Harmful or helpful : perceived solicitous and facilitative partner responses are differentially associated with pain and sexual satisfaction in women with provoked vestibulodynia.

Introduction.  Provoked vestibulodynia (PVD) is a highly prevalent vulvovaginal pain condition that negatively affects women's emotional, sexual, and relationship well-being. Recent studies have investigated the role of interpersonal variables, including partner responses. Aim.  We examined whether solicitous and facilitative partner responses were differentially associated with vulvovaginal pain and sexual satisfaction in women with PVD by examining each predictor while controlling for the other. Methods.  One hundred twenty-one women (M age = 30.60, SD = 10.53) with PVD or self-reported symptoms of PVD completed the solicitous subscale of the spouse response scale of the Multidimensional Pain Inventory, and the facilitative subscale of the Spouse Response Inventory. Participants also completed measures of pain, sexual function, sexual satisfaction, trait anxiety, and avoidance of pain and sexual behaviors (referred to as “avoidance”). Main Outcome Measures.  Dependent measures were the (i) Pain Rating Index of the McGill Pain Questionnaire with reference to pain during vaginal intercourse and (ii) Global Measure of Sexual Satisfaction Scale. Results.  Controlling for trait anxiety and avoidance, higher solicitous partner responses were associated with higher vulvovaginal pain intensity (β = 0.20, P = 0.03), and higher facilitative partner responses were associated with lower pain intensity (β = −0.20, P = 0.04). Controlling for sexual function, trait anxiety, and avoidance, higher facilitative partner responses were associated with higher sexual satisfaction (β = 0.15, P = 0.05). Conclusions.  Findings suggest that facilitative partner responses may aid in alleviating vulvovaginal pain and improving sexual satisfaction, whereas solicitous partner responses may contribute to greater pain.

Woman and partner-perceived partner responses predict pain and sexual satisfaction in vestibulodynia couples

Introduction.  Provoked vestibulodynia (PVD) is a highly prevalent vulvovaginal pain condition that results in significant sexual dysfunction, psychological distress, and reduced quality of life. Although some intra-individual psychological factors have been associated with PVD, studies to date have neglected the interpersonal context of this condition. Aim.  We examined whether partner responses to women's pain experience—from the perspective of both the woman and her partner—are associated with pain intensity, sexual function, and sexual satisfaction. Methods.  One hundred ninety-one couples (M age for women = 33.28, standard deviation [SD] = 12.07, M age for men = 35.79, SD = 12.44) in which the woman suffered from PVD completed the spouse response scale of the Multidimensional Pain Inventory, assessing perceptions of partners' responses to the pain. Women with PVD also completed measures of pain, sexual function, sexual satisfaction, depression, and dyadic adjustment. Main Outcome Measures.  Dependent measures were women's responses to: (i) a horizontal analog scale assessing the intensity of their pain during intercourse; (ii) the Female Sexual Function Index; and (iii) the Global Measure of Sexual Satisfaction Scale. Results.  Controlling for depression, higher solicitous partner responses were associated with higher levels of women's vulvovaginal pain intensity. This association was significant for partner-perceived responses (β = 0.29, P < 0.001) and for woman-perceived partner responses (β = 0.16, P = 0.04). After controlling for sexual function and dyadic adjustment, woman-perceived greater solicitous partner responses (β = 0.16, P = 0.02) predicted greater sexual satisfaction. Partner-perceived responses did not predict women's sexual satisfaction. Partner responses were not associated with women's sexual function. Conclusions.  Findings support the integration of dyadic processes in the conceptualization and treatment of PVD by suggesting that partner responses to pain affect pain intensity and sexual satisfaction in affected women.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

Prediction of Key Symptoms of Learning Disabilities in School-Age Children Using Rough Sets

This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attributes consist of the properties of learning disabilities. By finding the relationship between these attributes, the redundant attributes can be eliminated and core attributes determined. Also, rule mining is performed in rough sets using the algorithm LEM1. The prediction of LD is accurately done by using Rosetta, the rough set tool kit for analysis of data. The result obtained from this study is compared with the output of a similar study conducted by us using Support Vector Machine (SVM) with Sequential Minimal Optimisation (SMO) algorithm. It is found that, using the concepts of reduct and global covering, we can easily predict the learning disabilities in children

Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.

Performance Improvement of Fuzzy and Neuro Fuzzy Systems: Prediction of Learning Disabilities in School-age Children

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.

Assembly Guidance in Augmented Reality Environments Using a Virtual Interactive Tool

The application of augmented reality (AR) technology for assembly guidance is a novel approach in the traditional manufacturing domain. In this paper, we propose an AR approach for assembly guidance using a virtual interactive tool that is intuitive and easy to use. The virtual interactive tool, termed the Virtual Interaction Panel (VirIP), involves two tasks: the design of the VirIPs and the real-time tracking of an interaction pen using a Restricted Coulomb Energy (RCE) neural network. The VirIP includes virtual buttons, which have meaningful assembly information that can be activated by an interaction pen during the assembly process. A visual assembly tree structure (VATS) is used for information management and assembly instructions retrieval in this AR environment. VATS is a hierarchical tree structure that can be easily maintained via a visual interface. This paper describes a typical scenario for assembly guidance using VirIP and VATS. The main characteristic of the proposed AR system is the intuitive way in which an assembly operator can easily step through a pre-defined assembly plan/sequence without the need of any sensor schemes or markers attached on the assembly components.

Sexual behavior in Spanish adolescents of divorced parents

Resumen tomado de la publicaci??n

Prevalence and predictors of sexual aggression in dating relationships of adolescents and young adults

Prevalencia y predictores de la agresi??n sexual en las relaciones de noviazgo en adolescentes y j??venes. Son muchos los estudios publicados que analizan las influencias di??dicas en las relaciones de noviazgo en adolescentes y j??venes adultos. El objetivo de este estudio consiste en aplicar el modelo di??dico de la agresi??n f??sica hacia las parejas a la agresi??n sexual contra las parejas. Se ha utilizado una muestra de 4.052 adolescentes y j??venes adultos de ambos sexos, con edades comprendidas entre los 16 y los 26 a??os. El porcentaje de hombres agresores es significativamente superior que el de mujeres (35,7 por ciento vs 14,9 por ciento), y el porcentaje de v??ctimas de agresi??n sexual fue superior para las mujeres (25,1 por ciento vs 21,7 por ciento). Los resultados muestran que tanto la agresi??n como la victimizaci??n sexual son fundamentalmente de naturaleza psicol??gica, como, por ejemplo, la utilizaci??n de t??cticas coercitivas de naturaleza verbal. Tal como predice el modelo di??dico de agresi??n f??sica en las relaciones de noviazgo, la victimizaci??n sexual se predice en funci??n de la agresi??n sexual de los individuos estudiados tanto en el caso de los hombres como en el de las mujeres.

Working memory in school-aged children: Exhibition intervals and distracters effects in Memonum computerized test

This study assessed visual working memory through Memonum computerized test in schoolchildren. The effects of three exposure times (1, 4 and 8 seconds) have been evaluated, and the presentation of a distractor on the mnemonic performance in the test Memonum in 72 children from a college in the metropolitan area of Bucaramanga, Colombia, aged between 8 and 11 in grades third, fourth and fifth grade. It has been found significant difference regarding the exposure time in the variables number of hits and successes accumulated, showing a better mnemonic performance in participants who took the test during 8 seconds compared to children who took the test during 1 second; in addition, the presence of a distractor showed a significant difference regarding the strengths and successes accumulated. Such distractor is considered a stimulus generator interference that disrupts the storage capacity of working memory in children. Additionally, a significant difference was found with respect to the use of mental rehearsal strategy, indicating that participants who took the test in 4 and 8 seconds, respectively, assigned higher scores than children who took the test in 1 second. A long exposure time to stimuli during Memonum test increases the holding capacity. Also, the use of a distractor affects the storage capacity and this, at the same time, increases the school progression due to the use of mnemonic strategies that children use to ensure the memory of the numerical series

Executive functions in school-aged children: age and socioeconomic status effects

Lately, the study of prefrontal executive functions in grade scholars has noticeably increased. The aim of this study is to investigate the influence of age and socioeconomic status (sEs) on executive tasks performance and to analyze those socioeconomic variables that predict a better execution. A sample of 254 children aged between 7 and 12 years from the city of santa Fe, Argentina and belonging to different socioeconomic status were tested. A bat- tery of executive functions sensitive to prefrontal function was used to obtain the results. These in- dicate a significant influence of age and SES on executive functions. The cognitive patterns follow a different path according to the development and sEs effect. Besides, it is revealed a pattern of low cognitive functioning in low-sEs children in all executive functions. Finally, from the variables included in this study, it was found that only the educational level of the mother and the housing conditions are associated to the children’s executive function. The results are discussed in terms of the influence of the cerebral maturation and the envi- ronmental variables in the executive functioning.

Feminist Debate around ‘Trafficking’ in Women for the Purpose of Sexual Exploitation in Prostitution

Women trafficking, as a widespread phenomenon, is a complex topic with manifold consequences which have a direct bearing on the way in which the problem of trafficking is understood by regulatory institutions and their proposed solutions. The governmental strategy must respond to this multidimensional phenomenon through state tools to counteract the effects of crime and recognize that women, men, children and adolescents may be indiscriminately vulnerable to this scourge. Nevertheless, we must recognize that, due to cultural facts, women and girls constitute the majority of its victims and specific actions are required for them.

Construcción y validación de un instrumento diagnóstico para la representación cognitiva de la Orientación Psicopedagógica en Galicia. 'Construction and validation of a diagnostic instrument for the cognitive representation of the Guidance in Galicia'.

Resumen tomado de la publicación. Con el apoyo económico del departamento MIDE de la UNED

La violencia en el ??mbito escolar = La violence dans l'??cole = Violence in School

Percepciones y preocupaciones del profesorado con respecto a la violencia en la Educaci??n Secundaria y a las posibilidades de la educaci??n para elaborar estrategias y alternativas v??lidas para educar en favor de la paz, la justicia y el desarrollo. 42 profesores de Educaci??n Secundaria, seleccionados en funci??n de: cobertura geogr??fica, disponibilidad y criterios de tipo pr??ctico. La investigaci??n se distribuy?? en cuatro fases, la primera de car??cter exploratorio y de inmersi??n en la comunidad, en la segunda se realiz?? una din??mica con un grupo de discusi??n formado por educadores con circunstancias personales, profesionales y acad??micas distintas, en la tercera la realizaci??n de entrevistas pretest y selecci??n de la muestra y en la cuarta la interpretaci??n y categorizaci??n de la informaci??n obtenida de las entrevistas. Investigaci??n cualitativa de car??cter cuasi-etnogr??fico. No se puede afirmar que se disponga de un paradigma conceptual capaz de interpretar la naturaleza del problema de la violencia escolar en todas sus dimensiones. Su estudio requiere de una reflexi??n profunda sobre el alcance del problema que ponga las bases para comprender su naturaleza y gu??e el camino de la intervenci??n educativa para prevenirla; para ello es necesario multiplicar los procesos de investigaci??n y de intervenci??n que permitan acceder, de forma democr??tica y no traum??tica a su comprensi??n y erradicaci??n.

The effect of nonlinear frequency compression and linear frequency transposition on speech perception in school-aged children

The primary objective of this study is to determine whether nonlinear frequency compression and linear transposition algorithms provide speech perception benefit in school-aged children.