App Store Research Articles

Validated mobile applications in otolaryngology head and neck surgery for patient and physicians: A systematic literature review

ImportanceMobile apps in the field of ORL-HNS, are widely used by patients and physicians, but neither necessarily developed in collaboration with healthcare professionals nor subjected to regulations by the United States Food and Drug Administration guidelines, with a resultant potential of risk for its users. ObjectiveTo provide the ORL-HNS physician with an updated list of scientific peer review literature- validated mobile apps for safe use for both the clinician and the patients, for screening, diagnosis, therapy and follow up for various ORL-HNS pathologies. Evidence reviewA comprehensive systematic review of the scientific literature was conducted in “PubMed,” “EMBASE,” and “Web of Science” without limitation of publication date up to January 1st, 2023. The included papers validated mobile apps in the ORL-HNS discipline. Each study was evaluated using the “Strengthening the Reporting of Observational Studies in Epidemiology” (STROBE) tool. FindingsFrom the thousands of unregulated ORL-HNS mobile apps available for download and use in the various app stores, only 17 apps were validated for safe use by the clinician and/or patient. Their information is listed. Conclusions and relevanceThe limited number of validated mobile apps highlights the importance to use validated apps in clinical practice, to improve evidence-based medicine and patient safety. Physician are encouraged to use and recommend their patients to use validated mobile apps only, like any other tool in clinical practice in the evidence-based era.

AI and agents

AbstractEarlier this year, OpenAI released their GPTs framework, allowing users to set up Large Language Model (LLM)‐based personas, orchestrate them into a workflow and even offering their AI apps within an app store. This is the latest, and maybe the easiest to set up, in a string of agent‐based LLM orchestration platforms in the past year, harkening a new age of agent‐based engineering. But, like most breakthroughs, this one is also rooted in many years of research, and the reason the world is paying attention to it now is that, thanks to Generative AI and Large Language Models, we finally have artificial agents that are useful enough to scale to more serious problems.

Fashion Finder : Ai-Powered Image Analysis and Online Shopping Integration App

The proposed mobile application aims to revolutionize the fashion industry by providing users with a seamless way to discover and purchase clothing items through image recognition technology. The app allows users to either capture images of clothing items through their device's camera or upload images from their stored files. Leveraging machine learning and computer vision algorithms, the app identifies the corresponding clothing items within the images. Upon identification, the app interfaces with e-commerce platforms such as Amazon and Flipkart to search for similar items available for purchase. The development process involves extensive research, design, and implementation of features including image recognition, camera/file upload functionality, API integration with e-commerce platforms, user authentication, and additional user-friendly features. Through rigorous testing, deployment on major app stores, and continuous maintenance, the app aims to offer a seamless and engaging experience for fashion enthusiasts while adhering to user privacy and data security standards.

The death of privacy policies: How app stores shape GDPR compliance of apps

The death of privacy policies: How app stores shape GDPR compliance of apps

Why data about people are so hard to govern

AbstractHow data on individuals are gathered, analyzed, and stored remains largely ungoverned at both domestic and global levels. We address the unique governance problem posed by digital data to provide a framework for understanding why data governance remains elusive. Data are easily transferable and replicable, making them a useful tool. But this characteristic creates massive governance problems for all of us who want to have some agency and choice over how (or if) our data are collected and used. Moreover, data are co‐created: individuals are the object from which data are culled by an interested party. Yet, any data point has a marginal value of close to zero and thus individuals have little bargaining power when it comes to negotiating with data collectors. Relatedly, data follow the rule of winner take all—the parties that have the most can leverage that data for greater accuracy and utility, leading to natural oligopolies. Finally, data's value lies in combination with proprietary algorithms that analyze and predict the patterns. Given these characteristics, private governance solutions are ineffective. Public solutions will also likely be insufficient. The imbalance in market power between platforms that collect data and individuals will be reproduced in the political sphere. We conclude that some form of collective data governance is required. We examine the challenges to the data governance by looking a public effort, the EU's General Data Protection Regulation, a private effort, Apple's “privacy nutrition labels” in their App Store, and a collective effort, the First Nations Information Governance Centre in Canada.

Data Safety vs. App Privacy: Comparing the Usability of Android and iOS Privacy Labels

Privacy labels---standardized, compact representations of data collection and data use practices---are often presented as a solution to the shortcomings of privacy policies. Apple introduced mandatory privacy labels for apps in its App Store in December 2020; Google introduced mandatory labels for Android apps in July 2022. iOS app privacy labels have been evaluated and critiqued in prior work. In this work, we evaluated Android Data Safety Labels and explored how differences between the two label designs impact user comprehension and label utility. We conducted a between-subjects, semi-structured interview study with 12 Android users and 12 iOS users. While some users found Android Data Safety Labels informative and helpful, other users found them too vague. Compared to iOS App Privacy Labels, Android users found the distinction between data collection groups more intuitive and found explicit inclusion of omitted data collection groups more salient. However, some users expressed skepticism regarding elided information about collected data type categories. Most users missed critical information due to not expanding the accordion interface, and they were surprised by collection practices excluded from Android's definitions. Our findings also revealed that Android users generally appreciated information about security practices included in the labels, and iOS users wanted that information added.

Analisis Faktor-Faktor yang Berpengaruh terhadap Customer Satisfaction pada Aplikasi Mobile Health

The COVID-19 pandemic has brought positive changes to the digital health industry in Indonesia. Kimia Farma Mobile is a mobile health application that offers comprehensive features for its users. The difference in ratings on Google Play Store and Apple App Store can influence trust (brand trust) and customer satisfaction with this application. The quality of electronic services, such as application interface, delivery quality, and transaction security, is increasingly crucial in influencing customer evaluations and ratings. Therefore, this research aims to analyze the factors influencing customer satisfaction with this application. The research was conducted quantitatively online through Google Form. The sampling method used convenience sampling and was analyzed using Structural Equation Modeling-Analysis Moment of Structural (SEM-AMOS). The research findings indicate that e-service quality significantly affects brand trust and customer satisfaction. This suggests that to improve brand trust and customer satisfaction, the mobile health application should be user-friendly and secure. Furthermore, brand trust significantly influences customer satisfaction. This implies that to enhance customer satisfaction, the mobile health application should provide educational and accurate information and offer customer guarantees.

Pendampingan Penggunaan Aplikasi Budgeting Pada PT Jaya Selalu Juwana Jawa Tengah Guna Meningkatkan Pendapatan Usaha

The emerging issue in the latest technological advancements has become the most powerful mechanism for advancing living standards and environmental sustainability in the era of the 4.0 revolution, leading to the Society 5.0 era. The combination of technology, which also focuses on humans, will be balanced to advance economic growth. PT Jaya Selalu Juwana, located in Central Java, is a cold storage company engaged in the export of fresh products. This dedication to society is expected to increase knowledge and utilize technological advancements packaged through an application called "budgeting" that can be used to increase the revenue of PT Jaya Selalu Juwana, Central Java. In the future, PT Jaya Selalu Juwana, Central Java, can also analyze business activities ranging from income planning to projecting profit/loss through budgeting software applications that can be downloaded through the web or the Play Store and App Store.

Exploring Sentiment Trends: Deep Learning Analysis of Social Media Reviews on Google Play Store by Netizens

This study explores sentiment analysis of Instagram app reviews using Long Short-Term Memory (LSTM) algorithms. The rise of app stores has transformed digital interactions, particularly for social media apps. Leveraging LSTM, we aim to understand user sentiments expressed in Instagram application reviews, offering insights to enhance user experience and address concerns. The methodology involves data crawling, preprocessing, LSTM model training, and evaluation metrics. Our findings reveal promising results in accurately identifying user sentiments, with an accuracy of 77.77%, precision of 0.45, recall of 0.089, and F1-score of 0.15. This study underscores the importance of sentiment analysis in understanding user feedback and its implications for app development and user engagement.

Understanding smartphone users’ app usage with restricted permissions

PurposeSmartphone apps collect users' personal information, which triggers privacy concerns for app users. Consequently, app users restrict apps from accessing their personal information. This may impact the effectiveness of in-app advertising. However, research has not yet demonstrated what factors impact app users' decisions to use apps with restricted permissions. This study is aimed to bridge this gap.Design/methodology/approachUsing a quantitative research method, the authors collected the data from 384 app users via a structured questionnaire. The data were analysed using AMOS and fuzzy-set qualitative comparative analysis (fsQCA).FindingsThe findings suggest privacy concerns and risks have a significant positive effect on app usage with restricted permissions, whilst reputation, trust and perceived benefits have significant negative impact on it. Some app-related factors, such as the number of apps installed and type of apps, also impact app usage with restricted permissions.Practical implicationsBased on the findings, the authors provided several implications for app stores, app developers and app marketers.Originality/valueThis study examines the factors that influence smartphone users' decisions to use apps with restricted permission requests. By doing this, the authors' study contributes to the consumer behaviour literature in the context of smartphone app usage. Also, by explaining the underlying mechanisms through which the principles of communication privacy management theory operate in smartphone app context, the authors' research contributes to the communication privacy management theory.

The growing partisan politicization of non-political online spaces: A mixed-method analysis of news app reviews on Google Play between 2009 and 2022

Drawing on theories of identity politics and partisan polarization, we explored the politicization of Google Play’s news app reviews—an explicitly non-political domain. Using a mixed-methods approach, Analysis of Topic Model Networks (ANTMNs), combining topic modeling, network analysis, community detection, and theory-driven qualitative reading, we analyzed 759,143 reviews from 2009 to 2022 across 46 news apps. Three themes emerged: Technical, Content Quality, and Political. The political discourse in reviews has intensified over the years, with notable spikes around election periods. Accusations of bias were found to correlate most strongly with lower app ratings. The findings provide alarming empirical evidence for the politicization of non-political spaces, such as the app reviews section on app stores. With identity politics on the rise, this study sheds light on the importance of considering non-political online spaces for the study of political discourse.

Acceptance Analysis of Electronic Application Ready for Marriage and Pregnancy (Elsimil) Based on the Technology Acceptance Model (Tam) Approach

Purpose: The Elsimil application is an intervention effort to prevent stunting by conducting health screening which is followed up with assistance for marriage and pregnancy readiness to prospective brides. The Elsimil application review rating on the Play Store / App Store on February 01, 2023, which is 3.2, is still low and there are many user complaints related to difficulties in registering, operating the application and frequent system problems. The purpose of this study was to analyze the acceptance of the Elsimil application using the Technology Acceptance Model approach. Metod: This study uses analytical quantitative research with a cross sectional approach. Primary data obtained from a closed questionnaire, which explores the perceived ease, perceived usefulness, user attitude, and interest in using the Elsimil application. The number of samples was 33 Catin, then the data obtained was analyzed using the Partial Least Square (PLS) method using smartPLS software. Results and Discussion: Based on the results of the analysis, it shows that there is a significant effect of perceived convenience on perceived usefulness (p- value 0.045), effect of perceived convenience on user attitudes (p-value 0.000), effect of perceived usefulness on user attitudes (p-value 0.029), influence between user attitudes on interest (p-value 0.000). and influence between perceived usefulness on interest in using (p-value 0.132) in using the Elsimil application. In conclusion, of the five hypotheses proposed, four of them have a significant effect and one has no significant effect on the use of the Elsimil application.

Patient-Centered Chronic Wound Care Mobile Apps: Systematic Identification, Analysis, and Assessment.

The prevalence of chronic wounds is predicted to increase within the aging populations in industrialized countries. Patients experience significant distress due to pain, wound secretions, and the resulting immobilization. As the number of wounds continues to rise, their adequate care becomes increasingly costly in terms of health care resources worldwide. eHealth support systems are being increasingly integrated into patient care. However, to date, no systematic analysis of such apps for chronic wounds has been published. The aims of this study were to systematically identify and subjectively assess publicly available German- or English-language mobile apps for patients with chronic wounds, with quality assessments performed by both patients and physicians. Two reviewers independently conducted a systematic search and assessment of German- or English-language mobile apps for patients with chronic wounds that were available in the Google Play Store and Apple App Store from April 2022 to May 2022. In total, 3 apps met the inclusion and exclusion criteria and were reviewed independently by 10 physicians using the German Mobile App Rating Scale (MARS) and the System Usability Scale (SUS). The app with the highest mean MARS score was subsequently reviewed by 11 patients with chronic wounds using the German user version of the MARS (uMARS) and the SUS. Additionally, Affinity for Technology Interaction (ATI) scale scores were collected from both patients and physicians. This study assessed mobile apps for patients with chronic wounds that were selected from a pool of 118 identified apps. Of the 73 apps available in both app stores, 10 were patient oriented. After excluding apps with advertisements or costs, 3 apps were evaluated by 10 physicians. Mean MARS scores ranged from 2.64 (SD 0.65) to 3.88 (SD 0.65) out of 5, and mean SUS scores ranged from 50.75 (SD 27) to 80.5 (SD 17.7) out of 100. WUND APP received the highest mean MARS score (mean 3.88, SD 0.65 out of 5) among physicians. Hence, it was subsequently assessed by 11 patients and achieved a similar rating (uMARS score: mean 3.89, SD 0.4 out of 5). Technical affinity, as measured with the ATI scale, was slightly lower in patients (score: mean 3.62, SD 1.35 out of 6) compared to physicians (score: mean 3.88, SD 1.03 out 6). The quality ratings from physicians and patients were comparable and indicated mediocre app quality. Technical affinity, as assessed by using the ATI scale, was slightly lower for patients. Adequate apps for patients with chronic wounds remain limited, emphasizing the need for improved app development to meet patient needs. The ATI scale proved valuable for assessing technical affinity among different user groups.

Assessing the Quality and Behavior Change Potential of Vaping Cessation Apps: Systematic Search and Assessment.

An increasing number of people are using vapes (e-cigarettes), and with growing evidence of associated harms, there is a need for acceptable cessation support and interventions. Smartphone apps for health and well-being have increased in popularity and use. Limited published literature assesses the potential of apps to support vaping cessation. A systematic search of vaping cessation apps currently available in Australia for iOS and Android platforms was conducted. Apps were assessed against established health app assessment tools for quality and behavior change potential. A systematic search through the Australian Apple iTunes and Google Play stores was conducted using the search terms "vape"; "vaping"; "e-cigarette"; and "cessation," "quit," or "quitting" in May 2023. Only apps that encouraged the cessation of vaping were included. App descriptions were reviewed to determine if they were relevant for inclusion in this study, and relevant apps were downloaded onto the appropriate mobile device for review. The Mobile App Rating Scale (MARS) was used to rate the quality (engagement, functionality, aesthetics, and information) of the apps using an overall score out of 5. The App Behavior Change Scale (ABACUS) was used to assess the behavior change potential of each app using a score out of 21. An initial search of the app stores yielded 220 Android apps and 124 iOS apps. Screening against the inclusion criteria left 20 iOS apps and 10 Android apps for review. Six apps were available on both operating systems, and these were downloaded, reviewed, and reported separately for each operating system. The average MARS score for all apps assessed in this review was 3.1 (SD 0.41) out of 5. The reviewed apps overall performed well for the MARS elements relating to functionality, such as ease of use and navigation, but had the lowest scores for information-related elements, such as credibility. The number of ABACUS behavior change features per app ranged from 0 to 19 out of 21, with a mean of 8.9 (SD 4.51). The apps commonly included information-related features, such as requesting baseline information. The least common behavior change features were those relating to goal-setting, such as asking about the user's willingness for behavior change and providing feedback on current actions in comparison to future goals. The identified vaping cessation apps had moderate levels of quality and some behavior change components. Future vaping cessation apps could benefit from including more features that are known to support behavior change, such as goal-setting, to improve the potential benefit of these apps to support people to stop vaping. As guidelines for vaping cessation continue to be established, future apps need to reference these in their development.

Mobile Apps for Common Noncommunicable Disease Management: Systematic Search in App Stores and Evaluation Using the Mobile App Rating Scale.

The success of mobile apps in improving the lifestyle of patients with noncommunicable diseases through self-management interventions is contingent upon the emerging growth in this field. While users of mobile health (mHealth) apps continue to grow in number, little is known about the quality of available apps that provide self-management for common noncommunicable diseases such as diabetes, hypertension, and obesity. We aimed to investigate the availability, characteristics, and quality of mHealth apps for common noncommunicable disease health management that included dietary aspects (based on the developer's description), as well as their features for promoting health outcomes and self-monitoring. A systematic search of English-language apps on the Google Play Store (Google LLC) and Apple App Store (Apple Inc) was conducted between August 7, 2022, and September 13, 2022. The search terms used included weight management, obesity, diabetes, hypertension, cardiovascular diseases, stroke, and diet. The selected mHealth apps' titles and content were screened based on the description that was provided. Apps that were not designed with self-management features were excluded. We analyzed the mHealth apps by category and whether they involved health care professionals, were based on scientific testing, and had self-monitoring features. A validated and multidimensional tool, the Mobile App Rating Scale (MARS), was used to evaluate each mHealth app's quality based on a 5-point Likert scale from 1 (inadequate) to 5 (excellent). Overall, 42 apps were identified. Diabetes-specific mHealth apps accounted for 7% (n=3) of the market, hypertension apps for 12% (n=5), and general noncommunicable disease management apps for 21% (n=9). About 38% (n=16) of the apps were for managing chronic diseases, while 74% (n=31) were for weight management. Self-management features such as weight tracking, BMI calculators, diet tracking, and fluid intake tracking were seen in 86% (n=36) of the apps. Most mHealth apps (n=37, 88%) did not indicate whether there was involvement of health professionals in app development. Additionally, none of the apps reported scientific evidence demonstrating their efficacy in managing health. The overall mean MARS score was 3.2 of 5, with a range of 2.0 to 4.1. Functionality was the best-rated category (mean score 3.9, SD 0.5), followed by aesthetics (mean score 3.2, SD 0.9), information (mean score 3.1, SD 0.7), and engagement (mean score 2.9, SD 0.6). The quality of mHealth apps for managing chronic diseases was heterogeneous, with roughly half of them falling short of acceptable standards for both quality and content. The majority of apps contained scant information about scientific evidence and the developer's history. To increase user confidence and accomplish desired health outcomes, mHealth apps should be optimized with the help of health care professionals. Future studies on mHealth content analysis should focus on other diseases as well.

Mobile Applications to Support Multiple Sclerosis Communities: The Post-COVID-19 Scenario.

Introduction: The increase in the use of mobile apps since the COVID-19 pandemic, even among people with multiple sclerosis (PwMS) and health care providers (HCPs), has enabled access to reliable information, symptoms monitoring and management, and social connections. The pandemic has undoubtedly contributed to the acceleration of the "digital revolution." But how far has it progressed for the MS communities? Methods: Italian Google Play and App Store were queried, selecting MS-specific apps in English or Italian language and usable by a wide public. Results: Fifty-four (n = 54) MS-specific apps were identified; most were PwMS-oriented (83%), free of charge (94%), and in English language (76%). The 45 PwMS-oriented apps focused on increasing MS knowledge (71%), tracking symptoms (33%), and promoting networking with peers or HCPs (38%). The 13 HCPs-oriented tools addressed education and updates on MS (62%), disease assessment and management (54%), and research (15%). Google Search tool was also queried to find non-MS-specific apps to fulfill some unmet domains (as sleep, pain, sexual or mental health). Twenty-four additional apps were listed to provide a valuable contribution. Conclusion: The "digital revolution" led to increasingly customized tools for PwMS, especially as m-health or social-networking apps. However, apps to support other specific MS-relevant domains, appealing HCPs-oriented apps, and specific mobile tools for MS caregivers are still lacking. The absence of data assessing the usability and quality of MS apps in ecologically contexts leads to not reliable conclusions about potential benefits. A strong dialogue between MS communities and the digital industry is encouraged to fill this gap.

Can Your Smartphone Save A Life? A Systematic Review of Mobile-Based Interventions For Suicide Prevention

Mobile health (mHealth) apps are handy tools for tackling stigmatized mental health issues, including suicide. Mobile-based interventions for suicide prevention are easily accessible, increase the likelihood of honest reporting on sensitive topics and reduce stigma as compared to face-to-face or traditional interventions. Many mHealth apps for suicide prevention exist. However, the persuasive strategies employed in these apps and their efficacy remains unknown. To address this gap, we reviewed 80 suicide prevention apps available on app stores and in academic journals. We identified different persuasive strategies implemented in these apps using the Persuasive System Design (PSD) model. We also identified current trends within these apps, most and least-dominant implementations of persuasive strategies, effectiveness of apps, evaluation methods, and app content. We found that Personalization (n = 32) and Self-monitoring (n = 29) were the most-dominant strategies and Social Comparison, Social Role were the least-dominant strategies in suicide prevention apps. Based on our findings we discuss three major concerns in developing suicide prevention apps and offer recommendations for mitigating them. Our results show that persuasive strategies are a promising tool that can be used for designing suicide prevention apps. Our conclusions and recommendations will guide future work in suicide prevention app development and enhance the usability, effectiveness, and user-experience of such apps.

Matcha

Apple and Google introduced their versions of privacy nutrition labels to the mobile app stores to better inform users of the apps' data practices. However, these labels are self-reported by developers and have been found to contain many inaccuracies due to misunderstandings of the label taxonomy. In this work, we present Matcha, an IDE plugin that uses automated code analysis to help developers create accurate Google Play data safety labels. Developers can benefit from Matcha's ability to detect user data accesses and transmissions while staying in control of the generated label by adding custom Java annotations and modifying an auto-generated XML specification. Our evaluation with 12 developers showed that Matcha helped our participants improved the accuracy of a label they created with Google's official tool for a real-world app they developed. We found that participants preferred Matcha for its accuracy benefits. Drawing on Matcha, we discuss general design recommendations for developer tools used to create accurate standardized privacy notices.

A mobile app for wound cleansing

Objective: To develop a mobile application (app) to assist health professionals in the cleansing of wounds. The app aids in the evaluation of the wound and recommends wound cleansing procedures according to the wound characteristics.Methods: A contextualized instructional design was used in the development of a mobile app. A literature search was carried out to identify relevant studies for its construction. The development of the mobile app included the selection of multimedia app tools, definition of the navigation structure, planning of the environment configuration, and building of an environment for downloading the app to the mobile device.Results: The literature search yielded 15 articles. A mobile app was created with an easy-to-use graphic interface. The application stores the patient’s demographic and clinical information, health professional’s information, clinical evaluation of the wound, and recommends wound cleansing procedures and cleansing agents.Conclusion: The mobile app may be used in clinical practice to assist health professionals in the cleansing of wounds and in the selection of nursing interventions according to the different types of tissue, as well as in nursing education.

Mobile Health Applications (mHealth apps) for breastfeeding: a qualitative review using the Mobile Application Rating Scale.

mHealth apps are the most commonly used applications by women for seeking information and support for breastfeeding. The primary goal of this study is to provide a quality assessment of Italian-language mHealth apps for breastfeeding using the Italian version of the Mobile App Rating Scale (I-MARS). A systematic search was conducted on the Apple App Store, Google Play Store, and Windows Store. Inclusion criteria were: mHealth apps available in Italian, free of charge, and focused on the theme of breastfeeding. The quality assessment of the eligible mHealth apps was carried out on the latest available version using the I-MARS, by two authors independently. A total of 381 mHealth apps were identified, of which 38 mHealth apps were included and evaluated (n=9 on Google Play Store, n=29 on Apple App Store). The average total score of the objective dimension of I-MARS was found to be adequate, equal to 3,07±0,75, with a Cohen's Kappa score of 65,8%. The subjective dimension of the I-MARS, however, achieved a low average total score of 2,44±1,03, with a Cohen's Kappa score of 60,5%. In this regard, the subjective dimension of the I-MARS shows lower values compared to the subjective evaluation of the users (3,28±1,95). The informational quality dimension of mHealth apps was found to be lacking and/or inadequate in 80% of cases. 53% of the selected mHealth apps presented average quality scores that were adequate. The results of this study thus lay the groundwork for future recommendations for the development and proper use of mHealth apps for the protection, promotion, and support of breastfeeding.