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Research Exploring Traditional and Complementary Medicine Use in Malaysia: A Scoping Review.

  • Published In: Malaysian Journal of Medicine & Health Sciences, 2025, v. 21, n. 4. P. 337 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Lee, E. Lyn; Wei En Goo; Pei Se Wong; Barnes, Joanne 3 of 3

Abstract

Traditional and complementary medicine (T&CM) encompasses a broad spectrum of health practices and products outside conventional medicine. Many Malaysians use T&CM, but research on its prevalence and patterns of use in Malaysia is limited. This study aims to chart the landscape of published research on T&CM use in Malaysia and outline key focus areas. A systematic literature search in MEDLINE, EMBASE, CINAHL, and Scopus databases up to April 25, 2023, identified 153 relevant studies. Most studies lacked an operational definition for T&CM, leading to ambiguity regarding their scope and limiting cross-study comparisons. Research predominantly focused on sub-populations in Kuala Lumpur and Selangor, with few nationwide studies. Studies found substantial T&CM use and highlighted consumer knowledge, attitudes, and perceptions towards T&CM. Consumers spend substantial amounts of money out-of-pocket for T&CM. This review highlights the need for further nationally representative studies to inform evidence-based policies and healthcare strategies for T&CM in Malaysia. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Malaysian Journal of Medicine & Health Sciences. 2025/07, Vol. 21, Issue 4, p337
  • Document Type:Literature Review
  • Subject Area:Complementary and Alternative Medicine
  • Publication Date:2025
  • ISSN:1675-8544
  • DOI:10.47836/mjmhs.21.4.40
  • Accession Number:187778472
  • Copyright Statement:Copyright of Malaysian Journal of Medicine & Health Sciences is the property of Universiti Putra Malaysia 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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