Background:Social media, a strategy that embeds transformative technology and targeted messaging, is promising for optimizing recruitment in the clinical research enterprise. This study aimed to evaluate recruitment rates and outcomes of Facebook advertisements, a social media-based platform, and explored targeted recruitment messaging among a key population. Methods:A convergent parallel mixed-methods design, with secondary data analysis of Facebook advertisements and in-depth, semi-structured interviews (N=15) with recruiters, was conducted. The quantitative analysis included descriptive statistics and bivariate analyses between the conditions of targeted versus general advertisements. The qualitative analysis utilized a five-step reflexive thematic analysis approach. Data analyses were integrated through a joint display. Results:The recruitment rate among those exposed to the targeted advertisements (35%) was higher compared to the general advertisements (27%). A similar trend followed for the interest rate, with targeted advertisements (44%) having higher interest rates than the general advertisements (41%). The thematic analysis generated two themes related to tailored communication and accessible language for recruitment messaging. The integrated joint display elucidated that higher resonance with targeted messaging resulted in better recruitment outcomes. Conclusions:Targeted advertisements resulted in a modestly higher recruitment and interest rate compared to general advertisements on Facebook. Targeted advertisements were nearly twice as cost-effective in recruitment and expressed interest compared to general advertisements. Integrated joint display suggests that targeted advertisements and messaging, with tailored language, enhance recruitment and interest in clinical research with practical significance. Optimizing recruitment strategies is relevant for investigators to reduce obstacles in the clinical research enterprise. Findings suggest this strategy optimizes recruitment for a key population, offering promise for advancing efficient and representative clinical research that can benefit research investigators.
Increasing physical activity is important for reducing the risk of developing dementia. The Vitality Wellness Program (Vitality), an mHealth app designed to increase physical activity through rewards, has been shown to increase users' average step counts; however, its impact on health-related outcomes remains unclear. This study investigated the effects of a 12-week Vitality program on cognitive function among older adults. A total of 467 older adults aged 60-79, who lived or worked in Kobe City, Hyogo Prefecture, and owned a smartphone were recruited for this study. Participants underwent cognitive function testing prior to the intervention, followed by a 12-week intervention period during which they had unrestricted access to Vitality, and then underwent post-intervention cognitive function testing. Cognitive function, the primary outcome, was assessed using the Cogstate Brief Battery, with concentration and memory scores calculated; the number of rewards (up to 12) earned was also recorded as a secondary measure. The analysis included 314 older adults (mean age 67.6±4.9 years; 126 men) who completed pre- and post-intervention assessments. Following app use, significant improvements were observed in both concentration and memory scores (both P<0.001). However, no significant association was found between the number of rewards earned (7.3±4.2) and changes in cognitive function (Δconcentration score: P=0.32; Δmemory score: P=0.20). In conclusion, participation in Vitality contributed to improvements in cognitive function among older adults; however, these improvements could not be explained by rewards earned through the app.
Background and Objective:Cancer pain, a common and debilitating symptom among patients with advanced malignancies, often necessitates sustained, individualized management that extends beyond the clinic. Home-based management is therefore a natural setting for continuous assessment and timely intervention. Traditional home-based pain management approaches serve various functions but fall short in terms of sufficient timeliness, intelligence and individualization. Recent advances in telehealth are reshaping this landscape by enabling proactive, individualized, and scalable support. In this context, this review was conducted to elucidate the recent progress on application of telehealth in home-based management of cancer pain, providing new insights and general principles for both providers and patients. Methods:A comprehensive literature search was performed on PubMed, Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature (CINAHL). The search included randomized and non-randomized trials, cohort or pre-post studies, and systematic reviews that evaluated telehealth interventions aimed at home management of cancer pain. Search terms encompassed relevant keywords for cancer pain, home-based, pain management and telehealth. Key Content and Findings:Telehealth has empowered cancer pain management through remote symptom monitoring, real-time assessment, personalized intervention, smart pain management and provider-patient empowerment. It facilitates the identification and documentation of pain intensity fluctuations, improves patient-reported outcomes (PROs) and may reduce safety risks such as opioid overdose. Owing to its advantages in transcending time and space, telehealth has gained broad acceptance among both providers and patients. However, the successful implementation of telehealth in the home setting depends on seamless integration with multiple factors and support from different dimensions while overcoming numerous challenges and limitations. This may entail enormous efforts and consideration from different groups. Looking ahead, the greatest opportunities lie in artificial intelligence (AI) driven predictive analytics, systems or platforms to forecast pain fluctuations, personalize treatment and proactively reduce safety risks. Another promising direction is hybrid healthcare models that combine remote monitoring and in‑person interventions. Conclusions:This narrative review combs through the promising empowerment of telehealth in the home-based cancer pain management, discussing its multifaceted benefits, characterizing current challenges and limitations while providing a general principle for future research and application directions in telehealth empowered home-based management of cancer pain.
Background:Seasonal variations in physical and mental functioning among older adults have been widely reported; however, whether frailty risk exhibits season-specific patterns and associations with health-related outcomes remains unclear. This exploratory study aimed to examine season-specific associations between electricity-based frailty risk and health-related outcomes among community-dwelling older adults. Methods:Older adults living alone in apartment complexes in Osaka City, Japan were recruited. Monthly frailty risk indices, based on patterns of daily living behaviors such as wake-up time, bedtime, and time spent outside the home, were derived from household electricity consumption data collected over a 12-month period from October 2023 to September 2024. Life-space mobility, health-related quality of life (HRQoL), and physical function were assessed once via a face-to-face survey conducted between October and November 2024 using the Life-Space Assessment (LSA), the EuroQol 5-Dimension 5-Level questionnaire (EQ-5D-5L), and the Timed Up and Go (TUG) test, respectively. Seasonal mean frailty risk indices were classified according to the seasonal definitions provided by the Japan Meteorological Agency. Bayesian correlation and linear regression analyses were conducted separately for each season, and exploratory linear mixed-effects models were performed using the monthly Frailty Risk Index values. Results:Of the 18 individuals who participated, 14 [median age: 81.0 years, interquartile range (IQR), 10.3 years; 86% women] were included in the analysis. In winter, Bayesian analyses supported negative correlations between the Frailty Risk Index and the LSA [Bayes factor (BF10) =6.285, 95% credible interval (CrI): -0.857 to -0.146] and EQ-5D-5L (BF10 =13.95, 95% CrI: -0.885 to -0.237), whereas no sufficient evidence supported an association with physical function assessed by the TUG test. In Bayesian regression analyses, the winter model including both the LSA and EQ-5D-5L showed the highest posterior support (BFM =2.089, R2=0.603), although this finding should be interpreted cautiously owing to the small sample size. No sufficient evidence of an association was observed in spring, summer, or autumn. Conclusions:In this exploratory pilot study of 14 older adults living alone, electricity-based frailty risk was associated with life-space mobility and HRQoL, with associations observed for winter Frailty Risk Index values. However, the small sample size, single-time assessment of health-related outcomes, and potential residual confounding preclude definitive conclusions regarding season-specific effects. Larger longitudinal studies with repeated health assessments are needed to validate these findings.
Background:Artificial intelligence (AI) has emerged as a potential tool in nutrition counseling, but its performance compared with registered dietitians (RDs) remains unclear. This study aimed to compare the clinical quality, empathy, and readability of nutrition responses by a large language model (LLM, ChatGPT-4o) with those provided by licensed RDs, as assessed by RD evaluators. Methods:In this cross-sectional study, 100 nutrition-related questions were selected from public online forums where RDs had provided answers. Each question was paired with an AI-generated response. Licensed RDs (n=8), blinded to the source, rated responses for quality and empathy (5-point Likert scales) and overall performance (0-100). Readability was assessed using the Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), syllables per word, and words per sentence. Statistical analyses included independent two-tailed t-tests, z-tests for proportions meeting a threshold for "acceptable" (≥4), Pearson correlations, and sensitivity analyses by response length. Results:AI-generated responses scored higher than RD-authored responses for quality (4.48±0.31 vs. 2.56±0.76; P<0.001), empathy (4.62±0.37 vs. 3.21±0.62; P<0.001), and overall performance (91.10±5.38 vs. 66.83±14.71; P<0.001). AI scores clustered at the upper end, while RD scores were more variable. Quality and empathy were not correlated for AI (r=-0.10, P=0.32) but showed a moderate positive correlation for RDs (r=0.37, P<0.001). Nearly all AI responses met the ≥4 threshold for quality (96%) and empathy (97%), compared with few RD responses (3% and 14%; P<0.001). Word count did not differ, and longer RD responses were not associated with higher ratings. RDs' responses were more readable, with higher FRES (53.5±13.5 vs. 46.2±12.5; P<0.001), and simpler vocabulary (1.60±0.1 vs. 1.73±0.1 syllables/word, P<0.001), though both groups averaged a 10th-grade level on the FKGL, exceeding Centers for Disease Control and Prevention (CDC) and National Institutes of Health (NIH) recommendations. Conclusions:AI-generated nutrition responses demonstrated consistently high perceived quality and empathy, independent of length, while RD-authored responses display greater variability but higher readability. These findings highlight both the promise and the limitations of LLMs in nutrition counseling, suggesting that AI may complement, but not replace, human expertise, provided that accuracy, transparency, and professional oversight are maintained.
Background: The increasing integration of Internet of Things (IoT) technologies in smart-home environments has enabled continuous collection of behavioural data that can support cognitive health monitoring. Early identification of behavioural deviations associated with cognitive decline is critical for timely intervention and quality-of-life improvement among older adults. However, conventional clinical assessments are often episodic, subjective, and resource-intensive. The objective of this study is to develop a non-invasive, data-driven framework for analysing daily behavioural patterns from smart-home IoT data to support early cognitive-risk screening rather than clinical diagnosis. Methods: This study proposes HEALNET (Home Environment Assisted Learning Network), a hybrid deep learning (DL) framework that integrates convolutional neural networks (CNNs) for spatial feature extraction, long short-term memory (LSTM) networks for temporal sequence modelling, and ensemble machine learning (ML) classifiers including Random Forest (RF) and support vector machine (SVM). The framework analyses longitudinal behavioural data collected from smart-home IoT sensors. Experimental evaluation was conducted using publicly available Centre for Advanced Studies in Adaptive Systems (CASAS) smart-home datasets. Results: The proposed HEALNET framework achieved a classification accuracy of 94.2%, outperforming baseline ML and DL models. Results demonstrate that the integration of spatial, temporal, and statistical behavioural representations improves the detection of behavioural patterns associated with elevated cognitive-risk indicators. Conclusions: The findings indicate that continuous, unobtrusive behavioural monitoring using smart-home IoT data can provide reliable indicators for cognitive-risk screening. HEALNET serves as a research-stage framework supporting data-driven behavioural analysis rather than clinical diagnosis and aligns with Saudi Vision objectives for digital health innovation and quality-of-life enhancement.
Background:Maternal mental well-being during and after pregnancy is often overlooked, posing serious long-term risks to mothers and children. This systematic review aims to synthesize research on mobile health (mHealth) applications (apps) designed to support perinatal and postpartum mental well-being, with a focus on their design characteristics, intervention approaches, and reported effectiveness. Methods:We conducted a systematic review following the PRISMA 2020 guidelines. PubMed and Scopus were searched up to August 2025. Studies were included if they reported original research on mHealth apps targeting maternal mental well-being during or after pregnancy with a diagnostic or intervention component for mental health. Review papers, conference abstracts, and studies without an mHealth component were excluded. Results:From 2,127 articles, 15 met the inclusion criteria. These studies, published between 2017 and 2024, evaluated 13 distinct mHealth apps targeting primarily anxiety (12 studies), depression (8 studies), and stress (4 studies). Across all 15 studies, 24 screening methods were reported. Apps delivered interventions including mindfulness and guided meditation (7 studies) and cognitive behavioral therapy (CBT)-based tools and mood tracking (7 studies). Six app feature categories were identified: mental health screening, physical and mental well-being exercises and meditation, health education, visual design elements, healthcare support, and additional support features. Usability and engagement were most commonly evaluated using questionnaires and surveys (4 studies) and the Mobile Application Rating Scale (MARS) (3 studies). Six studies reported positive outcomes for depression symptoms. Common methodological limitations included small sample sizes, high dropout rates, and lack of long-term follow-up, constraining the generalizability of findings. Conclusions:This review demonstrates the potential of mHealth apps as accessible tools for supporting maternal mental well-being during pregnancy and the postpartum period. Clinicians should regard these tools as supplementary rather than standalone interventions until larger-scale efficacy trials are available. App developers are encouraged to design solutions that span both prenatal and postnatal periods, address multiple mental health conditions simultaneously, integrate validated screening methods, and combine health education, therapeutic, and behavioral support within a single platform. Future research should prioritize robust, longitudinal trials with diverse populations and standardized outcome measures to establish the evidence base needed for broader integration of mHealth into perinatal care.
Background:Existing e-health literacy assessment tools fail to accurately assess the e-health literacy status of pregnant women. We aimed to develop an e-health literacy scale for pregnant women, and evaluate its psychometric properties. Methods:The scale may provide a scientific tool for evaluating the e-health literacy of pregnant women and developing targeted intervention plans. The initial constructs and items of the scale were developed through a literature review, qualitative analysis, and Delphi expert consultation based on the e-health literacy interactive model. Item analysis used a sample (n=220) of pregnant women in China to develop the formal scale. Additional participants (n=230) completed a survey to assess the internal consistency and test-retest reliability, and the content, construct, convergence and discrimination validity, of the scale. Results:The e-health literacy scale for pregnant women consisted of 22 items, and four dimensions including e-health information acquisition ability, e-health information evaluation ability, e-health information interaction ability, and e-health information application ability. The Cronbach's alpha coefficient was 0.937, test-retest reliability was 0.772, and the content validity index was 0.962. The cumulative variance contribution rate of the four common factors was 64.159%, the Kendall harmony coefficients were 0.386 and 0.439 (P<0.001), and the confirmatory factor analysis model had acceptable goodness-of-fit indices [χ2/df =2.250, root mean squared error of approximation (RMSEA) =0.075]. The average variance extracted (AVE) of each dimension were all above 0.500, and the composite reliability (CR) were all >0.700. Conclusions:The e-health literacy scale for pregnant women showed satisfactory psychometric properties and practice implications.
Background: Traditionally, cancer survivorship behavioral intervention research has recruited from cancer registries, which can be costly and time intensive. Over the last decade, the advent of social media recruitment, hospital electronic medical record portals, and large provider networks has offered the possibility of non-paid recruitment sources to recruit cancer survivors cost-effectively. In this study, we used three non-cancer registry recruitment sources for a digital intervention to improve skin self-exams and sun protection among melanoma survivors. The objective of this study is to address critical knowledge gaps in melanoma research recruitment by comparing enrollment rates and participant demographics across digital and clinical sources, including social media, electronic health messaging, and dermatology practice network outreach. Methods: Adults aged 18-89 with a prior stage 0-III melanoma diagnosis, 3 months to 5 years post-surgery, no current disease, and nonadherent to thorough skin self-exams were eligible for this study. Recruitment occurred through paid Facebook advertisements targeted at high-melanoma-incidence cities, unpaid social media influencer outreach, EHR messages, and a national dermatology practice network. An online eligibility screener was disseminated across all sources, with safeguards to prevent fraudulent entries. Individuals deemed eligible were contacted to confirm eligibility and completed oral and digital consent before enrollment. Enrollment rates and demographics were calculated. Results: Of 230 participants enrolled from non-cancer registry sources, 122 participants (53.0%) came from a dermatology provider network, 56 participants (24.3%) came from social media, 46 participants (20.0%) came from EHR messaging, and 6 participants (2.6%) came from other sources. Social media recruitment yielded younger, predominantly female, more frequently employed and privately insured participants, and a higher proportion diagnosed at higher stages, compared with other sources. Despite recruitment success, over 1,700 fraudulent entries were detected and removed. Conclusions: Non-cancer registry sources can support enrollment for digital intervention research, but each approach carries unique trade-offs. Provider networks delivered high volumes of eligible participants with minimal burden, while social media provided broad reach but required intensive fraud monitoring and additional safeguards. These findings suggest that combining provider-based outreach with carefully managed social media efforts may offer an effective balance between reach and data integrity when recruiting cancer survivors.
Background:Engaging in regular physical activity is a key protective factor for reducing the risk of developing chronic health conditions associated with ageing. However, physical activity declines markedly with increasing age. The aim of this prospectively registered systematic review was to evaluate the effectiveness of mobile health (mHealth) physical activity interventions, and the behaviour change techniques (BCTs) they employ, in older adults. Methods:This review was registered in the International Prospective Register of Systematic Reviews (PROSPERO), CRD42022342016. Eight databases (APA PsycINFO, ClinicalTrials.gov, Cochrane Library, Medline, PubMed, Scopus, SPORTDiscus, Web of Science) were searched up to February 2025. Eligible studies were randomised controlled trials (RCTs) evaluating mHealth interventions (e.g., smartphone apps, wearable devices) designed to increase physical activity in community-dwelling older adults (≥65 years) living with and without chronic health conditions. Primary outcomes included measures of physical activity (both objective and self-reported), functional fitness, and adverse effects. Secondary outcomes were physiological health, psychosocial wellbeing, and cognition. Risk of bias was assessed using the Cochrane Risk of Bias tool version 2, and certainty of the evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results:Nine RCTs were included, assessing mHealth interventions such as wearable devices, smartphone apps, or virtual coaching. Due to methodological heterogeneity across studies, meta-analyses were not possible. A narrative synthesis revealed limited or inconsistent findings for all primary and secondary outcomes. Interventions incorporated a limited number of the 93 available BCTs, with the most frequently used being self-monitoring of behaviour, information about antecedents, and feedback on behaviour. There was substantial variation in the number and combination of BCTs employed across studies, limiting the ability to evaluate their individual or combined effectiveness. Due to insufficient data, it was not possible to compare the effectiveness of mHealth interventions between healthy older adults and those living with chronic ill-health. Conclusions:The current review highlights that further research in this area is needed, as well as a requirement to optimise the design of mHealth physical activity interventions that incorporate suitable BCTs so that they can adequately address the complex needs of those living with and without chronic health conditions.
Background: Although many studies have evaluated behavioral mobile health (mHealth) usability in adults, far fewer have examined acceptability among adolescents, particularly regarding sustained engagement for lifestyle and behavior change. Adolescents have distinct developmental needs and design preferences, yet most mHealth tools are adapted from adult models, contributing to low adoption and limited continued use. In adolescent mHealth, understanding acceptability among adolescents, caregivers, and clinicians is essential to ensure interventions are developmentally appropriate and feasible for clinical integration. Given the complex social and contextual factors shaping adolescent health behaviors, qualitative methods are well-suited to capturing stakeholder experiences beyond usability. This study examines the acceptability of CommitFitSM, an adolescent lifestyle mHealth app, to generate actionable insights for sustained engagement strategies. Methods: Two sequential assessments evaluated CommitFitSM acceptability using the seven domains of the Theoretical Framework of Acceptability (TFA; affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness, and self-efficacy), guided by theory-informed, stakeholder-refined questions assessing anticipated and experienced acceptability. In Study 1 (prospective design phase), 6 adolescents, 7 caregivers, and 12 clinicians participated in focus groups using a static prototype of the gamified app; discussions surfaced expectations, concerns, and perspectives essential for early-stage development. Participants were purposively selected to represent key roles: adolescents as end users, caregivers as family decision makers, and clinicians as system-level stakeholders evaluating workflow fit and implementation feasibility. In Study 2 (retrospective post-development phase), 10 adolescents used the full app for 2 weeks and completed individual interviews to provide personal experiences, usability feedback, and engagement patterns not evident in group settings. Data from both phases were analyzed using an abductive, Grounded Theory-informed approach. Results: Analysis demonstrated high acceptability across adolescents, caregivers, and clinicians. Two additional themes-intervention motivational aspects and stakeholder endorsement-emerged as critical determinants of adolescent engagement and sustained use. Findings reflected input from a sociodemographically diverse cohort varying by race, gender, household income, and rurality, as well as clinicians from family medicine, pediatrics, and psychology. Consistency in perceived acceptability across stakeholder groups and design and post development phases underscores the value of inclusive, multi-stakeholder involvement in developing clinically relevant adolescent mHealth interventions. Conclusions: Using the seven TFA domains, supplemented by intervention motivational aspects and stakeholder endorsement, this study identified key drivers of adolescent engagement with CommitFitSM. Findings suggest that acceptability-and conditions that support sustained engagement-may be strengthened when apps offer adaptive goal setting, progress feedback, and motivational features aligned with adolescent preferences, and when caregivers and clinicians actively support use. Applying this expanded nine-domain framework may enhance engagement and acceptability of adolescent mHealth apps and inform designs likely to support sustained use. Future work should evaluate and validate this framework across adolescent-focused applications to support scalable, stakeholder-responsive intervention design.
Short-term medical missions (STMMs) provide resource-limited regions with immediate healthcare services and can play a helpful role in bridging critical gaps in healthcare access, providing essential services, and contributing to capacity building in underserved communities. However, STMM teams have the potential to cause harm due to unfamiliarity with the patient population, culture, and disease epidemiology. Specifically, mobile primary care clinics run by STMMs are run in isolation and are not linked with any existing electronic health record (EHR) system, creating room for potential medical errors. To date, there have been limited attempts to tailor EHRs to STMM mobile clinics and existing systems remain in early developmental stages. We aim to develop an EHR system suited for STMMs that does not depend on internet connectivity, improves patient safety and patient care processes, and has longer-term sustainable applications. Traditional STMM clinic processes are described, and historical post-trip feedback were retrieved. Brainstorming with stakeholders was conducted to determine the essential features of the EHR system. A solution was chosen which involved the decentralisation of data over a peer-2-peer network functioning over a local area network (LAN) provided by any portable router. The process of development, implementation, troubleshooting of this EHR during an STMM in Timor-Leste over 5 days in both urban and rural locations is described. Post-implementation qualitative feedback has been encouraging especially in the aspect of clinic process, medication safety and ease of data access, analysis, and sharing. While this EHR has been useful, there are limitations such as the need for a stable power supply to the router and the lack of unique identifiers for patients in some settings that prohibits the linking of data across databases. Nonetheless, the development of our EHR is an important step in the right direction.
Background:Community health workers (CHWs) are an essential and rapidly growing part of the public health workforce. CHW activities are traditionally conducted in person, such as in clinics and at community events; social media could further extend their impact. Many health professionals use social media for disseminating health information, engaging patients, and promoting positive health change, while also navigating risks, such as privacy concerns. Training could be an effective approach to equipping CHWs with skills to maximize social media's benefits while mitigating risks. Furthermore, artificial intelligence (AI) tools are increasingly popular for creating, refining, or tailoring social media content and could be useful for CHWs who use social media. In this study, we conducted qualitative interviews to explore the potential benefits and drawbacks of using social media as a CHW tool, CHW preferences for social media skills training, and interest in learning how to use AI for social media content creation. Methods:We recruited CHWs in Louisiana, USA, through targeted e-mails to a CHW professional organization and agencies that employ CHWs. Between October 2024 and February 2025, we conducted 15 interviews. Interviews were audio-recorded and transcribed for analysis. We used deductive and general inductive approaches to analyze transcripts and generate themes. Results were finalized with input from experienced CHWs. Results:We identified five themes related to the benefits and drawbacks of social media use: reach and engagement, privacy and confidentiality, health education, organizational policy and expectations, and time and effort. For example, in terms of reach and engagement, CHWs highlighted social media as being particularly effective for reaching specific groups, such as young people, but also recognized that many clients they serve live in rural areas with limited internet access. All participants were supportive of a social media skills training, except for one. Participants commented on the format, teaching approaches, and content they would like to see in a social media skills training program for CHWs, such as incorporating interactive elements and teaching how to develop culturally sensitive content and navigate personal-professional boundaries. Many CHWs expressed hesitancy about training on how to use AI for content creation, noting concerns about authenticity and accuracy. Conclusions:Social media could be a powerful tool for boosting outreach efforts and expanding access to health information. However, using social media can present challenges in maintaining personal-professional boundaries and the privacy and confidentiality of CHWs and their clients. Results from our study can be used to inform the development and testing of a social media skills training that is responsive to CHW needs.
Background:Enhanced recovery after surgery (ERAS) programs are designed to reduce postoperative complications and accelerate recovery. Despite their proven benefits, maintaining patient adherence to these protocols remains a significant challenge. Mobile health (mHealth) applications have been introduced as potential tools to support adherence and improve perioperative outcomes; however, their effectiveness within ERAS pathways has not been clearly established. This review aims to evaluate the impact of mobile applications on protocol compliance, recovery, and clinical outcomes among surgical patients enrolled in ERAS programs. Methods:PubMed, EMBASE, and the Cochrane Library were systematically searched through February 2025 to identify studies comparing ERAS care with and without mobile application support. Due to heterogeneity in study design, outcomes, and app functionalities, a meta-analysis was not performed. The primary outcome was adherence to ERAS protocols. Secondary outcomes included quality of recovery, patient and clinician satisfaction, postoperative complication rates, hospital length of stay (LOS), and readmissions. Results:Eight studies encompassing 1,623 patients were included. Mobile app use was associated with improved adherence to ERAS components, particularly early mobilization and oral intake. Some studies reported higher Quality of Recovery-15 (QoR-15) scores and greater patient satisfaction, although these differences were not always statistically significant. The clinician reported reductions in unnecessary visits and improved communication. No study reported an increased rate of complications. One study found that non-adherent patients had a significantly higher risk of 30-day readmission; another reported reduced infection rates and better pain control. The risk of bias was moderate in most studies. Conclusions:mHealth applications integrated into ERAS protocols may improve adherence, recovery quality, and patient engagement without increasing adverse outcomes. However, the overall quality of evidence remains limited due to heterogeneity and a predominance of non-randomized studies.
Background:Rural areas have a shortage of dental care resources and geographical remoteness, which is a major issue. Teledentistry, a new technology, provides dental care remotely and can reduce the care gap between rural and urban areas. However, the utilization of teledentistry has not been fully understood in rural settings. This study reviewed the current status and potential of dental care services for teledentistry in rural areas. Methods:We searched for papers in MEDLINE/PubMed and CENTRAL published up to May 2024 with keywords of "rural" and "teledentistry" and conducted a scoping review based on the contents of the papers. Literature was limited to original articles, and conference abstracts, letters, editorials, and review papers were excluded. The target populations were subjects living in rural areas. Studies that compared the application with non-application of teledentistry and the remote approach with face-to-face approach were eligible. Results:Thirteen eligible papers were identified and divided into four categories of utilization. Four of the papers studied dental screening (checkups), five of pathological diagnoses, two of oral health support, and two of referrals to specialists. These papers covered studies in populations with a wide range of ages, from children to the elderly. The time reduction for access to services, acceptable satisfaction, and potential cost reduction were partly described. Overall, it was determined that teledentistry could indeed be useful. Conclusions:The current review demonstrates the useful applications of teledentistry in rural areas. Although the introduction of teledentistry may be considered suitable for dental care services in rural areas, further studies are required to establish it. With the development of photography, artificial intelligence, and communication systems, teledentistry will be a future challenge.
Background:Prescription digital therapeutics (DTx) are software-based medical interventions regulated by the Food and Drug Administration (FDA). Ensuring accessibility and equity is crucial, as effectiveness depends on patient engagement. This scoping review examines whether clinical validation studies adequately assess health equity, cultural competence, and digital accessibility. This study aimed to evaluate the extent to which FDA-mandated clinical trials of DTx products report diverse participant characteristics, cultural adaptations, and digital literacy considerations. Methods:A systematic search of PubMed, Google Scholar, and ClinicalTrials.gov identified clinical validation studies of FDA-approved DTx products. Studies were assessed for health equity factors using the PROGRESS-Plus framework and categorized based on reporting of cultural competence, linguistic accessibility, and digital literacy. Results:Thirty-two studies covering six FDA-approved DTx products were included. Over 60% reported participant demographics (gender, race/ethnicity, education level), but fewer than 15% addressed other health equity factors. Fifteen studies excluded participants who were not fluent in English. No studies incorporated cultural adaptation frameworks or linguistic translations. Two studies found digital literacy significantly affected intervention effectiveness. Conclusions:Clinical validation studies of DTx lack sufficient assessment of health equity, cultural competence, and digital accessibility. Addressing these gaps is essential to ensure equitable access and effectiveness for diverse populations.
Background:There is a discrepancy between the number of people who report a mental health need and the number of people who use mental health services. The SolanoConnex web-app was developed to address this disparity in a diverse county by enhancing access to existing mental health services, with this paper describing the participatory and iterative development process. Methods:The web-app was developed in a five-stage process beginning with (I) secondary data analysis and landscape data collection, followed by a participatory approach to (II) design the product using fictitious, representative patient profiles developed by an advisory board to test the algorithm, (III) develop the web-app. The web-app was (IV) beta-tested via one-on-one interviews during which participants had access to beta versions of the app and were asked to respond to a structured feedback questionnaire. Finally, the web-app was (V) launched with continued assessment of the product. Results:The advisory board patient profiles and beta-testing feedback led to changes in how priority information such as insurance and cost details, services in a preferred language, and services tailored to specific marginalized groups appeared, and the wording used to describe mental health in the dials. The activity of matching fictitious, representative patient profile to services with early versions of the app led to a reduction in how many clicks it took to get to a services page. These changes resulted in an easy-to-use, jargon-free and intuitive interface providing the necessary information to access mental health services that was tailored to the specific needs and attitudes of the local community. Modifications continue to be made as necessary. Conclusions:The rigorous multi-stage process with participation and oversight from numerous local stakeholders ensured the development of an end-product that addressed the county-specific gaps and barriers in accessing mental and emotional health services. The lessons derived from this process can benefit those attempting to develop a similar tool to address public health disparities.
Mobile health (mHealth) technologies offer promising tools for supporting behavior change and chronic disease management, yet the development of such tools remains complex and underexplored. While existing frameworks provide high-level guidance, they often lack practical detail, particularly regarding the logistics of app design and development with external vendors. This study addresses this gap by sharing lessons learned from the mHealth development process involving a multidisciplinary team. We report on the iterative process of re-designing, re-developing and re-evaluating two health education apps: Glow, for people living with type 2 diabetes, and WellFeet, for those at risk of developing foot ulcers. The development and evaluation followed a hybrid of two frameworks: Design Thinking framework and Rapid Application Development. The apps were evaluated in a co-design study, randomized controlled trial and a feasibility study. This report follows autoethnographic methods for data collection and analysis. The process of (re-)designing, (re-)developing and (re-)evaluating the apps yielded valuable insights in three areas: (re-)designing app features, adjusting to regulatory landscape, and synchronizing with the developer. (Re-)designing app features included improvements in tracking and gamification, notifications, and tailored education. Adjusting to the regulatory landscape occurred at the institutional, platform, and national levels. Effective synchronization with the developer required understanding and adapting to their workflow, improving testing protocols, and maintaining a strong rapport to navigate unexpected challenges. Key practice implications emerged: the need to clarify and adjust the project vision iteratively within multidisciplinary teams, and to approach this work with resilience, humility, and curiosity instead of authority. It is equally important to prepare for uncertainty and remain flexible, as evolving requirements and regulatory shifts can influence both product and project plans. In such environments, adaptability is not merely helpful-it is imperative.
