OBJECTIVE: This study aimed to translate and validate the English version of MAUQ (standalone for patients) into a Malay version of MAUQ (M-MAUQ) for mHealth app research and usage in future in Malaysia.
METHODS: Forward and backward translation and harmonization of M-MAUQ were conducted by Malay native speakers who also spoke English as their second language. The process began with a forward translation by 2 independent translators followed by harmonization to produce an initial translated version of M-MAUQ. Next, the forward translation was continued by another 2 translators who had never seen the original MAUQ. Lastly, harmonization was conducted among the committee members to resolve any ambiguity and inconsistency in the words and sentences of the items derived with the prefinal adapted questionnaire. Subsequently, content and face validations were performed with 10 experts and 10 target users, respectively. Modified kappa statistic was used to determine the interrater agreement among the raters. The reliability of the M-MAUQ was assessed by 51 healthy young adult mobile phone users. Participants needed to install the MyFitnessPal app and use it for 2 days for familiarization before completing the designated task and answer the M-MAUQ. The MyFitnessPal app was selected because it is one among the most popular installed mHealth apps globally available for iPhone and Android users and represents a standalone mHealth app.
RESULTS: The content validity index for the relevancy and clarity of M-MAUQ were determined to be 0.983 and 0.944, respectively, which indicated good relevancy and clarity. The face validity index for understandability was 0.961, which indicated that users understood the M-MAUQ. The kappa statistic for every item in M-MAUQ indicated excellent agreement between the raters (κ ranging from 0.76 to 1.09). The Cronbach α for 18 items was .946, which also indicated good reliability in assessing the usability of the mHealth app.
CONCLUSIONS: The M-MAUQ fulfilled the validation criteria as it revealed good reliability and validity similar to the original version. M-MAUQ can be used to assess the usability of mHealth apps in Malay in the future.
METHODS: A review and comparison of mHealth apps in pediatric care found in Google's Play Store (Android system) and Apple's App Store (iOS system) were performed. For the structured review of the available literature, Google Scholar, PubMed, IEEE Xplore Digital Library, and Science Direct online databases were used for the literature search. The assessment criteria used for comparison included requirement for Internet connection, size of application, information on disease, diagnostic tools, medical calculator, information on disease treatments, dosage recommendations, and drug interaction checker.
RESULTS: Fifty mHealth apps for general pediatric care and 8 mHealth apps for specific pediatric diseases were discussed in the literature. Of the 90 mHealth apps we reviewed, 27 that fulfilled the study criteria were selected for quality assessment. Medscape, Skyscape, and iGuideline scored the highest (score=7), while PediaBP scored the lowest (score=3).
CONCLUSIONS: Medscape, Skyscape, and iGuideline are the most comprehensive mHealth apps for HCPs as quick references for pediatric care. More studies about mHealth apps in pediatric care are warranted to ensure the quality and reliability of mHealth apps.
OBJECTIVE: To measure factors associated with mHealth adoption among primary care physicians (PCPs) in Malaysia.
METHODS: A cross-sectional study using a self-administered questionnaire was conducted among PCPs. The usage of mHealth apps by the PCPs has divided into the use of mHealth apps to support PCPs' clinical work and recommendation of mHealth apps for patient's use. Factors associated with mHealth adoption were analysed using multivariable logistic regression.
RESULTS: Among 217 PCPs in the study, 77.0% used mHealth apps frequently for medical references, 78.3% medical calculation and 30.9% interacting with electronic health records (EHRs). Only 22.1% of PCPs frequently recommended mHealth apps to patients for tracking health information, 22.1% patient education and 14.3% use as a medical device. Performance expectancy and facilitating conditions were associated with mHealth use for medical references. Family medicine trainees, working in a government practice and performance expectancy were the facilitators for the use of mHealth apps for medical calculation. Internet connectivity, performance expectancy and use by colleagues were associated with the use of mHealth with EHR. Performance expectancy was associated with mHealth apps' recommendation to patients to track health information and provide patient education.
CONCLUSIONS: PCPs often used mHealth apps to support their clinical work but seldom recommended mHealth apps to their patients. Training for PCPs is needed on the appraisal and knowledge of the mHealth apps for patient use.
METHODS: This study assessed access to and use of mobile technology and acceptability of mHealth among 150 HIV-positive MSM and TGW who were prescribed antiretroviral therapy (ART) in Malaysia-an emerging economy with rapid telecommunications growth and societal stigma against these groups.
RESULTS: Findings among the 114 MSM and 36 TGW reveal high levels of depression (42%), stigma (2.53/4.00) and risky sexual behavior (30%), and suboptimal ART adherence (22%). On the other hand, the sample had excellent access to smartphones (75.3%) and the internet (78%), and had high acceptance of mHealth especially for those with suboptimal ART adherence.
CONCLUSION: In settings like Malaysia where homosexuality and cross-dressing are socially and legally stigmatized, HIV prevention and treatment strategies delivered using an mHealth platform have the potential to overcome in-person barriers.
METHODS: A cross-sectional study was conducted from March to April 2021. An online survey, consisting of socio-demographic characteristics, Internet use, eHealth Literacy Scale and mobile health application utilisation, was distributed amongst pharmacy undergraduates in public and private universities in Malaysia. Data analysis included descriptive statistics, one-way analysis of variance test, Mann-Whitney U test and Kruskal-Wallis test.
RESULTS: A total of 415 participants completed the survey (response rate = 82.5%). The median eHealth Literacy Scale score (out of 40) was 31.0 ± 3.0 (interquartile range). More than one-third of participants (34.7%) were found to have low eHealth literacy. Many lacked confidence in making health decisions from online information (42.4%) and skills in distinguishing between high-quality and low-quality health resources (35.2%). Only 70.4% of the participants had mobile health applications installed on their smartphones and/or tablets. Some students felt that they were neither knowledgeable nor skilful enough to utilise mobile health applications (24.8%), whereas 23.9% were unaware of the mobile health applications available.
CONCLUSION: In summary, the eHealth literacy of Malaysian pharmacy students can be further enhanced by incorporating eHealth literacy-focused programmes into the curriculum. Moreover, pharmacy students' mobile health application utilisation can be improved through increased awareness and support from universities.
OBJECTIVES: Due to this discrepancy between the academic curriculum and the skills needed in the healthcare industry, the objectives of this study are to define the career pathway for eHealth professions and identify the challenges experienced by academic institutions and the industry in describing digital health professionals.
METHODS: We elicited qualitative data by conducting six focus groups with individuals from different professional backgrounds, including healthcare workers, information managers, computer sciences professionals, and workers in the revenue cycle who participated in a workshop on November 2-3, 2019, in Dubai. All focus group sessions were audio-recorded and transcribed, and participants were de-identified before analysis. An exploratory method was used to identify themes and subthemes. Saturation was reached when similar responses were found during the analysis. In this study, we found that respondents clearly defined eHealth career pathways based on criteria that included qualifications, experience, job scope, and competency. We also explored the challenges that the respondents encountered, including differences in the required skill sets and training and the need to standardize the academic curriculum across the GCC region, to recognize the various career pathways, and to develop local training programs. Additionally, country-specific projects have been initiated, such as the competency-based Digital Health framework, which was developed by the Saudi Commission of Healthcare Specialties (SCFHS) in 2018. Competency-based digital health frameworks generally include relevant job definitions, roles, and recommended competencies. Both the GCC taskforce and the Saudi studies capitalized on previous efforts by professional organizations, including Canada's Digital Health formerly known as (COACH), the U.S. Office of the National Coordinator for Health Information Technology (ONC), the American Medical Informatics Association (AMIA), and the Health Information and Management Systems Society (HIMSS).
RESULTS: In this study, we found that respondents defined eHealth career pathways based on different criteria such as: qualifications; various background of health and IT in the HI field; work experiences; job scope and competency. We also further explore the challenges that the respondents encountered which delineates four key aspects such as need of hybrid skills to manage the digital transformation, need of standardization of academic curriculum across GCC, recognition of the career pathways by the industry in order to open up career opportunity and career advancement, and availability of local training programs for up-skilling the current health workforce.
CONCLUSION: We believe that successful health digital transformation is not limited to technology advancement but requires an adaptive change in: the related competency-based frameworks, the organisation of work and career paths for eHealth professionals, and the development of educational programmes and joint degrees to equip clinicians with understanding of technology, and informaticians with understanding of healthcare. We anticipate that this work will be expanded and adopted by relevant professional and scientific bodies in the GCC region.
OBJECTIVE: With the growing body of evidence supporting the use of eHealth interventions, the intention is to conduct a meta-analysis on various health outcomes of eHealth interventions among ischaemic heart disease (IHD) patients.
METHODS: Based on PRISMA guidelines, eligible studies were searched through databases of Web of Science, Scopus, PubMed, EBSCOHost, and SAGE (PROSPERO registration CRD42021290091). Inclusion criteria were English language and randomised controlled trials published between 2011 to 2021 exploring health outcomes that empower IHD patients with eHealth interventions. RevMan 5.4 was utilised for meta-analysis, sensitivity analysis, and risk of bias (RoB) assessment while GRADE software for generating findings of physical health outcomes. Non-physical health outcomes were analysed using SWiM (synthesis without meta-analysis) method.
RESULTS: This review included 10 studies, whereby, six studies with 895 participants' data were pooled for physical health outcomes. Overall, the RoB varied significantly across domains, with the majority was low risks, a substantial proportion of high risks and a sizeable proportion of unclear. With GRADE evidence of moderate to high quality, eHealth interventions improved low density lipoprotien (LDL) levels in IHD patients when compared to usual care after 12 months of interventions (SMD -0.26, 95% CI [-0.45, -0.06], I2 = 0%, p = 0.01). Significance appraisal in each domain of the non-physical health outcomes found significant findings for medication adherence, physical activity and dietary behaviour, while half of the non-significant findings were found for other behavioural outcomes, psychological and quality of life.
CONCLUSIONS: Electronic Health interventions are found effective at lowering LDL cholesterol in long-term but benefits remain inconclusive for other physical and non-physical health outcomes for IHD patients. Integrating sustainable patient empowerment strategies with the advancement of eHealth interventions by utilising appropriate frameworks is recommended for future research.