Users' intention to continue using mHealth services: A DEMATEL approach during the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) has changed the way we use and perceive online services. This study examined the influence of service quality factors during COVID-19 on individuals' intention to continue use mHealth services. A decision-making trial and evaluation laboratory (DEMATEL) approach was used to identify and analyse the relationships between service quality and individuals' intention to continue use mHealth during the COVID-19 pandemic. Individuals' direct, indirect, and interdependent behaviours in relation to service quality and continues use of mHealth were studied. A total of 126 respondents were involved in this study. The results identified several associations between service quality factors and individuals' continuous use of mHealth. The most important factor found to influence users' decision to continuously use mHealth was assurance, followed by hedonic benefits, efficiency, reliability, and content quality. The relevant cause-and-effect relationships were identified and the direction for quality improvement was discussed. The outcomes from this study can support healthcare policy makers to swiftly and widely respond to COVID-19 challenges. The findings provide fundamental insights for healthcare organisations to promote continuous use of mHealth among people by prioritising service improvements.

Digital Innovations for Occupational Safety: Empowering Workers in Hazardous Environments.

BACKGROUND: The quest to increase safety awareness, make job sites safer, and promote decent work for all has led to the utilization of digital technologies in hazardous occupations. This study investigated the use of digital innovations for safety and health management in hazardous industries. The key challenges and recommendations associated with such use were also explored. METHOD: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, a total of 48 studies were reviewed to provide a framework for future pathways for the effective implementation of these innovations. FINDINGS: The results revealed four main categories of digital safety systems: wearable-based systems, augmented/virtual reality-based systems, artificial intelligence-based systems, and navigation-based systems. A wide range of technological, behavioral, and organizational challenges were identified in relation to the key themes. CONCLUSION: Outcomes from this review can inform policymakers and industrial decision-makers about the application of digital innovations for best safety practices in various hazardous work conditions.

Digital technology adaptation and initiatives: a systematic review of teaching and learning during COVID-19.

COVID-19 dramatically influenced students' and staff's learning and teaching experiences and approaches to learning. While many papers examined individual experiences in the context of higher education, synthesising these papers to determine enabling and hindering influences of digital adaptation was needed to guide the next phase of online learning reforms. This study explored the main dimensions of digital technology adaptation in higher education during the COVID-19 pandemic. The consequences for student and staff experiences and what aspects should be sustained and developed were discussed in this review. A total of 90 articles (published between 1st January 2020 and 30th June 2021) were identified and analysed based on the preferred reporting items for systematic reviews and meta-analyses framework. Four dimensions (with associated sub-factors) were found to influence student and staff experiences: techno-economic; personal and psychological; teaching, learning and assessment; and social. The findings highlighted that an integrated approach, across institutional, technical platforms, and individuals would be required to sustain digital learning initiatives during the crisis time. Supplementary Information: The online version contains supplementary material available at 10.1007/s12528-023-09376-z.

Early-stage pregnancy recognition on microblogs: Machine learning and lexicon-based approaches.

Pregnancy carries high medical and psychosocial risks that could lead pregnant women to experience serious health consequences. Providing protective measures for pregnant women is one of the critical tasks during the pregnancy period. This study proposes an emotion-based mechanism to detect the early stage of pregnancy using real-time data from Twitter. Pregnancy-related emotions (e.g., anger, fear, sadness, joy, and surprise) and polarity (positive and negative) were extracted from users' tweets using NRC Affect Intensity Lexicon and SentiStrength techniques. Then, pregnancy-related terms were extracted and mapped with pregnancy-related sentiments using part-of-speech tagging and association rules mining techniques. The results showed that pregnancy tweets contained high positivity, as well as significant amounts of joy, sadness, and fear. The classification results demonstrated the possibility of using users' sentiments for early-stage pregnancy recognition on microblogs. The proposed mechanism offers valuable insights to healthcare decision-makers, allowing them to develop a comprehensive understanding of users' health status based on social media posts.

The development of telemedicine programs in Sub-Saharan Africa: Progress and associated challenges.

Monitoring the progress of telemedicine use in Sub-Saharan Africa (SSA) countries has received a considerable attention from many health organizations and governmental agencies. This study reviewed the current progress and challenges in relation to the development of telemedicine programs in SSA. The results from reviewing 66 empirical studies revealed an unbalanced progress across SSA countries. Further, technological, organisational, legal and regulatory, individual, financial, and cultural aspects were identified as the major barriers to the success of telemedicine development in SSA. This study reported the current trends in telemedicine application, as well as highlighting critical barriers for consideration by healthcare decision makers. The outcomes from this study offer a number of recommendations to support wider implementation and sustainable usage of telemedicine in SSA.

A non-invasive machine learning mechanism for early disease recognition on Twitter: The case of anemia.

Social media sites, such as Twitter, provide the means for users to share their stories, feelings, and health conditions during the disease course. Anemia, the most common type of blood disorder, is recognized as a major public health problem all over the world. Yet very few studies have explored the potential of recognizing anemia from online posts. This study proposed a novel mechanism for recognizing anemia based on the associations between disease symptoms and patients' emotions posted on the Twitter platform. We used k-means and Latent Dirichlet Allocation (LDA) algorithms to group similar tweets and to identify hidden disease topics. Both disease emotions and symptoms were mapped using the Apriori algorithm. The proposed approach was evaluated using a number of classifiers. A higher prediction accuracy of 98.96 % was achieved using Sequential Minimal Optimization (SMO). The results revealed that fear and sadness emotions are dominant among anemic patients. The proposed mechanism is the first of its kind to diagnose anemia using textual information posted on social media sites. It can advance the development of intelligent health monitoring systems and clinical decision-support systems.

Telemedicine use in Sub-Saharan Africa: Barriers and policy recommendations for Covid-19 and beyond.

BACKGROUND: Telemedicine has been a useful healthcare alternative in the fight to contain the recent Covid-19 global pandemic. Yet the extent of its application and efficacy as an alternative route for healthcare provision remains a major concern for clinicians and patients. OBJECTIVE: This study sought to identify barriers to the successful implementation of telemedicine in Sub-Saharan African (SSA) countries. METHOD: A systematic review of the literature was conducted by applying the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for identifying, selecting, evaluating and interpreting findings. RESULTS: Our results from 66 empirical studies revealed a wide usage of telemedicine technology across SSA countries but also showed insufficient evidence of usage for fighting Covid-19 infection. Further, technological, organisational, legal and regulatory, individual, financial, and cultural aspects were identified as the major barriers to the successful implementation of telemedicine in SSA. A list of recommendations was produced for each telemedicine barrier. CONCLUSION: Our review shows current trends in telemedicine application, as well as highlighting critical barriers for consideration by healthcare decision makers. This review offers a number of recommendations to support wider implementation and sustainable usage of telemedicine in SSA.

Telemedicine in Middle Eastern countries: Progress, barriers, and policy recommendations.

BACKGROUND: Despite attempts to reform the healthcare delivery system in the Middle East, expectations for its progress have been-and for some still are-somewhat slow. OBJECTIVE: This study reviewed progress in the use and adoption of telemedicine in Middle Eastern countries. The key dimensions affecting the progress of telemedicine in these countries were identified. METHOD: A systematic review of the literature was conducted on 43 peer reviewed articles from 2010 to 2020. The review followed the scientific process of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of identification, selection, assessment, synthesis, and interpretation of findings. RESULTS: The results showed that progress made in the utilization of telemedicine was insufficient and varies across Middle Eastern countries. Certain cultural, financial, organizational, individual, technological, legal, and regulatory challenges were found to prevent telemedicine from being fully used to the point where the full range of medical services can be provided. For example, doctor and patient resistance, poor infrastructure, lack of funding, poor system quality, and lack of information technology training were associated with the low adoption of telemedicine in the region. CONCLUSION: This review provides a number of recommendations that will help policymakers to move toward the integration of innovative technologies in order to facilitate access to health information, health services, and training. It also recommends that health initiatives should focus on health education and health promotion in order to increase public awareness of the benefits of telemedicine services in the region.

A comparative review of mobile health and electronic health utilization in sub-Saharan African countries.

This study distinguished between the application of e-health and m-health technologies in sub-Saharan African (SSA) countries based on the dimensions of use, targeted diseases or health conditions, locations of use, and beneficiaries (types of patients or health workers) in a country specific context. It further characterized the main opportunities and challenges associated with these dimensions across the sub-region. A systematic review of the literature was conducted on 66 published peer reviewed articles. The review followed the scientific process of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of identification, selection, assessment, synthesis and interpretation of findings. The results of the study showed that m-health was prevalent in usage for promoting information for treatment and prevention of diseases as well as serving as an effective technology for reminders towards adherence. For e-health, the uniqueness lay in data acquisition and patients' records management; diagnosis; training and recruitment. While m-health was never used for monitoring or training and recruitment, e-health on the other hand could not serve the purpose of reminders or for reporting cases from the field. Both technologies were however useful for adherence, diagnosis, disease control mechanisms, information provision, and decision-making/referrals. HIV/AIDS, malaria, and maternal (postnatal and antenatal) healthcare were important in both m-health and e-health interventions mostly concentrated in the rural settings of South Africa and Kenya. ICT infrastructure, trained personnel, illiteracy, lack of multilingual text and voice messages were major challenges hindering the effective usage of both m-health and e-health technologies.