BACKGROUND AND OBJECTIVE

First responders must be physically and mentally healthy to ensure effective emergency response. However, literature showed that Filipino first responders continue to have elevated levels of stress and increased risk for post-traumatic stress and other mental health problems months after their deployment. The “Mi Salud” app was created to help Filipino first responders, their team leaders, and their agencies monitor and manage the responders’ real-time stress levels before, during, and after their deployment more effectively.

The “Mi Salud” app was pretested with Filipino first responders (n=30) to establish convergent validity using existing validated scales measuring the same construct. Participants also completed a Likert scale and questionnaire to assess user experience and app recommendations. During the rollout, first responders (n=32) tested the app and completed a survey on user experience and app recommendations. A focus group discussion (n=11; FGD) was conducted to further explore their experiences with the app. Survey data were analyzed using descriptive statistical methods, while FGD data were examined through thematic analysis.

Results from the online survey showed that the app was generally found to be helpful and that the recommendations within the app were useful. The emerging themes from the FGD corroborated many of the themes from the survey, particularly the benefits of using the app and the app’s ease of use. Positive effects were observed both on the responders and on the responders’ team leader and teammates, which further established the value of the “Mi Salud” app.

The findings show that the “Mi Salud” stress check-app may serve as a useful tool for monitoring and managing the stress levels, a critical aspect for Filipino first responders to maintain optimal functioning during deployments and daily activities.

BACKGROUND

Diabetes Mellitus Type 2 is a significant global health issue with a high prevalence in the Philippines. Managing this condition effectively is crucial, and digital technologies, particularly smartphone (mHealth) applications, have emerged as a potential tool in diabetes self-management.

This study evaluated the effectiveness of smartphone (mHealth) application use in achieving glycemic control among adults with Type 2 Diabetes Mellitus, focusing on HbA1c levels and medication adherence.

This systematic review and meta-analysis, adhering to PRISMA guidelines, analyzed randomized controlled trials from databases like PubMed and Embase, comparing interventions using mHealth applications with standard care. The primary measures were HbA1c levels and medication adherence.

Ten studies involving 20,984 participants were included in the meta-analysis. Using mHealth applications led to an average HbA1c reduction of 0.36%, indicating improved glycemic control. There was considerable heterogeneity (I2 = 91%) because of the clinical and methodological diversity of the included studies. Subgroup analysis showed that the younger and older age groups, shorter and longer T2DM duration, and lower and higher HbA1c baseline benefited from its use. Sensitivity analysis still showed high heterogeneity (95%-97%), reflecting clinical diversity. A narrative analysis of two studies highlighted the utility of mHealth applications in tracking diet, physical activity, and vital stats, aiding medication adherence through reminders and data sharing with healthcare providers.

This systematic review and meta-analysis showed the effectiveness of mHealth application use in achieving glycemic control among adults with Type 2 Diabetes Mellitus by improving HbA1c levels and medication adherence. Integrating mHealth applications as adjuncts in family and community medicine as part of personalized care for managing type 2 diabetes in the Philippines can help achieve glycemic control and medication adherence. Future studies should focus on longitudinal assessments, exploring cultural and linguistic factors in the Filipino context to optimize diabetes care within this specialized medical framework.

INTRODUCTION: Due to COVID-19 pandemic, many have shifted into working at home which led to physical inactivity. This may cause musculoskeletal discomfort, chronic disease, muscle atrophy and spinal imbalance due to improper and prolonged sitting posture. Since mobile devices are relatively available for most of the office workers, there were still a lack of evidence-based mobile applications that can counteract the inactivity through exercises, which led to the researchers to create an application called SitMate that consists of evidence-based exercises which aimed to prevent musculoskeletal discomfort among a business process outsourcing company Workforce Management Personnel (BPO-WMP). METHODS: Eleven participants (18-40 years old) full-time, work-from-home BPO-WMP were randomized into Treatment Group(TG)(n=6) and Control Group (CG)(n=5). The TG received one month intervention with the use of SitMate Application containing relaxation exercises, range of motion exercises and stretching exercises, and notifications for postural correction while the CG continued their usual working schedule. RESULTS: There were no significant differences between two groups on all body parts that were measured using the Cornell Musculoskeletal Discomfort Questionnaire, and no significant differences in the intragroup pre-test and post-test scores on all body parts between TG and CG. For the intra-group post-test of the TG, there were noted improvements on the hip/buttock, right shoulder, upper back (median = 0) and right wrist (median = 1.5). There was also a noted increase in discomfort on the neck (median = 1.5) and lower back (median = 3). For the post-test of the CG, there were noted improvements on the right shoulder, right wrist (median = 0) and lower back (median = 1.5). CONCLUSION This study has shown that the SitMate application does not effectively reduce the prolonged sitting-related discomfort among the personnel after 1 month of intervention.
mobile application ; musculoskeletal discomfort ; physical inactivity ; low back pain ; posture

Aged ; Feasibility Studies ; Health Status ; Humans ; Mobile Applications ; Treatment Outcome

BACKGROUND: To combat coronavirus disease 2019 (COVID-19), many countries have used contact tracing apps, including Japan's voluntary-use contact-confirming application (COCOA). The current study aimed to identify industry and workplace characteristics associated with the downloading of this COVID-19 contact tracing app. METHODS: This cross-sectional study of full-time workers used an online survey. Multiple logistic regression analysis was used to evaluate the associations of industry and workplace characteristics with contact tracing app use. RESULTS: Of the 27,036 participants, 25.1% had downloaded the COCOA. Workers in the public service (adjusted odds ratio [aOR] = 1.29, 95% confidence interval [CI] 1.14-1.45) and information technology (aOR = 1.38, 95% CI 1.20-1.58) industries were more likely to use the app than were those in the manufacturing industry. In contrast, app usage was less common among workers in the retail and wholesale (aOR = 0.87, 95% CI 0.76-0.99) and food/beverage (aOR = 0.81, 95% CI 0.70-0.94) industries, but further adjustment for company size attenuated these associations. Workers at larger companies were more likely to use the app. Compared with permanent employees, the odds of using the app were higher for managers and civil servants but lower for those who were self-employed. CONCLUSIONS Downloading of COCOA among Japanese workers was insufficient; thus, the mitigating effect of COCOA on the COVID-19 pandemic is considered to be limited. One possible reason for the under-implementation of the contact tracing app in the retail and wholesale and food/beverage industries is small company size, as suggested by the fully adjusted model results. An awareness campaign should be conducted to promote the widespread use of the contact tracing app in these industries.
Adult ; COVID-19/prevention & control* ; Contact Tracing/methods* ; Cross-Sectional Studies ; Female ; Humans ; Industry/classification* ; Japan/epidemiology* ; Male ; Middle Aged ; Mobile Applications/statistics & numerical data* ; SARS-CoV-2 ; Smartphone ; Workplace/statistics & numerical data*

The reference sites of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) were renewed in 2019. The DG Santé good practice Mobile Airways Sentinel networK was reviewed to meet the objectives of the EIP on AHA. It included 1) Management of care process, 2) Blueprint of digital transformation, 3) EIP on AHA, innovation to market, 4) Community for monitoring and assessment framework, 5) Political, organizational, technological and financial readiness, 6) Contributing to European co-operation and transferability, 7) Delivering evidence of impact against the triple win approach, 8) Contribution to the European Digital Transformation of Health and Care and 9) scale of demonstration and deployment of innovation
Asthma ; Masks ; Mobile Applications ; Rhinitis

Mobile healthcare services have been applied to manage some diseases, particularly chronic diseases. We aimed to evaluate the utility of a mobile application in nutritional intervention by observing cases of a mobile application in a series of patients with GDM. We provided a mobile-based intervention to GDM patients and collected biochemical and nutritional information. The mobile-based nutritional intervention was effective in controlling carbohydrate intake and improving blood glucose level for patients with GDM.]]>
Blood Glucose ; Child ; Chronic Disease ; Delivery of Health Care ; Diabetes, Gestational ; Diet Therapy ; Diet, Food, and Nutrition ; Female ; Humans ; Mobile Applications ; Mothers ; Pregnancy ; Prevalence

This paper designs a bluetooth-based low-power multi-parameter monitoring system. The system is mainly composed of ECG signal acquisition, respiratory signal acquisition, body temperature acquisition, bluetooth 4.0 transmission module and Android mobile phone APP display. The system collects the corresponding physiological signals through various collection parts, and can realize the monitoring of three physiological signals of electrocardiogram, respiration and body temperature. The Android mobile APP can display ECG, respiratory waveform and temperature data in real time. The system is small in size and low in power consumption, and has a good application prospect in portable and wearable medical applications.
Body Temperature ; Cell Phone ; Electrocardiography ; Humans ; Mobile Applications ; Monitoring, Physiologic/instrumentation* ; Respiratory Rate

OBJECTIVES: This pilot study aimed to provide an overview of the potential for blockchain technology in the healthcare system. The review covers technological topics from storing medical records in blockchains through patient personal data ownership and mobile apps for patient outreach. METHODS: We performed a preliminary survey to fill the gap that exists between purely technically focused manuscripts about blockchains, on the one hand, and the literature that is mostly concerned with marketing discussions about their expected economic impact on the other hand. RESULTS: The findings show that new digital platforms based on blockchains are emerging to enabling fast, simple, and seamless interaction between data providers, including patients themselves. CONCLUSIONS: We provide a conceptual understanding of the technical foundations of the potential for blockchain technology in healthcare, which is necessary to understand specific blockchain applications, evaluate business cases such as blockchain startups, or follow the discussion about its expected economic impacts.
Artificial Intelligence ; Commerce ; Delivery of Health Care* ; Foundations ; Genomics ; Hand ; Humans ; Information Storage and Retrieval ; Marketing ; Medical Records ; Mobile Applications ; Ownership ; Pilot Projects ; Telemedicine

OBJECTIVES: This study was conducted to examine the effects of mobile health (mHealth), using mobile phones as an intervention for weight loss in obese adults. METHODS: An electronic search was carried out using multiple databases. A meta-analysis of selected studies was performed. The effects of mHealth were analyzed using changes in body weight and body mass index (BMI). RESULTS: We identified 20 randomized controlled trials (RCTs) involving 2,318 participants who fit our inclusion criteria. The meta-analysis showed that body weight was reduced with a weighted mean difference (WMD) of −2.35 kg (95% confidence interval [CI], −2.84 to −1.87). An examination of the impact of duration of intervention showed that weight loss was greater after 6 months of mHealth (WMD = −2.66 kg) than between three and four months (WMD = −2.25 kg); it was maintained for up to 9 months (WMD = −2.62 kg). At 12 months, weight loss was reduced to a WMD of −1.23 kg. BMI decreased with a WMD of −0.77 kg/m2 (95% CI, −1.01 to −0.52). BMI changes were not statistically significant at 3 months (WMD = −1.10 kg/m2), but they were statistically significant at 6 months (WMD = −0.67 kg/m2). CONCLUSIONS: The use of mHealth for obese adults showed a modest short-term effect on body weight and BMI. Although the weight loss associated with mHealth did not meet the recommendation of the Scottish Intercollegiate Guideline Network, which considers a reduction of approximately 5 to 10 kg of the initial body weight as a successful intervention. Well-designed RCTs are needed to reveal the effects of mHealth interventions.
Adult* ; Body Mass Index ; Body Weight ; Cell Phones ; Humans ; Mobile Applications ; Obesity ; Telemedicine* ; Weight Loss