JOURNAL ARTICLE

Recognising and addressing loneliness and social isolation in older people.

  • Published In: Nursing Older People, 2025, v. 37, n. 3. P. 34 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Pimm, Emily 3 of 3

Abstract

Why you should read this article: • To understand why older people are particularly vulnerable to loneliness and social isolation • To improve your knowledge of interventions that can help to reduce the experiences of loneliness and social isolation for older people • To contribute towards revalidation as part of your 35 hours of CPD (UK readers) • To contribute towards your professional development and local registration renewal requirements (non-UK readers). Loneliness is widely recognised as a problematic issue in UK society. Older people are particularly vulnerable to loneliness and social isolation for various reasons, and the effects of these can be detrimental to their physical and mental health and well-being. Recognising the signs and symptoms associated with loneliness and social isolation is central to beginning the process of assessment and intervention. This article describes the concepts of loneliness and social isolation and explores their link to physical and mental health. The author also discusses some ways in which nurses can measure loneliness and provides some examples of interventions, such as health coaching and social prescribing, which can help to reduce the experiences of loneliness and social isolation in older people. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Nursing Older People. 2025/06, Vol. 37, Issue 3, p34
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:1472-0795
  • DOI:10.7748/nop.2025.e1490
  • Accession Number:185590662
  • Copyright Statement:Copyright of Nursing Older People 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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