Displaying publications 41 - 49 of 49 in total

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  1. Liu C, Lee WL, Teo CH, Zhang JH, Chong MC
    Digit Health, 2024;10:20552076241263695.
    PMID: 39070894 DOI: 10.1177/20552076241263695
    BACKGROUND: The persistently high incidence of stroke in many nations is suggestive of an area for further improvement on existing strategies of primary stroke prevention. Although the era of digitalisation has led to the increasing use of mobile applications (apps) in healthcare, more studies are needed to determine the efficacy of apps in producing the desired health outcomes across different nations and cultures.

    OBJECTIVE: To describe the development and evaluate the usability of a mobile app in delivering a culturally adapted stroke prevention educational programme for middle-aged adults in the Republic of China.

    METHODS: The educational programme was developed in three phases. In Phase 1, the process involved analysing requirements and designing structured modules. Phase 2 concentrated on expert consultation and technical development to deliver the educational programme. Phase 3 included a usability trial and refinement of the educational program based on trial results.

    RESULTS: Educational content was derived from the Chinese Guidelines for the Prevention and Treatment of Stroke and the Dietary Guidelines for Residents. The WeChat platform was used to deliver the educational programme. Participants expressed satisfaction with the content, interface, and functions of the apps, indicating that the apps have good usability.

    CONCLUSIONS: The development process of the Educational Programme was designed to maximise the culturally appropriate, and impact of lifestyle changes and stroke prevention. An app-based educational programme that has demonstrated good usability is a vital factor prior to deploying it in an intervention to evaluate its effects on health outcomes.

  2. Rajendran EG, Mohd Hairi F, Krishna Supramaniam R, T Mohd TAM
    Digit Health, 2024;10:20552076241256877.
    PMID: 39139190 DOI: 10.1177/20552076241256877
    BACKGROUND: Precision Public Health (PPH) is a newly emerging field in public health medicine. The application of various types of data allows PPH to deliver more tailored interventions to a specific population within a specific timeframe. However, the application of PPH possesses several challenges and limitations that need to be addressed.

    OBJECTIVE: We aim to provide evidence of the various use of PPH in outbreak management, the types of data that could be used in PPH application, and the limitations and barriers in the application of the PPH approach.

    METHODS AND ANALYSIS: Articles were searched in PubMed, Web of Science, and Science Direct. Our selection of articles was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for Scoping Review guidelines. The outcome of the evidence assessment was presented in narrative format instead of quantitative.

    RESULTS: A total of 27 articles were included in the scoping review. Most of the articles (74.1%) focused on PPH applications in performing disease surveillance and signal detection. Furthermore, the data type mostly used in the studies was surveillance (51.9%), environment (44.4), and Internet query data. Most of the articles emphasized data quality and availability (81.5%) as the main barriers in PPH applications followed by data integration and interoperability (29.6%).

    CONCLUSIONS: PPH applications in outbreak management utilize a wide range of data sources and analytical techniques to enhance disease surveillance, investigation, modeling, and prediction. By leveraging these tools and approaches, PPH contributes to more effective and efficient outbreak management, ultimately reducing the burden of infectious diseases on populations. The limitation and challenges in the application of PPH approaches in outbreak management emphasize the need to strengthen the surveillance systems, promote data sharing and collaboration among relevant stakeholders, and standardize data collection methods while upholding privacy and ethical principles.

  3. Mishra S, Chaudhury P, Tripathy HK, Sahoo KS, Jhanjhi NZ, Hassan Elnour AA, et al.
    Digit Health, 2024;10:20552076241256732.
    PMID: 39165388 DOI: 10.1177/20552076241256732
    OBJECTIVE: The modern era of cognitive intelligence in clinical space has led to the rise of 'Medical Cognitive Virtual Agents' (MCVAs) which are labeled as intelligent virtual assistants interacting with users in a context-sensitive and ambient manner. They aim to augment users' cognitive capabilities thereby helping both patients and medical experts in providing personalized healthcare like remote health tracking, emergency healthcare and robotic diagnosis of critical illness, among others. The objective of this study is to explore the technical aspects of MCVA and their relevance in modern healthcare.

    METHODS: In this study, a comprehensive and interpretable analysis of MCVAs are presented and their impacts are discussed. A novel system framework prototype based on artificial intelligence for MCVA is presented. Architectural workflow of potential applications of functionalities of MCVAs are detailed. A novel MCVA relevance survey analysis was undertaken during March-April 2023 at Bhubaneswar, Odisha, India to understand the current position of MCVA in society.

    RESULTS: Outcome of the survey delivered constructive results. Majority of people associated with healthcare showed their inclination towards MCVA. The curiosity for MCVA in Urban zone was more than in rural areas. Also, elderly citizens preferred using MCVA more as compared to youths. Medical decision support emerged as the most preferred application of MCVA.

    CONCLUSION: The article established and validated the relevance of MCVA in modern healthcare. The study showed that MCVA is likely to grow in future and can prove to be an effective assistance to medical experts in coming days.

  4. Aye LM, Tan MM, Schaefer A, Thurairajasingam S, Geldsetzer P, Soon LK, et al.
    Digit Health, 2024;10:20552076241278313.
    PMID: 39257871 DOI: 10.1177/20552076241278313
    BACKGROUND: Healthcare workers face burnout from high job demands and prolonged working conditions. While mental health services are available, barriers to access persist. Evidence suggests digital platforms can enhance accessibility. However, there is a lack of systematic reviews on the effectiveness of digital mental health interventions (DMHIs) for healthcare professionals. This review aims to synthesize evidence on DMHIs' effectiveness in reducing burnout, their acceptability by users, and implementation lessons learned.

    METHOD: This Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA)-guided review included 12 RCTs on DMHIs for healthcare professionals, published before 31 May 2024. The primary focus was on burnout, with secondary outcomes related to mental health and occupation. Quality appraisal used Cochrane risk of bias tools. A narrative synthesis explored DMHIs' effectiveness, acceptability, utilization, and implementation lessons.

    RESULTS: Significant improvements in mental health outcomes were observed in 10 out of 16 RCTs. Burnout and its constructs showed significant improvement in five RCTs. Studies that measured the acceptability of the interventions reported good acceptability. Factors such as attrition, intervention design and duration, cultural sensitivities, flexibility and ease of use, and support availability were identified as key implementation considerations.

    CONCLUSIONS: Web-based DMHIs positively impact burnout, mental health, and occupational outcomes among healthcare professionals, as shown in most RCTs. Future research should enhance DMHIs' effectiveness and acceptability by addressing identified factors. Increasing awareness of DMHIs' benefits will foster acceptance and positive attitudes. Lessons indicate that improving user engagement and effectiveness requires a multifaceted approach.

  5. Henry Basil J, Lim WH, Syed Ahmad SM, Menon Premakumar C, Mohd Tahir NA, Mhd Ali A, et al.
    Digit Health, 2024;10:20552076241286434.
    PMID: 39430694 DOI: 10.1177/20552076241286434
    OBJECTIVE: Neonates' physiological immaturity and complex dosing requirements heighten their susceptibility to medication administration errors (MAEs), with the potential for severe harm and substantial economic impact on healthcare systems. Developing an effective risk prediction model for MAEs is crucial to reduce and prevent harm.

    METHODS: This national-level, multicentre, prospective direct observational study was conducted in neonatal intensive care units (NICUs) of five public hospitals in Malaysia. Randomly selected nurses were directly observed during medication preparation and administration. Each observation was independently assessed for errors. Ten machine learning (ML) algorithms were applied with features derived from systematic reviews, incident reports, and expert consensus. Model performance, prioritising F1-score for MAEs, was evaluated using various measures. Feature importance was determined using the permutation-feature importance for robust comparison across ML algorithms.

    RESULTS: A total of 1093 doses were administered to 170 neonates, with mean age and birth weight of 33.43 (SD ± 5.13) weeks and 1.94 (SD ± 0.95) kg, respectively. F1-scores for the ten models ranged from 76.15% to 83.28%. Adaptive boosting (AdaBoost) emerged as the best-performing model (F1-score: 83.28%, accuracy: 77.63%, area under the receiver operating characteristic: 82.95%, precision: 84.72%, sensitivity: 81.88% and negative predictive value: 64.00%). The most influential features in AdaBoost were the intravenous route of administration, working hours, and nursing experience.

    CONCLUSIONS: This study developed and validated an ML-based model to predict the presence of MAEs among neonates in NICUs. AdaBoost was identified as the best-performing algorithm. Utilising the model's predictions, healthcare providers can potentially reduce MAE occurrence through timely interventions.

  6. Baragash RS, Aldowah H, Ghazal S
    Digit Health, 2022;8:20552076221132099.
    PMID: 36339904 DOI: 10.1177/20552076221132099
    OBJECTIVE: The use of virtual reality and augmented reality to improve older adults' quality of life has rapidly increased in recent years. This systematic mapping review aimed to provide a comprehensive overview of existing research that identifies and classifies current virtual reality and augmented reality applications that enhance the quality of life of older adults to increase the understanding of the impact of these technologies.

    METHODS: To reach this objective, a systematic mapping review was conducted of the studies published between 2009 and 2020 in major scientific databases, such as IEEE Xplore, Web of Science, Scopus, and PubMed. A total of 57 studies were analyzed and classified into four main quality of life domains: physical, cognitive, psychological, and social well-being.

    RESULTS: The findings showed that virtual reality and augmented reality have found their places in many quality of life studies of older adults. Although virtual reality and augmented reality applications are notably growing in the physical and cognitive well-being domains in training and rehabilitation settings, they are still in the early stages of development in psychological and social well-being research as well as healthcare settings. Our findings also revealed that virtual reality games, particularly motion-based exergames, and 3D augmented reality systems are the most common virtual reality and augmented reality types among the reviewed studies. Moreover, balance and attention were the most prevalent physical and cognitive functions when using motion-based and immersive virtual reality exergames and augmented reality systems and games, respectively, while confidence and interaction were the most dominant psychological and social functions.

    CONCLUSION: This mapping review provides a comprehensive overview of potential areas for further research in this field, thereby assisting researchers, technologists, and health practitioners in expanding this field of research.

  7. Ng WL, Ng CJ, Teo CH, Ang TF, Lee YK, Abdul Hadi H, et al.
    Digit Health, 2024;10:20552076241277710.
    PMID: 39247097 DOI: 10.1177/20552076241277710
    OBJECTIVE: Most dengue cases are managed in an outpatient setting, where patients are advised to return to the clinic daily for monitoring. Some patients can develop severe dengue at home and fail to recognise the deterioration. An application called DengueAid was designed as a self-monitoring tool for patients to reduce delay in seeking timely treatment. This study aimed to assess the feasibility of conducting a randomised controlled trial to determine the effectiveness of the DengueAid application.

    METHODS: Dengue patients were recruited from a public health clinic in Malaysia and randomised to either use the DengueAid application plus standard care for dengue or receive only the standard care. The outcomes evaluated were the (1) feasibility of recruitment, data collection and follow-up procedures; (2) preliminary clinical outcome measures; and (3) acceptability of DengueAid. Qualitative interviews were conducted for participants in the intervention arm to assess the acceptability of DengueAid.

    RESULTS: Thirty-seven patients were recruited with 97% (n = 36) retention rates. The recruitment rate was low (63% refusal rate, n = 62/99) with difficulty in data collection and follow-up due to the variable interval of care for dengue in an outpatient setting. DengueAid application was acceptable to the participants, but preliminary clinical outcomes and qualitative data suggested limited utility of the application. Unwell conditions of patients and limited access to healthcare are important factors impacting the application's utility.

    CONCLUSION: The feasibility trial uncovered issues with recruitment, data collection and follow-up processes. Further research and modification to the application are needed to improve its utility and usability.

  8. Malarvizhi CAN, Al Mamun A, Reza MNH, Masud MM
    Digit Health, 2024;10:20552076241272577.
    PMID: 39247095 DOI: 10.1177/20552076241272577
    The adoption of e-healthcare services is critical for improving healthcare accessibility and efficiency, particularly in regions with diverse populations, such as Malaysia. Although e-healthcare services offer numerous advantages, their adoption is considerably low and requires a thorough understanding of the key factors that influence their use. This study investigated the determinants and dynamics of e-healthcare adoption among adults over 40 years by extending the unified theory of acceptance and use of technology. We employed a quantitative research approach, specifically a cross-sectional design. Data were collected from 393 Malaysian respondents through a structured survey questionnaire, using convenience sampling. They were analyzed using partial least-squares-structural equation modeling. The findings revealed that performance expectancy, effort expectancy, social influence, and perceived product value significantly influenced individuals' intentions to use e-healthcare services. Meanwhile, perceived risk had an insignificant negative effect. Facilitating conditions significantly influenced individuals' intentions and actual usage of e-healthcare services. Furthermore, individuals' intentions to use e-healthcare services significantly affected their actual use of these services. Additionally, the intention to use e-healthcare services mediated the relationship between the factors and usage of e-healthcare services, except for perceived risk. Surprisingly, perceived service accuracy had no significant moderating effect on the relationship between individuals' intention to use and their actual use of e-healthcare services. This study offers valuable insights for educators, practitioners, and policymakers, enriching the scholarly discourse in this field. For education, integrating e-healthcare topics into curricula can enhance digital health literacy. In practice, healthcare providers should focus on improving user experience and addressing barriers to technology adoption. For policy making, developing supportive policies, and infrastructure to facilitate e-healthcare adoption is crucial to enhancing public health outcomes.
  9. Ahmad NA, Mat Ludin AF, Vanoh D, Tohit NM, Manaf ZA, Mohd Noah SA, et al.
    Digit Health, 2024;10:20552076241297213.
    PMID: 39600385 DOI: 10.1177/20552076241297213
    BACKGROUND: Technology advancement along with the increase in the older adults' population leads to the creation of health applications. The combination of exercise, nutrition, and cognition should be studied carefully in improving older adults' health.

    OBJECTIVE: The purpose of this study is to develop a health application, WeFit contains these three components and to determine its content validity, acceptability, and usability.

    METHODOLOGY: This study is a design and development study involving three phases. The first phase is the need analysis involving a review on 16 mobile applications available in Google play and iTunes App store as well as a review of six articles for identifying the perception of older adults in using mobile applications. Second phase is mobile application development and content validity. The content validity was determined using the Content Validity Index for Individual Items (I-CVI). Phase 3 evaluated the acceptance of the WeFit mobile application among older adults and health practitioners.

    RESULTS: Phase 1 indicated that half of the applications reviewed (50.0%) had physical activity component and the other half (50.0%) had a cognitive component, and none on nutrition. No application is reported to have all three components. In Phase 2, WeFit health application containing the three components was developed where users can view exercise and food recommendations and play cognitive games. WeFit had an I-CVI value of 0.98. With respect to acceptability, majority of the study participants (93.3%) understood the WeFit's content and the graphics used were appropriate. The usability study found that the majority of the older adults were satisfied with the interface and content. All health practitioners (100%) agreed WeFit is easy to use and agreed that it can guide them in giving medical advices.

    CONCLUSION: WeFit mobile app has been successfully developed, validated, and tested for acceptance among the older adults and health practitioners.

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