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  1. Htay MNN, Latt SS, Maung KS, Myint WW, Moe S
    Asia Pac J Public Health, 2020 07 16;32(6-7):320-327.
    PMID: 32672053 DOI: 10.1177/1010539520940199
    International migration has become a global phenomenon bringing with it complex and interrelated issues related to the physical and mental well-being of the people involved. This study investigated the mental well-being and factors associated with mental health among Myanmar migrant workers (MMW) in Malaysia. The cross-sectional study was conducted in Penang, Malaysia by using the WHO-5 Well-Being Index Scale (WHO-5) and the Mental Health subscale of 36 items in the Short Form Health Survey (SF-36). Among 192 migrant workers who were understudied, 79.2% had poor mental well-being according to the WHO-5 scale. The duration of stay in Malaysia and without receiving financial aid from their employers despite having a physical illness were significantly associated with poor mental well-being. Mental health support groups should target migrant workers for mental health education and find ways to provide assistance for them. Furthermore, premigration training should be delivered at the country of origin that also provides information on the availability of mental health support in the host country.
  2. Ong MF, Soh KL, Saimon R, Myint WW, Pawi S, Saidi HI
    Int J Nurs Pract, 2023 Aug;29(4):e13083.
    PMID: 35871775 DOI: 10.1111/ijn.13083
    AIMS: The aim of this study is to evaluate an evidence-based fall risk screening tool to predict the risk of falls suitable for independent community-dwelling older adults guided by the World Health Organization's International Classification of Functioning, Disability and Health (WHO-ICF) components, and to examine the reliability and validity of the fall risk screening tool to predict fall risks, and to examine the feasibility of tools among independent community-dwelling older adults.

    METHODS: A systematic literature search guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was performed using the EBSCOHost® platform, ScienceDirect, Scopus and Google Scholar between July and August 2021. Studies from January 2010 to January 2021 were eligible for review. Nine articles were eligible and included in this systematic review. The risk of bias assessment used the National Institutes of Health quality assessment tool for observational cohort and cross-sectional studies. The WHO-ICF helped to guide the categorization of fall risk factors.

    RESULTS: Seven screening tools adequately predicted fall risk among community-dwelling older adults. Six screening tools covered most of the components of the WHO-ICF, and three screening tools omitted the environmental factors. The modified 18-item Stay Independent Brochure demonstrated most of the predictive values in predicting fall risk. All tools are brief and easy to use in community or outpatient settings.

    CONCLUSION: The review explores the literature evaluating fall risk screening tools for nurses and other healthcare providers to assess fall risk among independent community-dwelling older adults. A fall risk screening tool consisting of risk factors alone might be able to predict fall risk. However, further refinements and validations of the tools before use are recommended.

  3. Ong MF, Soh KL, Saimon R, Saidi HI, Tiong IK, Myint WW, et al.
    J Adv Nurs, 2024 Apr 12.
    PMID: 38606809 DOI: 10.1111/jan.16190
    AIMS: To evaluate factors associated with fall protection motivation to engage in fall preventive behaviour among rural community-dwelling older adults aged 55 and above using the protection motivation theory scale.

    DESIGN: A cross-sectional study.

    METHODS: The study was conducted in a healthcare clinic in Malaysia, using multistage random sampling from November 2021 to January 2022. Three hundred seventy-five older adults aged 55 and older were included in the final analysis. There were 31 items in the final PMT scale. The analysis was performed within the whole population and grouped into 'faller' and 'non-faller', employing IBM SPSS version 26.0 for descriptive, independent t-test, chi-square, bivariate correlation and linear regressions.

    RESULTS: A total of 375 older participants were included in the study. Fallers (n = 82) and non-fallers (n = 293) show statistically significant differences in the characteristics of ethnicity, assistive device users, self-rating of intention and participation in previous fall prevention programmes. The multiple linear regression model revealed fear, coping appraisal and an interaction effect of fear with coping appraisal predicting fall protection motivation among older adults in rural communities.

    CONCLUSION: Findings from this study demonstrated that coping appraisal and fear predict the protection motivation of older adults in rural communities. Older adults without a history of falls and attaining higher education had better responses in coping appraisal, contributing to a reduction in perceived rewards and improving protection motivation. Conversely, older adults from lower education backgrounds tend to have higher non-preventive behaviours, leading to a decline in fall protection motivation.

    IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: These results contribute important information to nurses working with older adults with inadequate health literacy in rural communities, especially when planning and designing fall prevention interventions. The findings would benefit all nurses, healthcare providers, researchers and academicians who provide care for older adults.

    PATIENT OR PUBLIC CONTRIBUTION: Participants were briefed about the study, and their consent was obtained. They were only required to answer the questionnaire through interviews. Older individuals aged fifty-five and above in rural communities at the healthcare clinic who could read, write or understand Malay or English were included. Those who were suffering from mental health problems and refused to participate in the study were excluded from the study. Their personal information remained classified and not recorded in the database during the data entry or analysis.

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