A self-help mobile messaging intervention to improve subthreshold depressive symptoms among older adults in a socioeconomically deprived region of Brazil (PRODIGITAL): a pragmatic, two-arm randomised controlled trial.

Background: Subthreshold depression is a risk factor for major depression and is associated with increased morbidity and mortality, especially in older adults. There is emerging evidence that digital interventions, including self-help interventions, may reduce depressive symptoms. We aimed to evaluate the effectiveness of a mobile messaging intervention at reducing subthreshold depressive symptoms among older adults in Brazil. Methods: PRODIGITAL was a single blind, two-arm, individually randomised controlled trial conducted in 46 primary care clinics in the city of Guarulhos, Brazil. Individuals aged 60+ years were contacted by phone following a randomly ordered list for a screening assessment. Those who presented with anhedonia and/or depressed mood (Patient Health Questionnaire (PHQ)-2≥1), and who subsequently scored between 5 and 9 on the PHQ-9 were invited to participate. The intervention arm received the 'Viva Vida' digital self-help intervention consisting of automated multi-media messages sent via WhatsApp. Forty-eight audio and visual messages based on psychoeducation and behavioural activation were automatically delivered over six weeks. The control arm received a single message containing information about depression. The primary outcome was the difference in mean PHQ-9 scores between treatment arms at the three-month follow-up. All primary analyses were performed according to allocated arm with imputed data. The trial is registered with ReBEC, RBR-6c7ghfd. Findings: Participants were recruited between 8 September 2021 and 19 August 2022. Of the 454 participants enrolled, 223 were randomised to the intervention arm, 231 to the control arm. Participants' mean age was 65.3 years (SD 5.0) and 64.0% (n = 292) were female. A total of 385 (84.8%) completed the three-month follow-up assessment; no difference in mean PHQ-9 scores between the treatment arms was observed (adjusted difference: -0.61; 95% CI: -1.75, 0.53; p = 0.29). Interpretation: These results demonstrate that the Viva Vida digital self-help intervention did not help to improve subthreshold depressive symptoms amongst older adults. Further research is needed to understand why this self-help intervention was not effective in this population, and to explore how it might be adapted to achieve this goal. Funding: São Paulo Research Foundation and UK Joint Global Health Trials.

Assessing the Effectiveness of an mHealth Intervention to Support Men Who Have Sex With Men Engaging in Chemsex (Budd): Single-Case and Pre-Post Experimental Design Study.

BACKGROUND: This study focuses on the Budd app, a mobile health intervention designed for gay, bisexual, and other men who have sex with men who participate in chemsex. Chemsex, the use of psychoactive drugs in a sexual context, presents substantial health risks including increased HIV transmission and mental health issues. Addressing these risks requires innovative interventions tailored to the unique needs of this population. OBJECTIVE: This study aims to evaluate the effectiveness of the Budd app in promoting drug harm reduction practices among its users, focusing on knowledge, behavioral intention, risk behavior awareness, and self-efficacy. METHODS: The study used a mixed methods approach, combining a single-case experimental design and a pre-post study. A total of 10 participants from an outpatient clinic were recruited, and each attended the clinic 3 times. During the first visit, participants installed a restricted version of the Budd app, which allowed them to report daily mood and risk behavior after chemsex sessions. Phase A (baseline) lasted at least 2 weeks depending on chemsex participation. In the second visit, participants gained full access to the Budd app, initiating phase B (intervention). Phase B lasted at least 6 weeks, depending on chemsex participation, with identical data input as phase A. Participants completed pre- and postintervention surveys assessing behavioral determinants during the first and third visit. RESULTS: The study observed an increased knowledge about chemsex substances postintervention, with a mean percentage improvement in knowledge scores of 20.59% (SD 13.3%) among participants. Behavioral intention and self-efficacy showed mixed results, with some participants improving while others experienced a decrease. There was also a variable impact on awareness of risk behavior, with half of the participants reporting a decrease postintervention. Despite these mixed results, the app was generally well-received, with participants engaging with the app's features an average of 50 times during the study. CONCLUSIONS: The Budd app showed effectiveness in enhancing knowledge about chemsex substances among gay, bisexual, and other men who have sex with men. However, its impact on safe dosing behavior, behavioral intention, self-efficacy, and risk behavior awareness was inconsistent. These findings suggest that while educational interventions can increase knowledge, translating this into behavioral change is more complex and may require more participants, a longer follow-up period, and additional strategies and support mechanisms.

Use of AI in Mental Health Care: Community and Mental Health Professionals Survey.

Background: Artificial intelligence (AI) has been increasingly recognized as a potential solution to address mental health service challenges by automating tasks and providing new forms of support. Objective: This study is the first in a series which aims to estimate the current rates of AI technology use as well as perceived benefits, harms, and risks experienced by community members (CMs) and mental health professionals (MHPs). Methods: This study involved 2 web-based surveys conducted in Australia. The surveys collected data on demographics, technology comfort, attitudes toward AI, specific AI use cases, and experiences of benefits and harms from AI use. Descriptive statistics were calculated, and thematic analysis of open-ended responses were conducted. Results: The final sample consisted of 107 CMs and 86 MHPs. General attitudes toward AI varied, with CMs reporting neutral and MHPs reporting more positive attitudes. Regarding AI usage, 28% (30/108) of CMs used AI, primarily for quick support (18/30, 60%) and as a personal therapist (14/30, 47%). Among MHPs, 43% (37/86) used AI; mostly for research (24/37, 65%) and report writing (20/37, 54%). While the majority found AI to be generally beneficial (23/30, 77% of CMs and 34/37, 92% of MHPs), specific harms and concerns were experienced by 47% (14/30) of CMs and 51% (19/37) of MHPs. There was an equal mix of positive and negative sentiment toward the future of AI in mental health care in open feedback. Conclusions: Commercial AI tools are increasingly being used by CMs and MHPs. Respondents believe AI will offer future advantages for mental health care in terms of accessibility, cost reduction, personalization, and work efficiency. However, they were equally concerned about reducing human connection, ethics, privacy and regulation, medical errors, potential for misuse, and data security. Despite the immense potential, integration into mental health systems must be approached with caution, addressing legal and ethical concerns while developing safeguards to mitigate potential harms. Future surveys are planned to track use and acceptability of AI and associated issues over time.

Efficacy of WeChat-Based Digital Intervention Versus Metformin in Women With Polycystic Ovary Syndrome: Randomized Controlled Trial.

BACKGROUND: The first-line treatment for polycystic ovary syndrome (PCOS) is lifestyle modification. However, it is currently unknown whether digital medicine can assist patients with PCOS in maintaining a healthy lifestyle while alleviating PCOS symptoms. OBJECTIVE: This study aims to evaluate the efficacy of WeChat-based digital intervention versus metformin treatment in women with PCOS and insulin resistance. METHODS: A total of 80 women with PCOS and insulin resistance were recruited from an endocrinology clinic and randomly assigned to receive either a WeChat-based digital intervention (n=40, 50%) or metformin (n=40, 50%) for 12 weeks. The WeChat-based digital intervention consisted of 3 modules; a coach assisted the patients in using the intervention. The primary outcome was the change in a homeostatic model assessment for insulin resistance. At baseline and after the 12-week intervention, anthropometric parameters, menstruation frequency, sex hormone levels, metabolic factors, and body fat distribution were measured in the clinic. Furthermore, self-assessed web-based questionnaires on diet, exercise, sleep, anxiety, and depression were obtained. RESULTS: A total of 72 participants completed the follow-up (for a 90% follow-up rate), including 35 of 40 (88%) participants from the digital intervention group and 37 of 40 (93%) participants from the metformin group. The homeostatic model assessment for insulin resistance in the digital intervention group was significantly improved after 12 weeks of treatment with a mean change of -0.93 (95% CI -1.64 to -0.23), but no statistical difference was observed between the groups (least squares mean difference -0.20; 95% CI -0.98 to 0.58; P=.62). Both digital intervention and metformin treatment significantly improved menstruation frequency (digital intervention: P<.001; metformin: P<.001) and reduced body weight (digital intervention: P<.001; metformin: P<.001) and total fat mass (digital intervention: P<.001; metformin: P<.001). Furthermore, the digital intervention had a significant advantage over metformin in improving waist circumference (least squares mean difference -1.84; 95% CI -3.44 to -0.24; P=.03), waist-to-hip ratio (least squares mean difference -0.02; 95% CI -0.03 to 0.00; P=.03), total fat mass (least squares mean difference -1.59; 95% CI -2.88 to -0.30; P=.02), and dehydroepiandrosterone sulfate (least squares mean difference -69.73; 95% CI -129.70 to -9.75; P=.02). In terms of safety, the main adverse events were sensations of hunger in the digital intervention group (2/40, 5%) and gastrointestinal adverse events in the metformin group (12/40, 30%). CONCLUSIONS: Our data suggest that digital intervention is an effective treatment option for patients with PCOS, with an efficacy comparable to that of metformin, and that it can also alleviate the negative effects of medications and make it easier and more efficient to adhere to lifestyle treatments. WeChat-based digital interventions have the potential to provide a new path for the improvement and health of women with PCOS in China. TRIAL REGISTRATION: ClinicalTrials.gov NCT05386706; https://clinicaltrials.gov/study/NCT05386706.

Feasibility and Engagement of a Mobile App Preparation Program (Kwit) for Smoking Cessation in an Ecological Context: Quantitative Study.

BACKGROUND: Mobile health apps can facilitate access to effective treatment and therapeutic information services. However, the real-world effectiveness of mobile apps for smoking cessation and their potential impact in everyday settings remain unclear. OBJECTIVE: In an ecological context, this study aimed to estimate the engagement rate of a mobile app-based smoking cessation preparation program and its potential impact on users' willingness, ability, and readiness to quit smoking. METHODS: A total of 2331 "organic users" (ie, users who discover and install a mobile app on their own, without any prompts) chose 1 of 2 program versions of the mobile app (Kwit): the basic version or the premium version. Both versions were identical in design, with 4 more evidence-based content items and strategies in the premium version. Outcomes were analyzed based on automated data registered in the app (engagement rate, motivation to quit, motivation type, motivation levels, and satisfaction level). Mann-Whitney and χ2 tests were used to compare the results of both groups. RESULTS: As expected, in the ecological context, a high dropout rate was observed at different moments. A significant difference was observed between the 2 versions (n=2331; χ21=5.4; P=.02), with a proportionally higher engagement rate in the premium version (premium=4.7% vs basic=2%). Likewise, differences were also observed between the 2 groups in terms of reasons to quit (n=2331; χ24=19; P≤.001; V=0.08), motivation type (n=2331; χ27=14.7; P=.04), and motivation level. Users of the app's premium version more frequently reported "well-being" (23.3% vs 17.9%) and "planning a pregnancy" (7.4% vs 4.4%) as their primary reasons for quitting smoking compared to those with the basic version. Moreover, they reported being more likely to be driven in the smoking cessation process by intrinsic motivation (premium=28% vs basic=20.4%), as well as feeling significantly more willing (z score=156,055; P≤.001; Cohen d=0.15), able (z score=172,905; P=.04; Cohen d=0.09), and ready (z score=166,390; P=.005; Cohen d=0.12) to stop smoking than users who had the basic version before completion of the preparation program. Among participants who finished each version of the program (premium: 9/189, 4.8%; basic: 47/2142, 2.19%), significant improvements in motivation levels were observed in both groups, although in different areas for each group (willingness levels for the premium group and ability for the basic group). CONCLUSIONS: These results suggest that even in ecological contexts where engagement rates are meager, the Kwit preparation program can address ambivalence by increasing willingness to change, self-confidence, and readiness to quit among its users, especially those who feel less able to do so. Further development and evaluations are needed to better understand determinants for regular mobile health apps.

Identifying Marijuana Use Behaviors Among Youth Experiencing Homelessness Using a Machine Learning-Based Framework: Development and Evaluation Study.

BACKGROUND: Youth experiencing homelessness face substance use problems disproportionately compared to other youth. A study found that 69% of youth experiencing homelessness meet the criteria for dependence on at least 1 substance, compared to 1.8% for all US adolescents. In addition, they experience major structural and social inequalities, which further undermine their ability to receive the care they need. OBJECTIVE: The goal of this study was to develop a machine learning-based framework that uses the social media content (posts and interactions) of youth experiencing homelessness to predict their substance use behaviors (ie, the probability of using marijuana). With this framework, social workers and care providers can identify and reach out to youth experiencing homelessness who are at a higher risk of substance use. METHODS: We recruited 133 young people experiencing homelessness at a nonprofit organization located in a city in the western United States. After obtaining their consent, we collected the participants' social media conversations for the past year before they were recruited, and we asked the participants to complete a survey on their demographic information, health conditions, sexual behaviors, and substance use behaviors. Building on the social sharing of emotions theory and social support theory, we identified important features that can potentially predict substance use. Then, we used natural language processing techniques to extract such features from social media conversations and reactions and built a series of machine learning models to predict participants' marijuana use. RESULTS: We evaluated our models based on their predictive performance as well as their conformity with measures of fairness. Without predictive features from survey information, which may introduce sex and racial biases, our machine learning models can reach an area under the curve of 0.72 and an accuracy of 0.81 using only social media data when predicting marijuana use. We also evaluated the false-positive rate for each sex and age segment. CONCLUSIONS: We showed that textual interactions among youth experiencing homelessness and their friends on social media can serve as a powerful resource to predict their substance use. The framework we developed allows care providers to allocate resources efficiently to youth experiencing homelessness in the greatest need while costing minimal overhead. It can be extended to analyze and predict other health-related behaviors and conditions observed in this vulnerable community.

Efficacy of a Standalone Smartphone Application to Treat Postnatal Depression: A Randomized Controlled Trial.

INTRODUCTION: Smartphone app interventions based on cognitive-behavioral therapy (CBT) are promising scalable alternatives for treating mental disorders, but the evidence of their efficacy for postpartum depression is limited. We assessed the efficacy of Motherly, a standalone CBT-based smartphone app, in reducing symptoms of postpartum depression. METHODS: Women aged 18-40 with symptoms of postpartum depression were randomized either to intervention (Motherly app) or active control (COMVC app). The primary outcome was symptoms of depression measured by the Edinburgh Postnatal Depression Scale (EPDS) at post-treatment. Secondary outcomes were anxiety symptoms, parental stress, quality of sleep, behavioral activation, availability of response-contingent positive reinforcement, and clinical improvement at post-treatment and 1-month follow-up. Exploratory analyses were performed to investigate if app engagement was associated with treatment response. RESULTS: From November 2021 to August 2022, 1,751 women volunteered, of which 264 were randomized, and 215 provided primary outcome data. No statistically significant differences were found between groups at post-treatment: intervention: mean (SD): 12.75 (5.52); active control: 13.28 (5.32); p = 0.604. There was a statistically significant effect of the intervention on some of the secondary outcomes. Exploratory analyses suggest a dose-response relationship between Motherly app engagement and outcomes. CONCLUSION: Our standalone app intervention did not significantly reduce postnatal depression symptoms when compared to active control. Exploratory findings suggest that negative findings might be associated with insufficient app engagement. Consistent with current literature, our findings suggest that standalone app interventions for postpartum depression are not ready to be implemented in clinical practice.

Digital Health Innovations for Screening and Mitigating Mental Health Impacts of Adverse Childhood Experiences: Narrative Review.

Background: Exposures to both negative and positive experiences in childhood have proven to influence cardiovascular, immune, metabolic, and neurologic function throughout an individual's life. As such, adverse childhood experiences (ACEs) could have severe consequences on health and well-being into adulthood. Objective: This study presents a narrative review of the use of digital health technologies (DHTs) and artificial intelligence to screen and mitigate risks and mental health consequences associated with ACEs among children and youth. Methods: Several databases were searched for studies published from August 2017 to August 2022. Selected studies (1) explored the relationship between digital health interventions and mitigation of negative health outcomes associated with mental health in childhood and adolescence and (2) examined prevention of ACE occurrence associated with mental illness in childhood and adolescence. A total of 18 search papers were selected, according to our inclusion and exclusion criteria, to evaluate and identify means by which existing digital solutions may be useful in mitigating the mental health consequences associated with the occurrence of ACEs in childhood and adolescence and preventing ACE occurrence due to mental health consequences. We also highlighted a few knowledge gaps or barriers to DHT implementation and usability. Results: Findings from the search suggest that the incorporation of DHTs, if implemented successfully, has the potential to improve the quality of related care provisions for the management of mental health consequences of adverse or traumatic events in childhood, including posttraumatic stress disorder, suicidal behavior or ideation, anxiety or depression, and attention-deficit/hyperactivity disorder. Conclusions: The use of DHTs, machine learning tools, natural learning processing, and artificial intelligence can positively help in mitigating ACEs and associated risk factors. Under proper legal regulations, security, privacy, and confidentiality assurances, digital technologies could also assist in promoting positive childhood experiences in children and young adults, bolstering resilience, and providing reliable public health resources to serve populations in need.

Effectiveness of specialist nurse-led WeChat mini program management for disease control in asthma: A randomized controlled study.

BACKGROUND: Asthma is a common chronic respiratory disease in childhood, requiring effective management strategies. PURPOSE: This study aims to evaluate the effectiveness of a nurse-led WeChat Mini Program in managing asthma among children aged 6 to 11 years. METHODS: This randomized controlled trial adhered to the CONSORT checklist and was conducted at a tertiary hospital in China from January 2023 to August 2023. One hundred and eight children with asthma were randomly assigned to two groups, and 81 children completed the 6-month follow-up. All participants received asthma management from specialist nurses, including routine treatments such as inhaled corticosteroids. The experimental group also utilized the WeChat Mini Program for asthma management. Both groups underwent follow-up assessments at 3 and 6 months post-enrollment, which included the Childhood Asthma Control Test (C-ACT), asthma control levels, frequency of exacerbations, and lung function. RESULTS: At 3 and 6 months, the experimental group showed significantly higher C-ACT scores and a lower exacerbation frequency compared to the control group (p < 0.05). While Peak Expiratory Flow improved, Forced Expiratory Volume in 1 Second Percentage Predicted (FEV1%) and FEV1/FVC did not change significantly. CONCLUSIONS: The WeChat Mini Program significantly improved asthma control and reduced exacerbations but did not substantially enhance all lung function parameters. Further research is required to confirm its long-term effects. APPLICATION TO PRACTICE: Incorporating a specialist nurse-led digital management tool, such as the WeChat Mini Program, into standard pediatric asthma care may offer an effective management strategy.

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

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

Inclusion of Individuals With Lived Experiences in the Development of a Digital Intervention for Co-Occurring Depression and Cannabis Use: Mixed Methods Investigation.

BACKGROUND: Existing interventions for co-occurring depression and cannabis use often do not treat both disorders simultaneously and can result in higher rates of symptom relapse. Traditional in-person interventions are often difficult to obtain due to financial and time limitations, which may further prevent individuals with co-occurring depression and cannabis use from receiving adequate treatment. Digital interventions can increase the scalability and accessibility for these individuals, but few digital interventions exist to treat both disorders simultaneously. Targeting transdiagnostic processes of these disorders with a digital intervention-specifically positive valence system dysfunction-may yield improved access and outcomes. OBJECTIVE: Recent research has highlighted a need for the inclusion of individuals with lived experiences to assist in the co-design of interventions to enhance scalability and relevance of an intervention. Thus, the purpose of this study is to describe the process of eliciting feedback from individuals with elevated depressed symptoms and cannabis use and co-designing a digital intervention, Amplification of Positivity-Cannabis Use Disorder (AMP-C), focused on improving positive valence system dysfunction in these disorders. METHODS: Ten individuals who endorsed moderate to severe depressive symptoms and regular cannabis use (2-3×/week) were recruited online via Meta ads. Using a mixed methods approach, participants completed a 1-hour mixed methods interview over Zoom (Zoom Technologies Inc) where they gave their feedback and suggestions for the development of a mental health app, based on an existing treatment targeting positive valence system dysfunction, for depressive symptoms and cannabis use. The qualitative approach allowed for a broader investigation of participants' wants and needs regarding the engagement and scalability of AMP-C, and the quantitative approach allowed for specific ratings of intervention components to be potentially included. RESULTS: Participants perceived the 13 different components of AMP-C as overall helpful (mean 3.9-4.4, SD 0.5-1.1) and interesting (mean 4.0-4.9, SD 0.3-1.1) on a scale from 1 (not at all) to 5 (extremely). They gave qualitative feedback for increasing engagement in the app, including adding a social component, using notifications, and being able to track their symptoms and progress over time. CONCLUSIONS: This study highlights the importance of including individuals with lived experiences in the development of interventions, including digital interventions. This inclusion resulted in valuable feedback and suggestions for improving the proposed digital intervention targeting the positive valence system, AMP-C, to better match the wants and needs of individuals with depressive symptoms and cannabis use.

Touching Technology-Parents' Experiences of Remote Consultations for Children With Severe Congenital Cardiac Conditions: Quasi-Experimental Cohort Study.

Background: Remote consultations (RCs) using videoconferencing was recommended by the General Medical Council as the method for clinicians to provide patient consultations during the COVID-19 pandemic. Facilitating this while providing high-quality care depends on the usability and acceptability of the technology. Objective: This project aimed to investigate parents' experiences of using videoconferencing technology for real-time RCs with children who had congenital heart defects during the COVID-19 pandemic lockdown. Methods: This study's design was quasi-experimental and was underpinned by the Unified Theory of Acceptance and Use of Technology model that seeks to explain and predict an individual's intention to use a technology. Parents were informed of this study by the medical team, posters were made available in the wards and clinics, and leaflets were left for browsing. Clinician screening of potential participants led to the identification of 33 children and parents who were enrolled on this study. The intervention was a web-based RC by medical staff using a secure, interactive videoconferencing platform (Pexip). Each child and their mother or father received 8 RCs with the same specialist doctor or nurse. Measurements were taken using web-based questionnaires pre and post consultation at the first, middle, and last events; questions were focused on the acceptability, usability, and clinical applicability of RCs. Parents' experiences were explored using recorded interviews and analyzed thematically. Results: In total, 29 children aged 4-1052 (mean 95, SD 191.14) days completed the project, receiving a total of 189 RCs as part of their routine care. Parents' prior experience of consultation via videoconference was low; however, as time progressed, their use and acceptance of the technology increased. The intervention was warmly received by all parents who found the face-to-face component particularly useful for discussion with their child's medical team. Furthermore, parents noted the savings on time, money, and childcare. Conclusions: While in-person consultations are considered the gold standard of patient care, increasing pressures on health services and staff reduce availability. Given the ease of access and additional benefits experienced by parents and their children, it is proposed that hybrid models of consultation and care provision are equal, if not superior, to in-person consultations in the management of children with severe congenital heart defects while reducing costs and pressure on the health service and parents.

Using the Person-Based Approach to Co-Create and Optimize an App-Based Intervention to Support Better Sleep for Adolescents in the United Kingdom: Mixed Methods Study.

BACKGROUND: Poor sleep is a common problem in adolescents aged 14 to 18 years. Difficulties with sleep have been found to have a bidirectional link to mental health problems. OBJECTIVE: This new research sought to involve young people in the co-creation of a new app, particularly those from underserved communities. The Sleep Solved app uses science-based advice to improve sleep-related behaviors and well-being. The app was developed using the person-based approach, underpinned by the social cognitive theory and the social-ecological model of sleep health. METHODS: Young people (aged 14-18 y) were recruited from across the United Kingdom to contribute to patient and public involvement (PPI) activities. In partnership with our peer researcher (MHJ), we used a multitude of methods to engage with PPI contributors, including web-based workshops, surveys, think-aloud interviews, focus groups, and app beta testing. RESULTS: A total of 85 young people provided PPI feedback: 54 (64%) young women, 27 (32%) young men, 2 (2%) genderfluid people, 1 (1%) nonbinary person, and 1 (1%) who reported "prefer not to say." Their levels of deprivation ranged from among the 40% most deprived to the 20% least deprived areas. Most had self-identified sleep problems, ranging from 2 to 3 times per week to >4 times per week. Attitudes toward the app were positive, with praise for its usability and use of science-based yet accessible information. Think-aloud interviews and a focus group identified a range of elements that may influence the use of the app, including the need to pay attention to language choices and readability. User experiences in the form of narrated audio clips were used to normalize sleep problems and provide examples of how the app had helped these users. CONCLUSIONS: Young people were interested in using an app to better support their sleep and mental health. The app was co-created with strong links to theory- and evidence-based sleep hygiene behaviors. Future work to establish the effectiveness of the intervention, perhaps in a randomized controlled trial, would provide support for potential UK-wide rollout.

Outcomes of Providing Children Aged 7-12 Years With Access to Evidence-Based Anxiety Treatment Via a Standalone Digital Intervention Using Immersive Gaming Technology: Real-World Evaluation.

Background: Anxiety disorders are among the most common mental health conditions in childhood, but most children with anxiety disorders do not access evidence-based interventions. The delivery of therapeutic interventions via digital technologies has been proposed to significantly increase timely access to evidence-based treatment. Lumi Nova (BfB Labs Limited) is a digital therapeutic intervention designed to deliver evidence-based anxiety treatment for those aged 7-12 years through a mobile app incorporating immersive gaming technology. Objective: We aimed to evaluate the real-world impact of providing access to Lumi Nova through UK National Health Service-funded mental health services. Methods: We analyzed precollected anonymized data routinely captured through the implementation of Lumi Nova from children aged 7-12 years, who lived in the United Kingdom and had the opportunity to use the intervention for at least 1 week over an 18-month period. Engagement indices included whether the game key was activated, number of unique sessions, time spent engaging, and number of "challenges" completed. Clinical outcomes were assessed using the Goal-Based Outcomes measure and Child Outcome Rating Scale. Demographic data were analyzed to assess the health equality implications of Lumi Nova. Results: Of 1029 eligible families invited to use Lumi Nova, 644 (62.5%) activated their game key, of whom 374 (58.1%) completed at least one in-game graded exposure challenge. The median number of unique sessions was 6 (IQR 3-12) and the median time spent engaging with the intervention was 42 (IQR 15-79) minutes. For the subset of young people with paired outcomes, there were statistically significant small to medium improvements in goal-based outcome scores (n=224; t223=5.78, P<.001; d=0.37, 95% CI 0.25-0.52) and Child Outcome Rating Scale scores (n=123; t122=5.10, P<.001; d=0.46, 95% CI 0.27-0.65) between the first and last data points. Two in 5 young people's scores reflected a change that would be considered reliable. Analysis of demographic characteristics tentatively suggested that children from ethnic minority backgrounds and those living in the most deprived neighbourhoods may be less likely to access Lumi Nova, but children from socioeconomically deprived areas were more likely to successfully complete a challenge once they accessed the intervention (P=.02). However, the level of missing data and small number of children in some demographic groups limited meaningful statistical comparisons. Conclusions: This study provides initial evidence that Lumi Nova may be associated with improved outcomes for those aged 7-12 years seeking anxiety treatment in real-world settings. However, the lack of a control comparator group and information about concurrent treatments accessed by the young people, in addition to substantial attrition, limited the analysis that could be conducted and confidence in the conclusions drawn.

Design of a Temporally Augmented Text Messaging Bot to Improve Adolescents' Physical Activity and Engagement: Proof-of-Concept Study.

BACKGROUND: Digital interventions hold promise for improving physical activity in adolescents. However, a lack of empirical decision points (eg, timing of intervention prompts) is an evidence gap in the optimization of digital physical activity interventions. OBJECTIVE: The study examined the feasibility and acceptability, as well as the technical and functional reliability, of and participant engagement with a digital intervention that aligned its decision points to occur during times when adolescents typically exercise. This study also explored the impact of the intervention on adolescents' moderate to vigorous physical activity (MVPA) levels. Consistent with the Obesity-Related Behavioral Interventions Trials (ORBIT) model, the primary goal of the study was to identify opportunities to refine the intervention for preparation for future trials. METHODS: Ten adolescents completed a 7-day baseline monitoring period and Temporally Augmented Goal Setting (TAGS), a 20-day digital physical activity intervention that included a midday self-monitoring message that occurred when adolescents typically start to exercise (3 PM). Participants wore an accelerometer to measure their MVPA during the intervention. Participants completed questionnaires about the acceptability of the platform. Rates of recruitment and attrition (feasibility), user and technological errors (reliability), and engagement (average number of text message responses to the midday self-monitoring message) were calculated. The investigation team performed multilevel models to explore the effect of TAGS on MVPA levels from preintervention to intervention. In addition, as exploratory analyses, participants were matched to adolescents who previously completed a similar intervention, Network Underwritten Dynamic Goals Engine (NUDGE), without the midday self-monitoring message, to explore differences in MVPA between interventions. RESULTS: The TAGS intervention was mostly feasible, acceptable, and technically and functionally reliable. Adolescents showed adequate levels of engagement. Preintervention to intervention changes in MVPA were small (approximately a 2-minute change). Exploratory analyses revealed no greater benefit of TAGS on MVPA compared with NUDGE. CONCLUSIONS: TAGS shows promise for future trials with additional refinements given its feasibility, acceptability, technical and functional reliability, participants' rates of engagement, and the relative MVPA improvements. Opportunities to strengthen TAGS include reducing the burden of wearing devices and incorporating of other strategies at the 3 PM decision point. Further optimization of TAGS will inform the design of a Just-in-Time Adaptive Intervention for adolescent physical activity and prepare the intervention for more rigorous testing.

Telemedicine in the age of the pandemics: The prospects of web-based remote patient monitoring systems for orthopaedic ambulatory care management in the developing economies.

Objective: The goal of this research was to demonstrate the efficacy of telemedicine via design, implementation and evaluation of a web-based remote patient monitoring system (WB-RPMS) across the tertiary/university teaching hospitals in a developing country Nigeria, as a tool to continue to expand access to an affordable and resilient tertiary healthcare system through the challenging times of the COVID-19 pandemic or any future disruptions. Methods: This research employed an agile and human-centred design thinking philosophy, which saw the researchers iteratively collaborate with clinicians across the system development value chain. It also employed qualitative and quantitative research methods for new system evaluations. After the system's development, a 20-patient sample was randomly selected from members of the National Youth Service Corp to evaluate the WB-RPMS Patient Portal for usability and user experience through a survey based on the system usability scale. Again, the COREQ standards for reporting research result were adopted for this study. Results: The evaluation of the WB-RPMS Patient Portal by a select patient sample showed that 95.0% of the respondents believed that they would like to use the system frequently. It was also discovered that 90.0% of all respondents also indicated that they found the Patient Portal to be simple; 85.0% of the respondents believed and indicated that the WB-RPMS Patient Portal was easy to use. Conclusions: The result of the usability evaluation of the developed WB-RPMS Patient Portal showed that it was well received by the select patient sample and by the clinicians who participated in the development process. In fact, the performance of the system shows that it has the potential to remotely support and sustain improved access to affordable healthcare for outpatients in developing countries even during times of uncertainties and disruptions as recently occasioned by COVID-19 pandemic.

Development of a Health Insurance Navigation Program for Long-Term Childhood Cancer Survivors.

Adapting interventions to new contexts requires consideration of the needs, norms, and delivery structures of the new setting. We describe how we followed the ORBIT model of intervention development to create Health Insurance Navigation Tools (HINT), a health insurance patient navigation intervention for childhood cancer survivors. By engaging stakeholders and leveraging institutional resources, we identified and preemptively addressed real-world barriers, which may improve the feasibility and efficacy of the intervention. Using evidence-based implementation science models to adapt and refine interventions enhances rigor and reproducibility, implements checks and balances, and surmounts challenges of intervention rollout to accelerate the delivery of health insurance education to childhood cancer survivors.

The Use of Digital Interventions for Children and Adolescents with Autism Spectrum Disorder-A Meta-Analysis.

This comprehensive meta-analysis aimed to assess the effectiveness of digital interventions in improving developmental skills for children and adolescents with autism spectrum disorder (ASD). We conducted a systematic literature search based on three databases. A pre-test adjusted between-group standardized effect size was computed for effect size synthesis. We utilized a robust variance estimation model to analyze overall treatment effect. Moderator analyses and publication bias were also addressed. Twenty-eight studies (150 effect sizes) using randomized control trials (RCT; n = 22) or quasi-experimental designs (QED; n = 6) were included. Most studies (n = 22) included social-emotional skills as primary outcomes. The meta-analysis revealed a medium to large overall effect size, with Hedges' g = 0.62, 95% CI [0.36, 0.88], p < 0.001. We found that digital interventions have a statistically significantly large effect on enhancing social-emotional skills compared with language and communication skills, cognitive skills, daily living skills, and physical skills. The results of moderator analyses indicated that computer-based interventions have larger effect sizes in comparison to tablet/smartphone-based interventions. No statistically significant differences were observed between studies utilizing RCT and those using QED. We recommended the integration of digital interventions as supplemental resources in behavioral and educational interventions. Further research needs to focus on more females, young children, and adolescents with ASD in digital intervention research.

Just-in-Time Adaptive Interventions for Behavior Change in Physiological Health Outcomes and the Use Case for Knee Osteoarthritis: Systematic Review.

BACKGROUND: The prevalence of knee osteoarthritis (KOA) in the adult population is high and patients profit from individualized therapy approaches. Just-in-time adaptive interventions (JITAIs) are upcoming digital interventions for behavior change. OBJECTIVE: This systematic review summarizes the features and effectiveness of existing JITAIs regarding important physiological health outcomes and derives the most promising features for the use case of KOA. METHODS: The electronic databases PubMed, Web of Science, Scopus, and EBSCO were searched using keywords related to JITAIs, physical activity (PA), sedentary behavior (SB), physical function, quality of life, pain, and stiffness. JITAIs for adults that focused on the effectiveness of at least 1 of the selected outcomes were included and synthesized qualitatively. Study quality was assessed with the Quality Assessment Tool Effective Public Health Practice Project. RESULTS: A total of 45 studies with mainly weak overall quality were included in this review. The studies were mostly focused on PA and SB and no study examined stiffness. The design of JITAIs varied, with a frequency of decision points from a minute to a day, device-based measured and self-reported tailoring variables, intervention options including audible or vibration prompts and tailored feedback, and decision rules from simple if-then conditions based on 1 variable to more complex algorithms including contextual variables. CONCLUSIONS: The use of frequent decision points, device-based measured tailoring variables accompanied by user input, intervention options tailored to user preferences, and simple decision rules showed the most promising results in previous studies. This can be transferred to a JITAI for the use case of KOA by using target variables that include breaks in SB and an optimum of PA considering individual knee load for the health benefits of patients.

Digital therapeutics in hypertension: How to make sustainable lifestyle changes.

Various digital therapeutic products have been validated and approved since 2017. They have demonstrated efficacy and safety as a new therapeutic modality in various disorders or conditions. Hypertension is a common but serious condition that can be prevented or controlled with lifestyle changes and medicines. Although a digital therapeutic in hypertension is validated and approved in Japan, whether digital therapeutics (DTx) can significantly improve sustainable lifestyle changes is still a controversial topic. Most studies did not discuss the long-term gain challenges. In this review, the authors discuss the definition of DTx, and analyze the motivation, engagement and adherence challenges of DTx in hypertension. Some ongoing artificial intelligence (AI)-enabled or cognitive behavioral therapy (CBT)-based digital interventions and behavioral strategies for implementing sustainable lifestyle changes are identified and analyzed. With AI-enabled interventions and behavioral strategies, DTx might be one of the effective approaches to make sustainable lifestyle changes.