Coping with a Learning Disability: A Case Study

The purpose of this qualitative case study was to understand a child���s experience with a learning disability (LD) through the way that they cope with it, and how self-esteem, self-efficacy, attribution style, and social support contribute to this process. Qualitative interviews were conducted with one child, his parents, and his teacher, accompanied by a content analysis of the child���s psychosocial assessment report. It was found that the child copes well with having a learning disability, employing a problem-focused/approach coping style by seeking help and practicing for skills he struggles with, an emotion-focused coping style by implementing strategies to alleviate frustration, and compartmentalizing his disability. Further, self-esteem, self-efficacy, attribution style, social support and sports and leisure engagement were found to contribute positively to the coping process. These findings offer useful implications for parents, teachers, and practitioners to support other students with LD.

Learning disability prediction tool using ANN and ANFIS

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 15 % of children enrolled in schools. The prediction of LD is a vital and intricate job. The aim of this paper is to design an effective and powerful tool, using the two intelligent methods viz., Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System, for measuring the percentage of LD that affected in school-age children. In this study, we are proposing some soft computing methods in data preprocessing for improving the accuracy of the tool as well as the classifier. The data preprocessing is performed through Principal Component Analysis for attribute reduction and closest fit algorithm is used for imputing missing values. The main idea in developing the LD prediction tool is not only to predict the LD present in children but also to measure its percentage along with its class like low or minor or major. The system is implemented in Mathworks Software MatLab 7.10. The results obtained from this study have illustrated that the designed prediction system or tool is capable of measuring the LD effectively

Does the Presence of a Learning Disability Elicit a Stigmatization?

Aims: To determine whether or not a Learning Disability(LD) label leads to stigmatization. Study Design: This research used a 2(sex of participant) x 2(LD label)x 2 (Sex of stimulus person) factorial design. Place and Duration of Study: Bucknell University, between October 2010 and April 2011. Methodology: Sample: We included 200 participants (137 women and 63 men, ranging in age from 18 – 75 years, M = 26.41. Participants rated the stimulus individual on 27 personality traits, 8 Life success measures, and the Big-5 personality dimensions. Also, participants completed a Social Desirability measure. Results: A MANOVA revealed a main effect for the Learning Disability description, F(6, 185) = 6.41 p< .0001, eta2 = .17,for the Big-5 personality dimensions, Emotional Stability, F(1, 185) = 13.39, p < .001, eta2 = .066, and Openness to Experiences F(1,185) = 7.12, p< .008, eta2 = .036.Stimulus individuals described as having a learning disability were perceived as being less emotionally stable and more open to experiences than those described as not having a learning disability. Another MANOVA revealed a main effect for having a disability or not, F(8, 183) = 4.29, p< .0001, eta2 = .158, for the Life Success items, Attractiveness, F(1, 198) = 16.63, p< .0001, eta2 = .080, and Future Success,F(1, 198) = 4.57, p< .034, eta2 = .023. Stimulus individuals described as having a learning disability were perceived as being less attractive and with less potential for success than those described as not having a learning disability. Conclusion: The results of this research provide evidence that a bias exists toward those who have learning disabilities. The mere presence of an LD label had the ability to cause a differential perception of those with LDs and those without LDs.

Identifying the Negative Stigma Associated with Having a Learning Disability

Those with learning disabilities (LDs) can be characterized as a minority group, and like most groups of minorities they face a distinct stigma by the larger population. While there iscurrently a lack of research in understanding LD stigma, it has become increasingly important given the push for inclusive classrooms settings. In this study it was hypothesized that regardlessof a participants’ gender, when participants were given a hypothetical description of a person that included information indicating that the individual has a LD, the participants would rate that individual less favorably. Results were consistent with the hypothesis. Participants perceived the hypothetical LD individual as being less attractive, less successful, less emotionally stable,and more open to new experiences when compared to those participants who were given the non-LD description. These results show a level of negative bias in our population towards those with LDs. It is hoped that this research will help address the goal of inclusion and equality for those with LDs and aid in finding ways to identify, address, and attenuate these stigmatizations within all aspects of our society.

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.

The Northern Ireland Action Plan for Learning Disability Nursing

The Northern Ireland Action Plan for Learning Disability Nursing

Learning Disability Service Framework (PDF 3MB)

Learning Disability Service Framework - Easy Access Version

Learning Disability Service Framework

Easy Access Version

RQIA Review of the implementation of Promoting Quality Care (PQC) Good Practice Guidance on the Assessment and Management of Risk in Mental Health and Learning Disability Services (PDF1.07MB)

Overview Report October 2012

Substance use behaviours of young people with a moderate learning disability: a longitudinal analysis.

Substance use behaviors of young people attending a special school are reported over a 4-year period from the age of 12-16 years. The article investigated these behaviors by surveying a cohort of young people with a statement for moderate learning disabilities annually during the last 4 years of compulsory schooling. The findings show that these young people consistently reported lower levels of tobacco, alcohol, and cannabis use compared with those attending mainstream school. No other illicit drug use was reported. The potential implications of these findings are discussed in relation to the context and timing of targeted substance education and prevention initiatives for young people with moderate learning disability attending a special school.This resource was contributed by The National Documentation Centre on Drug Use.

Regional Guidelines for the Search of Patients, their Belongings and the Environment of Care within Adult Mental Health and Learning Disability Inpatient Settings

The overarching purpose of these guidelines is to ensure the safety and promote the protection of patients, staff and visitors by ensuring that dangerous items or hazardous substances are not brought into the in-patient setting, including illicit substances, prescribed / over the counter medications, dangerous items and alcohol or any other hazardous or potentially hazardous item or substance.

Type 2 Diabetes for people with a Learning Disability

�� Pictorial information about type 2 diabetes for people with a learning disability.

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.