Designing an Arabic Google Play Store User Review Dataset for Detecting App Requirement Issues

2021 ◽  
pp. 133-143
Author(s):  
Maha Al-Shamani ◽  
Mohammed Al-Sarem ◽  
Faisal Saeed ◽  
Wafa’a Almutairi
Keyword(s):  
Google Play ◽  
User Review

scholarly journals Analytics for measuring library use and satisfaction of mobile apps

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Simran Kaur ◽  
Rupak Chakravarty
Keyword(s):  
Design Methodology ◽  
Mobile Apps ◽  
Mobile App ◽  
Content Type ◽  
Library Use ◽  
Artificial Intelligence Algorithm ◽  
Android App ◽  
Google Play ◽  
Insight Into ◽  
User Review

Purpose User review is a significant component of mobile app markets such as the Google Play Store, App Store, Microsoft Store and others. Users submit their reviews for downloaded apps on these sites in the form of star ratings and text reviews. Apps can contain huge volumes of feedback, making it difficult for the user and the developer to skim through thousands of such reviews to get an insight into usage and impact of such apps. Thus, the current study aims to assess the usage and satisfaction among users of the Mendeley’s Android app vs iOS app. Design/methodology/approach The analytics are performed by using Appbot analytics software which captured, monitored, measured and analyzed the review results for a particular period. Appbot provides easy-to-understand insights of an app using artificial intelligence algorithm tools. Findings The findings of the study reveal strong inclination, adoption and usage of Mendeley’s Android app compared to that of iOS among users. Originality/value The value of this research is in getting an insight of the pattern/behavior of users towards using apps on different platforms (Android vs iOS) and provides valuable results for the app developers in monitoring usage and enhancing features for the satisfaction of users. Without mobile app analytics, one will be blindly trying out different things without any evidence to back up their experiments.

Mobile Applications for Health Management of Older Adults: A Scoping Review (Preprint)

2020 ◽  
Author(s):  
Nurul Asilah Ahmad ◽  
Shahrul Azman Mohd Noah ◽  
Arimi Fitri Mat Ludin ◽  
Suzana Shahar ◽  
Noorlaili Mohd Tohit
Keyword(s):  
Older Adults ◽  
Goal Setting ◽  
Mobile Applications ◽  
Health Management ◽  
Mobile Apps ◽  
Personalized Feedback ◽  
Self Monitoring ◽  
App Store ◽  
Evidenced Based ◽  
Google Play

BACKGROUND Currently, the use of smartphones to deliver health-related content has experienced a rapid growth, with more than 165,000 mobile health (mHealth) applications currently available in the digital marketplace such as iOS store and Google Play. Among these, there are several mobile applications (mobile apps) that offer tools for disease prevention and management among older generations. These mobile apps could potentially promote health behaviors which will reduce or delay the onset of disease. However, no review to date that has focused on the app marketplace specific for older adults and little is known regarding its evidence-based quality towards the health of older adults. OBJECTIVE The aim of this review was to characterize and critically appraise the content and functionality of mobile apps that focuses on health management and/or healthy lifestyle among older adults. METHODS An electronic search was conducted between May 2019 to December 2019 of the official app store for two major smartphone operating systems: iPhone operating system (iTunes App Store) and Android (Google Play Store). Stores were searched separately using predetermined search terms. Two authors screened apps based on information provided in the app description. Metadata from all included apps were abstracted into a standard assessment criteria form. Evidenced based strategies and health care expert involvement of included apps was assessed. Evidenced based strategies included: self-monitoring, goal setting, physical activity support, healthy eating support, weight and/or health assessment, personalized feedback, motivational strategies, cognitive training and social support. Two authors verified the data with reference to the apps and downloaded app themselves. RESULTS A total of 16 apps met the inclusion criteria. Six out of 16 (37.5%) apps were designed exclusively for the iOS platform while ten out of 16 (62.5%) were designed for Android platform exclusively. Physical activity component was the most common feature offered in all the apps (9/16, 56.3%) and followed by cognitive training (8/16, 50.0%). Diet/nutrition (0/16, 0%) feature, however, was not offered on all reviewed mobile apps. Of reviewed apps, 56.3% (9/16) provide education, 37.5% (6/16) provide self-monitoring features, 18.8% (3/16) provide goal setting features, 18.5% (3/16) provide personalized feedback, 6.3% (1/16) provide social support and none of the reviewed apps offers heart rate monitoring and reminder features to the users. CONCLUSIONS All reviewed mobile apps for older adults in managing health did not focused on diet/nutrition component, lack of functional components and lack of health care professional involvement in their development process. There is also a need to carry out scientific testing prior to the development of the app to ensure cost effective and its health benefits to older adults. Collaborative efforts between developers, researchers, health professionals and patients are needed in developing evidence-based, high quality mobile apps in managing health prior they are made available in the app store.

A review of mHealth depression apps: Assessing app functions for the Self-Determination Theory (Preprint)

2020 ◽  
Author(s):  
Luke Brownlow
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Basic Needs ◽  
Health Behavior Change ◽  
Self Determination Theory ◽  
Healthcare Research ◽  
The Self ◽  
Self Determination ◽  
Ideal Tool ◽  
Google Play

BACKGROUND Smartphone applications (apps) are an ideal tool that is highly accessible to people who wish to begin self-treatment for depression. While many studies have performed content analyses on healthcare apps, few studies have reviewed these apps for adherence to behavior theory. Furthermore, apps for depression management are underrepresented in healthcare research. OBJECTIVE The objective of this study is to assess mHealth depression apps using SDT as a theoretical framework for meeting needs of autonomy, competence and, relatedness METHODS All depression healthcare apps available in Australia from the iTunes and Google Play app stores that met the inclusion criteria were analyzed. Each app was reviewed based on price options, store availability, download rates, and how in-app functions met the three basic needs for motivation towards health behavior change outlined in the Self-Determination Theory (SDT). RESULTS The analysis of the apps showed that most apps were free to download (69.9%) and addressed at least one of the three needs (81.4%) of SDT. However, few apps addressed all three of the basic needs through their functions (7.7%), and no apps hosted all functions expected to stimulate motivation for health behavior change. Furthermore, neither store availability, price option nor download rate were accurate predictors that apps hosted in-app functions expected to meet the basic needs. CONCLUSIONS The results suggest that some depression healthcare apps that meet the basic needs would effectively stimulate motivation (i.e., autonomy, competence, and relatedness). However, each individual app is limited in its number of functions that meet the basic needs. People who want access to more functions would need to download a suite of apps.

Evaluation of Persian language epilepsy-related mobile apps: A systematic review and quality assessment with a focus on content (Preprint)

2020 ◽  
Author(s):  
Mina Zibaei ◽  
Reza Khajouei
Keyword(s):  
Information Quality ◽  
Mobile Apps ◽  
Self Care ◽  
Keywords Epilepsy ◽  
Limited Health Literacy ◽  
Persian Language ◽  
The Mean ◽  
Limited Health ◽  
Google Play

BACKGROUND In Iran, around 0.05 of population suffer from epilepsy. Poorer health outcomes stem from limited health literacy. The use of mHealth, especially for educating patients in terms of self-care can be very effective. But the important thing is the content that is presented by apps, especially when unreliable or biased information can negatively affect the patient-doctor relationship, causing anxiety or stress. Also, usability of mHealth apps and their impact on behavior change are the other important issues that should be considered. OBJECTIVE The purpose of this study was to assess the quality of Persian language epilepsy-related mobile applications in terms of functionality and quality with a focus on content. METHODS The Persian equivalent of the keywords 'epilepsy' and 'seizure' were searched in the Google Play, Cafe Bazaar and IranApps app stores and the Persian language applications about epilepsy were extracted. These apps were evaluated by two trained reviewers independently using the uMARS scale and DISCERN instrument. Also apps’ prices and the number of installations were assessed. RESULTS A total of 659 applications were retrieved, 78 of which were epilepsy-related. After exclusion of non-Persian language and duplicate apps, there remained 11 relevant apps. The overall mean uMARS score was 2.8 out of 5 while six out of 11 apps (54%) scored higher than 3. The mean figures for the section-specific scores were as follows: engagement 2.2, functionality 4.0, aesthetics 3.3, and information 2.3. The overall DISCERN scores ranged from 26 to 40 out of 80, while the mean score was 34.5. The mean score of reliability was 18.5. CONCLUSIONS This study showed that the overall information quality of the epilepsy apps is poor. The most important missing characteristics of these apps include lack of functionalities for self-care, missing entry date, lack of details about additional sources and inexistence of the risks/benefits of each treatment. The findings suggest that more efforts should be made to develop evidence-based epilepsy-related apps to cover broader domains of self-care and behavioral change techniques.

App review of anxiety and depression chatbots and their self-care features (Preprint)

2020 ◽  
Author(s):  
Arfan Ahmed ◽  
Nashva ALi ◽  
Sarah Aziz ◽  
Alaa A Abd-Alrazaq ◽  
Asmaa Hassan ◽  
...  
Keyword(s):  
Mental Health ◽  
Meta Analysis ◽  
Self Care ◽  
Anxiety And Depression ◽  
Conversational Agents ◽  
Eligibility Criteria ◽  
On Demand ◽  
User Ratings ◽  
Google Play

BACKGROUND Anxiety and depression rates are at an all-time high along with other mental health disorders. Smartphone-based mental health chatbots or conversational agents can aid psychiatrists and replace some of the costly human based interaction and represent a unique opportunity to expand the availability and quality of mental health services and treatment. Regular up-to-date reviews will allow medics and individuals to recommend or use anxiety and depression related smartphone based chatbots with greater confidence. OBJECTIVE Assess the quality and characteristics of chatbots for anxiety and depression available on Android and iOS systems. METHODS A search was performed in the App Store and Google Play Store following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol to identify existing chatbots for anxiety and depression. Eligibility of the chatbots was assessed by two individuals based on predefined eligibility criteria. Meta-data of the included chatbots and their characteristics were extracted from their description and upon installation by 2 reviewers. Finally, chatbots quality information was assessed by following the mHONcode principles. RESULTS Although around 1000 anxiety and depression related chatbots exist, only a few (n=11) contained actual chatbots that could provide the user a real substitute for a human-human based interaction, even with today's Artificial Intelligence advancements, only one of these chatbots had voice as an input/output modality. Of the selected apps that contained chatbots all were clearly built with a therapeutic human substitute goal in mind. The majority had high user ratings and downloads highlighting the popularity of such chatbots and their promising future within the realm of anxiety and depression. CONCLUSIONS Anxiety and depression chatbot apps have the potential to increase the capacity of mental health self-care providing much needed assistance to professionals. In the current covid-19 pandemic, chatbots can also serve as a conversational companion with the potential of combating loneliness, especially in lockdowns where there is a lack of social interaction. Due to the ubiquitous nature of chatbots users can access them on-demand at the touch of a screen on ones’ smartphone. Self-care interventions are known to be effective and exist in various forms and some can be made available as chatbot features, such as assessment, mood tracking, medicine tracking, or simply providing conversation in times of loneliness.

scholarly journals P50 Exploring the Merits and Availability of Smartphone Applications Related to Melanoma

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
Jade Kabbani ◽  
Jamil Kabbani ◽  
Jade Kabbani
Keyword(s):  
Clinical Management ◽  
Literature Search ◽  
Patient Access ◽  
Smartphone Applications ◽  
App Store ◽  
Widespread Availability ◽  
Smartphone Use ◽  
Clinical Tools ◽  
Google Play ◽  
Privacy Issues

Abstract Background The increased use of smartphone applications across healthcare specialties has been particularly relevant in dermatology, with dermatology related applications widely available on mainstream application stores. We reviewed published literature regarding melanoma-related applications, and the number and types of such applications available for download. Methods A literature search of “dermatology”, “smartphone” and “melanoma” was conducted to identify publications assessing applications of interest. “Melanoma” was searched in Apple’s (iOS) “App Store” and Google’s “Google Play”, and application purposes and ratings were analysed. Results 54 of the 63 literature search results explored smartphone use in relation to melanoma, describing benefits including quicker patient access to care, reduced referrals and hence unnecessary consultations, and improved accessibility to information. However, concerns include insufficient image quality, privacy issues related to encryption, and diagnostic inaccuracy. Searches on the Google Play and iOS stores identified 249 and 51 apps respectively. 25% of Google Play results were categorised as clinical tools, 17% as educational, and 58% as recreational. The corresponding results for the App store were 92%, 6% and 2%. 81% of the educational apps and 92% of the clinical management apps related to dermatology and melanoma on Google Play, whereas all of the clinical management apps and 67% of the education apps on the App store were of relevance. Conclusion The results illustrate the widespread availability of applications related to melanoma, particularly for educational and clinical purposes. Standardising photographing techniques, improving diagnostic accuracy, and privacy issues are important aspects to consider and warrant further investigation.

scholarly journals A first look at Android applications in Google Play related to COVID-19

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Jordan Samhi ◽  
Kevin Allix ◽  
Tegawendé F. Bissyandé ◽  
Jacques Klein
Keyword(s):  
Mobile Apps ◽  
Contact Tracing ◽  
Location Tracking ◽  
Response Effort ◽  
Sensitive Data ◽  
Android Apps ◽  
Digital World ◽  
Public Health Organizations ◽  
Android Applications ◽  
Google Play

AbstractDue to the convenience of access-on-demand to information and business solutions, mobile apps have become an important asset in the digital world. In the context of the COVID-19 pandemic, app developers have joined the response effort in various ways by releasing apps that target different user bases (e.g., all citizens or journalists), offer different services (e.g., location tracking or diagnostic-aid), provide generic or specialized information, etc. While many apps have raised some concerns by spreading misinformation or even malware, the literature does not yet provide a clear landscape of the different apps that were developed. In this study, we focus on the Android ecosystem and investigate Covid-related Android apps. In a best-effort scenario, we attempt to systematically identify all relevant apps and study their characteristics with the objective to provide a first taxonomy of Covid-related apps, broadening the relevance beyond the implementation of contact tracing. Overall, our study yields a number of empirical insights that contribute to enlarge the knowledge on Covid-related apps: (1) Developer communities contributed rapidly to the COVID-19, with dedicated apps released as early as January 2020; (2) Covid-related apps deliver digital tools to users (e.g., health diaries), serve to broadcast information to users (e.g., spread statistics), and collect data from users (e.g., for tracing); (3) Covid-related apps are less complex than standard apps; (4) they generally do not seem to leak sensitive data; (5) in the majority of cases, Covid-related apps are released by entities with past experience on the market, mostly official government entities or public health organizations.

scholarly journals Google Play Content Scraping and Knowledge Engineering using Natural Language Processing Techniques with the Analysis of User Reviews

2020 ◽  
Vol 30 (1) ◽  
pp. 192-208 ◽  
Author(s):  
Hamza Aldabbas ◽  
Abdullah Bajahzar ◽  
Meshrif Alruily ◽  
Ali Adil Qureshi ◽  
Rana M. Amir Latif ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Language Processing ◽  
Mobile Application ◽  
Knowledge Engineering ◽  
Machine Learning Algorithms ◽  
Application Development ◽  
User Reviews ◽  
N Gram ◽  
Logistic Regression Algorithm ◽  
Google Play

Abstract To maintain the competitive edge and evaluating the needs of the quality app is in the mobile application market. The user’s feedback on these applications plays an essential role in the mobile application development industry. The rapid growth of web technology gave people an opportunity to interact and express their review, rate and share their feedback about applications. In this paper we have scrapped 506259 of user reviews and applications rate from Google Play Store from 14 different categories. The statistical information was measured in the results using different of common machine learning algorithms such as the Logistic Regression, Random Forest Classifier, and Multinomial Naïve Bayes. Different parameters including the accuracy, precision, recall, and F1 score were used to evaluate Bigram, Trigram, and N-gram, and the statistical result of these algorithms was compared. The analysis of each algorithm, one by one, is performed, and the result has been evaluated. It is concluded that logistic regression is the best algorithm for review analysis of the Google Play Store applications. The results have been checked scientifically, and it is found that the accuracy of the logistic regression algorithm for analyzing different reviews based on three classes, i.e., positive, negative, and neutral.

scholarly journals Comprehensively addressing postpartum maternal health: a content and image review of commercially available mobile health apps

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Laura Tucker ◽  
Alan Cuevas Villagomez ◽  
Tamar Krishnamurti
Keyword(s):  
Maternal Health ◽  
Health Information ◽  
Mobile Health ◽  
Rating Scale ◽  
The United States ◽  
People Of Color ◽  
Evidence Based ◽  
Or Education ◽  
Google Play

Abstract Background The United States is currently facing a maternal morbidity and mortality crisis, with the highest rates of any resource-rich nation. In efforts to address this, new guidelines for postpartum care suggest that mobile health (mHealth) apps can help provide complementary clinical support for new mothers during the postpartum period. However, to date no study has evaluated the quality of existing mHealth tools targeted to this time period in terms of sufficiency of maternal health information, inclusivity of people of color, and app usability. Methods Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were used to review the peripartum apps from the Apple and Google Play stores in either the Health/Fitness, Medical, or Education categories. Apps were evaluated for extent and quality of maternal health information and inclusivity of people of color using an a priori coding scheme. App usability was evaluated using the Mobile Application Rating Scale (MARS) score. Results Of the 301 apps from the Apple and Google Play stores, 25 met criteria for final evaluation. Of the 30 maternal health topics coded for, the median number addressed by apps was 19.5 (65%). Peripartum behaviors were more frequently addressed than peripartum outpatient care topics and peripartum acute health risks. The coverage of maternal health information and inclusivity of people of color in app imagery both correlated positively with the MARS usability score of the app. Only 8 apps (32%) portrayed greater than 24% images of people of color- the percent of non-white Americans according to 2019 census estimates. There was no correlation between MARS usability score and number of app users, as estimated by number of ratings for the app available on the app store. In addition, apps with evidence-based maternal health information had greater MARS engagement, information, and aesthetics scores. However, presence of evidence-based information did not correlate with greater numbers of app users. Conclusions Current commercially available peripartum apps range widely in quality. Overall current app offerings generally do not provide adequate maternal health information and are not optimally accessible to the target users in terms of inclusivity of women of color or app usability. Apps delivering evidence-based information and more usable design are more likely to meet these standards but are not more likely to be downloaded by users.

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