DIGITAL HEALTH最新文献

Background: Technology advancement along with the increase in the older adults' population leads to the creation of health applications. The combination of exercise, nutrition, and cognition should be studied carefully in improving older adults' health.

Objective: The purpose of this study is to develop a health application, WeFit contains these three components and to determine its content validity, acceptability, and usability.

Methodology: This study is a design and development study involving three phases. The first phase is the need analysis involving a review on 16 mobile applications available in Google play and iTunes App store as well as a review of six articles for identifying the perception of older adults in using mobile applications. Second phase is mobile application development and content validity. The content validity was determined using the Content Validity Index for Individual Items (I-CVI). Phase 3 evaluated the acceptance of the WeFit mobile application among older adults and health practitioners.

Results: Phase 1 indicated that half of the applications reviewed (50.0%) had physical activity component and the other half (50.0%) had a cognitive component, and none on nutrition. No application is reported to have all three components. In Phase 2, WeFit health application containing the three components was developed where users can view exercise and food recommendations and play cognitive games. WeFit had an I-CVI value of 0.98. With respect to acceptability, majority of the study participants (93.3%) understood the WeFit's content and the graphics used were appropriate. The usability study found that the majority of the older adults were satisfied with the interface and content. All health practitioners (100%) agreed WeFit is easy to use and agreed that it can guide them in giving medical advices.

Conclusion: WeFit mobile app has been successfully developed, validated, and tested for acceptance among the older adults and health practitioners.

Objective: Mobile health (mHealth) applications are emerging as important healthcare technologies that can provide cost savings, better access to care, contribute to improved clinical outcomes, and support public health. An increasing number of mobile health (mHealth) applications are becoming available to download and use on mobile devices. However, unlocking this potential requires ensuring widespread acceptance and adoption of these applications. In this context, the aim of the study is to determine the impact of individuals' digital literacy levels on mobile health application usability and the mediating role of patient expertise in this impact.

Methods: The population of our study consists of individuals who reside in Yozgat city center and are 18 years old and over. Within the scope of the study, 647 individuals who agreed to participate in the research were reached. A survey form consisting of four sections (Socio-demographic characteristics, Digital Literacy Scale, mHealth App Usability Questionnaire, and Patient Expertise Scale) was used as a data collection tool in the study. Descriptive statistical methods were used to analyze the data and partial least squares path analysis (PLS-SEM) was used to analyze the research model.

Results: Digital literacy affects both patient expertise (β = 0.790, t = 35.560, p = 0.000) and mHealth app usability (β = 0.831, t = 46.020, p = 0.000). Additionally, it has been determined that patient expertise has a mediating role in the effect of digital literacy on mHealth app usability (β = 0.536, t = 17.477, p = 0.000).

Conclusions: It appears that individuals' digital literacy is an important precursor to the usability of mHealth apps and increases their usage experience. In this sense, it is thought that the concept of digital literacy can be used to increase the usability of mHealth apps for individuals. Overall, the findings provide new evidence for the healthcare context by integrating user diversity, particularly individuals' digital literacy, mHealth apps, and prior experience with mHealth.

Background: Although smartphone application for smoking cessation was considered a promising strategy, there were scarce studies on the combination of usual interventions and apps for smoking cessation in China. Our study aimed to evaluate the efficacy of the Cigarette-Burning application combined with medication intervention for smoking cessation.

Methods: A parallel, open-label randomized clinical trial was conducted with a ratio of 1:1 allocation into the bupropion plus app group and bupropion group. All participants received bupropion intervention. Besides, participants in the bupropion plus app group were required to download and use the Cigarette-Burning app. Follow-up visits were conducted at weeks 1, 2, 4, 9, 12, and 24 after initiation of treatment.

Results: Four hundred participants were eventually included and analyzed from July 2019 to June 2021. The continuous abstinence rate at 9-12 weeks was significantly higher in the bupropion plus app group (39.5%) than in the bupropion group (27.5%) (OR = 1.64, 95% CI: 1.04-2.60, p < .05). The similar result was found for the 24-week sustained abstinence rate. The results of subgroup analysis expressed that the 9-12 weeks continuous abstinence rate in the bupropion plus app group was significantly higher than the bupropion group when the age of participants ≥ 50, the education level was college and above, FTND scores > 5, age at starting smoking ≤ 18 (p < .05).

Conclusions: Our study found that the intervention combined with the Cigarette-Burning smartphone application is more effective than medication alone, and the application for smoking cessation could be an accessible complement to smoking cessation medication treatment.

Objective: This study aimed to investigate the potential of LINE, a major messaging app and social media platform in Japan, as an effective tool to enhance the health and dietary behaviors of young Japanese women who face health and dietary challenges.

Methods: A 6-week randomized controlled trial employing an intention-to-treat analysis was conducted on first-year female students (age range, 18-23 years) from one university and two junior colleges in Mie Prefecture. The participants were allocated to either an intervention group (n = 54) or a control (n = 55) group. The intervention group received health information focusing on proper intake and intake methods to maintain an appropriate weight and dietary balance via LINE 18 times over 6 weeks (3 times per week), whereas the control group continued their usual lifestyle without any additional intervention.

Results: The results revealed a significant increase in the percentage of participants in the intervention group who rated their health as "unhealthy" (from 25.9% to 40.3%). This may be attributed to increased health awareness among the participants, which led to more critical self-assessments-a phenomenon often referred to as the "health awareness paradox." Despite this increase in perceived unhealthiness, the intervention group showed a significant increase in the intakes of iron, vitamin C, dietary fiber, and potassium, indicating improved nutritional behavior.

Conclusion: The provision of health information through LINE over a 6-week period demonstrated potential as a tool for health education among young Japanese women. However, the observed increase in "unhealthy" self-rated health underscores the complexity of such interventions, suggesting that while nutritional behavior may improve, increased health awareness can paradoxically lead to more negative self-assessments. Further research is needed to explore the optimal duration and content of health information delivered via social media apps to maximize their effectiveness for health interventions.

Background: Telemedicine is one of the major trends in the evolution of modern medicine. Telemedicine encompasses a wide range of services with different characteristics. Healthcare organisations know limited information on developing and utilising different types of telemedicine service programmes as well as factors and spatial and temporal characteristics that influence their development.

Objective: To analyse the factors influencing the development of telemedicine, and to explore the priority order of different telemedicine services carried out by healthcare institutions, as well as the spatiotemporal evolution characteristics.

Methods: This study selected Zunyi City, a national pilot city for telemedicine in China, and employed multinomial logistic regression to analyse factors influencing the provision of different types of telemedicine service programmes by healthcare institutions and evaluate the spatial and temporal evolutionary characteristics of spatially visualised telemedicine service programmes.

Results: When the price of services increased, providers were more inclined to conduct teleconsultation (OR: 1.023) and telepathology (OR: 1.058) than tele-imaging, and the willingness to conduct telecardiology (OR: 0.775) and telemetry (OR: 0.997) was relatively low. Patients' out-of-pocket payments increased, and providers' willingness to conduct teleconsultations (OR: 49.401) and telepathology (OR: 5.039) increased. Healthcare organisations at higher level were more willing to carry out teleconsultation (OR: 14.052), telepathology (OR: 8.071) and telemetry (OR: 13.113). Compared with private hospitals, public hospitals were 17.760, 12.248 and 87.860 times more likely to conduct teleconsultations, telecardiology and telepathology than tele-imaging. The effectiveness of telemedicine development may be related to the level of local economic development.

Conclusion: Medical institutions carry out telemedicine service programmes with a certain order of priority. Their decisions are often influenced by various factors such as price, out-of-pocket payment ratio and level and attribute of the healthcare organisation. The development of telemedicine may follow an inverted 'U' pattern with the level of regional economic development.

Objective: The market for smartphone apps tracking menstrual cycles has expanded in recent years. These apps market themselves as empowering users to achieve their reproductive goals and maximize the chance of pregnancy. This paper presents the first open-access quantification of menstrual tracking app downloads globally, covering both the Global North and South. We also explore macro and micro-level reasons for app usage, testing national associations with downloads and analyzing user reviews.

Methods: We use data on app installations, reviews, and ratings from the Google Play Store and Apple App Store to estimate global app downloads using a Bayesian model. We perform regressions to test for national predictors of use, and multilingual topic models to analyze/cluster reviews left by users to understand individual reasons for use.

Results: We find that the majority of downloads are for three apps: Clue, Flo, and Period Tracker. Higher modern contraceptive prevalence and internet access are associated with more downloads, while low-income countries tend to have fewer. In low-income countries, a higher unmet need for family planning and total fertility rate are associated with more downloads. Individual reviews reveal the most common reasons for use are menstrual cycle tracking, achieving a pregnancy, community engagement, and avoiding pregnancy.

Conclusion: Existing research on menstrual tracking apps is largely confined to the Global North, but our study finds the use of these apps to be as prevalent throughout the Global South. Future research needs to urgently understand the implications these apps could have in a diversity of contexts.

Introduction: Applying and leveraging artificial intelligence within the healthcare domain has emerged as a fundamental pursuit to advance health. Data-driven models rooted in deep learning have become powerful tools for use in healthcare informatics. Nevertheless, healthcare data are highly sensitive and must be safeguarded, particularly information related to sexually transmissible infections (STIs) and human immunodeficiency virus (HIV).

Methods: We employed federated learning (FL) in combination with homomorphic encryption (HE) for STI/HIV prediction to train deep learning models on decentralized data while upholding rigorous privacy. The dataset included 168,459 data entries collected from eight countries between 2013 and 2018. The data for each country was split into two groups, with 70% allocated for training and 30% for testing. Our strategy was based on two-step aggregation to enhance model performance and leverage the area under the curve (AUC) and accuracy metrics and involved a secondary aggregation at the local level before utilizing the global model for each client. We introduced a dropout approach as an effective client-side solution to mitigate computational costs.

Results: Model performance was progressively enhanced from an AUC of 0.78 and an accuracy of 74.4% using the local model to an AUC of 0.94 and an accuracy of 90.7% using the more advanced model.

Conclusion: Our proposed model for STI/HIV risk prediction surpasses those achieved by local models and those constructed from centralized data sources, highlighting the potential of our approach to improve healthcare outcomes while safeguarding sensitive patient information.

Background and aims: Guidelines for exercise recommendations are typically designed for the population as a whole and do not account for individual differences, making it challenging to provide personalized exercise training for individuals with complex conditions. To address this issue, this study aimed to develop PAHFKB (Physical Activity-Heart Failure Knowledge Base), a knowledge-based system for personalized exercise prescription (EP) for heart failure (HF), by mining, analyzing, and organizing existing literature and data on the relationship between physical activity (PA) and HF.

Methods: Firstly, 3186 citations on PAHF were gathered from PubMed. Then, the data standards for personalized PAHF were defined with the entity-relationship model. Following data collection in accordance with these standards, PAHFKB was developed using MySQL and ASP.NET, integrating elaborate and diverse PAHF evidence, knowledge-based EP and visualization tools.

Results: PAHFKB (pahfkb.sysbio.org.cn) incorporated 357 studies published between 1989 and 2021, involving over 900,000 subjects from 43 countries. And 1010 PAHF items were extracted, encompassing 357 exercise training protocols, 333 outcomes, and 42 risk factors for HF prevention and intervention. Among all protocols, the most frequently employed regimen consisted of three 60-minute sessions of moderate-intensity aerobic exercise training on a weekly basis.

Conclusion: PAHFKB is an online system designed to support personalized EP in HF management. It incorporates diverse tools and visualization and will promote personalized decision support, establish data standards, and advance interpretable artificial intelligence in digital health. Ultimately, it will enhance clinical practice and digital therapy in the prevention and intervention of HF.

Tuberculosis (TB) disease has been of public health interest for decades. Its effect on women is more pronounced in their reproductive years. Nonadherence to treatment among people with TB undermines treatment outcomes and worsens the disease. Directly observed therapy for TB requires patients to take their medicine under observation. Mobile phones present the most potential in providing privacy. This study examined the use of short message service (SMS) reminders for monitoring TB treatment adherence among women in the Greater Accra Region, Ghana. A quasi-experimental approach was used to assess the effect of SMS reminder intervention in two phases. Ten facilities were divided into two groups of five, with 105 and 125 for intervention and control groups, respectively. Adherence was assessed using the Medication Adherence Rating Scale for both groups before and after implementing the intervention and thereafter compared. STATA 15 was used to analyze data. Bivariate analyses were performed to assess medication uptake and factors associated with medication nonadherence between the intervention and control groups. p Values < .05 were considered significant. The SMS reminder messages had positive effect on adherence (odds ratio = 4.45, 95% confidence interval = 1.64, 12.11, p < .01). Educational level was the only variable significantly associated with TB treatments adherence. The findings suggest that a one-way SMS is feasible for supporting adherence to TB treatment in Ghana and other similar contexts.

Background: Heart failure (HF) is a chronic disease characterized by high mortality and healthcare expenditures. Digital health solutions, including mobile health applications (apps), offer opportunities to enhance patients' self-care and quality of life. This qualitative study aimed to explore expectations, experiences, and usage behaviour of HF-patients regarding a self-care app (DoctorME app).

Methods: Semi-structured interviews were conducted at 2-3 weeks (initial: n = 38), and 4-6 months (post: n = 45) of app use across four European countries. Most patients were male (initial: 84%; post: 78%), aged 60-69 years (initial and post: 29%), with mild HF symptoms. Interviews were transcribed, pseudonymised, and analysed using qualitative content analysis.

Results: Five key themes were identified: 1) expectations, 2) perceived usability and benefit, 3) usage behaviour and experiences, 4) self-care, and 5) social influences. Patients expected and valued continuous monitoring of vital signs and weight, early detection of deterioration, and quick feedback. The app was considered user-friendly, with most patients using it as recommended (eight times per month). Those reporting improved self-care attributed it to increased awareness and a sense of security. Patients with established self-care routines did not perceive any additional benefit. Patients' perceptions on the impact of healthcare professionals' and relatives opinions on app use were divided.

Conclusions: User-friendliness, continuous monitoring, rapid feedback, and e-learning modules are crucial for integrating self-care apps into daily HF care. While technical reliability and individualisation may enhance long-term use, most HF patients considered the app as a complement to, not a replacement for, professional healthcare guidance.