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IMPORTANCE: Mobile 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. OBJECTIVE: To 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 REVIEW: A 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. FINDINGS: From 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 RELEVANCE: The 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.
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Aplicaciones Móviles , Otolaringología , Humanos , Procedimientos Quirúrgicos Otorrinolaringológicos/métodosRESUMEN
Mobile app developers are often obliged by regulatory frameworks to provide a privacy policy in natural comprehensible language to describe their apps' privacy practices. However, prior research has revealed that: (1) not all app developers offer links to their privacy policies; and (2) even if they do offer such access, it is difficult to determine if it is a valid link to a (valid) policy. While many prior studies looked at this issue in Google Play Store, Apple App Store, and particularly the iOS store, is much less clear. In this paper, we conduct the first and the largest study to investigate the previous issues in the iOS app store ecosystem. First, we introduce an App Privacy Policy Extractor (APPE), a system that embraces and analyses the metadata of over two million apps to give insightful information about the distribution of the supposed privacy policies, and the content of the provided privacy policy links, store-wide. The result shows that only 58.5% of apps provide links to purported privacy policies, while 39.3% do not provide policy links at all. Our investigation of the provided links shows that only 38.4% of those links were directed to actual privacy policies, while 61.6% failed to lead to a privacy policy. Further, for research purposes we introduce the App Privacy Policy Corpus (APPC-451K); the largest app privacy policy corpus consisting of data relating to more than 451K verified privacy policies.
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Aplicaciones Móviles , Privacidad , Ecosistema , Políticas , MetadatosRESUMEN
The global mHealth app market is rapidly expanding, especially since the COVID-19 pandemic. However, many of these mHealth apps have serious issues, as reported in their user reviews. Better understanding their key user concerns would help app developers improve their apps' quality and uptake. While app reviews have been used to study user feedback in many prior studies, many are limited in scope, size and/or analysis. In this paper, we introduce a very large-scale study and analysis of mHealth app reviews. We extracted and translated over 5 million user reviews for 278 mHealth apps. These reviews were then classified into 14 different aspects/categories of issues reported. Several mHealth app subcategories were examined to reveal differences in significant areas of user concerns, and to investigate the impact of different aspects of mhealth apps on their ratings. Based on our findings, women's health apps had the highest satisfaction ratings. Fitness activity tracking apps received the lowest and most unfavourable ratings from users. Over half of users who reported troubles leading them to uninstall mHealth apps gave a 1-star rating. Half of users gave the account and logging aspect only one star due to faults and issues encountered while registering or logging in. Over a third of users who expressed privacy concerns gave the app a 1-star rating. However, only 6% of users gave apps a one-star rating due to UI/UX concerns. 20% of users reported issues with handling of user requests and internationalisation concerns. We validated our findings by manually analysing a sample of 1,000 user reviews from each investigated aspect/category. We developed a list of recommendations for mHealth apps developers based on our user review analysis.
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BACKGROUND: Many pregnant women use the internet to obtain information about pregnancy and childbirth. Over 50% of pregnant women use pregnancy apps and must search through thousands of pregnancy or women's health-related apps available on app stores. The COVID-19 pandemic is changing how women receive prenatal care. Mobile health apps may help maintain women's satisfaction with their prenatal care. OBJECTIVE: Our objective is to identify pregnancy mobile apps and to evaluate the apps using a modified APPLICATIONS (app comprehensiveness, price, privacy, literature used, in-app purchases, connectivity, advertisements, text search field, images/videos, other special features, navigation ease, subjective presentation) scoring system. METHODS: A list of pregnancy apps was identified in the first 20 Google search results using the search term "pregnancy app." After excluding irrelevant, inaccurate, malfunctioning, or no longer available apps, all unique apps were downloaded and evaluated with the modified APPLICATIONS scoring system, which includes both objective and subjective criteria and evaluation of special features. RESULTS: A list of 57 unique pregnancy apps was generated. After 28 apps were excluded, the remaining 29 apps were evaluated, with a mean score of 9.4 points out of a maximum of 16. The highest scoring app scored 15 points. Over 60% (18/29) of apps did not have comprehensive information for every stage of pregnancy or did not contain all four desired components of pregnancy apps: health promotion/patient education, communication, health tracking, and notifications and reminders. Only 24% (7/29) of apps included a text search field, and only 28% (8/29) of apps cited literature. CONCLUSIONS: Our search yielded many high-scoring apps, but few contained all desired components and features. This list of identified and rated apps can lessen the burden on pregnant women and providers to find available apps on their own. Although health care providers should continue to vet apps before recommending them to patients, these findings also highlight that a Google search is a successful way for patients and providers to find useful and comprehensive pregnancy apps.
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COVID-19 , Aplicaciones Móviles , Telemedicina , Femenino , Humanos , Pandemias , Embarazo , Mujeres Embarazadas , SARS-CoV-2RESUMEN
Apple changed the communications landscape with its 2007 introduction of the iPhone. In little more than a decade, most Americans have become smartphone owners. With more than 200,000 applications (apps) for education available in the Apple App Store, we can infer that many smartphone owners use their devices to learn. Several surveys of medical students reveal that apps do indeed enhance clinical knowledge and provide comparable training with textbooks. We launched our first iOS app, the CTisus iQuiz, in 2010 in response to the growing number of portable devices, and with an intention to grow alongside technology. We now have 17 apps available for free on the App Store, and present tips here on how to successfully develop apps for radiology education. Furthermore, we detail the steps necessary to advertise a new app and use analytics to assess how the app is performing. Generating apps for radiology can play an important role in continuing education. As the medical and education fields are integrating increasingly with technology, it is essential that we use technology to reach and interact with its users. Creating iOS applications and using analytics to understand how they meet the goals of the developer can expand the reach of the medical and education communities and render information more accessible on mobile devices on a large scale.
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Aplicaciones Móviles , Radiología , Atención a la Salud , Humanos , Teléfono InteligenteRESUMEN
Many Americans use smartphone-based mobile applications to acquire health information. Our study evaluated the readability of mobile application-based patient educational materials (PEMs) about five prevalent cancers in the United States. The Apple and Google mobile application marketplaces were queried for breast, colon, lung, prostate, and stomach cancer-related applications, which were subsequently screened for PEMs and assessed with 10 validated readability assessments. Twenty-one pertinent applications yielded 249 articles that were written at an 11.8 ± 2.3 grade level; only 12 (4.8%) articles were written below an eighth grade level. The majority of cancer-related PEMs were written at too difficult reading levels for American patients.
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Comprensión , Redes de Comunicación de Computadores/estadística & datos numéricos , Sistemas de Información en Salud/estadística & datos numéricos , Aplicaciones Móviles/estadística & datos numéricos , Neoplasias/terapia , Teléfono Inteligente/estadística & datos numéricos , Humanos , Difusión de la Información/métodos , Neoplasias/diagnóstico , Educación del Paciente como Asunto/métodos , Estados UnidosRESUMEN
In the course of digitalization the smartphone is penetrating more and more areas of life giving the user mobile and almost ubiquitous access to the internet and other web applications. The advantages of mHealth are an integral part in some areas of patient care but in contrast to other disciplines, routine integration of mobile devices into orthopedics and trauma surgery is still in its infancy. A survey among German orthopedists and trauma surgeons revealed which kind of apps have become established in everyday clinical practice to date. Apps published by representative institutions such as the AO Foundation demonstrated the highest usage rates. In summary, the number of regularly used apps is low; however, the causes of this lack of acceptance have not yet been conclusively clarified. The authors of this study proclaim a significant increase in the use of mHealth and mobile devices in daily clinical practice in the future.
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Aplicaciones Móviles , Ortopedia , Teléfono Inteligente , Telemedicina , Alemania , HumanosRESUMEN
BACKGROUND: Adherence to medication is estimated to be around 50% for chronically ill patients in high-income countries. Improving the effectiveness of adherence interventions could have a far greater impact on population health than any improvement in specific medical treatments. Mobile health (mHealth) is one of the most effective solutions for helping patients improve their medication intake, notably through the use of mobile apps with reminder systems. With more than 327,000 apps available in the mHealth field, it is difficult for health care professionals and patients alike to choose which apps to recommend and use. OBJECTIVE: We aim to carry out a systematic search of medication management smartphone apps available in France that send reminders to patients and assess their quality using a validated scale. METHODS: Mobile apps were identified in October and November 2022 after a systematic keyword search on the 2 main app download platforms: App Store (Apple Inc) and Google Play Store. Inclusion criteria were free availability, date of last update, and availability in French. Next, 2 health care professionals independently evaluated the included apps using the French version of the Mobile App Rating Scale (MARS-F), an objective scoring system validated for assessing the overall quality of apps in the mHealth field. An intraclass correlation coefficient was calculated to determine interrater reliability. RESULTS: In total, 960 apps were identified and 49 were selected (25 from the App Store and 24 from the Google Play Store). Interrater reliability was excellent (intraclass correlation coefficient 0.92; 95% CI 0.87-0.95; P<.001). The average MARS-F score was 3.56 (SD 0.49) for apps on the App Store and 3.51 (SD 0.46) for those on the Google Play Store, with 10 apps scoring above 4 out of 5. Further, 2 apps were tested in at least one randomized controlled trial and showed positive results. The 2 apps with the highest ratings were Mediteo rappel de médicaments (Mediteo GmbH) and TOM rappel medicaments, pilule (Innovation6 GmbH), available on both platforms. Each app's MARS-F score was weakly correlated with user ratings on the App Store and moderately correlated on the Google Play Store. CONCLUSIONS: To our knowledge, this is the first study that used a validated scoring system to evaluate medication management apps that send medication reminders. The quality of the apps was heterogeneous, with only 2 having been studied in a randomized controlled trial with positive results. The evaluation of apps in real-life conditions by patients is necessary to determine their acceptability and effectiveness. Certification of apps is also essential to help health care professionals and patients identify validated apps.
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Administración del Tratamiento Farmacológico , Aplicaciones Móviles , Humanos , Francia , Reproducibilidad de los Resultados , Teléfono InteligenteRESUMEN
In today's digital world, app stores have become an essential part of software distribution, providing customers with a wide range of applications and opportunities for software developers to showcase their work. This study elaborates on the importance of end-user feedback for software evolution. However, in the literature, more emphasis has been given to high-rating & popular software apps while ignoring comparatively low-rating apps. Therefore, the proposed approach focuses on end-user reviews collected from 64 low-rated apps representing 14 categories in the Amazon App Store. We critically analyze feedback from low-rating apps and developed a grounded theory to identify various concepts important for software evolution and improving its quality including user interface (UI) and user experience (UX), functionality and features, compatibility and device-specific, performance and stability, customer support and responsiveness and security and privacy issues. Then, using a grounded theory and content analysis approach, a novel research dataset is curated to evaluate the performance of baseline machine learning (ML), and state-of-the-art deep learning (DL) algorithms in automatically classifying end-user feedback into frequently occurring issues. Various natural language processing and feature engineering techniques are utilized for improving and optimizing the performance of ML and DL classifiers. Also, an experimental study comparing various ML and DL algorithms, including multinomial naive Bayes (MNB), logistic regression (LR), random forest (RF), multi-layer perception (MLP), k-nearest neighbors (KNN), AdaBoost, Voting, convolutional neural network (CNN), long short-term memory (LSTM), bidirectional long short term memory (BiLSTM), gated recurrent unit (GRU), bidirectional gated recurrent unit (BiGRU), and recurrent neural network (RNN) classifiers, achieved satisfactory results in classifying end-user feedback to commonly occurring issues. Whereas, MLP, RF, BiGRU, GRU, CNN, LSTM, and Classifiers achieved average accuracies of 94%, 94%, 92%, 91%, 90%, 89%, and 89%, respectively. We employed the SHAP approach to identify the critical features associated with each issue type to enhance the explainability of the classifiers. This research sheds light on areas needing improvement in low-rated apps and opens up new avenues for developers to improve software quality based on user feedback.
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Google Play and Apple's App Store dominate the mobile health app market. We analyzed the metadata and descriptive texts of apps in the medical category using semi-automated retrospective app store analysis (SARASA) and compared the store offerings in terms of their number, descriptive texts, user ratings, medical device status, diseases, and conditions (both keyword-based). Relatively speaking, the store listings for the selected items were comparable.
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Aplicaciones Móviles , Telemedicina , Estudios RetrospectivosRESUMEN
Among the numerous innovations implemented in medical education since the beginning of the 21st century, small-group learning experiences have worked well for modern students and the application of computer technology provided access to thousands of lectures, images, and slides via the internet. This has helped to build an electronic foundation on which further educational adaptations have arisen in the current era, coupled with the altered communications landscape represented by Apple's introduction of the iPhone and Google's subsequent entrance onto the playing field. With the advent of smartphone applications (apps), education has taken on an even more personalized approach. Data show that the use of educational apps has been embraced by today's nursing and medical students, notably including radiology students. We survey recent research on the use and desirability of medical apps and offer practical tips for those ready to embark on developing medical, particularly radiology, educational apps including how to assess and hone them for optimal use.
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OBJECTIVES: The main objective of this work was to explore and characterize the current landscape of mobile applications available to treat mood disorders such as depression, bipolar disorder, and dysthymia. METHODS: We developed a tool that makes both the Apple App Store and the Google Play Store searchable using keywords and that facilitates the extraction of basic app information of the search results. All app results were filtered using various inclusion and exclusion criteria. We characterized all resultant applications according to their technical details. Furthermore, we searched for scientific publications on each app's website and PubMed, to understand whether any of the apps were supported by any type of scientific evidence on their acceptability, validation, use, effectiveness, etc. Results: Thirty apps were identified that fit the inclusion and exclusion criteria. The literature search yielded 27 publications related to the apps. However, these did not exclusively concern mood disorders. 6 were randomized studies and the rest included a protocol, pilot-, feasibility, case-, or qualitative studies, among others. The majority of studies were conducted on relatively small scales and 9 of the 27 studies did not explicitly study the effects of mobile application use on mental wellbeing. CONCLUSION: While there exists a wealth of mobile applications aimed at the treatment of mental health disorders, including mood disorders, this study showed that only a handful of these are backed by robust scientific evidence. This result uncovers a need for further clinically oriented and systematic validation and testing of such apps.
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Aplicaciones Móviles , Atención a la Salud , Humanos , Salud Mental , Trastornos del Humor/terapia , Motor de BúsquedaRESUMEN
In 2015, Apple launched an open-source software framework called ResearchKit. ResearchKit provides an infrastructure for conducting remote, smartphone-based research trials through the means of Apple's App Store. Such trials may have several advantages over conventional trial methods including the removal of geographic barriers, frequent assessments of participants in real-life settings, and increased inclusion of seldom-heard communities. The aim of the current study was to explore the feasibility of participant recruitment and the potential for data collection in the non-clinical population in a smartphone-based trial using ResearchKit. As a case example, an app called eMovit, a behavioural activation (BA) app with the aim of helping users to build healthy habits was used. The study was conducted over a 9-month period. Any iPhone user with access to the App Stores of The Netherlands, Belgium, and Germany could download the app and participate in the study. During the study period, the eMovit app was disseminated amongst potential users via social media posts (Twitter, Facebook, LinkedIn), paid social media advertisements (Facebook), digital newsletters and newspaper articles, blogposts and other websites. In total, 1,788 individuals visited the eMovit landing page. A total of 144 visitors subsequently entered Apple's App Store through that landing page. The eMovit product page was viewed 10,327 times on the App Store. With 79 installs, eMovit showed a conversion rate of 0.76% from product view to install of the app. Of those 79 installs, 53 users indicated that they were interested to participate in the research study and 36 subsequently consented and completed the demographics and the participants quiz. Fifteen participants completed the first PHQ-8 assessment and one participant completed the second PHQ-8 assessment. We conclude that from a technological point of view, the means provided by ResearchKit are well suited to be integrated into the app process and thus facilitate conducting smartphone-based studies. However, this study shows that although participant recruitment is technically straightforward, only low recruitment rates were achieved with the dissemination strategies applied. We argue that smartphone-based trials (using ResearchKit) require a well-designed app dissemination process to attain a sufficient sample size. Guidelines for smartphone-based trial designs and recommendations on how to work with challenges of mHealth research will ensure the quality of these trials, facilitate researchers to do more testing of mental health apps and with that enlarge the evidence-base for mHealth.
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BACKGROUND: Patients suffering from inflammatory bowel disease (IBD) frequently need long-term medical treatment. Mobile apps promise to complement and improve IBD management, but so far there has been no scientific analysis of their quality. OBJECTIVE: This study evaluated the quality of German mobile apps targeting IBD patients and physicians treating IBD patients using the Mobile Application Rating Scale (MARS). METHODS: The German Apple App Store and Google Play Store were systematically searched to identify German IBD mobile apps for patient and physician use. MARS was used by 6 physicians (3 using Android smartphones and 3 using iPhones) to independently assess app quality. Apps were randomly assigned so that the 4 apps with the most downloads were rated by all raters and the remaining apps were rated by 1 Android and 1 iOS user. RESULTS: In total, we identified 1764 apps in the Apple App Store and Google Play Store. After removing apps that were not related to IBD (n=1386) or not available in German (n=317), 61 apps remained. After removing duplicates (n=3) and apps for congresses (n=7), journals (n=4), and clinical studies (n=6), as well as excluding apps that were available in only 1 of the 2 app stores (n=20) and apps that could only be used with an additional device (n=7), we included a total of 14 apps. The app "CED Dokumentation und Tipps" had the highest overall median MARS score at 4.11/5. On the whole, the median MARS scores of the 14 apps ranged between 2.38/5 and 4.11/5. As there was no significant difference between iPhone and Android raters, we used the Wilcoxon comparison test to calculate P values. CONCLUSIONS: The MARS ratings showed that the quality of German IBD apps varied. We also discovered a discrepancy between app store ratings and MARS ratings, highlighting the difficulty of assessing perceived app quality. Despite promising results from international studies, there is little evidence for the clinical benefits of German IBD apps. Clinical studies and patient inclusion in the app development process are needed to effectively implement mobile apps in routine care.
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Enfermedades Inflamatorias del Intestino , Aplicaciones Móviles , Atención a la Salud , Humanos , Enfermedades Inflamatorias del Intestino/terapia , Teléfono InteligenteRESUMEN
BACKGROUND: It is undeniable that appropriate smartphone apps offer enormous opportunities for dealing with future challenges in orthopedic surgery and public health, in general. However, it is still unclear how the apps currently available in the two major app stores can be used in daily clinical routine by German orthopedic surgeons. OBJECTIVE: This study aimed to gain evidence regarding the quantity and quality of apps available in the two major app stores and their suitability for use by orthopedic surgeons in Germany. METHODS: We conducted a systematic, keyword-based app store screening to obtain evidence concerning the quantity and quality of commercially available apps. Apps that met the inclusion criteria were evaluated using the app synopsis-checklist for users and the German Mobile App Rating Scale for secure use, trustworthiness, and quality. RESULTS: The investigation revealed serious shortcomings regarding legal and medical aspects. Furthermore, most apps turned out to be useless and unsuitable for the clinical field of application (4242/4249, 99.84%). Finally, 7 trustworthy and high-quality apps (7/4249, 0.16%) offering secure usage in the daily clinical routine of orthopedists were identified. These apps mainly focused on education (5/7). None of them were CE (Conformité Européenne) certified. Moreover, there are no studies providing evidence that these apps have any positive use whatsoever. CONCLUSIONS: The data obtained in our study suggest that the number of trustworthy and high-quality apps on offer is extremely low. Nowadays, finding appropriate apps in the fast-moving, complex, dynamic, and rudimentarily controlled app stores is most challenging. Promising approaches, for example, systematic app store screenings, app-rating developments, reviews or app libraries, and the creation of consistent standards have been established. However, further efforts are necessary to ensure that these innovative mobile health apps not only provide the correct information but are also safe to use in daily clinical practice.
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Aplicaciones Móviles , Cirujanos Ortopédicos , Ortopedia , Alemania , HumanosRESUMEN
PURPOSE: The objective of this study was to review most of the existing free m-Health applications (Apps) that use the gamification approach to manage diabetes type 1 in both App and Google Play stores. METHODS: Free mobile health applications "apps" that were related to diabetes mellitus have been identified in both App and Google Play stores. In order to cover all the mentioned applications, the following keywords, "game for type 1 diabetes" and "gamification for type 1 diabetes" were used in English and Arabic languages. All applications that were collected in the inclusion process were carefully analyzed, and the game name, game description, game features, game mechanics, game themes, and operating systems were recorded. RESULTS: A total of eight gamified applications related to type 1 diabetes were identified. Seven of these applications were in English language and only one application was in Arabic language. The applications were categorized into three main categories based on the theme of the application. The categories were taking care of a character, quizzes, and the storytelling theme. Moreover, there was no application that included the social networking feature. CONCLUSION: This study highlighted the most important features of the free mobile health applications "apps" for diabetes type 1 available in Google Play and App stores that can contribute to enhance the self-management of the diabetes condition by patients in Saudi Arabia. The identified applications have important characteristics that can be used in the future for the care and self-control of type 1 diabetic patients in Saudi Arabia.
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BACKGROUND: Mobile mental health apps have become ubiquitous tools to assist people in managing symptoms of anxiety and depression. However, due to the lack of research and expert input that has accompanied the development of most apps, concerns have been raised by clinicians, researchers, and government authorities about their efficacy. OBJECTIVE: This review aimed to estimate the proportion of mental health apps offering comprehensive therapeutic treatments for anxiety and/or depression available in the app stores that have been developed using evidence-based frameworks. It also aimed to estimate the proportions of specific frameworks being used in an effort to understand which frameworks are having the most influence on app developers in this area. METHODS: A systematic review of the Apple App Store and Google Play store was performed to identify apps offering comprehensive therapeutic interventions that targeted anxiety and/or depression. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist was adapted to guide this approach. RESULTS: Of the 293 apps shortlisted as offering a therapeutic treatment for anxiety and/or depression, 162 (55.3%) mentioned an evidence-based framework in their app store descriptions. Of the 293 apps, 88 (30.0%) claimed to use cognitive behavioral therapy techniques, 46 (15.7%) claimed to use mindfulness, 27 (9.2%) claimed to use positive psychology, 10 (3.4%) claimed to use dialectical behavior therapy, 5 (1.7%) claimed to use acceptance and commitment therapy, and 20 (6.8%) claimed to use other techniques. Of the 162 apps that claimed to use a theoretical framework, only 10 (6.2%) had published evidence for their efficacy. CONCLUSIONS: The current proportion of apps developed using evidence-based frameworks is unacceptably low, and those without tested frameworks may be ineffective, or worse, pose a risk of harm to users. Future research should establish what other factors work in conjunction with evidence-based frameworks to produce efficacious mental health apps.
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One of the biggest growth areas in e-mental health resources has been the development and use of mobile mental health apps for smartphones and tablet devices. Such apps are being downloaded at increasing rates, but there have been questions about their efficacy and the research methodologies used to examine this. A review of the major app marketplaces, the Apple App Store and Google Play store, was conducted to locate apps claiming to offer a therapeutic treatment for depression and/or anxiety, and have research evidence for their effectiveness, according to their app store descriptions. App store descriptions were also analyzed to determine whether the app had been developed with mental health expert input; whether they had been developed in association with a government body, academic institution, or medical facility; and, whether or not they were free to download. Overall, 3.41% of apps had research to justify their claims of effectiveness, with the majority of that research undertaken by those involved in the development of the app. Other results indicated that 30.38% of shortlisted apps claimed to have expert development input; 20.48% had an affiliation with a government body, academic institution, or medical facility; and, 74.06% were free to download. Future research must consider other methodologies that may facilitate more research being completed on a greater number of apps, and future development needs to incorporate greater levels of input by mental health experts. Ways in which app stores could play a key role in encouraging more scientific research into the effectiveness of the mental health apps they sell are discussed.
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BACKGROUND: In the app stores of mobile platforms, consumers are confronted with an enormous number of mobile apps. Over the past few years, considerable research has been undertaken into to identifying, characterizing, and evaluating apps, be it in health-related or other contexts. However, many of these projects are restricted to specific areas of application and offer little flexibility in adapting the applied criteria. OBJECTIVE: This paper presents an adaptable method for selecting and characterizing mobile apps listed in a mobile App Store (the Apple App Store). The method is based on filtering processes using predefined criteria, through a semiautomated retrospective App Store analysis (SARASA). METHODS: To illustrate the SARASA process, keyword-based filtering and metadata-based description, review, and ranking steps were applied to a dataset, more specifically, an April 2018 readout of the Medical category of the German App Store, with the aim of obtaining a list of cardiology-related apps. RESULTS: From the original list of 39,427 apps within the "Medical" category of the App Store on April 14, 2018, 34,382 apps with store descriptions in languages other than German were removed. For the remaining 5045 apps, keywords related to cardiology were applied to filter the output, obtaining a final total of 335 subject-specific apps for further analysis and description. CONCLUSIONS: SARASA provides an easy to use method for applying filtering processes to identify apps matching predefined, formal criteria from app stores. The criteria can be well adapted to the needs of users. Automatic and manual analyses are easily combined when using SARASA. In the future, additional features, such as algorithmic topic analyses, may supplement the process. Although the area of application is currently limited to Apple's App Store, expansion to other stores is planned. The method stands or falls with the transparency of the app store providers and the manufacturers to make relevant meta-information available. It is up to them to liberalize information and restrict censorship to provide clients, customers, and users truly fair circumstances finding their way around the app market.