[Digital public health in Germany: status quo, challenges, and future perspectives : A position paper of the Digital Public Health Section of the German Public Health Association].

This position paper from the Digital Public Health Section of the German Public Health Association defines digital public health (DiPH) and describes its goals and potential. It also addresses the current situation and challenges as well as the need for action in Germany. The focus here is on the presentation of the nationwide promotion of (digital) health literacy; the application of DiPH in prevention, health promotion, and healthcare; the use of innovative preventive strategies for the prevention of non-communicable diseases; and the teaching of DiPH in academic public health programs.

Assessing the Digital Advancement of Public Health Systems Using Indicators Published in Gray Literature: Narrative Review.

Background: Revealing the full potential of digital public health (DiPH) systems requires a wide-ranging tool to assess their maturity and readiness for emerging technologies. Although a variety of indices exist to assess digital health systems, questions arise about the inclusion of indicators of information and communications technology maturity and readiness, digital (health) literacy, and interest in DiPH tools by the society and workforce, as well as the maturity of the legal framework and the readiness of digitalized health systems. Existing tools frequently target one of these domains while overlooking the others.

Design and Psychometric Evaluation of Nurses' Mobile Health Device Acceptance Scale (NMHDA-Scale): Application of the Expectation-Confirmation Theory.

Background: The use of mobile tools in nursing care is indispensable. Given the importance of nurses' acceptance of these tools in delivering effective care, this issue requires greater attention.

Objective: This study aims to design the Mobile Health Tool Acceptance Scale for Nurses based on the Expectation-Confirmation Theory and to evaluate it psychometrically.

Evaluating the Usability and Quality of a Clinical Mobile App for Assisting Physicians in Head Computed Tomography Scan Ordering: Mixed Methods Study.

Background: Among the numerous factors contributing to health care providers' engagement with mobile apps, including user characteristics (eg, dexterity, anatomy, and attitude) and mobile features (eg, screen and button size), usability and quality of apps have been introduced as the most influential factors.

Objective: This study aims to investigate the usability and quality of the Head Computed Tomography Scan Appropriateness Criteria (HAC) mobile app for physicians' computed tomography scan ordering.

Methods: Our study design was primarily based on methodological triangulation by using mixed methods research involving quantitative and qualitative think-aloud usability testing, quantitative analysis of the Mobile Apps Rating Scale (MARS) for quality assessment, and debriefing across 3 phases.

The Effect of a Mobile-Based Intervention on Physicians' Laboratory Test Ordering Behavior.

Utilizing digital tools, particularly mobile technologies, is viewed as a critical strategy to improve the efficient use of healthcare services. Quasi-experimental research was carried out with residents to investigate the impact of mobile-based feedback (MBF) on residents' laboratory test ordering behavior.

Comparing nnU-Net and deepflash2 for Histopathological Tumor Segmentation.

Machine Learning (ML) has evolved beyond being a specialized technique exclusively used by computer scientists. Besides the general ease of use, automated pipelines allow for training sophisticated ML models with minimal knowledge of computer science. In recent years, Automated ML (AutoML) frameworks have become serious competitors for specialized ML models and have even been able to outperform the latter for specific tasks.

Digital Transformation of the Healthcare Sector in Africa: First Results from a Study on Success Factors and Barriers for the Implementation of mHealth in South Africa and Tanzania.

This study explores the critical success factors and barriers to mHealth implementation in South Africa and Tanzania. Through an unstructured literature review and semi-structured interviews with eight mHealth experts, the study uncovers common challenges, including lack of alignment with user needs, inadequate government support, and sustainability issues. Critical success factors identified include user-friendly design and adaptable tools offered at low or no cost.

Insights into the Quality of Mobile Health Apps: Preliminary Results of an Analysis of MARS Scores.

Many mHelath applications have been developed, and the Mobile App Rating Scale (MARS) is a common tool for assessing them. This study aims to provide mean values for MARS scores found in recent literature. We systematically searched for literature in which MARS was used and analyzed them.

Serious Games in Orofacial Myofunctional Disorder Therapy for Children: An Expert Survey.

Orofacial Myofunctional Disorder (OMD) is believed to affect approximately 30-50% of all children. The various causes of OMD often revolve around an incorrect resting position of the tongue and cause symptoms such as difficulty in speech and swallowing. While these symptoms can persist and lead to jaw deformities, such as overjet and open bite, manual therapy has been shown to be effective, especially in children.

The Red Cross Red Crescent Health Information System (RCHIS): an electronic medical records and health information management system for the red cross red crescent emergency response units.

Background: The Red Cross and Red Crescent Movement (RCRC) utilizes specialized Emergency Response Units (ERUs) for international disaster response. However, data collection and reporting within ERUs have been time-consuming and paper-based. The Red Cross Red Crescent Health Information System (RCHIS) was developed to improve clinical documentation and reporting, ensuring accuracy and ease of use while increasing compliance with reporting standards.

Tanzania's and Germany's Digital Health Strategies and Their Consistency With the World Health Organization's Global Strategy on Digital Health 2020-2025: Comparative Policy Analysis.

Background: In recent years, the fast-paced adoption of digital health (DH) technologies has transformed health care delivery. However, this rapid evolution has also led to challenges such as uncoordinated development and information silos, impeding effective health care integration. Recognizing these challenges, nations have developed digital health strategies (DHSs), aligning with their national health priorities and guidance from global frameworks.

Methodological challenges in systematic reviews of mHealth interventions: Survey and consensus-based recommendations.

Objective: Mobile Health (mHealth) refers to using mobile devices to support health. This study aimed to identify specific methodological challenges in systematic reviews (SRs) of mHealth interventions and to develop guidance for addressing selected challenges.

Study Design And Setting: Two-phase participatory research project.

Mobile Apps for COVID-19: A Systematic Review of Reviews.

Background: One measure national governments took to react to the acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic was mobile applications (apps). This study aims to provide a high-level overview of published reviews of mobile apps used in association with coronavirus disease 19 (COVID-19), examine factors that contributed to the success of these apps, and provide data for further research into this topic.

Methods: We conducted a systematic review of reviews (also referred to as an umbrella review) and searched two databases, Medline and Embase, for peer-reviewed reviews of COVID-19 mobile apps that were written in English and published between January 1st 2020 and April 25th 2022.

Examining standardized tools used for the evaluation of mobile health applications for cardiovascular disease.

Cardiovascular disease is one of the leading causes of death worldwide. Scarce resources and rising costs are pushing healthcare systems to their limits. There is an urgency to develop, optimize and evaluate technologies that provide more effective care for patients.

Usability Assessment of an Electronic Medical Record-Embedded Clinical Decision Support System for Arterial Blood Gas Interpretation.

Since usability is considered a significant success factor for Clinical decision support systems (CDSSs), this study seeks to assess the usability of an electronic medical records-embedded CDSS for arterial blood gas (ABG) interpretation and ordering. The current study was conducted in the general ICU of a teaching hospital, using the System Usability Scale (SUS) and interviews with all anesthesiology residents and intensive care fellows in two rounds of CDSS usability testing. The feedback from the participants was discussed with the research team across a series of meetings, and the second version of CDSS was designed and tailored to participants' feedbacks.

Machine Learning Approaches for Detecting Coronary Artery Disease Using Angiography Imaging: A Scoping Review.

This scoping review aims to identify and summarize the current literature on Machine learning (ML) approaches for detecting coronary artery disease (CAD) using angiography imaging. We comprehensively searched several databases and identified 23 studies that met the inclusion criteria. They employed different types of angiography imaging including computed tomography and invasive coronary angiography.

Brain Tumor Classification and Segmentation Using Dual-Outputs for U-Net Architecture: O2U-Net.

We propose a modified version of the U-Net architecture for segmenting and classifying brain tumors, introducing another output between down- and up-sampling. Our proposed architecture utilizes two outputs, adding a classification output beside the segmentation output. The central idea is to use fully connected layers to classify each image before applying U-Net's up-sampling operations.

Apps for Covid-19 in Germany: assessment using the German Mobile App Rating Scale.

Objective: The purpose of this study is to provide an overview of apps to help control the spread of Covid-19 in Germany and rate them according to standardized instruments.

Materials And Methods: The Apple App Store and Google Play Store were systematically searched to identify apps dealing with Covid-19 in Germany. The German Mobile App Rating Scale (MARS-G) was used to independently assess app quality by 2 trained reviewers.

Enhancing mHealth data collection applications with sensing capabilities.

Smart mobile devices such as smartphones or tablets have become an important factor for collecting data in complex health scenarios (e.g., psychological studies, medical trials), and are more and more replacing traditional pen-and-paper instruments.

Chances and Risks of Using Robotic Assistance Systems in Early Neurological Rehabilitation: A Qualitative Analysis.

Robotic assistance systems offer new therapeutic perspectives for patient mobilization. This work aims to investigate the chances and risks of robotic assistance systems in early neurological rehabilitation. Nine professionals working in physiotherapy and nursing were interviewed on their opinion on robotic assistance systems.

Evaluating the Quality of a Clinical Mobile App for Physicians' CT Scan Ordering Using the MARS Rating Scale.

Given the lack of literature on the contributing factors to adopt mobile applications (apps) among physicians and the crucial role of the quality of the apps in their widespread use, the aim of this study is using the Mobile App Rating Scale (MARS) to evaluate the quality of the head CT scan appropriateness criteria app(HAC app). It was developed to assist medical interns and residents in ordering head CT scans. MARS is internationally recognized as an app rating tool and consists of four objective and subjective quality subscales quality subscale.

Key Elements for the Evaluation of mHealth Applications: Results from a Delphi Survey.

Mobile Health (mHealth) applications have seen strong growth in recent years, but they are often not systematically evaluated. A Delphi survey was conducted to identify key elements for the evaluation of mHealth applications. Sixteen experts participated in the study, and the study yielded a list of 79 key elements with expert consensus.

Development and Testing Requirements for an Integrated Maternal and Child Health Information System in Iran: A Design Thinking Case Study.

Background: Management of child health care can be negatively affected by incomplete recording, low data quality, and lack of data integration of health management information systems to support decision making and public health program needs. Given the importance of identifying key determinants of child health via capturing and integrating accurate and high-quality information, we aim to address this gap through the development and testing requirements for an integrated child health information system.

Subjects And Methods: A five-phase design thinking approach including empathizing, defining, ideation, prototyping, and testing was applied.

Development of clinical-guideline-based mobile application and its effect on head CT scan utilization in neurology and neurosurgery departments.

Background: There is little evidence regarding the adoption and intention of using mobile apps by health care professionals (HCP) and the effectiveness of using mobile apps among physicians is still unclear. To address this challenge, the current study seeks two objectives: developing and implementing a head CT scan appropriateness criteria mobile app (HAC app), and investigating the effect of HAC app on CT scan order.

Methods: A one arm intervention quasi experimental study with before/after analysis was conducted in neurology & neurosurgery (N&N) departments at the academic hospital.