Designing sustainable mobile weight management applications: information technology (IT) experts perspectives.

Background: Weight management mobile applications have become increasingly popular as a tool for individuals to achieve their weight loss goals. However, key challenges with mobile weight management applications are sustaining user engagement and promoting long-term behavior change. This study examines the key functions and features of weight management mobile applications from the viewpoint of information technology (IT) experts. We have developed a framework that outlines the optimal design strategies for mobile apps to support sustainable weight management. Methods: We conducted face-to-face interviews with five experts to evaluate and give input on the proposed framework. Results: Eight specialized functionalities have been categorized and defined based on initial framework system features and recommended features based on experts' feedback: (I) customization; (II) usability; (III) integration; (IV) online support; (V) tracking; (VI) nutrition database; (VII) gamification; and (VIII) notification. In addition, common functionalities were identified as (I) registration/sign in; (II) data privacy; (III) security; and (IV) user feedback. An online discussion indicates the system functionality in four themes: (I) configuration; (II) data analytics; (III) support/performance; and (IV) platform: iOS, Android, Native. Conclusions: These functionalities and features will be incorporated into a framework to design mobile applications for sustainable weight management. Also, to be part of user interface development for the user experience experiments.

The evolution and mapping trends of mobile health (m-Health): a bibliometric analysis (1997-2023).

Background: Mobile health (m-Health) is widely acknowledged as a pivotal domain for improving global healthcare and driving its digital health transformation. Despite the vast amount of literature published in recent years, bibliometric studies on m-Health remain limited in scope and coverage. This study presents a comprehensive review of m-Health literature extracted from Scopus and PubMed databases, spanning the period from 1997 to 2023, including publications during the coronavirus disease 2019 (COVID-19) pandemic. Methods: The combined Scopus and PubMed databases were used in this study. The search formula for the literature retrieval used the most appropriate and relevant keywords to m-Health. The bibliometric data importation, extraction and analysis of authors, titles, publication date, publication place, publisher, volume number, issue number, citation count, document type, author keywords, affiliation were all carried out using the 'Biblioshiny', 'EndNote X9®', 'Microsoft Excel®' and 'Microsoft Access®' software tools. Duplicate records were manually identified and removed. Visualization maps illustrating the recurrent keywords, collaboration patterns, and prolific publishing countries were generated using 'VOSviewer®'. Results: A total of 37,470 (20,703 from Scopus and 16,767 from PubMed) publications were selected for the literature analysis. The results provided the definitive literature evidence on the origin of the concept of m-Health in 2003. Significant increase in the publications followed the global surge of smart phones usage in 2007, and the emergence of m-Health applications (Apps) and their global markets and ecosystems. The number of the publications peaked between 2013 and 2022 with most citations in 2022. There was noticeable spike in m-Health literature during the COVID-19 pandemic. The results also showed that most of the highly cited publications, leading institutions, and most prolific authors were predominantly from the developed countries. The USA has the highest number of publications followed by the UK, Australia, Germany, Canada and China, with most of the prolific authors originating from these countries. Conclusions: In conclusion, while there has been a remarkable increase in global m-Health publications since 2003, most of the impactful literature and publications in this area originated from selected countries in the developed world. The study indicates a significant disparity between the published literature from developed compared to the developing countries. Addressing this disparity, further bibliographical studies are required to address these and other literature gaps.

mHealth app features that facilitate adolescent use for lifestyle management, and are endorsed by caregivers and health care providers.

Background: Mobile health (mHealth) apps are becoming a promising tool to motivate sustainable lifestyle and behavior changes, including modifications to diet and exercise. However, most current mHealth apps do not have meaningful, and sustained user acceptance, particularly, among adolescents. They perceive mHealth apps designed for adults to be tedious and visually unexciting, which discourage adolescent usage. Researchers and adolescent mHealth app developers would benefit from a foundational understanding of which functions and features adolescents feel would most motivate app use. Capturing caregivers' and health care providers' inputs are also important as both groups play an integral role in adolescent health care decision-making. The purpose of the study is to explore and analyze mHealth app features identified by adolescents, caregivers, and health care providers that have the potential to inspire continued use, thereby resulting in sustained health behavior changes in adolescents. Methods: We used inductive thematic analysis of qualitative data obtained from semi-structured focus groups conducted via Zoom©. Important features of mHealth apps that encourage adoption and continued use were explored with 25 participants, including adolescents, their caregivers, and health care providers. Results: Common features facilitating continual usage of mHealth apps that were identified as significant by participating adolescents, their caregivers and health care providers were: look and feel of the app, customization, educational information/recommendations, and integration with electronic health record. Features such as gamification and social interaction that are usually lacking in current adolescent mHealth apps were well recognized as meaningful for motivational purposes. Conclusions: The findings suggest that adolescents and caregivers identify an app as valuable when it is user-friendly and intuitive and appreciate features that are motivating and can engage users in positive behaviors. Health care providers prefer mHealth apps that are user-friendly and can be effectively integrated into the cycle of care, thereby enabling delivery of efficient and value-based health care. Thus, mHealth app designs that are informed by health care providers' clinical experience and needs, in combination with app features that are desired and supported by both adolescents and their caregivers, have the potential to motivate widespread adoption and long-term use, which could result in improved health behaviors and outcomes among adolescents.

Exploring User Experiences of the Mom2B mHealth Research App During the Perinatal Period: Qualitative Study.

BACKGROUND: Perinatal depression affects a significant number of women during pregnancy and after birth, and early identification is imperative for timely interventions and improved prognosis. Mobile apps offer the potential to overcome barriers to health care provision and facilitate clinical research. However, little is known about users' perceptions and acceptability of these apps, particularly digital phenotyping and ecological momentary assessment apps, a relatively novel category of apps and approach to data collection. Understanding user's concerns and the challenges they experience using the app will facilitate adoption and continued engagement. OBJECTIVE: This qualitative study explores the experiences and attitudes of users of the Mom2B mobile health (mHealth) research app (Uppsala University) during the perinatal period. In particular, we aimed to determine the acceptability of the app and any concerns about providing data through a mobile app. METHODS: Semistructured focus group interviews were conducted digitally in Swedish with 13 groups and a total of 41 participants. Participants had been active users of the Mom2B app for at least 6 weeks and included pregnant and postpartum women, both with and without depression symptomatology apparent in their last screening test. Interviews were recorded, transcribed verbatim, translated to English, and evaluated using inductive thematic analysis. RESULTS: Four themes were elicited: acceptability of sharing data, motivators and incentives, barriers to task completion, and user experience. Participants also gave suggestions for the improvement of features and user experience. CONCLUSIONS: The study findings suggest that app-based digital phenotyping is a feasible and acceptable method of conducting research and health care delivery among perinatal women. The Mom2B app was perceived as an efficient and practical tool that facilitates engagement in research as well as allows users to monitor their well-being and receive general and personalized information related to the perinatal period. However, this study also highlights the importance of trustworthiness, accessibility, and prompt technical issue resolution in the development of future research apps in cooperation with end users. The study contributes to the growing body of literature on the usability and acceptability of mobile apps for research and ecological momentary assessment and underscores the need for continued research in this area.

Promoting the social implementation of digital and mobile health: effects of regulation on user and non-user behavior in East Asia.

This study conducted policy and regulation analyses and user acceptance surveys in three East Asian countries with developed telecommunication infrastructure (China, South Korea, and Japan) to determine the most effective way to implement mobile health (mHealth). Regional differences in users' emphasis on the purpose of mHealth, including medical information referral or health management, appear to be influenced by regional regulation, thus making regulation analysis important when considering mHealth penetration strategies. Potential mHealth users have high expectations for medical information and correspondence, which is crucial for the pharmaceutical industry in terms of providing information and retaining patients. Furthermore, potential users are willing to use the system medically, which is beneficial to the pharmaceutical industry when introducing mHealth and prescriptions in combination.

The effect of a digital intervention on symptoms of depression in pregnant women exposed to Intimate partner violence in Denmark and Spain (STOP study).

INTRODUCTION AND OBJECTIVE: Intimate Partner Violence (IPV) during pregnancy is a significant public health concern associated with adverse maternal and fetal health outcomes, including increased risk of depression. This study aimed to assess the effectiveness of a digital empowerment-based intervention in reducing symptoms of depression among IPV-exposed pregnant women. STUDY DESIGN: This intervention study was nested within a cohort study conducted in Denmark and Spain. Pregnant women attending antenatal care were digital screened for IPV using the Abuse Assessment Screen (AAS) and the Women's Abuse Screening Tool (WAST). Those screening positive were offered a digital intervention comprising 3-6 video consultations with trained IPV counsellors and access to a safety planning app. Changes in depression scores from baseline to follow-up were evaluated using mixed model regression. RESULTS: From February 2021-October 2022, 1,545 pregnant women (9.6 %) screened positive for IPV within our population (8.5 % in Denmark and 17.0 % in Spain) with 485 (31.4 %) meeting the criteria for the intervention. Of those eligible, 104 (21.4 %) accepted the intervention, and 55 completed it (13.1 %). Post-intervention, a significant reduction in Edinburgh Postnatal Depression Scale (EPDS) was found, with a mean difference of -3.9 (95 % CI: -5.3; -2.4), compared to the average pre-intervention score of 11.3. Stratifying the analyses across sociodemographic variables did not alter the overall result, indicating a reduction in EPDS scores irrespective of setting or sociodemographic factors. Notably, the intervention was most effective for women initially presenting with EPDS scores above the depression cut-off. CONCLUSION: The findings suggest that a brief digital intervention is associated with a reduction in depression symptoms among pregnant women exposed to IPV, particularly among those with high depressive scores. This highlights the potential of digital interventions in delivering counseling and shows efficacy when administered by both midwives and psychologists in diverse settings. However, the absence of a control group underscores the need for caution in interpreting the results.

Current status and future prospects of Chinese mobile apps for hypertension management.

OBJECTIVE: This study aimed to evaluate the current situation of Chinese mobile apps for hypertension management and explore patients' real requirements for app use, providing a theoretical basis for the future improvement of hypertension apps. METHODS: We reviewed hypertension management apps from mobile app platforms, and summarized their functional characteristics. In addition, we conducted an online survey among 1000 hypertensive patients, collected valid responses, and analyzed the feedback data. RESULTS: Forty hypertension management apps were analyzed, with 72.5% offering no more than six functions, indicating limited coverage of advanced and comprehensive functionalities. Among the 934 valid survey responses, patients emphasized four main functions in apps for hypertension management: long-term dynamic blood pressure monitoring, scientific lifestyle management, strict medication management and systematic health knowledge delivering. CONCLUSION: The existing hypertension management apps mainly serve as "Digital Health" tools with unclear clinical efficacy. The future development of these apps lies in how they transition to "Digital Therapeutics" solutions to better meet patients' needs and provide clear clinical advantages.

The moderating effect of access to food facilities and recreational activity space on mHealth multiple health behavior change intervention.

OBJECTIVE: To evaluate whether the neighborhood social and built environment moderates response to a mobile health multiple health behavior change intervention targeting fruit/vegetable intake, sedentary behavior, and physical activity. METHODS: Participants were 156 Chicago-residing adults with unhealthy lifestyle behaviors. Using linear mixed models, we evaluated whether access to food facilities (fast food restaurants and grocery stores) and recreational activity spaces (gyms and parks) moderated the difference in behavior change between the active intervention condition relative to control. Using spatial data analysis (cross K functions), we also assessed whether participants who achieved goal levels of behaviors ("responders") were more or less likely than those who did not achieve intervention goals ("non-responders") to reside near fast food restaurants, grocery stores, gyms, or parks. RESULTS: According to linear mixed models, none of the neighborhood social and built environment factors moderated the difference in behavior change between the active intervention condition and the control condition (Likelihood Ratio (χ²[1] = 0.02-2.33, P-values > 0.05). Cross K functions showed that diet behavior change responders were more likely than non-responders to reside near fast food restaurants, but not grocery stores. The results for activity behavior change were more variable. Sedentary screen time responders were more likely to reside around recreational activity spaces than non-responders. Moderate-vigorous physical activity responders had greater and lesser clustering than non-responders around parks, dependent upon distance from the park to participant residence. CONCLUSIONS: A complex relationship was observed between residential proximity to Chicago facilities and response to multiple health behavior change intervention. Replication across diverse geographic settings and samples is necessary.

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

BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Behavior Change Techniques Within Digital Interventions for the Treatment of Eating Disorders: Systematic Review and Meta-Analysis.

BACKGROUND: Previous systematic reviews of digital eating disorder interventions have demonstrated effectiveness at improving symptoms of eating disorders; however, our understanding of how these interventions work and what contributes to their effectiveness is limited. Understanding the behavior change techniques (BCTs) that are most commonly included within effective interventions may provide valuable information for researchers and developers. Establishing whether these techniques have been informed by theory will identify whether they target those mechanisms of action that have been identified as core to changing eating disorder behaviors. It will also evaluate the importance of a theoretical approach to digital intervention design. OBJECTIVE: This study aims to define the BCTs within digital self-management interventions or minimally guided self-help interventions for adults with eating disorders that have been evaluated within randomized controlled trials. It also assessed which of the digital interventions were grounded in theory and the range of modes of delivery included. METHODS: A literature search identified randomized controlled trials of digital intervention for the treatment of adults with eating disorders with minimal therapist support. Each digital intervention was coded for BCTs using the established BCT Taxonomy v1; for the application of theory using an adapted version of the theory coding scheme (TCS); and for modes of delivery using the Mode of Delivery Ontology. A meta-analysis evaluated the evidence that any individual BCT moderated effect size or that other potential factors such as the application of theory or number of modes of delivery had an effect on eating disorder outcomes. RESULTS: Digital interventions included an average of 14 (SD 2.6; range 9-18) BCTs. Self-monitoring of behavior was included in all effective interventions, with Problem-solving, Information about antecedents, Feedback on behavior, Self-monitoring of outcomes of behavior, and Action planning identified in >75% (13/17) of effective interventions. Social support and Information about health consequences were more evident in effective interventions at follow-up compared with postintervention measurement. The mean number of modes of delivery was 4 (SD 1.6; range 2-7) out of 12 possible modes, with most interventions (15/17, 88%) being web based. Digital interventions that had a higher score on the TCS had a greater effect size than those with a lower TCS score (subgroup differences: χ21=9.7; P=.002; I²=89.7%) within the meta-analysis. No other subgroup analyses had statistically significant results. CONCLUSIONS: There was a high level of consistency in terms of the most common BCTs within effective interventions; however, there was no evidence that any specific BCT contributed to intervention efficacy. The interventions that were more strongly informed by theory demonstrated greater improvements in eating disorder outcomes compared to waitlist or treatment-as-usual controls. These results can be used to inform the development of future digital eating disorder interventions. TRIAL REGISTRATION: PROSPERO CRD42023410060; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=410060.

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study.

BACKGROUND: A coordinated care system helps provide timely access to treatment for suspected acute stroke. In Northwestern Ontario (NWO), Canada, communities are widespread with several hospitals offering various diagnostic equipment and services. Thus, resources are limited, and health care providers must often transfer patients with stroke to different hospital locations to ensure the most appropriate care access within recommended time frames. However, health care providers frequently situated temporarily (locum) in NWO or providing care remotely from other areas of Ontario may lack sufficient information and experience in the region to access care for a patient with a time-sensitive condition. Suboptimal decision-making may lead to multiple transfers before definitive stroke care is obtained, resulting in poor outcomes and additional health care system costs. OBJECTIVE: We aimed to develop a tool to inform and assist NWO health care providers in determining the best transfer options for patients with stroke to provide the most efficient care access. We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities. METHODS: Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. These data contained parameters regarding air (Ornge) and land medical transport (3 services), which were preprocessed and cleaned. For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model. RESULTS: In total, 70,623 records were collected in the data set from Ornge and land medical transport services to develop a prediction model. Various learning models were analyzed; all learning models perform better than the simple average of all points in predicting output variables. The decision tree model provided more accurate results than the other models. The decision tree model performed remarkably well, with the values from testing, validation, and the model within a close range. This model was used to develop the "NWO Navigate Stroke" system. The system provides accurate results and demonstrates that a mobile app can be a significant tool for health care providers navigating stroke care in NWO, potentially impacting patient care and outcomes. CONCLUSIONS: The NWO Navigate Stroke system uses a data-driven, reliable, accurate prediction model while considering all variations and is simultaneously linked to all required acute stroke management pathways and tools. It was tested using historical data, and the next step will to involve usability testing with end users.

Development and validation of the mobile adherence satisfaction scale (MASS) for medication adherence apps.

OBJECTIVE: To develop and validate the Mobile Adherence Satisfaction Scale (MASS) for assessing user satisfaction with mobile health applications aimed to improve medication adherence. METHODS: The study involved patients over 18 with asthma, hypertension, heart failure, or diabetes, who used the CareAide® app for six months. Scale development included a literature review, expert consultations, and patient interviews, initially identifying 129 items. These were refined to 27 using a two-round Delphi technique and grouped into six dimensions: user interface, perceived usability, system quality, service quality, feature satisfaction, and general satisfaction. A pilot study with 30 participants further refined the model, which was then validated with 135 participants using exploratory and confirmatory factor analyses in SPSS 29 and SmartPLS 4. Data were collected via self-administered questionnaires. RESULTS: A total of 135 complete questionnaires were analysed. Respondents had an average age of 66.7 years (SD = 11.6) with 42.2 % male (n = 57) and 57.8 % female (n = 78). After removal of an item due to cross loading, exploratory factor analysis resulted six dimensions and 26 items with Kaiser-Meyer-Olkin measure of 0.837 and Bartlett's Test of Sphericity (χ2(n = 325) = 2085.673, P < 0.001). The confirmatory factor analysis confirmed high reliability and validity: Cronbach's alpha values > 0.70 for each dimension and an overall alpha of 0.89, with Composite Reliability and Average Variance Extracted both >0.70 and >0.50, respectively, for each dimension. Structural model indicated a significant positive impact of user interface (ß = 0.226, P = 0.006) and feature satisfaction (ß = 0.230, P = 0.002) on general satisfaction, explaining 23.1 % of the variance (R2 = 0.231). CONCLUSION: The study developed and validated the MASS, a reliable tool for assessing user satisfaction with mHealth apps. User interface design and feature satisfaction are key for long-term engagement and consistent medication adherence.

Ethical considerations in telehealth and artificial intelligence for work related musculoskeletal disorders: A scoping review.

BACKGROUND: Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to perform tasks that typically require human intelligence. The integration of AI and telehealth applications in healthcare raises ethical concerns such as bias, transparency, data privacy, and accountability for errors. Several studies have assessed this topic, particularly with regard to musculoskeletal disorders, which will be the focus of this manuscript. OBJECTIVE: We will examine key ethical concepts including informed consent, data protection, confidentiality, physician malpractice, liability, and telemedicine regulations. METHODS: Ethical issues pertaining to the topic were explored through a review paper. The primary objective of this scoping review was to map and synthesize the existing literature concerning ethical considerations in telehealth and AI for work-related musculoskeletal disorders. RESULTS: Research demonstrates that medication effectiveness, patient and physician satisfaction, and accessibility costs are higher with telemedicine and AI methods compared to in-person approaches, particularly for work-related musculoskeletal disorders. Therefore, addressing ethical issues, including patient data privacy and security, is crucial in this field. By considering these factors, the adoption of emerging AI and telemedicine applications, especially for work-related musculoskeletal disorders, is likely to increase. CONCLUSION: AI and telemedicine offer significant advantages, particularly in addressing work-related musculoskeletal disorders. However, ethical and legal issues surrounding their practice require standardized rules to ensure equitable access, quality care, sustainable costs, professional liability, patient privacy, data protection, and confidentiality. Further practical research studies are needed to address these considerations more effectively.

Contactless and Calibration-Free Blood Pressure and Pulse Rate Monitor for Screening and Monitoring of Hypertension: Cross-Sectional Validation Study.

BACKGROUND: The key to reducing the immense morbidity and mortality burdens of cardiovascular diseases is to help people keep their blood pressure (BP) at safe levels. This requires that more people with hypertension be identified, diagnosed, and given tools to lower their BP. BP monitors are critical to hypertension diagnosis and management. However, there are characteristics of conventional BP monitors (oscillometric cuff sphygmomanometers) that hinder rapid and effective hypertension diagnosis and management. Calibration-free, software-only BP monitors that operate on ubiquitous mobile devices can enable on-demand BP monitoring, overcoming the hardware barriers of conventional BP monitors. OBJECTIVE: This study aims to investigate the accuracy of a contactless BP monitor software app for classifying the full range of clinically relevant BPs as hypertensive or nonhypertensive and to evaluate its accuracy for measuring the pulse rate (PR) and BP of people with BPs relevant to stage-1 hypertension. METHODS: The software app, known commercially as Lifelight, was investigated following the data collection and data analysis methodology outlined in International Organization for Standardization (ISO) 81060-2:2018/AMD 1:2020 "Non-invasive Sphygmomanometers-Part 2: Clinical investigation of automated measurement type." This validation study was conducted by the independent laboratory Element Materials Technology Boulder (formerly Clinimark). The study generated data from 85 people aged 18-85 years with a wide-ranging distribution of BPs specified in ISO 81060-2:2018/AMD 1:2020. At least 20% were required to have Fitzpatrick scale skin tones of 5 or 6 (ie, dark skin tones). The accuracy of the app's BP measurements was assessed by comparing its BP measurements with measurements made by dual-observer manual auscultation using the same-arm sequential method specified in ISO 81060-2:2018/AMD 1:2020. The accuracy of the app's PR measurements was assessed by comparing its measurements with concurrent electroencephalography-derived heart rate values. RESULTS: The app measured PR with an accuracy root-mean-square of 1.3 beats per minute and mean absolute error of 1.1 (SD 0.8) beats per minute. The sensitivity and specificity with which it determined that BPs exceeded the in-clinic systolic threshold for hypertension diagnosis were 70.1% and 71.7%, respectively. These rates are consistent with those reported for conventional BP monitors in a literature review by The National Institute for Health and Care Excellence. The app's mean error for measuring BP in the range of normotension and stage-1 hypertension (ie, 65/85, 76% of participants) was 6.5 (SD 12.9) mm Hg for systolic BP and 0.4 (SD 10.6) mm Hg for diastolic BP. Mean absolute error was 11.3 (SD 10.0) mm Hg and 8.6 (SD 6.8) mm Hg, respectively. CONCLUSIONS: A calibration-free, software-only medical device was independently tested against ISO 81060-2:2018/AMD 1:2020. The safety and performance demonstrated in this study suggest that this technique could be a potential solution for rapid and scalable screening and management of hypertension.

Using Wearables to Study Biopsychosocial Dynamics in Couples Who Cope With a Chronic Health Condition: Ambulatory Assessment Study.

BACKGROUND: Technology has become an integral part of our everyday life, and its use to manage and study health is no exception. Romantic partners play a critical role in managing chronic health conditions as they tend to be a primary source of support. OBJECTIVE: This study tests the feasibility of using commercial wearables to monitor couples' unique way of communicating and supporting each other and documents the physiological correlates of interpersonal dynamics (ie, heart rate linkage). METHODS: We analyzed 617 audio recordings of 5-minute duration (384 with concurrent heart rate data) and 527 brief self-reports collected from 11 couples in which 1 partner had type II diabetes during the course of their typical daily lives. Audio data were coded by trained raters for social support. The extent to which heart rate fluctuations were linked among couples was quantified using cross-correlations. Random-intercept multilevel models explored whether cross-correlations might differ by social contexts and exchanges. RESULTS: Sixty percent of audio recordings captured speech between partners and partners reported personal contact with each other in 75% of self-reports. Based on the coding, social support was found in 6% of recordings, whereas at least 1 partner self-reported social support about half the time (53%). Couples, on average, showed small to moderate interconnections in their heart rate fluctuations (r=0.04-0.22). Couples also varied in the extent to which there was lagged linkage, that is, meaning that changes in one partner's heart rate tended to precede changes in the other partner's heart rate. Exploratory analyses showed that heart rate linkage was stronger (1) in rater-coded partner conversations (vs moments of no rater-coded partner conversations: rdiff=0.13; P=.03), (2) when partners self-reported interpersonal contact (vs moments of no self-reported interpersonal contact: rdiff=0.20; P<.001), and (3) when partners self-reported social support exchanges (vs moments of no self-reported social support exchange: rdiff=0.15; P=.004). CONCLUSIONS: Our study provides initial evidence for the utility of using wearables to collect biopsychosocial data in couples managing a chronic health condition in daily life. Specifically, heart rate linkage might play a role in fostering chronic disease management as a couple. Insights from collecting such data could inform future technology interventions to promote healthy lifestyle engagement and adaptive chronic disease management. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/13685.

Effectiveness of a message service on child oral health practice via a social media application: A randomized controlled trial.

BACKGROUND: Early establishment of healthy oral health behaviours is important to reduce early childhood caries risk. Two-way social media applications can economically assist caregivers. AIM: To evaluate the effectiveness of a LINE™ messaging service (MS) on promoting good oral health behaviors in Thai children. DESIGN: One hundred and ninety caregiver-child dyads (children aged 6-36 months) who attended a university dental hospital and two other hospitals were randomly assigned to receive age-appropriate dental health education via MS or through traditional on-site visits. Infographic posters, video clips, and supportive messages were delivered weekly to the MS group. Parental oral health knowledge and children's oral health status and practice were assessed at baseline and 6-month follow-up. RESULTS: The MS group showed significantly better scores in feeding habits (p = .034) and toothbrushing practice (p = .007). Parental knowledge increased in both groups; however, knowledge increased significantly in the control group (p = .001). Both groups exhibited improvements in the debris score but not in caries progression. The caregivers rated both methods as high to the highest satisfaction. CONCLUSIONS: The MS yielded comparable outcomes to traditional dental visits in promoting oral health behaviours.

Evaluating the Quality and Comparative Validity of Manual Food Logging and Artificial Intelligence-Enabled Food Image Recognition in Apps for Nutrition Care.

For artificial intelligence (AI) to support nutrition care, high quality and accuracy of its features within smartphone applications (apps) are essential. This study evaluated popular apps' features, quality, behaviour change potential, and comparative validity of dietary assessment via manual logging and AI. The top 200 free and paid nutrition-related apps from Australia's Apple App and Google Play stores were screened (n = 800). Apps were assessed using MARS (quality) and ABACUS (behaviour change potential). Nutritional outputs from manual food logging and AI-enabled food-image recognition apps were compared with food records for Western, Asian, and Recommended diets. Among 18 apps, Noom scored highest on MARS (mean = 4.44) and ABACUS (21/21). From 16 manual food-logging apps, energy was overestimated for Western (mean: 1040 kJ) but underestimated for Asian (mean: -1520 kJ) diets. MyFitnessPal and Fastic had the highest accuracy (97% and 92%, respectively) out of seven AI-enabled food image recognition apps. Apps with more AI integration demonstrated better functionality, but automatic energy estimations from AI-enabled food image recognition were inaccurate. To enhance the integration of apps into nutrition care, collaborating with dietitians is essential for improving their credibility and comparative validity by expanding food databases. Moreover, training AI models are needed to improve AI-enabled food recognition, especially for mixed dishes and culturally diverse foods.

An evaluation of patient experience before and after elective colectomy for diverticulitis between patients older and younger than 65 years: A pilot feasibility study in mobile health use.

BACKGROUND: Mobile health (mHealth) platforms are being used to understand patient-reported experiences before and after surgery. Currently, there is limited literature describing the feasibility of using mHealth to evaluate patient experience among older adults. The objective of this study was to determine the feasibility of using mHealth to evaluate patient-reported outcomes among patients older and younger than 65 years undergoing elective colectomy for diverticulitis. METHODS: A prospective pilot study was performed between June 1, 2020 and August 31, 2021, enrolling patients aged > 18 years undergoing elective colectomy for diverticulitis at a single academic center (n = 62). A Health Insurance Portability and Accountability Act-compliant mHealth platform was used to deliver patient-reported quality-of-life surveys at 3 time points: preoperatively, 3 months postoperatively, and 6 months postoperatively. The primary outcome was the feasibility of using mHealth in patients older and younger than 65 years to collect outcomes using recruitment, engagement, and survey completion rates. Preliminary findings of patient experiences were evaluated for patients older and younger than 65 years as secondary outcomes. RESULTS: Overall, 33.9% of participants were older than 65 years with a median age of 59.8 years (IQR, 53.3-67.9). mHealth enrollment was high (100%) with survey response rates of 79% preoperatively, 64.5% at 3 months postoperatively, and 17.7% at 6 months postoperatively. Response rates were similar among patients older and younger than 65 years (P = .79 preoperatively and P = .39 at 3 months postoperatively). CONCLUSION: Utilization of mHealth to evaluate patient-reported outcomes is feasible in the preoperative and early postoperative settings, including older adults undergoing elective surgery for diverticulitis. Future work will focus on improving long-term outcomes to better examine potential differences when considering patient-centered outcomes among older adult patients.

An Automated Text Messaging Intervention to Reduce Substance Use Self-Stigma (Project RESTART): Protocol for a Feasibility and Acceptability Pilot Study.

BACKGROUND: Stigma is a barrier to treatment and harm reduction seeking in people who use drugs. Most stigma reduction interventions offer psychotherapy or psychoeducation in group-based clinical settings, failing to reach people who are not in treatment. SMS text messaging is an effective and acceptable modality for delivering health information to people who use drugs and may be a suitable conduit for providing information and advice to understand and cope with stigma. OBJECTIVE: This paper presents the protocol for a study that aims to determine the feasibility, acceptability, and preliminary effectiveness of a 4-week automated SMS text message intervention to increase stigma resistance and reduce self-stigma in people who use drugs. METHODS: We designed a novel automated SMS text message intervention to address the four personal-level constructs of stigma resistance: (1) not believing stigma and catching and challenging stigmatizing thoughts, (2) empowering oneself through learning about substance use and one's recovery, (3) maintaining one's recovery and proving stigma wrong, and (4) developing a meaningful identity and purpose apart from one's substance use. Theory-based messages were developed and pilot-tested in qualitative elicitation interviews with 22 people who use drugs, resulting in a library of 56 messages. In a single-group, within-subjects, community-based pilot trial, we will enroll 30 participants in the Resisting Stigma and Revaluating Your Thoughts (RESTART) intervention. Participants will receive 2 daily SMS text messages for 4 weeks. Implementation feasibility will be assessed through recruitment, enrollment, retention, and message delivery statistics. User feasibility and acceptability will be assessed at follow-up using 23 survey items informed by the Theoretical Framework of Acceptability. Primary effectiveness outcomes are changes in self-stigma (Substance Abuse Self-Stigma Scale) and stigma resistance (Stigma Resistance Scale) from baseline to follow-up measured via a self-administered survey. Secondary outcomes are changes in hope (Adult Dispositional Hope Scale) and self-esteem (Rosenberg Self-Esteem Scale). Feasibility and acceptability will be assessed with descriptive statistics; effectiveness outcomes will be assessed with paired 2-tailed t tests, and group differences will be explored using ANOVA. Overall, 12 participants will also be selected to complete acceptability interviews. RESULTS: This pilot study was funded by the National Institute on Drug Abuse in April 2023 and received regulatory approval in January 2024 by the University of North Carolina-Chapel Hill Institutional Review Board. Recruitment and enrollment began in March 2024. Follow-up visits are expected to conclude by May 2024. Results will be disseminated in relevant peer-reviewed journals. CONCLUSIONS: To the best of our knowledge, this is the first study to address substance use stigma via a self-help SMS text messaging program. Results will add to the nascent literature on stigma reduction in people who use drugs. This protocol may interest researchers who are considering text messaging to address psychosocial needs in hard-to-reach populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT06281548; https://clinicaltrials.gov/ct2/show/NCT06281548. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59224.