development, taking subsequent depressive symptoms into account. Results Children of mothers with 6 week PNDS were significantly more likely than children of non-symptomatic mothers to have poor cognitive outcome; however, this association was reduced to trend level when adjusted for later maternal depressive symptoms. Conclusion Effects of early PNDS on infant development may be partly explained by subsequent depressive symptoms.

Conceptualizing change in the Portuguese footwear industry: regional voices and cognitive spaces of agency

Expanding national services sectors and global competition aggravate current and perceived future market pressures on traditional manufacturing industries. These perceptions of change have provoked a growing intensification of geo-political discourses on technological innovation and ‘learning’, and calls for competency in design among other professional skills. However, these political discourses on innovation and learning have paralleled public concerns with the apparent ‘growth pains’ from factory closures and subsequent increases in unemployment, and its debilitating social and economic implications for local and regional development. In this respect the following investigation sets out to conceptualize change through the complementary and differing perceptions of industry and regional actors’ experiences or narratives, linking these perceptions to their structure-determined spheres of agent-environment interactivity. It aims to determine whether agents’ differing perceptions of industry transformation can have a role in the legitimization of their interests in, and in sustaining their organizational influence over the process of industry-regional transformation. It argues that industry and regional agent perceptions are among the cognitive aspects of agent-environment interactivity that permeate agency. It stresses agents’ ability to reason and manipulate their work environments to preserve their self-regulating interests in, and task representative influence over the multi-jurisdictional space of industry-regional transformation. The contributions of this investigation suggest that agents’ varied perceptions of industry and regional change inform or compete for influence over the redirection of regional, industry and business strategies. This claim offers a greater appreciation for the reflexive and complex institutional dimensions of industry planning and development, and the political responsibility to socially just forms of regional development. It positions the outcomes of this investigation at the nexus of intensifying geo-political discourses on the efficiency and equity of territorial development in Europe.

Assessment of cognitive symptoms in prodromal and early Huntington disease

The Functional Rating Scale Taskforce for pre-Huntington Disease (FuRST-pHD) is a multinational, multidisciplinary initiative with the goal of developing a data-driven, comprehensive, psychometrically sound, rating scale for assessing symptoms and functional ability in prodromal and early Huntington disease (HD) gene expansion carriers. The process involves input from numerous sources to identify relevant symptom domains, including HD individuals, caregivers, and experts from a variety of fields, as well as knowledge gained from the analysis of data from ongoing large-scale studies in HD using existing clinical scales. This is an iterative process in which an ongoing series of field tests in prodromal (prHD) and early HD individuals provides the team with data on which to make decisions regarding which questions should undergo further development or testing and which should be excluded. We report here the development and assessment of the first iteration of interview questions aimed to assess cognitive symptoms in prHD and early HD individuals.

Cognitive process modelling of controllers in en route air traffic control

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes.

Does training improve understanding of core concepts in cognitive behaviour therapy by people with intellectual disabilities? A randomized experiment

Background. People with intellectual disabilities (ID) experience similar or even higher rates of mental health problems than the general population and there is a need to develop appropriate treatments. Cognitive behaviour therapy (CBT) is effective for a wide range of disorders in the general population. However, there is some evidence that people with ID may lack the cognitive skills needed to take part in CBT. Aims. To test if people with ID can learn skills required for CBT, specifically the ability to distinguish between thoughts, feelings, and behaviours and to link thoughts and feelings (cognitive mediation). Method. A randomized independent groups design was used to examine the effect of training in CBT on two tasks measuring CBT skills. Thirty-four adults with ID were randomly allocated to the experimental condition ðN ¼ 18Þ or to the control condition ðN ¼ 16Þ. CBT skills were assessed blind at baseline and after the intervention. Results. The training led to significant improvements in participants’ ability to link thoughts and feelings, and this skill was generalized to new material. There was no effect of training on participants’ ability to distinguish amongst thoughts, feelings, and behaviours. People with ID can, therefore, learn some skills required for CBT. This implies that preparatory training for CBT might be useful for people with ID. The results might be applicable to other groups who find aspects of CBT difficult.

Skilloscopy: Bayesian modeling of decision makers' skill

This paper proposes and demonstrates an approach, Skilloscopy, to the assessment of decision makers. In an increasingly sophisticated, connected and information-rich world, decision making is becoming both more important and more difficult. At the same time, modelling decision-making on computers is becoming more feasible and of interest, partly because the information-input to those decisions is increasingly on record. The aims of Skilloscopy are to rate and rank decision makers in a domain relative to each other: the aims do not include an analysis of why a decision is wrong or suboptimal, nor the modelling of the underlying cognitive process of making the decisions. In the proposed method a decision-maker is characterised by a probability distribution of their competence in choosing among quantifiable alternatives. This probability distribution is derived by classic Bayesian inference from a combination of prior belief and the evidence of the decisions. Thus, decision-makers’ skills may be better compared, rated and ranked. The proposed method is applied and evaluated in the gamedomain of Chess. A large set of games by players across a broad range of the World Chess Federation (FIDE) Elo ratings has been used to infer the distribution of players’ rating directly from the moves they play rather than from game outcomes. Demonstration applications address questions frequently asked by the Chess community regarding the stability of the Elo rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The method of Skilloscopy may be applied in any decision domain where the value of the decision-options can be quantified.

Towards global drought early warning capability: expanding international cooperation for the development of a framework for global drought monitoring and forecasting

Drought is a global problem that has far-reaching impacts and especially 47 on vulnerable populations in developing regions. This paper highlights the need for a Global Drought Early Warning System (GDEWS), the elements that constitute its underlying framework (GDEWF) and the recent progress made towards its development. Many countries lack drought monitoring systems, as well as the capacity to respond via appropriate political, institutional and technological frameworks, and these have inhibited the development of integrated drought management plans or early warning systems. The GDEWS will provide a source of drought tools and products via the GDEWF for countries and regions to develop tailored drought early warning systems for their own users. A key goal of a GDEWS is to maximize the lead time for early warning, allowing drought managers and disaster coordinators more time to put mitigation measures in place to reduce the vulnerability to drought. To address this, the GDEWF will take both a top-down approach to provide global real-time drought monitoring and seasonal forecasting, and a bottom-up approach that builds upon existing national and regional systems to provide continental to global coverage. A number of challenges must be overcome, however, before a GDEWS can become a reality, including the lack of in-situ measurement networks and modest seasonal forecast skill in many regions, and the lack of infrastructure to translate data into useable information. A set of international partners, through a series of recent workshops and evolving collaborations, has made progress towards meeting these challenges and developing a global system.

Predicting long-term growth in students' mathematics achievement: the unique contributions of motivation and cognitive strategies

This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; Mage = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies.

Promoting mother–infant book sharing and infant attention and language development in an impoverished South African population: a pilot study

The low rates of child literacy in South Africa are cause for considerable concern. Research from the developed world shows that parental sharing of picture books with infants and young children is beneficial for child language and cognitive development, as well as literacy skills. We conducted a pilot study to examine whether such benefits might extend to an impoverished community in South Africa, by evaluating the impact of training mothers in book sharing with their 14–18 month old infants. Seventeen mothers received book sharing training; and 13 mothers did not, but instead received a comparison training in toy play. We assessed the mothers’ behavior during both book sharing and toy play before and after training, and we also assessed infant attention and language. Mothers receiving book sharing training engaged well with it, and they also benefited from it; thus, compared to the comparison group mothers, they became more sensitive, more facilitating, and more elaborative with their infants during book sharing, and they also became more sensitive to their infants during toy play. In addition, infants whose mothers received the book sharing training showed greater benefits than the comparison group infants in both their attention and language. Training in book sharing for families living in conditions of marked socio-economic adversity in South Africa has the potential to be of considerable benefit to child developmental progress. A large scale controlled trial is required to confirm this.

Effective interventions: 25 years outside the mainstream

25 years ago when the Durham conferences were in full swing, I presented results of investigations on language and behaviour in autism. I tentatively proposed that early language in autism might tell us about the cognitive skills of people with ASD and the behaviour might lead to greater understanding of which brain systems might be affected. In this presentation, I will update these topics and present a summary of other work I have been involved with in attempting to improve the lives of people with autism and their families. Data on three people with autism at the early stages of speech development showed an unusual pattern of learning colour and number names early. One possibility was that this skill represented a sign of weak central coherence – they only attended to one dimension. Colleagues of mine were equally puzzled so we tried to find out if my results could be replicated – they were not (see Schafer, Williams & Smith, 2014). Instead we found this pattern was also seen in Down Syndrome, but that early vocabulary in autism was associated with low Colorado Meaningfulness at least in comprehension. The Colorado Meaningfulness of a word is a measure of how many words can be associated with it and often involve extensive use of context. Our data suggest that the number of contexts in which a particular word can appear has a role in determining vocabulary in ASD which is consistent with the weak central coherence theory of autism. In the course of this work I also came across a group of young people with autism who appeared to have a written vocabulary but not a spoken one. It seems possible that print might be a medium of communication when speech is not. Repetitive behaviour in autism remains a mystery. We can use functional analysis to determine why the behaviour occurs, but a worryingly large percentage of behaviours are described as being internally driven or sensory reinforced. What does that mean in terms of brain activity – could it be system analogous to epilepsy, where brain activity becomes inappropriately synchronised? At the moment I cannot claim to have solved this problem, but if sensation is a driver then sensory interventions should make a difference. Data from a recent study will be presented to suggest that for some individuals this is the case. Social behaviour remains the key however, and it remains to be seen whether it is possible for social behaviour to be aided. One route that has potential is direct teaching of skills through drama and working with others who do not have social difficulties of the same type. The picture is complicated by changes in social skills with age and experience, but the failure of people with ASD to interact when in settings of social contact is little researched.

Language in genetic syndromes and cognitive modularity

In recent years, research into the impact of genetic abnormalities on cognitive development, including language, has become recognized for its potential to make valuable contributions to our understanding of the brain–behaviour relationships underlying language acquisition as well as to understanding the cognitive architecture of the human mind. The publication of Fodor’s ( 1983 ) book The Modularity of Mind has had a profound impact on the study of language and the cognitive architecture of the human mind. Its central claim is that many of the processes involved in comprehension are undertaken by special brain systems termed ‘modules’. This domain specificity of language or modularity has become a fundamental feature that differentiates competing theories and accounts of language acquisition (Fodor 1983 , 1985 ; Levy 1994 ; Karmiloff-Smith 1998 ). However, although the fact that the adult brain is modularized is hardly disputed, there are different views of how brain regions become specialized for specific functions. A question of some interest to theorists is whether the human brain is modularized from the outset (nativist view) or whether these distinct brain regions develop as a result of biological maturation and environmental input (neuroconstructivist view). One source of insight into these issues has been the study of developmental disorders, and in particular genetic syndromes, such as Williams syndrome (WS) and Down syndrome (DS). Because of their uneven profiles characterized by dissociations of different cognitive skills, these syndromes can help us address theoretically significant questions. Investigations into the linguistic and cognitive profiles of individuals with these genetic abnormalities have been used as evidence to advance theoretical views about innate modularity and the cognitive architecture of the human mind. The present chapter will be organized as follows. To begin, two different theoretical proposals in the modularity debate will be presented. Then studies of linguistic abilities in WS and in DS will be reviewed. Here, the emphasis will be mainly on WS due to the fact that theoretical debates have focused primarily on WS, there is a larger body of literature on WS, and DS subjects have typically been used for the purposes of comparison. Finally, the modularity debate will be revisited in light of the literature review of both WS and DS. Conclusions will be drawn regarding the contribution of these two genetic syndromes to the issue of cognitive modularity, and in particular innate modularity.

Cognitive and environmental factors influencing the process of spatial knowledge acquisition within virtual reality environments

As the fidelity of virtual environments (VE) continues to increase, the possibility of using them as training platforms is becoming increasingly realistic for a variety of application domains, including military and emergency personnel training. In the past, there was much debate on whether the acquisition and subsequent transfer of spatial knowledge from VEs to the real world is possible, or whether the differences in medium during training would essentially be an obstacle to truly learning geometric space. In this paper, the authors present various cognitive and environmental factors that not only contribute to this process, but also interact with each other to a certain degree, leading to a variable exposure time requirement in order for the process of spatial knowledge acquisition (SKA) to occur. The cognitive factors that the authors discuss include a variety of individual user differences such as: knowledge and experience; cognitive gender differences; aptitude and spatial orientation skill; and finally, cognitive styles. Environmental factors discussed include: Size, Spatial layout complexity and landmark distribution. It may seem obvious that since every individual's brain is unique - not only through experience, but also through genetic predisposition that a one size fits all approach to training would be illogical. Furthermore, considering that various cognitive differences may further emerge when a certain stimulus is present (e.g. complex environmental space), it would make even more sense to understand how these factors can impact spatial memory, and to try to adapt the training session by providing visual/auditory cues as well as by changing the exposure time requirements for each individual. The impact of this research domain is important to VE training in general, however within service and military domains, guaranteeing appropriate spatial training is critical in order to ensure that disorientation does not occur in a life or death scenario.

Probabilistic skill in ensemble seasonal forecasts

Simulation models are widely employed to make probability forecasts of future conditions on seasonal to annual lead times. Added value in such forecasts is reflected in the information they add, either to purely empirical statistical models or to simpler simulation models. An evaluation of seasonal probability forecasts from the Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction (DEMETER) and ENSEMBLES multi-model ensemble experiments is presented. Two particular regions are considered: Nino3.4 in the Pacific and the Main Development Region in the Atlantic; these regions were chosen before any spatial distribution of skill was examined. The ENSEMBLES models are found to have skill against the climatological distribution on seasonal time-scales. For models in ENSEMBLES that have a clearly defined predecessor model in DEMETER, the improvement from DEMETER to ENSEMBLES is discussed. Due to the long lead times of the forecasts and the evolution of observation technology, the forecast-outcome archive for seasonal forecast evaluation is small; arguably, evaluation data for seasonal forecasting will always be precious. Issues of information contamination from in-sample evaluation are discussed and impacts (both positive and negative) of variations in cross-validation protocol are demonstrated. Other difficulties due to the small forecast-outcome archive are identified. The claim that the multi-model ensemble provides a ‘better’ probability forecast than the best single model is examined and challenged. Significant forecast information beyond the climatological distribution is also demonstrated in a persistence probability forecast. The ENSEMBLES probability forecasts add significantly more information to empirical probability forecasts on seasonal time-scales than on decadal scales. Current operational forecasts might be enhanced by melding information from both simulation models and empirical models. Simulation models based on physical principles are sometimes expected, in principle, to outperform empirical models; direct comparison of their forecast skill provides information on progress toward that goal.