Process evaluation of an mHealth-based school education program to reduce salt intake scaling up in China (EduSaltS): a mixed methods study using the RE-AIM framework.

BACKGROUND: An mHealth-based school health education platform (EduSaltS) was promoted in real-world China to reduce salt intake among children and their families. This progress evaluation explores its implementation process and influencing factors using mixed methods. METHODS: The mixed-methods process evaluation employed the RE-AIM framework. Quantitative data were collected from a management website monitoring 54,435 third-grade students across two cities. Questionnaire surveys (n = 27,542) assessed pre- and post-education effectiveness. Mixed-effects models were used to control cluster effects. Qualitative interviews (23 individuals and 8 focus groups) identified program performance, facilitators, and barriers. Findings were triangulated using the RE-AIM framework. RESULTS: The program achieved 100% participation among all the third-grade classes of the 208 invited primary schools, with a 97.7% registration rate among all the 54,435 families, indicating high "Reach." Qualitative interviews revealed positive engagement from children and parents through the "small hands leading big hands" strategy. The high completion rate of 84.9% for each health cloud lesson and the significant improvement in salt reduction knowledge and behaviors scores from 75.0 (95%CI: 74.7-75.3) to 80.9 (95%CI: 80.6-81.2) out of 100 demonstrated the "Effect" of EduSaltS. The program's "Adoption" and "Implementation" were supported by attractive materials, reduced workload via auto-delivered lessons/activities and performance evaluation, and high fidelity to recommended activities, with medians 3.0 (IQR: 2.0-8.0)/class and 9.0 (IQR: 5.0-14.0)/school. Stable course completion rates (79.4%-93.4%) over one year indicated promising "Maintenance." Apart from the facilitating features praised by the interviewees, government support was the basis for the scaling up of EduSaltS. Barriers included the lack of smartphone skills among some parents and competing priorities for schools. Unhealthy off-campus environments, such as excessive use of salt in pre-packaged and restaurant foods, also hindered salt reduction efforts. The program's scalability was evident through its integration into existing health education, engagement of local governments and adaptation across various mobile devices. CONCLUSIONS: The mHealth-based school health education program is scalable and effective for public salt reduction in China. Identified barriers and facilitators can inform future health program scale-ups. The program's successful implementation demonstrates its potential for broader application in public health initiatives aimed at reducing dietary salt intake.

Scientific Production Dynamics in mHealth for Diabetes: Scientometric Analysis.

BACKGROUND: The widespread use of mobile technologies in health care (mobile health; mHealth) has facilitated disease management, especially for chronic illnesses such as diabetes. mHealth for diabetes is an attractive alternative to reduce costs and overcome geographical and temporal barriers to improve patients' conditions. OBJECTIVE: This study aims to reveal the dynamics of scientific publications on mHealth for diabetes to gain insights into who are the most prominent authors, countries, institutions, and journals and what are the most cited documents and current hot spots. METHODS: A scientometric analysis based on a competitive technology intelligence methodology was conducted. An innovative 8-step methodology supported by experts was executed considering scientific documents published between 1998 and 2021 in the Science Citation Index Expanded database. Publication language, publication output characteristics, journals, countries and institutions, authors, and most cited and most impactful articles were identified. RESULTS: The insights obtained show that a total of 1574 scientific articles were published by 7922 authors from 90 countries, with an average of 15 (SD 38) citations and 6.5 (SD 4.4) authors per article. These documents were published in 491 journals and 92 Web of Science categories. The most productive country was the United States, followed by the United Kingdom, China, Australia, and South Korea, and the top 3 most productive institutions came from the United States, whereas the top 3 most cited articles were published in 2016, 2009, and 2017 and the top 3 most impactful articles were published in 2016 and 2017. CONCLUSIONS: This approach provides a comprehensive knowledge panorama of research productivity in mHealth for diabetes, identifying new insights and opportunities for research and development and innovation, including collaboration with other entities, new areas of specialization, and human resource development. The findings obtained are useful for decision-making in policy planning, resource allocation, and identification of research opportunities, benefiting researchers, health professionals, and decision makers in their efforts to make significant contributions to the advancement of diabetes science.

Increasing adherence and collecting symptom-specific biometric signals in remote monitoring of heart failure patients: a randomized controlled trial.

OBJECTIVES: Mobile health (mHealth) regimens can improve health through the continuous monitoring of biometric parameters paired with appropriate interventions. However, adherence to monitoring tends to decay over time. Our randomized controlled trial sought to determine: (1) if a mobile app with gamification and financial incentives significantly increases adherence to mHealth monitoring in a population of heart failure patients; and (2) if activity data correlate with disease-specific symptoms. MATERIALS AND METHODS: We recruited individuals with heart failure into a prospective 180-day monitoring study with 3 arms. All 3 arms included monitoring with a connected weight scale and an activity tracker. The second arm included an additional mobile app with gamification, and the third arm included the mobile app and a financial incentive awarded based on adherence to mobile monitoring. RESULTS: We recruited 111 heart failure patients into the study. We found that the arm including the financial incentive led to significantly higher adherence to activity tracker (95% vs 72.2%, P = .01) and weight (87.5% vs 69.4%, P = .002) monitoring compared to the arm that included the monitoring devices alone. Furthermore, we found a significant correlation between daily steps and daily symptom severity. DISCUSSION AND CONCLUSION: Our findings indicate that mobile apps with added engagement features can be useful tools for improving adherence over time and may thus increase the impact of mHealth-driven interventions. Additionally, activity tracker data can provide passive monitoring of disease burden that may be used to predict future events.

eHealth and mHealth in Antimicrobial Stewardship to Reduce Mortality in Empirical Antimicrobial Therapy and a Systematic Review with a Meta-Analysis of Adequate Therapy.

The urgent requirement for swift diagnostic methods in pathogen identification and antimicrobial susceptibility testing is emphasized by rising bacterial resistance and limited treatment options, which are particularly critical in sepsis management. The shift from traditional phenotype-based methods to rapid molecular and mass spectrometry techniques has significantly reduced result turnaround times, enhancing patient outcomes. In this systematic review with meta-analysis, the aspects of correct empirical antimicrobial therapy are evaluated to determine their impact on mortality. We performed a systematic review and meta-analysis on EMBASE, the Cochrane Library, Web of Science, and MEDLINE. Studies evaluating mortality associated with empirical adequate and inadequate therapy in different sites of infection were included. Outcomes included clinical cures in microbiologically evaluable patients. Among the sites of infection, the most studied were bloodstream infections (n = 9), followed by respiratory tract infections (n = 5), intra-abdominal infections (n = 5), and urinary tract infections (evaluated by 3 studies). Inadequate therapy was associated with an increase in mortality between 11 and 68%. Technologies to speed up pathogen identification are extremely necessary to reduce mortality.

Feasibility and Acceptability of a Mobile Health Exercise Intervention for Inactive Adults: 3-Arm Randomized Controlled Pilot Trial.

BACKGROUND: Objective monitoring of self-directed physical activity (PA) is a common approach used in both fitness and health settings to promote exercise behavior, but adherence has been poor. Newer mobile health (mHealth) technologies could be a cost-effective approach to broadening accessibility and providing support for PA behavior change; yet, the optimal method of delivery of such interventions is still unclear. OBJECTIVE: This study aimed to determine the feasibility and acceptability of an mHealth exercise intervention delivered in combination with objective monitoring in 3 ways: health education emails, asynchronous exercise videos, or synchronous videoconference exercise classes. METHODS: Physically inactive (<30 min/wk) adults (cisgender women aged 31.5, SD 11.3 years, cisgender men aged 34.1, SD 28.9 years, and nonbinary individuals aged 22.0, SD 0 years) were randomized (1:1:1) to 8 weeks of increasing PA behavioral support: level 1 (health education+objective monitoring, n=26), level 2 (asynchronous contact, level 1+prerecorded exercise videos, n=30), or level 3 (synchronous contact, level 1+videoconference group exercise, n=28). Participants used a heart rate monitor during exercise and a mobile app for interaction. Primary outcomes were feasibility (accrual, retention, and adherence) and acceptability (user experience survey). Secondary outcomes assessed at baseline and 8 weeks included resting heart rate, self-reported PA, and quality of life. The exercise dose was evaluated throughout the intervention. RESULTS: Between August 2020 and August 2021, 204 adults were screened for eligibility. Out of 135 eligible participants, 84 (62%) enrolled in the study. Retention was 50% (13/26) in level 1, 60% (18/30) in level 2 and 82% (23/28) in level 3, while adherence was 31% (8/26) in level 1, 40% (12/30) in level 2 and 75% (21/28) in level 3. A total of 83% (70/84) of the study sample completed the intervention, but low response rates (64%, 54/84) were observed postintervention at week-8 assessments. Program satisfaction was highest in participants receiving exercise videos (level 2, 80%, 8/10) or exercise classes (level 3, 80%, 12/15), while only 63% (5/8) of level 1 reported the program as enjoyable. Level 3 was most likely to recommend the program (87%, 13/15), compared to 80% (8/10) in level 2 and 46% (5/8) in level 1. Self-reported PA significantly increased from baseline to intervention in level 3 (P<.001) and level 2 (P=.003), with no change in level 1. Level 3 appeared to exercise at higher doses throughout the intervention. CONCLUSIONS: Only the videoconference exercise class intervention met feasibility criteria, although postintervention response rates were low across all groups. Both videoconference and prerecorded videos had good acceptability, while objective monitoring and health education alone were not feasible or acceptable. Future studies are needed to examine the effectiveness of videoconference exercise interventions on health-related outcomes during nonpandemic times and how asynchronous interventions might maximize adherence. TRIAL REGISTRATION: ClinicalTrials.gov NCT05192421; https://clinicaltrials.gov/study/NCT05192421.

Artificial Intelligence as a Potential Catalyst to a More Equitable Cancer Care.

As we enter the era of digital interdependence, artificial intelligence (AI) emerges as a key instrument to transform health care and address disparities and barriers in access to services. This viewpoint explores AI's potential to reduce inequalities in cancer care by improving diagnostic accuracy, optimizing resource allocation, and expanding access to medical care, especially in underserved communities. Despite persistent barriers, such as socioeconomic and geographical disparities, AI can significantly improve health care delivery. Key applications include AI-driven health equity monitoring, predictive analytics, mental health support, and personalized medicine. This viewpoint highlights the need for inclusive development practices and ethical considerations to ensure diverse data representation and equitable access. Emphasizing the role of AI in cancer care, especially in low- and middle-income countries, we underscore the importance of collaborative and multidisciplinary efforts to integrate AI effectively and ethically into health systems. This call to action highlights the need for further research on user experiences and the unique social, cultural, and political barriers to AI implementation in cancer care.

Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment.

BACKGROUND: Mobile health (mHealth) solutions can improve the quality, accessibility, and equity of health services, fostering early rehabilitation. For individuals with hearing loss, mHealth apps might be designed to support the decision-making processes in auditory diagnostics and provide treatment recommendations to the user (eg, hearing aid need). For some individuals, such an mHealth app might be the first contact with a hearing diagnostic service and should motivate users with hearing loss to seek professional help in a targeted manner. However, personalizing treatment recommendations is only possible by knowing the individual's profile regarding the outcome of interest. OBJECTIVE: This study aims to characterize individuals who are more or less prone to seeking professional help after the repeated use of an app-based hearing test. The goal was to derive relevant hearing-related traits and personality characteristics for personalized treatment recommendations for users of mHealth hearing solutions. METHODS: In total, 185 (n=106, 57.3% female) nonaided older individuals (mean age 63.8, SD 6.6 y) with subjective hearing loss participated in a mobile study. We collected cross-sectional and longitudinal data on a comprehensive set of 83 hearing-related and psychological measures among those previously found to predict hearing help seeking. Readiness to seek help was assessed as the outcome variable at study end and after 2 months. Participants were classified into help seekers and nonseekers using several supervised machine learning algorithms (random forest, naïve Bayes, and support vector machine). The most relevant features for prediction were identified using feature importance analysis. RESULTS: The algorithms correctly predicted action to seek help at study end in 65.9% (122/185) to 70.3% (130/185) of cases, reaching 74.8% (98/131) classification accuracy at follow-up. Among the most important features for classification beyond hearing performance were the perceived consequences of hearing loss in daily life, attitude toward hearing aids, motivation to seek help, physical health, sensory sensitivity personality trait, neuroticism, and income. CONCLUSIONS: This study contributes to the identification of individual characteristics that predict help seeking in older individuals with self-reported hearing loss. Suggestions are made for their implementation in an individual-profiling algorithm and for deriving targeted recommendations in mHealth hearing apps.

The Impact of a Gamified Intervention on Daily Steps in Real-Life Conditions: Retrospective Analysis of 4800 Individuals.

BACKGROUND: Digital interventions integrating gamification features hold promise to promote daily steps. However, results regarding the effectiveness of this type of intervention are heterogeneous and not yet confirmed in real-life contexts. OBJECTIVE: This study aims to examine the effectiveness of a gamified intervention and its potential moderators in a large sample using real-world data. Specifically, we tested (1) whether a gamified intervention enhanced daily steps during the intervention and follow-up periods compared to baseline, (2) whether this enhancement was higher in participants in the intervention than in nonparticipants, and (3) what participant characteristics or intervention parameters moderated the effect of the program. METHODS: Data from 4819 individuals who registered for a mobile health Kiplin program between 2019 and 2022 were retrospectively analyzed. In this intervention, participants could take part in one or several games in which their daily step count was tracked, allowing individuals to play with their overall activity. Nonparticipants were people who registered for the program but did not take part in the intervention and were considered as a control group. Daily step counts were measured via accelerometers embedded in either commercial wearables or smartphones of the participants. Exposure to the intervention, the intervention content, and participants' characteristics were included in multilevel models to test the study objectives. RESULTS: Participants in the intervention group demonstrated a significantly greater increase in mean daily steps from baseline than nonparticipants (P<.001). However, intervention effectiveness depended on participants' initial physical activity. The daily steps of participants with <7500 baseline daily steps significantly improved from baseline both during the Kiplin intervention (+3291 daily steps) and the follow-up period (+945 daily steps), whereas participants with a higher baseline had no improvement or significant decreases in daily steps after the intervention. Age (P<.001) and exposure (P<.001) positively moderated the intervention effect. CONCLUSIONS: In real-world settings and among a large sample, the Kiplin intervention was significantly effective in increasing the daily steps of participants from baseline during intervention and follow-up periods compared to nonparticipants. Interestingly, responses to the intervention differed based on participants' initial steps, with the existence of a plateau effect. Drawing on the insights of self-determination theory, we can assume that the effect of gamification could depend of the initial motivation and activity of participants.

Investigating Best Practices for Ecological Momentary Assessment: Nationwide Factorial Experiment.

BACKGROUND: Ecological momentary assessment (EMA) is a measurement methodology that involves the repeated collection of real-time data on participants' behavior and experience in their natural environment. While EMA allows researchers to gain valuable insights into dynamic behavioral processes, the need for frequent self-reporting can be burdensome and disruptive. Compliance with EMA protocols is important for accurate, unbiased sampling; yet, there is no "gold standard" for EMA study design to promote compliance. OBJECTIVE: The purpose of this study was to use a factorial design to identify optimal study design factors, or combinations of factors, for achieving the highest completion rates for smartphone-based EMAs. METHODS: Participants recruited from across the United States were randomized to 1 of 2 levels on each of 5 design factors in a 2×2×2×2×2 design (32 conditions): factor 1-number of questions per EMA survey (15 vs 25); factor 2-number of EMAs per day (2 vs 4); factor 3-EMA prompting schedule (random vs fixed times); factor 4-payment type (US $1 paid per EMA vs payment based on the percentage of EMAs completed); and factor 5-EMA response scale type (ie, slider-type response scale vs Likert-type response scale; this is the only within-person factor; each participant was randomized to complete slider- or Likert-type questions for the first 14 days or second 14 days of the study period). All participants were asked to complete prompted EMAs for 28 days. The effect of each factor on EMA completion was examined, as well as the effects of factor interactions on EMA completion. Finally, relations between demographic and socioenvironmental factors and EMA completion were examined. RESULTS: Participants (N=411) were aged 48.4 (SD 12.1) years; 75.7% (311/411) were female, 72.5% (298/411) were White, 18.0% (74/411) were Black or African American, 2.7% (11/411) were Asian, 1.5% (6/411) were American Indian or Alaska Native, 5.4% (22/411) belonged to more than one race, and 9.6% (38/396) were Hispanic/Latino. On average, participants completed 83.8% (28,948/34,552) of scheduled EMAs, and 96.6% (397/411) of participants completed the follow-up survey. Results indicated that there were no significant main effects of the design factors on compliance and no significant interactions. Analyses also indicated that older adults, those without a history of substance use problems, and those without current depression tended to complete more EMAs than their counterparts. No other demographic or socioenvironmental factors were related to EMA completion rates. Finally, the app was well liked (ie, system usability scale score=82.7), and there was a statistically significant positive association between liking the app and EMA compliance. CONCLUSIONS: Study results have broad implications for developing best practices guidelines for future studies that use EMA methodologies. TRIAL REGISTRATION: ClinicalTrials.gov number NCT05194228; https://clinicaltrials.gov/study/NCT05194228.

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

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

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

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

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

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

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

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

Associations Between Weight Discrimination, Eating-Disorder-Related Psychiatric Impairment, and Eating-Disorder Treatment Interest Across the Weight Spectrum.

OBJECTIVE: Only approximately 20% of college students with an eating disorder (ED) seek treatment. One barrier to seeking treatment is weight discrimination. Past research demonstrates that experiencing weight discrimination is associated with increased ED risk and decreased in-person treatment engagement. Weight discrimination may be a particularly relevant treatment barrier for students who have a higher body weight given their higher likelihood of experiencing weight discrimination. METHODS: College students with a probable ED diagnosis (N = 372; Mage = 23.94; 73.12% women, 18.55% men, 6.18% another gender; 11.29% Asian, 4.57% Black, 12.63% Hispanic, 83.60% White, 4.84% Native American, and 0.54% another race) completed an online self-report survey that included the Clinical Impairment Assessment (CIA), Experience of Weight Discrimination (EWD) Scale, and a 0-100 scale to indicate interest in participating in virtual guided self-help ED treatment. RESULTS: Linear regression showed significant positive relationships between weight discrimination and ED-related psychiatric impairment and treatment interest. DISCUSSION: Elevations in CIA scores corroborate past literature that suggested that weight discrimination was positively related to ED psychopathology. Contrary to past research, college students who experienced weight discrimination had greater treatment interest. Students who experience weight discrimination may view virtual self-guided treatment as less weight-stigmatizing due to the "do-it-yourself" approach and no in-person interactions. Findings highlight the potential impacts of weight discrimination on acceptability of ED-related care. Future research is needed to identify ways to reduce weight discrimination and promote weight-inclusive practices in the medical system.

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

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

Improving COVID-19 contact tracing and testing of exposed individuals in Cameroon using digital health technology: a cluster randomised trial.

Background: Contact tracing was described as a key strategy to contribute to controlling the spread of severe acute respiratory syndrome of Coronavirus 2 (SARS-CoV-2) but implementing it can be a challenge. Digitalisation of contact tracing is among the proposed solutions being explored in sub-Saharan African settings. We assessed the effectiveness of a digital tool to expand SARS-CoV-2 testing in exposed individuals in Cameroon. Methods: We conducted a cluster-randomised (1:1) trial in eight health districts, including 22 facilities and SARS-CoV-2 testing units, randomly assigned to a digital (intervention) or standard (control) contact tracing approach. The intervention consisted of a contact tracing module added to the digital platform "Mamal PRO" used for monitoring and coordination of Coronavirus Disease 2019 pandemic response in Cameroon. The primary outcome was the proportion of contacts declared by SAR-CoV-2 index patients who were successfully traced and tested for SARS-CoV-2 evaluated with a Poisson regression model with cluster adjustment. This study is registered with ClinicalTrials.gov (NCT05684887). Findings: Between October 18, 2022, and March 31, 2023, we enrolled 164 index patients in the intervention arm and 149 in the control arm, who identified 854 and 849 contacts, respectively. In the intervention arm, 93.8% (801/854) of identified contacts were successfully reached by the tracing unit versus 54.5% (463/849) in the control arm. The intervention significantly increased the likelihood of successfully tracing contacts (adjusted relative risks (RR) 1.72 [95% CI: 1.00-2.95], p = 0.049). The median (interquartile range, IQR) time to successfully tracing contacts was 0 days [IQR: 0, 1] in the intervention and 1 day [IQR: 0, 2] in the control arm. In the intervention arm, 21.3% (182/854) of identified contacts received SARS-CoV-2 testing compared to 14.5% (123/849) in the control arm (adjusted RR 1.47 [95% CI: 0.44-4.90], p = 0.530). Interpretation: Digitalising the contact tracing process improved exposure notification and facilitated the tracing of a greater number of contacts of individuals infected with SARS-CoV-2 in resource-limited settings. Funding: The study was funded by FIND, United Kingdom (FCDO 40105983), Switzerland (81066910), Netherlands (SDD 4000004160), Canada (DFATD 7429348), The Kingdom of Saudi Arabia (FIND-ACT-A DX PARTNERSHIP 20.08.2020), The Rockefeller Foundation (2020 HTH 059), Germany (BMZ Covid-19 Diagnostic and Surveillance Response 27.07.2021), Australia (DFAT 76442), Kuwait (M239/2020), The Government of Portugal and Partners (ANF, BCP, CGF, APIFARMA) and The BlackRock Foundation (Grant Agreement as of April 20, 2022).

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

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

Holistic Approach for the Early Detection of Oral Cancer: A Comprehensive Training Module.

Objectives: Oral cancer is significantly high in India, and screening is an effective approach to downstage the disease. Educating Community Health Workers (CHWs) on early oral cancer detection is an effective step toward reducing the burden and serves as a first step toward facilitating the transfer of knowledge. Therefore, the purpose of this hands-on education was to equip CHWs with insight on the advanced diagnostics, preventive techniques, and innovations for the early detection of oral cancer. Materials and Methods: A total of 178 participants were trained in two groups: Group 1 received training for screening and primary prevention, while group 2 received training on updates in recent diagnostic adjuncts and innovations, AI-enabled point-of-care diagnostics, and essential patient care in management of Oral Potentially Malignant Disorders (OPMDs). Pre- and post-assessment questionnaires were used to evaluate the participants. Results: The knowledge assessment scores between the pre- and post-tests showed a statistically significant difference (p < 0.001), with rise in mean score of 3.99 from baseline. Six months following training, knowledge retention revealed a statistically significant difference (p < 0.001) in the participants' ability to recall the information. Conclusion: A well-structured training module can create awareness, impart knowledge and upskill the CHWs for early detection of oral cancer. Retraining of CHWs is required for knowledge retention post-training.

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

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

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

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