Promoting oral health in adults with learning disability

Introduction: It is complex to define learning disabilities, there is no single universal definition used; there are different interpretations and definitions used for learning disabilities in different countries and communities. Primarily, the term “learning disability” sometimes used as “learning difficulties” is a term widely used in UK. There are various types and degree of severity of learning disabilities depending upon the extent of disorder. Though different definitions used all over the world, its types and classification coupled with their health and oral health needs are discussed in this review. Objectives:  To review the background literature on definitions of learning disabilities and health needs of this population.  To review literature on individual clinical preventive intervention to determine the effectiveness in promoting oral health amongst adults in learning disabilities.  To review literature in relation to community based preventive dental measures.  To determine the interventions in this areas are appropriate to support policy and practice and if these interventions establish good evidence to suggest that the oral health needs of adults with learning disabilities are met or not.  To make recommendations in implementing future preventive oral health interventions for adults with learning disabilities. Methodology: It was develop a comprehensive narrative synthesis of previously published literature from different sources and summarizes the whole research in a particular area identifying gap of knowledge. It provides a broad perspective of a subject and supports continuing education. It also is directed to inform policy and further research. It is a qualitative type of research with a broad question and critical analysis of literature published in books, article and journals. The research question evaluated on PICOS criteria is: Effectiveness of preventive dental interventions in adults with learning disabilities. The research question clearly defines the PICOS i.e. participants, interventions, comparison, outcome and study design. The Cochrane database of systematic reviews (CDSR), Database of Abstracts of Reviews of effects (DARE) through York University and National institute of Health and Clinical Excellence (NICE) was searched to identify need of this review. There was no literature review found on the preventive dental interventions found hence, justifying this review. The guidance used in this review is from York University and methods opted for search of literature is based on the following: Type of participants, interventions, outcome measure, studies and search. The review of literature; author search; systematic and narrative reviews, through the following electronic databases via UFP library services: Pub-Med, Medline, EMBASE, CINHAL, Google scholar; Science Direct; Social and Medicine. A comprehensive search of all available literature from 1990-2015, including systematic reviews, policy documents and some guideline documents was done. Internet resource used to access; Department of Health, World Health Organization, Disability World, Disability Rights Commission, the Stationery office, MENCAP, Australian Learning Disability Association. The literature search was carried out with single word, combined words and phrases, authors' names and the title of literature search. Results: It is primarily looking at the oral health interventions available for adults with learning disabilities in clinical settings and the community measures observed over a period of 25 years 1990-2015. There were 7of the clinical intervention studies and one community based intervention study was added in this review. Conclusion: There is a gap of knowledge identified in not having ample research in the area of preventive dental interventions in adults with learning or intellectual disabilities and there is a need of more research, studies need to be of a better quality and a special consideration is required in the community settings where maintenance of oral hygiene for this vulnerable group of society is hugely dependent on their caregivers. Though, the policy and guideline directs on the preventive dental interventions of adults with LD there still a gap evident in understanding and implication of the guidance in practice by the dental and care support team. Understanding learning disabilities and to identify their behavior, compliance and oral health needs is paramount for all professionals working with or for them at each level.

Invisible disability, visible people: a closer look at the experiences of teachers with learning disabilities /

Throughout their schooling experiences, students with learning disabilities (LD) face numerous academic and socioemotional challenges. Some of these individuals rise above these obstacles to obtain a postsecondary education and become professionals. Recently, there have been a number of individuals with learning disabilities who have chosen a career in teaching. There is a lack of research that documents the experiences of teachers with learning disabilities. The purpose of this qualitative study is to gain an understanding of the challenges that the teachers with learning disabilities strive to overcome and the supports that they receive ^^^ch facilitate their inception into teaching. Four teachers with learning disabilities were the participants in this collective case study research. Data were collected through semistructured interviews. These data were coded, collapsed into themes, and the results were presented in a narrative form. The resultant 9 themes are: (a) Perspectives on School Experiences, (b) Identification and Effective Accommodations, (c) Isolation, Frustration, and Support, (d) Awareness of Learning Disability at Age 18, (e) Disclosure of Learning Disability, (f) Negative Impact of the Learning Disability Label, (g) Desire, Drive, and Obstacles, (h) Empathy, Compassion, and Self-Concept, and (i) Critical Views of Colleagues. The themes reflect the common experiences among participants. The discussion brings forth new information that is not found in other research. The impHcations of this research will interest teacher federations, parents of students with LD, teachers, and educational researchers.

The meaning of dependence and independence of older people with a disability in Ireland

The paper presents the findings of a research study carried out in Ireland in 2006 (Murphy et al., 2007) which explored the meaning of dependence and independence for older people with a disability. The research adopted a grounded theory approach; purposive sampling was used initially with some relational sampling towards the latter interviews. The sample was comprised of 143 older people with one of six disabilities: stroke (n=20), arthritis (20), depression (20), sensory disability (20), a learning disability (24), and dementia (18). All participants lived at home, some participants required high levels of help in activities of living while others were mostly independent. An interview schedule was used to guide interviews, all of which were tape recorded and transcribed. Data was collected on levels of dependence and independence using the Katz scale. Participants recorded high levels of independence in relation to transferring (93%), toileting (92%), dressing (87%), continence (87%) and feeding (98%). The main area of dependence where participants required assistance from others was with bathing (77%). The constant comparative technique was used to analyze qualitative data. The findings of the study would suggest that participants personal definition of their independence or dependence shifted relative to others and/or improvement or worsening of their capacity People were aware of the difference between independence and dependence, but these two concepts were not always perceived as opposites. It was possible to be independent and dependent at the same time. People valued being able to do things for themselves, accepted help when necessary but wanted to reciprocate when possible. Participants used varied coping strategies to regain and retain control of their lives. Strategies to promote older peoples independence and self esteem will be explored in this paper.

Learning Difficulties and Ethnicity

This framework is to help people and organisations (e.g. Learning Disability Partnership Boards) work towards ensuring that local services are culturally competent/appropriate.

Learning Disabilities and Health

This factsheet on learning disability has been compiled by the Department of Health South East. It highlights the health inequalities experienced by those with learning disabilities and summarises the main health-related issues. It details key publications such as 'Valuing People Now', which was launched in Jan-09, and provides information about strategies, resources and national drivers including Local Area Agreements. It can serve as a useful tool for PCTs, commissioners, those involved in service development, and those with a public health remit in order to improve practice and health outcomes among those with learning disability at both local and regional levels. For further information contact: Jonathan Campion (jonathan.campion@dh.gsi.gov.uk) or Jo Nurse (jo.nurse@dh.gsi.gov.uk)

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.

Significance Of Classification Techniques In Prediction Of Learning Disabilities

The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age children. LDs affect about 10 percent of all children enrolled in schools. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Decision trees and clustering are powerful and popular tools used for classification and prediction in Data mining. Different rules extracted from the decision tree are used for prediction of learning disabilities. Clustering is the assignment of a set of observations into subsets, called clusters, which are useful in finding the different signs and symptoms (attributes) present in the LD affected child. In this paper, J48 algorithm is used for constructing the decision tree and K-means algorithm is used for creating the clusters. By applying these classification techniques, LD in any child can be identified

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.

Attribute reduction and missing value imputing with ANN: prediction of learning disabilities

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned

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.

Auditory middle latency response and phonological awareness in students with learning disabilities

Introduction Behavioral tests of auditory processing have been applied in schools and highlight the association between phonological awareness abilities and auditory processing, confirming that low performance on phonological awareness tests may be due to low performance on auditory processing tests. Objective To characterize the auditory middle latency response and the phonological awareness tests and to investigate correlations between responses in a group of children with learning disorders. Methods The study included 25 students with learning disabilities. Phonological awareness and auditory middle latency response were tested with electrodes placed on the left and right hemispheres. The correlation between the measurements was performed using the Spearman rank correlation coefficient. Results There is some correlation between the tests, especially between the Pa component and syllabic awareness, where moderate negative correlation is observed. Conclusion In this study, when phonological awareness subtests were performed, specifically phonemic awareness, the students showed a low score for the age group, although for the objective examination, prolonged Pa latency in the contralateral via was observed. Negative weak to moderate correlation for Pa wave latency was observed, as was positive weak correlation for Na-Pa amplitude.

Dexamethasone aggravates hippocampal apoptosis and learning deficiency in pneumococcal meningitis in infant rats.

In an infant rat model of pneumococcal meningitis the effect of dexamethasone on neuronal injury in the hippocampus and on learning disability after recovery from the disease was examined. Treatment with dexamethasone or vehicle was started 18 h after infection, concomitant with antibiotics. Neuronal apoptosis in the hippocampal dentate gyrus 34 h after infection was significantly aggravated by dexamethasone treatment compared with vehicle controls (p = 0.02). Three weeks after acute pneumococcal meningitis, learning capacity of animals was assessed in the Morris water maze. The results showed a significantly impaired learning performance of infected animals treated with dexamethasone compared with vehicle controls (p = 0.01). Dexamethasone had no effect on hippocampal injury or learning in uninfected controls. Thus, dexamethasone as adjuvant therapy increased hippocampal cell injury and reduced learning capacity in this model of pneumococcal meningitis in infant rats.

Meeting in the middle: Improving communication in primary health care consultations with people with an intellectual disability

The increased presence and participation in Australian society of people with an intellectual disability provides challenges for the provision of primary health care. General practitioners (GPs) identify themselves as ill equipped to provide for this heterogeneous population. A major obstacle to the provision of appropriate health care is seen as inadequate communication between the GP and the person with an intellectual disability, who may or may not be accompanied by a carer or advocate. This qualitative study in which five GPs, three people with intellectual disability, seven carers and two advocates (parent and friend) were interviewed was conducted in Brisbane, Australia. The aim was to better understand the factors that have an impact upon the success of communication in a medical consultation. Findings suggested that GPs were concerned with the aspects of communication difficulties which influenced their ability to adequately diagnose, manage and inform patients. Implications for practice management were also identified. People with intellectual disability reported frustration when they felt that they could not communicate adequately with the GP and annoyance when they were not included in the communication exchange. Carers were strong advocates for the person with intellectual disability, but indicated insufficient skill and knowledge to provide the level of assistance required in the consultation. The outcome was a model of cooperation that outlined the responsibilities of all players in the medical encounter, prior to, during and after the event.