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.

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*

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

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

OBJECTIVES: Ecological momentary assessment (EMA) methods are known to have validity for capturing momentary changes in variables over time. However, data quality relies on the completion rates, which are influenced by both participants' characteristics and study designs. This study applied an EMA method using a mobile application to assess momentary moods and stress levels in patients with Moyamoya disease to examine variables associated with EMA completion rates. METHODS: Adults with Moyamoya disease were recruited from a tertiary hospital in Seoul. Patients with cognitive impairment were excluded. The EMA survey was loaded as a mobile application onto the participants' personal smartphones. Notifications were sent at semi-random intervals four times a day for seven consecutive days. Daily completion rates were calculated as the percentage of completed responses per day; overall completion rates were calculated as the proportion of completed responses per total of the 28 scheduled measures in the study and assessed through a descriptive analysis, t-test, ANOVA, and regression analysis, with mixed modeling to identify the point at which the daily completion rate significantly decreased. RESULTS: A total of 98 participants responded (mean age, 41.00 ± 10.30 years; 69.4% female; 75.5% married). The overall completion rate was 70.66%, with no gender or age differences found. The daily completion rate decreased significantly after day 5 (p = 0.029). CONCLUSIONS: Obtaining a good completion rate is essential for quality data in EMA methods. Strategic approaches to a study design should be established to encourage participants throughout a study to improve completion rates.
Adult ; Cognition Disorders ; Data Accuracy ; Epidemiologic Factors ; Female ; Guideline Adherence ; Humans ; Methods ; Mobile Applications ; Moyamoya Disease ; Seoul ; Smartphone ; Tertiary Care Centers

OBJECTIVES: To describe the step-by-step person-centered, theory-based development of the KELA.AE app for Arabic speaking hemodialysis patients. METHODS: A step-by-step person-driven theory-based approach was conducted to develop a self-monitoring and educational dietary app for hemodialysis patients. The development follows the Integration, Design, Assessment, and Sharing (IDEAS) framework. Qualitative, semi-structured interviews with 6 hemodialysis patients and 6 healthcare practitioners (dietitians and nephrologists) were performed to assess the need for an app, the willingness to use an app, and features desired in an app. RESULTS: The KELA.AE app, which includes a self-monitoring feature, CKD-friendly recipes, and a theory-based, evidence-based educational feature was developed. Qualitative analysis of interviews revealed two predominant themes from patient interviews ‘Experience with the diet’, ‘App evaluation’, and one theme from interviews with healthcare practitioners ‘App evaluation’. Patients expressed frustration with current accessibility of dietary information along with the need for educational materials in the app. The review of the KELA.AE prototype was positive overall, and patients reported a willingness to use the app. Healthcare practitioners considered the app accurate, simple, and culturally sensitive but expressed concerns about app misuse and the replacement of healthcare practitioners. CONCLUSIONS: The KELA.AE app was found to be satisfactory and supportive of the participants' needs. Changes were made to the app as suggested during the interviews.
Arabs ; Delivery of Health Care ; Diet ; Frustration ; Health Behavior ; Humans ; Kidney Failure, Chronic ; Mobile Applications ; Renal Dialysis ; Telemedicine

Recent studies have developed simple techniques for monitoring and assessing sleep. However, several issues remain to be solved for example high-cost sensor and algorithm as a home-use device. In this study, we aimed to develop an inexpensive and simple sleep monitoring system using a camera and video processing. Polysomnography (PSG) recordings were performed in six subjects for four consecutive nights. Subjects' body movements were simultaneously recorded by the web camera. Body movement was extracted by video processing from the video data and fi ve parameters were calculated for machine learning. Four sleep stages (WAKE, LIGHT, DEEP and REM) were estimated by applying these fi ve parameters to a support vector machine. The overall estimation accuracy was 70.3 ± 11.3% with the highest accuracy for DEEP (82.8 ± 4.7%) and the lowest for LIGHT (53.0 ± 4.0%) compared with correct sleep stages manually scored on PSG data by a sleep technician. Estimation accuracy for REM sleep was 68.0 ± 6.8%. The kappa was 0.19 ± 0.04 for all subjects. The present non-contact sleep monitoring system showed suffi cient accuracy in sleep stage estimation with REM sleep detection being accomplished. Low-cost computing power of this system can be advantageous for mobile application and modularization into home-device.
Machine Learning ; Methods ; Mobile Applications ; Polysomnography ; Sleep Stages ; Sleep, REM ; Support Vector Machine