Breaking bad news to people with learning disabilities: barriers and tools.

  • Published In: Learning Disability Practice, 2023, v. 26, n. 6. P. 33 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Green, Joanne; Wilcox, Jo 3 of 3

Abstract

Why you should read this article: • To recognise the challenges in breaking bad news to people with learning disabilities • To consider various tools that you could use in your practice to break bad news • To count towards revalidation as part of your 35 hours of CPD, or you may wish to write a reflective account (UK readers) • To contribute towards your professional development and local registration renewal requirements (non-UK readers) Breaking bad news is a challenging aspect of healthcare professionals' roles in any setting. In learning disability settings, specific challenges compound the difficulty of this task. For example, a person who has cognitive difficulties may not understand an abstract concept such as death; the person's family may be concerned that hearing bad news will be too distressing for them; or the healthcare professional may be reluctant to talk about death because of their own beliefs and values. This article discusses the barriers related to breaking bad news to people with learning disabilities. It also describes several tools – generic and specific to the learning disability field – which healthcare professionals can use to inform and improve their practice in this area. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Learning Disability Practice. 2023/12, Vol. 26, Issue 6, p33
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2023
  • ISSN:1465-8712
  • DOI:10.7748/ldp.2023.e2208
  • Accession Number:174199608
  • Copyright Statement:Copyright of Learning Disability Practice is the property of Royal College of Nursing of the United Kingdom (The) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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