Connected Mental Health Solutions: Global Attitudes, Preferences, and Concerns.

Background: Connected mental health (CMH) presents several technology-based solutions, which can help overcome many mental care delivery barriers. However, attitudes toward the use of CMH are diverse and differ from a cohort to another. Objective: The purpose of this study is to investigate the global attitudes toward CMH use and assess the use of technology for mental care. Methods: This study presents a synthesis of literature available in Scopus, Science Direct, and PubMed digital libraries, investigating attitudes toward CMH in different cohorts from different countries, based on a systematic review of relevant publications. This study also analyzes technology use patterns of the cohorts investigated, the reported preferred criteria that should be considered in CMH, and issues and concerns regarding CMH use. Results: One hundred and one publications were selected and analyzed. These publications were originated from different countries, with the majority (n = 23) being conducted in Australia. These studies reported positive attitudes of investigated cohorts toward CMH use and high technology use and ownership. Several preferred criteria were reported, mainly revolving around providing blended care functionalities, educational content, and mental health professionals (MHPs) support. Whereas concerns and issues related to CMH use addressed technical problems related to access to technology and to CMH solutions, the digital divide, lack of knowledge and use of CMH, and general reservations to use CMH. Concerns related to institutional and work barriers were also identified. Conclusions: Attitudes toward CMH show promising results from users and MHP views. However, factors such as providing blended care options and considering technical concerns should be taken into consideration for the successful adoption of CMH.

A process model for quality in use evaluation of clinical decision support systems.

CONTEXT: Clinical decision support systems (CDSSs) are used to help healthcare professionals in making decisions, offering them a tool for improved medical care practices based on monitoring and management procedures. Although CDSSs exhibit many advantages, challenges remain in terms of their adoption in the clinician community. One such issue is related to user satisfaction and the system reliability. Ensuring the quality of CDSSs is a way to improve their acceptance and adoption. OBJECTIVE: This study aims to propose a process model for evaluation of the quality in use characteristics of a CDSS to identify deficiencies that reduce its use by healthcare professionals. METHODS: We reviewed the existing literature on CDSS assessment and developed a process model based on the international standards ISO/IEC 25010 System and software quality models, and ISO/IEC 25022 Measurement of quality in use. To select measures for evaluating these characteristics, we adopted the Goal-Question-Metric (GQM) method. We evaluated the quality in use characteristics because they can represent system usability. Measurement of these characteristics helps us understand user needs, improve the user experience, and mitigate the low acceptance of CDSS, particularly by the primary users. RESULTS: We developed a process model for measuring the quality in use (QiU) characteristics of CDSSs, explaining its applicability through an illustrative example focused on the characteristics of satisfaction and efficiency. CONCLUSION: We consider that the proposed process model will benefit the CDSS adoption and contribute to the improvement of the quality of such systems by measuring its QiU.

Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain-Computer Interfaces: A Systematic Literature Review.

Humans interact with computers through various devices. Such interactions may not require any physical movement, thus aiding people with severe motor disabilities in communicating with external devices. The brain-computer interface (BCI) has turned into a field involving new elements for assistive and rehabilitative technologies. This systematic literature review (SLR) aims to help BCI investigator and investors to decide which devices to select or which studies to support based on the current market examination. This examination of noninvasive EEG devices is based on published BCI studies in different research areas. In this SLR, the research area of noninvasive BCIs using electroencephalography (EEG) was analyzed by examining the types of equipment used for assistive, adaptive, and rehabilitative BCIs. For this SLR, candidate studies were selected from the IEEE digital library, PubMed, Scopus, and ScienceDirect. The inclusion criteria (IC) were limited to studies focusing on applications and devices of the BCI technology. The data used herein were selected using IC and exclusion criteria to ensure quality assessment. The selected articles were divided into four main research areas: education, engineering, entertainment, and medicine. Overall, 238 papers were selected based on IC. Moreover, 28 companies were identified that developed wired and wireless equipment as means of BCI assistive technology. The findings of this review indicate that the implications of using BCIs for assistive, adaptive, and rehabilitative technologies are encouraging for people with severe motor disabilities and healthy people. With an increasing number of healthy people using BCIs, other research areas, such as the motivation of players when participating in games or the security of soldiers when observing certain areas, can be studied and collaborated using the BCI technology. However, such BCI systems must be simple (wearable), convenient (sensor fabrics and self-adjusting abilities), and inexpensive.

A Systematic Literature Review on e-Mental Health Solutions to Assist Health Care Workers During COVID-19.

Background: e-Mental health is an established field of exploiting information and communication technologies for mental health care. It offers different solutions and has shown effectiveness in managing many psychological issues. Introduction: The coronavirus disease 2019 (COVID-19) pandemic has critically influenced health care systems and health care workers (HCWs). HCWs are working under hard conditions, and are suffering from different psychological issues, including anxiety, stress, and depression. Consequently, there is an undeniable need of mental care interventions for HCWs. Under the circumstances caused by COVID-19, e-health interventions can be used as tools to assist HCWs with their mental health. These solutions can provide mental health care support remotely, respecting the recommended safety measures. Materials and Methods: This study aims to identify e-mental health interventions, reported in the literature, that are developed for HCWs during the COVID-19 pandemic. A systematic literature review was conducted following the PRISMA protocol by searching the following digital libraries: IEEE, ACM, ScienceDirect, Scopus, and PubMed. Results and Discussion: Eleven publications were selected. The identified e-mental health interventions consisted of social media platforms, e-learning content, online resources and mobile applications. Only 27% of the studies included empirical evaluation of the reported interventions, 55% listed challenges and limitations related to the adoption of the reported interventions. And 45% presented interventions developed specifically for HCWs in China. The overall feedback on the identified interventions was positive, yet a lack of empirical evaluation was identified, especially regarding qualitative evidence. Conclusions: The COVID-19 pandemic has highlighted the importance and need for e-mental health solutions for HCWs.

Investigating the Impact of Usability on Energy Efficiency of Web-based Personal Health Records.

Usability plays an important role in eHealth applications for their widespread adoption. These software systems have been studied in depth in the literature from this perspective. However, the energy consumption of information systems in the eHealth domain lacks comprehensive research. In this paper, the relationship between the energy consumption of the main components of a PC and the usability evaluations of graphical user interfaces (GUI) were studied in client applications. For this purpose, personal health records (PHR) were used as a case study. A set of 4 web-based PHRs were evaluated with the performance of 20 common tasks in the aforementioned systems. The usability evaluations were carried out by 4 experts. A total of 8 heuristics particularly designed for electronic health record systems and based on the Nielsen usability heuristics were employed. The instantaneous energy values of the power supply and the monitor were collected with an energy consumption measuring equipment. As a result, the following significant correlations were found. In NoMoreClipboard between the Memory heuristic and the power supply (rs = 0.495, p = 0.044), and the Minimalist heuristic and the monitor (rs = - 0.513, p = 0.035). In PatientsLikeMe between the Minimalist heuristic and the power supply (rs = - 0.479, p = 0.083), as well as in the Error heuristic and the power supply (rs = - 0.638, p = 0.014). Finally, in Health Companion between the Match heuristic and the power supply (rs = - 0.481, p = 0.043), and the Error heuristic and the power supply again (rs = - 0.602, p = 0.008). Apart from that, the tasks were divided into those with excellent and fair usability. Those tasks with high usability scores were evaluated to detect whether they also had low energy consumption during task performance. Significant differences were found in PatientsLikeMe with respect to the Error heuristic and the power supply (212.39 ± 18.85W). Significant differences were also found in Health Companion with respect to the Match heuristic and the power supply (199.91 ± 7.19W). The results were discussed to reveal the fundamentals of how implementing usability can impact on energy costs when running client applications.

Connected Mental Health: Systematic Mapping Study.

BACKGROUND: Although mental health issues constitute an increasing global burden affecting a large number of people, the mental health care industry is still facing several care delivery barriers such as stigma, education, and cost. Connected mental health (CMH), which refers to the use of information and communication technologies in mental health care, can assist in overcoming these barriers. OBJECTIVE: The aim of this systematic mapping study is to provide an overview and a structured understanding of CMH literature available in the Scopus database. METHODS: A total of 289 selected publications were analyzed based on 8 classification criteria: publication year, publication source, research type, contribution type, empirical type, mental health issues, targeted cohort groups, and countries where the empirically evaluated studies were conducted. RESULTS: The results showed that there was an increasing interest in CMH publications; journals were the main publication channels of the selected papers; exploratory research was the dominant research type; advantages and challenges of the use of technology for mental health care were the most investigated subjects; most of the selected studies had not been evaluated empirically; depression and anxiety were the most addressed mental disorders; young people were the most targeted cohort groups in the selected publications; and Australia, followed by the United States, was the country where most empirically evaluated studies were conducted. CONCLUSIONS: CMH is a promising research field to present novel approaches to assist in the management, treatment, and diagnosis of mental health issues that can help overcome existing mental health care delivery barriers. Future research should be shifted toward providing evidence-based studies to examine the effectiveness of CMH solutions and identify related issues.

Connected Health User Willingness to Share Personal Health Data: Questionnaire Study.

BACKGROUND: Connected health has created opportunities for leveraging health data to deliver preventive and personalized health care services. The increasing number of personal devices and advances in measurement technologies contribute to an exponential growth in digital health data. The practices for sharing data across the health ecosystem are evolving as there are more opportunities for using such data to deliver responsive health services. OBJECTIVE: The objective of this study was to explore user attitudes toward sharing personal health data (PHD). The study was executed within the first year after the implementation of the new General Data Protection Regulation (GDPR) legal framework. METHODS: The authors analyzed the results of an online questionnaire survey to explore the willingness of 8004 people using connected health services across four European countries to share their PHD and the conditions under which they would be willing to do so. RESULTS: Our findings indicate that the majority of users are willing to share their personal PHD for scientific research (1811/8004, 22.63%). Age, education level, and occupation of the participants, in addition to the level of digitalization in their country were found to be associated with data sharing attitudes. CONCLUSIONS: Positive attitudes toward data sharing for scientific research can be perceived as an indication of trust established between users and academia. Nevertheless, the interpretation of data sharing attitudes is a complex process, related to and influenced by various factors.

Free blood donation mobile applications.

Blood donation (BD) is a noble act and mobile applications (apps) can help increase awareness about it. This paper analyzes and assesses the characteristics of free apps for BD as regards features and functionality. A search in Google Play, Apple Apps store, Blackberry App World and Windows Mobile App store was carried out to select 169 free BD apps from the 188 apps identified. The results presented in this paper show that the majority of the apps selected have been developed for the Android operating system. Moreover, most of the apps selected are available to help users search for donors. Few of the apps could not be installed and/or accessed. Of those that could be installed: half of them do not require any kind of authentication; a few of them are available in more than one language; half of them have a geographical restriction; around 60 % of them do not notify the user of BD events and requests; one, which is available for Android and iOS, can connect with a laboratory; around 45 % of them allow users to share information via social networks, and the majority of them do not provide BD recommendations. These results are used as a basis to provide app developers with certain recommendations. There is a need for better BD apps with more features in order to increase the number of volunteer donors.

Compliance of blood donation apps with mobile OS usability guidelines.

The aim of this paper is to employ the guidelines of Android, iOS, Blackberry and Windows Phone to analyze the usability compliance of free blood donation (BD) apps. An analysis process based on a systematic review protocol is used to select free BD apps. An assessment is conducted using a questionnaire composed of 13 questions concerning the compliance of free BD apps with Android, Blackberry, iOS and Windows Phone usability guidelines. A total of 133 free BD apps have been selected from the 188 BD apps identified. Around 63% of the free BD apps selected have a good compliance with mobile OS usability recommendations. Around 72% of Android, 57% of Windows Phone, 33% of iOS and 33% of Blackberry BD apps have a high usability score. The aspect of BD app behavior should be improved along with some style components: the use of pictures to explain ideas and the adaptation of the app to both horizontal and vertical orientations. Structure patterns should also be used to improve the structure aspect of a BD app. Usability is a quality aspect that should be improved in current BD apps. Our study provides smartphone users with a list of usable free BD apps and BD app developers with recommendations.

Free Web-based personal health records: an analysis of functionality.

This paper analyzes and assesses the functionality of free Web-based PHRs as regards health information, user actions and connection with other tools. A systematic literature review in Medline, ACM Digital Library, IEEE Digital Library and ScienceDirect was used to select 19 free Web-based PHRs from the 47 PHRs identified. The results show that none of the PHRs selected met 100% of the 28 functions presented in this paper. Two free Web-based PHRs target a particular public. Around 90 % of the PHRs identified allow users throughout the world to create their own profiles without any geographical restrictions. Only half of the PHRs selected provide physicians with user actions. Few PHRs can connect with other tools. There was considerable variability in the types of data included in free Web-based PHRs. Functionality may have implications for PHR use and adoption, particularly as regards patients with chronic illnesses or disabilities. Support for standard medical document formats and protocols are required to enable data to be exchanged with other stakeholders in the health care domain. The results of our study may assist users in selecting the PHR that best fits their needs, since no significant connection exists between the number of functions of the PHRs identified and their popularity.

A Conceptual Framework to Design Connected Mental Health Solutions in the United Arab Emirates: Questionnaire Study.

BACKGROUND: Connected mental health (CMH) is a field presenting information and communications technology-based mental care interventions that could help overcome many mental care delivery barriers. Culture and background influence people's attitudes, preferences, and acceptance of such solutions. Therefore, the suitability of CMH solutions to the targeted population is an important factor in their successful adoption. OBJECTIVE: The aim of this study is to develop a framework for the design and creation of CMH solutions suitable for the UAE context. The framework is based on investigating enablers and barriers of CMH adoption in the United Arab Emirates, from the mental health professional's (MHP) perspective and from related literature. METHODS: A survey of literature on relevant studies addressing the use of technology for mental care in Arab countries, and a web-based questionnaire-based survey with 17 MHPs practicing in the United Arab Emirates investigating their attitudes and views toward CMH was conducted. Results from the questionnaire and from related studies were analyzed to develop the design framework. RESULTS: On the basis of findings from the literature survey and analyzing MHP answers to the web-based survey, a framework for the design of CMH solutions for the UAE population was developed. The framework presents four types of recommendation categories: favorable criteria, which included blended care, anonymity, and ease of use; cultural factors including availability in multiple languages, mainly Arabic and English, in addition to religious and cultural considerations; technical considerations, including good-quality communication, availability in formats compatible with mobile phones, and providing technical support; and users' health and data safety considerations, including users' suitability testing, confidentiality, and ensuring MHP integrity. CONCLUSIONS: CMH has the potential to help overcome many mental care barriers in the United Arab Emirates in particular and in the Arab world in general. CMH adoption in the United Arab Emirates has a potential for success. However, many factors should be taken into account, mainly cultural, religious, and linguistic aspects.

A Biofeedback-Based Mobile App With Serious Games for Young Adults With Anxiety in the United Arab Emirates: Development and Usability Study.

BACKGROUND: Following the outbreak of COVID-19, several studies have reported that young adults encountered a rise in anxiety symptoms, which could negatively affect their quality of life. Promising evidence suggests that mobile apps with biofeedback, serious games, breathing exercises, and positive messaging, among other features, are useful for anxiety self-management and treatment. OBJECTIVE: This study aimed to develop and evaluate the usability of a biofeedback-based app with serious games for young adults with anxiety in the United Arab Emirates (UAE). METHODS: This study consists of two phases: Phase I describes the design and development of the app, while Phase II presents the results of a usability evaluation by experts. To elicit the app's requirements during Phase I, we conducted (1) a survey to investigate preferences of young adults in the UAE for mobile games for stress relief; (2) an analysis of serious games for anxiety; and (3) interviews with mental health professionals and young adults in the UAE. In Phase II, five experts tested the usability of the developed app using a set of Nielsen's usability heuristics. RESULTS: A fully functional biofeedback-based app with serious games was co-designed with mental health professionals. The app included 4 games (ie, a biofeedback game, card game, arcade game, and memory game), 2 relaxation techniques (ie, a breathing exercise and yoga videos), and 2 additional features (ie, positive messaging and a mood tracking calendar). The results of Phase II showed that the developed app is efficient, simple, and easy to use. Overall, the app design scored an average of 4 out of 5. CONCLUSIONS: The elicitation techniques used in Phase I resulted in the development of an easy-to-use app for the self-management of anxiety. Further research is required to determine the app's usability and effectiveness in the target population.

Biofeedback-Based Connected Mental Health Interventions for Anxiety: Systematic Literature Review.

BACKGROUND: Connected mental health, which refers to the use of technology for mental health care and technology-based therapeutic solutions, has become an established field of research. Biofeedback is one of the approaches used in connected mental health solutions, which is mainly based on the analysis of physiological indicators for the assessment and management of the psychological state. Biofeedback is recommended by many therapists and has been used for conditions including depression, insomnia, and anxiety. Anxiety is associated with several physiological symptoms, including muscle tension and breathing issues, which makes the inclusion of biofeedback useful for anxiety detection and management. OBJECTIVE: The aim of this study was to identify interventions using biofeedback as a part of their process for anxiety management and investigate their perceived effectiveness. METHODS: A systematic literature review of publications presenting empirically evaluated biofeedback-based interventions for anxiety was conducted. The systematic literature review was based on publications retrieved from IEEE Digital Library, PubMed, ScienceDirect, and Scopus. A preliminary selection of papers was identified, examined, and filtered to include only relevant publications. Studies in the final selection were classified and analyzed to extract the modalities of use of biofeedback in the identified interventions, the types of physiological data that were collected and analyzed and the sensors used to collect them. Processes and outcomes of the empirical evaluations were also extracted. RESULTS: After final selection, 13 publications presenting different interventions were investigated. The interventions addressed either primarily anxiety disorders or anxiety associated with health issues such as migraine, Parkinson disease, and rheumatology. Solutions combined biofeedback with other techniques including virtual reality, music therapy, games, and relaxation practices and used different sensors including cardiovascular belts, wrist sensors, or stretch sensors to collect physiological data such as heart rate, respiration indicators, and movement information. The interventions targeted different cohorts including children, students, and patients. Overall, outcomes from the empirical evaluations yielded positive results and emphasized the effectiveness of connected mental health solutions using biofeedback for anxiety; however, certain unfavorable outcomes, such as interventions not having an effect on anxiety and patients' preferring traditional therapy, were reported in studies addressing patients with specific physical health issues. CONCLUSIONS: The use of biofeedback in connected mental health interventions for the treatment and management of anxiety allows better screening and understanding of both psychological and physiological patient information, as well as of the association between the two. The inclusion of biofeedback could improve the outcome of interventions and boost their effectiveness; however, when used with patients suffering from certain physical health issues, suitability investigations are needed.

Quality-in-use characteristics for clinical decision support system assessment.

BACKGROUND: Clinical decision support systems (CDSSs) are developed to support healthcare practitioners with decision-making about therapy and diagnosis' confirmation, among others. Although there are many advantages of using CDSSs, there are still many challenges in their adoption. Therefore, it is essential to ensure the quality of the system, so that it can be used confidently and securely. OBJECTIVE: This study aims to propose a set of (sub)characteristics which should be considered in evaluating the quality-in-use of CDSSs, based on the ISO/IEC 25010 standard and on existing literature. METHODS: We reviewed the existing literature on CDSS assessment and presented a list of quality characteristics evaluated. RESULTS: Ten quality characteristics and 56 sub-characteristics were identified and selected from the literature, in which usability was evaluated the most. An example of a scenario has been presented to illustrate our assessment approach of satisfaction and efficiency as important quality-in-use characteristics to be applied in the evaluation of a CDSS. CONCLUSION: The proposed approach will contribute in bridging the gap between the quality of CDSSs and their adoption.

End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19: A Theoretical Framework.

Respiratory symptoms can be caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms: coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases, such as the COVID-19 pandemic. Among the factors that contributed to the spread of the COVID-19 pandemic were the late diagnosis or misinterpretation of COVID-19 symptoms as regular flu-like symptoms. Research has shown that one of the possible differentiators of the underlying causes of different respiratory diseases could be the cough sound, which comes in different types and forms. A reliable lab-free tool for early and accurate diagnosis, which can differentiate between different respiratory diseases is therefore very much needed, particularly during the current pandemic. This concept paper discusses a medical hypothesis of an end-to-end portable system that can record data from patients with symptoms, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly theoretical solution could play an important part in the early diagnosis.

Impact of COVID-19 on the psychological health of university students in Spain and their attitudes toward Mobile mental health solutions.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has had an impact on several aspects of life, including university students' mental health. Mobile mental care applications (apps) comprise a form of online mental care that enables the delivery of remote mental care. OBJECTIVES: This study aimed to explore the impact of COVID-19 on the mental health of university students in Spain and to explore their attitudes toward the use of mobile mental care apps. METHOD: Respondents answered a survey, which comprised two sections. The first included the 12-item General Health Questionnaire (GHQ-12) that was employed to assess the students' mental health. The second section included six questions developed by the authors to explore the students' attitudes toward mental care apps. RESULTS: The results showed that the students suffered from anxiety and depression as well as social dysfunction. Further, 91.3 % of the students had never used a mobile app for mental health, 36.3 % were unaware of such apps, and 79.2 % were willing to use them in the future. CONCLUSIONS: The COVID-19 pandemic had a significant impact on the psychological health of university students. Mobile mental care apps may be an effective and efficient way to access mental care, particularly during a pandemic.

A Study on the Relationship between Usability of GUIs and Power Consumption of a PC: The Case of PHRs.

Usability is key to achieve quality in software products. The client applications with a high score in usability might impact on the power consumption when they are run in a PC. For this reason, energy savings turn to be critical in green software systems. In this paper the relationship between the usability evaluations of the GUIs and the power consumption measurements of the main components of a PC were analysed. A set of 5 web-based personal health records (PHRs) were selected as a case study. The usability assessment was performed by an expert, employing the 14 principles of design by Alan Dix as heuristics. They were scored on a Likert scale after performing a collection of common tasks in the PHRs. At the same time, an equipment to measure the energy consumption of hard disk drive, graphics card, processor, monitor and power supply was used. Spearman's index was studied for the correlations between the usability assessments and the power consumption measurements. As a results, some weak relationships were found. A total of 5 usability heuristics were observed to may influence energy consumption when they were considered in the implementation of the PHRs. These heuristics were the following ones: consistency, task migratability, observability, recoverability and responsiveness. Based on the results, the usability principles of design cannot always be related to lower energy consumption. Future research should focus on the tradeoffs between usability and power consumption of client applications when they are used in a computer.

An analysis on self-management and treatment-related functionality and characteristics of highly rated anxiety apps.

BACKGROUND AND OBJECTIVE: Anxiety is a common emotion that people often feel in certain situations. But when the feeling of anxiety is persistent and interferes with a person's day to day life then this may likely be an anxiety disorder. Anxiety disorders are a common issue worldwide and can fall under general anxiety, panic attacks, and social anxiety among others. They can be disabling and can impact all aspects of an individual's life, including work, education, and personal relationships. It is important that people with anxiety receive appropriate care, which in some cases may prove difficult due to mental health care delivery barriers such as cost, stigma, or distance from mental health services. A potential solution to this could be mobile mental health applications. These can serve as effective and promising tools to assist in the management of anxiety and to overcome some of the aforementioned barriers. The objective of this study is to provide an analysis of treatment and management-related functionality and characteristics of high-rated mobile applications (apps) for anxiety, which are available for Android and iOS systems. METHOD: A broad search was performed in the Google Play Store and App Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing apps for anxiety. A set of free and highly rated apps for anxiety were identified and the selected apps were then installed and analyzed according to a predefined data extraction strategy. RESULTS: A total of 167 anxiety apps were selected (123 Android apps and 44 iOS apps). Besides anxiety, the selected apps addressed several health issues including stress, depression, sleep issues, and eating disorders. The apps adopted various treatment and management approaches such as meditation, breathing exercises, mindfulness and cognitive behavioral therapy. Results also showed that 51% of the selected apps used various gamification features to motivate users to keep using them, 32% provided social features including chat, communication with others and links to sources of help; 46% offered offline availability; and only 19% reported involvement of mental health professionals in their design. CONCLUSIONS: Anxiety apps incorporate various mental health care management methods and approaches. Apps can serve as promising tools to assist large numbers of people suffering from general anxiety or from anxiety disorders, anytime, anywhere, and particularly in the current COVID-19 pandemic.

Investigating the Impact of COVID-19 Lockdown on the Psychological Health of University Students and Their Attitudes Toward Mobile Mental Health Solutions: Two-Part Questionnaire Study.

BACKGROUND: The COVID-19 outbreak was first reported to the World Health Organization on December 31, 2019, and it was officially declared a public health emergency of international concern on January 30, 2020. The COVID-19 outbreak and the safety measures taken to control it caused many psychological issues in populations worldwide, such as depression, anxiety, and stress. OBJECTIVE: The objectives of this study were to assess the psychological effects of the lockdown due to the COVID-19 outbreak on university students in the United Arab Emirates (UAE) and to investigate the students' awareness of mobile mental health care apps as well as their attitudes toward the use of these apps. METHODS: A two-part self-administered web-based questionnaire was delivered to students at United Arab Emirates University. The first part of the questionnaire assessed the mental state of the participants using the 12-item General Health Questionnaire (GHQ-12), while the second part contained questions investigating the participants' awareness of and attitudes toward mental health care apps. Students were invited to fill out the web-based questionnaire via social media and mailing lists. RESULTS: A total of 154 students participated in the survey, and the majority were female. The results of the GHQ-12 analysis showed that the students were experiencing psychological issues related to depression and anxiety as well as social dysfunction. The results also revealed a lack of awareness of mental health care apps and uncertainty regarding the use of such apps. Approximately one-third of the participants (44/154, 28.6%) suggested preferred functionalities and characteristics of mobile mental health care apps, such as affordable price, simple design, ease of use, web-based therapy, communication with others experiencing the same issues, and tracking of mental status. CONCLUSIONS: Like many groups of people worldwide, university students in the UAE were psychologically affected by the lockdown due to the COVID-19 outbreak. Although apps can be useful tools for mental health care delivery, especially in circumstances such as those produced by the outbreak, the students in this study showed a lack of awareness of these apps and mixed attitudes toward them. Improving the digital health literacy of university students in the UAE by increasing their awareness of mental health care apps and the treatment methods and benefits of the apps, as well as involving students in the app creation process, may encourage students to use these tools for mental health care.

Clinical decision support systems for chronic diseases: A Systematic literature review.

A Clinical Decision Support System (CDSS) aims to assist physicians, nurses and other professionals in decision-making related to the patient's clinical condition. CDSSs deal with pertinent and critical data, and special care should be taken in their design to ensure the development of usable, secure and reliable tools. OBJECTIVE: This paper aims to investigate existing literature dealing with the development process of CDSSs for monitoring chronic diseases, analysing their functionalities and characteristics, and the software engineering representation in their design. METHODS: A systematic literature review (SLR) is conducted to analyse the literature on CDSSs for monitoring chronic diseases and the application of software engineering techniques in their design. RESULTS: Fourteen included studies revealed that the most addressed disease was diabetes (42.8%) and the most commonly proposed approach was diagnostic (85.7%). Regarding data sources, the studies show a predominance on the use of databases (85.7%), with other data sources such as sensors (42.8%) and self-report (28.6%) also being considered. Analysing the representation for engineering techniques, we found Behaviour diagrams (42.8%) to be the most frequent, closely followed by Structural diagrams (35.7%) and others (78.6%) being largely mentioned. Some studies also approached the requirement specification (21.4%). The most common target evaluation was the performance of the system (64.2%) and the most common metric was accuracy (57.1%). CONCLUSION: We conclude that software engineering, in its completeness, has scarce representation in studies focused on the development of CDSSs for chronic diseases.