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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.

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BACKGROUND: Queer individuals continue to be marginalized in South Africa; they experience various health care challenges (eg, stigma, discrimination, prejudice, harassment, and humiliation), mental health issues (eg, suicide and depression), and an increased spread of HIV or AIDS and sexually transmitted illnesses (STIs; chlamydia, gonorrhea, and syphilis). Mobile health (mHealth) apps have the potential to resolve the health care deficits experienced by health care providers when managing queer individuals and by queer individuals when accessing sexual-reproductive health care services and needs, thus ensuring inclusivity and the promotion of health and well-being. Studies have proven that the nominal group technique (NGT) could be used to solve different social and health problems and develop innovative solutions. This technique ensures that different voices are represented during decision-making processes and leads to robust results. OBJECTIVE: This study aims to identify important contents to include in the development of an mHealth app for addressing the sexual-reproductive health care services and needs of queer individuals. METHODS: We invited a group of 13 experts from different fields, such as researchers, queer activists, sexual and reproductive health experts, private practicing health care providers, innovators, and private health care stakeholders, to take part in a face-to-face NGT. The NGT was conducted in the form of a workshop with 1 moderator, 2 research assistants, and 1 principal investigator. The workshop lasted approximately 2 hours 46 minutes and 55 seconds. We followed and applied 5 NGT steps in the workshop for experts to reach consensus. The main question that experts were expected to answer was as follows: Which content should be included in the mHealth app for addressing sexual-reproductive health care services and needs for queer individuals? This question was guided by user demographics and background, health education and information, privacy and security, accessibility and inclusivity, functionality and menu options, personalization and user engagement, service integration and partnerships, feedback and improvement, cultural sensitivity and ethical considerations, legal and regulatory compliance, and connectivity and data use. RESULTS: Overall, experts voted and ranked the following main icons: menu options (66 points), privacy and security (39 points), user engagement (27 points), information hub (26 points), user demographics (20 points), connectivity (16 points), service integration and partnerships (10 points), functionalities (10 points), and accessibility and inclusivity (7 points). CONCLUSIONS: Conducting an NGT with experts from different fields, possessing vast skill sets, knowledge, and expertise, enabled us to obtain targeted data on the development of an mHealth app to address sexual-reproductive health care services and needs for queer individuals. This approach emphasized the usefulness of a multidisciplinary perspective to inform the development of our mHealth app and demonstrated the future need for continuity in using this approach for other digital health care innovations and interventions.

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BACKGROUND: Mental health conditions are highly prevalent among US veterans. The Veterans Health Administration (VHA) is committed to enhancing mental health care through the integration of measurement-based care (MBC) practices, guided by its Collect-Share-Act model. Incorporating the use of remote mobile apps may further support the implementation of MBC for mental health care. OBJECTIVE: This study aims to evaluate veteran experiences with Mental Health Checkup (MHC), a VHA mobile app to support remote MBC for mental health. METHODS: Our mixed methods sequential explanatory evaluation encompassed mailed surveys with veterans who used MHC and follow-up semistructured interviews with a subset of survey respondents. We analyzed survey data using descriptive statistics. We then compared responses between veterans who indicated having used MHC for ≥3 versus <3 months using χ2 tests. We analyzed interview data using thematic analysis. RESULTS: We received 533 surveys (533/2631, for a 20% response rate) and completed 20 interviews. Findings from these data supported one another and highlighted 4 key themes. (1) The MHC app had positive impacts on care processes for veterans: a majority of MHC users overall, and a greater proportion who had used MHC for ≥3 months (versus <3 months), agreed or strongly agreed that using MHC helped them be more engaged in their health and health care (169/262, 65%), make decisions about their treatment (157/262, 60%), and set goals related to their health and health care (156/262, 60%). Similarly, interviewees described that visualizing progress through graphs of their assessment data over time motivated them to continue therapy and increased self-awareness. (2) A majority of respondents overall, and a greater proportion who had used MHC for ≥3 months (versus <3 months), agreed/strongly agreed that using MHC enhanced their communication (112/164, 68% versus 51/98, 52%; P=.009) and rapport (95/164, 58% versus 42/98, 43%; P=.02) with their VHA providers. Likewise, interviewees described how MHC helped focus therapy time and facilitated trust. (3) However, veterans also endorsed some challenges using MHC. Among respondents overall, these included difficulty understanding graphs of their assessment data (102/245, 42%), not receiving enough training on the app (73/259, 28%), and not being able to change responses to assessment questions (72/256, 28%). (4) Interviewees offered suggestions for improving the app (eg, facilitating ease of log-in, offering additional reminder features) and for increasing adoption (eg, marketing the app and its potential advantages for veterans receiving mental health care). CONCLUSIONS: Although experiences with the MHC app varied, veterans were positive overall about its use. Veterans described associations between the use of MHC and engagement in their own care, self-management, and interactions with their VHA mental health providers. Findings support the potential of MHC as a technology capable of supporting the VHA's Collect-Share-Act model of MBC.

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BACKGROUND: Local anesthetics (LAs) are regularly used to alleviate pain during medical or surgical procedures. Their use is generally considered safe, but exceeding the maximum recommended doses can lead to LA systemic toxicity, a rare but potentially lethal complication. Determining maximum safe doses is therefore mandatory before performing local anesthesia, but rules are often unclear and the factors affecting dose calculation are numerous. Mobile health apps have been shown to help clinical decision-making, but most currently available apps present significant limitations. The Local Anesthetics Dose Calculator (LoAD Calc) app was designed to overcome these limitations by taking all relevant parameters into account. Before deploying this app in a clinical setting, it should be tested to determine its effectiveness and whether clinicians would be willing to use it. OBJECTIVE: The primary objective will be to evaluate the effectiveness of the LoAD Calc app through written simulated cases. The secondary objective will be to determine whether physicians find this app easier, faster, and safer than the methods they generally use. METHODS: We describe a parallel-group randomized controlled trial protocol. Anesthesiologists working at the Geneva University Hospitals will be invited to participate. Participants will be asked to compute the maximum dose of LA in 10 simulated clinical cases using 3 different LAs. The maximum safe dose will be determined manually using the same calculation rules that were used to develop LoAD Calc, without using the app itself. An overdose will be considered any dose higher than the correct dose, rounded to the superior integer, while an underdose will be defined as the optimal calculated dose minus 20%, rounded to the inferior integer. Randomization will be stratified according to current position (resident vs registrar). The participants allocated to the LoAD Calc (experimental) group will use the LoAD Calc app to compute the maximum safe LA doses. Those allocated to the control group will be asked to use the method they generally use. The primary outcome will be the overall overdose rate. Secondary outcomes will include the overdose rate according to ideal and actual body weight and to each specific LA, the overall underdose rate, and the time taken to complete these calculations. The app's usability will also be assessed. RESULTS: A sample size of 46 participants will be needed to detect a difference of 10% with a power of 90%. Thus, a target of 50 participants was set to allow for attrition and exclusion criteria. We expect recruitment to begin during the winter of 2023, data analysis in the spring of 2024, and results by the end of 2024. CONCLUSIONS: This study should determine whether LoAD Calc, a mobile health app designed to compute maximum safe LA doses, is safer and more efficient than traditional LA calculation methods. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/53679.

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BACKGROUND: Direct support professionals support people with intellectual and developmental disabilities with essential health and community living needs. Despite an unrelenting workforce shortage crisis, limited evidence-based resources exist for their support. Resilience, or the ability to thrive in the face of challenges, is a target for health care professional wellbeing initiatives. As an "invisible" workforce interspersed throughout various community-based settings, direct support professionals may benefit from resources provided via mobile health apps. OBJECTIVES: To assess direct support professionals' acceptability of and preferences for the design of a mobile health app prototype to support their resilience, DSP Thrive. METHOD: This concept generation and prototype design study employed a two-phase qualitative-descriptive design. Phase 1 assessed direct support professionals' acceptability of and preferences for a mobile health app for direct support professional resilience. Phase 2 elicited feedback on mock-up images of an initial prototype. Data were collected via qualitative interviews (n = 13), and transcripts were analyzed using content analysis. RESULTS: Phase 1: Direct support professionals identified three primary opportunities for an app to support their resilience: learning via educational resources, practicing resilience strategies, and cultivating a peer support network. Based on these findings, the DSP Thrive app prototype was designed with Learn, Practice, and Connect functions. Phase 2: User feedback on walk-throughs of mock-up images indicated initial acceptability of the prototype design with considerations for further development identified. CONCLUSIONS: Engaging direct support professionals in user-centered design of mobile health apps may help to bridge the gap to resilience resources for this essential workforce population.

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BACKGROUND: Reproductive health conditions such as endometriosis, uterine fibroids, and polycystic ovary syndrome (PCOS) affect a large proportion of women and people who menstruate worldwide. Prevalence estimates for these conditions range from 5% to 40% of women of reproductive age. Long diagnostic delays, up to 12 years, are common and contribute to health complications and increased health care costs. Symptom checker apps provide users with information and tools to better understand their symptoms and thus have the potential to reduce the time to diagnosis for reproductive health conditions. OBJECTIVE: This study aimed to evaluate the agreement between clinicians and 3 symptom checkers (developed by Flo Health UK Limited) in assessing symptoms of endometriosis, uterine fibroids, and PCOS using vignettes. We also aimed to present a robust example of vignette case creation, review, and classification in the context of predeployment testing and validation of digital health symptom checker tools. METHODS: Independent general practitioners were recruited to create clinical case vignettes of simulated users for the purpose of testing each condition symptom checker; vignettes created for each condition contained a mixture of condition-positive and condition-negative outcomes. A second panel of general practitioners then reviewed, approved, and modified (if necessary) each vignette. A third group of general practitioners reviewed each vignette case and designated a final classification. Vignettes were then entered into the symptom checkers by a fourth, different group of general practitioners. The outcomes of each symptom checker were then compared with the final classification of each vignette to produce accuracy metrics including percent agreement, sensitivity, specificity, positive predictive value, and negative predictive value. RESULTS: A total of 24 cases were created per condition. Overall, exact matches between the vignette general practitioner classification and the symptom checker outcome were 83% (n=20) for endometriosis, 83% (n=20) for uterine fibroids, and 88% (n=21) for PCOS. For each symptom checker, sensitivity was reported as 81.8% for endometriosis, 84.6% for uterine fibroids, and 100% for PCOS; specificity was reported as 84.6% for endometriosis, 81.8% for uterine fibroids, and 75% for PCOS; positive predictive value was reported as 81.8% for endometriosis, 84.6% for uterine fibroids, 80% for PCOS; and negative predictive value was reported as 84.6% for endometriosis, 81.8% for uterine fibroids, and 100% for PCOS. CONCLUSIONS: The single-condition symptom checkers have high levels of agreement with general practitioner classification for endometriosis, uterine fibroids, and PCOS. Given long delays in diagnosis for many reproductive health conditions, which lead to increased medical costs and potential health complications for individuals and health care providers, innovative health apps and symptom checkers hold the potential to improve care pathways.

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BACKGROUND: Identifying high-risk individuals is crucial for preventing cardiovascular diseases (CVDs). Currently, risk assessment is mostly performed by physicians. Mobile health apps could help decouple the determination of risk from medical resources by allowing unrestricted self-assessment. The respective test results need to be interpretable for laypersons. OBJECTIVE: Together with a patient organization, we aimed to design a digital risk calculator that allows people to individually assess and optimize their CVD risk. The risk calculator was integrated into the mobile health app HerzFit, which provides the respective background information. METHODS: To cover a broad spectrum of individuals for both primary and secondary prevention, we integrated the respective scores (Framingham 10-year CVD, Systematic Coronary Risk Evaluation 2, Systematic Coronary Risk Evaluation 2 in Older Persons, and Secondary Manifestations Of Arterial Disease) into a single risk calculator that was recalibrated for the German population. In primary prevention, an individual's heart age is estimated, which gives the user an easy-to-understand metric for assessing cardiac health. For secondary prevention, the risk of recurrence was assessed. In addition, a comparison of expected to mean and optimal risk levels was determined. The risk calculator is available free of charge. Data safety is ensured by processing the data locally on the users' smartphones. RESULTS: Offering a risk calculator to the general population requires the use of multiple instruments, as each provides only a limited spectrum in terms of age and risk distribution. The integration of 4 internationally recommended scores allows risk calculation in individuals aged 30 to 90 years with and without CVD. Such integration requires recalibration and harmonization to provide consistent and plausible estimates. In the first 14 months after the launch, the HerzFit calculator was downloaded more than 96,000 times, indicating great demand. Public information campaigns proved effective in publicizing the risk calculator and contributed significantly to download numbers. CONCLUSIONS: The HerzFit calculator provides CVD risk assessment for the general population. The public demonstrated great demand for such a risk calculator as it was downloaded up to 10,000 times per month, depending on campaigns creating awareness for the instrument.

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BACKGROUND: Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits for both patients and health care providers, the adoption of mHealth is low, and only a limited number of studies have examined the intention to download mHealth apps. OBJECTIVE: In this study, we investigated individuals' preferences in the adoption of a health app. METHODS: We conducted a discrete choice experimental study in 3 countries (Spain: n=800, Germany: n=800, and the Netherlands: n=416) with 4 different attributes and levels (ie, price: €1.99 vs €4.99 [a currency exchange rate of €1=US $1.09 is applicable] vs for free, data protection: data protection vs no information, recommendation: patients' association vs doctors, and manufacturer: medical association vs pharmaceutical company). Participants were randomly assigned. For the analyses, we used the conditional logistic model separately for each country. RESULTS: The results showed that price and data protection were considered important factors that significantly increased the probability to download an mHealth app. In general, the source of the recommendation and the manufacturer affected the probability to download the mHealth app less. However, in Germany and the Netherlands, we found that if the app was manufactured by a pharmaceutical company, the probability to download the mHealth app decreased. CONCLUSIONS: mHealth tools are highly promising to reduce health care costs and increase the effectiveness of traditional health interventions and therapies. Improving data protection, reducing costs, and creating sound business models are the major driving forces to increase the adoption of mHealth apps in the future. It is thereby essential to create trustworthy standards for mobile apps, whereby prices, legislation concerning data protection, and health professionals can have a leading role to inform the potential consumers.

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BACKGROUND: Timely collection of patient-reported outcomes (PROs) decreases emergency department visits and hospitalizations and increases survival. However, little is known about the outcome predictivity of unpaid informal caregivers' reporting using similar clinical outcome assessments. OBJECTIVE: The aim of this study is to assess whether caregivers and adults with cancer adhered to a planned schedule for electronically collecting patient-reported outcomes (PROs) and if PROs were associated with future clinical events. METHODS: We developed 2 iPhone apps to collect PROs, one for patients with cancer and another for caregivers. We enrolled 52 patient-caregiver dyads from Kaiser Permanente Northern California in a nonrandomized study. Participants used the apps independently for 4 weeks. Specific clinical events were obtained from the patients' electronic health records up to 6 months following the study. We used logistic and quasi-Poisson regression analyses to test associations between PROs and clinical events. RESULTS: Participants completed 97% (251/260) of the planned Patient-Reported Outcomes Common Terminology Criteria for Adverse Events (PRO-CTCAE) surveys and 98% (254/260) of the Patient-Reported Outcomes Measurement Information System (PROMIS) surveys. PRO-CTCAE surveys completed by caregivers were associated with patients' hospitalizations or emergency department visits, grade 3-4 treatment-related adverse events, dose reductions (P<.05), and hospice referrals (P=.03). PROMIS surveys completed by caregivers were associated with hospice referrals (P=.02). PRO-CTCAE surveys completed by patients were not associated with any clinical events, but their baseline PROMIS surveys were associated with mortality (P=.03), while their antecedent or final PROMIS surveys were associated with all clinical events examined except for total days of treatment breaks. CONCLUSIONS: In this study, caregivers and patients completed PROs using smartphone apps as requested. The association of caregiver PRO-CTCAE surveys with patient clinical events suggests that this is a feasible approach to reducing patient burden in clinical trial data collection and may help provide early information about increasing symptom severity.

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CONTEXT: Adolescents and young adults (AYA) with spina bifida (SB) are more susceptible to obesity due to impaired mobility. There is limited access to physical activity for this population. OBJECTIVE: The primary aim of this study was to evaluate the feasibility of a mobile health app in a weight management program for AYA with SB. This was determined by measuring program adherence, active use of the app (defined as ≥3 uses per week), and user rating of the Pt Pal™ mobile app. Secondary outcomes were changes in BMI, quality of life, and health behavior, and the number of active participants over time. METHODS: Patients from the SB Clinic of a large metropolitan hospital between the ages of 11-21 years and overweight were invited to participate. The program consisted of group nutrition sessions and an individualized exercise plan using a mobile app with coaching. Outcome measures were program adherence, changes in BMI, and validated survey responses. Descriptive statistical analysis was performed. RESULTS: Fifteen participants enrolled, and ten participants completed the program. Five of the ten participants attended the nutrition sessions. The number of active app users declined after the first week. Seventy percent of participants decreased their BMI. Most participants reported the program improved their ability to exercise regularly, eat a healthier diet and feel more self-confident. Peds QL™ psychosocial health domains increased postintervention. The YRBS showed increased physical activity and less sedentary time postintervention. CONCLUSIONS: This mobile app-based weight management program with coaching implemented may not be feasible for adoption in the general population of AYA with SB; however, it was well received by some, and further testing is needed to determine how to improve feasibility. This study provides useful information to guide future programs utilizing digital health and coaching.

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Background: Many individuals with intellectual disability (ID) have a sedentary lifestyle. Few interventions aimed at increasing their level of physical activity (PA) have shown lasting effects. Aim: To assess the feasibility and acceptability of a pilot intervention study using innovative mobile health (mHealth) support systems to encourage PA in individuals with ID. Methods: Nine individuals with ID and a low level of PA, aged 16-36 years, were included in the present convergent triangulation mixed method design. Two mHealth support systems (apps) were developed and tested. PA was measured with a Fitbit smartwatch, accelerometer, the International Physical Activity Questionnaire-Short Form (IPAQ-S), and Goal attainment scaling. Data were collected through online pre-, mid- (4 weeks), and post-intervention (12 weeks) questionnaires and activity trackers. Semi-structured qualitative interviews with participants and/or a family or staff member were held after the 12-week follow-up. Data were analyzed using conventional nonparametric statistics and thematic analyses. Results: The response rate and retention to the trial were 16% and 100%, respectively. Data quality was high, except for missing data from Fitbit activity trackers of approximately 30% from the 4- and 12-week follow-up stages. The feasibility challenges with activity trackers include rashes, size, non-acceptance, and loss of motivation. Participants and family members/staff reported interest in the study theme and were pleased with the data collection method. All but one participant achieved their PA goals. Most participants reported being satisfied with the apps as they were enjoyable or provided a reminder for performing physical and other activities. Social support for PA among family members also increased. However, app support from staff and family members was needed, and apps were not used regularly. Two of nine participants (22%) had increased their PA measured as steps per day with Fitbit at the 12-week follow-up. Conclusions: The acceptability and feasibility of using tailored mobile applications in natural settings to increase PA among adults with ID are promising. This study aligns with previous studies in showing the challenges to increasing PA, which requires the inclusion of family members, staff, and stakeholders. The intervention requires modifications before a randomized controlled trial can be conducted.

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BACKGROUND: Conversational user interfaces, or chatbots, are becoming more popular in the realm of digital health and well-being. While many studies focus on measuring the cause or effect of a digital intervention on people's health and well-being (outcomes), there is a need to understand how users really engage and use a digital intervention in the real world. OBJECTIVE: In this study, we examine the user logs of a mental well-being chatbot called ChatPal, which is based on the concept of positive psychology. The aim of this research is to analyze the log data from the chatbot to provide insight into usage patterns, the different types of users using clustering, and associations between the usage of the app's features. METHODS: Log data from ChatPal was analyzed to explore usage. A number of user characteristics including user tenure, unique days, mood logs recorded, conversations accessed, and total number of interactions were used with k-means clustering to identify user archetypes. Association rule mining was used to explore links between conversations. RESULTS: ChatPal log data revealed 579 individuals older than 18 years used the app with most users being female (n=387, 67%). User interactions peaked around breakfast, lunchtime, and early evening. Clustering revealed 3 groups including "abandoning users" (n=473), "sporadic users" (n=93), and "frequent transient users" (n=13). Each cluster had distinct usage characteristics, and the features were significantly different (P<.001) across each group. While all conversations within the chatbot were accessed at least once by users, the "treat yourself like a friend" conversation was the most popular, which was accessed by 29% (n=168) of users. However, only 11.7% (n=68) of users repeated this exercise more than once. Analysis of transitions between conversations revealed strong links between "treat yourself like a friend," "soothing touch," and "thoughts diary" among others. Association rule mining confirmed these 3 conversations as having the strongest linkages and suggested other associations between the co-use of chatbot features. CONCLUSIONS: This study has provided insight into the types of people using the ChatPal chatbot, patterns of use, and associations between the usage of the app's features, which can be used to further develop the app by considering the features most accessed by users.

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Objective: This study aimed to design, develop, assess and refine the EMPOWER-SUSTAIN Self-Management Mobile App© among primary care physicians (PCP) and patients with metabolic syndrome (MetS) in primary care. Methodology: Using the software-development-life-cycle (SDLC) iterative model, storyboard and wireframe were drafted; and a mock prototype was designed to illustrate the content and function graphically. Subsequently, a working prototype was developed. Qualitative studies using the 'think-aloud' and cognitive-task-analysis methods were conducted for the utility and usability testing. Topic guide was based on the 10-Nielsen's-Heuristic-Principles. Utility testing was conducted among PCP in which they 'thought-aloud' while performing tasks using the mobile app. Usability testing was conducted among MetS patients after they were given the app for 3 weeks. They 'thought-aloud' while performing tasks using the app. Interviews were audio- and video-recorded, and transcribed verbatim. Thematic content analysis was performed. Result: Seven PCP and nine patients participated in the utility and usability testing, respectively. Six themes (efficiency of use, user control and freedom, appearance and aesthetic features, clinical content, error prevention, and help and documentation) emerged. PCP found the mobile app attractive and relevant sections were easy to find. They suggested adding 'zoom/swipe' functions and some parts needed bigger fonts. Patients commented that the app was user-friendly, has nice interface, and straightforward language. It helped them understand their health better. Based on these findings, the mobile app was refined. Conclusion: This app was produced using a robust SDLC method to increase users' satisfaction and sustainability of its use. It could potentially improve self-management behaviour among MetS patients in primary care.

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BACKGROUND: Being overweight or obese presents a major risk factor for noncommunicable diseases (NCDs) such as cardiovascular disease, diabetes, and musculoskeletal disorders. These problems are preventable and solvable via weight reduction and increased physical activity and exercise. The number of adults who are overweight or affected by obesity has tripled in the last 4 decades. Using mobile health (mHealth) apps can help users with health issues, including reducing their weight by restricting their daily calorie intake, which can be recorded along with other parameters, such as physical activity and exercise. These features could further enhance health and prevent NCDs. ThaiSook, a Thai mHealth app developed by the National Science and Technology Development Agency, aims to promote healthy lifestyles and reduce the risk behaviors of NCDs. OBJECTIVE: This study aimed to determine whether ThaiSook users were successful in 1-month weight reduction and identify which demographic factors or logging functions were associated with significant weight reduction. METHODS: A secondary data analysis was performed using data collected from the "MED PSU×ThaiSook Healthier Challenge," a month-long challenge to encourage a healthy lifestyle. We enrolled 376 participants to evaluate the study outcomes. The variables, comprising demographic characteristics (ie, sex, generation, group size, and BMI), were classified into 4 groups: normal (18.5-22.9 kg/m2), overweight (23-24.9 kg/m2), obese I (25-29.9 kg/m2), and obese II (BMI ≥30 kg/m2). Logging functions (ie, water, fruit and vegetables, sleep, workout, step, and run) were classified into 2 groups: consistent (≥80%) and inconsistent (<80%) users. Weight reduction was categorized into 3 groups: no weight reduction, slight weight reduction (0%-3%), and significant weight reduction (>3%). RESULTS: Of 376 participants, most were female (n=346, 92%), had normal BMI (n=178, 47.3%), belonged to Generation Y (n=147, 46.7%), and had a medium group size (6-10 members; n=250, 66.5%). The results showed that 56 (14.9%) participants had 1-month significant weight loss, and the median weight reduction of the group was -3.85% (IQR -3.40% to -4.50%). Most participants (264/376, 70.2%) experienced weight loss, with an overall median weight loss of -1.08% (IQR -2.40% to 0.00%). The factors associated with significant weight reduction were consistently logging workouts (adjusted odds ratio [AOR] 1.69, 95% CI 1.07-2.68), being Generation Z (AOR 3.06, 95% CI 1.01-9.33), and being overweight or being obese compared to those with normal BMI (AOR 2.66, 95% CI 1.41-5.07; AOR 1.76, 95% CI 1.08-2.87, respectively). CONCLUSIONS: More than half of the "MED PSU×ThaiSook Healthier Challenge" participants achieved a slight weight reduction, and 14.9% (56/376) of users lost significant weight. Factors including workout logging, being Generation Z, being overweight, and being obese were associated with significant weight reduction.

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BACKGROUND: The prevalence of obesity among Canadian children is rising, partly because of increasingly obesogenic environments that limit opportunities for physical activity and healthy nutrition. Live 5-2-1-0 is a community-based multisectoral childhood obesity prevention initiative that engages stakeholders to promote and support the message of consuming ≥5 servings of vegetables and fruits, having <2 hours of recreational screen time, participating in ≥1 hour of active play, and consuming 0 sugary drinks every day. A Live 5-2-1-0 Toolkit for health care providers (HCPs) was previously developed and piloted in 2 pediatric clinics at British Columbia Children's Hospital. OBJECTIVE: This study aimed to co-create, in partnership with children, parents, and HCPs, a Live 5-2-1-0 mobile app that supports healthy behavior change and could be used as part of the Live 5-2-1-0 Toolkit for HCPs. METHODS: Three focus groups (FGs) were conducted using human-centered design and participatory approaches. In FG 1, children (separately) and parents and HCPs (together) participated in sessions on app conceptualization and design. Researchers and app developers analyzed and interpreted qualitative data from FG 1 in an ideation session, and key themes were subsequently presented separately to parents, children, and HCPs in FG-2 (co-creation) sessions to identify desired app features. Parents and children tested a prototype in FG 3, provided feedback on usability and content, and completed questionnaires. Thematic analysis and descriptive statistics were used for the qualitative and quantitative data, respectively. RESULTS: In total, 14 children (mean age 10.2, SD 1.3 years; 5/14, 36% male; 5/14, 36% White), 12 parents (9/12, 75% aged 40-49 years; 2/12, 17% male; 7/12, 58% White), and 18 HCPs participated; most parents and children (20/26, 77%) participated in ≥2 FGs. Parents wanted an app that empowered children to adopt healthy behaviors using internal motivation and accountability, whereas children described challenge-oriented goals and family-based activities as motivating. Parents and children identified gamification, goal setting, daily steps, family-based rewards, and daily notifications as desired features; HCPs wanted baseline behavior assessments and to track users' behavior change progress. Following prototype testing, parents and children reported ease in completing tasks, with a median score of 7 (IQR 6-7) on a 7-point Likert scale (1=very difficult; 7=very easy). Children liked most suggested rewards (28/37, 76%) and found 79% (76/96) of suggested daily challenges (healthy behavior activities that users complete to achieve their goal) realistic to achieve. Participant suggestions included strategies to maintain users' interest and content that further motivates healthy behavior change. CONCLUSIONS: Co-creating a mobile health app with children, parents, and HCPs was feasible. Stakeholders desired an app that facilitated shared decision-making with children as active agents in behavior change. Future research will involve clinical implementation and assessment of the usability and effectiveness of the Live 5-2-1-0 app.

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PURPOSE: Medical follow-up after bariatric surgery is recommended. However, the compliance was poor. This study aimed to evaluate the feasibility of a smartphone-based fully remote follow-up (FU) program for patients after bariatric surgery. METHODS: In the interventional group, patients were followed up using a smartphone application (app), through which questionnaires were sent regularly. Participants in the control group underwent standard FU at the outpatient clinic every three months. After 12 months, all the participants were evaluated at an outpatient clinic. RESULTS: Between August 2020 and March 2021, 44 and 43 patients in the interventional and control groups, respectively, were included in the analysis after three patients were lost to FU, and three withdrew their informed consent because they wished for more personal contact with medical caregivers. After 12 months, total weight loss (TWL), %TWL, and percentage of excess weight loss (%EWL) did not differ between groups. There were no significant differences in the complication rates, including surgical complications, malnutrition, and micronutrition deficiency. The parameters of bioelectrical impedance analysis and quality of life did not differ between the groups. Vitamins and minerals in serum were similar in both groups except for calcium, which was significantly higher in the interventional group (2.52 mmol/L vs. 2.35 mmol/L, p = 0.038). CONCLUSION: Fully remote FU with a smartphone application is at least as effective as traditional in-person FU in an outpatient clinic after bariatric surgery. Through remote FU, patients can save time and medical professionals may have more resources for patients with more severe problems.

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BACKGROUND: The success rate of tuberculosis (TB) treatment in Malaysia remains below the recommended World Health Organization target of 90% despite the implementation of directly observed therapy, short-course, a physical drug monitoring system, since 1994. With increasing numbers of patients with TB in Malaysia defaulting on treatment, exploring another method to improve TB treatment adherence is vital. The use of gamification and real-time elements via video-observed therapies in mobile apps is one such method expected to induce motivation toward TB treatment adherence. OBJECTIVE: This study aimed to document the process of designing, developing, and validating the gamification, motivation, and real-time elements in the Gamified Real-time Video Observed Therapies (GRVOTS) mobile app. METHODS: The modified nominal group technique via a panel of 11 experts was used to validate the presence of the gamification and motivation elements inside the app, which were assessed based on the percentage of agreement among the experts. RESULTS: The GRVOTS mobile app, which can be used by patients, supervisors, and administrators, was successfully developed. For validation purposes, the gamification and motivation features of the app were validated as they achieved a total mean percentage of agreement of 97.95% (SD 2.51%), which was significantly higher than the minimum agreement score of 70% (P<.001). Further, each component of gamification, motivation, and technology was also rated at 70% or more. Among the gamification elements, fun received the lowest scores, possibly because the nature of serious games does not prioritize the fun element and because the perception of fun varies by personality. The least popular element in motivation was relatedness, as stigma and discrimination hinder interaction features, such as leaderboards and chats, in the mobile app. CONCLUSIONS: It has been validated that the GRVOTS mobile app contains gamification and motivation elements, which are intended to encourage medication adherence to TB treatment.

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BACKGROUND: Mobile health (mHealth) technology holds great promise as an easily accessible and effective solution to improve population health at scale. Despite the abundance of mHealth offerings, only a minority are grounded in evidence-based practice, whereas even fewer have line of sight into population-level health care spending, limiting the clinical utility of such tools. OBJECTIVE: This study aimed to explore the influence of a health plan-sponsored, wearable-based, and reward-driven digital health intervention (DHI) on health care spending over 1 year. The DHI was delivered through a smartphone-based mHealth app available only to members of a large commercial health plan and leveraged a combination of behavioral economics, user-generated sensor data from the connected wearable device, and claims history to create personalized, evidence-based recommendations for each user. METHODS: This study deployed a propensity score-matched, 2-group, and pre-post observational design. Adults (≥18 years of age) enrolled in a large, national commercial health plan and self-enlisted in the DHI for ≥7 months were allocated to the intervention group (n=56,816). Members who were eligible for the DHI but did not enlist were propensity score-matched to the comparison group (n=56,816). Average (and relative change from baseline) medical and pharmacy spending per user per month was computed for each member of the intervention and comparison groups during the pre- (ie, 12 months) and postenlistment (ie, 7-12 months) periods using claims data. RESULTS: Baseline characteristics and medical spending were similar between groups (P=.89). On average, the total included sample population (N=113,632) consisted of young to middle-age (mean age 38.81 years), mostly White (n=55,562, 48.90%), male (n=46,731, 41.12%) and female (n=66,482, 58.51%) participants. Compared to a propensity score-matched cohort, DHI users demonstrated approximately US $10 per user per month lower average medical spending (P=.02) with a concomitant increase in preventive care activities and decrease in nonemergent emergency department admissions. These savings translated to approximately US $6.8 million in avoidable health care costs over the course of 1 year. CONCLUSIONS: This employer-sponsored, digital health engagement program has a high likelihood for return on investment within 1 year owing to clinically meaningful changes in health-seeking behaviors and downstream medical cost savings. Future research should aim to elucidate health behavior-related mechanisms in support of these findings and continue to explore novel strategies to ensure equitable access of DHIs to underserved populations that stand to benefit the most.

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BACKGROUND: SMS text messaging and other mobile health (mHealth) interventions may improve knowledge transfer, strengthen access to social support (SS), and promote positive health behaviors among women in the perinatal period. However, few mHealth apps have been taken to scale in sub-Saharan Africa. OBJECTIVE: We evaluated the feasibility, acceptability, and preliminary efficacy of a novel, mHealth-based, and patient-centered messaging app designed using behavioral science frameworks to promote maternity service use among pregnant women in Uganda. METHODS: We performed a pilot randomized controlled trial between August 2020 and May 2021 at a referral hospital in Southwestern Uganda. We included 120 adult pregnant women enrolled in a 1:1:1 ratio to receive routine antenatal care (ANC; control), scheduled SMS text or audio messages from a novel messaging prototype (scheduled messaging [SM]), and SM plus SMS text messaging reminders to 2 participant-identified social supporters (SS). Participants completed face-to-face surveys at enrollment and in the postpartum period. The primary outcomes were feasibility and acceptability of the messaging prototype. Other outcomes included ANC attendance, skilled delivery, and SS. We conducted qualitative exit interviews with 15 women from each intervention arm to explore the intervention mechanisms. Quantitative and qualitative data were analyzed using STATA and NVivo, respectively. RESULTS: More than 85% and 75% of participants received ≥85% of the intended SMS text messages or voice calls, respectively. More than 85% of the intended messages were received within 1 hour of the expected time; 18% (7/40) of women experienced network issues for both intervention groups. Over 90% (36/40) of the intervention participants found this app useful, easy to use, engaging, and compatible and strongly recommended it to others; 70% (28/40), 78% (31/40), and 98% (39/40; P=.04) of women in the control, SM, and SS arms, respectively, had a skilled delivery. Half (20/40), 83% (33/40), and all (40/40; P=.001) of the women in the control, SM, and SS arms attended ≥4 ANC visits, respectively. Women in the SS arm reported the highest support (median 3.4, IQR 2.8-3.6; P=.02); <20% (8/40; P=.002) missed any scheduled ANC visit owing to lack of transportation. Qualitative data showed that women liked the app; they were able to comprehend ANC and skilled delivery benefits and easily share and discuss tailored information with their significant others, who in turn committed to providing them the needed support to prepare and seek help. CONCLUSIONS: We demonstrated that developing a novel patient-centered and tailored messaging app that leverages SS networks and relationships is a feasible, acceptable, and useful approach to communicate important targeted health-related information and support pregnant women in rural Southwestern Uganda to use available maternity care services. Further evaluation of maternal-fetal outcomes and integration of this intervention into routine care is needed. TRIAL REGISTRATION: ClinicalTrials.gov NCT04313348; https://clinicaltrials.gov/ct2/show/NCT04313348.

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BACKGROUND: Mental health is an increasing concern among vulnerable populations, including college students and veterans. OBJECTIVE: The purpose of this study was to determine if mobile health technology combined with health coaching can better enable a user to self-manage their mental health. METHODS: This study evaluated the mobile app "Biofeedback" that provided health coaching on stress self-management for college student veterans' mental health concerns. Twenty-four college student veterans were recruited from a large public university in Texas during the spring 2020 semester, impacted by COVID-19. Ten participants were assigned to the intervention group where they used the mobile Biofeedback app on their smartphones and smartwatches, and 14 were assigned to the control group without the app; assignment was based on mobile phone compatibility. Both groups participated in one initial lab session where they learned a deep-breathing exercise technique. The intervention group was then asked to use the mobile Biofeedback app during their daily lives and a smartwatch, and the control group was asked to perform the breathing exercises on their own. Both groups filled out Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) self-assessments at 2-week intervals. At the end of the semester, both groups were given an exit interview to provide user experience and perceived benefits of health coaching via the mobile biofeedback app. RESULTS: The deep-breathing exercise in the initial lab session reduced stress in both groups. Over the course of the study, the app recorded 565 coached breathing exercises with a significant decrease (approximately 3 beats per minute) in participants' heart rate during the 6-minute time period immediately after conducting the breathing exercises (Spearman rank correlation coefficient -0.61, P<.001; S=9,816,176). There was no significant difference between the two groups for PHQ-9 and GAD-7 scores over the course of the semester. Exit interview responses indicated that participants perceived that the mobile Biofeedback app improved their health and helped them address stress challenges. All participants reported that the intervention helped them manage their stress better and expressed that health coaching via a mobile device would improve their overall health. CONCLUSIONS: Participants reported a positive perception of the app for their mental health self-management during a stressful semester. Future work should examine long-term effects of the app with a larger sample size balanced between male and female participants, randomized participant allocation, real-time detection of mental health symptoms, and additional features of the app.