Interactive Journal of Medical Research最新文献

Background: Dengue fever remains the most significant vector-borne disease in Southeast Asia, imposing a substantial burden on public health systems. Global warming and increased international mobility may exacerbate the disease's prevalence. Furthermore, the unprecedented COVID-19 pandemic may have influenced the epidemiological patterns of dengue.

Objective: This study aimed to evaluate epidemiological changes in dengue incidence in Southeast Asia.

Methods: We conducted a retrospective, multicountry ecological study analyzing trends in dengue incidence in 7 Southeast Asian countries from January 2000 to December 2023. Data were extracted from official World Health Organization reports and national health department databases. Countries with data that were incomplete, inconsistent, or not publicly available were excluded from the final analysis. Annual incidence rates were analyzed, and linear trends were calculated to assess long-term patterns.

Results: Epidemiological data from 7 Southeast Asian countries, comprising Thailand, Singapore, Vietnam, Malaysia, the Philippines, Cambodia, and Taiwan, were analyzed across the 24-year study period. A notable nadir in dengue cases was observed coinciding with the COVID-19 pandemic. Significant increasing trends in dengue incidence were identified in Singapore, Vietnam, Malaysia, and the Philippines (slopes: 8.243, 6.513, 8.737, and 8.172; R2 values: 0.14, 0.34, 0.345, and 0.46, respectively, all P<.05).

Conclusions: Dengue fever continues to pose a significant public health challenge in Southeast Asia. Our analysis demonstrates a substantial increase in dengue cases in several countries over the study period. While a temporary decline was observed during the COVID-19 pandemic, a subsequent resurgence of cases highlights the persistent threat of dengue in the region. These findings underscore the critical need for sustained surveillance and innovative control strategies to mitigate the impact of dengue in Southeast Asia.

Background: Electronic resources have become a predominant modality for health information dissemination in recent years. eHealth literacy (eHL) means individuals' competencies to effectively acquire and use health information from electronic sources. Enhancing eHL is thus essential to facilitate individuals' effective engagement with electronic resources and promote improved health management.

Objective: This scoping review aimed to synthesize the characteristics of eHL interventions, thereby providing a reference for future intervention strategies.

Methods: A comprehensive search of PubMed, Embase, Cochrane Library, Web of Science, ProQuest, CINAHL, CNKI, VIP, Wan Fang Data, and Sino Med limited to Chinese and English-language studies published before August 2024 was conducted. The interventional studies included had the explicit primary objective of enhancing eHL. We also incorporated studies that assessed eHL as a secondary outcome or mediator influencing health behaviors or clinical outcomes. All publications were required to provide publicly accessible complete datasets. We excluded conference abstracts and protocols. Academic theses and dissertations were included if they underwent institutional quality assurance through rigorous academic review processes and met predefined eligibility criteria.

Results: A total of 35 studies were included in this review. The most prevalent eHL interventions (12/35, 34%) were delivered via mobile apps and devices in various settings, including educational institutions, public spaces, health care facilities, and community centers. These interventions predominantly focused on enhancing information literacy, health literacy, and computer literacy across the 6 domains of eHL: traditional, health, information, scientific, media, and computer literacy. A majority of the interventions were conducted on a weekly basis (6/13, 46%) and had a duration of 24 weeks (6/35, 17%). However, 77% (27/35) of interventions did not assess long-term effects. The primary outcomes of eHL interventions encompassed perceived eHL, actual eHealth knowledge and skills, health literacy, health behavior, and clinical outcomes, with 86% (30/35) indicating positive effects. The eHealth Literacy Scale was the most frequently used assessment tool.

Conclusions: This study synthesizes the characteristics of eHL interventions. Current eHL interventions exhibit limitations in theoretical grounding, longitudinal tracking, and traditional or media literacy components. Overreliance on self-reported metrics constrains validity assessment. Future work should strengthen theoretical frameworks, integrate objective metrics, and enhance longitudinal designs.

Background: The pathogenesis of atherosclerotic thrombosis primarily involves platelet activation and aggregation, making antiplatelet therapy the cornerstone of treatment for such diseases.

Objective: This meta-analysis aimed to compare the safety and efficacy of aspirin and indobufen in antiplatelet therapy for patients with atherosclerotic diseases.

Methods: We searched the Cochrane Library, PubMed, Embase, Web of Science, and the Chinese Wanfang databases. The literature was screened according to predefined inclusion and exclusion criteria. Risk ratio (RR) was used to assess the magnitude of risk associated with exposure and our inclusion criteria are as follows: (1) the study population comprised adults (aged 18 years and older) with coronary heart disease caused by coronary artery atherosclerosis or stroke caused by intracranial atherosclerosis; (2) the intervention was represented by indobufen in the study groups versus aspirin in the control groups; (3) the primary outcome was the incidence of major adverse cardiovascular and cerebrovascular events or any bleeding or Bleeding Academic Research Consortium 2/3/5 bleeding; (4) the secondary outcomes were cardiovascular death, myocardial infarction, and ischemic stroke; adverse cardiovascular events such as coronary thrombus reformation, heart failure, myocardial infarction, stroke, angina pectoris, and cardiovascular death; stroke; myocardial infarction; and cardiovascular death; and (5) the studies were randomized clinical trials with either crossover or parallel designs or prospective observational trials.

Results: Eighteen trials with a total of 12,981 patients were included in this study. Compared to aspirin, indobufen reduced the risk of (1) bleeding events (RR 0.54, 95% CI 0.41-0.71; P<.0001), (2) Bleeding Academic Research Consortium 2/3/5 bleeding (RR 0.50, 95% CI 0.26-0.94; P=.03), (3) adverse cardiovascular events (RR 0.43, 95% CI 0.30-0.61; P<.00001), and (4) myocardial infarction (RR 0.60, 95% CI 0.41-0.89; P=.01). However, there were no significant differences between the 2 groups in terms of major adverse cardiovascular and cerebrovascular events, stroke, or cardiovascular mortality.

Conclusions: Compared with aspirin, indobufen demonstrated better safety and was not inferior to aspirin in terms of efficacy, with superior results in some aspects (eg, fewer risks of adverse cardiovascular events and myocardial infarction). Further studies with larger sample sizes or longer follow-up periods may provide additional evidence.

Background: Body dissatisfaction is a condition where individuals are dissatisfied with their physical appearance. It has become a global issue, especially among children and emerging adults. A growing number of digital interventions have been developed to address body dissatisfaction in children and emerging adults; however, controversies remain regarding their efficacy, underscoring the need for a comprehensive synthesis of current evidence.

Objective: This systematic review aimed to explore the effectiveness of digital interventions in improving body image-related outcomes among children and emerging adults.

Methods: From inception to April 24, 2024, a literature search was performed across 7 databases-PubMed, Web of Science, MEDLINE, EBSCO (Elton B Stephens Company), Cochrane Library, CNKI (China National Knowledge Infrastructure), and WANFANG-to identify randomized controlled trials (RCTs) with a predefined set of inclusion criteria. This systematic review was reported in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. Study selection, data extraction, and risk of bias assessment using the Cochrane Risk-of-Bias Tool 2.0 were conducted independently by 2 researchers. Standardized mean differences (SMDs) and 95% CIs from the included RCTs were calculated for the meta-analysis. Heterogeneity was assessed with I² values. A fixed-effects model was used when I²≤50%, and a random-effects model was selected when I²>50%.

Results: Twenty RCTs with 5251 participants (2610 in intervention groups and 2641 in control groups) met the inclusion criteria. Digital interventions included web pages, mobile apps, computer-based videos, computer-based sessions, internet-based sessions, internet games, chatbots, podcasts, and social media. Our results indicate that digital interventions could significantly improve body dissatisfaction (SMD=0.38, 95% CI -0.63 to -0.13; I2=55%; P=.003), physical appearance comparison (SMD=-0.24, 95% CI -0.45 to -0.03; I2=0%; P=.003), thin-ideal internalization (SMD=-0.28, 95% CI -0.36 to -0.2; I2=41%; P<.001), self-esteem (SMD=0.14, 95% CI 0.07-0.21; I2=21%; P<.001), self-compassion (SMD=0.55, 95% CI 0.33-0.78; I2=35%; P<.001), and depression (SMD=-0.59, 95% CI -0.97 to -0.21; I2=0%; P=.002), with small to medium effect sizes.

Conclusions: While digital interventions improved body dissatisfaction among children and emerging adults, additional well-designed, rigorous, and large-scale RCTs are needed to decisively provide estimates of the effectiveness of digital interventions on body dissatisfaction.

Background: Digitally delivered physical exercise interventions are becoming increasingly popular in addressing the obesity epidemic. However, there remains uncertainty on their efficacy regarding the reduction of body weight (BW) and body fat, which may, at least partly, be due to variations in study designs and inconsistent adherence to international physical activity (PA) guidelines.

Objective: This study aimed to evaluate the effectiveness of digital exercise interventions based on PA guidelines in reducing BW and fat in adults with overweight or obesity, as well as their impact on PA-related factors.

Methods: This review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Comprehensive searches were performed in October 2024 across PubMed, Cochrane Library, Web of Science, and Ovid MEDLINE databases. Eligible studies included adults (aged ≥18 years) with objectively confirmed overweight or obesity who used digital interventions aligned with international PA guidelines. Risk of bias was evaluated using the Cochrane Risk of Bias (version 2) tool for randomized controlled trials and the Risk of Bias in Nonrandomized Studies of Interventions tool for nonrandomized studies. A random-effects meta-analysis with Hartung-Knapp adjustment was performed using R software.

Results: Out of 4948 studies identified, 188 (3.8%) were screened in full and 30 (0.6%) met the eligibility criteria. Intervention durations ranged from 8 weeks to 24 months (average 6.4, SD 5.5 months). Meta-analysis showed that guideline-based digital exercise interventions significantly reduced BW compared to controls (mean difference [MD]=-1.17 kg; P=.003; I²=0.0%), with subgroup analysis revealing greater effects in active (nondigital) controls (MD=-1.23 kg; I²=7.5%) compared to passive (waitlist) controls (MD=-0.52 kg; I²=0.0%). A significant reduction in BMI was observed (MD=-0.50 kg/m²; P=.003), although with substantial heterogeneity (I²=70.0%), and subgroup analysis showed greater effects compared to passive controls (MD=-0.70 kg/m²; I²=43.1%) rather than to active controls (MD=-0.45 kg/m²; I²=74.5%). No significant effect was observed for body fat percentage overall (MD=-0.08%; P=.84; I²=7.4%). Qualitative analysis (including findings from noncomparative studies) showed that guideline-based digital exercise interventions led to significant reductions in BW (22/25, 88% studies; range -1.3 to -8.4 kg); BMI (19/23, 83% of studies; range -0.4 to -3.4 kg/m²); waist circumference (15/16, 94% of studies; range -2.1 to -9.2 cm), body fat percentage (9/9, 100% of studies; range -0.3% to -4.1%); and fat mass (7/7, 100% of studies; range -0.4 to -6.5 kg), while findings for waist-to-hip ratio and PA outcomes were inc

Background: A popular trend in depression forecasting research is the development of machine learning models trained with various types of smartphone sensor data and periodic self-ratings to derive early indications of changes in depression severity. While most works focus on model performance, there is little concern about the universal usability and reliable operation of such systems across smartphone platforms. This review serves as foundational work for the MENTINA clinical trial, which investigates smartphone-based health self-management for depression. The usability and reliability of mobile apps for depression are commonly perceived through the lens of the approaches and interventions offered rather than the reliability of the built-in mobile phone functions to support effortless and exact delivery of intended interventions.

Objective: This work aimed to synthesize existing systematic reviews to identify smartphone sensor modalities used in mental health monitoring and, building on this foundation, assess the cross-platform availability of these data streams using PhoneDB to inform the design and implementation of digital depression indication systems.

Methods: To identify the already used hardware and software sensors and their purposes in mental health monitoring, an umbrella review was conducted. Three electronic databases, including PubMed, Web of Science Core Collection, and Scopus, were searched using smartphone, sensor data, and depression keyword combination to retrieve relevant literature reviews published within the last 5 years (2019-2024). Once the initial search was completed, the extracted hardware sensors were checked for availability on Android and iOS smartphones by analyzing device specifications in PhoneDB over the last 10 years.

Results: The extracted data streams observed across the 9 included studies covered 16 hardware and 3 software data streams. Hardware data streams included accelerometers, barometers, battery levels, Bluetooth, cameras, cellular networks, GPSs, gyroscopes, humidity, light sensors, magnetometers, proximity sensors, sound sensors, step counters, temperature sensors, and Wi-Fi. Software data streams included app usage, call and message logs, and screen status. Hardware component availability on Android and iOS systems showed the changes in component trends from 2014 to 2024 as of September 2024, with the accelerometers, batteries, cameras, and GPSs remaining consistent on Android and iOS, while components such as gyroscopes, step counters, and barometers gradually increased over the years, particularly on Android.

Conclusions: Multiple data streams identified in the literature review showed a consistent increase in availability over time, enabling improved use of these outputs for depression forecasting and the training of machine learning models with diverse smartphone data, including sen