Factores determinantes na adesão parental ao tratamento oclusivo em crianças amblíopes

Introdução - Estudos de investigação recentes apontam para o facto de que cerca de 1/3 dos olhos amblíopes não chegam à acuidade visual de 5/10 apesar da terapia oclusiva. Uma das razões apontadas é a não adesão ao tratamento. O objectivo do presente estudo é contribuir para a determinação do grau de influência dos factores psicossociais na adesão à terapia oclusiva por parte dos pais de crianças amblíopes e avaliar se existem diferenças significativas entre as recomendações do Ortoptista, a percepção parental dessas mesmas recomendações e o comportamento descrito. Metodologia - Foi efectuado um estudo quantitativo transversal, no qual participaram pais de crianças amblíopes (n=100), a realizar tratamento oclusivo num hospital público e numa clínica privada em Lisboa. Os pais responderam a um questionário baseado na Teoria da Motivação e Protecção (TMP) de Rogers, no qual foram analisadas variáveis parentais como a gravidade, vulnerabilidade, auto-eficácia, intenções de comportamento, eficácia da resposta e barreiras ao tratamento. Adicionalmente, foram analisadas as variáveis percepção parental do número de horas de oclusão e comportamento parental descrito. Resultados - Os resultados apontam para uma percentagem de 72% de adesão parental ao tratamento oclusivo e uma percentagem de 28% de não adesão. As variáveis intenções de comportamento (p=O,Ol 5) e eficácia da resposta (p=O,Ol 1) demonstraram ser significativas na predição da adesão parental ao tratamento oclusivo em crianças amblíopes (a=0,05). Foi detectada uma correlação positiva moderada (kappa=0, 536) entre o número de horas de oclusão recomendado pelo Ortoptista e a percepção parental dessas mesmas recomendações e uma correlação positiva forte (kappa=0,700) entre o número de horas de oclusão percepcionadas e o comportamento descrito. Conclusões - A prévia noção por parte dos pais de que o tratamento é uma mais-valia com consequências benéficas, provoca o desenvolvimento de uma resposta adaptativa de coping, neste caso de adesão ao tratamento oclusivo. A intenção positiva dos pais para realizar o tratamento e a prévia noção da sua eficácia na melhoria da acuidade visual da criança são preditivas da adesão por parte destes. Nesse sentido a probabilidade da adesão ao tratamento será maior se os pais associarem a adopção do comportamento recomendado à melhoria do estado de saúde das crianças, o que de facto foi demonstrado por esta investigação.

Parental predictors of poor visual outcome with occlusion treatment for unilateral amblyopia

Aim: Visual acuity outcome of amblyopia treatment depends on the compliance. This study aimed to determine parental predictors of poor visual outcome with occlusion treatment in unilateral amblyopia and identify the relationship between occlusion recommendations and the patient's actual dose of occlusion reported by the parents. Methods: This study comprised three phases: refractive adaptation for a period of 18 weeks after spectacle correction; occlusion of 3 to 6 hours per day during a period of 6 months; questionnaire administration and completion by parents. Visual acuity as assessed using the Sheridan-Gardiner singles or Snellen acuity chart was used as a measure of visual outcome. Correlation analysis was used to describe the strength and direction of two variables: prescribed occlusion reported by the doctor and actual dose reported by parents. A logistic binary model was adjusted using the following variables: severity, vulnerability, self-efficacy, behaviour intentions, perceived efficacy and treatment barriers, parents' and childrens' age, and parents' level of education. Results: The study included 100 parents (mean age 38.9 years, SD approx 9.2) of 100 children (mean age 6.3 years, SD approx 2.4) with amblyopia. Twenty-eight percent of children had no improvement in visual acuity. The results showed a positive mild correlation (kappa = 0.54) between the prescribed occlusion and actual dose reported by parents. Three predictors for poor visual outcome with occlusion were identified: parents' level of education (OR = 9.28; 95%CI 1.32-65.41); treatment barriers (OR = 2.75; 95%CI 1.22-6.20); interaction between severity and vulnerability (OR = 3.64; 95%CI 1.21-10.93). Severity (OR = 0.07; 95%CI 0.00-0.72) and vulnerability (OR = 0.06; 95%CI 0.05-0.74) when considered in isolation were identified as protective factors. Conclusions: Parents frequently do not use the correct dosage of occlusion as recommended. Parents' educational level and awareness of treatment barriers were predictors of poor visual outcome. Lower levels of education represented a 9-times higher risk of having a poor visual outcome with occlusion treatment.

Low Complexity Intra Mode Selection for Efficient Distributed Video Coding

Motion compensated frame interpolation (MCFI) is one of the most efficient solutions to generate side information (SI) in the context of distributed video coding. However, it creates SI with rather significant motion compensated errors for some frame regions while rather small for some other regions depending on the video content. In this paper, a low complexity Infra mode selection algorithm is proposed to select the most 'critical' blocks in the WZ frame and help the decoder with some reliable data for those blocks. For each block, the novel coding mode selection algorithm estimates the encoding rate for the Intra based and WZ coding modes and determines the best coding mode while maintaining a low encoder complexity. The proposed solution is evaluated in terms of rate-distortion performance with improvements up to 1.2 dB regarding a WZ coding mode only solution.

Application of GIS-based multi-criteria analysis for site selection of aquifer recharge with reclaimed water

Reclaimed water from small wastewater treatment facilities in the rural areas of the Beira Interior region (Portugal) may constitute an alternative water source for aquifer recharge. A 21-month monitoring period in a constructed wetland treatment system has shown that 21,500 m(3) year(-1) of treated wastewater (reclaimed water) could be used for aquifer recharge. A GIS-based multi-criteria analysis was performed, combining ten thematic maps and economic, environmental and technical criteria, in order to produce a suitability map for the location of sites for reclaimed water infiltration. The areas chosen for aquifer recharge with infiltration basins are mainly composed of anthrosol with more than 1 m deep and fine sand texture, which allows an average infiltration velocity of up to 1 m d(-1). These characteristics will provide a final polishing treatment of the reclaimed water after infiltration (soil aquifer treatment (SAT)), suitable for the removal of the residual load (trace organics, nutrients, heavy metals and pathogens). The risk of groundwater contamination is low since the water table in the anthrosol areas ranges from 10 m to 50 m. Oil the other hand, these depths allow a guaranteed unsaturated area suitable for SAT. An area of 13,944 ha was selected for study, but only 1607 ha are suitable for reclaimed water infiltration. Approximately 1280 m(2) were considered enough to set up 4 infiltration basins to work in flooding and drying cycles.

Parental cognitive dimensions associated with preschool children’s eating habits: an intervention study

Childhood excessive weight and obesity are a major public health concern from early childhood. Early childhood is an important period of development for developing healthy eating habits, that may be associated with an adequate present/future BMI. There is extensive evidence that children’s food intake is shaped by early experiences, suggesting ways in which parenting practices may be promoting obesity. But what leads parents to endorse healthier or detrimental educational practices and routines needs further study. 1. Perception of children’s weight: parents of overweight or obese children often fail to correctly perceive their children as overweight; failing to recognize their children’s excessive weight may impeach parents from implementing the best educational practices. 2. Concern: relation between the adequacy of mothers perception of their children’s weight and the level of concern - parental concern is be associated with parental practices. 3. Attribution of control: also, if parents do not consider their children’s eating behavior at least partially controllable by them, they may relinquish some of their responsibility in this area. Self-efficacy: evidence linking parental self-efficacy to parent competence and to parenting practices and behaviors; low parental self-efficacy related to the control of everyday behavior of young children may lead parents to abandon more consistent health practices and endorse permissive and inconsistent strategies. We designed 2 sequential studies that aim to contribute to the understanding of cognitive determinants of children’s eating patterns.

What parental cognitive dimensions are important to understand children’s eating habits?

Obesidade é uma preocupação de saúde pública. Objetivos OMS - Redução a zero da taxa de crescimento da obesidade e uma redução em 10% na prevalência de atividade física insuficiente. Em Portugal, os estudos de prevalência apontam para valores entre 24% e os 34% de crianças e jovens pré-obesos e obesos. Extensa confirmação da obesidade infantil como preditor da obesidade na idade adulta. Em alguns países há indicadores de que a taxa de obesidade infantil começa a ter uma ligeira diminuição, provavelmente fruto de intervenções no macrosistema. Necessidade de intervenção direta nos microssistemas familiar e escolar da criança para uma intervenção mais abrangente e eficaz. Existe um ampla confirmação da influência parental nos comportamentos alimentares da criança. Os comportamentais parentais relacionados com a alimentação da criança são influenciados por variáveis cognitivas parentais. A maioria dos pais de crianças com excesso de peso subavalia o peso do seu filho, mas não de outras crianças. Os pais das crianças pré-escolares distorcem mais o peso do que os pais de crianças mais velhas. Os pais com uma perceção correta utilizam mais estratégias de restrição alimentar.

Promoção da auto-eficácia parental para a alimentação saudável infantil: áreas de intervenção

Barreiras parentais à alimentação saudável: 1) intrapessoais (relacionadas com a criança preferências alimentares; o estado de saúde; dificuldades de mudança de hábitos; relacionadas com os pais: baixo controlo; baixa auto-eficácia; stress parental); 2) interpessoais (comportamento da criança às refeições; estrutura da família; influências dos pares e de outros familiares; tempo disponível); 3) ambientais (escola; recursos financeiros; tempo disponível). Objetivos do estudo: identificação das barreiras percecionadas pelos pais a uma alimentação saudável da criança; identificar as estratégias de confronto que os pais utilizam para lidar com estas barreiras; identificar as diferenças das barreiras e estratégias utilizadas ao longo do desenvolvimento da criança; avaliar o grau de eficácia atribuído às estratégias utilizadas.

Por uma família participativa: estratégias e propostas de atividade para o envolvimento parental

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

O envolvimento parental: partilhar vivências e experiências

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion. © 2014 Springer-Verlag Berlin Heidelberg.

An unsupervised approach to feature discretization and selection

Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.