User Experience of a Just-in-Time Smartphone Resonance Breathing Application for Substance Use Disorder: Acceptability, Appropriateness, and Feasibility.

BACKGROUND: Addressing the negative impact of substance use disorders (SUDs) on individuals, families, and communities is a public health priority. Most treatments and interventions require engagement with a healthcare provider or someone who can offer recovery support. The need for interventions that facilitate self-management of relapse triggers at the moment they occur is also critical. Our study aimed to explore the user experience of individuals using a just-in-time smartphone episodic resonance breathing (eRPB) intervention to address stress, anxiety, and drug cravings. METHODS: We conducted an 8-week pilot study of the eRPB with 30 individuals in recovery from SUD. Data on 3 indicators of user experience-acceptability, appropriateness, and feasibility-were collected using survey questions (n = 30) and semi-structured interviews (n = 11). We performed univariate analysis on the survey data and deductive thematic analysis on the qualitative data. RESULTS: A majority of the survey respondents agreed that the application (app) was acceptable (> 77%), appropriate (> 82%), and feasible (> 89%). Several interview participants stated that the app helped them relax and manage stress and cravings and expressed appreciation for the simplicity of its design. Participants also reported barriers to feasibility (such as forgetting to use the app) and recommendations for improvement (such as the addition of motivational messages). CONCLUSIONS: Our findings show that individuals in recovery from SUD had highly positive experiences with the eRPB app. A positive user experience may improve adherence to the intervention and, ultimately, the self-management of stress, anxiety, and craving relapse triggers.

Role perceptions and experiences of adult children in remote glucose management for older parents with type 2 diabetes mellitus: a qualitative study.

BACKGROUND: With the advent of the smart phone era, managing blood glucose at home through apps will become more common for older individuals with diabetes. Adult children play important roles in glucose management of older parents. Few studies have explored how adult children really feel about engaging in the glucose management of their older parents with type 2 diabetes mellitus (T2DM) through mobile apps. This study provides insights into the role perceptions and experiences of adult children of older parents with T2DM participating in glucose management through mobile apps. METHODS: In this qualitative study, 16 adult children of older parents with T2DM, who had used mobile apps to manage blood glucose for 6 months, were recruited through purposive sampling. Semi-structured, in-depth, face-to-face interviews to explore their role perceptions and experiences in remotely managing their older parents' blood glucose were conducted. The Consolidated Criteria for Reporting Qualitative Research (COREQ) were followed to ensure rigor in the study. The data collected were analyzed by applying Colaizzi's seven-step qualitative analysis method. RESULTS: Six themes and eight sub-themes were identified in this study. Adult children's perceived roles in glucose management of older parents with T2DM through mobile apps could be categorized into four themes: health decision-maker, remote supervisor, health educator and emotional supporter. The experiences of participation could be categorized into two themes: facilitators to participation and barriers to participation. CONCLUSION: Some barriers existed for adult children of older parents with T2DM participating in glucose management through mobile apps; however, the findings of this study were generally positive. It was beneficial and feasible for adult children to co-manage the blood glucose of older parents. Co-managing blood glucose levels in older parents with T2DM can enhance both adherence rates and confidence in managing blood glucose effectively.

Acceptability of Gynecologic e-Health Modalities by Hispanic/Latina Women of Reproductive Age.

Introduction: Electronic health (e-Health) modalities effectively address healthcare access limitations; however, there are limited data on their adoption by Hispanic/Latina women who are disproportionally affected by health disparities. Methods: We conducted a cross-sectional study by disseminating an anonymous electronic questionnaire via social media to assess the perception of Hispanic/Latina women of reproductive age regarding facilitators and barriers for using e-Health modalities, including telemedicine and mobile apps, to monitor gynecologic health. Results: The questionnaire was completed by 351 Hispanic/Latina participants with high levels (98.3%) of advanced technological expertise. Current use of a gynecologic mobile app was reported by 63.8%, primarily for menstruation (85.1%) and ovulation (46.3%) tracking. While only 17.6% of participants were offered the option of a gynecologic consultation via telemedicine, the majority (90.5%) would agree to one. Higher education and advanced technological expertise correlated with acceptance of telemedicine for gynecological consults. Being younger (<29 y/o), a student, not having a preferred gynecologist and having a lower income significantly correlated with gynecologic mobile app acceptability. Conclusions: We showed that e-Health modalities are highly acceptable for Hispanic/Latina women of reproductive age to facilitate gynecological care and documented factors that are significantly associated with e-Health acceptability. These findings are relevant to public health emergencies that cause access to care limitations disproportionally affecting this already underserved population.

App-Based Addiction Prevention at German Vocational Schools: Implementation and Reach for a Cluster-Randomized Controlled Trial.

This article examines the implementation, participation rates, and potential determinants of participation in the digital addiction prevention program "ready4life." A two-arm cluster-randomized trial recruited German vocational students via class-based strategies. Intervention group received 16 weeks of in-app coaching; the control group received health behavior information, with coaching offered after 12 months. Potential determinants of participation were analyzed based on class and individual characteristics. Out of 525 contacted schools, 35 participated, enrolling 376 classes. Implementation during the pandemic required flexible adjustments, with 49.7% of introductions conducted in person, 43.1% digitally via online streaming, and 7.2% received a video link via email. Despite challenges, 72.3% of the vocational students downloaded the app, and 46.7% gave informed consent. Participation rates were highest among (associate) professionals, vocational grammar school classes, classes introduced by females, younger individuals, members of the project team, and classes introduced face-to-face. Female gender, lower social competencies, lifetime cannabis use, higher problematic internet use, and higher perceived stress were associated with higher individual participation. The study highlights the importance of proactive outreach and personalized interventions for addiction prevention programs in vocational schools. While reached students aligned with the aims of the app, tailored recruitment strategies could enhance engagement among under-represented groups. The trial was registered in the German Clinical Trials Register (DRKS): DRKS00022328; registration date 09.10.2020.

Mobile App-Based Mindfulness Intervention for Addressing Psychological Distress Among Survivors of Hospitalization for COVID-19 Infection.

BACKGROUND: Psychological distress symptoms are present and persistent among many patients who survive a critical illness like COVID-19. RESEARCH QUESTION: Could a self-directed mobile app-delivered mindfulness intervention be feasibly and rapidly implemented within a clinical trials network to reduce distress symptoms? STUDY DESIGN AND METHODS: A randomized clinical trial was conducted between January 2021 and May 2022 at 29 US sites and included survivors of hospitalization due to COVID-19-related illness with elevated symptoms of depression at discharge. Participants were randomized to intervention or usual care control. The intervention consisted of four themed weeks of daily audio, video, and text content. All study procedures were virtual. The primary outcome was depression symptoms assessed with the Patient Health Questionnaire 9 at 3 months. Secondary outcomes included anxiety (Generalized Anxiety Disorder 7-item scale), quality of life (EQ-5D), and adherence. We used general linear models to estimate treatment arm differences in outcomes over time. RESULTS: Among 56 randomized participants (mean age ± SD, 51.0 ± 13.2 years; 38 female [67.9%]; 14 Black participants [25%]), 45 (intervention: n = 23 [79%]; control: n = 22 [81%]) were retained at 6 months. There was no difference in mean improvement between intervention and control participants at 3 months in Patient Health Questionnaire 9 (-0.5 vs 0.1), Generalized Anxiety Disorder 7-item scale (-0.3 vs 0.1), or EQ-5D (-0.03 vs 0.02) scores, respectively; 6-month results were similar. Only 15 participants (51.7%) initiated the intervention, whereas the mean number ± SD of the 56 prescribed intervention activities completed was 12.0 ± 15.2. Regulatory approvals delayed trial initiation by nearly a year. INTERPRETATION: Among survivors of COVID-19 hospitalization with elevated psychological distress symptoms, a self-directed mobile app-based mindfulness intervention had poor adherence. Future psychological distress interventions mobilized at broad scale should focus efforts on patient engagement and regulatory simplification to enhance success. TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT04581200; URL: www.clinicaltrials.gov.

Effectiveness of Mobile App Interventions to Improve Periodontal Health: Protocol for a Systematic Review and Meta-Analysis.

BACKGROUND: Periodontal health plays a key role as a shared reference point for evaluating periodontal diseases and identifying significant treatment outcomes. Providing adequate instruction and enhancing the motivation of patients to maintain proper oral hygiene are crucial factors for successful periodontal treatment, with self-performed regular oral hygiene identified as a critical factor in improving the outcomes of treatment for periodontal diseases. Recently, mobile health (mHealth) solutions, especially mobile apps, have emerged as valuable tools for self-management in chronic diseases such as periodontal disease, providing essential health education and monitoring capabilities. However, the use of mHealth apps for periodontal health is complex owing to various interacting components such as patient behavior, socioeconomic status, and adherence to oral hygiene practices. Existing literature has indicated positive effects of mHealth on oral health behaviors, knowledge, attitude, practice, plaque index score, and gingivitis reduction. However, there has been no systematic review of mobile apps specifically targeting patients with periodontal disease. Understanding the design and impact of mHealth apps is crucial for creating high-quality apps. OBJECTIVE: The aim of this systematic review and meta-analysis is to evaluate the effectiveness of existing mobile apps in promoting periodontal health. METHODS: A comprehensive search strategy will be performed in multiple electronic databases (PubMed, EBSCOhost, CINAHL Plus, Dentistry & Oral Sciences, ScienceDirect, Scopus, and Cochrane Central Register of Controlled Trials) with the following keywords in the title/abstract: "mobile application," "mobile health," "mHealth," "telemedicine," "periodontal health," "periodontitis," and "text message." Only randomized controlled trials will be included that assessed the following outcomes to measure periodontal health improvement: gingival index, bleeding index, periodontal pocket depth, and clinical attachment loss. Covidence will be used for data collection, and a PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) flowchart will be used to describe the selection process of the included, identified, and excluded studies. The Confidence in Network Meta-Analysis approach will be used for meta-analysis of the extracted data from the included studies. RESULTS: This review will not require ethical approval since no primary data will be included. As of July 2024, a total of 83 articles retrieved from various databases have been imported to Covidence with 13 articles deemed eligible for inclusion in the review. The review is currently ongoing and is expected to be complete by the end of 2024 with the results published in early 2025. CONCLUSIONS: This systematic review and meta-analysis will contribute to developing mobile apps with enhanced criteria to improve periodontal clinical outcomes. The review emphasizes the importance of mHealth and preventing periodontal disease, which can set the stage for informed global health care strategies. TRIAL REGISTRATION: PROSPERO CRD42022340827; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=340827. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50479.

Algorithmic Spaced Retrieval Enhances Long-Term Memory in Alzheimer Disease: Case-Control Pilot Study.

BACKGROUND: Spaced retrieval is a learning technique that involves engaging in repeated memory testing after increasingly lengthy intervals of time. Spaced retrieval has been shown to improve long-term memory in Alzheimer disease (AD), but it has historically been difficult to implement in the everyday lives of individuals with AD. OBJECTIVE: This research aims to determine, in people with mild cognitive impairment (MCI) due to AD, the efficacy and feasibility of a mobile app that combines spaced retrieval with a machine learning algorithm to enhance memory retention. Specifically, the app prompts users to answer questions during brief daily sessions, and a machine learning algorithm tracks each user's rate of forgetting to determine the optimal spacing schedule to prevent anticipated forgetting. METHODS: In this pilot study, 61 participants (young adults: n=21, 34%; healthy older adults: n=20, 33%; people with MCI due to AD: n=20, 33%) used the app for 4 weeks to learn new facts and relearn forgotten name-face associations. Participation during the 4-week period was characterized by using the app once per day to answer 15 questions about the facts and names. After the 4-week learning phase, participants completed 2 recognition memory tests approximately 1 week apart, which tested memory for information they had studied using the app as well as information they had not studied. RESULTS: After using the mobile app for 1 month, every person with MCI due to AD demonstrated improvements in memory for new facts that they had studied via the app compared to baseline (P<.001). All but one person with MCI due to AD (19/20, 95%) showed improvements of more than 10 percentage points, comparable to the improvements shown by young adults and healthy older adults. Memory for name-face associations was similarly improved for all participant groups after using the app but to a lesser degree. Furthermore, for both new facts and name-face associations, we found no memory decay for any participant group after they took a break of approximately 1 week from using the app at the end of the study. Regarding usability, of the 20 people with MCI due to AD, 16 (80%) self-adhered to the app's automated practice schedule, and half of them (n=10, 50%) expressed an interest in continuing to use it. CONCLUSIONS: These results demonstrate early evidence that spaced retrieval mobile apps are both feasible for people with early-stage AD to use in their everyday lives and effective for supporting memory retention of recently learned facts and name-face associations.

Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review.

Spatiotemporal parameters such as gait velocity and stride length are simple indicators of functional status and can be used to predict major adverse outcomes in older adults. A smartphone can be used for gait analysis by providing spatiotemporal parameters useful for improving the diagnosis and rehabilitation processes in frail people. The aim of this study was to review articles published in the last 20 years (from 2004 to 2024) concerning the application of smartphones to assess the spatiotemporal parameters of gait in older adults. This systematic review was performed in line with Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA), and original articles were identified by searching seven electronic databases: SciVerse (ScienceDirect), Excerpta Medica Database (EMBASE), Medline, Scopus, PubMed, Web of Science and the Cochrane Library. Studies were rigorously screened using the inclusion criteria of smartphones and mobile apps, older adults and spatiotemporal gait parameters, and results were narratively synthesized. Seventy-three articles were initially identified while searching the scientific literature regarding this topic. Eleven articles were selected and included in this review. Analysis of these studies covered information about gait assessment using mobile apps recorded in 723 older adults and 164 control cases. Analysis of data related to the application of smartphones to assess spatiotemporal parameters of gait in older adults showed moderate-to-excellent test-retest reliability and validity (ICCs around 0.9) of gait speed, the most common parameter reported. Additionally, gait speeds recorded with mobile apps showed excellent agreement when compared to gold standard systems. Smartphones and mobile apps are useful, non-invasive, low-cost and objective tools that are being extensively used to perform gait analysis in older adults. Smartphones and mobile apps can reliably identify spatiotemporal parameters related to adverse outcomes, such as a slow gait speed, as predictors and outcomes in clinical practice and research involving older adults.

Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System.

The delivery market in Republic of Korea has experienced significant growth, leading to a surge in motorcycle-related accidents. However, there is a lack of comprehensive data collection systems for motorcycle safety management. This study focused on designing and implementing a foundational data collection system to monitor and evaluate motorcycle driving behavior. To achieve this, eleven risky behaviors were defined, identified using image-based, GIS-based, and inertial-sensor-based methods. A motorcycle-mounted sensing device was installed to assess driving, with drivers reviewing their patterns through an app and all data monitored via a web interface. The system was applied and tested using a testbed. This study is significant as it successfully conducted foundational data collection for motorcycle safety management and designed and implemented a system for monitoring and evaluation.

Technology-Based Strategy to Improve Medication Compliance Among Patients With Schizophrenia Spectrum Disorders.

INTRODUCTION:  Non-compliance to medications remains a challenging problem in schizophrenia. Newer strategies with high feasibility and acceptability are always being researched. This study aimed to assess the effectiveness of technology-based intervention in improving medication compliance in individuals with schizophrenia. METHOD: This was a prospective intervention study where participants were required to use the SuperMD smartphone application (Digital-Health Technologies Pte Ltd, Kuala Lumpur, Malaysia) for a month. A change in the Medication Adherence Rating Scale-Malay Translation (MARS-M) and Malay Translation of Drug Adherence Inventory-9 (MDAI-9) scores indicated a change in compliance and attitude to medication. Positive and Negative Syndrome Scale (PANSS) was used to assess change in symptoms and insight. Medication compliance was also obtained from the SuperMD application. Paired T-test was used to evaluate the significance of changes in mean scores of research variables over the study period. Wilcoxon signed-rank test was used to analyze the subscale of MDAI-9 and the change in PANSS score. The Kruskal-Wallis test was used to determine the effect of the change of insight on the level of compliance with medication. RESULTS: There were 36 participants in this study. The results showed statistically significant improvement in compliance (0.65, p ≤ 0.01) but not in attitude towards medication (0.78, p = 0.065). There was also an improvement in PANNS score (-2.58, P ≤ 0.01). There was no significant change in insight (χ2(2) = 3.802, p = 0.15).  Conclusion:The use of technology-based strategies like SuperMD is effective in improving medication compliance for individuals with schizophrenia.

Effects of Mobile Applications on Weight-Related, Behavior and Metabolic Outcomes for Adults with Overweight and Obesity: A Systematic Review and Meta-Analysis.

The meta-analysis aimed to explore the effects of mobile phone applications on weight-related, behavior, and metabolic outcomes among adults with overweight and obesity. Six databases were searched for relevant randomized controlled trials (RCTs) published between January 1, 2010 and November 7, 2023 in English. Two independent authors conducted study selection, data extraction, quality assessment. The effect size of interventions was calculated using mean difference. A random-effects model was applied for data analysis. A total of 27 studies were included. The results indicated that mobile phone application intervention reduced weight (MD=-1.38 kg, P<0.001, 95% CI -1.97 to -0.80), BMI (MD=-0.44 kg/m2, P<0.001, 95% CI -0.57 to -0.30), WC (MD=-2.13 cm, P=0.004, 95% CI -3.57 to -0.69), fat mass, and DBP (MD=-2.04 mmHg, P=0.01, 95% CI -3.65 to 0.44) with statistical significance. Future studies could consider how to optimize app interventions through behavior change strategies to enhance their overall effectiveness.

The Acceptability, Engagement, and Feasibility of Mental Health Apps for Marginalized and Underserved Young People: Systematic Review and Qualitative Study.

BACKGROUND: Smartphone apps may provide an opportunity to deliver mental health resources and interventions in a scalable and cost-effective manner. However, young people from marginalized and underserved groups face numerous and unique challenges to accessing, engaging with, and benefiting from these apps. OBJECTIVE: This study aims to better understand the acceptability (ie, perceived usefulness and satisfaction with an app) and feasibility (ie, the extent to which an app was successfully used) of mental health apps for underserved young people. A secondary aim was to establish whether adaptations can be made to increase the accessibility and inclusivity of apps for these groups. METHODS: We conducted 2 sequential studies, consisting of a systematic literature review of mental health apps for underserved populations followed by a qualitative study with underserved young male participants (n=20; age: mean 19). Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, an electronic search of 5 databases was conducted in 2021. The search yielded 18,687 results, of which 14 articles met the eligibility criteria. RESULTS: The included studies comprised a range of groups, including those affected by homelessness, having physical health conditions, living in low- and middle-income countries, and those with sexual and gender minority identities. Establishing and maintaining user engagement was a pervasive challenge across mental health apps and populations, and dropout was a reported problem among nearly all the included studies. Positive subjective reports of usability, satisfaction, and acceptability were insufficient to determine users' objective engagement. CONCLUSIONS: Despite the significant amount of funding directed to the development of mental health apps, juxtaposed with only limited empirical evidence to support their effectiveness, few apps have been deliberately developed or adapted to meet the heterogeneous needs of marginalized and underserved young people. Before mental health apps are scaled up, a greater understanding is needed of the types of services that more at-risk young people and those in limited-resource settings prefer (eg, standard vs digital) followed by more rigorous and consistent demonstrations of acceptability, effectiveness, and cost-effectiveness. Adopting an iterative participatory approach by involving young people in the development and evaluation process is an essential step in enhancing the adoption of any intervention, including apps, in "real-world" settings and will support future implementation and sustainability efforts to ensure that marginalized and underserved groups are reached. TRIAL REGISTRATION: PROSPERO CRD42021254241; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=254241.

Development Plan for the Clinical Application of Maternity and Child Health Mobile App.

In 2021, the World Health Organization designated the theme for World Patient Safety Day as "Safe Maternal and Newborn Care" with the aim of raising awareness of the importance of maternal and newborn safety and improving their overall safety. Many healthcare institutions in Taiwan currently provide printed materials such as childbirth guidelines and nursing instructions to patients. However, mobile applications in the current digital world might be more handy to assist pregnant women in understanding the changes during pregnancy and provide relevant health education in order to help reduce pregnancy and childbirth complications, as well as decrease maternal and neonatal mortality rates.

Efficacy of Mobile App-Based Cognitive Behavioral Therapy for Insomnia: Multicenter, Single-Blind Randomized Clinical Trial.

BACKGROUND: Cognitive behavioral therapy for insomnia (CBTi) is the first-line therapy for chronic insomnia. Mobile app-based CBTi (MCBTi) can enhance the accessibility of CBTi treatment; however, few studies have evaluated the effectiveness of MCBTi using a multicenter, randomized controlled trial design. OBJECTIVE: We aimed to assess the efficacy of Somzz, an MCBTi that provides real-time and tailored feedback to users, through comparison with an active comparator app. METHODS: In our multicenter, single-blind randomized controlled trial study, participants were recruited from 3 university hospitals and randomized into a Somzz group and a sleep hygiene education (SHE) group at a 1:1 ratio. The intervention included 6 sessions for 6 weeks, with follow-up visits over a 4-month period. The Somzz group received audiovisual sleep education, guidance on relaxation therapy, and real-time feedback on sleep behavior. The primary outcome was the Insomnia Severity Index score, and secondary outcomes included sleep diary measures and mental health self-reports. We analyzed the outcomes based on the intention-to-treat principle. RESULTS: A total of 98 participants were randomized into the Somzz (n=49, 50%) and SHE (n=49, 50%) groups. Insomnia Severity Index scores for the Somzz group were significantly lower at the postintervention time point (9.0 vs 12.8; t95=3.85; F2,95=22.76; ηp2=0.13; P<.001) and at the 3-month follow-up visit (11.3 vs 14.7; t68=2.61; F2,68=5.85; ηp2=0.03; P=.01) compared to those of the SHE group. The Somzz group maintained their treatment effect at the postintervention time point and follow-ups, with a moderate to large effect size (Cohen d=-0.62 to -1.35; P<.01 in all cases). Furthermore, the Somzz group showed better sleep efficiency (t95=-3.32; F2,91=69.87; ηp2=0.41; P=.001), wake after sleep onset (t95=2.55; F2,91=51.81; ηp2=0.36; P=.01), satisfaction (t95=-2.05; F2,91=26.63; ηp2=0.20; P=.04) related to sleep, and mental health outcomes, including depression (t95=2.11; F2,94=29.64; ηp2=0.21; P=.04) and quality of life (t95=-3.13; F2,94=54.20; ηp2=0.33; P=.002), compared to the SHE group after the intervention. The attrition rate in the Somzz group was 12% (6/49). CONCLUSIONS: Somzz outperformed SHE in improving insomnia, mental health, and quality of life. The MCBTi can be a highly accessible, time-efficient, and effective treatment option for chronic insomnia, with high compliance. TRIAL REGISTRATION: Clinical Research Information Service (CRiS) KCT0007292; https://cris.nih.go.kr/cris/search/detailSearch.do?seq=22214&search_page=L.

Efficacy of an Artificial Intelligence App (Aysa) in Dermatological Diagnosis: Cross-Sectional Analysis.

BACKGROUND: Dermatology is an ideal specialty for artificial intelligence (AI)-driven image recognition to improve diagnostic accuracy and patient care. Lack of dermatologists in many parts of the world and the high frequency of cutaneous disorders and malignancies highlight the increasing need for AI-aided diagnosis. Although AI-based applications for the identification of dermatological conditions are widely available, research assessing their reliability and accuracy is lacking. OBJECTIVE: The aim of this study was to analyze the efficacy of the Aysa AI app as a preliminary diagnostic tool for various dermatological conditions in a semiurban town in India. METHODS: This observational cross-sectional study included patients over the age of 2 years who visited the dermatology clinic. Images of lesions from individuals with various skin disorders were uploaded to the app after obtaining informed consent. The app was used to make a patient profile, identify lesion morphology, plot the location on a human model, and answer questions regarding duration and symptoms. The app presented eight differential diagnoses, which were compared with the clinical diagnosis. The model's performance was evaluated using sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1-score. Comparison of categorical variables was performed with the χ2 test and statistical significance was considered at P<.05. RESULTS: A total of 700 patients were part of the study. A wide variety of skin conditions were grouped into 12 categories. The AI model had a mean top-1 sensitivity of 71% (95% CI 61.5%-74.3%), top-3 sensitivity of 86.1% (95% CI 83.4%-88.6%), and all-8 sensitivity of 95.1% (95% CI 93.3%-96.6%). The top-1 sensitivities for diagnosis of skin infestations, disorders of keratinization, other inflammatory conditions, and bacterial infections were 85.7%, 85.7%, 82.7%, and 81.8%, respectively. In the case of photodermatoses and malignant tumors, the top-1 sensitivities were 33.3% and 10%, respectively. Each category had a strong correlation between the clinical diagnosis and the probable diagnoses (P<.001). CONCLUSIONS: The Aysa app showed promising results in identifying most dermatoses.

Raising Awareness of Mistreatment Policies and Reporting Procedures Using a Novel Medical Student Mobile Application.

BACKGROUND: Reports of mistreatment are an important first step to improving medical students' learning environment. Students may not report mistreatment due to a lack of awareness of institutional policies, reporting procedures, or for fear of reprisal. AIM: We sought to determine if a medical school cross-platform mobile application (app) could be used to improve students' awareness of mistreatment policies and procedures. SETTING AND PARTICIPANTS: Participants in this intervention included Drexel University College of Medicine (DUCOM) medical students, faculty, and Student Affairs Deans. PROGRAM DESCRIPTION: We created the DUCOMpass© app to make mistreatment policies and procedures more readily available and to ease mistreatment reporting for medical students. PROGRAM EVALUATION: To determine the efficacy of the app at raising mistreatment awareness, we analyzed our institutional Graduation Questionnaire data before and after the introduction of the app (from 2016 to 2023) as compared with the national average. We verified our students' self-reported data with app usage data. DISCUSSION: To our knowledge, this is the first instance of a medical school mobile app being implemented to successfully address medical student mistreatment awareness and reporting. We found that reaching students in a familiar and easily accessible mode(s) of communication is a catalyst for lasting change. NIH TRIAL REGISTRY: Not applicable.

GranoScan: an AI-powered mobile app for in-field identification of biotic threats of wheat.

Capitalizing on the widespread adoption of smartphones among farmers and the application of artificial intelligence in computer vision, a variety of mobile applications have recently emerged in the agricultural domain. This paper introduces GranoScan, a freely available mobile app accessible on major online platforms, specifically designed for the real-time detection and identification of over 80 threats affecting wheat in the Mediterranean region. Developed through a co-design methodology involving direct collaboration with Italian farmers, this participatory approach resulted in an app featuring: (i) a graphical interface optimized for diverse in-field lighting conditions, (ii) a user-friendly interface allowing swift selection from a predefined menu, (iii) operability even in low or no connectivity, (iv) a straightforward operational guide, and (v) the ability to specify an area of interest in the photo for targeted threat identification. Underpinning GranoScan is a deep learning architecture named efficient minimal adaptive ensembling that was used to obtain accurate and robust artificial intelligence models. The method is based on an ensembling strategy that uses as core models two instances of the EfficientNet-b0 architecture, selected through the weighted F1-score. In this phase a very good precision is reached with peaks of 100% for pests, as well as in leaf damage and root disease tasks, and in some classes of spike and stem disease tasks. For weeds in the post-germination phase, the precision values range between 80% and 100%, while 100% is reached in all the classes for pre-flowering weeds, except one. Regarding recognition accuracy towards end-users in-field photos, GranoScan achieved good performances, with a mean accuracy of 77% and 95% for leaf diseases and for spike, stem and root diseases, respectively. Pests gained an accuracy of up to 94%, while for weeds the app shows a great ability (100% accuracy) in recognizing whether the target weed is a dicot or monocot and 60% accuracy for distinguishing species in both the post-germination and pre-flowering stage. Our precision and accuracy results conform to or outperform those of other studies deploying artificial intelligence models on mobile devices, confirming that GranoScan is a valuable tool also in challenging outdoor conditions.

Understanding and Involving the Perspective of Pregnant Women as Users When Designing the Framework of e-Health and Exercise Interventions during Pregnancy: Preliminary Study.

Health and exercise technology may promote a healthy lifestyle during pregnancy. The objective of this cross-sectional study was to understand and involve the perspective of pregnant women as users in the design of a framework for future e-health and exercise interventions during pregnancy. Pregnant women replied to a questionnaire aimed at understanding their physical activity patterns, needs, and preferences regarding the use of mobile applications (apps). The main results showed that one-third of the women did not practice any type of exercise during pregnancy. Women preferred to exercise in a gym, outdoors, or at home. The majority already had or were currently using a fitness app, but never used any pregnancy-specific app. Most women agreed that it was important to have a specific app for pregnancy to improve knowledge about recommendations on lifestyle, have direct contact with health and exercise professionals, have social interaction with other mothers, and have guidance on preparation for childbirth and postpartum recovery. Understanding and involving the perspective of pregnant women as users will allow researchers to improve the design of a pregnancy-specific app and future e-health and exercise interventions during pregnancy. These preliminary results will lead to the development of the "active pregnancy app" focused on the promotion of an active and healthy lifestyle during pregnancy and postpartum.

An App-Based Physical Activity Intervention in Community-Dwelling Chinese-, Tagalog-, and Vietnamese-Speaking Americans: Single-Arm Intervention Study.

BACKGROUND: Physical inactivity is associated with adverse health outcomes among Asian Americans, who exhibit the least adherence to physical activity guidelines compared with other racial and ethnic groups. Mobile app-based interventions are a promising approach to promote healthy behaviors. However, there is a lack of app-based interventions focused on improving physical activity among Asian Americans whose primary language is not English. OBJECTIVE: This pilot study aimed to assess the feasibility and acceptability of a 5-week intervention using a culturally and linguistically adapted, evidence-based mobile phone app with an accelerometer program, to promote physical activity among Chinese-, Tagalog-, or Vietnamese-speaking Americans. METHODS: Participants were recruited through collaborations with community-based organizations. The intervention was adapted from a 12-month physical activity randomized controlled trial involving the app and accelerometer for English-speaking adults. Sociodemographic characteristics, lifestyle factors, and physical measurements were collected at the baseline visit. A 7-day run-in period was conducted to screen for the participants who could wear a Fitbit One (Fitbit LLC) accelerometer and complete the app's daily step diary. During the 4-week intervention period, participants wore the accelerometer and reported their daily steps in the app. Participants also received daily messages to reinforce key contents taught during an in-person educational session, remind them to input steps, and provide tailored feedback. Feasibility measures were the percentage of eligible participants completing the run-in period and the percentage of participants who used the app diary for at least 5 out of 7 days during the intervention period. We conducted poststudy participant interviews to explore overall intervention acceptability. RESULTS: A total of 19 participants were enrolled at the beginning of the study with a mean age of 47 (SD 13.3; range 29-70) years, and 58% (n=11) of them were female. Of the participants, 26% (n=5) were Chinese, 32% (n=6) were Vietnamese, and 42% (n=8) were Filipino. All participants met the run-in criteria to proceed with the intervention. Adherence to the app diary ranged from 74% (n=14) in week 2 to 95% (n=18) in week 4. The daily average steps per week from accelerometers increased each week from 8451 (SD 3378) steps during the run-in period to 10,930 (SD 4213) steps in week 4. Participants reported positive experiences including an increased motivation to walk and the enjoyment of being able to monitor their physical activity. CONCLUSIONS: This is the first pilot study of a multicomponent intervention and evidence-based mobile phone app to promote physical activity among Asian Americans who use apps in traditional Chinese, Tagalog, or Vietnamese, which demonstrated high feasibility and acceptability. Future work focused on multilingual mobile apps to address disparities in physical inactivity among Asian Americans should be considered.

Mobile-UI-Repair: a deep learning based UI smell detection technique for mobile user interface.

The graphical user interface (GUI) in mobile applications plays a crucial role in connecting users with mobile applications. GUIs often receive many UI design smells, bugs, or feature enhancement requests. The design smells include text overlap, component occlusion, blur screens, null values, and missing images. It also provides for the behavior of mobile applications during their usage. Manual testing of mobile applications (app as short in the rest of the document) is essential to ensuring app quality, especially for identifying usability and accessibility that may be missed during automated testing. However, it is time-consuming and inefficient due to the need for testers to perform actions repeatedly and the possibility of missing some functionalities. Although several approaches have been proposed, they require significant performance improvement. In addition, the key challenges of these approaches are incorporating the design guidelines and rules necessary to follow during app development and combine the syntactical and semantic information available on the development forums. In this study, we proposed a UI bug identification and localization approach called Mobile-UI-Repair (M-UI-R). M-UI-R is capable of recognizing graphical user interfaces (GUIs) display issues and accurately identifying the specific location of the bug within the GUI. M-UI-R is trained and tested on the history data and also validated on real-time data. The evaluation shows that the average precision is 87.7% and the average recall is 86.5% achieved in the detection of UI display issues. M-UI-R also achieved an average precision of 71.5% and an average recall of 70.7% in the localization of UI design smell. Moreover, a survey involving eight developers demonstrates that the proposed approach provides valuable support for enhancing the user interface of mobile applications. This aids developers in their efforts to fix bugs.