MFS Design in Appstore-enabled Smart Featurephones for Low-literate, Marginalized Communities

Mobile Financial Services (MFS) has gained significant popularity during the COVID-19 pandemic, especially among marginalized and low-income, low-literate communities around the world. Such communities have not been traditionally considered while designing MFS services via smartphone apps or USSD services in featurephones. Financial constraints limit such end-users towards basic featurephones, where recent appstore support has made it possible to deploy app-based MFS solutions beyond USSD. This new featurephone platform is a relatively underexplored area in terms of addressing design issues related to aforementioned end-users while developing MFS solutions. Our work addresses this gap by presenting qualitative findings on barriers to technology access focused on MFS solutions in marginal communities. We present a prototype non-USSD, app-based solution on an appstore-supported featurephone platform designed via a human-centered approach. This work has the potential to increase the financial inclusivity of marginalized communities in cashless MFS transactions via low-cost, appstore-enabled featurephones. © 2023 ACM.

The shock, the coping, the resilience: smartphone application use reveals Covid-19 lockdown effects on human behaviors.

Human mobility restriction policies have been widely used to contain the coronavirus disease-19 (COVID-19). However, a critical question is how these policies affect individuals' behavioral and psychological well-being during and after confinement periods. Here, we analyze China's five most stringent city-level lockdowns in 2021, treating them as natural experiments that allow for examining behavioral changes in millions of people through smartphone application use. We made three fundamental observations. First, the use of physical and economic activity-related apps experienced a steep decline, yet apps that provide daily necessities maintained normal usage. Second, apps that fulfilled lower-level human needs, such as working, socializing, information seeking, and entertainment, saw an immediate and substantial increase in screen time. Those that satisfied higher-level needs, such as education, only attracted delayed attention. Third, human behaviors demonstrated resilience as most routines resumed after the lockdowns were lifted. Nonetheless, long-term lifestyle changes were observed, as significant numbers of people chose to continue working and learning online, becoming "digital residents." This study also demonstrates the capability of smartphone screen time analytics in the study of human behaviors. Supplementary Information: The online version contains supplementary material available at 10.1140/epjds/s13688-023-00391-9.

Origin Destination Estimation Carrying over Rolling Proximity Identifiers with RSSI

Origin destination (OD) data describing passengers' flows is essential for improving bus route operational efficiency. Manual collection of OD data is still conducted, so automatic OD data acquisition using the internet of things (IoT) is desired. One method utilizes Bluetooth beacon identifiers to understand passengers' flows while considering their privacy. Still, while random MAC addresses can estimate the number of devices there, they are insufficient for generating ODs. In contrast, in response to the COVID-19 pandemic, the government promoted the exposure notification system to prevent secondary infection. The smartphone app exchanges short-term identifiers called Rolling Proximity Identifiers (RPIs), updated every 15 minutes. This research aims to realize tracking during bus rides with only a few RPIs carryovers, since bus rides are only about an hour long at most. We evaluated the system on a bus in Kyoto City and successfully tracked passengers for 55 minutes, the experiment's maximum length. © 2022 IEEE.

On the voluntariness of public health apps: a European case study on digital contact tracing

As evidenced during the COVID-19 pandemic, there is a growing reliance on smartphone apps such as digital contact tracing apps and vaccination passports to respond to and mitigate public health threats. In light of the European Commission's guidance, Member States typically offer such apps on a voluntary, ‘opt-in' basis. In this paper, we question the extent to which the individual choice to use these apps–and similar future technologies–is indeed a voluntary one. By explicating ethical and legal considerations governing the choice situations surrounding the use of smartphone apps, specifically those related to the negative consequences that declining the use of these apps may have (e.g. loss of opportunities, social exclusion, stigma), we argue that the projected downsides of refusal may in effect limit the liberty to decline for certain subpopulations. To mitigate these concerns, we recommend three categories of approaches that may be employed by governments to safeguard voluntariness. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Mobile opportunity against stress: Open study protocol on the effectiveness of a mobile platform for stress self-management in the post-pandemic era.

Mobile health platforms have shown promise in the management of various mental health conditions (including stress, anxiety, and depression) and cognitive behavioral strategies emerged as a popular and effective option offered by the platforms. This paper presents the protocol of a study aimed to test the effectiveness of a mobile platform that uses cognitive-behavioral strategies for stress self-management in the Tuscany region (Italy). The mobile app is adapted to the specific needs of each vulnerable population for which it is designed: young and older people, healthcare professionals, entrepreneurs. The app will be evaluated on the following outcomes: (i) perceived susceptibility and severity of the pandemic situation, perceived benefits, and costs of preventive health behaviors, (ii) knowledge about Covid-19 preventive behaviors and negative consequences of social distancing, (iii) stress and psychopathological symptoms (i.e., anxiety, depression, and post-traumatic stress symptoms) and cognitive distortions. If successful, we expect that the platform could give various groups clinical benefits by providing symptom self-monitoring and early intervention, consolidating the number of mental health programs available, and decreasing barriers to treatment-seeking. This population-level approach has the potential to improve mental health outcomes in pandemic periods for many people.

Smartphone apps for mental health and wellbeing: A usage survey and machine learning analysis of psychological and behavioral predictors.

Objective: Despite the availability of thousands of mental health applications, the extent to which they are used and the factors associated with their use remain largely unknown. The present study aims to (a) assess in a representative US-based population sample the use of smartphone apps for mental health and wellbeing (SAMHW), (b) determine the variables predicting the use of SAMHW, and (c) explore how a set of variables related to mental health, smartphone use, and smartphone "addiction" may be associated with the use of SAMHW. Methods: Data was collected via online questionnaire from 1989 adults. The data gathered included information on smartphone use behavior, mental health, and the use of SAMHW. Latent class analysis was used to categorize participants. Machine learning and logistic regression analyses were used to determine the most important predictors of SAMHW use and associations between predictors and outcome variables. Results: While two-thirds of participants had a statistically high probability for using SAMHW, nearly twice more had high probability for using them to improve wellbeing compared to using them to address mental health problems (43% vs. 18%). In both groups, these participants were more likely to be female and in the younger adult age bracket than male and in the adult or older adult age bracket. According to the machine learning model, the most important predictors for using the relevant smartphone apps were variables associated with smartphone problematic use, COVID-19 impact, and mental health problems. Conclusion: Findings from the present study confirm that the use of SAMHW is growing, particularly among younger adult and female individuals who are negatively impacted by problematic smartphone use, COVID-19, and mental health problems. These individuals tend to bypass traditional care via psychotherapy or psychopharmacology, relying instead on smartphones to address mental health conditions or improve wellbeing. Advising users of these apps to also seek professional help and promoting efforts to prove the efficacy and safety of SAMHW would seem necessary.

Beyond the Pandemic and Privacy Concerns: Perceived Benefit and Expected Use of Pandemic-Tracking Apps in India

Pandemic-tracking apps could be a viable pandemic-mitigation technique, although their efficacy has been weakened by limited adoption in many places. Therefore, it is important to investigate how the perceptions of such apps are formed in different regions, which may help explain the differences in adoption. We replicated prior work on the adoption of pandemic-tracking apps in the United States with participants from India (n = 236). We identified that the perceptions of pandemic-tracking apps are connected to social orientation, familiarity with health-related technology, and demographics. We found that the perceptions and expected use were uncorrelated with privacy concerns, suggesting that privacy may not necessarily be the most suitable lens for studying the adoption of pandemic-tracking apps in India. Based on the findings, we make several recommendations for future pandemic-preparedness campaigns and identify the need to continue the trend toward contextualizing privacy-centered research with privacy-adjacent individual factors across multiple regions. © 2022 Owner/Author.

COVID-19 Infection Risk Assessment for Shoppers in Retail Stores

Over the last few years, a large number of smartphone apps have been developed to 'flatten the curve' of the rising number of COVID-19 infections. Knowledge of potential symptoms and their distribution enables the early identification of infected individuals. We developed a mobile app-based crowdsourcing methodology to assess the COVID-19 infection risk through shopping habits at indoor retail stores. The app's goal is to instil trust in customers to visit stores, which will assist small and medium businesses to survive their operations in the near term. According to the literature, there are several implementations for COVID-19 infection risk estimations for such scenarios. A mobile app prototype was developed, and the risk was calculated using the COVID-19 Aerosol Transmission Estimator model established by the University of Colorado Boulder. The developed prototype mobile app was tested with end users to gather their feedback through a questionnaire. In comparison to the complex implementation associated with AI-based alternatives, this solution could be delivered at a lower cost with adequate accuracy of COVID-19 infection risk assessments. © 2022 IEEE.

Augmented Reality in Clothing Consumer Customization in COVID-19 Pandemic: A Preliminary Study

Emergencies produce significant changes in people's habits and lifestyles. Further, it also impacts our clothing tastes and preferences because social interaction is reduced, and everyday activities are performed at home. Thus, this paper shows a psychographic analysis to determine the type, style, color, and other clothing characteristics users preferred across the pandemic. In addition, some considerations have been taken into account to understand the clothing characteristics users will look for in post-pandemic presential jobs. In this context, the first version of a smartphone app using augmented reality (AR) has been developed. Three-dimensional objects were designed using Blender, while the smartphone app was set up using Unity, accompanied by modules such as AR Foundation, ARCore XR Plugin, and DOTween. The application allows the overview of the selected three-dimensional garment and relevant information about its components. Statistical analysis shows a vital essential between the monthly income of the participants and their purchasing decision;likewise, between sex and upper garments usage. Experimental tests inside a retail store validate this proposal throughout a new sample of 44 people. Ultimately, they filled out a usability test (SUS) that confirmed the application acceptance with an 82.73%. Finally, they gave the corresponding feedback on their experience using the app. Consequently, relevant information that might be used in future research to understand the consumer needs in a matter of clothing emergencies or confinement is passing through has been exposed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Promoting Hand Hygiene During the COVID-19 Pandemic: Parallel Randomized Trial for the Optimization of the Soapp App.

BACKGROUND: Hand hygiene is an effective behavior for preventing the spread of the respiratory disease COVID-19 and was included in public health guidelines worldwide. Behavior change interventions addressing hand hygiene have the potential to support the adherence to public health recommendations and, thereby, prevent the spread of COVID-19. However, randomized trials are largely absent during a pandemic; therefore, there is little knowledge about the most effective strategies to promote hand hygiene during an ongoing pandemic. This study addresses this gap by presenting the results of the optimization phase of a Multiphase Optimization Strategy of Soapp, a smartphone app for promoting hand hygiene in the context of the COVID-19 pandemic. OBJECTIVE: This study aimed to identify the most effective combination and sequence of 3 theory- and evidence-based intervention modules (habit, motivation, and social norms) for promoting hand hygiene. To this end, 9 versions of Soapp were developed (conditions), and 2 optimization criteria were defined: the condition with the largest increase in hand hygiene at follow-up and condition with the highest engagement, usability, and satisfaction based on quantitative and qualitative analyses. METHODS: This study was a parallel randomized trial with 9 intervention conditions defined by the combination of 2 intervention modules and their sequence. The trial was conducted from March to August 2021 with interested participants from the Swiss general population (N=232; randomized). Randomization was performed using Qualtrics (Qualtrics International Inc), and blinding was ensured. The duration of the intervention was 34 days. The primary outcome was self-reported hand hygiene at follow-up, which was assessed using an electronic diary. The secondary outcomes were user engagement, usability, and satisfaction assessed at follow-up. Nine participants were further invited to participate in semistructured exit interviews. A set of ANOVAs was performed to test the main hypotheses, whereas a thematic analysis was performed to analyze the qualitative data. RESULTS: The results showed a significant increase in hand hygiene over time across all conditions. There was no interaction effect between time and intervention condition. Similarly, no between-group differences in engagement, usability, and satisfaction emerged. Seven themes (eg, "variety and timeliness of the task load" and "social interaction") were found in the thematic analysis. CONCLUSIONS: The effectiveness of Soapp in promoting hand hygiene laid the foundation for the next evaluation phase of the app. More generally, the study supported the value of digital interventions in pandemic contexts. The findings showed no differential effect of intervention conditions involving different combinations and sequences of the habit, motivation, and social norms modules on hand hygiene, engagement, usability, and satisfaction. In the absence of quantitative differences, we relied on the results from the thematic analysis to select the best version of Soapp for the evaluation phase. TRIAL REGISTRATION: ClinicalTrials.gov NCT04830761; https://clinicaltrials.gov/ct2/show/NCT04830761. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-055971.

A Three-Stage Framework for Optimizing Customized Bus Operations Considering COVID-19 Social Distancing Measures

The COVID-19 pandemic has imposed several adverse impacts on the public transit sector. Significant decline in public transit ridership has been observed in many cities around the world. Public transit agencies are facing with increasing financial burden in providing viable transit service. To survive in this difficult COVID-19 period, public transit agencies are working hard on developing innovative and cost-effective transit services. Customized bus (CB) service is such a kind of smart transit services that provides personalized, comfortable, and safe travel service by collecting passenger travel requests via smartphone apps. This work proposes a three-stage optimization framework for optimizing the operations-planning process of CB service considering COVID-19 imposed social distancing constraints. At the first stage, based on traveler's requests, stops are determined, and feasible CB routes are generated following the shortest-path principles. The second stage generates an initial feasible vehicle schedule complying with the COVID-19 imposed constraints. The schedule is further optimized by using a deficit function-based graphical vehicle scheduling technique at the third stage. Results of a numerical example demonstrated the effectiveness of the three-stage optimization framework. © 2022 IEEE.

Issues on Japanese COVID-19 Exposure Notifications Application (COCOA)

This study investigates problems related to COCOA, which is a smartphone app officially provided by Japan's Ministry of Health, Labour and Welfare (MHLW) that is designed to notify users when they have been in close contact with coronavirus disease 2019 (COVID-19) positive persons, and thus help the government and healthcare organizations contain the spread of the virus. The information we have obtained thus far indicates that poor utilization rates of the app are due to significant program flaws, which caused the initial usage to be sluggish, as well as the failures of various health centers to adequately provide polymerase chain reaction (PCR) testing for COCOA notification recipients, which exacerbated sluggishness issues. Furthermore, a related survey revealed that although the government provides an integrated data system called the Health Center Real-time Information-sharing System on COVID-19 (Japanese abbreviation HER-SYS), information on fever outpatients (hospital names, locations, consultation times, presence or absence of PCR testing, etc.) corresponding to each local government is still not fully available. © 2022 IEEE.

Designing to Fight Pandemics: A Review of Literature and Identifying Design Patterns for COVID-19 Tracing Apps

Throughout the pandemic, digital contact tracing using smartphone applications (or apps) has been endorsed by many authorities across the globe as a tool to limit the spread of COVID-19. Consequently, to deploy contact tracing in large populations, multiple contact tracing apps have been developed and deployed globally. However, due to the relative recency of the COVID-19 pandemic as well as the suddenness of the need for contact tracing at this scale, app designers are often left with no systematic guidelines. Designers today lack guidelines on what factors might affect perceptions and adoption of their apps. They also lack a knowledgebase of features that could be appropriate to include in their app for a given context. To address this gap, we conducted a review of the academic literature on attitudes towards and adoption of COVID-19 response apps, as well as a feature review of a diverse set of international tracing apps. Our investigation yielded a set of design patterns which can be used readily by designers of contact tracing apps. Our work lays the foundation to identify opportunities for new contextual feature design and use. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Investigation of UX and Flow Experience in Sports Activities during the Covid-19 Pandemic: A Comparative Analysis of Cycling Apps

Since the onset of the Covid-19 pandemic, a dramatic increase in mHealth application (app) downloads has been documented. However, overall dwell retention for fitness apps is low, so gamification techniques are used within apps with the goal of positively influencing the user experience and ultimately the user's motivation. The so-called flow, which is related to intrinsic motivation, has been little explored in the context of cycling apps. Therefore, we conducted a quasi-experimental cycling study with 34 cyclists (20 female, 14 male;19 to 57 years old) who tested the adidas Running by Runtastic (Adidas Runtastic), Komoot, and Strava cycling apps during a 20-minute bike ride. After testing each cycling app, they completed the User Experience Questionnaire (UEQ) and the Flow State Scale-2 Short (FSS-2S). Our results showed no significant differences across the six factors of the UEQ, nor across the total score of the FSS-2S. Thus, we conclude that the three cycling apps Adidas Runtastic, Komoot, and Strava are perceived and rated almost equally by female and male cyclists.

Mobile Apps in Retail: Usage Frequency Before, During, and After the SARS-CoV-2 Pandemic – Insights from the German Market

In the context of the SARS-CoV-2 pandemic and the increasing digitization of stationary retail, mobile apps in retail (MAR) have gained attention among many consumers. This study examines how the frequency of MAR usage changed before and during the pandemic and how consumers estimate how MAR usage will evolve after the pandemic. Additionally, the role of affinity to mobile devices usage (AMU) in this context is examined. Furthermore, the relevance of pandemic-specific MAR features is elaborated. Based on an online questionnaire with 167 responses, it can be shown that MAR have gained significant relevance in the context of the pandemic and will continue to be an important tool for customers when shopping stationary after the pandemic. A moderating role of AMU cannot be confirmed. Click & collect and online shopping are identified as the most important MAR functions in the context of the pandemic. Information about rules for pandemic compliant shopping doesn't play much of a role for consumers. The results are an important signal for retailers to continue their efforts in digitization and MAR development. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Effectiveness and Usability of Digital Tools to Support Dietary Self-Management of Gestational Diabetes Mellitus: A Systematic Review.

Advice on dietary intake is an essential first line intervention for the management of gestational diabetes mellitus (GDM). Digital tools such as web-based and smartphone apps have been suggested to provide a novel way of providing information on diet for optimal glucose regulation in women with GDM. This systematic review explores the effectiveness and usability of digital tools designed to support dietary self-management of GDM. A systematic search of Medline, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, and Scopus using key search terms identified 1476 papers reporting research studies, of which 16 met the specified inclusion criteria. The quality of the included studies was assessed using the ErasmusAGE Quality Score or the Mixed Methods Appraisal Tool (MMAT) version 2018. The findings show that the adoption of digital tools may be an effective approach to support self-management relating to healthy diet, health behaviour, and adherence to therapy in women with GDM as a usable intervention. However, there is a lack of evidence concerning the effectiveness of tools to support the dietary management of GDM. Consideration for ethnic specific dietary advice and evidence-based frameworks in the development of effective digital tools for dietary management of GDM should be considered as these aspects have been limited in the studies reviewed.

Design and Development of Modular and Open System (MOST) for Pandemic Precaution

With the new normal of our daily lives caused by the novel COVID 19, it has become a requirement to sanitize our hands and go through manual temperature screening via a handheld infrared thermometer. Moreover, our contact info must be provided either using a smartphone app or logbook. This process is time consuming and causes long queues. Therefore, to expedite this process, a device named Modular and Open System (MOST) was designed and developed. The MOST chassis is built using an aluminum bar. This chassis is attached with a spring-operated mechanism used to dispense a liquid sanitizer from a bottle manually using the foot. The chassis is also installed with a controller, camera, MLX90614 temperature sensor, touchscreen, barcode scanner, and tower light. These components are used to perform contactless temperature measurement, capture a person’s information, display the temperature, and alert the user about their health condition. The information can be of any data such as name, phone number, identification number and others as long it is in a barcode format. Meanwhile, to improve the accuracy for temperature measurement, a distance compensation algorithm based on a quadratic least square method is applied in the MOST system. It is tested, MOST is able to expedite this process and the accuracy of temperature measurement to a user is 99%. A person only needs to stand in front of it, flash the barcode either using a card or smartphone and thus the health status can be displayed. Moreover, the data including date, time, measured temperature, and person’s information are recorded. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Determinants of the acceptance and adoption of a digital contact tracing tool during the COVID-19 pandemic in Singapore.

The motivations that govern the adoption of digital contact tracing (DCT) tools are complex and not well understood. Hence, we assessed the factors influencing the acceptance and adoption of Singapore's national DCT tool - TraceTogether - during the COVID-19 pandemic. We surveyed 3943 visitors of Tan Tock Seng Hospital from July 2020 to February 2021 and stratified the analyses into three cohorts. Each cohort was stratified based on the time when significant policy interventions were introduced to increase the adoption of TraceTogether. Binary logistic regression was preceded by principal components analysis to reduce the Likert items. Respondents who 'perceived TraceTogether as useful and necessary' had higher likelihood of accepting it but those with 'Concerns about personal data collected by TraceTogether' had lower likelihood of accepting and adopting the tool. The injunctive and descriptive social norms were also positively associated with both the acceptance and adoption of the tool. Liberal individualism was mixed in the population and negatively associated with the acceptance and adoption of TraceTogether. Policy measures to increase the uptake of a national DCT bridged the digital divide and accelerated its adoption. However, good public communications are crucial to address the barriers of acceptance to improve voluntary uptake widespread adoption.

Digital Communication to Compensate for Social Distancing: Results of a Survey on the Local Communication App DorfFunk

This paper aims to determine the potentials as well as the limitations of digital communication to compensate for the massive decrease in direct social interaction due to the Covid-19 pandemic. The availability of “DorfFunk” – a smartphone app for communication in local rural communities – was expanded in three German federal states during the spring of 2020 to counteract some of the negative consequences of measures taken to contain the spread of the virus (curfews, quarantines, social distancing). Here, we present the results of a survey on the experiences, needs, and perceived benefits/limitations of DorfFunk users in times of the pandemic. The results indicate that DorfFunk can contribute to coping with such a situation, especially in the local sphere. Local information and the connection to the community turned out to be of importance, while functionalities for the interaction with other individuals were regarded as secondary. The benefits of DorfFunk were valued more positively in regions where the service had been established already before the pandemic. © 2021, Springer Nature Switzerland AG.

What is the Current and Future Status of Digital Mental Health Interventions?

The prevalence of mental disorders continues to increase, especially with the advent of the COVID-19 pandemic. Although we have evidence-based psychological treatments to address these conditions, most people encounter some barriers to receiving this help (e.g., stigma, geographical or time limitations). Digital mental health interventions (e.g., Internet-based interventions, smartphone apps, mixed realities -virtual and augmented reality) provide an opportunity to improve accessibility to these treatments. This article summarizes the main contributions of the different types of digital mental health solutions. It analyzes their limitations (e.g., drop-out rates, lack of engagement, lack of personalization, lack of cultural adaptations) and showcases the latest sophisticated and innovative technological advances under the umbrella of precision medicine (e.g., digital phenotyping, chatbots, or conversational agents). Finally, future challenges related to the need for real world implementation of these interventions, the use of predictive methodology, and hybrid models of care in clinical practice, among others, are discussed.