METHODS: This study aimed to explore the acceptance of medical delivery drones among medical practitioners as well as the public community in Malaysia using a knowledge, attitude, and perception (KAP) model and statistical analysis to decrease uncertainty. Bivariate and multivariate analyses of the results were performed in SPSS.
RESULTS: A total of 639 respondents took part in the survey, of which 557 complete responses were finally analyzed. The results showed that the overall acceptance rate for medical delivery drones was positive. The acceptance rate was significantly correlated with knowledge, attitude, and perception scores but not with sociodemographic factors.
DISCUSSION: Raising awareness and educating the medical as well as public communities regarding the potential role and benefits of drones are therefore important in garnering support for drone usage for medical purposes.
METHODS: We adopted the Joanna Briggs Institute's scoping review protocol and followed the Cochrane Rapid Review method to accelerate the review process, using the Implementation and Operation of Mobile Health projects framework and The Extended Technology Acceptance Model of Mobile Telephony to categorise the results. We conducted the review in four stages: (1) establishing value, (2) identifying digital health policy, (3) searching for evidence of infrastructure, design, and end-user adoption, (4) local input to interpret relevance and adoption factors. We used open-source national/international statistics such as the World Health Organization, International Telecommunication Union, Groupe Speciale Mobile, and local news/articles/government statistics to scope the current status, and systematically searched five databases for locally relevant exemplars.
RESULTS: We found 118 studies (2015-2021) and 114 supplementary online news articles and national statistics. Digital health policy was available in all countries, but scarce skilled labour, lack of legislation/interoperability support, and interrupted electricity and internet services were limitations. Older patients, women and those living in rural areas were least likely to have access to ICT infrastructure. Renewable energy has potential in enabling digital health care. Low usage mobile data and voice service packages are relatively affordable options for mHealth in the five countries.
CONCLUSIONS: Effective implementation of digital health technologies requires a supportive policy, stable electricity infrastructures, affordable mobile internet service, and good understanding of the socio-economic context in order to tailor the intervention such that it functional, accessible, feasible, user-friendly and trusted by the target users. We suggest a checklist of contextual factors that developers of digital health initiatives in LMICs should consider at an early stage in the development process.
OBJECTIVE: The goal of this study was to gain insight into (1) access and utilization of communication technology (eg, landline phone, internet, mobile phone), (2) acceptability of mHealth-based interventions for HIV prevention services, and (3) preferences regarding the format and frequency of mHealth interventions among Malaysian men who have sex with men.
METHODS: We conducted a cross-sectional survey with Malaysian men who have sex with men between July 2018 and March 2020. Participants were recruited using respondent-driven sampling in the Greater Kuala Lumpur region of Malaysia. We collected information on demographic characteristics, HIV risk-related behaviors, access to and the frequency of use of communication technology, and acceptability of using mHealth for HIV prevention using a self-administered questionnaire with a 5-point scale (1, never; 2, rarely; 3, sometimes; 4, often; 5, all the time).
RESULTS: A total of 376 men participated in the survey. Almost all respondents owned or had access to a smartphone with internet access (368/376, 97.9%) and accessed the internet daily (373/376, 99.2%), mainly on a smartphone (334/376, 88.8%). Participants on average used smartphones primarily for social networking (mean 4.5, SD 0.8), followed by sending or receiving emails (mean 4.0, SD 1.0), and searching for health-related information (mean 3.5, SD 0.9). There was high acceptance of the use of mHealth for HIV prevention (mean 4.1, SD 1.5), including for receiving HIV prevention information (345/376, 91.8%), receiving medication reminders (336/376, 89.4%), screening and monitoring sexual activity (306/376, 81.4%) or illicit drug use (281/376, 74.7%), and monitoring drug cravings (280/376, 74.5%). Participants overwhelmingly preferred a smartphone app over other modalities (eg, text, phone call, email) for engaging in mHealth HIV prevention tools. Preference for app notifications ranged from 186/336 (53.9%), for receiving HIV prevention information, to 212/336 (69.3%), for screening and monitoring sexual activity. Acceptance of mHealth was higher for those who were university graduates (P=.003), living in a relationship with a partner (P=.04), engaged in sexualized drug use (P=.01), and engaged in receptive anal sex (P=.006).
CONCLUSIONS: Findings from this study provide support for developing and deploying mHealth strategies for HIV prevention using a smartphone app in men who have sex with men-a key population with suboptimal engagement in HIV prevention and treatment.
METHODS: All fourth-year pharmacy students enrolled in Monash University in 2017 were provided access to MOVE. Cost-minimization analyses were performed to evaluate the cost of introducing MOVE in the pharmacy course using the smallest cohort size (Malaysia campus) of 40 students as the base case. We also determined under what circumstances MOVE would be more cost-effective, considering the different operational situations such as when student numbers increased or when the number of simulation modules created were increased.
RESULTS: The overall cost of setup and implementation of MOVE in the first year of implementation among 40 students was US $94.38 per student. In comparison, the face-to-face workshop cost was US $64.14 per student. On the second year of implementation, the ongoing cost of operation of MOVE was US $32.86 per student compared with US $58.97 per student using face-to-face workshop. A net benefit using MOVE was observed after the third year of implementation. Larger savings were noted when the cohort size extends larger than 100 students.
CONCLUSIONS: Monash OSCE Virtual Experience was a flexible and cost-effective approach to aid students in preparation for an OSCE and enhanced students' learning experience. The wider applicability of these findings will need to be explored in other settings.