Machine Learning-Based Approach for Identifying Research Gaps: COVID-19 as a Case Study.

BACKGROUND: Research gaps refer to unanswered questions in the existing body of knowledge, either due to a lack of studies or inconclusive results. Research gaps are essential starting points and motivation in scientific research. Traditional methods for identifying research gaps, such as literature reviews and expert opinions, can be time consuming, labor intensive, and prone to bias. They may also fall short when dealing with rapidly evolving or time-sensitive subjects. Thus, innovative scalable approaches are needed to identify research gaps, systematically assess the literature, and prioritize areas for further study in the topic of interest. OBJECTIVE: In this paper, we propose a machine learning-based approach for identifying research gaps through the analysis of scientific literature. We used the COVID-19 pandemic as a case study. METHODS: We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. Our approach is based on the BERTopic topic modeling technique, which leverages transformers and class-based term frequency-inverse document frequency to create dense clusters allowing for easily interpretable topics. Our BERTopic-based approach involves 3 stages: embedding documents, clustering documents (dimension reduction and clustering), and representing topics (generating candidates and maximizing candidate relevance). RESULTS: After applying the study selection criteria, we included 33,206 abstracts in the analysis of this study. The final list of research gaps identified 21 different areas, which were grouped into 6 principal topics. These topics were: "virus of COVID-19," "risk factors of COVID-19," "prevention of COVID-19," "treatment of COVID-19," "health care delivery during COVID-19," "and impact of COVID-19." The most prominent topic, observed in over half of the analyzed studies, was "the impact of COVID-19." CONCLUSIONS: The proposed machine learning-based approach has the potential to identify research gaps in scientific literature. This study is not intended to replace individual literature research within a selected topic. Instead, it can serve as a guide to formulate precise literature search queries in specific areas associated with research questions that previous publications have earmarked for future exploration. Future research should leverage an up-to-date list of studies that are retrieved from the most common databases in the target area. When feasible, full texts or, at minimum, discussion sections should be analyzed rather than limiting their analysis to abstracts. Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.

Technological Challenges and Solutions in Emergency Remote Teaching for Nursing: An International Cross-Sectional Survey.

OBJECTIVES: With the sudden global shift to online learning modalities, this study aimed to understand the unique challenges and experiences of emergency remote teaching (ERT) in nursing education. METHODS: We conducted a comprehensive online international cross-sectional survey to capture the current state and firsthand experiences of ERT in the nursing discipline. Our analytical methods included a combination of traditional statistical analysis, advanced natural language processing techniques, latent Dirichlet allocation using Python, and a thorough qualitative assessment of feedback from open-ended questions. RESULTS: We received responses from 328 nursing educators from 18 different countries. The data revealed generally positive satisfaction levels, strong technological self-efficacy, and significant support from their institutions. Notably, the characteristics of professors, such as age (p = 0.02) and position (p = 0.03), influenced satisfaction levels. The ERT experience varied significantly by country, as evidenced by satisfaction (p = 0.05), delivery (p = 0.001), teacher-student interaction (p = 0.04), and willingness to use ERT in the future (p = 0.04). However, concerns were raised about the depth of content, the transition to online delivery, teacher-student interaction, and the technology gap. CONCLUSIONS: Our findings can help advance nursing education. Nevertheless, collaborative efforts from all stakeholders are essential to address current challenges, achieve digital equity, and develop a standardized curriculum for nursing education.

Assessing the Quality, Privacy, and Security of Breast Cancer Apps for Arabic Speakers: Systematic Search and Review of Smartphone Apps.

BACKGROUND: Breast cancer is a widespread disease, and its incidence is rapidly increasing in the Middle East and North Africa region. With the increasing availability of smartphone apps for various health purposes, breast cancer apps have emerged as tools for raising awareness, providing support, and empowering women affected by this disease. These apps offer many features, including information on breast cancer risk factors, self-examination guides, appointment reminders, and community support groups or hotlines. Using apps raises the risk of privacy and security issues, and we hope that examining these features of the apps will contribute to the understanding of how technology can be used to improve these apps and provide insights for future development and improvement of breast cancer apps. OBJECTIVE: This study aims to critically review the quality, privacy, and security of breast cancer apps available to Arabic speakers. METHODS: Similar to several recent studies, we used a systematic search for apps available in Google Play and Apple App stores using both the web interface and the built-in native stores installed on smartphones. The search was conducted in mid-December 2022 in Arabic using the following keywords: سرطان الثدي - فحص سرطان الثدي - علاج سرطان الثدي - مرض سرطان الثدي - أعراض سرطان الثدي - فحص الثدي (breast cancer, breast cancer treatment, breast cancer disease, breast cancer symptoms, breast cancer screening, and breast test). These preidentified search terms are based on earlier work concerning the top searched breast cancer topics by Arabic speakers through Google's search engine. We excluded apps that did not have an Arabic interface, were developed for non-Arabic speakers, were paid, needed a subscription, or were directed toward health care workers. The Mobile App Rating Scale was used to evaluate the quality of the apps concerning their engagement, functionality, aesthetics, and information. A risk score was calculated for the apps to determine their security risk factors. RESULTS: Only 9 apps were included, with most (6/9, 67%) being supported by advertisements and categorized as informational. Overall, the apps had low numbers of downloads (>10 to >1000). The majority of the included apps (8/9, 89%) requested dangerous access permissions, including access to storage, media files, and the camera. The average security score of the included apps was 3.22, while only 2 apps provided information about data security and privacy. The included apps achieved an overall average quality score of 3.27, with individual dimension scores of 4.75 for functionality, 3.04 for information, 3.00 for aesthetics, and 2.32 for engagement. CONCLUSIONS: The limited availability of breast cancer apps available to Arabic speakers should be a call to action and prompt health care organizations and developers to join forces and collaboratively develop information-rich, usable, functional, engaging, and secure apps.

Exploring the Challenges and Opportunities of Adopting and Using Telemedicine for Diabetes Care and Management: Qualitative Semistructured Interview Study Among Health Care Providers and Patients With Diabetes.

BACKGROUND: Around the world, over half of the global population experiences noncommunicable diseases, resulting in premature death. Health care providers (HCPs) can deliver medical treatment from a distance by using digital advancements such as telemedicine. However, there is a limited understanding of the difficulties and opportunities of implementing telemedicine solutions in different socioeconomic and cultural environments, including Kuwait. OBJECTIVE: The purpose of this study is to (1) examine the obstacles and benefits of telemedicine in the context of diabetes treatment and management, as perceived by both HCPs and patients with diabetes; (2) investigate the nonfunctional requirements for telemedicine applications used in diabetes care and management; and (3) provide suggestions to enhance the integration and adoption of telemedicine in Kuwait's health care system for diabetes care and management. METHODS: The research used a qualitative and exploratory design, with semistructured interviews as the main data collection method. Participants were recruited on the internet through social media platforms due to the COVID-19 pandemic. The results were analyzed using thematic analysis and the Framework Method. The "diffusion of innovation" model was used as a perspective to interpret the findings. RESULTS: A total of 20 participants were included in this study-10 HCPs and 10 patients with diabetes-all of whom supported telemedicine. The HCPs reported that many diabetes cases could be managed through telemedicine, with only a few requiring in-person visits. Patients with diabetes noted the convenience and time-saving aspect of telemedicine. Both groups recommended the creation of a secure and user-friendly telemedicine system similar to popular social media platforms. Additionally, participants emphasized the importance of telemedicine during the pandemic as a way to prioritize patient safety. CONCLUSIONS: The results of this study provide valuable insights into the needs and preferences of both HCPs and patients with diabetes in a resource-rich country like Kuwait to embrace telemedicine. The COVID-19 pandemic has changed the way medical care is provided and has pushed both groups to consider digital solutions for ongoing diabetes management and treatment.

Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions.

The integration of large language models (LLMs), such as those in the Generative Pre-trained Transformers (GPT) series, into medical education has the potential to transform learning experiences for students and elevate their knowledge, skills, and competence. Drawing on a wealth of professional and academic experience, we propose that LLMs hold promise for revolutionizing medical curriculum development, teaching methodologies, personalized study plans and learning materials, student assessments, and more. However, we also critically examine the challenges that such integration might pose by addressing issues of algorithmic bias, overreliance, plagiarism, misinformation, inequity, privacy, and copyright concerns in medical education. As we navigate the shift from an information-driven educational paradigm to an artificial intelligence (AI)-driven educational paradigm, we argue that it is paramount to understand both the potential and the pitfalls of LLMs in medical education. This paper thus offers our perspective on the opportunities and challenges of using LLMs in this context. We believe that the insights gleaned from this analysis will serve as a foundation for future recommendations and best practices in the field, fostering the responsible and effective use of AI technologies in medical education.

Understanding mindsets, skills, current practices, and barriers of adoption of digital accessibility in Kuwait's software development landscape.

The responsibility for creating accessible software within the development of digital services is important for multiple reasons, mainly equity and inclusion. However, adopting and sustaining the development of accessible digital solutions has always been challenging, more so in countries that are relatively new to the concept of universal design, and physical and digital accessibility, and where legal sanctions are not yet established. This work investigates the technology scene in the State of Kuwait and analyses the responses of computing professionals with regard to their skills, best practices and procurement of accessible tech and to their level of awareness toward people with disabilities. The findings reveal a low level of awareness among tech professionals with regard to disabilities and digital accessibility-related standards. The findings also highlight a lack of available guidance for developing inclusive design and accessibility. Additionally, time constraints, lack of training, legal enforcement and fundamentals concepts during undergraduate and higher education contributed to observed weaknesses. Participants were keen to learn more and benefited from flyers and free professional development courses offered as incentives for survey completion.

Artificial Intelligence-Driven Serious Games in Health Care: Scoping Review.

BACKGROUND: Artificial intelligence (AI)-driven serious games have been used in health care to offer a customizable and immersive experience. Summarizing the features of the current AI-driven serious games is very important to explore how they have been developed and used and their current state to plan on how to leverage them in the current and future health care needs. OBJECTIVE: This study aimed to explore the features of AI-driven serious games in health care as reported by previous research. METHODS: We conducted a scoping review to achieve the abovementioned objective. The most popular databases in the information technology and health fields (ie, MEDLINE, PsycInfo, Embase, CINAHL, IEEE Xplore, ACM Digital Library, and Google Scholar) were searched using keywords related to serious games and AI. Two reviewers independently performed the study selection process. Three reviewers independently extracted data from the included studies. A narrative approach was used for data synthesis. RESULTS: The search process returned 1470 records. Of these 1470 records, 46 (31.29%) met all eligibility criteria. A total of 64 different serious games were found in the included studies. Motor impairment was the most common health condition targeted by these serious games. Serious games were used for rehabilitation in most of the studies. The most common genres of serious games were role-playing games, puzzle games, and platform games. Unity was the most prominent game engine used to develop serious games. PCs were the most common platform used to play serious games. The most common algorithm used in the included studies was support vector machine. The most common purposes of AI were the detection of disease and the evaluation of user performance. The size of the data set ranged from 36 to 795,600. The most common validation techniques used in the included studies were k-fold cross-validation and training-test split validation. Accuracy was the most commonly used metric for evaluating the performance of AI models. CONCLUSIONS: The last decade witnessed an increase in the development of AI-driven serious games for health care purposes, targeting various health conditions, and leveraging multiple AI algorithms; this rising trend is expected to continue for years to come. Although the evidence uncovered in this study shows promising applications of AI-driven serious games, larger and more rigorous, diverse, and robust studies may be needed to examine the efficacy and effectiveness of AI-driven serious games in different populations with different health conditions.

The Factors Contributing to Physicians' Current Use of and Satisfaction With Electronic Health Records in Kuwait's Public Health Care: Cross-sectional Questionnaire Study.

BACKGROUND: Electronic health record (EHR) has emerged as a backbone health care organization that aims to integrate health care records and automate clinical workflow. With the adoption of the eHealth care system, health information communication technologies and EHRs are offering significant health care advantages in the form of error reduction, improved communication, and patient satisfaction. OBJECTIVE: This study aimed to (1) investigate factors associated with physicians' EHR adoption status and prevalence of EHRs in Kuwait and (2) identify factors predicting physician satisfaction with EHRs in public hospitals in Kuwait. METHODS: This study was conducted at Kuwait's public Al-Jahra hospital from May to September 2019, using quantitative research methods. Primary data were gathered via questionnaires distributed among 295 physicians recruited using convenience sampling. Data were analyzed in SPSS using descriptive, bivariate, and multivariate linear regression, adjusted for demographics. RESULTS: Results of the study revealed that the controlled variable of gender (ß=-.197; P=.02) along with explanatory variables, such as training quality (ß=.068; P=.005), perception of barriers (ß=-.107; P=.04), and effect on physician (ß=.521; P<.001) have a significant statistical relationship with physicians' EHR adoption status. Furthermore, findings also suggested that controlled variables of gender (ß=-.193; P=.02), education (ß=-.164; P=.03), effect on physician (ß=.417; P<.001), and level of ease of use (ß=.254; P<.001) are significant predictors of the degree of physician satisfaction with the EHR system. CONCLUSIONS: The findings of this study had significant managerial and practical implications for creating an inductive environment for the acceptance of EHR systems across a broad spectrum of health care system in Kuwait.

A procurement-based classification of pharmaceutical supplies for diabetes disease management.

Background and Aims: Diabetes is among the most prevalent noncommunicable chronic diseases globally and carries a substantial expense in worldwide health care. Pharmaceutical supplies related to diabetes management account for 20%-40% of the disease's management cos, and this percentage continues to increase. This study examines the pharmaceutical expenses associated with one of the most common chronic diseases: diabetes. Specifically, we measure the extent to which patient health and demographic factors drive the annual cost of pharmaceutical supplies for diabetes management. Second, the study applied a procurement-centric classification scheme to pharmaceutical items involved in diabetes treatment. Methods: Data on 98,648 pharmaceutical-dispensing transactions (related to 2828 patients) over 1 year were collected from a specialized diabetes health center. Pharmaceutical prices from the sample were compared internationally to ensure that the findings apply to other countries. The association between the item cost and the number of unique patients prescribed pharmaceutical products was estimated at the category and subcategory levels. Results: Approximately 80% of total pharmaceutical expenditures were attributed to 20% of patients. Two of 20 pharmaceutical categories-anti-diabetes drugs and insulin-accounted for 34% of products dispensed and 57% of total pharmaceutical expenditures. Age, body mass index, and diabetes type were essential factors in predicting supply cost per patient. Conclusion: Applying the portfolio purchasing model also suggested that some clinically similar items, like insulin types, are best procured through divergent procurement strategies or vendors for optimal cost efficiency. A better understanding of the diverse array of diabetes supplies can reveal opportunities for better strategic supply management. This supply classification approach can also be applied in other supply-intensive specialties, such as orthopedics.

The Effectiveness of Serious Games in Improving Memory Among Older Adults With Cognitive Impairment: Systematic Review and Meta-analysis.

BACKGROUND: Memory, one of the main cognitive functions, is known to decline with age. Serious games have been used for improving memory in older adults. The effectiveness of serious games in improving memory has been assessed by many studies. To draw definitive conclusions about the effectiveness of serious games, the findings of these studies need to be pooled and aggregated. OBJECTIVE: This study aimed to assess the effectiveness of serious games in improving memory in older adults with cognitive impairment. METHODS: A systematic review of randomized controlled trials was carried out. The search sources included 8 databases, the reference lists of the included studies and relevant reviews, and the studies that cited the included studies. In total, 2 reviewers (AA and MH) independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence appraisal. Extracted data were synthesized using a narrative approach and a statistical approach (ie, multilevel meta-analysis), as appropriate. RESULTS: Of the 618 citations retrieved, 18 (2.9%) met the eligibility criteria for this review. Of these 18 studies, 15 (83%) randomized controlled trials were included in 10 multilevel meta-analyses. We found that serious games were more effective than no or passive interventions in improving nonverbal memory (P=.02; standardized mean difference [SMD]=0.46, 95% CI 0.09-0.83) and working memory (P=.04; SMD=0.31, 95% CI 0.01-0.60) but not verbal memory (P=.13; SMD=0.39, 95% CI -0.11 to 0.89). The review also showed that serious games were more effective than conventional exercises in improving verbal memory (P=.003; SMD=0.46, 95% CI 0.16-0.77) but not nonverbal memory (P=.30; SMD=-0.19, 95% CI -0.54 to 0.17) or working memory (P=.99; SMD=0.00, 95% CI -0.45 to 0.45). Serious games were as effective as conventional cognitive activities in improving verbal memory (P=.14; SMD=0.66, 95% CI -0.21 to 1.54), nonverbal memory (P=.94; SMD=-0.01, 95% CI -0.32 to 0.30), and working memory (P=.08; SMD=0.37, 95% CI -0.05 to 0.78) among older adults with cognitive impairment. Finally, the effect of adaptive serious games on working memory was comparable with that of nonadaptive serious games (P=.08; SMD=0.18, 95% CI -0.02 to 0.37). CONCLUSIONS: Serious games have the potential to improve verbal, nonverbal, and working memory in older adults with cognitive impairment. However, our findings should be interpreted cautiously given that most meta-analyses were based on a few studies (≤3) and judged to have a low quality of evidence. Therefore, serious games should be offered as a supplement to existing proven and safe interventions rather than as a complete substitute until further, more robust evidence is available. Future studies should investigate the short- and long-term effects of serious games on memory and other cognitive abilities among people of different age groups with or without cognitive impairment.

Effectiveness of Serious Games for Improving Executive Functions Among Older Adults With Cognitive Impairment: Systematic Review and Meta-analysis.

BACKGROUND: Executive functions are one of the known cognitive abilities that decline with age. They are the high-order cognitive processes that enable an individual to concentrate, plan, and take action. Serious games, which are games developed for specific purposes other than entertainment, could play a positive role in improving executive functions. Several systematic reviews have pooled the evidence about the effectiveness of serious games in improving executive functions; however, they are limited by some weaknesses. OBJECTIVE: This study aims to investigate the effectiveness of serious games for improving executive functions among older adults with cognitive impairment. METHODS: A systematic review of randomized controlled trials (RCTs) was conducted. To retrieve relevant studies, 8 electronic databases were searched. Further, reference lists of the included studies and relevant reviews were screened, and we checked studies that cited our included studies. Two reviewers independently checked the eligibility of the studies, extracted data from the included studies, assessed the risk of bias, and appraised the quality of the evidence. We used a narrative and statistical approach, as appropriate, to synthesize results of the included studies. RESULTS: Of 548 publications identified, 16 RCTs were eventually included in this review. Of the 16 studies, 14 studies were included in 6 meta-analyses. Our meta-analyses showed that serious games are as effective as no or passive interventions at improving executive functions (P=.29). Surprisingly, conventional exercises were more effective than serious games at improving executive functions (P=.03). Our subgroup analysis showed that both types of serious games (cognitive training games, P=.08; exergames, P=.16) are as effective as conventional exercises at improving executive functions. No difference was found between adaptive serious games and nonadaptive serious games for improving executive functions (P=.59). CONCLUSIONS: Serious games are not superior to no or passive interventions and conventional exercises at improving executive functions among older adults with cognitive impairment. However, our findings remain inconclusive due to the low quality of the evidence, the small sample size in most included studies, and the paucity of studies included in the meta-analyses. Accordingly, until more robust evidence is available, serious games should not be offered by health care providers nor used by patients for improving executive functions among older adults with cognitive impairment. Further reviews are needed to assess the long-term effect of serious games on specific executive functions or other cognitive abilities among people from different age groups with or without cognitive impairment. TRIAL REGISTRATION: PROSPERO CRD42021272757; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=272757.

Diabetes Self-management Apps: Systematic Review of Adoption Determinants and Future Research Agenda.

BACKGROUND: Most diabetes management involves self-management. Effective self-management of the condition improves diabetes control, reduces the risk of complications, and improves patient outcomes. Mobile apps for diabetes self-management (DSM) can enhance patients' self-management activities. However, they are only effective if clinicians recommend them, and patients use them. OBJECTIVE: This study aimed to explore the determinants of DSM apps' use by patients and their recommendations by health care professionals (HCPs). It also outlines the future research agenda for using DSM apps in diabetes care. METHODS: We systematically reviewed the factors affecting the adoption of DSM apps by both patients and HCPs. Searches were performed using PubMed, Scopus, CINAHL, Cochrane Central, ACM, and Xplore digital libraries for articles published from 2008 to 2020. The search terms were diabetes, mobile apps, and self-management. Relevant data were extracted from the included studies and analyzed using a thematic synthesis approach. RESULTS: A total of 28 studies met the inclusion criteria. We identified a range of determinants related to patients' and HCPs' characteristics, experiences, and preferences. Young female patients were more likely to adopt DSM apps. Patients' perceptions of the benefits of apps, ease of use, and recommendations by patients and other HCPs strongly affect their intention to use DSM apps. HCPs are less likely to recommend these apps if they do not perceive their benefits and may not recommend their use if they are unaware of their existence or credibility. Young and technology-savvy HCPs were more likely to recommend DSM apps. CONCLUSIONS: Despite the potential of DSM apps to improve patients' self-care activities and diabetes outcomes, HCPs and patients remain hesitant to use them. However, the COVID-19 pandemic may hasten the integration of technology into diabetes care. The use of DSM apps may become a part of the new normal.

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.

Towards Automated Screening of Literature on Artificial Intelligence in Nursing.

We evaluate the performance of multiple text classification methods used to automate the screening of article abstracts in terms of their relevance to a topic of interest. The aim is to develop a system that can be first trained on a set of manually screened article abstracts before using it to identify additional articles on the same topic. Here the focus is on articles related to the topic "artificial intelligence in nursing". Eight text classification methods are tested, as well as two simple ensemble systems. The results indicate that it is feasible to use text classification technology to support the manual screening process of article abstracts when conducting a literature review. The best results are achieved by an ensemble system, which achieves a F1-score of 0.41, with a sensitivity of 0.54 and a specificity of 0.96. Future work directions are discussed.

Exploring the Use and Adoption of Wearable Physical Activity Trackers in Oil-Rich Nations: A Qualitative Study of Youth Perspectives from Kuwait.

This study aimed to uncover participants' perspectives about the use of self-tracking wearables and describe the barriers and motivators for adopting them. Qualitative data were collected through semi-structured interviews. The analysis of the transcribed interviewed followed a thematic analysis approach and utilized the Framework method. The findings highlight the importance of wearables to increase physical activity health interventions targeting sedentary lifestyles.

The Untapped Potential of Nursing and Allied Health Data for Improved Representation of Social Determinants of Health and Intersectionality in Artificial Intelligence Applications: A Rapid Review.

OBJECTIVES: The objective of this paper is to draw attention to the currently underused potential of clinical documentation by nursing and allied health professions to improve the representation of social determinants of health (SDoH) and intersectionality data in electronic health records (EHRs), towards the development of equitable artificial intelligence (AI) technologies. METHODS: A rapid review of the literature on the inclusion of nursing and allied health data and the nature of health equity information representation in the development and/or use of artificial intelligence approaches alongside expert perspectives from the International Medical Informatics Association (IMIA) Student and Emerging Professionals Working Group. RESULTS: Consideration of social determinants of health and intersectionality data are limited in both the medical AI and nursing and allied health AI literature. As a concept being newly discussed in the context of AI, the lack of discussion of intersectionality in the literature was unsurprising. However, the limited consideration of social determinants of health was surprising, given its relatively longstanding recognition and the importance of representation of the features of diverse populations as a key requirement for equitable AI. CONCLUSIONS: Leveraging the rich contextual data collected by nursing and allied health professions has the potential to improve the capture and representation of social determinants of health and intersectionality. This will require addressing issues related to valuing AI goals (e.g., diagnostics versus supporting care delivery) and improved EHR infrastructure to facilitate documentation of data beyond medicine. Leveraging nursing and allied health data to support equitable AI development represents a current open question for further exploration and research.

Evaluating breast cancer websites targeting Arabic speakers: empirical investigation of popularity, availability, accessibility, readability, and quality.

BACKGROUND: Nowadays, patients have access to all types of health information on the internet, influencing their decision-making process. The Middle East and North Africa (MENA) region consists of 22 countries with an estimated population of around 600 million. Breast cancer is the highest diagnosed cancer in this region. Websites are commonly the go-to cancer information sources. A large population of the MENA region is only fluent in the Arabic language, thus access to Arabic websites is in more demand. However, little is known about breast cancer websites that cater to an Arabic-speaking audience. This study aims at evaluating Arabic breast cancer websites and offering recommendations to improve engagement and access to health information. METHODS: This study employed a cross-sectional analysis approach. Google trends was used to reveal the top searched topics across the MENA region, which in turn were used as search terms to identify the websites. To be included, a website had to be active, available in Arabic, and contain breast cancer information. The evaluation was based on a combination of automated and expert-based evaluation methods through five dimensions: Availability, Accessibility, Readability, Quality, and Popularity. RESULTS: Overall most of the websites performed poorly in the five dimensions and require careful reassessment concerning design, content, and readability levels; Only one website performed well in all dimensions, except for readability. Generally, the readability scores indicated that the websites were above the recommended level of reading. None of the websites passed the automated accessibility tests. The expert evaluation using the "Health on the Net" checklist showed good results for most websites. CONCLUSIONS: Breast cancer rates are rising in the MENA region, therefore having comprehensive, accurate, trustworthy, and easy-to-understand health information in their native language is a must. The results from this study show a need for improving the accessibility to breast cancer information websites available to Arabic speakers. The search was limited to three search engines yielding 10 websites and only one tool was used per dimension. Future work is needed to overcome these limitations. Collaboration between multiple stakeholders is necessary to develop websites that contain easy-to-read and understand high-quality information.

The Effectiveness and Safety of Serious Games for Improving Cognitive Abilities Among Elderly People With Cognitive Impairment: Systematic Review and Meta-Analysis.

BACKGROUND: Cognitive impairment is a mental disorder that commonly affects elderly people. Serious games, which are games that have a purpose other than entertainment, have been used as a nonpharmacological intervention for improving cognitive abilities. The effectiveness and safety of serious games for improving cognitive abilities have been investigated by several systematic reviews; however, they are limited by design and methodological weaknesses. OBJECTIVE: This study aims to assess the effectiveness and safety of serious games for improving cognitive abilities among elderly people with cognitive impairment. METHODS: A systematic review of randomized controlled trials (RCTs) was conducted. The following 8 electronic databases were searched: MEDLINE, Embase, CINAHL, PsycINFO, ACM Digital Library, IEEE Xplore, Scopus, and Google Scholar. We also screened reference lists of the included studies and relevant reviews, as well as checked studies citing our included studies. 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. RESULTS: Fifteen studies met the eligibility criteria among 466 citations retrieved. Of those, 14 RCTs were eventually included in the meta-analysis. We found that, regardless of their type, serious games were more effective than no intervention (P=.04) and conventional exercises (P=.002) for improving global cognition among elderly people with cognitive impairment. Further, a subgroup analysis showed that cognitive training games were more effective than no intervention (P=.05) and conventional exercises (P<.001) for improving global cognition among elderly people with cognitive impairment. Another subgroup analysis demonstrated that exergames (a category of serious games that includes physical exercises) are as effective as no intervention and conventional exercises (P=.38) for improving global cognition among elderly people with cognitive impairment. Although some studies found adverse events from using serious games, the number of adverse events (ie, falls and exacerbations of pre-existing arthritis symptoms) was comparable between the serious game and control groups. CONCLUSIONS: Serious games and specifically cognitive training games have the potential to improve global cognition among elderly people with cognitive impairment. However, our findings remain inconclusive because the quality of evidence in all meta-analyses was very low, mainly due to the risk of bias raised in the majority of the included studies, high heterogeneity of the evidence, and imprecision of total effect sizes. Therefore, psychologists, psychiatrists, and patients should consider offering serious games as a complement and not a substitute to existing interventions until further more robust evidence is available. Further studies are needed to assess the effect of exergames, the safety of serious games, and their long-term effects.

Implementation and Experiences of Telehealth: Balancing Policies With Practice in Countries of South Asia, Kuwait, and the European Union.

This viewpoint summarizes the discussion that occurred during the "Translating Policy to Practice in Telehealth-Lessons from Global Implementation Experiences" panel that was held virtually at Telemedicon2020, December 18-20, 2020. This panel brought together policy and implementation experts from some countries of South Asia, Kuwait, and the European Union to share their experiences in the development and implementation of telehealth standards and of the scale up of telehealth interventions within health systems. Several common themes arose from the discussion, including the significant role of people; encouragement by respective government policymakers; addressing concerns, particularly related to privacy, confidentiality, and security; and capacity building of human resources. These are discussed in turn, along with the future directions identified by the panelists, which emphasized the need for active encouragement toward the adoption and diffusion of digital health in general and of telehealth in particular. All stakeholders, ranging from governmental policymakers to common citizens, need to come together to build trusting partnerships to realize the advantages offered by telehealth.

The Effectiveness of Serious Games in Alleviating Anxiety: Systematic Review and Meta-analysis.

BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.