There is no evidence that learning a natural human language is cognitively harmful to children. To the contrary, multilingualism has been argued to be beneficial to all. Nevertheless, many professionals advise the parents of deaf children that their children should not learn a sign language during their early years, despite strong evidence across many research disciplines that sign languages are natural human languages. Their recommendations are based on a combination of misperceptions about (1) the difficulty of learning a sign language, (2) the effects of bilingualism, and particularly bimodalism, (3) the bona fide status of languages that lack a written form, (4) the effects of a sign language on acquiring literacy, (5) the ability of technologies to address the needs of deaf children and (6) the effects that use of a sign language will have on family cohesion. We expose these misperceptions as based in prejudice and urge institutions involved in educating professionals concerned with the healthcare, raising and educating of deaf children to include appropriate information about first language acquisition and the importance of a sign language for deaf children. We further urge such professionals to advise the parents of deaf children properly, which means to strongly advise the introduction of a sign language as soon as hearing loss is detected.
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http://dx.doi.org/10.1136/medethics-2015-103242 | DOI Listing |
BMC Public Health
January 2025
Social Determinants of Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran.
Background: Health Technology Assessment (HTA) is crucial for optimizing healthcare investments and improving system efficiency. In Iran, the rising costs of healthcare technologies and systemic inefficiencies have highlighted the need for a structured HTA framework. However, despite academic discussions, HTA has not yet been fully integrated into formal health policy.
View Article and Find Full Text PDFSci Rep
January 2025
University Institute of Computing, Chandigarh University, Punjab, India.
Automatic Sign Language Recognition Systems (ASLR) offers smooth communication between hearing-impaired and normal-hearing individuals, enhancing educational opportunities for impaired. However, it struggles with "curse of dimensionality" due to excessive features resulting in prolonged training time and exhaustive computational demand. This paper proposes technique that integrates machine learning and swarm intelligence to effectively address this issue.
View Article and Find Full Text PDFAfr J Disabil
December 2024
Department of Audiology, Faculty of Human and Community Development, University of the Witwatersrand, Braamfontein, South Africa.
Background: Parents of Deaf or hard-of-hearing (DHH) children are faced with a plethora of overwhelming decisions concerning their children, particularly during the early stages of development. Among these decisions are those concerning assistive devices and the modes of communication for their child.
Objectives: The aim of this study was to explore the perceptions of parents of DHH children towards the various modes of communication for their children within the South African context.
Ann Transl Med
December 2024
Division of Advanced Gastrointestinal and Bariatric Surgery, Mayo Clinic, Jacksonville, FL, USA.
Background: Addressing language barriers through accurate interpretation is crucial for providing quality care and establishing trust. While the ability of artificial intelligence (AI) to translate medical documentation has been studied, its role for patient-provider communication is less explored. This review evaluates AI's effectiveness in clinical translation by assessing accuracy, usability, satisfaction, and feedback on its use.
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