Designing Mobile Applications for Emergency Response: Citizens Acting as Human Sensors

Mobile Apps to Support Mental Health Response in Natural Disasters: Scoping Review

BACKGROUND

Disasters are becoming more frequent due to the impact of extreme weather events attributed to climate change, causing loss of lives, property, and psychological trauma. Mental health response to disasters emphasizes prevention and mitigation, and mobile health (mHealth) apps have been used for mental health promotion and treatment. However, little is known about their use in the mental health components of disaster management.

OBJECTIVE

This scoping review was conducted to explore the use of mobile phone apps for mental health responses to natural disasters and to identify gaps in the literature.

METHODS

We identified relevant keywords and subject headings and conducted comprehensive searches in 6 electronic databases. Studies in which participants were exposed to a man-made disaster were included if the sample also included some participants exposed to a natural hazard. Only full-text studies published in English were included. The initial titles and abstracts of the unique papers were screened by 2 independent review authors. Full texts of the selected papers that met the inclusion criteria were reviewed by the 2 independent reviewers. Data were extracted from each selected full-text paper and synthesized using a narrative approach based on the outcome measures, duration, frequency of use of the mobile phone apps, and the outcomes. This scoping review was reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews).

RESULTS

Of the 1398 papers retrieved, 5 were included in this review. A total of 3 studies were conducted on participants exposed to psychological stress following a disaster while 2 were for disaster relief workers. The mobile phone apps for the interventions included Training for Life Skills, Sonoma Rises, Headspace, Psychological First Aid, and Substance Abuse and Mental Health Services Administration (SAMHSA) Behavioural Health Disaster Response Apps. The different studies assessed the effectiveness or efficacy of the mobile app, feasibility, acceptability, and characteristics of app use or predictors of use. Different measures were used to assess the effectiveness of the apps' use as either the primary or secondary outcome.

CONCLUSIONS

A limited number of studies are exploring the use of mobile phone apps for mental health responses to disasters. The 5 studies included in this review showed promising results. Mobile apps have the potential to provide effective mental health support before, during, and after disasters. However, further research is needed to explore the potential of mobile phone apps in mental health responses to all hazards.

Where horizontal and vertical surveillances meet: Sense-making of US COVID-19 contact-tracing apps during a health crisis

Analyzing user reviews of seven US digital contact-tracing apps for COVID-19, this article unpacks how the new form of surveillance technology is understood and experienced by individuals during a global health crisis. The findings suggest that the app users felt empowered via self-tracking capacity and expressed community-level care and concerns, including those regarding the marginalized. At the same time, the users were raising doubts over technical effectiveness, navigating varying levels of voluntary choice available, and negotiating privacy concerns depending on the (dis)trust they held of institutional entities behind the governance of the apps. We argue that it is critical to investigate how surveillance technologies are situated across horizontal and vertical relationships in people's everyday lives to fully understand the individual and societal acceptance and/or refusal of the very systems during crises.

IoT-Based COVID-19 Diagnosing and Monitoring Systems: A Survey

To date, the novel Coronavirus (SARS-CoV-2) has infected millions and has caused the deaths of thousands of people around the world. At the moment, five antibodies, two from China, two from the U.S., and one from the UK, have already been widely utilized and numerous vaccines are under the trail process. In order to reach herd immunity, around 70% of the population would need to be inoculated. It may take several years to hinder the spread of SARS-CoV-2. Governments and concerned authorities have taken stringent measurements such as enforcing partial, complete, or smart lockdowns, building temporary medical facilities, advocating social distancing, and mandating masks in public as well as setting up awareness campaigns. Furthermore, there have been massive efforts in various research areas and a wide variety of tools, technologies and techniques have been explored and developed to combat the war against this pandemic. Interestingly, machine learning (ML) algorithms and internet of Things (IoTs) technology are the pioneers in this race. Up till now, several real-time and intelligent IoT-based COVID-19 diagnosing, and monitoring systems have been proposed to tackle the pandemic. In this article we have analyzed a wide range of IoTs technologies which can be used in diagnosing and monitoring the infected individuals and hotspot areas. Furthermore, we identify the challenges and also provide our vision about the future research on COVID-19.

Patient triage system for supporting the operation of dispatch centres and rescue teams

BACKGROUND

The Thai medical application for patient triage, namely Triagist, is an mHealth application designed to support the pre-hospital process. However, since the functions of the application that are necessary for the pre-hospital process have been found not to be fully developed, the addition of a back-end system has been considered to increase its performance and usability.

OBJECTIVE

To determine the ability of the previous version to effectively manage the pre-hospital process and analyse the current problems with the pre-hospital operation. Therefore, the new system was developed to support the connection of dispatch centres or operational centres to the Triagist mobile application and system evaluation.

METHOD

Design thinking methodology was used to analyse, design and develop a patient triage system to support the pre-hospital process in Thailand based on users' requirements. 68 active members of the rescue teams and emergency medical staff in Chiang Mai and Lampang provinces were recruited to test the reliability of the system based on a prototype application.

RESULTS

The new medical mobile application for patient triage in Thailand was validated for use due to containing the two essential functions of Initial Dispatch Code (IDC) geolocation and IDC management. When the system was tested by emergency staff who were responsible for using it, those with the least experience were found to use it better than their highly experienced colleagues. Moreover, in cases where the system had been implemented, it was found to determine the frequency of symptoms, the time period during which cases occurred, and the density of cases in each area.

CONCLUSION

This system, which has been developed based on the use of smart technology, will play an important role in supporting emergency services in Thailand by enhancing the efficiency of the pre-hospital process. Emergency centres will receive IDC information from the geolocation system so that they can determine patients' location without undue delay. Emergency services will be able to rapidly prepare the necessary resources and administrative tasks will be supported by linking the dispatch centre to central rescue teams.

Detecting and Tracking Criminals in the Real World through an IoT-Based System

Criminals and related illegal activities represent problems that are neither trivial to predict nor easy to handle once they are identified. The Police Forces (PFs) typically base their strategies solely on their intra-communication, by neglecting the involvement of third parties, such as the citizens, in the investigation chain which results in a lack of timeliness among the occurrence of the criminal event, its identification, and intervention. In this regard, a system based on IoT social devices, for supporting the detection and tracking of criminals in the real world, is proposed. It aims to enable the communication and collaboration between citizens and PFs in the criminal investigation process by combining app-based technologies and embracing the advantages of an Edge-based architecture in terms of responsiveness, energy saving, local data computation, and distribution, along with information sharing. The proposed model as well as the algorithms, defined on the top of it, have been evaluated through a simulator for showing the logic of the system functioning, whereas the functionality of the app was assessed through a user study conducted upon a group of 30 users. Finally, the additional advantage in terms of intervention time was compared to statistical results.