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

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Pre-exposure prophylaxis (PrEP) adherence remains a challenge among young men who have sex with men (MSM). We developed and tested a smartphone application ("app"), "DOT Diary", which combines automated directly observed therapy (DOT) with information about PrEP protection levels, pill-taking reminders, a sexual behavior diary, and a PrEP dosing calendar. To contextualize trial results, we qualitatively explored participants' app experiences. The trial enrolled 100 young MSM in San Francisco and Atlanta. Participants were randomized 2:1 to DOT Diary versus standard-of-care and followed for 24 weeks. Interviews were conducted with 24 intervention participants. Data were analyzed using a memo-writing approach. Most expressed overall satisfaction with the app ("it was good for its purpose"), despite concerns about technical glitches. The most popular app features were the monthly calendar showing days PrEP was taken and information about level of protection based on pills taken. The DOT component helped participants establish PrEP routines. The reminders were "annoying but effective" at motivating dosing. Opinions about the sexual behavior diary varied. Overall, DOT Diary was acceptable; participants were willing to use it daily to record pill-taking. Critical components included the information about PrEP protection levels and calendar, while others may be modified to improve future success.Trial registration: ClinicalTrials.gov identifier: NCT03771638.

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BACKGROUND: Chronic noncommunicable diseases (NCDs) account for major disability and premature mortality worldwide, with low- and middle-income countries being disproportionately burdened. Given the negative impact of NCDs on employee performance and work productivity, there is a rising need for stakeholders to identify effective workplace solutions that can improve employee health outcomes. As the workplace becomes more dispersed post pandemic, digital behavioral coaching offers a scalable, personalized, and cost-effective method of managing chronic disease risk factors among employees. OBJECTIVE: This study aimed to retrospectively evaluate the impact of a digital behavioral coaching program on year-to-year changes in employee health status in a cohort of Indonesian employees. METHODS: This retrospective real-world exploratory analysis of secondary health data followed 774 employees of an Indonesian company who completed company-sponsored health screenings between 2021 and 2022 and were given access to Naluri (Naluri Hidup Sdn Bhd), a holistic digital therapeutics platform offering digital behavioral health coaching and self-help tools. Participants were retrospectively classified as those who received active coaching (n=177), passive coaching (n=108), and no coaching (n=489). Linear mixed-effects models were used to evaluate the year-to-year changes in health outcomes across the 3 employee groups, with post hoc analyses evaluating within-group differences between the 2 time points and between-group differences at follow-up. RESULTS: Significant time×group interaction effects were detected for body weight, BMI, hemoglobin A1c, low-density lipoprotein, total cholesterol, and systolic and diastolic blood pressure. Post hoc pairwise comparisons revealed significant improvements in hemoglobin A1c (mean difference [Mdiff]=-0.14, P=.008), high-density lipoprotein (Mdiff=+2.14, P<.001), and total cholesterol (Mdiff=-11.45, P<.001) for employees in the Active Coaching group between 2021 and 2022, with the other 2 groups reporting deteriorations in multiple health outcomes throughout the 2 time points. At follow-up, those who received active coaching between 2021 and 2022 reported significantly lower body weight (P<.001), BMI (P=.001), low-density lipoprotein (P=.045), and total cholesterol (P<.001) than the No Coaching group. CONCLUSIONS: This study demonstrates real-world outcomes and implications supporting the use of workplace digital behavioral coaching in improving employee health status. Given the rising burden of NCDs in the Southeast Asian region, our findings underscore the role that workplace digital health interventions can play in preventing and managing chronic disease risk factors.

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BACKGROUND: Adolescent and adult obesity continues to be a public health epidemic in the United States. Despite the popularity of mHealth apps with gamification among adolescents, there are insufficient studies to evaluate the efficacy of gamified mHealth apps and financial incentives to motivate sustained health behavior change in adolescents or their adult caregivers. OBJECTIVE: This study aims to evaluate the effectiveness of gamification techniques and financial incentives used in the novel "CommitFit" mHealth app to motivate health behavior change and improve various mental and physical health metrics in adolescents and their caregivers. METHODS: This study is a 3-month randomized controlled trial (RCT) with 30 adolescents (aged 13-15 years) and their adult caregivers (N=60). It evaluates "CommitFit," which uses gamification including points and leaderboards to motivate logging and achievement of self-selected health behavior goals (eg, more water, sleep, physical activity, fruits, or vegetables or fewer sugary beverages). The RCT had three arms, each with 10 dyads: (1) CommitFit-only users; (2) CommitFit$, where adolescents were paid US $0.05 for each point they earned; and (3) waitlist control. Intervention dyads used the app for 3 months and had the option to use it for the fourth month without prompts or extra financial incentives. User analytic software was used to evaluate the frequency of user logs and goal achievement. Monthly surveys evaluated self-reported change in the 5 CommitFit health behaviors. Changes in BMI and blood pressure were evaluated for all participants at 3 clinical visits. Mental health, gamification, and behavior economics surveys were completed during the clinical visits. RESULTS: Recruitment began in August 2023 and was completed in 10 weeks. The research team successfully recruited and enrolled 30 dyads. Researchers emailed and called 89 caregivers on a physician-approved adolescent patient list, a 33% recruitment rate. Data collection and analysis will be conducted in the spring and summer of 2024. The results of this study are anticipated to be published between late 2024 and early 2025. CONCLUSIONS: This RCT will expand knowledge of the effectiveness of gamification techniques, financial incentives, and mHealth apps to motivate sustained health behavior change among adolescents and caregivers. These results may offer new opportunities to caregivers, health insurers, health care systems, and clinicians to motivate health behavior change in adolescents and caregivers, with the ultimate goal of preventing or reducing obesity and obesity-related diseases. Additional gamification, mental health surveys, and app user analytics included in the study may provide further insight into the characteristics of adolescents or caregivers who would benefit the most from using a gamified mHealth app like CommitFit. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/63505.

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BACKGROUND: Lifestyle modifications are a key part of type 2 diabetes mellitus treatment. Many patients find long-term self-management difficult, and mobile apps could be a solution. In 2010, in the United States, a mobile app was approved as an official medical device. Similar apps have entered the Japanese market but are yet to be classified as medical devices. OBJECTIVE: The objective of this study was to determine the efficacy of Save Medical Corporation (SMC)-01, a mobile app for the support of lifestyle modifications among Japanese patients with type 2 diabetes mellitus. METHODS: This was a 24-week multi-institutional, prospective randomized controlled trial. The intervention group received SMC-01, an app with functions allowing patients to record data and receive personalized feedback to encourage a healthier lifestyle. The control group used paper journals for diabetes self-management. The primary outcome was the between-group difference in change in hemoglobin A1c from baseline to week 12. RESULTS: The change in hemoglobin A1c from baseline to week 12 was -0.05% (95% CI -0.14% to 0.04%) in the intervention group and 0.06% (95% CI -0.04% to 0.15%) in the control group. The between-group difference in change was -0.11% (95% CI -0.24% to 0.03%; P=.11). CONCLUSIONS: There was no statistically significant change in glycemic control. The lack of change could be due to SMC-01 insufficiently inducing behavior change, absence of screening for patients who have high intention to change their lifestyle, low effective usage of SMC-01 due to design issues, or problems with the SMC-01 intervention. Future efforts should focus on these issues in the early phase of developing interventions. TRIAL REGISTRATION: Japan Registry of Clinical Trials jRCT2032200033; https://jrct.niph.go.jp/latest-detail/jRCT2032200033.

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BACKGROUND: Exercise therapy is recommended by international guidelines as a core treatment for patients with knee osteoarthritis. However, there is a significant gap between recommendations and practice in health care. Digital exercise apps are promising to help solve this undersupply. OBJECTIVE: This study aims to evaluate the efficacy of a 12-week fully automated app-based exercise intervention with and without a supporting knee brace on health-related outcomes, performance measures, and adherence in patients with knee osteoarthritis. METHODS: This closed user group trial included participants with moderate to severe unicondylar painful knee osteoarthritis. Randomization was 1:1:2 into an intervention group (IG) with 2 subgroups (app-based training [IG A] and app-based training and a supportive knee brace [IG AB]) and a control group (CG). The intervention included a 12-week home exercise program with 3 sessions per week. Instructions for the exercises were given via the app and monitored using 2 accelerometers placed below and above the affected knee joint. Participants in the CG did not receive any study intervention but were allowed to make use of usual care. Osteoarthritis-specific pain (Knee Injury and Osteoarthritis Outcome Score) was defined as the primary outcome, and secondary outcomes included all other Knee Injury and Osteoarthritis Outcome Score subscales, general health-related quality of life (Veterans RAND 12-item Health Survey), psychological measures (eg, exercise self-efficacy), performance measures (strength and postural control), and the monitoring of adherence and safety. Outcomes were assessed at baseline and after 12 weeks. Intervention effects were calculated using baseline-adjusted analysis of covariance for the joint comparison of IG A and IG AB versus the CG using a per-protocol approach. Subgroup analyses were conducted for each IG separately. RESULTS: A total of 61 participants were included (IG: n=30, 49%; CG: n=31, 51%; male: n=31, 51%; female: n=30, 49%; mean age 62.9, SD 8.5 years; mean BMI 27.7, SD 4.5 kg/m2). Analysis revealed statistically significant effects in favor of the IG for pain reduction (P<.001; effect size [ES]=0.76), improvements in physical function (P<.001; ES=0.64), improvements in symptoms (P=.01; ES=0.53), improvements in sport and recreation activities (P=.02; ES=0.47), improvements in knee-related quality of life (P<.001; ES=0.76), and improvements in the physical component of general health-related quality of life (P<.001; ES=0.74). Mean differences ranged from 6.0 to 13.2 points (scale range 0-100). ESs indicated small to medium effects. No effects were found for psychological and performance measures. Participants adhered to 92.5% (899/972) of all scheduled exercise sessions. CONCLUSIONS: Individuals with knee osteoarthritis undergoing a 12-week sensor-assisted app-based exercise intervention with or without an additional knee brace experienced clinically meaningful treatment effects regarding pain relief and improvements in physical function as well as other osteoarthritis-specific concerns compared to controls. TRIAL REGISTRATION: German Clinical Trials Register (DRKS) DRKS00023269; https://drks.de/search/de/trial/DRKS00023269.

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The majority of Black women with hypertension in the United States have smartphones or tablets and use social media, and many use wearable activity trackers and health or wellness apps, digital tools that can be used to support lifestyle changes and medication adherence.

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Digital mental health interventions are routinely integrated into mental health services internationally and can contribute to reducing the global mental health treatment gap identified by the World Health Organization. Research teams designing and delivering evaluations frequently invest substantial effort in deliberating on ethical and legal challenges around digital mental health interventions. In this article, we reflect on our own research experience with digital mental health intervention design and evaluation to identify 8 of the most critical challenges that we or others have faced, and that have ethical or legal consequences. These include: (1) harm caused by online recruitment work; (2) monitoring of intervention safety; (3) exclusion of specific demographic or clinical groups; (4) inadequate robustness of effectiveness and cost-effectiveness findings; (5) adequately conceptualizing and supporting engagement and adherence; (6) structural barriers to implementation; (7) data protection and intellectual property; and (8) regulatory ambiguity relating to digital mental health interventions that are medical devices. As we describe these challenges, we have highlighted serious consequences that can or have occurred, such as substantial delays to studies if regulations around Software as a Medical Device (SaMD) are not fully understood, or if regulations change substantially during the study lifecycle. Collectively, the challenges we have identified highlight a substantial body of required knowledge and expertise, either within the team or through access to external experts. Ensuring access to knowledge requires careful planning and adequate financial resources (for example, paying public contributors to engage in debate on critical ethical issues or paying for legal opinions on regulatory issues). Access to such resources can be planned for on a per-study basis and enabled through funding proposals. However, organizations regularly engaged in the development and evaluation of digital mental health interventions should consider creating or supporting structures such as advisory groups that can retain necessary competencies, such as in medical device regulation.

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INTRODUCTION: The potential benefits of eHealth support in enhancing patient care, satisfaction, and cancer outcomes are well-established; however, its integration into routine care has been gradual. The emergence of the COVID-19 pandemic in 2020 dramatically affected cancer patients, imposing multifaceted challenges that impede traditional doctor-patient interactions. Consequently, there has been a surge in the adoption of eHealth for supporting oncological therapies. This study investigates the fundamental prerequisites for transitioning to a more digitally oriented routine care, focusing on the availability of appropriate technical equipment and the cultivation of a positive mindset towards eHealth among breast cancer patients. PATIENTS AND METHODS: In 2013, 2016, and 2020, breast cancer patients participated in surveys utilizing a comprehensive paper questionnaire encompassing 29 inquiries about their health status, technical equipment, and attitudes toward digital therapy support. RESULTS: A total of 959 patients participated in the interviews. Comparative analyses between the 2013, 2016, and 2020 surveys revealed a widespread increase in internet access and device ownership across various age groups. By 2020, 3 quarters of patients were utilizing the internet for health-related topics. Notably, there has been a considerable improvement in patients' personal attitudes towards eHealth and their expectations for future digital therapy support. DISCUSSION: Over the seven years spanned by the surveys, there has been a substantial positive shift in the attitudes of breast cancer patients towards eHealth, accompanied by a marked improvement in their technical equipment. This study reveals that the essential prerequisites for digital therapy support now appear to be prevalent among breast cancer patients.

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The rise of mHealth has transformed maternal healthcare in low- and middle-income countries, enhancing care and women's access to quality services. The "Kapasia Model," launched in 2017 in Bangladesh, aims to connect beneficiaries with healthcare providers, improve antenatal care (ANC) and reduce maternal mortality. This study aimed to explore healthcare providers' perspective on digitalized ANC services within the Kapasia model. Conducted from January to July 2022, it involved 30 in-depth interviews with community-level healthcare providers across 17 facilities in Kapasia Upazila, Gazipur. A thematic analysis was performed to analyze data. The findings revealed that healthcare providers emphasized the Kapasia Model's role in raising awareness and knowledge of pregnancy care and increasing antenatal care attendance. They viewed digitalized service as means of improving connectivity and access to healthcare for pregnant women. However, providers also discussed challenges such as women's limited access to mobile phones and the time-consuming nature of completing information forms. Overall, healthcare providers supported integration of digital tools and endorsed digitalization in their workflow. Addressing these challenges is essential for optimizing ANC delivery and improving quality of services. Insights from this study will inform evidence-based decisions for future scaling-up and replication by policymakers and stakeholders in similar settings.

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OBJECTIVES: In solving the trust issues surrounding machine learning algorithms whose reasoning cannot be understood, advancements can be made toward the integration of machine learning algorithms into mHealth applications. The aim of this paper is to provide a transparency layer to black-box machine learning algorithms and empower mHealth applications to maximize their efficiency. METHODS: Using a machine learning testing framework, we present the process of knowledge transfer between a white-box model and a black-box model and the evaluation process to validate the success of the knowledge transfer. RESULTS: The presentation layer of the final output of the base white-box model and the knowledge-infused white-box model shows clear differences in reasoning. The correlation between the base black-box model and the new knowledge-infused model is very high, indicating that the knowledge transfer was successful. CONCLUSION: There is a clear need for transparency in digital health and health in general. Adding solutions to the toolbox of explainable artificial intelligence is one way to gradually decrease the obscurity of black-box models.

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This study aims to review the proposed methodologies and reported performances of automated algorithms for seizure forecast. A systematic review was conducted on studies reported up to May 10, 2024. Four databases and registers were searched, and studies were included when they proposed an original algorithm for automatic human epileptic seizure forecast that was patient specific, based on intraindividual cyclic distribution of events and/or surrogate measures of the preictal state and provided an evaluation of the performance. Two meta-analyses were performed, one evaluating area under the ROC curve (AUC) and another Brier Skill Score (BSS). Eighteen studies met the eligibility criteria, totaling 43 included algorithms. A total of 419 patients participated in the studies, and 19442 seizures were reported across studies. Of the analyzed algorithms, 23 were eligible for the meta-analysis with AUC and 12 with BSS. The overall mean AUC was 0.71, which was similar between the studies that relied solely on surrogate measures of the preictal state, on cyclic distributions of events, and on a combination of these. BSS was also similar for the three types of input data, with an overall mean BSS of 0.13. This study provides a characterization of the state of the art in seizure forecast algorithms along with their performances, setting a benchmark for future developments. It identified a considerable lack of standardization across study design and evaluation, leading to the proposal of guidelines for the design of seizure forecast solutions.

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BACKGROUND: Timely diagnosis and treatment for ST-elevation myocardial infarction (STEMI) requires a coordinated response from multiple providers. Rapid intervention is key to reducing mortality and morbidity. Activation of the cardiac catheterization laboratory may occur through verbal communication and may also involve the secure sharing of electrocardiographic images between frontline health care providers and interventional cardiologists. To improve this response, we developed a quick, easy-to-use, privacy-compliant smartphone app, that is SMART AMI-ACS (Strategic Management of Acute Reperfusion and Therapies in Acute Myocardial Infarction Acute Coronary Syndromes), for real-time verbal communication and sharing of electrocardiographic images among health care providers in Ontario, Canada. The app further provides information about diagnosis, management, and risk calculators for patients presenting with acute coronary syndrome. OBJECTIVE: This study aims to integrate the app into workflow processes to improve communication for STEMI activation, resulting in decreased treatment times, improved patient outcomes, and reduced unnecessary catheterization laboratory activation and transfer. METHODS: Implementation of the app will be guided by the Reach, Effectiveness, Acceptability, Implementation, and Maintenance (RE-AIM) framework to measure impact. The study will use quantitative registry data already being collected through the SMART AMI project (STEMI registry), the use of the SMART AMI app, and quantitative and qualitative survey data from physicians. Survey questions will be based on the Consolidated Framework for Implementation Research. Descriptive quantitative analysis and thematic qualitative analysis of survey results will be conducted. Continuous variables will be described using either mean and SD or median and IQR values at pre- and postintervention periods by the study sites. Categorical variables, such as false activation, will be described as frequencies (percentages). For each outcome, an interrupted time series regression model will be fitted to evaluate the impact of the app. RESULTS: The primary outcomes of this study include the usability, acceptability, and functionality of the app for physicians. This will be measured using electronic surveys to identify barriers and facilitators to app use. Other key outcomes will measure the implementation of the app by reviewing the timing-of-care intervals, false "avoidable" catheterization laboratory activation rates, and uptake and use of the app by physicians. Prospective evaluation will be conducted between April 1, 2022, and March 31, 2023. However, for the timing- and accuracy-of-care outcomes, registry data will be compared from January 1, 2019, to March 31, 2023. Data analysis is expected to be completed in Fall 2024, with the completion of a paper for publication anticipated by the end of 2024. CONCLUSIONS: Smartphone technology is well integrated into clinical practice and widely accessible. The proposed solution being tested is secure and leverages the accessibility of smartphones. Emergency medicine physicians can use this app to quickly, securely, and accurately transmit information ensuring faster and more appropriate decision-making for STEMI activation. TRIAL REGISTRATION: ClinicalTrials.gov NCT05290389; https://clinicaltrials.gov/study/NCT05290389. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55506.

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PURPOSE: To evaluate the effectiveness of educational eHealth and mHealth interventions on self-care ability, quality of life (QoL), ostomy complications and other health outcomes in enterostomy patients. METHODS: A comprehensive database search yielded 7385 records, which were narrowed down to 13 RCTs through stringent PRISMA-guided selection. These studies, conducted globally from 2015 to 2023, involved a total of 1530 participants and employed various eHealth and mHealth platforms, from mobile apps to telehealth systems. Primary outcomes assessed were self-care ability, QoL, and ostomy complications, mostly analyzed using a random-effects model due to inherent study heterogeneity. RESULTS: The meta-analysis showed significant improvements in self-care ability (SMD = 0.85, CI = [0.23, 1.47], P = 0.007) and QoL (SMD = 0.64, CI = [0.50, 0.79], P < 0.001) among participants receiving eHealth and mHealth interventions compared to those receiving standard care. eHealth and mHealth interventions also led to a reduction in ostomy complications (SMD = 0.18, CI = [0.12, 0.27], P < 0.001). Secondary outcomes revealed significant improvements in stoma adjustment (SMD = 1.13, CI = [0.70, 1.56], P < 0.001) and self-efficacy (SMD = 0.51, CI = [0.38, 0.64], P < 0.001). The effects on psychological well-being were mixed, with some studies showing benefits in reducing depression and anxiety symptoms, albeit with high heterogeneity. CONCLUSIONS: eHealth and mHealth interventions appear effective in improving essential health outcomes for enterostomy patients, though the heterogeneity among studies suggests that results should be interpreted with caution. The effectiveness of these interventions underscores the need for their integration into routine care, tailored to individual patient needs and local healthcare settings. Further research is required to determine the most effective eHealth and mHealth modalities and to explore their long-term benefits and scalability.

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Background: The number of migrants at the Mexico-US border has increased to historic levels, and frequently changing immigration policy impacts this population as they await entry into the US. This study evaluated the usability and health effects of the Customs and Border Protection (CBP) One™ mobile application among asylum seekers near the US port of entry in Reynosa, Mexico. Methods: We conducted semi-structured qualitative interviews with 20 asylum seekers in Reynosa, Mexico, in February 2023. Our objective was to explore the subjective experiences of migrants, usability of CBP One™, and presence of perceived health effects from using the application. Interviews were conducted until saturation occurred, transcribed verbatim into Word, coded in NVivo using a validated, team-based coding methodology, and analyzed according to internal domains, external domains, and health effects regarding CBP One™. Results: Twenty participants originated from eight countries throughout Latin America and the Caribbean. In total, 18 subthemes were identified among internal, external, and effects domains. Internal themes included a confusing application interface (80%), technical malfunction (60%), and perceived racial bias from the photo-capture features (15%). External themes challenging CBP One™ use included unavailable appointment slots (80%), inequity and inaccessibility (35%), and inadequate internet (25%). Most perceived effects were negative (85%), including worsening mental health effects (40%), exacerbation of pre-existing physical conditions (35%), and forgoing health expenditures to pay for internet (25%). Conclusions: Our findings suggest that asylum seekers at the Reynosa port of entry perceive CBP One™ negatively, with detrimental effects towards their mental and physical health. This study highlights how immigration policy can influence health and suggests that more creative and humane approaches are needed for people seeking asylum at the Mexico-US border.

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Traditional public health surveillance efforts are generally based on self-reported data. Although well validated, these methods may nevertheless be subjected to limitations such as biases, delays, and costs or logistical challenges. An alternative is the use of smart technologies (eg, smartphones and smartwatches) to complement self-report indicators. Having embedded sensors that provide zero-effort, passive, and continuous monitoring of health variables, these devices generate data that could be leveraged for cases in which the data are related to the same self-report metric of interest. However, some challenges must be considered when discussing the use of mobile health technologies for public health to ensure digital health equity, privacy, and best practices. This paper provides, through a review of major Canadian surveys and mobile health studies, an overview of research involving mobile data for public health, including a mapping of variables currently collected by public health surveys that could be complemented with self-report, challenges to technology adoption, and considerations on digital health equity, with a specific focus on the Canadian context. Population characteristics from major smart technology brands-Apple, Fitbit, and Samsung-and demographic barriers to the use of technology are provided. We conclude with public health implications and present our view that public health agencies and researchers should leverage mobile health data while being mindful of the current barriers and limitations to device use and access. In this manner, data ecosystems that leverage personal smart devices for public health can be put in place as appropriate, as we move toward a future in which barriers to technology adoption are decreasing.

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BACKGROUND: Web-based programmes offer parents of children with communication difficulties promising access to parent-mediated, early interventions. However, empirical evaluations of such programmes are limited. This study focused on parents and used mixed methods to examine the feasibility of ComAlong online. METHODS: ComAlong online is a Swedish, self-managed web-resource teaching parents supportive strategies to promote child communication. Data of different types were collected from a total of 71 parents: ten individual parent interviews, 21 pre-questionnaires and 10 post-questionnaires, and finally 50 anonymous digital evaluation surveys. Descriptive statistics and deductive qualitative content analysis were used. RESULTS: Findings indicate that parents perceived improved child communication and own competence after using the ComAlong online. The most valued parts included podcasts with experts and videos of parent-child interaction. Parents reported that the resource was easy to use, but they wanted to have gained access to the resource when the child was younger. Suggestions for changes included adding a chat function with experts, a parent net forum, and the possibility of creating personalised playlists of videos and podcasts. Evaluation of the research process revealed difficulties in recruiting parents from local child healthcare services and parents of children not yet with a diagnosis. CONCLUSIONS: This study supports the potential for self-managed, web-based resources to disseminate evidence-based parent training for supporting early communication development. Importantly, parents lack individual guidance from experts and contact with other parents. Also, measures need to be made to disseminate the resources within local child healthcare services.

Web-based service delivery programmes and digital technology offer promising access to parent-mediated interventions to support children with communication difficulties, but the empirical evaluations of such programmes are limited.Parents perceive web-based, self-managed resources teaching supportive strategies to promote child communication, in this case ComAlong online, easy to use, and such resources may improve child communication and increase competence in parents.Parents want to have access to web-based communication resources, such as ComAlong Online, early in the child's life, and a chat function with experts, a parent forum, and the possibility of creating personalised playlists of videos and podcasts are desired functionality.

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OBJECTIVE: Mobile health (mHealth), defined as the use of mobile phones or applications in healthcare, has been developed to enhance asthma care; yet implementation is inconsistent, and few studies have focused on provider perspectives on use in daily practice. The purpose of this study was to explore primary care pediatric provider perspectives regarding mHealth use in clinical practice for children with asthma. METHODS: A qualitative, descriptive approach was utilized to perform semi-structured interviews on asthma mHealth use with providers caring for children with asthma. Interview transcripts were coded by two independent investigators and any differences were reconciled. Interviews continued until thematic saturation was achieved. RESULTS AND CONCLUSIONS: Seventeen pediatric providers were recruited and interviewed. Three themes identified included implementation benefits, implementation barriers, and reporting desires, with 11 subthemes. Many subthemes were consistent across providers (e.g. self-management benefits and electronic medical record integration), while others such as provider clinical burden and approach to integrating mHealth data reports into daily workflow demonstrated variability. Provider perspectives highlight the potential of mHealth applications in asthma self-management while offering challenges related to clinical burden and suggestions for reporting and workflow integration. These results provide valuable perspectives on mHealth use and reporting to ensure provider efficiency and technology-enhanced asthma care. This study investigates pediatric provider perspectives on asthma mobile health use and reporting in daily practice, a topic that has not sufficiently been explored within the literature. Results can guide best practices, encourage more consistent use, and maximize the benefits of asthma mHealth tools by providers.

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Background: The electronic health record (EHR) is integral to improving healthcare efficiency and quality. Its successful implementation hinges on patient willingness to use it, particularly in Germany where concerns about data security and privacy significantly influence usage intention. Little is known about how specific characteristics of medical data influence patients' intention to use the EHR. Objective: This study aims to validate the privacy calculus model (PCM) regarding EHRs and to assess how personal and disease characteristics, namely disease-related stigma and disease time course, affect PCM predictions. Methods: An online survey was conducted to empirically validate the PCM for EHR, incorporating a case vignette varying in disease-related stigma (high/low) and time course (acute/chronic), with N = 241 participants, aged 18 years and older residing in Germany with no previous experience with the diseases mentioned in the respective medical reports. Participants were randomized (single-blinded) into four groups in parallel: high stigma and acute time course (n = 74), high stigma and chronic time course (n = 56), low stigma and acute time course (n = 62) and low stigma and chronic time course (n = 49). The data were analyzed using structural equation modeling with partial least squares. Results: The model explains R² = 71.8% of the variance in intention to use. The intention to use is influenced by perceived benefits, data privacy concerns, trust in the provider, and social norms. However, only the disease's time course, not stigma, affects this intention. For acute diseases, perceived benefits and social norms are influential, whereas for chronic diseases, perceived benefits, privacy concerns, and trust in the provider influence intention. Conclusions: The PCM validation for EHRs reveals that personal and disease characteristics shape usage intention in Germany. The need for tailored EHR adoption strategies that address specific needs and concerns of patients with different disease types. Such strategies could lead to a more successful and widespread implementation of EHRs, especially in privacy-conscious contexts.

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BACKGROUND: Liver cancer (LC) screening, such as AFP test and abdominal ultrasound, is an effective way to prevent LC, one of the most common cancers worldwide. Despite the proven screening benefits, screening participation among high-risk populations for LC remains low. This suggests that targeted, systematic, and effective interventions should be provided to improve knowledge and awareness related to LC screening, enhance screening intentions, and thereby promote screening behaviors. Telephone is people's main medium of daily communication and mHealth-based programs offer a potential and effective solution for promoting health behaviors. The purpose of this study is to develop and implement a mHealth (WeChat app) based intervention guided by Fogg's Behavior Model (FBM) to augment the knowledge of LC prevention among people at risk of LC and enhance their motivation for screening, and to validate its effectiveness in improving LC screening. METHODS: We propose a two-arm, single-blind randomized controlled trial with 82 at-risk individuals of LC, delivering a 6-month mHealth-based intervention program with optional health counseling. Recruitment will be through tertiary hospitals and community organizations in 4 districts in Heng Yang. In total, 82 individuals at high risk for HCC will be randomized 1:1 to intervention or control (usual care) groups. The intervention group will receive intervention, whose contents are based on the FBM model, via multiple forms of media including PowerPoint presentation, multimedia video, health information booklet and screening message, which is delivered in the WeChat Applet. Control dyads will be provided with usual health education. Outcomes will be assessed at baseline and post-intervention. DISCUSSION: The findings of this study will provide evidence of the benefits of utilizing mHealth-based approaches in intervention development to enhance the effectiveness of screening adherence for high-risk people of LC. Further, the findings would provide reference to the potential incorporation of the targeted intervention in local community organizations. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR2400080530) Date registered: 31/1/2024.

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