The Triple E project: a factorial randomised controlled trial to enhance engagement with eHealth approaches to improve health risk behaviours among adolescents.

BACKGROUND: Digital, or eHealth, interventions are highly promising approaches to help adolescents improve their health behaviours and reduce their risk of chronic disease. However, they often have low uptake and retention. There is also a paucity of high-quality research into the predictors of eHealth engagement, and a lack of studies that have systematically evaluated existing engagement strategies in adolescent populations. This paper describes the protocol for a randomised controlled trial which primarily aims to assess the effectiveness of different strategies in increasing engagement with a healthy lifestyles app, Health4Life. Associations between the engagement strategies and improvements in adolescent health behaviours (healthy eating, physical activity, sleep, recreational screen time, smoking, alcohol use) will also be examined, along with potential predictors of adolescents' intentions to use health apps and their use of the Health4Life app. METHODS: The current study will aim to recruit 336 adolescent and parent/guardian dyads (total sample N = 672) primarily through Australia wide online advertising. All adolescent participants will have access to the Health4Life app (a multiple health behaviour change, self-monitoring mobile app). The trial will employ a 24 factorial design, where participants will be randomly allocated to receive 1 of 16 different combinations of the four engagement strategies to be evaluated: text messages, access to a health coach, access to additional gamified app content, and provision of parent/guardian information resources. Adolescents and parents/guardians will both complete consent processes, baseline assessments, and a follow-up assessment after 3 months. All participants will also be invited to complete a qualitative interview shortly after follow-up. The primary outcome, app engagement, will be assessed via an App Engagement Index (Ei) using data collected in the Health4Life app and the Mobile App Rating Scale - User version. DISCUSSION: This research will contribute significantly to building our understanding of the types of strategies that are most effective in increasing adolescents' engagement with health apps and which factors may predict adolescents' use of health apps. TRIAL REGISTRATION: The trial is registered at the Australian New Zealand Clinical Trials Registry (ACTRN12623000399695). Date registered: 19/04/2023.

Choice architecture promotes sustainable choices in online food-delivery apps.

Greenhouse gas emissions from the food system constitute about one-third of the global total, hence mitigation in this sphere of human activity is a vital goal for research and policy. This study empirically tests the effectiveness of different interventions to reduce the carbon footprint of food choices made on food-delivery apps, using an incentive-compatible online randomized controlled trial with 4,008 participants. The experiment utilized an interactive web platform that mimics popular online food-delivery platforms (such as Just Eat) and included three treatment conditions: a sign-posted meat tax, a carbon-footprint label, and a choice-architecture intervention that changed the order of the menu so that the lowest carbon-impact restaurants and dishes were presented first. Results show that only the choice-architecture nudge significantly reduced the average meal carbon footprint-by 0.3 kg/CO2e per order (12%), driven by a 5.6 percentage point (13%) reduction in high-carbon meal choices. Moreover, we find evidence of significant health and well-being co-benefits. Menu repositioning resulted in the average meal order having greater nutritional value and fewer calories, whilst significantly increasing self-reported satisfaction with the meal choice. Simple back-of-the-envelope calculations suggest that menu repositioning would be a highly cost-effective policy instrument if implemented at scale, with the return on investment expected to be in the range of £1.28 to £3.85 per metric ton of avoided CO2 emissions, depending on implementation costs.

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

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.

Quality Assessment of Digital Health Apps: Umbrella Review.

BACKGROUND: With an increasing number of digital health apps available in app stores, it is important to assess these technologies reliably regarding their quality. This is done to mitigate the risks associated with their use. There are many different guidelines, methods, and metrics available to assess digital health apps with regard to their quality. OBJECTIVE: This study aimed to give a holistic summary of the current methods and "condition agnostic" frameworks that are broadly applicable for the quality assessment of all digital health apps. METHODS: A systematic search of literature was conducted on 4 databases: Scopus, PubMed, ACM Digital Library, and IEEE Xplore. We followed the PICOS (Population, Patient, or Problem; Intervention; Comparison; Outcomes; and Study Design) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodologies when conducting this umbrella review. The search was conducted on January 26, 2024, for review articles published between 2018 and 2023. We identified 4781 candidate papers for inclusion; after title and abstract screening, 39 remained. After full-text analysis, we included 15 review articles in the full review. RESULTS: Of the 15 review articles, scoping reviews were the most common (n=6, 40%), followed by systematic reviews (n=4, 27%), narrative reviews (n=4, 27%), and a rapid review (n=1, 7%). A total of 4 (27%) review articles proposed assessment criteria for digital health apps. "Data privacy and/or security" was the most mentioned criterion (n=13, 87%) and "Cost" was the least mentioned criterion (n=1, 7%) for the assessment of digital health apps. The Mobile App Rating Scale was the most frequently used framework for quality assessment of digital health apps. CONCLUSIONS: There is a lack of unity or consolidation across identified frameworks, as most do not meet all the identified criteria from the reviewed articles. Safety concerns associated with the use of digital health apps may be mitigated with the use of quality frameworks.

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

Introduction: 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. Methods: 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. Results: 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). Discussion: A gap exists in the availability of high-quality MHA designed for healthcare professionals to facilitate shared decision-making in cardiovascular risk assessment. Systematic Review Registration: The International Prospective Register of Systematic Reviews, identifier CRD42023453807.

mHealth Apps in the Digital Marketplace for Pediatric Patients With Cancer: Systematic Search and Analysis.

Background: The substantial increase in smartphone ownership has led to a rise in mobile health (mHealth) app use. Developing tailored features through mHealth apps creates a pathway to address the health care needs of pediatric patients with cancer and their families who have complex care needs. However, few apps are designed specifically to integrate with pediatric cancer care. Objective: This study reports a systematic search and analysis of mHealth apps available on the Apple App (iOS) and Google Play (Android) stores designed for pediatric cancer through a list of features that serve (1) patients, (2) caregivers, or (3) both audiences. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we reviewed apps for pediatric patients with cancer and caregivers available as of January 30, 2024. We searched the Apple App and Google Play stores with a list of keyword combinations focusing on pediatric cancer care. The inclusion criteria were (1) specifically apps targeted toward pediatric patients with cancer, their families, or both; (2) available in either app store; and (3) available in English. Apps were assessed using the Mobile Application Rating Scale (MARS). The MARS is a quality assessment for mHealth apps, including components of engagement, functionality, aesthetics, and informational quality (5-point Likert scale items-1: low and 5: high quality). Results: In total, 22 apps were identified and 17 of those apps were available on both platforms. The most popular features (n=12) were resource sharing, symptom tracking, reminders, care team connections, journaling, community support, medication tracking, data visualizations, and appointment tracking. Features and interfaces were designed for caregivers (n=9) more frequently than the patients (n=7) while a subset of apps created options for both users (n=6). A total of 16 apps received positive reviews (mean 4.4, SD 0.59; Min=3.1, Max=5.0). A small subset (n=3) achieved over 5000 downloads; however, the majority (n=15) had fewer than 500. More than half (n=12) of the apps were not available in English. Apps requested access to a range of device functionalities to operate (mean 2.72, SD 3.13; Min=0, Max=10). Out of 22, a total of 17 apps were publicly accessible. The mean MARS scores for the apps ranged from 1.71 (SD 0.75) to 4.33 (SD 0.82). Overall, apps scored high on functionality (mean 3.72, SD 0.54) but low on engagement (mean 3.02, SD 0.93). Conclusions: Our review highlights the promising yet underdeveloped potential of mHealth apps in pediatric oncology care, underscoring the need for more inclusive, comprehensive, and integrative digital health solutions. Future developments should actively involve key stakeholders from the pediatric oncology community, including patients, families, and health care professionals, to ensure the apps meet specific needs while addressing linguistic and cultural barriers.

Dark patterns, dark nudges, sludge and misinformation: alcohol industry apps and digital tools.

Many alcohol-industry-funded (AIF) organizations disseminate eHealth/mHealth tools that claim to assist users in making health decisions by monitoring alcohol consumption, e.g. blood alcohol calculators, AUDIT scores, consumption trackers. Previously, AIF materials were found to contain health misinformation that could increase consumption (dark nudges) or make healthy behaviour change more difficult (sludge). The accuracy and functionality of AIF tools have never been analysed, and given the history of AIF materials it is possible they contain misinformation and function as covert marketing channels to promote alcohol-industry-friendly narratives on the causes and possible solutions of alcohol-related harms. We evaluated the information accuracy and framing, behaviour change techniques (BCTs), and functions of AIF digital tools (n = 15, from the UK, Ireland, the USA, Canada, New Zealand, Australia; including Drinkaware, Drinkwise, Educ'alcool and others), compared to a non-industry-funded independent sample (n = 10). We identified misinformation and 'dark patterns' (interface design strategies for influencing users against their interest) throughout AIF tools; significantly fewer provided accurate feedback (33% vs 100%), and significantly more omitted information on cancer (67% vs 10%) and cardiovascular disease (80% vs 30%) and promoted industry-friendly narratives (47% vs 0%). AIF tools encouraged consumption through priming nudges (53%) and social norming (40%). AIF tools utilized fewer BCTs, provided users with more limited pre-set options (54%), and fewer drink choices (mean 24 vs 275). Their input structure often impeded their ability to provide guideline advice. We conclude that AIF tools contain pro-industry misinformation strategies and dark patterns that misinform users about their consumption and could 'nudge' them towards continuing to drink alcohol-characteristics of 'Dark Apps' designs.

Mobile Apps for Vaccination Services: Content Analysis and Quality Assessment.

BACKGROUND: Vaccination services are increasingly in demand by the public, and mobile apps are an effective tool to meet that demand. However, the characteristics and quality of these apps are unknown. OBJECTIVE: Commonly used vaccination service apps on the market were surveyed with regard to quality, service content, and user experience to evaluate and guide users. METHODS: The Qimai Data mobile app data analytics platform was used to search for common vaccination service apps by keyword, and the WeChat and Alipay platforms were searched for apps. The apps included in the study were independently evaluated by two reviewers using the Mobile Application Rating Scale, and the service content and user experience of the apps were analyzed. The intragroup correlation coefficient between raters was used to measure interrater reliability. RESULTS: In the app stores of the four major Android platforms and the iOS app store, 1092 and 207 apps were found, respectively; 189 WeChat applets and 30 Alipay applets were also found. A total of 29 apps was ultimately included in this study according to the inclusion criteria, including 21 independent apps, 4 WeChat applets, and 4 Alipay applets. Significant differences were found between independent apps and applets in terms of the quality score (t449.57=-5.301; P<.001) and the subjective quality score (z=-4.753; P<.001). No significant differences were found between iOS and Android platforms in terms of the quality score (t1404=-2.55; P=.80) and the subjective quality score (z=-0.137; P=.89). There was good intragroup consistency among the raters. CONCLUSIONS: In this study, independent apps and nonindependent apps that rely on social and payment platforms for implementation were included in the vaccination services category. The overall quality of these apps was acceptable. Nonindependent running apps were found to have slightly lower scores and showed room for improvement, and scores for the participatory apps were found to be generally low overall.

Measuring Environmental and Behavioral Drivers of Chronic Diseases Using Smartphone-Based Digital Phenotyping: Intensive Longitudinal Observational mHealth Substudy Embedded in 2 Prospective Cohorts of Adults.

BACKGROUND: Previous studies investigating environmental and behavioral drivers of chronic disease have often had limited temporal and spatial data coverage. Smartphone-based digital phenotyping mitigates the limitations of these studies by using intensive data collection schemes that take advantage of the widespread use of smartphones while allowing for less burdensome data collection and longer follow-up periods. In addition, smartphone apps can be programmed to conduct daily or intraday surveys on health behaviors and psychological well-being. OBJECTIVE: The aim of this study was to investigate the feasibility and scalability of embedding smartphone-based digital phenotyping in large epidemiological cohorts by examining participant adherence to a smartphone-based data collection protocol in 2 ongoing nationwide prospective cohort studies. METHODS: Participants (N=2394) of the Beiwe Substudy of the Nurses' Health Study 3 and Growing Up Today Study were followed over 1 year. During this time, they completed questionnaires every 10 days delivered via the Beiwe smartphone app covering topics such as emotions, stress and enjoyment, physical activity, access to green spaces, pets, diet (vegetables, meats, beverages, nuts and dairy, and fruits), sleep, and sitting. These questionnaires aimed to measure participants' key health behaviors to combine them with objectively assessed high-resolution GPS and accelerometer data provided by participants during the same period. RESULTS: Between July 2021 and June 2023, we received 11.1 TB of GPS and accelerometer data from 2394 participants and 23,682 survey responses. The average follow-up time for each participant was 214 (SD 148) days. During this period, participants provided an average of 14.8 (SD 5.9) valid hours of GPS data and 13.2 (SD 4.8) valid hours of accelerometer data. Using a 10-hour cutoff, we found that 51.46% (1232/2394) and 53.23% (1274/2394) of participants had >50% of valid data collection days for GPS and accelerometer data, respectively. In addition, each participant submitted an average of 10 (SD 11) surveys during the same period, with a mean response rate of 36% across all surveys (SD 17%; median 41%). After initial processing of GPS and accelerometer data, we also found that participants spent an average of 14.6 (SD 7.5) hours per day at home and 1.6 (SD 1.6) hours per day on trips. We also recorded an average of 1046 (SD 1029) steps per day. CONCLUSIONS: In this study, smartphone-based digital phenotyping was used to collect intensive longitudinal data on lifestyle and behavioral factors in 2 well-established prospective cohorts. Our assessment of adherence to smartphone-based data collection protocols over 1 year suggests that adherence in our study was either higher or similar to most previous studies with shorter follow-up periods and smaller sample sizes. Our efforts resulted in a large dataset on health behaviors that can be linked to spatial datasets to examine environmental and behavioral drivers of chronic disease.

Perceptions of the Use of Mobile Technologies for Smoking Cessation: Focus Group Study With Individuals of Low Socioeconomic Status Who Smoke.

BACKGROUND: The use of mobile technologies to deliver behavioral health interventions, including smoking cessation support, has grown. Users' perceptions are important determinants of the adoption and use of new technologies. However, little is known about users' perceptions of mobile technologies as smoking cessation aids, particularly among disadvantaged individuals who smoke. OBJECTIVE: This study aimed to examine the acceptance of mobile technologies for smoking cessation among young adults with low socioeconomic status who smoke. METHODS: In total, 38 current cigarette smokers, 18 to 29 years old, who wanted to quit and did not have a 4-year college degree nor were enrolled in a 4-year college, participated in 12 semistructured digital focus groups. The moderation guide was guided by the Unified Theory of Acceptance and Use of Technology. Discussions were audio recorded, transcribed verbatim, and coded for the Unified Theory of Acceptance and Use of Technology constructs (ie, effort expectancy, facilitating conditions, performance expectancy, and social influence), sentiment (ie, negative, neutral, and positive), and purpose of using mobile technologies (ie, lifestyle and health management and smoking cessation) following a deductive thematic analysis approach. RESULTS: Participants had positive experiences using mobile technologies for lifestyle and health management, primarily for fitness and dietary purposes. Salient themes were facilitating conditions of use (44/80, 55%), with prior experiences and costs subthemes, followed by perceived usefulness of mobile technologies in helping users attain health goals (22/80, 27.50%), which were generally positive. Ease of use (11/80, 13.75%) and social influences (3/80, 3.75%) were minimally discussed. Conversely, participants had limited awareness of smoking cessation uses of mobile technologies, which was the primary barrier under facilitating conditions discussed (33/51, 64.70%). Participants expressed skepticism about the usefulness of mobile technologies in helping them quit smoking (14/51, 27.45%). Effort expectancy was not discussed, given participants' limited prior use. Social influences on mobile technology use for smoking cessation were minimally discussed (4/51, 7.84%). CONCLUSIONS: The use of mobile technologies for smoking cessation was unknown to young adults with low socioeconomic status who smoke. To reduce cigarette smoking and associated health disparities, increasing awareness and use of evidence-based mobile-based smoking cessation interventions are needed. Smoking cessation interventions should incorporate features perceived as useful and easy to use to capitalize on positive user experiences and the acceptability of mobile technologies for lifestyle and health management.

Smartphone Screen Time Characteristics in People With Suicidal Thoughts: Retrospective Observational Data Analysis Study.

Background: Smartphone-based monitoring in natural settings provides opportunities to monitor mental health behaviors, including suicidal thoughts and behaviors. To date, most suicidal thoughts and behaviors research using smartphones has primarily relied on collecting so-called "active" data, requiring participants to engage by completing surveys. Data collected passively from smartphone sensors and logs may offer an objectively measured representation of an individual's behavior, including smartphone screen time. Objective: This study aims to present methods for identifying screen-on bouts and deriving screen time characteristics from passively collected smartphone state logs and to estimate daily smartphone screen time in people with suicidal thinking, providing a more reliable alternative to traditional self-report. Methods: Participants (N=126; median age 22, IQR 16-33 years) installed the Beiwe app (Harvard University) on their smartphones, which passively collected phone state logs for up to 6 months after discharge from an inpatient psychiatric unit (adolescents) or emergency department visit (adults). We derived daily screen time measures from these logs, including screen-on time, screen-on bout duration, screen-off bout duration, and screen-on bout count. We estimated the mean of these measures across age subgroups (adults and adolescents), phone operating systems (Android and iOS), and monitoring stages after the discharge (first 4 weeks vs subsequent weeks). We evaluated the sensitivity of daily screen time measures to changes in the parameters of the screen-on bout identification method. Additionally, we estimated the impact of a daylight time change on minute-level screen time using function-on-scalar generalized linear mixed-effects regression. Results: The median monitoring period was 169 (IQR 42-169) days. For adolescents and adults, mean daily screen-on time was 254.6 (95% CI 231.4-277.7) and 271.0 (95% CI 252.2-289.8) minutes, mean daily screen-on bout duration was 4.233 (95% CI 3.565-4.902) and 4.998 (95% CI 4.455-5.541) minutes, mean daily screen-off bout duration was 25.90 (95% CI 20.09-31.71) and 26.90 (95% CI 22.18-31.66) minutes, and mean daily screen-on bout count (natural logarithm transformed) was 4.192 (95% CI 4.041-4.343) and 4.090 (95% CI 3.968-4.213), respectively; there were no significant differences between smartphone operating systems (all P values were >.05). The daily measures were not significantly different for the first 4 weeks compared to the fifth week onward (all P values were >.05), except average screen-on bout in adults (P value = .018). Our sensitivity analysis indicated that in the screen-on bout identification method, the cap on an individual screen-on bout duration has a substantial effect on the resulting daily screen time measures. We observed time windows with a statistically significant effect of daylight time change on screen-on time (based on 95% joint confidence intervals bands), plausibly attributable to sleep time adjustments related to clock changes. Conclusions: Passively collected phone logs offer an alternative to self-report measures for studying smartphone screen time characteristics in people with suicidal thinking. Our work demonstrates the feasibility of this approach, opening doors for further research on the associations between daily screen time, mental health, and other factors.

Automated Detection of Neurodevelopmental Disorders Using Face-to-Face Mobile Technology Among Typically Developing Greek Children: Randomized Controlled Trial.

BACKGROUND: Neurodevelopmental disorders (NDs) are characterized by heterogeneity, complexity, and interactions among multiple domains with long-lasting effects in adulthood. Early and accurate identification of children at risk for NDs is crucial for timely intervention, yet many cases remain undiagnosed, leading to missed opportunities for effective interventions. Digital tools can help clinicians assist and identify NDs. The concept of using serious games to enhance health care has gained attention among a growing group of scientists, entrepreneurs, and clinicians. OBJECTIVE: This study aims to explore the core principles of automated mobile detection of NDs in typically developing Greek children, using a serious game developed within the SmartSpeech project, designed to evaluate multiple developmental domains through principal component analysis (PCA). METHODS: A total of 229 typically developing children aged 4 to 12 years participated in the study. The recruitment process involved open calls through public and private health and educational institutions across Greece. Parents were thoroughly informed about the study's objectives and procedures, and written consent was obtained. Children engaged under the clinician's face-to-face supervision with the serious game "Apsou," which assesses 18 developmental domains, including speech, language, psychomotor, cognitive, psychoemotional, and hearing abilities. Data from the children's interactions were analyzed using PCA to identify key components and underlying principles of ND detection. RESULTS: A sample of 229 typically developing preschoolers and early school-aged children played the Apsou mobile serious game for automated detection of NDs. Performing a PCA, the findings identified 5 main components accounting for about 80% of the data variability that potentially have significant prognostic implications for a safe diagnosis of NDs. Varimax rotation explained 61.44% of the total variance. The results underscore key theoretical principles crucial for the automated detection of NDs. These principles encompass communication skills, speech and language development, vocal processing, cognitive skills and sensory functions, and visual-spatial skills. These components align with the theoretical principles of child development and provide a robust framework for automated ND detection. CONCLUSIONS: The study highlights the feasibility and effectiveness of using serious games for early ND detection in children. The identified principal components offer valuable insights into critical developmental domains, paving the way for the development of advanced machine learning applications to support highly accurate predictions and classifications for automated screening, diagnosis, prognosis, or intervention planning in ND clinical decision-making. Future research should focus on validating these findings across diverse populations integrating additional features such as biometric data and longitudinal tracking to enhance the accuracy and reliability of automated detection systems. TRIAL REGISTRATION: ClinicalTrials.gov NCT06633874; https://clinicaltrials.gov/study/NCT06633874. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-https://doi.org/10.3390/signals4020021.

Engaging Diverse African American/Black and Latine Youth and Emerging Adults Living with HIV into Research: Description of Recruitment Strategies and Lessons Learned.

Improving engagement along the HIV care continuum and reducing racial/ethnic disparities are necessary to end the HIV epidemic. Research on African American/Black and Latine (AABL) younger people living with HIV (LWH) is essential to this goal. However, a number of key subgroups are challenging to locate and engage, and are therefore under-represented in research. Primary among these are persons with non-suppressed HIV viral load, severe socioeconomic disadvantage, transgender/gender expansive identities, and refugee/migrant/immigrant populations. Research in community settings is needed to complement studies conducted in medical institutions. The present study describes the efficiency of recruitment strategies used in the community to enroll AABL young and emerging adults LWH ages 19-28 years. Strategies were designed to be culturally responsive and structurally salient. They were: peer-to-peer, social media, classified advertisements (newspaper, craigslist), subway ads, dating apps (Jack'd, Positive Singles), and direct recruitment in community-based organizations. Data were analyzed using mainly descriptive statistics and interpreted using a consensus building approach. We screened 575 individuals in a first step, 409 were eligible (71%), of these 297 presented to the second screening step (73%), but 112 were lost. Almost all presenting at the second step were eligible (98%, 291/297) and 94% enrolled (274/291). Peer-to-peer, dating app (Jack'd), direct recruitment, and craigslist were the most efficient strategies. Recruitment on dating apps was superior to the peer-to-peer approach in yielding eligible participants (OR = 1.5; 95% CI: 0.98-2.3; p = 0.06). The sample enrolled was diverse with respect to HIV viral suppression, gender identify, sexual orientation, immigration status, and barriers to HIV care engagement. We discuss the advantages and disadvantages of each strategy. Recruitment is a vital aspect of research and warrants attention in the empirical literature.

Dating Apps and Shifting Sexual Subjectivities of Men Seeking Men Online.

Leading theories of the recent history of sexuality have pointed to trends toward detraditionalization and precarity in intimate relations, but also to democratization and innovation. This study grounded in 79 qualitative interviews with men seeking men online considers their experiences in light of these theories. The rise of dating apps has generated sexual fields that have shaped the sexual subjectivities of the current era in multiple ways. The narratives of study participants show much more than the hook-up culture that dating apps are best known for. They speak to experiences of superficiality, unmet expectations, and sometimes bruising intersections with hierarchies defined by age, race, body type, gender expression, and serostatus. Yet at the same time, they show a strong aspiration to sociability, social network building, and reach for a language of affiliation beyond the kin and friendship terms of the larger society. Generational comparisons indicate the shifting sexual subjectivities that dating apps have shaped by constituting virtual sexual fields.

Reliability Issues of Mobile Nutrition Apps for Cardiovascular Disease Prevention: Comparative Study.

Background: Controlling saturated fat and cholesterol intake is important for the prevention of cardiovascular diseases. Although the use of mobile diet-tracking apps has been increasing, the reliability of nutrition apps in tracking saturated fats and cholesterol across different nations remains underexplored. Objective: This study aimed to examine the reliability and consistency of nutrition apps focusing on saturated fat and cholesterol intake across different national contexts. The study focused on 3 key concerns: data omission, inconsistency (variability) of saturated fat and cholesterol values within an app, and the reliability of commercial apps across different national contexts. Methods: Nutrient data from 4 consumer-grade apps (COFIT, MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!) and an academic app (Formosa FoodApp) were compared against 2 national reference databases (US Department of Agriculture [USDA]-Food and Nutrient Database for Dietary Studies [FNDDS] and Taiwan Food Composition Database [FCD]). Percentages of missing nutrients were recorded, and coefficients of variation were used to compute data inconsistencies. One-way ANOVAs were used to examine differences among apps, and paired 2-tailed t tests were used to compare the apps to national reference data. The reliability across different national contexts was investigated by comparing the Chinese and English versions of MyFitnessPal with the USDA-FNDDS and Taiwan FCD. Results: Across the 5 apps, 836 food codes from 42 items were analyzed. Four apps, including COFIT, MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!, significantly underestimated saturated fats, with errors ranging from -13.8% to -40.3% (all P<.05). All apps underestimated cholesterol, with errors ranging from -26.3% to -60.3% (all P<.05). COFIT omitted 47% of saturated fat data, and MyFitnessPal-Chinese missed 62% of cholesterol data. The coefficients of variation of beef, chicken, and seafood ranged from 78% to 145%, from 74% to 112%, and from 97% to 124% across MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!, respectively, indicating a high variability in saturated fats across different food groups. Similarly, cholesterol variability was consistently high in dairy (71%-118%) and prepackaged foods (84%-118%) across all selected apps. When examining the reliability of MyFitnessPal across different national contexts, errors in MyFitnessPal were consistent across different national FCDs (USDA-FNDSS and Taiwan FCD). Regardless of the FCDs used as a reference, these errors persisted to be statistically significant, indicating that the app's core database is the source of the problems rather than just mismatches or variances in external FCDs. Conclusions: The findings reveal substantial inaccuracies and inconsistencies in diet-tracking apps' reporting of saturated fats and cholesterol. These issues raise concerns for the effectiveness of using consumer-grade nutrition apps in cardiovascular disease prevention across different national contexts and within the apps themselves.

Evaluating a Mobile App Supporting Evidence-Based Parenting Skills: Thematic Analysis of Parent Experience.

Background: Disruptive behavior disorders are among the most common disorders of childhood, and evidence-based parenting programs are the first-line treatment. Digital microinterventions have been proposed as one possible means of supporting parenting style change by giving parents in-the-moment advice about how to respond to challenging behavior. Until now, no digital microintervention supporting evidence-based parenting skills programs has been evaluated. Objective: The aim of this study is to evaluate the subjective experience of parents using a digital microintervention to support evidence-based parenting skills, with particular attention to acceptability, usability, family relationships, and parents' values. Methods: We conducted serial interviews with 11 parents of 33 children before and after spending 3 weeks using an app including 3 digital microinterventions. Parents were recruited via local authorities in the Midlands region of the United Kingdom. Previous participation in a parenting program was an inclusion criterion. Interviews explored family composition; child behavior problems; and experience of using the mobile app, including barriers to use. Thematic analysis was conducted from a user-centered design perspective, and illustrative case vignettes were produced. Results: Many parents used the app in ways that helped them rather than strictly following the instructions they were given. Parents described a range of barriers to using the app including practical problems and failure to change child behavior. Parents and children responded in a variety of ways to the use of the phone, with many wholeheartedly embracing the convenience of technology. Case vignettes illustrate the uniqueness of each family's experience. Conclusions: Parents' use of a mobile app supporting evidence-based parenting skills is difficult to predict due to the unique challenges each family encounters. Many parents found it an acceptable and helpful addition to family life, but increased personalization is likely to be key to supporting parents. Future digital microintervention developers should keep in mind that parents are likely to use the app pragmatically rather than following instructions, may struggle to use a complex app under pressure, and are likely to hold complex feelings about parenting with an app.

Artificial intelligence-driven transformations in diabetes care: a comprehensive literature review.

Artificial intelligence (AI) has been applied in healthcare for diagnosis, treatments, disease management, and for studying underlying mechanisms and disease complications in diseases like diabetes and metabolic disorders. This review is a comprehensive overview of various applications of AI in the healthcare system for managing diabetes. A literature search was conducted on PubMed to locate studies integrating AI in the diagnosis, treatment, management and prevention of diabetes. As diabetes is now considered a pandemic now so employing AI and machine learning approaches can be applied to limit diabetes in areas with higher prevalence. Machine learning algorithms can visualize big datasets, and make predictions. AI-powered mobile apps and the closed-loop system automated glucose monitoring and insulin delivery can lower the burden on insulin. AI can help identify disease markers and potential risk factors as well. While promising, AI's integration in the medical field is still challenging due to privacy, data security, bias, and transparency. Overall, AI's potential can be harnessed for better patient outcomes through personalized treatment.

Positive views, attitudes, and acceptability toward mHealth applications in addressing queer sexual and reproductive health: Healthcare providers and the queer individuals.

Objective: In the age of digital health, mankind has resources to write over the historical narrative of queer individuals' healthcare exclusions. The main purpose of this study was to explore the perspectives of both healthcare providers (HCPs) and queer individuals regarding the use of web-based tools and mobile health applications (mHealth apps) in the context of addressing queer individuals' sexual and reproductive health services and needs (SRHSN). Methods: An overall study was conducted as an exploratory sequential mixed method. This article provides findings from the performed qualitative cycle. The selection method was led by purposeful sampling, which targeted 33 HCPs delivering SRHSN within the defined study settings. Additionally, respondent-driven sampling was employed to select 22 queer individuals. Throughout the study, semi-structured one-on-one face-to-face interviews were used to collect data. Results: Four major themes and related sub-themes emerged from HCPs and queer individuals: (a) aid queer individuals with consultations and treatment improvements, (b) drawing parallels with technology in other sectors, (c) enhancing knowledge and education, and (d) positive perception of technological advancements. Conclusions: In accordance with our findings, HCPs and queer individuals were all positive and sees mHealth apps as a tool to address SRHSN for homosexual people.

Assessing the quality of breast cancer-related videos on TikTok: A cross-sectional study.

Purpose: Breast cancer, the most common cancer in women globally, highlights the need for patient education. Despite many breast cancer discussions on TikTok, their scientific evaluation is lacking. Our study seeks to assess the content quality and accuracy of popular TikTok videos on breast cancer, to improve the dissemination of health knowledge. Methods: On August 22, 2023, we collected the top 100 trending videos from TikTok's Chinese version using "breast cancer/breast nodule" as keywords. We noted their length, TikTok duration, likes, comments, favorites, reposts, uploader types, and topics. Four assessment tools were used: Goobie's six questions, the Patient Educational Material Assessment Tool (PEMAT), the Video Information and Quality Index (VIQI), and the Global Quality Score (GQS). These instruments evaluate videos based on content, informational integrity, and overall quality. Results: Among the 100 videos, content quality was low with Goobie's questions mostly scoring 0, except for management at 1.0 (QR 1.0). PEMAT scores were moderate: 54.1 (QR 1.6) for sum, 47.0 (QR 18.8) for PEMAT-A, and 52.3 (QR 11.7) for PEMAT-U. Regarding the quality of information, the VIQI (sum) median was 14.1 (QR 0.2). Additionally, the median GQS score was 3.5 (QR 0.1). Medical professionals' videos focused on breast cancer stages, while patient videos centered on personal experiences. Patient videos had lower content and overall quality compared to those by medical professionals (PEMAT, GQS: P < 0.001, P = 0.004) but received more comments, indicating higher engagement (all P < 0.05). Conclusion: TikTok's breast cancer content shows educational potential, but while informational quality is moderate, content quality needs improvement. Videos by medical professionals are of higher quality. We recommend increased involvement of healthcare professionals on TikTok to enhance content quality. Non-medical users should share verified information, and TikTok should strengthen its content vetting. Users must scrutinize the credibility of health information on social platforms.

Utilization and engagement with an employer-provided digital mental health platform: An international perspective.

Objective: This retrospective study (2020-2022) compared the usage patterns across international regions of an employer-provided digital mental health platform, which is available in native languages and offers both self-guided digital activities and one-on-one sessions. Methods: Routine data from the platform were analyzed by describing the demographic profile of 178,119 users from different geographical regions, their baseline mental health status and burnout levels, as well as patterns of engagement. Statistical analyses were conducted using logistic and ordered logit models to examine the association between cumulative engagement with the platform over time and baseline characteristics. Results: The platform had high engagement and satisfaction levels across regions and age groups. Female users were more engaged than males in both self-guided digital activities and one-on-one sessions. Older users and those from non-US regions were more engaged in self-guided digital activities, while younger users and those from the US were more engaged in one-on-one sessions. Symptoms of anxiety were also associated with engagement with one-on-one sessions. Conclusions: The study's findings provide valuable insights into the benefits of digital platforms in addressing mental health needs of employers from different regions. Future research should focus on exploring the specific factors that influence engagement with digital mental health platforms and how these platforms can be optimized and tailored to better serve diverse populations.