A scope of mobile health solutions in COVID-19 pandemics

Exploring mHealth design opportunities for blind and visually impaired older users

Background

Mobile health (mHealth) applications (apps) are crucial in delivering health information and services to older adults. Despite their importance, blind and visually impaired (BVI) older individuals often face significant challenges in app accessibility and usability. This study delves into the design preferences and expectations of BVI older users and underscores the necessity of user-centered design for inclusive mHealth apps.

Methods

Conducted in September 2023, the study comprised six focus group interviews. Each session involved two to four participants who began with self-introductions, followed by discussions centered on three open-ended interview questions.

Results

The study involved 14 participants: four with severe low vision and 10 totally blind. The primary design principles highlighted were "customizability" and "simplicity". The participants stressed the importance of intuitively designed main pages aligning with user patterns. Further, the participants articulated the following mHealth app feature or menu recommendations: editable profiles, emergency contact access, adaptable data presentation, data exportation, audible color details, customizable colors for varying visual needs, audible error feedback, feasible data input methods, toolbars, and habit-establishing reminders. Discussions also touched on the vital role of clear health data visualizations and comprehensible app-based health information.

Conclusions

The findings illuminate paths for software developers and health scientists working towards more inclusive mHealth solutions. It is essential during the development phase to prioritize app learnability to accommodate a broad range of users, ensuring that even those with disabilities can effectively use technological innovations to address health disparities.

Willingness to Use Digital Health Screening and Tracking Tools for Public Health in Sexual Minority Populations in a National Probability Sample: Quantitative Intersectional Analysis

BACKGROUND

Little is known about sexual minority adults' willingness to use digital health tools, such as pandemic-related tools for screening and tracking, outside of HIV prevention and intervention efforts for sexual minority men, specifically. Additionally, given the current cultural climate in the United States, heterosexual and sexual minority adults may differ in their willingness to use digital health tools, and there may be within-group differences among sexual minority adults.

OBJECTIVE

This study compared sexual minority and heterosexual adults' willingness to use COVID-19-related digital health tools for public health screening and tracking and tested whether sexual minority adults differed from each other by age group, gender, and race or ethnicity.

METHODS

We analyzed data from a cross-sectional, national probability survey (n=2047) implemented from May 30 to June 8, 2020, in the United States during the height of the public health response to the COVID-19 pandemic. Using latent-variable modeling, heterosexual and sexual minority adults were tested for differences in their willingness to use digital health tools for public health screening and tracking. Among sexual minority adults, specifically, associations with age, gender, and race or ethnicity were assessed.

RESULTS

On average, sexual minority adults showed greater willingness to use digital health tools for screening and tracking than heterosexual adults (latent factor mean difference 0.46, 95% CI 0.15-0.77). Among sexual minority adults, there were no differences by age group, gender, or race or ethnicity. However, African American (b=0.41, 95% CI 0.19-0.62), Hispanic or Latino (b=0.36, 95% CI 0.18-0.55), and other racial or ethnic minority (b=0.54, 95% CI 0.31-0.77) heterosexual adults showed greater willingness to use digital health tools for screening and tracking than White heterosexual adults.

CONCLUSIONS

In the United States, sexual minority adults were more willing to use digital health tools for screening and tracking than heterosexual adults. Sexual minority adults did not differ from each other by age, gender, or race or ethnicity in terms of their willingness to use these digital health tools, so no sexual orientation-based or intersectional disparities were identified. Furthermore, White heterosexual adults were less willing to use these tools than racial or ethnic minority heterosexual adults. Findings support the use of digital health tools with sexual minority adults, which could be important for other public health-related concerns (eg, the recent example of mpox). Additional studies are needed regarding the decision-making process of White heterosexual adults regarding the use of digital health tools to address public health crises, including pandemics or outbreaks that disproportionately affect minoritized populations.

Aphasia disrupts usual care: "I'm not mad, I'm not deaf" - the experiences of individuals with aphasia and family members in hospital

PURPOSE

Communication difficulties are highly prevalent in the stroke population, with implications for patient experience, safety and outcomes. This study explores the experiences of people with aphasia and family members regarding healthcare communication in acute and subacute stroke settings.

METHODS AND MATERIALS

A phenomenological approach was used to understand participants' experiences. Participants took part in a focus group and data were analysed using an inductive thematic approach.

RESULTS

For individuals with aphasia (n = 4) and family members (n = 2), five themes were generated: "aphasia makes it hard to communicate," "hospital staff focus on the patient's medical status only," "people with aphasia do not get the help they need to improve," "staff lack the skills to communicate with people with aphasia," and "staff are crucial to improving healthcare communication."

CONCLUSIONS

The stroke team has expertise in the medical management of stroke but struggle to communicate with patients with aphasia. Patients' experience of healthcare communication is often one-way and limited to following instructions, with missed opportunities to discuss core topics such as prognosis, rehabilitation, and person-specific needs. Patients and families assert that all members of the stroke healthcare team should be able to adapt communication to accommodate patients.

Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review

BACKGROUND

In the modern world, mobile apps are essential for human advancement, and pandemic control is no exception. The use of mobile apps and technology for the detection and diagnosis of COVID-19 has been the subject of numerous investigations, although no thorough analysis of COVID-19 pandemic prevention has been conducted using mobile apps, creating a gap.

OBJECTIVE

With the intention of helping software companies and clinical researchers, this study provides comprehensive information regarding the different fields in which mobile apps were used to diagnose COVID-19 during the pandemic.

METHODS

In this systematic review, 535 studies were found after searching 5 major research databases (ScienceDirect, Scopus, PubMed, Web of Science, and IEEE). Of these, only 42 (7.9%) studies concerned with diagnosing and detecting COVID-19 were chosen after applying inclusion and exclusion criteria using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol.

RESULTS

Mobile apps were categorized into 6 areas based on the content of these 42 studies: contact tracing, data gathering, data visualization, artificial intelligence (AI)-based diagnosis, rule- and guideline-based diagnosis, and data transformation. Patients with COVID-19 were identified via mobile apps using a variety of clinical, geographic, demographic, radiological, serological, and laboratory data. Most studies concentrated on using AI methods to identify people who might have COVID-19. Additionally, symptoms, cough sounds, and radiological images were used more frequently compared to other data types. Deep learning techniques, such as convolutional neural networks, performed comparatively better in the processing of health care data than other types of AI techniques, which improved the diagnosis of COVID-19.

CONCLUSIONS

Mobile apps could soon play a significant role as a powerful tool for data collection, epidemic health data analysis, and the early identification of suspected cases. These technologies can work with the internet of things, cloud storage, 5th-generation technology, and cloud computing. Processing pipelines can be moved to mobile device processing cores using new deep learning methods, such as lightweight neural networks. In the event of future pandemics, mobile apps will play a critical role in rapid diagnosis using various image data and clinical symptoms. Consequently, the rapid diagnosis of these diseases can improve the management of their effects and obtain excellent results in treating patients.

Timing, Indicators, and Approaches to Digital Patient Experience Evaluation: Umbrella Systematic Review

BACKGROUND

The increasing prevalence of DH applications has outpaced research and practice in digital health (DH) evaluations. Patient experience (PEx) was reported as one of the challenges facing the health system by the World Health Organization. To generate evidence on DH and promote the appropriate integration and use of technologies, a standard evaluation of PEx in DH is required.

OBJECTIVE

This study aims to systematically identify evaluation timing considerations (ie, when to measure), evaluation indicators (ie, what to measure), and evaluation approaches (ie, how to measure) with regard to digital PEx. The overall aim of this study is to generate an evaluation guide for further improving digital PEx evaluation.

METHODS

This is a 2-phase study parallel to our previous study. In phase 1, literature reviews related to PEx in DH were systematically searched from Scopus, PubMed, and Web of Science databases. Two independent raters conducted 2 rounds of paper screening, including title and abstract screening and full-text screening, and assessed the interrater reliability for 20% (round 1: 23/115 and round 2: 12/58) random samples using the Fleiss-Cohen coefficient (round 1: k1=0.88 and round 2: k2=0.80). When reaching interrater reliability (k>0.60), TW conducted the rest of the screening process, leaving any uncertainties for group discussions. Overall, 38% (45/119) of the articles were considered eligible for further thematic analysis. In phase 2, to check if there were any meaningful novel insights that would change our conclusions, we performed an updated literature search in which we collected 294 newly published reviews, of which 102 (34.7%) were identified as eligible articles. We considered them to have no important changes to our original results on the research objectives. Therefore, they were not integrated into the synthesis of this review and were used as supplementary materials.

RESULTS

Our review highlights 5 typical evaluation objectives that serve 5 stakeholder groups separately. We identified a set of key evaluation timing considerations and classified them into 3 categories: intervention maturity stages, timing of the evaluation, and timing of data collection. Information on evaluation indicators of digital PEx was identified and summarized into 3 categories (intervention outputs, patient outcomes, and health care system impact), 9 themes, and 22 subthemes. A set of evaluation theories, common study designs, data collection methods and instruments, and data analysis approaches was captured, which can be used or adapted to evaluate digital PEx.

CONCLUSIONS

Our findings enabled us to generate an evaluation guide to help DH intervention researchers, designers, developers, and program evaluators evaluate digital PEx. Finally, we propose 6 directions for encouraging further digital PEx evaluation research and practice to address the challenge of poor PEx.

Exploring Maternal and Infant Health App Development and Effectiveness Research: Scoping Review

BACKGROUND

Globally, high rates of maternal and infant mortality call for interventions during the perinatal period to engage pregnant people as well as their loved ones in care. Mobile health technologies have become ubiquitous in our lives and in health care settings. However, there is a need to further explore their safety and effectiveness to support and improve health outcomes locally and globally.

OBJECTIVE

The aim of this study was to review and synthesize published literature that described the development process or effectiveness evaluations of maternal and infant apps.

METHODS

We applied a methodological framework for scoping reviews as well as the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines; in addition, the systematic review platform Covidence (Veritas Health Innovation Ltd) was used to facilitate the review of included studies. Search terms were developed collaboratively, and health sciences-associated databases were searched for studies conducted between January 1, 2000, and February 4, 2022. We excluded studies about apps that only gathered or tracked data or targeted care providers.

RESULTS

A total of 1027 articles were included for title and abstract screening, of which 87 (8.47%) were chosen for full-text screening. Of these 87 articles, 74 (85%) were excluded with reasons, and 19 (22%) were included. Four articles were added at data extraction from hand searching and 2 others were excluded. Thus, we reviewed and synthesized data from 11 unique studies reported in 21 articles published between 2017 and 2021. The included studies represented 8 different countries. Most of the apps (8/11, 73%) were in English, although apps were also developed in Arabic, Bahasa Indonesia, and Nepali. The articles reviewed revealed the early stage of development of the field of maternal and infant health apps, with modest evidence of app use and achievement of study outcomes. Only 1 (9%) of the 11 apps was endorsed by an independent health care provider society. App development and evaluation processes emerged, and specific app features were identified as vital for well-functioning apps. End-user engagement occurred in some, but not all, parts of app research and development.

CONCLUSIONS

Apps to improve maternal and infant health are being developed and launched in enormous numbers, with many of them not developed with mothers' needs in mind. There are concerns about privacy, safety, and the standardization of current apps as well as a need for professional or institution-specific guidelines or best practices. Despite challenges inherent in currently available apps and their design processes, maternal and infant app technology holds promise for achieving health equity goals and improving maternal and child health outcomes. Finally, we propose recommendations for advancing the knowledge base for maternal and infant apps.

Willingness to pay for health apps, its sociodemographic correlates, and reasons for being unwilling to pay

Background

Knowledge about whether, how much, and why individuals are willing to pay for health apps is limited.

Objectives

This study aimed to examine (1) the proportion of individuals willing to pay for health apps, (2) their willingness to pay (WTP; i.e. the maximum price the individual is willing to pay) for health apps, (3) the sociodemographic correlates determining whether individuals are willing to pay for these apps, (4) the sociodemographic correlates of their WTP, and (5) reasons for being unwilling to pay.

Methods

Six hundred adults were invited to participate in a questionnaire survey examining their sociodemographic characteristics, WTP for health apps, and reasons for being unwilling to pay. Sociodemographic characteristics and WTP for health apps were analyzed using descriptive statistics. Logistic regression was applied to examine the sociodemographic variables correlated with whether individuals were willing to pay for health apps. Among those who were willing to pay, log-linear regression was conducted to examine the sociodemographic correlates of their WTP. The reasons for unwillingness to pay were descriptively analyzed.

Results

A total of 577 individuals completed the questionnaire. Of them, 58.9% were willing to pay for health apps. Their median WTP was HK$50 (HK$1 ≈ US$0.13). Participants with a bachelor's degree or higher and those who had previously installed health apps were more inclined to pay for health apps. WTP was positively associated with the maximum price previously paid for a health app. The most frequently cited reasons for being unwilling to pay were the belief that the government should provide free health apps, distrust in health apps, and a lack of awareness of health apps and their benefits.

Conclusions

This study provides insights that can inform strategies to enhance the marketability, affordability, and accessibility of health apps.

Medical Personnel Behavior Preferences for Providing mHealth Service in China: A Discrete Choice Experiment

Purpose

This study aims to investigate factors affecting medical personnel behavioral preferences for providing mHealth in China, so as to provide decision-making basis for mHealth providers and managers to encourage more doctors to participate in mHealth service delivery.

Methods

Typical case sampling techniques were applied in a hospital setting to conduct a discrete choice experimental questionnaire survey of doctors (n=216) concerning mHealth preferences between July and October 2022. A conditional logit model was used to assess medical personnel preferences for each attribute and level of mHealth services.

Results

Length of service, information security, subjects of treatment and financial compensation all have a significant effect on medical staff's preference for providing mHealth services (p < 0.05). In terms of service duration and financial compensation, medical staff preferred mHealth services that provided shorter service duration and higher financial compensation; in terms of information security, medical staff preferred mHealth services with confidentiality of diagnostic and therapeutic information compared to information disclosure; and in terms of treatment targets, medical staff preferred the general population compared to key populations, such as pregnant women, the elderly, infants and children.

Conclusion

The preference of medical professionals to provide mHealth services is affected by a variety of factors. By enhancing the confidentiality of information in mHealth services, providing more options for service recipients, increasing their financial compensation, and shortening the duration of the service or increasing the number of service hours that can be adjusted can guide improvement of mHealth services and promoting of its adoption among medical professionals.

Human-centred artificial intelligence for mobile health sensing: challenges and opportunities

Advances in wearable sensing and mobile computing have enabled the collection of health and well-being data outside of traditional laboratory and hospital settings, paving the way for a new era of mobile health. Meanwhile, artificial intelligence (AI) has made significant strides in various domains, demonstrating its potential to revolutionize healthcare. Devices can now diagnose diseases, predict heart irregularities and unlock the full potential of human cognition. However, the application of machine learning (ML) to mobile health sensing poses unique challenges due to noisy sensor measurements, high-dimensional data, sparse and irregular time series, heterogeneity in data, privacy concerns and resource constraints. Despite the recognition of the value of mobile sensing, leveraging these datasets has lagged behind other areas of ML. Furthermore, obtaining quality annotations and ground truth for such data is often expensive or impractical. While recent large-scale longitudinal studies have shown promise in leveraging wearable sensor data for health monitoring and prediction, they also introduce new challenges for data modelling. This paper explores the challenges and opportunities of human-centred AI for mobile health, focusing on key sensing modalities such as audio, location and activity tracking. We discuss the limitations of current approaches and propose potential solutions.

The development and evaluation of a mHealth, community education and navigation intervention to improve clinical breast examination uptake in Segamat Malaysia: A randomised controlled trial

INTRODUCTION

Breast cancer (BC) screening uptake in Malaysia is low and a high number of cases present at a late stage. Community navigation and mobile health (mHealth) may increase screening attendance, particularly by women from rural communities. This randomized controlled study evaluated an intervention that used mHealth and community health workers to educate women about BC screening and navigate them to clinical breast examination (CBE) services in the context of the COVID-19 pandemic.

METHODS

Women aged 40-74 years, from Segamat, Malaysia, with a mobile phone number, who participated in the South East Asian Community Observatory health survey, (2018) were randomized to an intervention (IG) or comparison group (CG). The IG received a multi-component mHealth intervention, i.e. information about BC was provided through a website, and telephone calls and text messages from community health workers (CHWs) were used to raise BC awareness and navigate women to CBE services. The CG received no intervention other than the usual option to access opportunistic screening. Regression analyses were conducted to investigate between-group differences over time in uptake of screening and variable influences on CBE screening participation.

RESULTS

We recruited 483 women in total; 122/225 from the IG and 144/258 from the CG completed the baseline and follow-up survey. Uptake of CBE by the IG was 45.8% (103/225) whilst 3.5% (5/144) of women from the CG who completed the follow-up survey reported that they attended a CBE during the study period (adjusted OR 37.21, 95% CI 14.13; 98.00, p<0.001). All IG women with a positive CBE attended a follow-up mammogram (11/11). Attendance by IG women was lower among women with a household income ≥RM 4,850 (adjusted OR 0.48, 95% CI 0.20; 0.95, p = 0.038) compared to participants with a household income

CONCLUSION

The results suggested that the bespoke multicomponent mHealth intervention may be used to address the significant public health problem of low uptake of BC screening in rural Malaysia.

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Key Words Collapse

MESH Headings

• Female
• Humans
• Malaysia
• Pandemics
• COVID-19/diagnosis
• COVID-19/epidemiology
• Health Education
• Breast Neoplasms/epidemiology
• Telemedicine

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Grants

• MR/V005901/1 Medical Research Council
• 537084059 Medical Research Council
• MIGHT

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Affiliation(s)

Désirée Schliemann Centre for Public Health and UKCRC Centre of Excellence for Public Health, Queen’s University Belfast, Belfast, United Kingdom
Aminatul Saadiah Abdul Jamil South East Asia Community Observatory (SEACO), Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia Faculty of Science and Technology, Health Industry Technology, Islamic Science University of Malaysia, Nilai, Malaysia
Devi Mohan Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia
Min Min Tan South East Asia Community Observatory (SEACO), Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia
Christopher R. Cardwell Centre for Public Health and UKCRC Centre of Excellence for Public Health, Queen’s University Belfast, Belfast, United Kingdom
Roshidi Ismail South East Asia Community Observatory (SEACO), Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia
Nur Aishah Taib Department of Surgery, Faculty of Medicine, UM Cancer Research Institute, University of Malaya, Kuala Lumpur, Malaysia
Tin Tin Su South East Asia Community Observatory (SEACO), Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Malaysia
Michael Donnelly Centre for Public Health and UKCRC Centre of Excellence for Public Health, Queen’s University Belfast, Belfast, United Kingdom

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Wearables for Stress Management: A Scoping Review

In recent years, wearable devices have been increasingly used to monitor people's health. This has helped healthcare professionals provide timely interventions to support their patients. In this study, we investigated how wearables help people manage stress. We conducted a scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) standard to address this question. We searched studies in Scopus, IEEE Explore, and Pubmed databases. We included studies reporting user evaluations of wearable-based strategies, reporting their impact on health or usability outcomes. A total of 6259 studies were identified, of which 40 met the inclusion criteria. Based on our findings, we identified that 21 studies report using commercial wearable devices; the most common are smartwatches and smart bands. Thirty-one studies report significant stress reduction using different interventions and interaction modalities. Finally, we identified that the interventions are designed with the following aims: (1) to self-regulate during stress episodes, (2) to support self-regulation therapies for long-term goals, and (3) to provide stress awareness for prevention, consisting of people's ability to recall, recognize and understand their stress.

Nutrition and Diet Apps: Brazilian Panorama before and during the COVID-19 Pandemic

In the last decade, we have seen a substantial increase in the development and use of mobile technology to improve diet and healthy eating behaviors.

OBJECTIVE

To describe the characteristics of nutrition and diet apps before and after the COVID-19 pandemic available in Brazil.

METHODS

Nutrition and diet apps were identified using the official Apple and Google stores. The search occurred in January 2020 and May 2022 in Brazil. We extracted the nutritional content and standard indicators (e.g., being developed before or after 2020, number of languages, target population, investment, prices, seller, number of reviews and downloads, consumer rating).

RESULTS

280 apps were launched before and 411 during the COVID-19 period. Most apps were available in at least ten languages (96.6%), with no indication of age (95.6%) or partial or full cost (59%). As for the contents, 18.9% addressed personal diet suggestions; 73.4%, nutritional education; 48.8%, revenues; 35.9%, physical activity with a nutritional guide; 2.3%, nutritional recommendation for eating out; 23.9%, grocery shopping with a scan code; 32.4%, food diary; 18.9%, water intake; and 4.6%, nutrition/diseases. The data show an evolution that may have been boosted by the pandemic and that reveals a trend towards the development of apps with educational content.

CONCLUSION

During the pandemic, there was a positive qualitative and quantitative movement in e-health regarding the promotion of education.

Investigating Individuals' Preferences in Determining the Functions of Smartphone Apps for Fighting Pandemics: Best-Worst Scaling Survey Study

BACKGROUND

Smartphone apps have been beneficial in controlling and preventing the COVID-19 pandemic. However, there is a gap in research surrounding the importance of smartphone app functions from a user's perspective. Although the insights and opinions of different stakeholders, such as policymakers and medical professionals, can influence the success of a public health policy, any strategy will face difficulty in achieving the expected effect if it is not based on a method that users can accept.

OBJECTIVE

This study aimed to assess the importance of a hypothetical smartphone app's functions for managing health during a pandemic based on the perspective of user preferences.

METHODS

A cross-sectional and web-based survey using the best-worst scaling (BWS) method was used to investigate the general population's preferences for important smartphone app functions. Participants were recruited from a professional surveying company's web-based surveying panel. The attributes of the BWS questionnaire were developed based on a robust process, including literature review, interviews, and expert discussion. A balanced incomplete block design was used to construct the choice task to ensure the effectiveness of the research design. Count analysis, conditional logit model analysis, and mixed logit analysis were used to estimate preference heterogeneity among respondents.

RESULTS

The responses of 2153 participants were eligible for analysis. Nearly 55% (1192/2153) were female, and the mean age was 31.4 years. Most participants (1765/2153, 81.9%) had completed tertiary or higher education, and approximately 70% (1523/2153) were urban residents. The 3 most vital functions according to their selection were "surveillance and monitoring of infected cases," "quick self-screening," and "early detection of infected cases." The mixed logit regression model identified significant heterogeneity in preferences among respondents, and stratified analysis showed that some heterogeneities varied in respondents by demographics and COVID-19-related characteristics. Participants who preferred to use the app were more likely to assign a high weight to the preventive functions than those who did not prefer to use it. Conversely, participants who showed lower willingness to use the app tended to indicate a higher preference for supportive functions than those who preferred to use it.

CONCLUSIONS

This study ranks the importance of smartphone app features that provide health care services during a pandemic based on the general population's preferences in China. It provides empirical evidence for decision-makers to develop eHealth policies and strategies that address future public health crises from a person-centered care perspective. Continued use of apps and smart investment in digital health can help improve health outcomes and reduce the burden of disease on individuals and communities.

An interactive national digital surveillance system to fight against COVID-19 in Bangladesh

Background

COVID-19 has affected many people globally, including in Bangladesh. Due to a lack of preparedness and resources, Bangladesh has experienced a catastrophic health crisis, and the devastation caused by this deadly virus has not yet been halted. Hence, precise and rapid diagnostics and infection tracing are essential for managing the condition and limiting its spread. The conventional screening procedure, such as reverse transcription polymerase chain reaction (RT-PCR), is not available in most rural areas and is time-consuming. Therefore, a data-driven intelligent surveillance system can be advantageous for rapid COVID-19 screening and risk estimation.

Objectives

This study describes the design, development, implementation, and characteristics of a nationwide web-based surveillance system for educating, screening, and tracking COVID-19 at the community level in Bangladesh.

Methods

The system consists of a mobile phone application and a cloud server. The data is collected by community health professionals via home visits or telephone calls and analyzed using rule-based artificial intelligence (AI). Depending on the results of the screening procedure, a further decision is made regarding the patient. This digital surveillance system in Bangladesh provides a platform to support government and non-government organizations, including health workers and healthcare facilities, in identifying patients at risk of COVID-19. It refers people to the nearest government healthcare facility, collecting and testing samples, tracking and tracing positive cases, following up with patients, and documenting patient outcomes.

Results

This study began in April 2020, and the results are provided in this paper till December 2022. The system has successfully completed 1,980,323 screenings. Our rule-based AI model categorized them into five separate risk groups based on the acquired patient information. According to the data, around 51% of the overall screened populations are safe, 35% are low risk, 9% are high risk, 4% are mid risk, and the remaining 1% is very high risk. The dashboard integrates all collected data from around the nation onto a single platform.

Conclusion

This screening can help the symptomatic patient take immediate action, such as isolation or hospitalization, depending on the severity. This surveillance system can also be utilized for risk mapping, planning, and allocating health resources to more vulnerable areas to reduce the virus's severity.

A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs)

With the numerous advances and broad applications of mobile health (mHealth), establishing concrete data sharing, privacy, and governance strategies at national (or regional) levels is essential to protect individual privacy and data usage. This article applies the recent Health Data Governance Principles to provide a guiding framework for low- and middle-income countries (LMICs) to create a comprehensive mHealth data governance strategy. We provide three objectives: (1) establish data rights and ownership to promote equitable benefits from health data, (2) protect people through building trust and addressing patients' concerns, and (3) promote health value by enhancing health systems and services. We also recommend actions for realizing each objective to guide LMICs based on their unique mHealth data ecosystems. These objectives require adopting a regulatory framework for data rights and protection, building trust for data sharing, and enhancing interoperability to use new datasets in advancing healthcare services and innovation.

Mobile applications in the Philippines during the COVID-19 pandemic: systematic search, use case mapping, and quality assessment using the Mobile App Rating Scale (MARS)

Background

In the Philippines, various mobile health apps were implemented during the COVID-19 pandemic with very little knowledge in terms of their quality. The aims of this paper were 1) to systemically search for mobile apps with COVID-19 pandemic use case that are implemented in the Philippines; 2) to assess the apps using Mobile App Rating Scale (MARS); and 3) to identify the critical points for future improvements of these apps.

Methods

To identify existing mobile applications with COVID-19 pandemic use case employed in the Philippines, Google Play and Apple App Stores were systematically searched. Further search was conducted using the Google Search. Data were extracted from the app web store profile and apps were categorized according to use cases. Mobile apps that met the inclusion criteria were independently assessed and scored by two researchers using the MARS-a 23-item, expert-based rating scale for assessing the quality of mHealth applications.

Results

A total of 27 apps were identified and assessed using MARS. The majority of the apps are designed for managing exposure to COVID-19 and for promoting health monitoring. The overall MARS score of all the apps is 3.62 points (SD 0.7), with a maximum score of 4.7 for an app used for telehealth and a minimum of 2.3 for a COVID-19 health declaration app. The majority (n = 19, 70%) of the apps are equal to or exceeded the minimum "acceptable" MARS score of 3.0. Looking at the categories, the apps for raising awareness received the highest MARS score of 4.58 (SD 0.03) while those designed for managing exposure to COVID-19 received the lowest mean score of 3.06 (SD 0.6).

Conclusions

There is a heterogenous quality of mHealth apps implemented during the COVID-19 pandemic in the Philippines. The study also identified areas to better improve the tools. Considering that mHealth is expected to be an integral part of the healthcare system post-pandemic, the results warrant better policies and guidance in the development and implementation to ensure quality across the board and as a result, positively impact health outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44247-023-00007-2.

Understanding Post-Adoption Behavioral Intentions of Mobile Health Service Users: An Empirical Study during COVID-19

This study aims to understand the post-adoption behaviors of mobile health (m-Health) service users during the COVID-19 pandemic. Drawing on the stimulus-organism-response framework, we examined the effects of user personality traits, doctor characteristics, and perceived risks on user continuance intentions and positive word of mouth (WOM) when using m-Health, as mediated by cognitive and emotional trust. The empirical data were collected via an online survey questionnaire from 621 m-Health service users in China and were verified with partial least squares structural equation modeling. The results showed that personal traits and doctor characteristics were positively associated and the perceived risks were negatively associated with both cognitive and emotional trust. Both cognitive and emotional trust significantly influenced users' post-adoption behavioral intentions in terms of continuance intentions and positive WOM, with different magnitudes. This study provides new insights for the promotion of the sustainable development of m-Health businesses after or during the pandemic.

Developing and Evaluating a Measure of the Willingness to Use Pandemic-Related mHealth Tools Using National Probability Samples in the United States: Quantitative Psychometric Analyses and Tests of Sociodemographic Group Differences

BACKGROUND

There are no psychometrically validated measures of the willingness to engage in public health screening and prevention efforts, particularly mobile health (mHealth)-based tracking, that can be adapted to future crises post-COVID-19.

OBJECTIVE

The psychometric properties of a novel measure of the willingness to participate in pandemic-related screening and tracking, including the willingness to use pandemic-related mHealth tools, were tested.

METHODS

Data were from a cross-sectional, national probability survey deployed in 3 cross-sectional stages several weeks apart to adult residents of the United States (N=6475; stage 1 n=2190, 33.82%; stage 2 n=2238, 34.56%; and stage 3 n=2047, 31.62%) from the AmeriSpeak probability-based research panel covering approximately 97% of the US household population. Five items asked about the willingness to use mHealth tools for COVID-19-related screening and tracking and provide biological specimens for COVID-19 testing.

RESULTS

In the first, exploratory sample, 3 of 5 items loaded onto 1 underlying factor, the willingness to use pandemic-related mHealth tools, based on exploratory factor analysis (EFA). A 2-factor solution, including the 3-item factor, fit the data (root mean square error of approximation [RMSEA]=0.038, comparative fit index [CFI]=1.000, standardized root mean square residual [SRMR]=0.005), and the factor loadings for the 3 items ranged from 0.849 to 0.893. In the second, validation sample, the reliability of the 3-item measure was high (Cronbach α=.90), and 1 underlying factor for the 3 items was confirmed using confirmatory factor analysis (CFA): RMSEA=0, CFI=1.000, SRMR=0 (a saturated model); factor loadings ranged from 1.000 to 0.962. The factor was independently associated with COVID-19-preventive behaviors (eg, "worn a face mask": r=0.313, SE=0.041, P<.001; "kept a 6-foot distance from those outside my household": r=0.282, SE=0.050, P<.001) and the willingness to provide biological specimens for COVID-19 testing (ie, swab to cheek or nose: r=0.709, SE=0.017, P<.001; small blood draw: r=0.684, SE=0.019, P<.001). In the third, multiple-group sample, the measure was invariant, or measured the same thing in the same way (ie, difference in CFI [ΔCFI]<0.010 across all grouping categories), across age groups, gender, racial/ethnic groups, education levels, US geographic region, and population density (ie, rural, suburban, urban). When repeated across different samples, factor-analytic findings were essentially the same. Additionally, there were mean differences (ΔM) in the willingness to use mHealth tools across samples, mainly based on race or ethnicity and population density. For example, in SD units, suburban (ΔM=-0.30, SE=0.13, P=.001) and urban (ΔM=-0.42, SE=0.12, P<.001) adults showed less willingness to use mHealth tools than rural adults in the third sample collected on May 30-June 8, 2020, but no differences were detected in the first sample collected on April 20-26, 2020.

CONCLUSIONS

Findings showed that the screener is psychometrically valid. It can also be adapted to future public health crises. Racial and ethnic minority adults showed a greater willingness to use mHealth tools than White adults. Rural adults showed more mHealth willingness than suburban and urban adults. Findings have implications for public health screening and tracking and understanding digital health inequities, including lack of uptake.

SMS-based digital health intervention in Rwanda's home-based care program for remote management of COVID-19 cases and contacts: A qualitative study of sustainability and scalability

Background

COVID-19 pandemic resulted in unprecedented global health challenges. Rwanda identified its first COVID-19 case on March 14, 2020 and subsequently introduced Home-Base Care (HBC) Program in August 2020 following community transmission of the virus and to alleviate logistical and financial strain on the healthcare system. Cases and contacts eligible for HBC were remotely supported by WelTel, an SMS-based mHealth intervention that was successfully implemented before for HIV epidemic in Rwanda. Enrolled cases and contacts were supported and monitored daily via their cell and/or mobile phones until they complete isolation/quarantine period. This study explored the rationale, perspectives, and experiences of key informants (KIs) during the implementation WelTel's mHealth tool for HBC in Rwanda.

Methods

Semi-structured one-on-one virtual interviews were conducted with KIs in this qualitative study. The KIs were classified into 2 major categories: (A) Senior staff including policymakers, directors, and senior managers; (B) Technical teams including case managers, and other staff supporting the implementation of WelTel (e.g., IT staff). Interviews were audio-recorded, transcribed, and analyzed in NVivo. Thematic analysis was conducted using a hybrid approach. A topic guide was developed using the Modified Consolidated Framework for Implementation Research and feedback from local stakeholders.

Results

7 KIs were interviewed. Five themes emerged following thematic analysis including: SMS-Based mHealth for Home-Isolation; Facilitators for Intervention Adoption; Barriers for Intervention Adoption; Infection prevention and control for Home-Isolation; and SMS-Based mHealth for Future Pandemics and Epidemics. Based on interviews, strong political commitment and advanced digital infrastructure were major facilitators for adopting WelTel for HBC. A major barrier to adopting WelTel was identified as technical-based issues. This was followed by local communication culture. All participates agreed on the significance of using WelTel to improve access and adherence to infection prevention and control measures, understand transmission dynamics, and inform public health decision-making regarding HBC.

Conclusions

Rwanda successfully adopted WelTel for supporting and monitoring COVID-19 cases and contacts in home-isolation and the implementation was instrumental to the country's effort to manage the pandemic. Experiences and perspectives of cases and contacts enrolled into WelTel must be explored to understand the appropriateness and effectiveness of the intervention.

End-users' perspectives on the quality and design of mHealth technologies during the COVID-19 pandemic in the Philippines: A Qualitative Study

BACKGROUND

The COVID-19 pandemic has expanded the use of mHealth technologies in contact tracing, communicating COVID-related information, and monitoring the health conditions of the general population in the Philippines. However, the limited end-user engagement in the features and feedback along the development cycle of mHealth technologies results to risks in adoption. The WHO recommends user-centric design and development of mHealth technologies to ensure responsiveness to the needs of the end-users.

OBJECTIVE

The goal of the study is to understand, using the end-users' perspectives, the design and quality of mHealth technology implementations in the Philippines during the COVID-19 pandemic with focus on areas identified by stakeholders: 1) utility, 2) technology readiness level, 3) design, 4) information, 5) usability, 6) features, and 7) security and privacy.

METHODS

Using a descriptive qualitative design, we conducted five interviews and three FGDs with a total of 16 participants, six males and ten females. Questions were based on the Mobile App Rating Scale (MARS). Utilizing the cyclical coding approach, transcripts were analyzed using NVivo 12. Domains and themes were identified.

RESULTS

The qualitative analysis identified eighteen themes that were organized under the seven focus areas: 1) utility: use of mHealth technologies; motivations in using mHealth; 2) technology readiness: mobile technology literacy, user segmentation; 3) design: user interface design, language and content accessibility, and technology design; 4) information: accuracy of information, use of information; 5) usability: design factors, dependency on human processes, and technical issues; 6) features: interoperability and data integration, other feature and design recommendations, and technology features and upgrades, and 7) privacy and security: trust that mHealth can secure data, lack of information, and policies. To highlight, accessibility, privacy and security, simple interface, and integration are some of the design and quality areas that end-users find important and consider in using mHealth tools.

CONCLUSIONS

Engaging end-users in the development and design of mHealth technologies ensures adoption and accessibility making it a valuable tool in curbing the pandemic. The six principles for developers, researchers, and implementers to consider when scaling up or developing new mHealth solutions in low resource settings are: 1) should be driven by value in its implementation; 2) should be inclusive; 3) addresses users' physical and cognitive restrictions; 4) ensures privacy and security; 5) designed in accordance to digital health systems' standards; and 6) should be trusted by the end-users.

CLINICALTRIAL

Development and Usability Assessment of a Mobile App (Demensia KITA) to Support Dementia Caregivers in Malaysia: A Study Protocol

The impact of dementia on caregivers is complex and multi-dimensional. In low- and middle-income settings, caregivers are often left without adequate support, despite their multiple needs. These include health information, caregiving skills, social and emotional support, and access to local resources-all of which can be partially fulfilled by technology. In recent years, mobile apps have emerged and proven useful for caregivers. We found a few existing apps suitable for Malaysian users in terms of affordability and cultural and linguistic compatibility. Our study aims to design a mobile app that suits dementia caregivers in Malaysia and consists of three phases. Phase I is content development that employs Focus Group Discussion (FGD) and Nominal Group Technique (NGT) involving field experts. Phase II comprises a mobile app (Demensia KITA) designed in collaboration with a software developer specializing in mobile health apps. Phase III entails testing the usability of the app using the Malay version of the mHealth App Usability Questionnaire (M-MAUQ). This study protocol elaborates on the rigorous steps of designing a mobile app and testing its usability, along with anticipated challenges. Our protocol will provide insight for future researchers, healthcare providers, and policymakers and pave the way for better use of digital technology in the field of aging and caregiving.

COVID-19 Mobile Health Apps: An Overview of Mobile Applications in Indonesia

Background

Mobile health applications (mHealth apps) have been widely used for various purposes for mitigating the COVID-19 pandemic, such as self-assessment, contact tracing, disseminating information, minimizing exposure, and reducing face-to-face health consultation. The objective of this study is to systematically review COVID-19 related mHealth apps and highlight gaps to inform the development of future mHealth initiatives in Indonesia.

Methods

A systematic search strategy using a PRISMA flowchart was used to identify mHealth apps available in Google Play and Apple Play stores. We searched mHealth apps using certain specific terms related to COVID-19 outbreaks. The inclusion criteria were apps-based smartphone users related to COVID-19 using local language, free of cost, available in the Google Play and Apple Play Stores, and supported by the Indonesian government. We excluded games, apps on infectious diseases unrelated to COVID-19 specifically, and apps with non-Bahasa Indonesia (Indonesian language). The selected mHealth apps were assessed based on two measures: (1) the WHO guidelines on digital health intervention and (2) the four dimensions of the mHealth technology fit framework. In addition, user feedback from experienced and non-experienced users was conducted to evaluate four dimensions of the apps.

Results

A total of 339 mHealth apps were generated from the initial search, remaining seven selected apps that met inclusion criteria. The results highlighted that mHealth apps reviewed had still not been widely used by the general public. The applications were purposed to disseminate information, conduct a self-risk assessment, provide an online community forum, and telemedicine or teleconsultation regarding COVID-19. Data services, including data storage, aggregation, and data exchange, are available in most apps. The rarest function found was contact tracing and assisting health management and health workers, such as the availability of testing facilities, reporting test results, and prescribing medication. The main issues reported were the lack of data security and data privacy protection, integration and infrastructures, usability, and usefulness.

Conclusion

Our study highlighted the necessity to improve mHealth apps' functions related to assisting health workers and the function of digital contact tracing. An effort to increase public awareness regarding the use of mHealth is also necessary to streamline the function of this innovation. Policymakers must consider usefulness, usability, integration, and infrastructure issues to improve their mHealth function.

Interaction Empowerment in Mobile Health: Concepts, Challenges, and Perspectives

In its most trending interpretation, empowerment in health care is implemented as a patient-centered approach. In the same sense, many mobile health (mHealth) apps are being developed with a primary focus on the individual user. The integration of mHealth apps into the health care system has the potential to counteract existing challenges, including incomplete or nonstandardized medical data and lack of communication, especially in the intersectional context (eg, patients, medical forces). However, concerns about data security and privacy, regional differences in regulations, lack of accessibility, and nontransparent apps hinder the successful integration of mHealth into the health care system. One approach to address this is to rethink the interpretation of empowerment. On that basis, we here examine existing approaches of individual empowerment and subsequently analyze a different view of empowerment in digital health, namely interaction empowerment. Such a change of perspective could positively influence intersectoral communication and facilitate secure data and knowledge sharing. We discuss this novel viewpoint on empowerment, focusing on more efficient integration and development of mHealth approaches. A renewed interpretation of empowerment could thus buffer current limitations of individual empowerment while also advancing digitization of the health system.

A framework for information technology-based management against COVID-19 in Iran

Background

The COVID-19 pandemic has become a global concern. Iran is one of the countries affected most by the SARS-CoV-2 outbreak. As a result, the use of information technology (IT) has a variety of applications for pandemic management. The purpose of this study was to develop a conceptual framework for responding to the COVID-19 pandemic via IT management, based on extensive literature review and expert knowledge.

Methods

The conceptual framework is developed in three stages: (1) a literature review to gather practical experience with IT applications for managing the COVID-19 pandemic, (2) a study of Iranian documents and papers that present Iran’s practical experience with COVID-19, and (3) developing a conceptual framework based on the previous steps and validating it through a Delphi approach in two rounds, and by 13 experts.

Results

The proposed conceptual framework demonstrates that during pandemics, 22 different types of technologies were used for various purposes, including virtual education, early warning, rapid screening and diagnosis of infected individuals, and data management. These objectives were classified into six categories, with the following applications highlighted: (1) Prevention (M-health, Internet search queries, telehealth, robotics, Internet of things (IoT), Artificial Intelligence (AI), big data, Virtual Reality (VR), social media); (2) Diagnosis (M-health, drones, telehealth, IoT, Robotics, AI, Decision Support System (DSS), Electronic Health Record (EHR)); (3) Treatment (Telehealth, M-health, AI, Robotic, VR, IoT); (4) Follow-up (Telehealth, M-health, VR), (5) Management & planning (Geographic information system, M-health, IoT, blockchain), and (6) Protection (IoT, AI, Robotic and automatic vehicles, Augmented Reality (AR)). In Iran, the use of IT for prevention has been emphasized through M-health, internet search queries, social media, video conferencing, management and planning objectives using databases, health information systems, dashboards, surveillance systems, and vaccine coverage.

Conclusions

IT capabilities were critical during the COVID-19 outbreak. Practical experience demonstrates that various aspects of information technologies were overlooked. To combat this pandemic, the government and decision-makers of this country should consider strategic planning that incorporates successful experiences against COVID-19 and the most advanced IT capabilities.

The Effect of M-Health-Based Core Stability Exercise Combined with Self-Compassion Training for Patients with Nonspecific Chronic Low Back Pain: A Randomized Controlled Pilot Study

Introduction

Nonspecific chronic low back pain (NCLBP) is a leading contributor to disease burden worldwide, and the management of NCLBP has always been a problem. This study is designed to explore the feasibility and efficacy of m-health-based core stability exercise (CSE) combined with self-compassion training (SCT) and compare it with m-health-based CSE alone for the management of NCLBP.

Methods

This study is a pilot, patient-blinded randomized controlled trial. Participants with NCLBP were randomized into an intervention group and a control group. All the participants received m-health-based CSE, but those in the intervention group also received SCT before CSE. The intervention took place weekly on Saturday or Sunday for 4 weeks in total. Patients self-assessed their outcomes by filling out electronic questionnaires at 4 and 16 weeks after the start of the study. The primary outcome metrics for these questionnaires were back pain disability (based on the Roland–Morris Disability Questionnaire, RMDQ) and Pain intensity (Numeric Rating Scale, NRS; current pain, worst pain, average pain). The secondary outcome metrics were anxiety (GAD-7,7-item Generalized Anxiety Disorder scale), Depression Symptoms (PHQ-9,Patient Health Questionnaire-9), pain catastrophizing (PCS, Pain Catastrophizing Scale) and Self-efficiency (PSEQ, Pain Self-Efficiency Questionnaire).

Results

A total of 37 patients comprising 28 (75.7%) females completed the study, with 19 patients in the intervention group and 18 in the control group. The mean (SD) patient age was 35.2 (11.1) years. For all primary outcomes, although there were no significant differences between groups, we found that participants in the intervention group improved function and pain earlier. The RMDQ score changed by − 1.771 points (95% CI − 3.768 to 0.227) from baseline to 4 weeks in the control group and by − 4.822 points (95% CI − 6.752 to − 2.892) in the intervention group (difference between groups, − 3.052 [95% CI − 5.836 to − 0.267]). Also, the RMDQ score changed by − 3.328 points (95% CI − 5.252 to − 1.403) from baseline to 16 weeks in the control group and by − 5.124 points (95% CI − 7.014 to − 3.233) in the intervention group (difference between groups − 1.796 [95% CI − 4.501 to 0.909]). A similar pattern was found in the NRS scores. For secondary outcomes, the intervention group was superior to the control group in for GAD-7 (intervention difference from CSE along at week 16, − 2.156 [95% CI − 4.434 to − 0.122; P value for group effect was 0.030]). At the end of treatment, the improvement in PCS in the intervention group was significant (difference in PCS score at week 4, − 6.718 [95% CI − 11.872 to − 1.564]). We also found significant changes in PCS in the control group (− 6.326 [95% CI, − 11.250 to − 1.401]) at the 16-week follow-up. As for PSEQ, there were no apparent differences between the two groups. There were no adverse events relented to study participation.

Conclusions

The pilot study is feasible to deliver, and our results indicate that participants in the group of m-health-based CSE combined with SCT may experience faster relief from pain intensity and back disability than those in the group of m-health-based CSE alone.

Trial Registration

ChiCTR2100042810.

The impact of chronic low back pain on people’s life quality and social economy is increasing year by year. Helping patients self-manage low back pain through a biological-psycho-social model seems to be an effective management approach, but the lack of connectivity between disciplines limits the development of multidisciplinary collaboration. Mindfulness-related therapy (self-compassion training) has been proven to be effective in chronic pain, and exercise therapy is widely used in rehabilitation medicine. In this study, these two programs were combined. We also used mobile health technology in the study, which brings a lot of convenience for research. The results of the study showed that the efficacy of the combined group seemed to be more obvious and worthy of further study.

Mobile technology: A tool for healthcare and a boon in pandemic

Healthcare systems deal with disease prevention, early detection, diagnosis, investigation, and timely, affordable, and safe treatment. For the delivery of services in the health sector, communication is the key to linking the service provider and the patients. Mobile technology in the recent past has rendered various platforms of communications for the healthcare system. Thus, in health, mobile technology has greatly contributed to time management and cost reduction for healthcare at every level including hospital visits to individual appointments with doctors, hence the convenience. With advancements in mobile technologies and the growing number of mobile users, newer opportunities have opened up for the use of mobiles for patient care. Emerging information and communication technologies with the help of the Internet of Things (IoT) have been instrumental in integrating different domains of the health sector with mobile technology. Thus, the technology may have the potential to become powerful medical tools to support the health sector at all levels of care. In this review, the concept, applications, and advantages of mobile technology for health and the present pandemic have been discussed. It also discusses mobile health technology, as a support system for convenient and safer healthcare for public health, and the opportunities to improve its applications for unseen future health crises.

A multi-method analytical approach to predicting young adults' intention to invest in mHealth during the COVID-19 pandemic

Mobile-based health (mHealth) systems are proving to be a popular alternative to the traditional visits to healthcare providers. They can also be useful and effective in fighting the spread of infectious diseases, such as the COVID-19 pandemic. Even though young adults are the most prevalent mHealth user group, the relevant literature has overlooked their intention to invest in and use mHealth services. This study aims to investigate the predictors that influence young adults' intention to invest in mHealth (IINmH), particularly during the COVID-19 crisis, by designing a research methodology that incorporates both the health belief model (HBM) and the expectation-confirmation model (ECM). As an expansion of the integrated HBM-ECM model, this study proposes two additional predictors: mobile Internet speed and mobile Internet cost. A multi-method analytical approach, including partial least squares structural equation modelling (PLS-SEM), fuzzy-set qualitative comparative analysis (fsQCA), and machine learning (ML), was utilised together with a sample dataset of 558 respondents. The dataset-about young adults in Bangladesh with an experience of using mHealth-was obtained through a structured questionnaire to examine the complex causal relationships of the integrated model. The findings from PLS-SEM indicate that value-for-money, mobile Internet cost, health motivation, and confirmation of services all have a substantial impact on young adults' IINmH during the COVID-19 pandemic. At the same time, the fsQCA results indicate that a combination of predictors, instead of any individual predictor, had a significant impact on predicting IINmH. Among ML methods, the XGBoost classifier outperformed other classifiers in predicting the IINmH, which was then used to perform sensitivity analysis to determine the relevance of features. We expect this multi-method analytical approach to make a significant contribution to the mHealth domain as well as the broad information systems literature.

Mobile Apps Leveraged in the COVID-19 Pandemic in East and South-East Asia: Review and Content Analysis

Background

The COVID-19 pandemic increased attention to digital tools to support governmental public health policies in East and South-East Asia. Mobile apps related to the COVID-19 pandemic continue to emerge and evolve with a wide variety of characteristics and functions. However, there is a paucity of studies evaluating such apps in this region, with most of the available studies conducted in the early days of the pandemic.

Objective

This study aimed to examine free apps developed or supported by governments in the East and South-East Asian region and highlight their key characteristics and functions. We also sought to interpret how the release dates of these apps were related to the commencement dates of other COVID-19 public health policies.

Methods

We systematically searched for apps in Apple App Store and Google Play Store and analyzed the contents of eligible apps. Mobile apps released or updated with COVID-19–related functions between March 1 and May 7, 2021, in Singapore, Taiwan, South Korea, China (mainland), Japan, Thailand, Hong Kong, Vietnam, Malaysia, Indonesia, and the Philippines were included. The CoronaNet Research Project database was also examined to determine the timeline of public health policy commencement dates in relation to the release dates of the included apps. We assessed each app’s official website, media reports, and literature through content analysis. Descriptive statistics were used to summarize relevant information gathered from the mobile apps using RStudio.

Results

Of the 1943 mobile apps initially identified, 46 were eligible, with almost 70% of the apps being intended for the general public. Most apps were from Vietnam (n=9, 20%), followed by Malaysia, Singapore, and Thailand (n=6 each, 13%). Of note, most apps for quarantine monitoring (n=6, 13%) were mandatory for the target users or a population subset. The most common function was health monitoring (32/46, 70%), followed by raising public health awareness (19/46, 41%) through education and information dissemination. Other functions included monitoring quarantine (12/46, 26%), providing health resources (12/46, 26%). COVID-19 vaccination management functions began to appear in parallel with vaccine rollout (7/46, 15%). Regarding the timing of the introduction of mobile solutions, the majority of mobile apps emerged close to the commencement dates of other public health policies in the early stages of the pandemic between March and April 2020.

Conclusions

In East and South-East Asia, most governments used mobile health apps as adjuncts to public health measures for tracking COVID-19 cases and delivering credible information. In addition, these apps have evolved by expanding their functions for COVID-19 vaccination.

Intelligent health system for the investigation of consenting COVID-19 patients and precision medicine

Advancing frontiers of clinical research, we discuss the need for intelligent health systems to support a deeper investigation of COVID-19. We hypothesize that the convergence of the healthcare data and staggering developments in artificial intelligence have the potential to elevate the recovery process with diagnostic and predictive analysis to identify major causes of mortality, modifiable risk factors and actionable information that supports the early detection and prevention of COVID-19. However, current constraints include the recruitment of COVID-19 patients for research; translational integration of electronic health records and diversified public datasets; and the development of artificial intelligence systems for data-intensive computational modeling to assist clinical decision making. We propose a novel nexus of machine learning algorithms to examine COVID-19 data granularity from population studies to subgroups stratification and ensure best modeling strategies within the data continuum.