Supporting clients to make positive changes in health behaviours using the transtheoretical model and motivational interviewing.

  • Published In: Mental Health Practice, 2025, v. 28, n. 1. P. 34 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: James, Philip; Reilly, Roisin 3 of 3

Abstract

Why you should read this article: • To recognise the importance of supporting people with mental health issues to make positive changes in health behaviours • To understand the main elements of the transtheoretical model and motivational interviewing, and how nurses can apply these to support behaviour change • 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). The Making Every Contact Count (MECC) framework seeks to use the daily contacts between healthcare staff and the public as opportunities to promote positive changes in people’s health. MECC focuses on four domains – healthy eating, physical activity, reducing alcohol consumption and smoking cessation – which can be challenging topics for mental health nurses to raise and discuss with clients. People with mental health issues are at increased risk of various physical health issues, therefore positive behaviour change interventions are an important part of mental health nursing practice. This article provides an overview of the transtheoretical model (stages of change) and motivational interviewing, explaining how nurses can use these in tandem to support clients to make positive changes in health behaviours. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Mental Health Practice. 2025/01, Vol. 28, Issue 1, p34
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:1465-8720
  • DOI:10.7748/mhp.2024.e1712
  • Accession Number:182122232
  • Copyright Statement:Copyright of Mental Health 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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