Commercialization of User Data by Developers of Medicines-Related Apps: a Content Analysis.
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ABSTRACT:
SUBMITTER: Grundy Q
PROVIDER: S-EPMC6854147 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
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Commercialization of User Data by Developers of Medicines-Related Apps: a Content Analysis.
Grundy Quinn Q Chiu Kellia K Bero Lisa L
Journal of general internal medicine 20191201 12
<h4>Background</h4>Developers of medicines-related apps collect a variety of technical, health-related, and identifying user information to improve and tailor services. User data may also be used for promotional purposes. Apps, for example, may be used to skirt regulation of direct-to-consumer advertising of medicines. Researchers have documented routine and extensive sharing of user data with third parties for commercial purposes, but little is known about the ways that app developers or "first ...[more]
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Project description:OBJECTIVES:To investigate whether and how user data are shared by top rated medicines related mobile applications (apps) and to characterise privacy risks to app users, both clinicians and consumers. DESIGN:Traffic, content, and network analysis. SETTING:Top rated medicines related apps for the Android mobile platform available in the Medical store category of Google Play in the United Kingdom, United States, Canada, and Australia. PARTICIPANTS:24 of 821 apps identified by an app store crawling program. Included apps pertained to medicines information, dispensing, administration, prescribing, or use, and were interactive. INTERVENTIONS:Laboratory based traffic analysis of each app downloaded onto a smartphone, simulating real world use with four dummy scripts. The app's baseline traffic related to 28 different types of user data was observed. To identify privacy leaks, one source of user data was modified and deviations in the resulting traffic observed. MAIN OUTCOME MEASURES:Identities and characterisation of entities directly receiving user data from sampled apps. Secondary content analysis of company websites and privacy policies identified data recipients' main activities; network analysis characterised their data sharing relations. RESULTS:19/24 (79%) of sampled apps shared user data. 55 unique entities, owned by 46 parent companies, received or processed app user data, including developers and parent companies (first parties) and service providers (third parties). 18 (33%) provided infrastructure related services such as cloud services. 37 (67%) provided services related to the collection and analysis of user data, including analytics or advertising, suggesting heightened privacy risks. Network analysis revealed that first and third parties received a median of 3 (interquartile range 1-6, range 1-24) unique transmissions of user data. Third parties advertised the ability to share user data with 216 "fourth parties"; within this network (n=237), entities had access to a median of 3 (interquartile range 1-11, range 1-140) unique transmissions of user data. Several companies occupied central positions within the network with the ability to aggregate and re-identify user data. CONCLUSIONS:Sharing of user data is routine, yet far from transparent. Clinicians should be conscious of privacy risks in their own use of apps and, when recommending apps, explain the potential for loss of privacy as part of informed consent. Privacy regulation should emphasise the accountabilities of those who control and process user data. Developers should disclose all data sharing practices and allow users to choose precisely what data are shared and with whom.
| S-EPMC6425456 | biostudies-literature
Project description:BackgroundMobile health apps are increasingly available and used in a clinical context to monitor young people's mood and mental health. Despite the benefits of accessibility and cost-effectiveness, consumer engagement remains a hurdle for uptake and continued use. Hundreds of mood-monitoring apps are publicly available to young people on app stores; however, few studies have examined consumer perspectives. App store reviews held on Google and Apple platforms provide a large, rich source of naturally generated, publicly available user reviews. Although commercial developers use these data to modify and improve their apps, to date, there has been very little in-depth evaluation of app store user reviews within scientific research, and our current understanding of what makes apps engaging and valuable to young people is limited.ObjectiveThis study aims to gain a better understanding of what app users consider useful to encourage frequent and prolonged use of mood-monitoring apps appropriate for young people.MethodsA systematic approach was applied to the selection of apps and reviews. We identified mood-monitoring apps (n=53) by a combination of automated application programming interface (API) methods. We only included apps appropriate for young people based on app store age categories (apps available to those younger than 18 years). We subsequently downloaded all available user reviews via API data scraping methods and selected a representative subsample of reviews (n=1803) for manual qualitative content analysis.ResultsThe qualitative content analysis revealed 8 main themes: accessibility (34%), flexibility (21%), recording and representation of mood (18%), user requests (17%), reflecting on mood (16%), technical features (16%), design (13%), and health promotion (11%). A total of 6 minor themes were also identified: notification and reminders; recommendation; privacy, security, and transparency; developer; adverts; and social/community.ConclusionsUsers value mood-monitoring apps that can be personalized to their needs, have a simple and intuitive design, and allow accurate representation and review of complex and fluctuating moods. App store reviews are a valuable repository of user engagement feedback and provide a wealth of information about what users value in an app and what user needs are not being met. Users perceive mood-monitoring apps positively, but over 20% of reviews identified the need for improvement.
| S-EPMC7585773 | biostudies-literature
Project description:BACKGROUND:With the accessibility and widespread use of mobile phones, mobile phone apps targeting medication adherence may be useful tools to help patients take medications as prescribed. OBJECTIVE:Our objectives were to (1) characterize and assess mobile phone medication adherence apps guided by a conceptual framework on the focus of adherence interventions and (2) conduct a content analysis of Web-based reviews to explore users' perspectives and experiences with mobile phone medication adherence apps. METHODS:We searched for mobile phone medication adherence apps using keyword searches in Apple and Android operating systems. We characterized all apps in terms of number of downloads, ratings, languages, cost, and disease target. We categorized apps according to 4 key features of (1) alerting to take medication, (2) tracking medication taking, (3) reminding to refill or indicating amount of medication left, and (4) storing medication information. We then selected representative apps from each operating system for detailed quality assessment and user testing. We also downloaded Web-based reviews for these selected apps and conducted a qualitative content analysis using an inductive approach involving steps of initial open coding, construction of categories, and abstraction into themes. RESULTS:We identified 704 apps (443 from Apple and 261 from Android). The majority of apps across both operating systems had 1 or 2 features-specifically, 37.2% (165/443) and 38.1% (169/443) of Apple apps, respectively, and 41.4% (108/261) and 31.4% (108/261) of Android apps, respectively. Quality assessment and user testing of 20 selected apps revealed apps varied in quality and commonly focused on behavioral strategies to enhance medication adherence through alerts, reminders, and logs. A total of 1323 eligible Web-based reviews from these 20 selected apps were analyzed, and the following themes emerged: (1) features and functions appreciated by users, which included the ability to set up customized medication regimen details and reminders, monitor other health information (eg, vitals, supplements, and manage multiple people or pets), support health care visits (eg, having a list of medications and necessary health information in 1 app); (2) negative user experiences that captured technical difficulties (glitches, confusing app navigation, and poor interoperability), dosage schedule, and reminder setup inflexibility; and (3) desired functions and features related to optimization of information input, improvement of reminders, and upgrading app performance (better synchronization or backup of data and interoperability). CONCLUSIONS:A large number of mobile phone medication adherence apps are currently available. The majority of apps have features representing a behavioral approach to intervention. Findings of the content analysis offer mostly positive feedback as well as insights into current limitations and improvements that could be addressed in current and future medication adherence apps.
| S-EPMC6374723 | biostudies-literature
Project description:BackgroundPeople with suicidal thoughts are more inclined to seek technology-delivered interventions than in-person forms of treatment, making mobile apps for suicide prevention an ideal platform for treatment delivery. This review examines apps designed for suicide prevention, with a specific focus on user engagement.ObjectiveThis study aims to update the literature and broadly evaluate the landscape of mobile health apps for suicide prevention; examine apps with key features and primary approaches to suicide prevention; and systematically evaluate the engagement, functionality, aesthetics, and information of the apps.MethodsAll apps related to suicidal thoughts and behaviors were identified in the Google Play and iOS app stores and were systematically reviewed for their content and quality. The mobile app rating scale (MARS) was used to evaluate app usability and engagement.ResultsOf the 66 apps identified, 42 (64%) were specifically designed for people with suicidal ideation, and 59 (89%) had at least one best practice feature for suicide risk reduction. The mean overall MARS score of all apps was 3.5 (range 2.1-4.5), with 83% (55/66) of apps having a minimum acceptability score of 3. The total MARS score was not associated with the user app rating (r=-0.001; P=.99) or the number of features (r=0.24; P=.09).ConclusionsThis study identified many usable and engaging apps in app stores designed for suicide prevention. However, there are only limited apps for clinicians. Thus, mobile apps for suicide prevention should be carefully developed and clinically evaluated.
| S-EPMC8319780 | biostudies-literature
Project description:BackgroundMany countries across the globe have released their own COVID-19 contact tracing apps. This has resulted in the proliferation of several apps that used a variety of technologies. With the absence of a standardized approach used by the authorities, policy makers, and developers, many of these apps were unique. Therefore, they varied by function and the underlying technology used for contact tracing and infection reporting.ObjectiveThe goal of this study was to analyze most of the COVID-19 contact tracing apps in use today. Beyond investigating the privacy features, design, and implications of these apps, this research examined the underlying technologies used in contact tracing apps. It also attempted to provide some insights into their level of penetration and to gauge their public reception. This research also investigated the data collection, reporting, retention, and destruction procedures used by each of the apps under review.MethodsThis research study evaluated 13 apps corresponding to 10 countries based on the underlying technology used. The inclusion criteria ensured that most COVID-19-declared epicenters (ie, countries) were included in the sample, such as Italy. The evaluated apps also included countries that did relatively well in controlling the outbreak of COVID-19, such as Singapore. Informational and unofficial contact tracing apps were excluded from this study. A total of 30,000 reviews corresponding to the 13 apps were scraped from app store webpages and analyzed.ResultsThis study identified seven distinct technologies used by COVID-19 tracing apps and 13 distinct apps. The United States was reported to have released the most contact tracing apps, followed by Italy. Bluetooth was the most frequently used underlying technology, employed by seven apps, whereas three apps used GPS. The Norwegian, Singaporean, Georgian, and New Zealand apps were among those that collected the most personal information from users, whereas some apps, such as the Swiss app and the Italian (Immuni) app, did not collect any user information. The observed minimum amount of time implemented for most of the apps with regard to data destruction was 14 days, while the Georgian app retained records for 3 years. No significant battery drainage issue was reported for most of the apps. Interestingly, only about 2% of the reviewers expressed concerns about their privacy across all apps. The number and frequency of technical issues reported on the Apple App Store were significantly more than those reported on Google Play; the highest was with the New Zealand app, with 27% of the reviewers reporting technical difficulties (ie, 10% out of 27% scraped reviews reported that the app did not work). The Norwegian, Swiss, and US (PathCheck) apps had the least reported technical issues, sitting at just below 10%. In terms of usability, many apps, such as those from Singapore, Australia, and Switzerland, did not provide the users with an option to sign out from their apps.ConclusionsThis article highlighted the fact that COVID-19 contact tracing apps are still facing many obstacles toward their widespread and public acceptance. The main challenges are related to the technical, usability, and privacy issues or to the requirements reported by some users.
| S-EPMC7879719 | biostudies-literature
Project description:BackgroundWith the unprecedented growth of mobile technology, a plethora of dialysis diet apps have been developed to promote patient dietary self-management. Nevertheless, the utility of such apps remains questionable.ObjectiveThis study aimed to evaluate the content, features, and quality of commercial dialysis diet apps for adult dialysis patients.MethodsThis study consisted of a quantitative content analysis of commercial dialysis diet apps downloaded from Google Play and the Apple App Store available in the Asian marketplace, searched for using the following keywords in English: dialysis diet and diet for kidney disease. Free and paid apps available in English that provide nutrition information for adult dialysis patients were included. Apps that were not relevant to the dialysis diet, not meant for patient self-management, or redundant were excluded. Apps were evaluated for language medium (subscore=1), credibility (subscore=1), food database (subscore=1), valuable features (subscore=12), health-behavior theory constructs (subscore=60), and technical quality (subscore=25). The relationships among the variables of interest were determined by Pearson correlation. Stepwise multiple linear regression analysis was performed to identify the features that contribute to greater technical quality of dialysis diet apps. Statistical significance was defined as P<.05.ResultsA total of 22 out of 253 apps (8.7%) were eligible for evaluation. Based on a 100-point scale, the mean overall score of the apps was 31.30 (SD 14.28). Only 5% (1/22) of the apps offered relevant language options, and 46% (10/22) contained food databases. In addition, 54% (12/22) of the apps were not credible. The mean score for valuable features was 3.45 (SD 1.63) out of 12, in which general education (16/22, 73%), free download (15/22, 68%), and usability (13/22, 59%) were the three most popular features. However, the apps scored a mean of 13.41 (SD 11.56) out of 60 for health-behavior theory constructs. The overall app technical quality was considered poor, with a mean score of 2.70 (SD 0.41) out of 5. The scores of valuable features (r=.65, P=.001) and health-behavior theory constructs (r=.55, P=.009) were positively correlated with the overall technical quality of the commercial dialysis diet apps. Features such as free download (β=.43, P=.03) and usability (β=.41, P=.03) could significantly determine the functional quality of the apps. Health-behavior theory constructs such as self-monitoring could significantly predict both the subjective quality (β=.55, P=.008) and the engagement quality (β=.66, P=.001) of the apps, whereas the information quality domain could be determined by plan or orders (β=.48, P=.007) and knowledge (β=.45, P=.01).ConclusionsAlthough most of the available commercial dialysis diet apps are free and easy to use, they are subject to theory deficiency, limited language options, and a lack of food databases, credibility, tailored education, and overall technical quality.
| S-EPMC7296424 | biostudies-literature
Project description:Medication adherence is an expensive and damaging problem for patients and health care providers. Patients adhere to only 50% of drugs prescribed for chronic diseases in developed nations. Digital health has paved the way for innovative smartphone solutions to tackle this challenge. However, despite numerous apps available claiming to improve adherence, a thorough review of adherence apps has not been carried out to date.The aims of this study were to (1) review medication adherence apps available in app repositories in terms of their evidence base, medical professional involvement in development, and strategies used to facilitate behavior change and improve adherence and (2) provide a system of classification for these apps.In April 2015, relevant medication adherence apps were identified by searching the Apple App Store and the Google Play Store using a combination of relevant search terms. Data extracted included app store source, app price, documentation of health care professional (HCP) involvement during app development, and evidence base for each respective app. Free apps were downloaded to explore the strategies used to promote medication adherence. Testing involved a standardized medication regimen of three reminders over a 4-hour period. Nonadherence features designed to enhance user experience were also documented.The app repository search identified a total of 5881 apps. Of these, 805 fulfilled the inclusion criteria initially and were tested. Furthermore, 681 apps were further analyzed for data extraction. Of these, 420 apps were free for testing, 58 were inaccessible and 203 required payment. Of the 420 free apps, 57 apps were developed with HCP involvement and an evidence base was identified in only 4 apps. Of the paid apps, 9 apps had HCP involvement, 1 app had a documented evidence base, and 1 app had both. In addition, 18 inaccessible apps were produced with HCP involvement, whereas 2 apps had a documented evidence base. The 420 free apps were further analyzed to identify strategies used to improve medication adherence. This identified three broad categories of adherence strategies, reminder, behavioral, and educational. A total of 250 apps utilized a single method, 149 apps used two methods, and only 22 apps utilized all three methods.To our knowledge, this is the first study to systematically review all available medication adherence apps on the two largest app repositories. The results demonstrate a concerning lack of HCP involvement in app development and evidence base of effectiveness. More collaboration is required between relevant stakeholders to ensure development of high quality and relevant adherence apps with well-powered and robust clinical trials investigating the effectiveness of these interventions. A sound evidence base will encourage the adoption of effective adherence apps, and thus improve patient welfare in the process.
| S-EPMC5878368 | biostudies-literature
Project description:BackgroundLow milk production is one of the main reasons for premature breastfeeding cessation. Smartphone apps have the potential to assist mothers with promoting, interpreting, tracking, or learning about milk production. It is not known whether breastfeeding apps contain high-quality, engaging, and diverse content and features that could be used by mothers to increase their breastfeeding self-efficacy and answer their questions about milk production.ObjectiveThe overarching objective of this study was to identify and evaluate features and content within breastfeeding apps that could be used by mothers to increase breastfeeding self-efficacy and answer their questions about milk production. The secondary objectives were to quantify the diversity of representation of breastfeeding experiences within breastfeeding apps and to define the type of organization that is most likely to create free apps and/or apps with high-quality, engaging, and diverse features and content related to milk production.MethodsBreastfeeding apps were identified in the Apple App Store. All features that assist mothers with tracking, promoting, or interpreting milk production in the first 0-6 months postpartum were noted. Every screen containing educational information about milk production was identified and saved for review. Images of mothers and caretakers within the selected screenshots were assessed. Three scoresheets informed by Social Cognitive Theory were created to evaluate all identified features, educational content, and images representing the breastfeeding experience.ResultsForty-one breastfeeding apps were reviewed. Only seven apps contained both features and educational content related to milk production. Thirteen apps that contained educational content related to milk production received a mean combined content and cultural diversity score of 15.3 of 78. Of the 48 photos reviewed in screenshots that contained educational content on milk production, 87.5% (n=42) were of white women and their infants. For-profit companies and large organizations were most likely to create free apps and apps that received high scores on the combined content and diversity or features scoresheet, respectively.ConclusionsFeatures and educational content related to milk production and breastfeeding imagery within breastfeeding apps were evaluated using three novel scoresheets informed by Social Cognitive Theory. Few apps contained both features that promote breastfeeding self-efficacy and high-quality, engaging, educational content with images of diverse caretakers. Thus, it is likely that parents, especially those from minority or low-income groups, have limited options when selecting a breastfeeding app. App developers could use the scoresheets and findings in this review to develop breastfeeding apps that assist mothers with interpreting, tracking, or learning about milk production through high-quality and engaging features, content, and imagery.
| S-EPMC6715395 | biostudies-literature
Project description:BackgroundThe prevalence of obesity in India is increasing at an alarming rate. Obesity-related mHealth apps have proffered an exciting opportunity to remotely deliver obesity-related information. This opportunity raises the question of whether such apps are truly effective.ObjectiveThe aim of this study was to identify existing obesity-related mHealth apps in India and evaluate the potential of the apps' contents to promote health behavior change. This study also aimed to discover the general quality of obesity-related mHealth apps.MethodsA systematic search for obesity-related mHealth apps was conducted in both the Google Play Store and the Apple App Store. The features and quality of the sample apps were assessed using the Mobile Application Rating Scale (MARS) and the potential of the sample apps' contents to promote health behavior change was assessed using the PRECEDE-PROCEED Model (PPM).ResultsA total of 13 apps (11 from the Google Play Store and 2 from the Apple App Store) were considered eligible for the study. The general quality of the 13 apps assessed using MARS resulted in mean scores ranging from 1.8 to 3.7. The bivariate Pearson correlation between the MARS rating and app user rating failed to establish statistically significant results. The multivariate regression analysis result indicated that the PPM factors are significant determinants of health behavior change (F3,9=63.186; P<.001) and 95.5% of the variance (R2=0.955; P<.001) in the dependent variable (health behavior change) can be explained by the independent variables (PPM factors).ConclusionsIn general, mHealth apps are found to be more effective when they are based on theory. The presence of PPM factors in an mHealth app can greatly influence the likelihood of health behavior change among users. So, we suggest mHealth app developers consider this to develop efficient apps. Also, mHealth app developers should consider providing health information from credible sources and indicating the sources of the information, which will increase the perceived credibility of the apps among the users. We strongly recommend health professionals and health organizations be involved in the development of mHealth apps. Future research should include mHealth app users to understand better the apps' effectiveness in bringing about health behavior change.
| S-EPMC9133986 | biostudies-literature
Project description:ContextMore than 78 countries have developed COVID contact-tracing apps to limit the spread of coronavirus. However, many experts and scientists cast doubt on the effectiveness of those apps. For each app, a large number of reviews have been entered by end-users in app stores.ObjectiveOur goal is to gain insights into the user reviews of those apps, and to find out the main problems that users have reported. Our focus is to assess the "software in society" aspects of the apps, based on user reviews.MethodWe selected nine European national apps for our analysis and used a commercial app-review analytics tool to extract and mine the user reviews. For all the apps combined, our dataset includes 39,425 user reviews.ResultsResults show that users are generally dissatisfied with the nine apps under study, except the Scottish ("Protect Scotland") app. Some of the major issues that users have complained about are high battery drainage and doubts on whether apps are really working.ConclusionOur results show that more work is needed by the stakeholders behind the apps (e.g., app developers, decision-makers, public health experts) to improve the public adoption, software quality and public perception of these apps.
| S-EPMC8566091 | biostudies-literature