Issues facing the application of telemedicine in developing countries: Hashemite Kingdom of Jordan and Syrian Arab Republic

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Telemedicine delivers healthcare between geographically separated locations using medical expertise supported by communication technology. Physicians and specialists from one site can provide diagnosis, treatment and consultation to patients at a remote site. This makes the use of telemedicine particularly affective in rural and remote areas that have limited access to healthcare services. This study identifies the factors that affect the use and adoption of telemedicine in developing countries and rural areas in general, taking the Hashemite Kingdom of Jordan and the Syrian Arab Republic as cases studies. We have developed two guideline frameworks to be applied to telemedicine projects at the pre- implementation phase. The main purpose of the guideline frameworks is to assess the readiness of the Jordanian and Syrian health care system to use telemedicine and to assist any healthcare provider who is considering implementing a telemedicine project in either of these two countries. The guideline framework can be transferred and applied to any other country for which similar circumstances apply. Our guideline frameworks are based on interviews with key stakeholders including doctors, technicians, engineers, and decision makers, and administering questionnaires to further key stakeholders including patients, ensuring that we gain opinion from people from different backgrounds and with different roles in the healthcare system. Our research has identified specific key issues which inhibit the use of telemedicine: poor technology infrastructure; lack of funding; lack of IT education; insufficient training for clinicians; doctors’ resistance; patients’ resistance; and lack of knowledge about healthcare and technology. This work provides a clear idea of the current readiness in both countries and proposes two guideline frameworks that will aid the use of telemedicine. Their dissemination will create awareness and spread knowledge, which will help the decision makers to appreciate the potential role of telemedicine and help them to facilitate the process of introduction and so spread telemedicine in both Jordan and Syria

Effect of culture on acceptance of telemedicine in Middle Eastern countries: Case study of Jordan and Syria

© Mary Ann Liebert, INC.We investigated issues that affect the use and adoption of telemedicine in Middle Eastern countries, taking the Hashemite Kingdom of Jordan and the Syrian Arab Republic as case studies. Our study is based on interviews with key stakeholders (including doctors, technicians, engineers, and decision makers) and questionnaires administered to key stakeholders (including patients), ensuring opinion was gained from people from a full range of backgrounds and roles in the healthcare system. We found doctor and patient resistance was a major issue preventing the adoption of telemedicine in both countries, followed by poor infrastructure, lack of funding, and lack of information technology training. Our research identifies that culture is a greater issue than technical matters for the adoption of telemedicine in Middle Eastern countries. Based on our preliminary results we developed a guideline framework for each country that might be applied to telemedicine projects at the pre-implementation phase. The proposed guideline framework was validated through a return visit to the stakeholders and seeking further opinion

Issues facing the application of telemedicine in developing countries : Hashemite Kingdom of Jordan and Syrian Arab Republic

Telemedicine delivers healthcare between geographically separated locations using medical expertise supported by communication technology. Physicians and specialists from one site can provide diagnosis, treatment and consultation to patients at a remote site. This makes the use of telemedicine particularly affective in rural and remote areas that have limited access to healthcare services. This study identifies the factors that affect the use and adoption of telemedicine in developing countries and rural areas in general, taking the Hashemite Kingdom of Jordan and the Syrian Arab Republic as cases studies. We have developed two guideline frameworks to be applied to telemedicine projects at the pre- implementation phase. The main purpose of the guideline frameworks is to assess the readiness of the Jordanian and Syrian health care system to use telemedicine and to assist any healthcare provider who is considering implementing a telemedicine project in either of these two countries. The guideline framework can be transferred and applied to any other country for which similar circumstances apply. Our guideline frameworks are based on interviews with key stakeholders including doctors, technicians, engineers, and decision makers, and administering questionnaires to further key stakeholders including patients, ensuring that we gain opinion from people from different backgrounds and with different roles in the healthcare system. Our research has identified specific key issues which inhibit the use of telemedicine: poor technology infrastructure; lack of funding; lack of IT education; insufficient training for clinicians; doctors’ resistance; patients’ resistance; and lack of knowledge about healthcare and technology. This work provides a clear idea of the current readiness in both countries and proposes two guideline frameworks that will aid the use of telemedicine. Their dissemination will create awareness and spread knowledge, which will help the decision makers to appreciate the potential role of telemedicine and help them to facilitate the process of introduction and so spread telemedicine in both Jordan and Syria.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Clinicians perceptions of a telemedicine system : a mixed method study of Makassar City, Indonesia

Background: This case study in Makassar City, Indonesia aims to investigate the clinicians’ perceptions, including both satisfaction and barriers in using telemedicine in a large, established program which supported 3974 consultations in 2017. Methods: A mixed methodology was used in this research utilizing a questionnaire with 12 questions, and semi-structured interviews. A purposeful sample of clinicians using the telemedicine system at the 39 primary care clinics in Makassar City were surveyed. A total of 100 clinicians participated in this study. All of them completed the questionnaires (76.9% response rate) and 15 of them were interviewed. Results: The result showed that 78% of the clinicians were satisfied with the telemedicine system. In free text responses 69% said that telemedicine allowed quicker diagnosis and treatment, 47% said poor internet connectivity was a significant obstacle in using the system, and 40% suggested improvement to the infrastructure including internet connection and electricity. Conclusion: Overall, the clinicians were satisfied with the system, with the main benefit of rendering the diagnosis faster and easier for patients. However, poor internet connectivity was indicated as the main barrier. Most of the clinicians suggested improving the infrastructure especially the internet network

Technical Metrics Used to Evaluate Health Care Chatbots: Scoping Review

Dialog agents (chatbots) have a long history of application in health care, where they have been used for tasks such as supporting patient self-management and providing counseling. Their use is expected to grow with increasing demands on health systems and improving artificial intelligence (AI) capability. Approaches to the evaluation of health care chatbots, however, appear to be diverse and haphazard, resulting in a potential barrier to the advancement of the field. This study aims to identify the technical (nonclinical) metrics used by previous studies to evaluate health care chatbots. Studies were identified by searching 7 bibliographic databases (eg, MEDLINE and PsycINFO) in addition to conducting backward and forward reference list checking of the included studies and relevant reviews. The studies were independently selected by two reviewers who then extracted data from the included studies. Extracted data were synthesized narratively by grouping the identified metrics into categories based on the aspect of chatbots that the metrics evaluated. Of the 1498 citations retrieved, 65 studies were included in this review. Chatbots were evaluated using 27 technical metrics, which were related to chatbots as a whole (eg, usability, classifier performance, speed), response generation (eg, comprehensibility, realism, repetitiveness), response understanding (eg, chatbot understanding as assessed by users, word error rate, concept error rate), and esthetics (eg, appearance of the virtual agent, background color, and content). The technical metrics of health chatbot studies were diverse, with survey designs and global usability metrics dominating. The lack of standardization and paucity of objective measures make it difficult to compare the performance of health chatbots and could inhibit advancement of the field. We suggest that researchers more frequently include metrics computed from conversation logs. In addition, we recommend the development of a framework of technical metrics with recommendations for specific circumstances for their inclusion in chatbot studies

Role of digital health in coordinating patient care in a hub-and-spoke hierarchy of cancer care facilities : a scoping review

Background: Coordinating cancer care is complicated due to the involvement of multiple service providers which often leads to fragmentation. The evolution of digital health has led to the development of technology-enabled models of healthcare delivery. This scoping review provides a comprehensive summary of the use of digital health in coordinating cancer care via hub-and-spoke models. Methods: A scoping review of the literature was undertaken using the framework developed by Arksey and O’Malley. Research articles published between 2010 and 2022 were retrieved from four electronic databases (PubMed/MEDLINE, Web of Sciences, Cochrane Reviews and Global Health Library). The preferred reporting items for systematic reviews and meta-analyses extension for the scoping reviews (PRISMA-ScR) checklist were followed to present the findings. Result: In total, 311 articles were found of which 7 studies that met the inclusion criteria were included. The use of videoconferencing was predominant across all the studies. The number of spokes varied across the studies ranging from 1 to 63. Three studies aimed to evaluate the impact on access to cancer care among patients, two studies were related to capacity building of the health care workers at the spoke sites, one study was based on a peer review of radiotherapy plans, and one study was related to risk assessment and patient navigation. The introduction of digital health led to reduced travel time and waiting period for patients, and standardisation of radiotherapy plans at spokes. Tele-mentoring intervention aimed at capacity-building resulted in higher confidence and increased knowledge among the spoke learners. Conclusion: There is limited evidence for the role of digital health in the hub-and-spoke design. Although all the studies have highlighted the digital components being used to coordinate care, the bottlenecks, Which were overcome during the implementation of the interventions and the impact on cancer outcomes, need to be rigorously analysed

The effectiveness of serious games in alleviating anxiety : systematic review and meta-analysis

Anxiety is a mental disorder characterized by apprehension, tension, uneasiness, and other related behavioral disturbances. One of the nonpharmacological treatments used for reducing anxiety is serious games, which are games that have a purpose other than entertainment. The effectiveness of serious games in alleviating anxiety has been investigated by several systematic reviews; however, they were limited by design and methodological weaknesses. This study aims to assess the effectiveness of serious games in alleviating anxiety by summarizing the results of previous studies and providing an up-to-date review. We conducted a systematic review of randomized controlled trials (RCTs). The following seven databases were searched: MEDLINE, CINAHL, PsycINFO, ACM Digital Library, IEEE Xplore, Scopus, and Google Scholar. We also conducted backward and forward reference list checking for the included studies and relevant reviews. Two reviewers independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence appraisal. We used a narrative and statistical approach, as appropriate, to synthesize the results of the included studies. Of the 935 citations retrieved, 33 studies were included in this review. Of these, 22 RCTs were eventually included in the meta-analysis. Very low-quality evidence from 9 RCTs and 5 RCTs showed no statistically significant effect of exergames (games entailing physical exercises) on anxiety levels when compared with conventional exercises (P=.70) and no intervention (P=.27), respectively. Although 6 RCTs demonstrated a statistically and clinically significant effect of computerized cognitive behavioral therapy games on anxiety levels when compared with no intervention (P=.01), the quality of the evidence reported was low. Similarly, low-quality evidence from 3 RCTs showed a statistically and clinically significant effect of biofeedback games on anxiety levels when compared with conventional video games (P=.03). This review shows that exergames can be as effective as conventional exercises in alleviating anxiety; computerized cognitive behavioral therapy games and exergames can be more effective than no intervention, and biofeedback games can be more effective than conventional video games. However, our findings remain inconclusive, mainly because there was a high risk of bias in the individual studies included, the quality of meta-analyzed evidence was low, few studies were included in some meta-analyses, patients without anxiety were recruited in most studies, and purpose-shifted serious games were used in most studies. Therefore, serious games should be considered complementary to existing interventions. Researchers should use serious games that are designed specifically to alleviate depression, deliver other therapeutic modalities, and recruit a diverse population of patients with anxiety. [Abstract copyright: ©Alaa Abd-alrazaq, Mohannad Alajlani, Dari Alhuwail, Jens Schneider, Laila Akhu-Zaheya, Arfan Ahmed, Mowafa Househ. Originally published in JMIR Serious Games (https://games.jmir.org), 14.02.2022.

Blockchain technologies to mitigate COVID-19 challenges : a scoping review

Background: As public health strategists and policymakers explore different approaches to lessen the devastating effects of novel coronavirus disease (COVID-19), blockchain technology has emerged as a resource that can be utilized in numerous ways. Many blockchain technologies have been proposed or implemented during the COVID-19 pandemic; however, to the best of our knowledge, no comprehensive reviews have been conducted to uncover and summarise the main feature of these technologies. Objective: This study aims to explore proposed or implemented blockchain technologies used to mitigate the COVID-19 challenges as reported in the literature. Methods: We conducted a scoping review in line with guidelines of PRISMA Extension for Scoping Reviews (PRISMA-ScR). To identify relevant studies, we searched 11 bibliographic databases (e.g., EMBASE and MEDLINE) and conducted backward and forward reference list checking of the included studies and relevant reviews. The study selection and data extraction were conducted by 2 reviewers independently. Data extracted from the included studies was narratively summarised and described. Results: 19 of 225 retrieved studies met eligibility criteria in this review. The included studies reported 10 used cases of blockchain to mitigate COVID-19 challenges; the most prominent use cases were contact tracing and immunity passports. While the blockchain technology was developed in 10 studies, its use was proposed in the remaining 9 studies. The public blockchain technology was the most commonly utilized type in the included studies. All together, 8 different consensus mechanisms were used in the included studies. Out of 10 studies that identified the used platform, 9 studies used Ethereum to run the blockchain. Solidity was the most prominent programming language used in developing blockchain technology in the included studies. The transaction cost was reported in only 4 of the included studies and varied between USD 10−10 and USD 5. The expected latency and expected scalability were not identified in the included studies. Conclusion: Blockchain technologies are expected to play an integral role in the fight against the COVID-19 pandemic. Many possible applications of blockchain were found in this review; however, most of them are not mature enough to reveal their expected impact in the fight against COVID-19. We encourage governments, health authorities, and policymakers to consider all blockchain applications suggested in the current review to combat COVID-19 challenges. There is a pressing need to empirically examine how effective blockchain technologies are in mitigating COVID-19 challenges. Further studies are required to assess the performance of blockchain technologies’ fight against COVID-19 in terms of transaction cost, scalability, and/or latency when using different consensus algorithms, platforms, and access types

The performance of wearable AI in detecting stress among students : systematic review and meta-analysis

Students usually encounter stress throughout their academic path. Ongoing stressors may lead to chronic stress, adversely affecting their physical and mental well-being. Thus, early detection and monitoring of stress among students are crucial. Wearable artificial intelligence (AI) has emerged as a valuable tool for this purpose. It offers an objective, noninvasive, nonobtrusive, automated approach to continuously monitor biomarkers in real time, thereby addressing the limitations of traditional approaches such as self-reported questionnaires. This systematic review and meta-analysis aim to assess the performance of wearable AI in detecting and predicting stress among students. Search sources in this review included 7 electronic databases (MEDLINE, Embase, PsycINFO, ACM Digital Library, Scopus, IEEE Xplore, and Google Scholar). We also checked the reference lists of the included studies and checked studies that cited the included studies. The search was conducted on June 12, 2023. This review included research articles centered on the creation or application of AI algorithms for the detection or prediction of stress among students using data from wearable devices. In total, 2 independent reviewers performed study selection, data extraction, and risk-of-bias assessment. The Quality Assessment of Diagnostic Accuracy Studies-Revised tool was adapted and used to examine the risk of bias in the included studies. Evidence synthesis was conducted using narrative and statistical techniques. This review included 5.8% (19/327) of the studies retrieved from the search sources. A meta-analysis of 37 accuracy estimates derived from 32% (6/19) of the studies revealed a pooled mean accuracy of 0.856 (95% CI 0.70-0.93). Subgroup analyses demonstrated that the accuracy of wearable AI was moderated by the number of stress classes (P=.02), type of wearable device (P=.049), location of the wearable device (P=.02), data set size (P=.009), and ground truth (P=.001). The average estimates of sensitivity, specificity, and F -score were 0.755 (SD 0.181), 0.744 (SD 0.147), and 0.759 (SD 0.139), respectively. Wearable AI shows promise in detecting student stress but currently has suboptimal performance. The results of the subgroup analyses should be carefully interpreted given that many of these findings may be due to other confounding factors rather than the underlying grouping characteristics. Thus, wearable AI should be used alongside other assessments (eg, clinical questionnaires) until further evidence is available. Future research should explore the ability of wearable AI to differentiate types of stress, distinguish stress from other mental health issues, predict future occurrences of stress, consider factors such as the placement of the wearable device and the methods used to assess the ground truth, and report detailed results to facilitate the conduct of meta-analyses. PROSPERO CRD42023435051; http://tinyurl.com/3fzb5rnp. [Abstract copyright: ©Alaa Abd-alrazaq, Mohannad Alajlani, Reham Ahmad, Rawan AlSaad, Sarah Aziz, Arfan Ahmed, Mohammed Alsahli, Rafat Damseh, Javaid Sheikh. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.01.2024.

The performance of artificial intelligence-driven technologies in diagnosing mental disorders : an umbrella review

Artificial intelligence (AI) has been successfully exploited in diagnosing many mental disorders. Numerous systematic reviews summarize the evidence on the accuracy of AI models in diagnosing different mental disorders. This umbrella review aims to synthesize results of previous systematic reviews on the performance of AI models in diagnosing mental disorders. To identify relevant systematic reviews, we searched 11 electronic databases, checked the reference list of the included reviews, and checked the reviews that cited the included reviews. Two reviewers independently selected the relevant reviews, extracted the data from them, and appraised their quality. We synthesized the extracted data using the narrative approach. We included 15 systematic reviews of 852 citations identified. The included reviews assessed the performance of AI models in diagnosing Alzheimer's disease (n = 7), mild cognitive impairment (n = 6), schizophrenia (n = 3), bipolar disease (n = 2), autism spectrum disorder (n = 1), obsessive-compulsive disorder (n = 1), post-traumatic stress disorder (n = 1), and psychotic disorders (n = 1). The performance of the AI models in diagnosing these mental disorders ranged between 21% and 100%. AI technologies offer great promise in diagnosing mental health disorders. The reported performance metrics paint a vivid picture of a bright future for AI in this field. Healthcare professionals in the field should cautiously and consciously begin to explore the opportunities of AI-based tools for their daily routine. It would also be encouraging to see a greater number of meta-analyses and further systematic reviews on performance of AI models in diagnosing other common mental disorders such as depression and anxiety