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Readability and collocations in Malaysian online health brochures: a corpus-assisted analysis

Chong, Veronica Xin Yeen (2021) Readability and collocations in Malaysian online health brochures: a corpus-assisted analysis. Final Year Project, UTAR.

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    Abstract

    Brochures are commonly used by health professionals to disseminate salient information to their target audience. However, little attention is given to investigate the readability of communicable disease brochures and the frequent collocates that appear with the communicable diseases. Previous studies stated that medical related reading materials are presented beyond the recommended reading level, Grade 6, hence making it incomprehensible for those with low educational attainment. This study aims to investigate the readability of communicable disease brochures and find out the frequent collocation of communicable disease produced by Kementerian Kesihatan Malaysia (KKM). Three formulas were used to calculate the readability scores of communicable disease brochures: Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL) and Simple Measure of Gobbledygook (SMOG). The frequent collocates of communicable disease are determined using GraphColl in #Lancsbox. The findings indicate that all brochures are written beyond the recommend level and the frequent collocates of communicable diseases are used to describe three important themes which are the transmission of the disease, vaccination and the name of the communicable disease. By improving the readability of communicable disease brochures may promote better health literacy and it is crucial for the target audience to comprehend these brochures to encourage voluntary health behaviours.

    Item Type: Final Year Project / Dissertation / Thesis (Final Year Project)
    Subjects: H Social Sciences > H Social Sciences (General)
    Q Science > QP Physiology
    R Medicine > R Medicine (General)
    Divisions: Faculty of Arts and Social Science > Bachelor of Arts (Honours) English Language
    Depositing User: ML Main Library
    Date Deposited: 30 Dec 2022 16:43
    Last Modified: 30 Dec 2022 16:43
    URI: http://eprints.utar.edu.my/id/eprint/4471

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