App Store Research Articles

Evaluation of Indonesia’s police public service platforms through sentiment and thematic analysis

The Indonesian national police (Polri) offer public services through mobile apps: Digital korlantas polri (DigiKorlantas) and samsat digital nasional (SIGNAL). Sentiment analysis gauges public perceptions, serving as a basis for e-government evaluation using user ratings and comments from app stores. Keyword relevance is assessed via feature extraction and Naïve Bayes classification. Thematic analysis is implemented using N-grams methods to identify the factors affecting the effectiveness based on user experiences. The accuracy of the model reaches 81.09% where it indicates a high performance. DigiKorlantas acquires slightly more negative reviews in comparation with positive reviews which are 51% and 49% respectively. In contrast, positive sentiment is dominant on SIGNAL which reach 58%, compared with negative sentiment that in 42%. N-grams reveal similar review patterns for both apps. Some of the solutions are Korlantas Polri should enhance the verification functionality with several techniques such as retinex algorithms or optical character recognition pipeline and increase the capacity of supporting server then releasing an updated version of application to address errors or bugs. This analysis can be alternative evaluation by the Polri to measure the success of the application and find out the continuous improvement of the process and the system.

Does the end justify the means? The European Commission’s proposed regulation laying down rules to prevent and combat child sexual abuse

Abstract The European Commission’s Proposed Regulation Laying Down Rules to Prevent and Combat Child Sexual Abuse aims to impose obligations related to detecting, reporting, removing, and blocking known and new online child sexual abuse material (CSAM), as well as the solicitation of children (grooming), on providers of hosting services, interpersonal communication services, software application stores, internet access services, and other relevant services. This paper navigates through state-of-the-art technological tools for detecting online CSAM, scrutinizing their potential legal impact and technical issues associated with each tool and unveiling potential fundamental rights implications. It strives to answer the question of whether the proposed rules are aligned with the state-of-the-art detection technologies in effectively addressing online CSAM without jeopardizing other fundamental rights, intending to foster a nuanced understanding of the proposal’s potential shortcomings. Upholding democracy and the presumption of innocence demands careful consideration of the impact of new technologies, emphasizing the importance of thorough studies to inform legal frameworks. Without such scrutiny, the proposed regulation risks undermining fundamental rights in its pursuit of child protection in the digital landscape.

Prevention, diagnosis and pharmacological treatment of infections in pregnancy: The mobile app GAIA! for healthcare providers and patients

ObjectiveTo develop and assess the GAIA! app, designed to assist pregnant women and healthcare professionals in managing infectious diseases during pregnancy, and to bridge the information gap between health professionals and expectant mothers. Study DesignThis collaborative initiative in Italy involved partnerships with the University of Florence, Careggi University Hospital, and other institutions. The app, built on the Ionic framework, is available on both Apple and Google App Stores. It offers two distinct modes: “healthcare providers” and “patients.” Content for the app was derived from extensive literature reviews and clinical guidelines. ResultsSince its August 2022 launch, the GAIA! app has garnered over 2,500 downloads, indicating its effectiveness and acceptance within the community. The app differentiates itself from others, such as the Sanford Guide, by focusing specifically on the needs of pregnant women. It ensures cross-platform compatibility, a user-friendly interface, and offline functionality. ConclusionsThe GAIA! app has successfully addressed a niche in infectious disease management for pregnant women, gaining significant traction within the community. While it has seen substantial success, challenges like continuous updates and potential language expansion remain. Future endeavors will address these challenges and further evaluate the app’s impact on maternal and child health.

Assessing the Level of Cybersecurity Awareness and Practices of Application Users and Their Impact on Privacy Policy Consents: A Case Study in Application Downloading

The aim of this study is to understand the level of cybersecurity awareness and practices of application users and determine the impact on their consent to privacy policies through a case study in application downloading. To achieve this aim, this study employs quantitative research methodology. The primary data collection instrument is a structured questionnaire designed to gather insights and perspectives from 65 participants of application users in the Kingdom of Saudi Arabia, including several types of applications. The collected data was collected and analyzed using SPSS software. The findings revealed that most of the study participants disagree that they understand the importance of cybersecurity measures when using mobile applications with a frequency of 27 and a percentage of 41.5%. Also, most of the study participants disagree that they are aware about negative cybersecurity practices with a frequency of 26 and a percentage of 40%. Furthermore, only 23 participants are paying attention to Download applications from only official app stores or trusted sources with a percentage of 35.4% The findings of the study also revealed that a p-value related to Pearson Chi-Square is (0.019) which is less than a significance level of (0.05), this proves a significant statistical relationship between cybersecurity awareness and practices of application users on privacy policy consents.

Fairness and contestability in the provision of software application stores services

Fairness and contestability in the provision of software application stores services

Teaching three-phase half-wave power electronic rectifier with gamified augmented reality support

This paper presents a support tool designed for instructors in technical education within engineering programs, focusing specifically on power electronics and laboratory procedures related to the three-phase half-wave rectifier. The Augmented Reality (AR) application was developed for Android devices using Unity+Vuforia, employing a gamification-based approach. The application allows students to evaluate their knowledge and skills in real-time and offers an interactive learning environment. It provides learning diagnostics and sends each student's evaluation to a database stored on Google-Forms that is accessible by the instructor or assessor in question. It's important to note that this APP is freely accessible through the Android APP store. The learning strategy is around a game that tests players on their knowledge of measuring devices and theoretical concepts. Additionally, there is a puzzle task that encourages learners to correctly arrange the waveforms in a rectifier. Students can also connect the half-wave rectifier's essential connections and the transformer's delta-star connections through touch interaction. A comparison study between traditional teaching methods and the innovative AR-based approach has been conducted. This educational proposal itself is an innovative solution that will be especially helpful for laboratories lacking useful equipment in Mexican colleges. To test the effect of AR application on student success, an experimental study was conducted on two groups of students (a control group [non-using AR] and a test group [using AR]). To determine significant difference in acquired learning, an ANOVA statistical analysis was conducted using independent sample tests. According to tests result, there is a significant difference in the acquired knowledge for those who used the designed tool. The probability value (p = 1e-5 <0.05) for the use of AR is found. They increase their initial average grade from 27.08% to 72.3%, in contrast to the control group with no significant increasing learning, reporting an initial average grade of 28.75–43.33%. These results show that the use of AR in electronic practice makes a significant difference in student success.

Self-Assessment Instruments for Supporting Family Caregivers: An Integrative Review.

Family caregivers take on a variety of tasks when caring for relatives in need of care. Depending on the situation and the intensity of care, they may experience multidimensional burdens, such as physical, psychological, social, or financial stress. The aim of the present study was to identify and appraise self-assessment instruments (SAIs) that capture the dimensions of family caregivers' burdens and that support family caregivers in easily identifying their caregiving role, activities, burden, and needs. We performed an integrative review with a broad-based strategy. A literature search was conducted on PubMed, Google Scholar, Google, and mobile app stores in March 2020. After screening the records based on the eligibility criteria, we appraised the tools we found for their usefulness for family care and nursing practice. From a total of 2654 hits, 45 suitable SAIs from 274 records were identified and analyzed in this way. Finally, nine SAIs were identified and analyzed in detail based on further criteria such as their psychometric properties, advantages, and disadvantages. They are presented in multi-page vignettes with additional information for healthcare professionals. These SAIs have proven useful in assessing the dimensions of caregiver burden and can be recommended for application in family care and nursing practice.

A shot in the dark: the impact of online visibility on the search for an effective sleep app.

Dictated by consumer ratings and concealed algorithms, high levels of online visibility are granted to certain sleep apps on mainstream modes of app selection. Yet, it remains unclear to what extent these highly visible apps are evidence-based. The objectives of this review were to identify and describe the apps with the greatest online visibility when searching for a sleep app and to assess the claimed and actual research associated with them. A keyword search was conducted in Google Play and Google search. Titles of the most visible apps were retrieved. App descriptions were examined to identify research claims made about app effectiveness on sleep and other health-related outcomes. A follow-up search on PubMed and Google Scholar was conducted to verify claims. The keyword search identified 53 highly visible apps. Examination of app store descriptions found that no reference to research was made for the majority of apps (n = 45, 84.9%). Published research studies were available for just 3 apps, with most studies evaluating app impact on non sleep-related outcomes. There was some evidence to attesting to the effectiveness of 2 apps in improving sleep. This review demonstrates how, when carrying out a typical search for a sleep app, information about the evidence base for the majority of highly visible apps is not available. Results highlight the need for the improvement of mainstream modes of app selection in terms of better consumer-app specificity and increased transparency regarding the access to information about the evidence base for apps. Power N, Boivin DB, Perreault M. A shot in the dark: the impact of online visibility on the search for an effective sleep app. J Clin Sleep Med. 2024;20(8):1379-1386.

Why this app? How user ratings and app store rankings impact educators' selection of educational apps

Research indicates that educators value certain benchmarks of educational quality when choosing educational apps from app stores (i.e., curriculum, feedback, scaffolding, learning theory, and development team). However, it is unclear how other users' ratings of the app, or the app's ranking on the app store's list of “top” educational apps, might impact educators' evaluations. The present study examines how educational benchmarks, ratings, and rankings influence educators' selection of educational apps. One-hundred and fifty elementary educators viewed 18 researcher-created educational app pages and indicated their willingness to download, pay for, and rate each app. Results from a repeated-measures MANOVA and non-parametric tests revealed that educators preferred benchmark apps to buzzword apps, with a medium sized effect. However, they also had a strong preference for apps with positive user ratings, with a large effect, and preferred apps with a bottom ranking, with a medium effect. To improve app selection, educators should rely on their own knowledge to choose apps rather than relying on user ratings or company rankings. Companies running app stores should improve their user ratings and rankings systems to facilitate selection of apps that include evidence-backed benchmarks of app quality.

WHO USES MHEALTH IN HYPERTENSION CARE? - INSIGHTS FROM A QUANTITATIVE SURVEY AMONG HYPERTENSION APP USERS

Objective: Digital health technologies, particularly mHealth apps, are proving to be effective tools for both prevention and monitoring of hypertension therapy. The aim of this study is to gain an in-depth understanding of the profiles and adoption patterns of mHealth users in hypertension care. Design and method: From January to October 2023, a quantitative, standardized questionnaire-survey was conducted with users of a hypertension-focused mHealth app (Hypertension.App). The data analysis included descriptive statistics as well as Bayesian univariate and multivariate logistic regressions. The study is part of the Innovation Fund Project DiPaH. Results: Overall, 255 questionnaires were included in the analysis. The mean age of the app users was 53.6 ± 13.9 years. Most participants were male (54.3%, 139/255), 42.9% (109/255) were female and 0.79% (2/255) non-binary. Most participants had a university degree (44.5%, 113/255) or high school diploma (22%, 56/255). The majority reported that they live in an urban environment (57.8%, 147/255). Overall, 44.5% (113/255) of the participants reported a monthly net income of more than 2500 € per month and 20.1% (51/255) an income between 1500-2500€ per month. The mean eHEALS score (eHealth literacy / 1-40) was 31.0 ± 4.91. Most users received a hypertension diagnosis more than 10 years ago (60.2%, 153/255) or more than 10 years ago. The most common method of discovering the app was personal searches on the web or app store (44.1%, 112/255). The majority reported using the app at least once a week (80.7%, 205/255), with daily usage reported by 52.4% (133/255). However, the app's integration into formal medical treatment was limited, with only 11.8% (30/255) of participants having their medication adjusted based on app entries. Conclusions: The high frequency of app usage suggests that users find it a valuable tool in monitoring their blood pressure. The results indicate that people with a high level of education, high income and in urban regions are more likely to use mHealth in hypertension care. Additionally, the limited integration of the app into medical treatment indicates a gap between personal health monitoring and formal healthcare.

Variety-Based Congestion in Online Markets: Evidence from Mobile Apps

In many online markets, consumers have to spend time and effort browsing through products. The addition of new products could make other products less visible, creating congestion externalities. Using Android app store data, I take advantage of a natural experiment—a redesign of part of the store—to show evidence of congestion externalities online: more apps in the market directly reduce per app usage/downloads. The natural experiment also increases long-run entry, but a structural demand model that accounts for congestion externalities suggests that 40 percent of consumer variety welfare gains are lost from higher congestion. (JEL D12, D22, D62, L86)

Attributes, Quality, and Downloads of Dementia-Related Mobile Apps for Patients With Dementia and Their Caregivers: App Review and Evaluation Study.

The adoption of mobile health (mHealth) apps among older adults (>65 years) is rapidly increasing. However, use of such apps has not been fully effective in supporting people with dementia and their caregivers in their daily lives. This is mainly attributed to the heterogeneous quality of mHealth apps, highlighting the need for improved app quality in the development of dementia-related mHealth apps. The aims of this study were (1) to assess the quality and content of mobile apps for dementia management and (2) to investigate the relationship between app quality and download numbers. We reviewed dementia-related mHealth apps available in the Google Play Store and Apple App Store in Taiwan. The identified mobile apps were stratified according to a random sampling approach and evaluated by five independent reviewers with sufficient training and proficiency in the field of mHealth and the related health care sector. App quality was scored according to the user version of the Mobile Application Rating Scale. A correlation analysis was then performed between the app quality score and number of app downloads. Among the 17 apps that were evaluated, only one was specifically designed to provide dementia-related education. The mean score for the overall app quality was 3.35 (SD 0.56), with the engagement (mean 3.04, SD 0.82) and information (mean 3.14, SD 0.88) sections of the scale receiving the lowest ratings. Our analyses showed clear differences between the top three- and bottom three-rated apps, particularly in the entertainment and interest subsections of the engagement category where the ratings ranged from 1.4 to 5. The top three apps had a common feature in their interface, which included memory, attention, focus, calculation, and speed-training games, whereas the apps that received lower ratings were found to be deficient in providing adequate information. Although there was a correlation between the number of downloads (5000 or more) and app quality (t15=4.087, P<.001), this may not be a significant determinant of the app's perceived impact. The quality of dementia-related mHealth apps is highly variable. In particular, our results show that the top three quality apps performed well in terms of engagement and information, and they all received more than 5000 downloads. The findings of this study are limited due to the small sample size and possibility of disregarding exceptional occurrences. Publicly available expert ratings of mobile apps could help people with dementia and their caregivers choose a quality mHealth app.

Effects of app icon familiarity and authority on app icon image fit and usage intention: focusing on the moderating effects of app icon features and app type

PurposeThis research delves into the dynamic realm of app design by examining the impact of app icon familiarity and authority on image fit, influencing users' app usage intention. Focusing on the distinctive circumstances of Chinese and Korean customers, the study aims to provide insightful information about how application user behavior changes.Design/methodology/approachUtilizing structural equation modeling, the study employs data from 293 Korean and Chinese consumers. The research design incorporates a thoughtful approach, including parallel translation methods, focus group interviews, and pre-experimental testing to ensure survey accuracy and validity. The study strategically selects stimuli from the Apple App Store rankings, emphasizing icon features and type considerations.FindingsThe results provide important new information about the connections between usage intention, image fit, authority, and familiarity with app icons. Notably, app icon familiarity and authority positively influence image fit. Furthermore, app icon image fit emerges as a positive predictor of usage intention, mediating the complex interplay between familiarity, authority, and intention. The study also identifies moderating effects, shedding light on the nuanced role of app icon features and types.Originality/valueOriginating from a comprehensive exploration of icons, this study significantly contributes to the field by exploring icon differences and uncovering the intricate mechanisms guiding users' decisions. The findings offer valuable insights for app designers, marketers, and researchers seeking a deeper understanding of user behavior in diverse cultural contexts, thereby enhancing the theoretical and practical foundations in app usability and consumer behavior.

Sentiment analysis on google play store app users’ reviews based on deep learning approach

Sentiment analysis on google play store app users’ reviews based on deep learning approach

Prioritizing user requirements for digital products using explainable artificial intelligence: A data-driven analysis on video conferencing apps

The advent of Industry 5.0 has brought a wealth of digital information to mobile app stores. With the help of emerging technologies such as machine learning and explainable artificial intelligence (XAI), these large amounts of user-generated data can be efficiently captured and analyzed. In this study, we propose an app store analysis framework and demonstrate the utility of the framework by mining and prioritizing user requirements in three popular video conferencing apps. We used the Sentistrength sentiment analysis tool, structural topic modeling, the Gephi web analysis tool, machine learning, and XAI techniques to conduct an in-depth analysis of user requirements in Microsoft Teams, ZOOM Cloud Meetings, and Google Meet. The findings indicated that Steal data, Audio and video quality, Customer service, Hacker issues, Meeting and account passwords, Mute and unmute, Features, and Office platform were the web conferencing system's key areas for improvement. The study demonstrated the usability of app store analysis frameworks and the great potential of XAI to provide insights about requirements prioritization by interpreting machine learning models. Additionally, it offered valuable suggestions for app developers on using the massive data in app stores to improve their apps.

Research on Apple's Marketing Strategy

With the rapid development of science and technology, electronics continue to emerge, and the market competition is increasingly fierce. Apple, with successful marketing strategies, and strong technical support, emerged among many electronics products, becoming the industry giant. Since Apple launched the App Store, the online application market has been developing rapidly, which not only promotes mobile Internet. The development of the network has changed the revenue structure of mobile value-added services and promoted the re-integration and improvement of the mobile network industry chain. In this stage, how to enter and seize the market better and faster has become the primary problem of Apple. This paper discusses the current market situation of Apple, analyzes the target market selection, and focuses on the main competitive advantages of Apple. Then, by introducing a marketing information management system, a series of marketing channels are organized for Apple and marketing countermeasures. The management system enables to effective implementation of the marketing and promotion plan, as well as evaluation, monitoring, and update of the implementation results in a reasonable and timely manner, laying a good foundation for successful marketing. The work provided valuable advice. Through an in-depth analysis of Apple, people can deeply understand its core competitiveness and enterprise development of the layout of ideas. The paper also provides examples and references for enterprises to optimize their business models.

Regulatory Standards and Guidance for the Use of Health Apps for Self-Management in Sub-Saharan Africa: Scoping Review.

Health apps are increasingly recognized as crucial tools for enhancing health care delivery. Many countries, particularly those in sub-Saharan Africa, can substantially benefit from using health apps to support self-management and thus help to achieve universal health coverage and the third sustainable development goal. However, most health apps published in app stores are of unknown or poor quality, which poses a risk to patient safety. Regulatory standards and guidance can help address this risk and promote patient safety. This review aims to assess the regulatory standards and guidance for health apps supporting evidence-based best practices in sub-Saharan Africa with a focus on self-management. A methodological framework for scoping reviews was applied. A search strategy was built and applied across the following databases, gray literature sources, and institutional websites: PubMed, Scopus, World Health Organization (WHO) African Index Medicus, OpenGrey, WHO Regional Office for Africa Library, ICTworks, WHO Directory of eHealth policies, HIS Strengthening Resource Center, International Telecommunication Union, Ministry of Health websites, and Google. The search covered the period between January 2005 and January 2024. The findings were analyzed using a deductive descriptive content analysis. The policy analysis framework was adapted and used to organize the findings. The Reporting Items for Stakeholder Analysis tool guided the identification and mapping of key stakeholders based on their roles in regulating health apps for self-management. The study included 49 documents from 31 sub-Saharan African countries. While all the documents were relevant for stakeholder identification and mapping, only 3 regulatory standards and guidance contained relevant information on regulation of health apps. These standards and guidance primarily aimed to build mutual trust; promote integration, inclusion, and equitable access to services; and address implementation issues and poor coordination. They provided guidance on systems quality, software acquisition and maintenance, security measures, data exchange, interoperability and integration, involvement of relevant stakeholders, and equitable access to services. To enhance implementation, the standards highlight that legal authority, coordination of activities, building capacity, and monitoring and evaluation are required. A number of stakeholders, including governments, regulatory bodies, funders, intergovernmental and nongovernmental organizations, academia, and the health care community, were identified to play key roles in regulating health apps. Health apps have huge potential to support self-management in sub-Saharan Africa, but the lack of regulatory standards and guidance constitutes a major barrier. Hence, for these apps to be safely and effectively integrated into health care, more attention should be given to regulation. Learning from countries with effective regulations can help sub-Saharan Africa build a more robust and responsive regulatory system, ensuring the safe and beneficial use of health apps across the region. RR2-10.1136/bmjopen-2018-025714.

Balancing security and contestability in the DMA: the case of app stores

ABSTRACT The EU’s Digital Markets Act will require certain large tech firms’ ecosystems to become more open. The Act contains few exceptions – but law-makers did include special protections for undertakings providing operating systems, like Apple and Google, to protect security. This paper explores how the Commission should assess these measures. It argues that security is not a “trump card” to undermine the Act’s objectives – instead, Apple and Google must balance security benefits of their measures against any limitations on contestability. Furthermore, the Act should continue to allow both firms to differentiate their products’ approach to security. However, Apple’s (and to a lesser extent Google’s) security measures are likely to be heavily disputed. The Act does not give the Commission effective powers to efficiently resolve such disputes nor to force gatekeepers to change their approaches to security.

Detection System Based on Text Adversarial and Multi-Information Fusion for Inappropriate Comments in Mobile Application Reviews

With the rapid development of mobile application technology, the content and forms of comments disseminated on the internet are becoming increasingly complex. Various comments serve as users’ firsthand reference materials for understanding the application. However, some comments contain a significant amount of inappropriate content unrelated to the app itself, such as gambling, loans, pornography, and game account recharging, seriously impacting the user experience. Therefore, this article aims to assist users in filtering out irrelevant and inappropriate messages, enabling them to quickly obtain useful and relevant information. This study focuses on analyzing actual comments on various Chinese apps on the Apple App Store. However, these irrelevant comments exhibit a certain degree of concealment, sparsity, and complexity, which increases the difficulty of detection. Additionally, due to language differences, the existing English research methods exhibit relatively poor adaptability to Chinese textual data. To overcome these challenges, this paper proposes a research method named “blend net”, which combines text adversarial and multi-information fusion detection to enhance the overall performance of the system. The experimental results demonstrate that the method proposed in this paper achieves precision and recall rates both exceeding 98%, representing an improvement of at least 2% compared to existing methods.

Immediate Effects of Instrument-Assisted Soft-Tissue Mobilization Versus Dry Needling on Trigger Point Pain and Tightness of Calf Muscles in Long-Distance Runners.

Introduction Muscle tightness is frequently identified as a potential precursor to muscle injuries. Reclaiming flexibility and enhancing range of motion (ROM) is crucial for preventing injuries and achieving improvements in performance.The present study examines the immediate effects of instrument-assisted soft-tissue mobilization (IASTM) and dry needling (DN) in reducing trigger point pain and calf tightness in long-distance runners. Methodology A total of 40 long-distance runners were recruited in the study (30 males and 10 females). The procedure was performed under the author's surveillance at the sports complex. These recruited players were placed into two groups: the IASTM (n=20) and the DN (n=20) group.The outcome measures used were the pressure algometer for assessing pain pressure threshold and the lunge test. An iPhone Measure app (Measure app, Apple App Store 2023) is used to assess ankle dorsiflexion ROM. The evaluation took place both prior to and immediately following the interventionand 48 hours after the intervention. Result The analysis within each group revealed a significant alteration in pain pressure threshold for both the IASTM and DN groups (p≤0.05), along with a relative enhancement in ankle dorsiflexion ROMobserved in the IASTM group (p≤0.05). Between-group analysis revealed a notable difference with an effect size difference of Cohen's d=1.06 (large difference) in pain pressure threshold, d=0.21 (small difference) in lunge test, and d=0.57 (medium difference) in ankle dorsiflexion ROM. Conclusion The present study concludes that both groups, IASTM and DN, showed significant effects in improving pain pressure threshold in long-distance runners. However, DN showed better results. IASTM showed significant results in enhancing the ankle dorsiflexion ROM immediately. This implies thatit can be used in conjunction with stretching to decrease pain and enhance flexibility, hence improving performance and preventing injuries.