Under the Nakba Tree

Mowafa Said Househ’s family fled Palestine in 1948 and arrived in Canada in the 1970s. He spent his childhood in Edmonton, Alberta, where he grew up as a visible minority and a Muslim whose family had a deeply fractured history. In the year 2000, when Mowafa visited his family’s homeland of Palestine at the beginning of the Second Intifada, he witnessed the effects of prolonged conflict and occupation. It was those observations and that experience that inspired him not only to tell his story but to realize many of the intergenerational and colonial traumas that he shares with the Indigenous people of Turtle Island. His moving memoir depicts the lives of those who live on occupied land and the struggles that define them.Publishe

The impact of automating laboratory request forms on the quality of healthcare services

SummaryIn recent decades, healthcare organizations have undergone a significant transformation with the integration of Information and Communication Technologies within healthcare operations to improve healthcare services. Various technologies such as Hospital Information Systems (HIS), Electronic Health Records (EHR) and Laboratory Information Systems (LIS) have been incorporated into healthcare services. The aim of this study is to evaluate the completeness of outpatients' laboratory paper based request forms in comparison with a electronic laboratory request system. This study was carried out in the laboratory department at King Abdulaziz Medical City (KAMC), National Guard Health Affairs, Riyadh, Saudi Arabia. We used a sample size calculator for comparing two proportions. We estimated the sample size to be 228 for each group. Any laboratory requests including paper and electronic forms were included. We categorized the clarity of the forms into understandable, readable, and unclear. A total of 57 incomplete paper forms or 25% were identified as being incomplete. For electronic forms, there were no incomplete fields, as all fields were mandatory, therefore, rendering them complete. The total of understandable paper-based laboratory forms was 11.4%. Additionally, it was found that the total of readable was 33.8% and the total for unclear was 54.8%, while for electronic-based forms, there were no unclear forms. Electronic based laboratory forms provide a more complete, accurate, clear, and understandable format than paper-based laboratory records. Based on these findings, KAMC should move toward the implementation of electronic-based laboratory request forms for the outpatient laboratory department

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

The Effectiveness of Mobile Phone Messaging–Based Interventions to Promote Physical Activity in Type 2 Diabetes Mellitus: Systematic Review and Meta-analysis

Background: Type 2 diabetes mellitus (T2DM) is increasing in prevalence worldwide. Physical activity (PA) is an important aspect of self-care and first-line management for T2DM. Mobile text messages (SMS) can be used to support self-management in people with T2DM, but the effectiveness of mobile text messages-based interventions in increasing physical activity is still unclear.Objective: The study aimed to assess the effectiveness of mobile phone messaging on PA in people with T2DM by summarizing and pooling the findings of previous literature.Methods: A systematic review was conducted to accomplish this objective. Search sources included 5 bibliographic databases (MEDLINE, Cochrane Library, CINAHL, Web of Science, EMBASE), the search engine “Google Scholar”, and backward and forward reference list checking of the included studies and relevant reviews. Two reviewers independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence evaluation. Results of included studies were synthesized narratively and statistically, as appropriate. Results: We included 6 of 541 retrieved studies. Four of the studies showed a statistically significant effect of text messages on physical activity. Although a meta-analysis of results of two studies showed a statistically significant effect (P=.05) of text messages on physical activity, the effect was not clinically important. A meta-analysis of findings of 2 studies showed a non-significant effect (P=.14) of text messages on glycaemic control. Two studies found a non-significant effect of text messages on anthropometric measures (weight and BMI).Conclusions: Text messaging interventions show promise for increasing physical activity. However, it is not possible to conclude from this review whether text messages have a significant effect on physical activity, glycaemic control, or anthropometric measures among patients with T2DM. This is due to the limited number of studies, the high overall risk of bias in most of the included studies and the low quality of meta-analysed evidence. There is a need for more high-quality primary studies

The Effectiveness of Mobile Phone Messaging–Based Interventions to Promote Physical Activity in Type 2 Diabetes Mellitus: Systematic Review and Meta-analysis (Preprint)

Background:Type 2 diabetes mellitus (T2DM) is increasing in prevalence worldwide. Physical activity (PA) is an important aspect of self-care and first-line management for T2DM. Mobile text messages (SMS) can be used to support self-management in people with T2DM, but the effectiveness of mobile text messages-based interventions in increasing physical activity is still unclear.Objective:The study aimed to assess the effectiveness of mobile phone messaging on PA in people with T2DM by summarizing and pooling the findings of previous literature.Methods:A systematic review was conducted to accomplish this objective. Search sources included 5 bibliographic databases (MEDLINE, Cochrane Library, CINAHL, Web of Science, EMBASE), the search engine “Google Scholar”, and backward and forward reference list checking of the included studies and relevant reviews. Two reviewers independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence evaluation. Results of included studies were synthesized narratively and statistically, as appropriate.Results:We included 6 of 541 retrieved studies. Four of the studies showed a statistically significant effect of text messages on physical activity. Although a meta-analysis of results of two studies showed a statistically significant effect (P=.05) of text messages on physical activity, the effect was not clinically important. A meta-analysis of findings of 2 studies showed a non-significant effect (P=.14) of text messages on glycaemic control. Two studies found a non-significant effect of text messages on anthropometric measures (weight and BMI).Conclusions:Text messaging interventions show promise for increasing physical activity. However, it is not possible to conclude from this review whether text messages have a significant effect on physical activity, glycaemic control, or anthropometric measures among patients with T2DM. This is due to the limited number of studies, the high overall risk of bias in most of the included studies and the low quality of meta-analysed evidence. There is a need for more high-quality primary studies

Wearable artificial intelligence for anxiety and depression: A scoping review

Background: Anxiety and depression are the most common mental disorders worldwide. Owing to the lack of psychiatrists around the world, the incorporation of AI and wearable devices (wearable artificial intelligence (AI)) have been exploited to provide mental health services. Objective: The current review aimed to explore the features of wearable AI used for anxiety and depression to identify application areas and open research issues. Methods: We searched 8 electronic databases (MEDLINE, PsycINFO, EMBASE, CINAHL, IEEE Xplore, ACM Digital Library, Scopus, and Google Scholar). Then, we checked studies that cited the included studies, and screened studies that were cited by the included studies. Study selection and data extraction were carried out by two reviewers independently. The extracted data were aggregated and summarized using the narrative synthesis. Results: Of the 1203 citations identified, 69 studies were included in this review. About two thirds of the studies used wearable AI for depression while the remaining studies used it for anxiety. The most frequent application of wearable AI was diagnosing anxiety and depression while no studies used it for treatment purposes. The majority of studies targeted individuals between the ages of 18 and 65. The most common wearable devices used in the studies were Actiwatch AW4. The wrist-worn devices were most common in the studies. The most commonly used data for model development were physical activity data, sleep data, and heart rate data. The most frequently used dataset from open sources was Depresjon. The most commonly used algorithms were Random Forest (RF) and Support Vector Machine (SVM). Conclusions: Wearable AI can offer great promise in providing mental health services related to anxiety and depression. Wearable AI can be used by individuals as a pre-screening assessment of anxiety and depression. Further reviews are needed to statistically synthesize studies’ results related to the performance and effectiveness of wearable AI. Given its potential, tech companies should invest more in wearable AI for treatment purposes for anxiety and depression

Ethical Considerations for Participatory Health through Social Media: Healthcare Workforce and Policy Maker Perspectives

Objectives: To identify the different ethical issues that should be considered in participatory health through social media from different stakeholder perspectives (i.e., patients/service users, health professionals, health information technology (IT) professionals, and policy makers) in any healthcare context. Methods: We implemented a two-round survey composed of open ended questions in the first round, aggregated into a list of ethical issues rated for importance by participants in the second round, to generate a ranked list of possible ethical issues in participatory health based on healthcare professionals’ and policy makers’ opinions on both their own point of view and their beliefs for other stakeholders’ perspectives. 1 Introduction Nowadays, individuals have more autonomy, access to information, and human capital to support their health decisions than previously fathomable [1, 2]. These informed, connected, and socially supported health consumers (or patients) are leading a shift in the way healthcare is approached, delivered, and governed. This very notion lies at the heart of participatory health, which centers on collaboration and shared-decision making [2, 3]. Results: Twenty-six individuals responded in the first round of the survey. Multiple ethical issues were identified for each perspective. Data privacy, data security, and digital literacy were common themes in all perspectives. Thirty-three individuals completed the second round of the survey. Data privacy and data security were ranked among the three most important ethical issues in all perspectives. Quality assurance was the most important issue from the healthcare professionals’ perspective and the second most important issue from the patients’ perspective. Data privacy was the most important consideration for patients/service users. Digital literacy was ranked as the fourth most important issue, except for policy makers’ perspective. Conclusions: Different stakeholders’ opinions fairly agreed that there are common ethical issues that should be considered across the four groups (patients, healthcare professionals, health IT professionals, policy makers) such as data privacy, security, and quality assurance

Artificial Intelligence for Participatory Health: Applications, Impact, and Future Implications

Objective: Artificial intelligence (AI) provides people and professionals working in the field of participatory health informatics an opportunity to derive robust insights from a variety of online sources. The objective of this paper is to identify current state of the art and application areas of AI in the context of participatory health. Methods: A search was conducted across seven databases (PubMed, Embase, CINAHL, PsychInfo, ACM Digital Library, IEEExplore, and SCOPUS), covering articles published since 2013. Additionally, clinical trials involving AI in participatory health contexts registered at clinicaltrials.gov were collected and analyzed. Results: Twenty-two articles and 12 trials were selected for review. The most common application of AI in participatory health was the secondary analysis of social media data: self-reported data including patient experiences with healthcare facilities, reports of adverse drug reactions, safety and efficacy concerns about over-the-counter medications, and other perspectives on medications. Other application areas included determining which online forum threads required moderator assistance, identifying users who were likely to drop out from a forum, extracting terms used in an online forum to learn its vocabulary, highlighting contextual information that is missing from online questions and answers, and paraphrasing technical medical terms for consumers. Conclusions: While AI for supporting participatory health is still in its infancy, there are a number of important research priorities that should be considered for the advancement of the field. Further research evaluating the impact of AI in participatory health informatics on the psychosocial wellbeing of individuals would help in facilitating the wider acceptance of AI into the healthcare ecosystem

The metaverse digital environments: a scoping review of the challenges, privacy and security issues

The concept of the “metaverse” has garnered significant attention recently, positioned as the “next frontier” of the internet. This emerging digital realm carries substantial economic and financial implications for both IT and non-IT industries. However, the integration and evolution of these virtual universes bring forth a multitude of intricate issues and quandaries that demand resolution. Within this research endeavor, our objective was to delve into and appraise the array of challenges, privacy concerns, and security issues that have come to light during the development of metaverse virtual environments in the wake of the COVID-19 pandemic. Through a meticulous review and analysis of literature spanning from January 2020 to December 2022, we have meticulously identified and scrutinized 29 distinct challenges, along with 12 policy, privacy, and security matters intertwined with the metaverse. Among the challenges we unearthed, the foremost were concerns pertaining to the costs associated with hardware and software, implementation complexities, digital disparities, and the ethical and moral quandaries surrounding socio-control, collectively cited by 43%, 40%, and 33% of the surveyed articles, respectively. Turning our focus to policy, privacy, and security issues, the top three concerns that emerged from our investigation encompassed the formulation of metaverse rules and principles, the encroachment of privacy threats within the metaverse, and the looming challenges concerning data management, all mentioned in 43%, 40%, and 33% of the examined literature. In summation, the development of virtual environments within the metaverse is a multifaceted and dynamically evolving domain, offering both opportunities and hurdles for researchers and practitioners alike. It is our aspiration that the insights, challenges, and recommendations articulated in this report will catalyze extensive dialogues among industry stakeholders, governmental bodies, and other interested parties concerning the metaverse's destiny and the world they aim to construct or bequeath to future generations

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.