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  1. Jacob SA, Chong EY, Goh SL, Palanisamy UD
    Mhealth, 2021;7:29.
    PMID: 33898598 DOI: 10.21037/mhealth.2020.01.04
    Background: Deaf and hard-of-hearing (DHH) patients have trouble communicating with community pharmacists and accessing the healthcare system. This study explored the views on a proposed mobile health (mHealth) app in terms of design and features, that will be able to bridge the communication gap between community pharmacists and DHH patients.

    Methods: A community-based participatory research method was utilized. Two focus group discussions (FGDs) were conducted in Malaysian sign language (BIM) with a total of 10 DHH individuals. Respondents were recruited using purposive sampling. Video-recordings were transcribed and analyzed using a thematic approach.

    Results: Two themes emerged: (I) challenges and scepticism of the healthcare system; and (II) features of the mHealth app. Respondents expressed fears and concerns about accessing healthcare services, and stressed on the need for sign language interpreters. There were also concerns about data privacy and security. With regard to app features, the majority preferred videos instead of text to convey information about their disease and medication, due to their lower literacy levels.

    Conclusions: For an mHealth app to be effective, app designers must ensure the app is individualised according to the cultural and linguistic diversity of the target audience. Pharmacists should also educate patients on the potential benefits of the app in terms of assisting patients with their medicine-taking.

  2. Lee JY, Wong CP, Lee SWH
    Mhealth, 2020;6:6.
    PMID: 32190617 DOI: 10.21037/mhealth.2019.09.16
    Background: Information and communication technology can be a useful tool to improve population health especially in low-middle income countries. However, the full potential of m-health may be limited by the users' health and technology literacy. This study aims to explore the m-health and technology literacy among Malaysians, and factors that may promote the use of m-health.

    Methods: A cross-sectional study was performed among residents residing around Klang and Petaling district in Selangor, Malaysia from November 2015 to January 2017. Multivariable logistic regression models were used to assess the predictors of mobile device and health apps usage and examine the association between apps use and intention to change behavior with sociodemographic predictors.

    Results: A total of 4,504 respondents participated in our survey. Most respondents reported that they owned a mobile or smartphone, which was commonly used to make calls and deliver text messages. However, only one-fifth (20.4%) of respondents were familiar with the term m-health or had used a health related application, with millennial (individuals aged ≤39 years) generally more aware of the term m-health and were more likely to use m-health as a tool for health management. The most commonly used application were for promoting adherence as well as self-efficacy (e.g., lifestyle advice). Other factors associated with higher levels of m-health use were individuals with higher level of education and individuals taking multiple medications.

    Conclusions: While most Malaysian were not familiar with m-health, they reported to have a positive attitude towards m-health. Malaysians were willing to use m-health to manage their health conditions but expressed that they required further education and training. As m-health is still at its infancy in Malaysia, there is potential to further develop m-health as an innovative solution to manage the population health.

  3. Loh BCS, Then PHH
    Mhealth, 2017;3:45.
    PMID: 29184897 DOI: 10.21037/mhealth.2017.09.01
    Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications.
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