Search Results (232)

Introduction: Adolescents and young adults (AYAs), especially those from underserved communities, often face barriers to sexual and reproductive health (SRH). This pilot study evaluated the implementation of mobile health technologies to promote SRH care, including the integration of the Rapid Adolescent Prevention Screening^TM (RAAPS) and the Health-E You/Salud iTu^TM (Health-E You) app at a School-Based Health Center (SBHC) in Los Angeles using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework. Methods: This multi-method pilot study included the implementation of an integrated tool with two components, the RAAPS electronic health screening tool and the Health-E You app, which delivers tailored SRH education and contraceptive decision support to patients (who were sex-assigned as female at birth) and provides an electronic summary to clinicians to better prepare them for the visit with their patient. Quantitative data on tool usage were collected directly from the back-end data storage for the apps, and qualitative data were obtained through semi-structured interviews and in-clinic observations. Thematic analysis was conducted to identify implementation barriers and facilitators. Results: Between April 2024 and June 2024, 60 unique patients (14–19 years of age) had a healthcare visit. Of these, 35.00% used the integrated RAAPS/Health-E You app, and 88.33% completed the Health-E You app only. All five clinic staff were interviewed and expressed that they valued the tools for their educational impact, noting that they enhanced SRH discussions and helped uncover sensitive information that students might not disclose face-to-face. However, the tools affected clinic workflows and caused rooming delays due to the time-intensive setup process and lack of integration with the clinic’s primary electronic medical record system. In addition, they also reported that the time to complete the screener and app within the context of a 30-min appointment limited the time available for direct patient care. Additionally, staff reported that some students struggled with the two-step process and did not complete all components of the tool. Despite these challenges, clinic staff strongly supported renewing the RAAPS license and continued use of the Health-E You app, emphasizing the platform’s potential for improving SRH care and its educational value. Conclusions: The integrated RAAPS and Health-E You app platform demonstrated educational value and improved SRH care but faced operational and technical barriers in implementing the tool. These findings emphasize the potential of such tools to address SRH disparities among vulnerable AYAs while providing a framework for future implementations in SBHCs. Full article

Obesity is a global epidemic with substantial health and economic impacts, making scalable weight management strategies essential. A comprehensive synthesis of eHealth interventions for weight management is needed to guide clinical practice. This umbrella review evaluated mobile and web-based interventions for weight loss in adults with overweight or obesity, compared to conventional or non-intervention controls. Systematic reviews were identified across five electronic databases from inception to February 2025. Two reviewers independently selected studies and assessed methodological quality using AMSTAR 2. Pooled estimates were calculated using random-effects models. Eleven systematic reviews (261 primary studies, 62,407 participants) were included. Mobile app interventions yielded a significant reduction in body weight (MD = −1.32 kg; I² = 82%), as did long-term eHealth interventions (MD = −1.13 kg; I² = 76%). Most meta-analyses showed high heterogeneity. Web-based interventions showed no significant effect. In conclusion, mobile apps and long-term eHealth interventions resulted in modest but statistically significant reductions in body weight, body mass index, and waist circumference. The evidence for web-based approaches remains inconclusive. Further research should focus on low-resource settings, primary care, and the integration of emerging technologies such as artificial intelligence. (PROSPERO CRD42025644218). Full article

Background: Spinal cord injury is a multisystem disease which compromises independence and quality of life; remote care models represent an opportunity for long-term management of complications. The aim of this study was to explore remote care models for chronic spinal cord injury patients. Methods: A systematic review of the literature was carried out. Five databases (PubMed, CINAHL, Web of Science, Cochrane Library, Google Scholar) were systematically explored with a time limit of five years. Included studies were assessed using Jadad Score and PEDro Scale. Results: Four RCTs were included in this systematic review. In all studies, multidisciplinary home care supported by technology were compared with in-person models. Remote care models were effective in managing pressure injury, infection, and muscle atrophy and improve quality of life. Conclusions: Remote care models can be a key tool for improving self-efficacy, decreasing hospitalizations and preventing long-term mortality. Full article

Artificial intelligence (AI)-powered mental health chatbots have evolved quickly as scalable means for psychological support, bringing novel solutions through natural language processing (NLP), mobile accessibility, and generative AI. This systematic literature review (SLR), following PRISMA 2020 guidelines, collates evidence from 25 published, peer-reviewed studies between 2020 and 2025 and reviews therapeutic techniques, cultural adaptation, technical design, system assessment, and ethics. Studies were extracted from seven academic databases, screened against specific inclusion criteria, and thematically analyzed. Cognitive behavioral therapy (CBT) was the most common therapeutic model, featured in 15 systems, frequently being used jointly with journaling, mindfulness, and behavioral activation, followed by emotion-based approaches, which were featured in seven systems. Innovative techniques like GPT-based emotional processing, multimodal interaction (e.g., AR/VR), and LSTM-SVM classification models (greater than 94% accuracy) showed increased conversation flexibility but missed long-term clinical validation. Cultural adaptability was varied, and effective localization was seen in systems like XiaoE, okBot, and Luda Lee, while Western-oriented systems had restricted contextual adaptability. Accessibility and inclusivity are still major challenges, especially within low-resource settings, since digital literacy, support for multiple languages, and infrastructure deficits are still challenges. Ethical aspects—data privacy, explainability, and crisis plans—were under-evidenced for most deployments. This review is different from previous ones since it focuses on cultural adaptability, ethics, and hybrid public health incorporation and proposes a comprehensive approach for deploying AI mental health chatbots safely, effectively, and inclusively. Central to this review, symmetry is emphasized as a fundamental idea incorporated into frameworks for cultural adaptation, decision-making processes, and therapeutic structures. In particular, symmetry ensures equal cultural responsiveness, balanced user–chatbot interactions, and ethically aligned AI systems, all of which enhance the efficacy and dependability of mental health services. Recognizing these benefits, the review further underscores the necessity for more rigorous academic research into the development, deployment, and evaluation of mental health chatbots and apps, particularly to address cultural sensitivity, ethical accountability, and long-term clinical outcomes. Full article

Background: Obesity in adults is a growing health concern. The principal interventions used in obesity management are lifestyle-change interventions such as diet, exercise, and behavioral therapy. Although they are effective, current treatment options have not succeeded in halting the global rise in the prevalence of obesity or achieving sustained long-term weight maintenance at the population level. E-health and m-health are both integral components of digital health that focus on the use of technology to improve healthcare delivery and outcomes. The use of eHealth/mHealth might improve the management of some of these treatments. Several digital health interventions to manage obesity are currently in clinical trials. Objective: The aim of our systematic review is to evaluate whether digital health interventions (e-Health and m-Health) have effects on changes in anthropometric measures, such as weight, BMI, and waist circumference and behaviors such as energy intake, eating behaviors, and physical activity. Methods: A search was conducted for randomized controlled trials (RCTs) conducted through 4 October 2024 through three databases (Medline, Web of Science, and Scopus). Studies were included if they evaluated digital health interventions (e-Health and m-Health) compared to control groups in overweight or obese adults (BMI ≥ 25 kg/m²) and reported anthropometric or lifestyle behavioral outcomes. Study quality was assessed using the Cochrane Risk of Bias Tool (RoB 2). Meta-analyses were performed using random-effects or fixed-effects models as appropriate, with statistical significance set at p < 0.05. Results: Twenty-two RCTs involving diverse populations (obese adults, overweight individuals, postpartum women, patients with eating disorders) were included. Digital interventions included biofeedback devices, smartphone apps, e-coaching systems, web-based interventions, and mixed approaches. Only waist circumference showed a statistically significant reduction (WMD = −1.77 cm; 95% CI: −3.10 to −0.44; p = 0.009). No significant effects were observed for BMI (WMD = −0.43 kg/m²; p = 0.247), body weight (WMD = 0.42 kg; p = 0.341), or lifestyle behaviors, including physical activity (SMD = −0.01; p = 0.939) and eating behavior (SMD = −0.13; p = 0.341). Body-fat percentage showed a borderline-significant trend toward reduction (WMD = −0.79%; p = 0.068). High heterogeneity was observed across most outcomes (I² > 80%), indicating substantial variability between studies. Quality assessment revealed predominant judgments of “Some Concerns” and “High Risk” across the evaluated domains. Conclusions: Digital health interventions produce modest but significant benefits on waist circumference in overweight and obese adults, without significant effects on other anthropometric or behavioral parameters. The high heterogeneity observed underscores the need for more personalized approaches and future research focused on identifying the most effective components of digital interventions. Digital health interventions should be positioned as valuable adjuncts to, rather than replacements for, established obesity treatments. Their integration within comprehensive care models may enhance traditional interventions through continuous monitoring, real-time feedback, and improved accessibility, but interventions with proven efficacy such as behavioral counseling and clinical oversight should be maintained. Full article

Background: Digital health, especially in Primary Health Care (PHC), has been expanding rapidly, encompassing various technologies to improve care. This study aims to evaluate the integration of digital technologies in PHC, identifying barriers and facilitators in a Brazilian capital in an urban context. Methods: A survey with a questionnaire based on a validated model was used, involving physicians and nurses from Basic Health Units. The analysis included descriptive statistics and association tests in the SPSS software, with a significance level of 5%. Results: The findings show the presence of computers and the use of e-SUS/Electronic Citizen Record in all units, highlighting WhatsApp^®, telephone calls, and other digital media as the main used tools. It was observed that there was limited digital infrastructure, a lack of adequate training for professionals or specific protocols for the organization of digital actions and statistical associations with the performance of digital health actions. Conclusions: It is recommended to strengthen policies for professional qualification and investments in infrastructure, aiming at the continuity and improvement of the use of Information and Communication Technologies in PHC. These findings offer comparable insights for similar contexts in Brazil in urban PHC settings and countries with equivalent socioeconomic contexts and analogous public health systems. Full article

The challenges and increasing number of elderly individuals requiring remote monitoring at home highlight the need for technological innovations. This study devised an eHealth mobile application designed to detect abnormal movement behavior and alert caregivers when a lack of movement is detected for an abnormal period. By utilizing the built-in accelerometer of a conventional mobile phone, an application was developed to accurately record movement patterns and identify active and idle states. Fuzzy logic, an artificial intelligence (AI)-inspired paradigm particularly effective for real-time reasoning under uncertainty, was integrated to analyze activity data and generate timely alerts, ensuring rapid response in emergencies. The approach reduced development costs while leveraging the widespread familiarity with mobile phones, facilitating easy adoption. The approach involved collecting real-time accelerometry data, analyzing movement patterns using fuzzy logic-based inferencing, and implementing a rule-based decision system to classify user activity and detect inactivity. This pilot study primarily validated the devised fuzzy logic method and the functional prototype of the mobile application, demonstrating its potential to leverage universal smartphone accelerometers for accessible remote monitoring. Using fuzzy logic, temporal and behavioral symmetry in movement patterns were adapted to detect asymmetric anomalies, e.g., abnormal inactivity or falls. The study is particularly relevant considering lonely individuals found deceased in their homes long after dying. By providing real-time monitoring and proactive alerts, this eHealth solution offers a scalable, cost-effective approach to improving elderly care, enhancing safety, and reducing the risk of unnoticed deaths through fuzzy logic. Full article

In patients undergoing systemic treatment for cancer, symptom tracking via electronic patient-reported outcomes (ePROs) has been used to optimize communication and monitoring, and facilitate the early detection of adverse effects and to compare the side effects of similar drugs. We aimed to examine whether the patterns in electronic patient-reported outcomes, without any additional clinician data input, are predictive of the underlying cancer type and reflect tumor- and treatment-associated symptom clusters (SCs). The data were derived from a total of 226 patients who self-reported on the presence and severity (according to the Common Terminology Criteria for Adverse Events (CTCAEs)) of more than 90 available symptoms via the medidux^TM app (versions 2.0 and 3.2, developed by mobile Health AG based in Zurich, Switzerland). Among these, 172 had breast cancer as the primary tumor, 19 had lung, 16 had gut, 12 had blood–lymph, and 7 had prostate cancer. For this secondary analysis, a subgroup of 25 patients with breast cancer were randomly selected to reduce the risk of overfitting. The symptoms were aggregated by counting the days on which a particular symptom was reported, resulting in a symptom vector for each patient. A logistic regression model was trained to predict the type of the respective tumor from the symptom vectors, and the symptoms with coefficients above (0.1) were graphically displayed. The machine learning model was not able to recognize any of the patients with prostate and blood–lymph cancer, likely as these cancer types were barely represented in the dataset. The Area Under the Curve (AUC) values for the three remaining cancer types were breast cancer: 0.74 (95% CI [0.624, 0.848]); gut cancer: 0.78 (95% CI [0.659, 0.893]); and lung cancer: 0.63 (95% CI [0.495, 0.771]). Despite the small datasets, for the breast and gut cancers, the respective models demonstrated a fair predictive performance (AUC > 0.7). The generalization of the findings are limited especially due to the heterogeneity of the dataset. This line of research could be especially interesting to monitor individual treatment trajectories. Deviations in the electronic patient-reported symptoms from the treatment-associated symptom patterns could dynamically indicate treatment non-adherence or lower treatment efficacy, without clinician input or additional costs. Similar analyses on larger patient cohorts are needed to validate these preliminary findings and to identify specific and robust treatment profiles. Full article

The prognosis for Hormonal Receptor positive-HER2-negative (HR+ HER2-negative) metastatic breast cancer (mBC) has significantly improved by advances in hormone therapies, targeted drugs, and antibody–drug conjugates (ADCs). Nevertheless, maintaining quality of life (QoL), managing symptoms, and reducing treatment-related toxicity remain essential. Background: eHealth solutions offer new opportunities to enhance patient engagement and well-being through digital tools. This paper aims to delineate the fundamental functionalities and objectives of TreC_Metha, a technologically advanced instrument to provide effective support during all care process of patients diagnosed with HR+HER2-negative mBC able to proactively change its configuration depending on the treatment line or on the intra-line treatment phase the patient undergoes, as set by the healthcare team. Methods: The TreC_Metha platform was developed through a structured, evidence-based four-phase process aimed at scalability, usability, and clinical relevance. The development began with a formal analysis of the metastatic breast cancer (mBC) care pathway using BPMN modeling to map phases, activities, and stakeholders, highlighting differences from early-stage breast cancer. This analysis informed the identification of key points where digital support could enhance care. Patient needs were assessed through a web-based questionnaire (N = 20) and two focus groups (N = 11), enabling a participatory design approach. Based on these insights, the platform’s functional and non-functional requirements were defined, leading to the design and implementation of a patient-facing mobile app and a clinical dashboard tailored to mBC-specific needs. Results: Preliminary findings from the web survey focus groups revealed significant gaps in communication and information delivery during the mBC care journey, contributing to patient anxiety and reduced confidence. Participants expressed a preference for digital and printed resources to improve understanding and facilitate interactions with healthcare providers. These insights informed the development of the TreC_Metha platform. The clinical dashboard enables real-time monitoring and decision-making, while the mobile app supports bidirectional communication, therapy adherence, and patient-reported data collection. A system prototype is currently under refinement and will undergo usability testing with a small cohort of users. Following this phase, the pilot study will evaluate the platform’s impact on QoL, aiming for a ≥10% improvement in outcome measures and contributing to a more patient-centered care model in the mBC setting. Conclusions: TreC_Metha represents an innovative tool that may enable involvement and active participation in the mBC care process for both a multidisciplinary care team of professionals and the patient, and that can be easily adapted to other cancer types and chronic diseases. Full article

Humans interact with virtual environments for a variety of purposes, and the use of telemedicine services and e-health platforms has become increasingly significant in recent years. Telepsychology is an emerging service and is understood as the provision of psychological aid and counseling through the use of telecommunication technologies. This study investigates the impact of visual backgrounds in a mental health simulation app and explores the decision-making of potential patients for telepsychology. In this experimental study, we developed an instrument to assess the preferences for manipulated features of photomontages and portraits. A total of 310 participants from diverse backgrounds were surveyed about their preferences regarding visual backgrounds and silhouettes for this hypothetical service, with key independent variables such as complexity, naturalness, and color hues being manipulated. Our findings represent the first example of data collected on background preferences in telepsychology. The results suggest a preference for backgrounds with medium complexity and naturalness for clinical settings. Additionally, we observed variations in preferences based on gender and age. These findings highlight the importance of customizing visual elements to enhance patient engagement in telepsychology. Full article

Background: Chronic health conditions frequently result in gait disturbances, impacting quality of life and mobility. Smartphone-based gait analysis has emerged as a promising alternative to traditional methods, offering accessibility, cost effectiveness, and portability. This systematic review evaluates smartphone-based inertial measurement units’ validity, reliability, and sensitivity for assessing gait parameters in individuals with chronic conditions. Methods: A comprehensive literature search in Web of Science, PubMed, Google Scholar, and SportDiscus identified 54 eligible studies. Results: Validity was evaluated in 70% of the included studies, with results showing moderate-to-strong associations between smartphone apps and gold-standard systems (e.g., Vicon), particularly for parameters such as gait speed and stride length (e.g., r = 0.42–0.97). However, variability was evident across studies depending on the health condition, measurement protocols, and device placement. Reliability, examined in only 27% of the included studies, displayed a similar trend, with intraclass correlation coefficients (ICCs) ranging from moderate (ICC = 0.53) to excellent (ICC = 0.95) for spatiotemporal parameters. Sensitivity and specificity metrics were explored in 41% and 35% of the included studies, respectively, with several applications achieving over 90% accuracy in detecting gait abnormalities. Feasibility was rated positively in 94% of the included studies, emphasising the practical advantages of smartphones in diverse settings. Conclusions: The findings of this systematic review endorse the clinical potential of smartphones for remote and real-world gait analysis, while highlighting the need for standardised methodologies. Future research should adopt a more comprehensive approach to psychometric evaluation, ensuring that reliability aspects are adequately explored. Additionally, long-term studies are needed to assess the effectiveness of smartphone-based technologies in supporting the personalised treatment and proactive management of chronic conditions. Full article

Aims: High smoking rates and deprivation levels in the North East of England have led to an opportunity to pilot a tobacco dependency treatment offer for NHS (National Health Service) staff who smoke, to make a supported quit attempt. The direct and indirect benefits to staff, patients, and NHS organisations are well documented. This study aimed to evaluate service acceptability. Methods: The service included up to 12 weeks of free nicotine replacement therapy (NRT) and/or a refillable e-cigarette, motivational support, and premium access to the Smoke-Free app. The service evaluation used a mixed-methods design, combining the Theoretical Framework of Acceptability (TFA) questionnaire and semi-structured interviews with staff who had accessed the offer. The quantitative data were analysed using descriptive statistics and qualitative data via thematic analysis. Results: Sixty-eight survey responses reflected high acceptability and revealed four themes relating to the service familiarity and ease of access, suitability of the NRT/E-liquid ordering service, the vape kit, and behavioural support. Conclusions: The service was deemed highly acceptable, and service users’ experiences informed recommendations for improving future tobacco dependency services. This is the first known application of the TFA to an evaluation of a smoking cessation intervention, and it contributes to a broader body of research on reducing tobacco dependency. Full article

In recent times, the emergence of Move-to-Earn (M2E) applications has revolutionized the intersection of digital innovation and physical wellness. Unlike their predecessors in the Play-to-Earn (P2E) domain, M2E apps incentivize physical activity, offering rewards for real-world movement such as walking or running. This shift aligns with a growing global focus on health consciousness that is propelled by the widespread adoption of smartphones and an increased awareness of the benefits of maintaining an active lifestyle. However, the rising popularity of these platforms has also brought about new problematic activities, with some users exploiting additional automated devices to simulate physical activity and claim rewards. In response, we propose an AI-based method aimed at distinguishing genuine user engagement from artificially generated auto-walker activity to ensure the integrity of reward distributions in M2E platforms. To demonstrate the generalizability of our model, we use a total of six open gait datasets and auto-walker datasets of automatic walking devices measured with various smartphones. Under unbiased and transparent evaluation, our model shows its ability to effectively discriminate auto-walker and genuine gait data not only on the seen datasets but also on the unseen datasets; it attained an F1-score of 0.997 on the auto-walker datasets and an F1-score of 1.000 on the genuine datasets. Full article

Every adolescent should have the right to make their own choices about their sexual and reproductive health (SRH). Achieving this goal can be challenging, especially in low- and middle-income countries (LMICs), where social norms and insufficient resources may limit access to information. Technology is increasingly being leveraged in LMICs to reach adolescents. We searched the literature to understand the landscape of digital SRH interventions in LMICs. The review addressed three questions: (1) What are the interventions and how effective are they? (2) What are adolescent preferences for information? And (3) What do the interventions cost? There is a wide variety in the populations addressed (e.g., adolescents with HIV, pregnant/post-partum adolescents) and the locations of the interventions, with the majority in sub-Saharan Africa. The types of interventions were evenly distributed between “push” approaches, where adolescents are sent information; “pull” approaches, where adolescents reach information from a website or app; and “two-way” approaches, which combine push and pull aspects. The most positive features identified were convenience and privacy. The major challenge is inadequate smartphone penetration in very low-income adolescents, especially girls. The evidence on the effectiveness of these interventions is mixed. Most studies show that SRH knowledge increases, but this does not necessarily lead to behavior change. Full article

Background: The COVID-19 pandemic significantly increased public interest in e-health literacy, especially among university students. However, gaps remain in their ability to find and use credible online health information. Purpose: This study explores the effects of public health emergencies on e-health literacy among Chinese university students, aiming to identify influencing factors and propose solutions to improve digital health education. Methods: A structured survey using the eHEALS scale and additional questionnaires was administered to 300 students in Northern China. Statistical analysis was conducted using SPSS 25.0, focusing on literacy levels and their determinants. Results: The pandemic heightened interest in e-health, leading to modest improvements in literacy levels. However, challenges persist, including evaluating the credibility of information and addressing privacy concerns. Apps emerged as the most widely used e-health tools. Discussion: Findings highlight the importance of targeted health education programs to bridge gaps in e-health literacy and support students in effectively using digital health tools. The results emphasize integrating privacy safeguards and enhancing user trust in e-health systems. Conclusions: Enhancing e-health literacy can empower students to make informed health decisions, fostering better self-management and resilience during public health crises. Full article