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The advance of digitalization is constantly bringing new solutions to various areas of life in our society. The COVID-19 pandemic, among other things, brought increased attention to the application and support of treatments through digital solutions in the healthcare sector due to contact restrictions. However, the development of digital solutions comes at a high cost in terms of time and expenses. Mobile app development requires the development of two separate apps for the two respective market-leading mobile operating systems iOS and Android. Cross-platform frameworks make it possible to develop apps for both operating systems on a single code base, thus saving the development and maintenance of two separate codes. Flutter is currently the most popular cross-platform framework for the development of mobile apps. This paper has evaluated Flutter based on an existing criteria catalogue. As a usage context for the evaluation, a prototype for Cancer Counselling App of the University Medical Center Freiburg was implemented. According to the gained own prototyping experience with Flutter and a thorough literature analysis in this area, the criteria catalogue was filled out and the result was compared with other mobile App development paradigms. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
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Context: Nowadays, mobile applications (or apps) have become vital in our daily life, particularly within education. Many institutions increasingly rely on mobile apps to provide access to all their students. However, many education mobile apps remain inaccessible to users with disabilities who need to utilize accessibility features like talkback or screen reader features. Accessibility features have to be considered in mobile apps to foster equity and inclusion in the educational environment allowing to use of such apps without limitations. Gaps in the accessibility to educational systems persist. Objective: In this paper, we focus on the accessibility of the Blackboard mobile app, which is one of the most common Learning Management Systems (LMS) used by many universities, especially during the current COVID-19 pandemic. Method: This study is divided into two-fold. First, we conduct a survey using questionnaires and interviews to explore the extent to which students consider the Blackboard mobile app usability. A Total of 1,308 hearing students and 65 deaf and hard-of-hearing students participated in the study. Second, we collected 15,478 user reviews from the Google Play Store and analyzed the reviews to extract accessibility issues. Result: We observed that most deaf and hard-of-hearing students found difficulty in the Blackboard mobile app, compared to hearing students. Also, our app store analysis showed that only 31% of the reviews reported violations of accessibility principles that apps like Blackboard must comply with. This study highlights these violations and their corresponding implications to support LMS frameworks in becoming more inclusive for all users. © 2023 ACM.
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Sharing economy-based services are more prevalent in contemporary society, especially after the covid-19 pandemic. However, from the user's perspective, it is still unclear what factors define the success of sharing economy-based apps. To address this issue, we conducted a study using an integrated theoretical framework that incorporated cognitive load theory, social network theory, and theory of planned behavior. 448 samples were collected from three tourist destinations in India to test the model. The results showed that mobile app user interface, interaction, and social networking would positively impact user satisfaction with sharing economy-based apps. User satisfaction also leads to recommendation and continuance intention. The study findings have several implications and recommendations for future studies on sharing economy apps. © 2023 Taylor & Francis Group, LLC.
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Objectives: Mindfulness meditation apps are used by millions of adults in the USA to improve mental health. However, many new app subscribers quickly abandon their use. The purpose of this study was to determine the behavioral, demographic, and socioeconomic factors associated with the abandonment of meditation apps during the COVID-19 pandemic. Method: A survey was distributed to subscribers of a popular meditation app, Calm, at the start of the COVID-19 pandemic in March 2020 that assessed meditation app behavior and meditation habit strength, as well as demographic and socioeconomic information. App usage data were also collected from the start of each participant's subscription until May 2021. A total of 3275 respondents were included in the analyses. Participants were divided into three cohorts according to their subscription start date: (1) long-term subscribers (> 1 year before pandemic start), (2) pre-pandemic subscribers (< 4 months before pandemic start), and (3) pandemic subscribers (joined during the pandemic). Results: Meditating after an existing routine was associated with a lower risk of app abandonment for pre-pandemic subscribers (hazard ratio = 0.607, 95% CI: 0.422, 0.874; p = 0.007) and for pandemic subscribers (hazard ratio = 0.434, 95% CI: 0.285, 0.66; p < 0.001). Additionally, meditating "whenever I can" was associated with lower risk of abandonment among pandemic subscribers (hazard ratio = 0.437, 95% CI: 0.271, 0.706; p < 0.001), and no behavioral factors were significant predictors of app abandonment among the long-term subscribers. Conclusions: These results show that combining meditation with an existing daily routine was a commonly utilized strategy for promoting persistent meditation app use during the COVID-19 pandemic for many subscribers. This finding supports existing evidence that pairing new behaviors with an existing routine is an effective method for establishing new health habits. Preregistration: This study is not pre-registered.
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During the COVID-19 pandemic, many countries have developed contact tracing technologies to curb the spread of the disease by locating and isolating people who have been in contact with coronavirus carriers. Subsequently, understanding why people install and use contact tracing applications is becoming central to their effectiveness and impact. However, involuntary systems can crowd out the use of voluntary applications when several contact tracing initiatives are employed simultaneously. To investigate this hypothesis, we analyze the concurrent deployment of two contact tracing technologies in Israel: centralized mass surveillance technologies and a voluntary contact tracing mobile app. Based on a representative survey of Israelis (n=519), our findings show that positive attitudes toward mass surveillance were related to a reduced likelihood of installing contact tracing apps and an increased likelihood of uninstalling them. These results also hold when controlling for privacy concerns, attitudes toward the app, trust in authorities, and demographic properties. We conclude the paper by suggesting a broader framework for analyzing crowding out effects in ecosystems that combine involuntary surveillance and voluntary participation. © 2023 ACM.
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The impact of COVID-19 on shopping behaviour preferences has resulted in the accelerated adoption of e-commerce and increased traffic of first-time e-commerce shoppers worldwide. This study compared experienced versus inexperienced mobile consumers' shopping experiences on smartphones. A mixed-methods research, combining mobile eye-tracking technology and interviews, was employed. The comparison of experienced and inexperienced users showed significant differences in regards to time spent on various stages of the shopping journey, used elements of the website and problem areas encountered. Inexperienced users have higher expectations towards fashion retailer's website. Mobile consumers' prior experience using retailers' digital shopping platform is a key parameter in user experience research and participants' recruitment. The findings of this research have managerial and methodological implications and can be used in understanding the behaviour differences between current and potential customers, and in developing personalised shopping experiences on smartphones by feeding these into retailers' digital analytics database and marketing strategy.
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An elderly squire indicated the importance of medication intake in everyday life. Some individuals forget to take medicine on time. Also, monitor using the scheduled medicine to help people with an illness. In addition, technology has increased for utilization in healthcare. According to Harvard Medical School by Stephanie Watson about the technology advancement is flourishing in the Philippines, and telehealth stays with innovation to improve digital health platforms. In addition, healthcare services are facing challenges with Covid-19. On the other hand, telehealth gives good service, and about 91% of consumers use digital healthcare services. Also, A reminder system should be simple, familiar, flexible, and recognizable.Technology can positively impact the lives of older people, including their physical and mental health and daily activities. Technology can help people become active. It also increases awareness and motivation to increase physical activity. © 2022 IEEE.
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Currently, people’s highly busy lifestyles and sedentary behavior contribute negatively to multiple health factors. During the COVID-19 pandemic, the different sanitary measures, such as limited mobility and the closing of gyms and sports centers, have contributed to limited physical activity. In this context, there are several apps to enhance physical activity across all mobile stores with an emphasis on mobile sensing. However, the use of a formal theory incorporated into the app development and interventions is less evident. A theory-based approach contributes to understanding the reasons and situations in which an intervention strategy can have an impact. The present work considers the Elaboration Likelihood Model (ELM), which addresses persuasion and attitude change. Can we develop a persuasive app that promotes physical activity based on contemporary attitudes and behavioral change theories? We developed a mobile application for Android OS. Then, 63 participants tested it, and were encouraged to think of ideas or arguments in favor of doing physical activity in a high elaboration task. A mediation analysis was done, with results showing that attitudes partially mediate the association between thought and physical activity. Participants’thoughts were seen to be positively correlated with their attitudes;and, in turn, participants’attitudes were correlated with their behavioral intention (to do physical activity). This suggests that a theory-based approach for the active production of biased beliefs is effective when designing an app that encourages positive attitudes toward physical activity. Author
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The speed of spread of Coronavirus Disease 2019 led to global lockdowns and disruptions in the academic sector. The study examined the impact of mobile technology on physics education during lockdowns. Data were collected through an online survey and later evaluated using regression tools, frequency, and an analysis of variance (ANOVA). The findings revealed that the usage of mobile technology had statistically significant effects on physics instructors' and students' academics during the coronavirus lockdown. Most of the participants admitted that the use of mobile technologies such as smartphones, laptops, PDAs, Zoom, mobile apps, etc. were very useful and helpful for continued education amid the pandemic restrictions. Online teaching is very effective during lock-down with smartphones and laptops on different platforms. The paper brings the limelight to the growing power of mobile technology solutions in physics education. © 2018 Tsinghua University Press.
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Introduction: Early determination of COVID-19 severity and health outcomes could facilitate better treatment of patients. Different methods and tools have been developed for predicting outcomes of COVID-19, but they are difficult to use in routine clinical practice. Methods: We conducted a prospective cohort study of inpatients aged 20–92 years, diagnosed with COVID-19 to determine whether their individual 5-year absolute risk of stroke at the time of hospital admission predicts the course of COVID-19 severity and mortality. The risk of stroke was determined by the Stroke Riskometer mobile application. Results: We examined 385 patients hospitalized with COVID-19 (median age 61 years). The participants were categorized based on COVID-19 severity: 271 (70.4%) to the "not severe” and 114 (29.6%) to the "severe” groups. The median risk of stroke the next day after hospitalization was significantly higher among patients in the severe group (2.83, 95% CI: 2.35–4.68) versus the not severe group (1.11, 95% CI: 1.00–1.29). The median risk of stroke and median systolic blood pressure (SBP) were significantly higher among non-survivors (12.04, 95% CI: 2.73–21.19) and (150, 95% CI: 140–170) versus survivors (1.31, 95% CI: 1.14–1.52) and (134, 95% CI: 130–135), respectively. Those who spent more than 2.5 h a week on physical activity were 3.1 times more likely to survive from COVID-19. Those who consumed more than one standard alcohol drink a day, or suffered with atrial fibrillation, or had poor memory were 2.5, 2.3, and 2.6 times more likely not to survive from COVID-19, respectively. Conclusions: High risk of stroke, physical inactivity, alcohol intake, high SBP, and atrial fibrillation are associated with severity and mortality of COVID-19. Our findings suggest that the Stroke Riskometer app could be used as a simple predictive tool of COVID-19 severity and mortality.
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Mobile applications have become popular tools for supporting healthy nutrition behavior. Current tools are primarily based on the detailed tracking of a user's direct consumption, thus intervening only during or even after a user has eaten something. With increasing home office hours (especially during the COVID-19 pandemic), people are eating more often at home, which has also led to a decrease in fruit and vegetable consumption. Therefore, we aim to support people in the food-shopping process. We suggest a mobile application that helps people reflect on their purchases and tries to nudge users toward healthier product choices. We conducted a pilot study with 31 participants who used the application for two consecutive weeks. During this time, we observed a decrease in the caloric values per 100 g of purchases. Furthermore, we collected positive feedback on the app regarding acceptance, usability, and user experience. © 2023 IEEE Computer Society. All rights reserved.
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BACKGROUND: Prenatal education encourages healthy behavioral choices and reduces rates of adverse birth outcomes. The use of mobile health (mHealth) technologies during pregnancy is increasing and changing how pregnant people acquire prenatal education. SmartMom is an evidence-based prenatal education SMS text messaging program that overcomes barriers to prenatal class attendance, including rural or remote location, cost, stigma among participants, lack of instructors, and cessation of classes during the COVID-19 pandemic. OBJECTIVE: We sought to explore perceived information needs and preferences for the content and structure of prenatal education mHealth programs among persons enrolled in or eligible to enroll in SmartMom. METHODS: This was a qualitative focus group study conducted as part of a development and usability study of the SmartMom program. Participants were older than 19 years of age, Canadian residents, fluent in English, and either currently pregnant or pregnant within the last year. We asked open-ended questions about information-seeking behaviors during pregnancy, the nature of the information that participants were seeking, how they wanted to receive information, and if SmartMom was meeting these needs. Focus groups took place via videoconference technology (Zoom) between August and December 2020. We used reflexive thematic analysis to identify themes that emerged from the data and the constant comparison method to compare initial coding to emerging themes. RESULTS: We conducted 6 semistructured focus groups with 16 participants. All participants reported living with a partner and owning a cell phone. The majority (n=13, 81%) used at least 1 app for prenatal education. Our analysis revealed that "having reliable information is the most important thing" (theme 1); pregnant people value inclusive, local, and strength-based information (theme 2); and SMS text messages are a simple, easy, and timely modality ("It was nice to have that [information] fed to you"; theme 3). Participants perceived that SmartMom SMS text messages met their needs for prenatal education and were more convenient than using apps. SmartMom's opt-in supplemental message streams, which allowed users to tailor the program to their needs, were viewed favorably. Participants also identified that prenatal education programs were not meeting the needs of diverse populations, such as Indigenous people and LGBTQIA2S+ (lesbian, gay, bisexual, transgender, queer and/or questioning, intersex, asexual, Two-Spirit plus) communities. CONCLUSIONS: The shift toward digital prenatal education, accelerated by the COVID-19 pandemic, has resulted in a plethora of web- or mobile technology-based programs, but few of these have been evaluated. Participants in our focus groups revealed concerns about the reliability and comprehensiveness of digital resources for prenatal education. The SmartMom SMS text messaging program was viewed as being evidence-based, providing comprehensive content without searching, and permitting tailoring to individual needs through opt-in message streams. Prenatal education must also meet the needs of diverse populations.
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Background: Positive prospective mental imagery plays an important role in mental well-being, and depressive symptoms have been associated with difficulties in generating positive prospective mental images (PPMIs). We used a mobile app to gather PPMIs generated by young adults during the COVID-19 pandemic and analyzed content, characteristics, and associations with depressive symptoms. Methods: This is a secondary analysis of a randomized controlled trial with 95 healthy young adults allocated into two groups (intervention and control). Participants used the mobile app decreasing mental health symptoms for seven consecutive days. Fifty participants in the intervention group reported PPMIs at least three times per day using a mobile app inducing PPMI generation. We categorized entries into themes and applied moderation models to investigate associations between PPMI characteristics and depressive symptoms. Results: We distinguished 25 PPMI themes. The most frequent were related to consuming food and drinks, watching TV/streaming platforms, and doing sports. Vividness and ease of generation of PPMIs, but not their anticipation, pleasure intensity or number of engagements with the app were associated with fewer depressive symptoms. Conclusions: We identified PPMI themes in young adults and found significant negative associations between depressive symptoms and vividness and generation ease of PPMIs. These results may inform prevention and intervention science, including the design of personalized interventions. We discuss implications for future studies and treatment development for individuals experiencing diminished PPMI. Supplementary Information: The online version contains supplementary material available at 10.1007/s10608-023-10378-5.
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In the Covid-19 pandemic situation, the world is looking for immunity-boosting techniques for fighting against coronavirus. Every plant is medicine in one or another way, but Ayurveda explains the uses of plant-based medicines and immunity boosters for specific requirements of the human body. To help Ayurveda, botanists are trying to identify more species of medicinal immunity-boosting plants by evaluating the characteristics of the leaf. For a normal person, detecting immunity-boosting plants is a difficult task. Deep learning networks provide highly accurate results in image processing. In the medicinal plant analysis, many leaves are like each other. So, the direct analysis of leaf images using the deep learning network causes many issues for medicinal plant identification. Hence, keeping the requirement of a method at large to help all human beings, the proposed leaf shape descriptor with the deep learning-based mobile application is developed for the identification of immunity-boosting medicinal plants using a smartphone. SDAMPI algorithm explained numerical descriptor generation for closed shapes. This mobile application achieved 96%accuracy for the 64 × 64 sized images.
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BACKGROUND: Efficient digitization in medicine still is in its infancy but undeniably has great potential for current and future challenges in health care. Thus far, the rollout of medical apps has not resulted in widespread use of smartphones in the German health care sector-the reasons for this have not been clarified so far. Nevertheless, the lack of user involvement in the development process and content creation might contribute to low acceptance of these products. OBJECTIVE: This study aims to outline an approach to involve medical expertise without any coding knowledge for developing medical app content and functions. METHODS: An end user-operable backend was built. Its usability was evaluated using a usability evaluation test protocol. The results of the usability tests were evaluated by the app development team, and the usability test was repeated for optimizing backend usability. In total, 40 criteria to measure the ease of app usage were defined a priori. The usability test comprised 20 tasks that had to be fulfilled. Usability tasks were analyzed for completion, dropout, and test duration. Due to the COVID-19 pandemic, digital videoconferencing platforms (Zoom and QuickTime Player) were used to complete usability questionnaires. Finally, several backend-based apps for several specialties (infectiology, plastic and reconstructive surgery, and orthopedics) were developed by health care professionals as prototypes. RESULTS: Initial usability testing was conducted with 5 participants (4 men and 1 woman; mean age 39.2, SD 5.97 years). All of them could complete the assigned backend tasks with only a few workflow interruptions and some minor errors. After usability optimization, the workflow completion time decreased from 5.03 minutes to 3.50 minutes, indicating a time saving. The basic backend structure was clear to all test users and the handling was intuitive to learn. Some minor errors in the backend occurred during the test rounds. The apps developed using the aforementioned approach are in clinical use as a proof of concept. CONCLUSIONS: Backends offering operability for medical professionals might have great potential for app development in the mobile health sector. Sophisticated and time-saving usability are pivotal for the acceptance of medical software, as illustrated by the backend-based apps presented herein, which are in clinical use as a proof of concept. Basic interventions are essential and sufficient for adequate usability optimization. Practicable, well-structured software usability evaluation is possible based on the usability evaluation test protocol.
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OBJECTIVES: To explore how smokers view common functions and characteristics of smoking cessation apps. DESIGN: Systematic review. SEARCH SOURCES: CINAHL PLUS, MEDLINE, PsycINFO, EMBASE, IEEE Xplore, ACM Digital Library, and Google Scholar. REVIEW METHODS: Seven digital databases were searched separately using relevant search terms. Search results were uploaded to Covidence. Inclusion and exclusion criteria were identified with the expert team in advance. Titles, abstracts, and full texts were screened by two reviewers independently. Any disagreements were discussed in research meetings. Pertinent data were extracted and analysed using qualitative content analysis. Findings were presented in a narrative approach. RESULTS: 28 studies were included in this review. The overarching themes were app functionality and app characteristics. Under app "functionality", six subthemes emerged: 1) education; 2) tracking; 3) social support; 4) compensation; 5) distraction, and 6) reminding. Under "app characteristics", five subthemes emerged: 1) simplification, 2) personalisation, 3) diverse content forms, 4) interactivity, and 5) privacy and security. CONCLUSION: Understanding user needs and expectations is crucial for developing a programme theory for smoking cessation app interventions. Relevant needs identified in this review should be linked to broader theories of smoking cessation and app-based intervention.
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Mobile Applications , Smoking Cessation , Text Messaging , Humans , Smoking Cessation/methods , Smokers , Qualitative ResearchABSTRACT
Previous literature has documented that mobile application utilization increased exponentially throughout the ongoing COVID-19 epidemic. To comprehend the possible antecedents of individuals' psychological well-being, this research invokes motivation theory and associated literature on perceived assessment (cognitive trust, perceived value, and perceived threat) to comprehensively investigate the determinants of factors influencing mobile app users' health-related information behaviors and psychological outcomes. Data were gathered collected from 898 users of mobile apps, and this article adopted structural equation modeling (SEM) to evaluate the hypothesis generation model. Obtained findings demonstrated that cognitive trust and perceived value positively impacted seeking and sharing health-related information, which subsequently benefited individuals' psychological well-being during the public health crisis. Furthermore, perceived threat exerted a negative impact on seeking and sharing health-related information. These results contribute to existing studies on psychological well-being by broadening the antecedence domain of information practices and revealing the underlying psychological mechanism behind this dynamic process. This study could also benefit practitioners by providing insights into embedded system and mobile app development, which would play a pivotal role in enhancing user experiences that optimize psychological well-being. © 2023 Elsevier Ltd
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The COVID-19 pandemic has affected the student fraternity to physically access the laboratory and conduct experiments offline. Across the world, new platforms have been designed with ICT tools for the smooth conduction of academics specifically for laboratory courses. This article aims to provide quality circle-based guidance to the community to develop a Virtual Laboratory. The virtual lab is developed through an emphasis on Quality Circle methodology. The Quality Circle team has developed an instructional methodology known as the virtual laboratory (VL). It incorporates pedagogical techniques that help students to better understand the theoretical concepts in an effective and joyful way. © 2022, Rajarambapu Institute Of Technology. All rights reserved.
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Due to the spread of COVID-19 all around the world, there is a need of automatic system for primary tongue ulcer cancerous cell detection since everyone do not go to hospital due to the panic and fear of virus spread. These diseases if avoided may spread soon. So, in such a situation, there is global need of improvement in disease sensing through remote devices using non-invasive methods. Automatic tongue analysis supports the examiner to identify the problem which can be finally verified using invasive methods. In automated tongue analysis image quality, segmentation of the affected region plays an important role for disease identification. This paper proposes mobile-based image sensing and sending the image to the examiner, if examiner finds an issue in the image, the examiner may guide the user to go for further treatment. For segmentation of abnormal area, K-mean clustering is used by varying its parameters.Copyright © 2022 Inderscience Enterprises Ltd.
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The COVID-19 virus has governments worldwide implementing new testing strategies, trying to increase their testing capacity so they can have a complete picture of the spread of COVID-19 with as much fidelity as possible. Simultaneously, people are looking to make sense of all the information and official recommendations to manage COVID-19. We present a DT for health in the context of the COVID-19 endemic stage aiming at bridging the gap between health authorities and the general population while offering an alternative approach to screen entire communities at a relatively low cost. We outline the architecture for the platform and present open challenges to make it a safe and effective tool to combat COVID-19 after our first iteration on it. © 2023 Elsevier Inc. All rights reserved.