App Functionality Research Articles

Smartphone Apps for Pulmonary Hypertension: Systematic Search and Content Evaluation.

Pulmonary hypertension (PH) is a chronic and complex condition, requiring consistent management and education. The widespread use of smartphones has opened possibilities for mobile health apps to support both patients and health care professionals in monitoring and managing PH more effectively. This study aimed to identify and assess the quality of free smartphone apps for PH targeted at either patients or health care professionals. A systematic search was conducted on freely available apps for patients with PH and health care professionals, accessed from a Spanish IP address, on Android (Google Play) and iOS (App Store) platforms. Searches were performed in October 2022 and 2023. Apps were independently analyzed by two reviewers, focusing on general characteristics. Quality assessment was based on the Mobile Application Rating Scale (MARS) framework, and Mann-Whitney U tests compared mean MARS scores against specific variables. In the overall study, 21 apps were identified. In the 2022 search, 19 apps were listed (9 iOS, 7 Android, 3 available on both platforms). In the subsequent 2023 search, 16 apps were identified (6 Android, 7 iOS, 3 available on both platforms). Of those identified in 2022, 14 remained available in 2023, with only 7 updated since 2022. In addition, 12 apps targeted patients or the general population, while 9 targeted health care professionals; none involved patients in the development or design. Conversely, 13 apps involving health care professionals were identified. There were 10 apps that received pharmaceutical industry funding. The primary goal for 81% (17/21) of the apps was to disseminate general information about PH. The overall mean MARS quality was acceptable in 2022 and 2023, with mean ratings of 3.1 (SD 0.6) and 3.3 (SD 0.5), respectively. The functionality category achieved the highest scores in both years, indicating ease of use and intuitive navigation. In contrast, the subjective quality domain consistently received the lowest ratings in the MARS assessment across both years. None of the apps underwent clinical testing themselves; however, 2 incorporated tools or algorithms derived from trials. The overall quality of iOS apps statistically outperformed that of Android apps in both years (P<.05). Furthermore, the involvement of health care professionals in app development was associated with enhanced quality, a trend observed in both years (P=.003 for both years). This review of mobile health apps for PH reveals their emergent development stage, with generally acceptable quality but lacking refinement. It highlights the critical role of health care professionals in app development, as they contribute significantly to quality and reliability. Despite this, a notable stagnation in app quality and functionality improvement over 2 years points to a need for continuous innovation and clinical validation for effective clinical integration. This research advocates for future app developers to actively engage with health care professionals, integrate patient insights, and mandate rigorous clinical validation for PH management.

Enhancing nursing care through technology and standardized nursing language: The TEC-MED multilingual platform.

This study describes the design, integration, and semantic interoperability process of a minimum data set using standardized nursing language in the caring module of the TEC-MED care platform. The caring module was developed in three phases (2020-2022): platform concept, functional design and construction, and testing and evaluation. Phases involved collaboration among academics, information technology developers, and social/healthcare professionals. Nursing taxonomies (NANDA-I, NOC, NIC) were integrated to support the nursing process. The platform was piloted in six Mediterranean countries. The final platform features an assessment module with eight dimensions for data collection on older adults and their caregivers. A clinical decision support system links assessment data with nursing diagnoses, outcomes, and interventions. The platform is available in six languages (English, Spanish, French, Italian, Greek, and Arabic). Usability testing identified the need for improved Arabic language support. The TEC-MED platform is a pioneering tool using standardized nursing language to improve care for older adults in the Mediterranean. The platform's multilingualism promotes accessibility. Limitations include offline use and mobile app functionality. Pilot testing is underway to evaluate effectiveness and facilitate cross-cultural validation of nursing taxonomies. The TEC-MED platform offers standardized nursing care for older adults across the Mediterranean, promoting consistent communication and evidence-based practice. This approach has the potential to improve care quality and accessibility for a vulnerable population.

Factors Influencing Consumers’ Resistance Towards Property Rental Payments In Proptech Apps

This study investigates the reasons behind resistance to using the payment functionalities of proptech apps among users who have adopted the search features but not the payment feature. To explore this, the study employs Innovation Resistance Theory (IRT), mixed with variables from UTAUT2. Previous research showed that various barriers can influence user resistance to app payments. A mixed-methods approach is used in this research, combining qualitative preliminary testing and quantitative main testing. The study adopts convenience sampling to gather data. Data were collected through questionnaire and analyzed using Multiple Linear Regression Analysis in SPSS 27.0. The findings reveal that three main barriers—Risk, Tradition, and Image—significantly influence users from making payments through proptech apps. The Risk Barrier pertains to concerns over security and privacy. The Tradition Barrier involves users' preference for conventional method ways over alternatives. The Image Barrier relates to the perception of the app's reputation and trustworthiness. Future research recommendation include conducting discriminant analysis to compare non-adopters of proptech app payments distinct groups, incorporate demographic elements such as age, income, and gender as moderating variables and including additional independent variables that can expand the research scope. This study contributes to the existing literature by addressing user resistance to increase the adoption of digital payment functionalities in proptech applications. The findings can help app developers and marketers design better strategies to overcome these barriers and promote wider acceptance of proptech app payments.

Exploring the Impact of AI Enhancement on the Sports App Community: Analyzing Human-Computer Interaction and Social Factors Using a Hybrid SEM-ANN Approach

The iteration of AI technology has enhanced the industry competitiveness of sports apps and brought a new emotional experience to users. However, the community function of AI-enabled sports apps has not yet received sufficient attention. This study adopts the technology acceptance model framework through the human-computer interaction and social psychology perspectives, incorporating perceived interactivity (human-human interaction, human-information interaction, human-system interaction), user experience (functional experience, content experience, and emotional experience), attachment theory (emotional attachment, emotional loyalty), social identity, social trust, and satisfaction variables to construct a theoretical model. It aims to solve the problem of how AI can enhance users’ emotional interaction, community stickiness, and ultimately social interaction satisfaction in sports apps. Through literature review, theoretical analysis, and case study, the Chinese “KEEP” APP was identified as the research object, and the questionnaire was constructed with an improved test scale. The study used a cross-sectional sampling method to collect data from Chinese online platforms for three months (N = 520) and tested the hypotheses in the theoretical model through structural equation modeling and artificial neural networks. The results of the study show that (1) emotional attachment, emotional loyalty, social identity, and social trust positively and significantly affect user satisfaction; (2) emotional attachment and social identity positively and significantly affect human-human interaction; (3) perceived usefulness, social identity, and social trust significantly construct an influence loop on the internal path. Compared with existing studies, this study proposes a multidimensional innovative framework that reveals the deeper influence mechanism of AI technology in sports APP communities and makes up for the shortcomings of existing studies in terms of users’ emotional interactions and community stickiness. Through this study, sports APP developers and operators, marketers, AI technology developers, as well as sports enthusiasts, and general users can obtain specific practical suggestions to further optimize the design and functionality of sports apps, and enhance the overall user experience and satisfaction.

Nutrition-Related Mobile Apps in the Spanish App Stores: Quality and Content Analysis.

Mobile apps represent accessible and cost-effective tools to improve nutrition and prevent chronic diseases. However, most of these apps have been characterized as having limited functionality, raising concerns about their effectiveness, acceptability, and efficacy. The aims of the study were to assess the quality of popular nutrition-related app platforms in Spain and to describe their characteristics and functionalities. We screened apps providing information on dietary advice, food advice, and nutritional content in the Apple App Store and Google Play Store in Spain from March 2 to March 16, 2024. Apps with a star rating of ≥4 (of 5 stars), those available in Spanish, those that were free of charge, those last updated after January 2022, those with >500 reviews, and those with >500,000 downloads were included. The quality of apps was assessed using the user version of the Mobile App Rating Scale (uMARS). General characteristics and nutritional, health, and market-related functionalities of the nutrition-related apps were described. Correlations among total and uMARS sections, star ratings, and number of reviews and downloads were evaluated. Among the 1460 apps identified in the search, 42 apps met the criteria. The majority of these (n=20, 48%) aimed at recording and analyzing food intake, followed by those providing nutritional plans or diets (n=9, 21%), advising on healthy habits (n=7, 17%), and offering recipes (n=6, 14%). The most prevalent nutritional functionalities offered were recording and monitoring body measurements (n=30, 71%), food tracking (n=26, 62%), and dietary analysis (n=25, 60%), whereas nutrition education was less common (n=16, 38%). Among market-related functionalities, advertisements were the most common among the study apps (n=30, 71%), followed by the option of sharing on social media (n=29, 69%) and customizable reminders (n=26, 62%). Sharing the recorded information in the app with health professionals was infrequent (n=1, 2%). The mean (SD) total uMARS score (maximum 5 points) was 3.78 (0.35), while the mean (SD) uMARS scores for functionality, aesthetics, engagement, and information were 4.21 (0.38), 3.94 (0.54), 3.51 (0.46), and 3.48 (0.44), respectively. Lower mean scores were observed for the subjective quality (mean 2.65, SD 0.56) and perceived impact (mean 3.06, SD 0.67). Moderate to strong positive significant correlations were mostly observed between total uMARS and section-specific uMARS scores, while the correlations between the uMARS section scores were mostly moderate positive. Total uMARS scores were very weakly correlated with user rating, number of reviews, and number of downloads. The quality of popular nutrition-related app platforms in Spain was acceptable, with observed remarkable differences between sections. The majority of the apps were appealing due to their user-friendly interfaces. Only a few apps, however, provided dietary structure analysis or nutritional education. Further research is needed to assess the long-term impact of these apps on users.

The Medium is the Message: How Secure Messaging Apps Leak Sensitive Data to Push Notification Services

Like most modern software, secure messaging apps rely on thirdparty components to implement important app functionality. Although this practice reduces engineering costs, it also introduces the risk of inadvertent privacy breaches due to misconfiguration errors or incomplete documentation. Our research investigated secure messaging apps' usage of Google's Firebase Cloud Messaging (FCM) service to send push notifications to Android devices. We analyzed 21 popular secure messaging apps from the Google Play Store to determine what personal information these apps leak in the payload of push notifications sent via FCM. Of these apps, 11 leaked metadata, including user identifiers (10 apps), sender or recipient names (7 apps), and phone numbers (2 apps), while 4 apps leaked the actual message content. Furthermore, none of the data we observed being leaked to FCM was specifically disclosed in those apps' privacy disclosures. We also found several apps employing strategies to mitigate this privacy leakage to FCM, with varying levels of success. Of the strategies we identified, none appeared to be common, shared, or well-supported. We argue that this is fundamentally an economics problem: incentives need to be correctly aligned to motivate platforms and SDK providers to make their systems secure and private by default.

Exploration of the Application of Modern Information Technology in the Teaching of Criminal Law

With the arrival of the information age, modern information technology is more and more widely used in the teaching of criminal law, injecting fresh blood into it and revitalizing the discipline of criminal law. However, the use of modern information technology by criminal law teachers in the practical teaching of criminal law often fails to achieve the expected results, which indicates that the level of modern information technology mastered by criminal law teachers needs to be improved. In order to stimulate students' interest in learning criminal law in the new era, teachers of criminal law need to give full play to the advantages of modern information technology, and not only reasonably use cell phone APP function, micro classes and short videos and other skills to improve the level of modern information skills of their own teachers in the teaching of criminal law, but also pay attention to the organic fusion of the teaching method and modern information technology, highlighting the key points of the teaching, and focusing on the teaching effect.

Navigating user discontent in wearable tech: an in-depth study of Fitbit reviews

ABSTRACT In the burgeoning field of wearable technology, Fitbit has emerged as an influential entity. Even the most influential companies, however, need to understand user dissatisfaction, particularly extracted from critical reviews, in order to enhance the user experience. This study analyzes a subset of 28,664 Fitbit consumer reviews from the Google Store, all giving it a rating of 1 out of 5 points, in order to identify the reasons for user dissatisfaction. Employing thematic analysis, sentiment analysis, and topic modelling, our research reveals prominent issues impacting user perception. Key findings include significant challenges with device syncing, app functionality, and customer service, alongside a spectrum of sentiments ranging from neutral to negative. Topic modelling further distinguishes various categories of user feedback, underscoring the diversity in user experiences and expectations. These insights suggest a pressing need for improvements in technical functionality, user interface design, and customer support. This study contributes to a deeper understanding of consumer experiences in wearable technology, offering valuable guidance for enhancing product design and customer engagement strategies in this dynamic market.

Mobile health apps for cardiovascular risk assessment: a systematic review.

mHealth apps (MHA) are emerging as promising tools for cardiovascular risk assessment, but few meet the standards required for clinical use. We aim to evaluate the quality and functionality of mHealth apps for cardiovascular risk assessment by healthcare professionals. We conducted a systematic review of MHA for cardiovascular risk assessment in the Apple Store, Play Store, and Microsoft Store until August 2023. Our eligibility criteria were based on the 2021 European Society Cardiology Guidelines on Cardiovascular Disease Prevention in Clinical Practice, the Framingham Risk Score, and the Atherosclerotic Cardiovascular Disease score. Our protocol was drafted using the Preferred Reporting items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. To assess quality, we used the validated Mobile Apps Rating Scale (MARS) score, which includes 19 items across four objective scales (engagement, functionality, aesthetics, and information quality) and one additional subjective scale. For functionality evaluation, we used the IMS Institute for Healthcare Informatics functionality scale. We performed data synthesis by generating descriptive statistics. A total of 18 MHA were included in the review. The most common scores used were the Framingham score, ASCVD score, and Score 2. Only six apps achieved an overall score of 4 or greater in the MARS evaluation. The MHA with the highest MARS score was ESC CVD Risk Calculation (5 points), followed by ASCVD Risk Estimator Plus (4.9 points). In the IMS scale, four MHA had a high functionality score: ASCVD Risk Estimator Plus (5 points), ESC CVD Risk Calculation (5 points), MDCalc Medical Calculator (4 points), and Calculate by QsMD (4 points). A gap exists in the availability of high-quality MHA designed for healthcare professionals to facilitate shared decision-making in cardiovascular risk assessment. The International Prospective Register of Systematic Reviews, identifier CRD42023453807.

Analysis of cognitive behavioural therapy apps for generalised anxiety disorder: Evidence-based content and user experience

Mental illness substantially contributes to the global burden of disease, with anxiety high in prevalence. The increase of mobile technology, mental health apps have potential to lessen this burden. However, within apps, the use of evidence-based interventions, such as cognitive behavioural therapy (CBT) are limited. Regardless, many commercially available mental health apps are highly rated by users, highlighting the need to understand what makes mental health apps valuable to the user. The contribution of this study was to uncover apps that support generalised anxiety disorder (GAD) and worry with a CBT basis, explore app functionality, and user experience. Firstly, by identifying apps that support GAD and worry and included CBT. Secondly, by identifying and analysing therapeutic and engagement functions within the apps, and finally, by thematically analysing user reviews. Six apps were identified to support GAD and worry that purported to be CBT-based. However, CBT therapeutic features and engagement features were minimally present in the apps. User reviews yielded 112 comments about the apps and key themes were identified about the app users’ global experiences with the app, and about the combination of technological (e.g., useability, reliability) and therapeutic experiences (e.g., learning and using skills). Future development of quality apps to support GAD and worry must consider the empirical standing of both therapeutic and technology aspects, to provide efficacious and engaging interventions.

Assessment of Eye Care Apps for Children and Adolescents Based on the Mobile App Rating Scale: Content Analysis and Quality Assessment.

In China, the current situation of myopia among children and adolescents is very serious. Prevention and control of myopia are inhibited by the lack of medical resources and the low awareness about eye care. Nevertheless, mobile apps provide an effective means to solve these problems. Since the health app market in China is still immature, it has become particularly important to conduct a study to assess the quality of eye-care apps to facilitate the development of better eye-care service strategies. This study aimed to evaluate the quality, functionality, medical evidence, and professional background of eye-care apps targeting children and adolescents in the Chinese app stores. A systematic search on iOS and Android app stores was performed to identify eye-care apps for children and adolescents. The general characteristics, development context, and functional features of the apps were described. Quality assessment of the apps was completed by 2 independent researchers using the Mobile App Rating Scale. This study included 29 apps, of which 17 (59%) were developed by commercial organizations and 12 (41%) had a design with relevant scientific basis. The main built-in functions of these apps include self-testing (18/29, 62%), eye exercises (16/29, 55%), and eye-care education (16/29, 55%). The mean overall quality of eye-care apps was 3.49 (SD 0.33), with a score ranging from 2.89 to 4.39. The overall Mobile App Rating Scale score exhibited a significant positive correlation with the subscale scores (r=0.81-0.91; P<.001). In addition, although most apps provided basic eye-care features, there are some deficiencies. For example, only a few apps were developed with the participation of medical organizations or professional ophthalmologists, and most of the apps were updated infrequently, failing to provide the latest eye-care information and technology in a timely manner. In general, the quality of eye-care apps for children and teenagers in Chinese app stores is good. These apps fulfill users' needs for eye-care services to a certain extent, but they still suffer from insufficient medical background, low user engagement, and untimely updates. In order to further improve the effectiveness of eye-care apps, cooperation with medical institutions and professional ophthalmologists should be strengthened to enhance the scientific and authoritative nature of the apps. At the same time, interactive features and regular updates should be added to enhance user participation and the continuity of the apps. This study provides a reference for future development or improvement of eye-care apps, which can help promote myopia prevention and control.

Food Delivery Apps and Their Potential to Address Food Insecurity in Older Adults: A Review.

The proportion of older adults is increasing globally, yet many of them experience food insecurity. Technological innovations, such as increased access to internet- and mobile-based food delivery apps (FDAs), may help mitigate food insecurity. However, this topic has been understudied. This scoping review searched for publications and online technical reports from around the world using interdisciplinary databases like ScienceDirect and internet sources like government websites, respectively. Eligible references were published recently (2019-present) and focused on general technology use, including apps, among older adults (≥50 years) or FDAs for food insecurity or nutritional health generally or specifically among older adults. The search identified 19 studies from 10 countries and extracted relevant information for summary tables. A limited number of studies supported the idea that FDAs can help address food insecurity, but there are important equity considerations for older adults living in rural areas or with constrained physical abilities. Consistently, customized app features and functions increased the intention to use FDAs. In addition, FDAs may have health and environmental impacts, such as food waste and increased access or promotion of ultraprocessed foods. Additional research is needed to elucidate the potential of FDAs to address food insecurity generally and specifically among older adults.

Establishing an Evaluation Indicator System for User Satisfaction With Hypertension Management Apps: Combining User-Generated Content and Analytic Hierarchy Process.

Hypertension management apps (HMAs) can be effective in controlling blood pressure, but their actual impact is often suboptimal. Establishing a user satisfaction evaluation indicator system for HMAs can assist app developers in enhancing app design and functionality, while also helping users identify apps that best meet their needs. This approach aims to improve the overall effectiveness of app usage. This study aims to systematically collect data on HMAs and their user reviews in the United States and China. It analyzes app usage patterns and functional characteristics, identifies factors influencing user satisfaction from existing research, and develops a satisfaction evaluation indicator system to provide more accurate recommendations for improving user satisfaction. We conducted a descriptive statistical analysis to assess the development status of HMAs in both countries and applied the task-technology fit model to evaluate whether the app functionalities align with business needs. We separately summarized the factors influencing user satisfaction in both countries from previous research, utilized the analytic hierarchy process to develop an evaluation indicator system for HMA user satisfaction, and calculated satisfaction levels. Based on these findings, we propose improvements to enhance app functionality and user satisfaction. In terms of current development status, there were fewer HMAs and user reviews in China compared with the United States. Regarding app functional availability, fewer than 5% (4/91) of the apps achieved a demand fulfillment rate exceeding 80% (8/10). Overall, user satisfaction in both countries was low. In the United States, user satisfaction was lowest for advertising distribution, data synchronization, and reliability. By contrast, Chinese apps need improvements in cost efficiency and compatibility.

Validation of a Bluetooth Self-Fitting Device for People With Mild-to-Moderate Hearing Loss in Quiet or Noisy Environments.

The purpose of this study was to evaluate the benefits of a Bluetooth self-fitting device using an in situ hearing screening test and self-fitting processes. Thirty Mandarin-speaking individuals (16 men and 14 women) with mild-to-moderate hearing loss participated in this study. The hearing screening test was conducted using neckband earphones of a Bluetooth self-fitting device controlled by a smartphone app. The hearing screening tests were compared with the pure-tone audiometry in an audiometric booth. The amplification benefits of the self-fitting program-aided condition were evaluated and compared with those of unaided and preset program-aided conditions using the Mandarin Hearing in Noise Test (MHINT) and questionnaires. The pure-tone audiometry and hearing screening test results exhibited strong positive correlations at all test frequencies. In the environment with 90° noise, the sentence reception thresholds (SRTs) obtained for the self-fitting program-aided condition were significantly lower (p = .032) than those obtained for the unaided condition, whereas no significant difference was observed between the preset program-aided and the unaided conditions. Moreover, the participants' satisfaction ratings for the devices were consistent with their MHINT results, with a strong positive correlation observed between satisfaction with self-fitting and user satisfaction in smartphone app's control, functionality, and learning. Younger participants were significantly more satisfied in learning to use the app. Bluetooth self-fitting devices can be used for simplified in situ hearing screenings with a sensitivity of 90.4%. The satisfaction ratings and improvements in SRTs indicate significant clinical benefits of the self-fitting program compared with the preset program, particularly in the 90°-noise environments.

From resistance to acceptance: developing health task measures to boost mHealth adoption among older adults: mixed-methods approach and innovation resistance

PurposeThere are two main objectives in this study. First, we aim to develop a set of constructs for health task management support (HTMS) features to evaluate which health-related tasks are supported by mobile health application (mHealth app) functions. Second, drawing on innovation resistance theory (IRT), we examine the impacts of the newly developed HTMS dimensions on perceived usefulness, alongside other barrier factors contributing to technology anxiety.Design/methodology/approachUsing a mixed-method research design, this research seeks to develop new measurement scales that reflect how mHealth apps support older adults’ health-related needs based on interviews. Subsequently, data were collected from older adults and exploratory factor analysis was used to confirm the validity of the new scales. Partial least squares structural equation modeling (PLS-SEM) was used to analyze survey data from 602 older adults.FindingsThe PLS-SEM results indicated that medical management task support, dietary task support, and exercise task support were positively associated with perceived usefulness, while perceived complexity and dispositional resistance to change were identified as antecedents of technology anxiety. Perceived usefulness and technology anxiety were found to positively and negatively influence adoption intention, respectively.Originality/valueThis study enriches the information systems literature by developing a multidimensional construct that delineates how older adults’ health-related needs can be supported by features of mHealth apps. Drawing on IRT, we complement the existing literature on resistance to innovation by systematically examining the impact of five types of barriers on technology anxiety.

Online Survey Study on the Needs of Former Intensive-Care Patients for the Development of a User-Friendly App.

The aim of this online-survey study is the development and evaluation of a mobile health application specifically designed to meet the needs of individuals who have previously undergone intensive-care treatment. User acceptance and perception play a crucial role in refining and optimizing the app's features and functionalities. By actively incorporating suggestions and insights from users, the goal is to enhance the overall usability and better cater to the diverse needs of individuals in post-intensive care recovery. This iterative approach ensures that the application remains responsive to the evolving requirements of its target audience. Overall, the emphasis is on creating a user-centric and adaptive tool for former intensive care patients, to develop a user-friendly mobile app.

Enhancing the Capabilities of Continuous Glucose Monitoring With a Predictive App.

Despite abundant evidence demonstrating the benefits of continuous glucose monitoring (CGM) in diabetes management, a significant proportion of people using this technology still struggle to achieve glycemic targets. To address this challenge, we propose the Accu-Chek® SmartGuide Predict app, an innovative CGM digital companion that incorporates a suite of advanced glucose predictive functionalities aiming to inform users earlier about acute glycemic situations. The app's functionalities, powered by three machine learning models, include a two-hour glucose forecast, a 30-minute low glucose detection, and a nighttime low glucose prediction for bedtime interventions. Evaluation of the models' performance included three data sets, comprising subjects with T1D on MDI (n = 21), subjects with type 2 diabetes (T2D) on MDI (n = 59), and subjects with T1D on insulin pump therapy (n = 226). On an aggregated data set, the two-hour glucose prediction model, at a forecasting horizon of 30, 45, 60, and 120 minutes, achieved a percentage of data points in zones A and B of Consensus Error Grid of: 99.8%, 99.3%, 98.7%, and 96.3%, respectively. The 30-minute low glucose prediction model achieved an accuracy, sensitivity, specificity, mean lead time, and area under the receiver operating characteristic curve (ROC AUC) of: 98.9%, 95.2%, 98.9%, 16.2 minutes, and 0.958, respectively. The nighttime low glucose prediction model achieved an accuracy, sensitivity, specificity, and ROC AUC of: 86.5%, 55.3%, 91.6%, and 0.859, respectively. The consistency of the performance of the three predictive models when evaluated on different cohorts of subjects with T1D and T2D on different insulin therapies, including real-world data, offers reassurance for real-world efficacy.

Adaptation of a Theory-Based Mobile App to Improve Access to HIV Prevention Services for Transgender Women in Malaysia: Focus Group Study.

Globally, transgender women have been disproportionately affected by the HIV epidemic, including in Malaysia, where an estimated 11% of transgender women are living with HIV. Available interventions designed specifically to meet transgender women's needs for HIV prevention are limited. Mobile health, particularly smartphone mobile apps, is an innovative and cost-effective strategy for reaching transgender women and delivering interventions to reduce HIV vulnerability. This study aims to adapt a theory-based mobile health HIV prevention smartphone app, HealthMindr, to meet the unique needs of transgender women in Malaysia. We conducted theater testing of the HealthMindr app with transgender women and key stakeholders and explored barriers to transgender women's uptake of HIV pre-exposure prophylaxis (PrEP). From February to April 2022, a total of 6 focus group (FG) sessions were conducted with 29 participants: 4 FG sessions with transgender women (n=18, 62%) and 2 FG sessions with stakeholders (n=11, 38%) providing HIV prevention services to transgender women in Malaysia. Barriers to PrEP uptake and gender-affirming care services among transgender women in Malaysia were explored. Participants were then introduced to the HealthMindr app and provided a comprehensive tour of the app's features and functions. Participants provided feedback on the app and on how existing features should be adapted to meet the needs of transgender women, as well as any features that should be removed or added. Each FG was digitally recorded and transcribed. Transcripts were coded inductively using Dedoose software (version 9.0.54; SocioCultural Research Consultants, LLC) and analyzed to identify and interpret emerging themes. Six subthemes related to PrEP barriers were found: stigma and discrimination, limited PrEP knowledge, high PrEP cost, accessibility concerns, alternative prevention methods, and perceived adverse effects. Participants suggested several recommendations regarding the attributes and app features that would be the most useful for transgender women in Malaysia. Adaptation and refinement of the app were related to the attributes of the app (user interface, security, customizable colors, themes, and avatars), feedback, and requests for additional mobile app functional (appointment booking, e-consultation, e-pharmacy, medicine tracker, mood tracker, resources, and service site locator) and communication (peer support group, live chat, and discussion forum) features. The results reveal that multifaceted barriers hinder PrEP uptake and use among transgender women in Malaysia. The findings also provide detailed recommendations for successfully adapting the HealthMindr app to the context of Malaysian transgender women, with a potential solution for delivering tailored HIV prevention, including PrEP, and increasing accessibility to gender-affirming care services.

OSCEai: personalized interactive learning for undergraduate medical education

Background: This study aims to evaluate the effectiveness of the OSCEai, a large language model-based platform that simulates clinical encounters, in enhancing undergraduate medical education. Methods: A web-based application, OSCEai, was developed to bridge theoretical and practical learning. Following use, medical students from the University of Calgary Class of 2026 completed an anonymized survey on the usability, utility, and overall experience of OSCEai. Results: A total of 37 respondents answered the anonymized survey. The OSCEai platform was highly valued for its ability to provide data on demand (33/37), support self-paced learning (30/37), and offer realistic patient interactions (29/37). The ease of use and medical content quality were rated at 4.73 (95% CI: 4.58 to 4.88) and 4.70 (95% CI: 4.55 to 4.86) out of 5, respectively. Some participants (8/37) commented that few cases were not representative and needed clarification about app functionality. Despite these limitations, OSCEai was favorably compared to lecture-based teaching methods, with an overall reception rating of 4.62 (95% CI: 4.46 to 4.79) out of 5. Interpretation: The OSCEai platform fills a gap in medical training through its scalable, interactive, and personalized design. The findings suggest that integrating technologies, like OSCEai, into medical curricula can enhance the quality and efficacy of medical education.

A Remote Oral Self-Care Behaviors Assessment System in Vulnerable Populations: Usability and Feasibility Study.

Preventative self-care can reduce dental disease that disproportionately burdens vulnerable populations. Personalized digital oral self-care behavioral interventions offer a promising solution. However, the success of these digital interventions depends on toothbrushing data collection e-platforms attuned to the needs and preferences of vulnerable communities. The aim of this study is to assess the usability and feasibility of the Remote Oral Behaviors Assessment System (ROBAS), which has been adapted to address the unique requirements of socioeconomically disadvantaged minority individuals. A cohort of 53 community-clinic participants, including 31 (58%) Latino and 22 (42%) Black individuals with no prior experience using electric toothbrushes, were recruited to use ROBAS, with planned assessments at baseline, 2 months, and 4 months. Beyond evaluating ROBAS's technical performance, extensive feedback was gathered to gauge users' experiences, viewpoints, and overall contentment. The System Usability Scale (SUS) served as a primary metric for assessing user satisfaction and acceptability. ROBAS exhibited largely reliable and consistent data-gathering capabilities. SUS scores (mean 75.6, SD 14.5) reflected participant contentment within a range of values for other commonly used digital devices and technologies. Among participants who answered questions about willingness to pay for ROBAS, 97% (30/31) indicated that they were willing to pay for ROBAS either as a one-time payment or as a subscription-based service. Additionally, 87.5% of participants expressed that they would endorse it to acquaintances. Most participants expressed no reservations about privacy; among those who expressed privacy concerns (n=20, 50%), the concerns included exposure of information (n=18, 45%), monitoring of brushing habits (n=12, 30%), and collection of information (n=14, 35%), although these concerns did not significantly correlate with specific participant traits. In qualitative terms, users valued ROBAS's ability to monitor brushing habits but called for refinements, especially in Wi-Fi and application connectivity. Recommendations for system improvements encompassed enhanced app functionality, individualized coaching, more comprehensive brushing data, and the addition of flossing activity tracking. The research highlights ROBAS's promise as a digital platform for unobtrusively tracking daily oral self-care activities in marginalized communities. The system proved to be both feasible, as evidenced by its stable and accurate data capture of brushing behaviors, and user-friendly, as reflected by strong SUS scores and positive user feedback. Influential factors for its uptake included ease of learning and operation, and the feedback provided.