Comprehensive framework for developing mHealth-based behavior change interventions.

Background: Understanding human behaviors has been the subject of several studies. Their main goal was to inform behavior change interventions aimed at promoting positive behaviors and improving negative ones. However, as a non-expert in behavioral science, it is extremely difficult for researchers from other disciplines to design and develop evidence-based behavior change interventions.

Understanding aberrant driving intentions based on the Theory of Planned Behavior: Literature review and Meta-Analysis.

Introduction: Despite deployed efforts to establish strict road safety standards, human factors is still the leading cause of road crashes. To identify determinants of driver's behavior, TPB (Theory of Planned Behavior) is widely used as a prominent theory of behavior change. However, the existence of different aberrant driving behaviors (decision errors, recognition errors, violations, and physical condition related errors) and several studies using TPB to understand driving behavior, makes it important to conduct a literature review and a meta-analysis of existing studies to use their results in effective driving behavior change interventions.

Multimodality Fusion Strategies in Eye Disease Diagnosis.

Multimodality fusion has gained significance in medical applications, particularly in diagnosing challenging diseases like eye diseases, notably diabetic eye diseases that pose risks of vision loss and blindness. Mono-modality eye disease diagnosis proves difficult, often missing crucial disease indicators. In response, researchers advocate multimodality-based approaches to enhance diagnostics.

Functional size measurement of postnatal care apps: Morocco case study.

This study empirically evaluates the functionality coverage of 18 mobile applications (apps) for Postnatal care including a recently developed app in Morocco ". This evaluation is based on a comparison of the COSMIC _ISO 19,761 functional size of these apps with the score obtained in a previous evaluation based on functions extraction through a quality assessment questionnaire. This comparison allows to discuss the relationship between the functional size of the 18 apps, their users' ratings in the Play Store as well as the number of downloads.

Effects of Gamification on the Benefits of Student Response Systems in Learning of Human Anatomy: Three Experimental Studies.

This paper presents three experiments to assess the impact of gamifying an audience response system on the perceptions and educational performance of students. An audience response system called SIDRA (Immediate Audience Response System in Spanish) and two audience response systems with gamification features, R-G-SIDRA (gamified SIDRA with ranking) and RB-G-SIDRA (gamified SIDRA with ranking and badges), were used in a General and Descriptive Human Anatomy course. Students participated in an empirical study.

Taking the pulse of a classroom with a gamified audience response system.

Background And Objective: This paper presents an empirical study of a gamified mobile-based assessment approach that can be used to engage students and improve their educational performance.

Method: A gamified audience response system called G-SIDRA was employed. Three gamification elements were used to motivate students in classroom activities: badges for achievements to increase engagement, points to indicate progression and performance in the subject and ranking for promoting competitiveness.

Mobile Technology for Improved Contraceptive Care in Morocco.

The fulfillment of unmet needs for contraception can help women reach their reproductive goals. Therefore, there is a growing concern worldwide about contraception and women's knowledge of making an advised choice about it. In this aspect, an outgrown number of apps are now available providing information concerning contraception whether it concerns natural contraception or modern contraception.

Reviewing Machine Learning and Image Processing Based Decision-Making Systems for Breast Cancer Imaging.

Breast cancer (BC) is the leading cause of death among women worldwide. It affects in general women older than 40 years old. Medical images analysis is one of the most promising research areas since it provides facilities for diagnosis and decision-making of several diseases such as BC.

Missing data techniques in classification for cardiovascular dysautonomias diagnosis.

Missing data (MD) is a common and inevitable problem facing data mining (DM)-based decision systems in e-health since many medical historical datasets contain a huge number of missing values. Therefore, a pre-processing stage is usually required to deal with missing values before building any DM-based decision system. The purpose of this paper is to evaluate the impact of MD techniques on classification systems in cardiovascular dysautonomias diagnosis.

A mapping study of ensemble classification methods in lung cancer decision support systems.

Achieving a high level of classification accuracy in medical datasets is a capital need for researchers to provide effective decision systems to assist doctors in work. In many domains of artificial intelligence, ensemble classification methods are able to improve the performance of single classifiers. This paper reports the state of the art of ensemble classification methods in lung cancer detection.

Homogeneous and heterogeneous ensemble classification methods in diabetes disease: a review.

This paper explores the use of ensemble classification methods in the context of the diabetes disease. An analysis was carried out that formulates and answers seven research questions: publication trends, channels and venues; medical tasks undertaken; ensemble types proposed; single techniques used to construct the ensemble methods; rules used to draw the output of the ensemble; datasets used to build and evaluate the ensemble methods; and tools used. A total of 107 papers were chosen after a study selection process.

Using ensemble classification methods in lung cancer disease.

This paper presents an overview of the use of ensemble classification methods in the lung cancer disease. An analysis is carried out according to seven aspects: publication trends, channels and venues; medical tasks tackled; ensemble types proposed; single techniques used to construct the ensemble methods; rules used to draw the output of the ensemble; datasets used to build and evaluate the ensemble methods; and tools used. The application of ensemble methods in lung cancer disease started in 2003.

Improving Accessibility for People with Disabilities: A Case Study on Inclusive Beach Tourism.

Disability is an important area in biomedical engineering. But research on disability should not only focus on the healthcare aspects, but also on the integration of people with disabilities in the cultural and social contexts, such as the existence of architectural elements that prevent the use of common public services. The present research aims to improve accessibility and enjoyment of people with physical and motor disabilities to the tourist resources of the area of interest.

Applying trans-theoretical model for blood donation among Spanish adults: a cross-sectional study.

Background: Relying solely on altruistic appeals may fail to fulfil the increasing demand for blood supplies. Current research has largely been attempted to determine and understand motives that serve as blood donation drivers. The Trans-Theoretical Model of behaviour change (TTM) can be used to conceptualise the process of intentional blood donation behaviour.

Mobile health applications for postnatal care: Review and analysis of functionalities and technical features.

Background: Providing a continuum of care from antenatal, childbirth and postnatal period results in reduced maternal and neonatal morbidity and mortality. Timely, high quality postnatal care is crucial for maximizing maternal and newborn health. In this vein, the use of postnatal mobile applications constitutes a promising strategy.

Sizing Prenatal mPHRs using COSMIC Measurement Method.

This paper presents an empirical evaluation of the COSMIC Function Points method (e.g., ISO 19761) through measuring the functional size of 33 prenatal mobile Personal Health Records (mPHRs) apps.

Reviewing ensemble classification methods in breast cancer.

Context: Ensemble methods consist of combining more than one single technique to solve the same task. This approach was designed to overcome the weaknesses of single techniques and consolidate their strengths. Ensemble methods are now widely used to carry out prediction tasks (e.

Software Development Effort Estimation Using Regression Fuzzy Models.

Software effort estimation plays a critical role in project management. Erroneous results may lead to overestimating or underestimating effort, which can have catastrophic consequences on project resources. Machine-learning techniques are increasingly popular in the field.

Evaluating the Privacy Policies of Mobile Personal Health Records for Pregnancy Monitoring.

A mobile personal health record (mPHR) for pregnancy monitoring allows the pregnant woman to track and manage her personal health data. However, owing to the privacy and security issues that may threaten the exchange of this sensitive data, a privacy policy should be established. The aim of this study is to evaluate the privacy policies of 19 mPHRs for pregnancy monitoring (12 for iOS and 7 for Android) using a template covering the characteristics of privacy, security, and standards and regulations.

Reusable Software Usability Specifications for mHealth Applications.

One of the key factors for the adoption of mobile technologies, and in particular of mobile health applications, is usability. A usable application will be easier to use and understand by users, and will improve user's interaction with it. This paper proposes a software requirements catalog for usable mobile health applications, which can be used for the development of new applications, or the evaluation of existing ones.

Systematic mapping study of data mining-based empirical studies in cardiology.

Data mining provides the methodology and technology to transform huge amount of data into useful information for decision making. It is a powerful process to extract knowledge and discover new patterns embedded in large data sets. Data mining has been increasingly used in medicine, particularly in cardiology.

A systematic review of gamification in e-Health.

Gamification is a relatively new trend that focuses on applying game mechanics to non-game contexts in order to engage audiences and to inject a little fun into mundane activities besides generating motivational and cognitive benefits. While many fields such as Business, Marketing and e-Learning have taken advantage of the potential of gamification, the digital healthcare domain has also started to exploit this emerging trend. This paper aims to summarize the current knowledge regarding gamified e-Health applications.

E-health internationalization requirements for audit purposes.

Background And Objective: In the 21st century, e-health is proving to be one of the strongest drivers for the global transformation of the health care industry. Health information is currently truly ubiquitous and widespread, but in order to guarantee that everyone can appropriately access and understand this information, regardless of their origin, it is essential to bridge the international gap. The diversity of health information seekers languages and cultures signifies that e-health applications must be adapted to satisfy their needs.

Are the expected benefits of requirements reuse hampered by distance? An experiment.

Background: Software development processes are often performed by distributed teams which may be separated by great distances. Global software development (GSD) has undergone a significant growth in recent years. The challenges concerning GSD are especially relevant to requirements engineering (RE).

Software project management tools in global software development: a systematic mapping study.

Global software development (GSD) which is a growing trend in the software industry is characterized by a highly distributed environment. Performing software project management (SPM) in such conditions implies the need to overcome new limitations resulting from cultural, temporal and geographic separation. The aim of this research is to discover and classify the various tools mentioned in literature that provide GSD project managers with support and to identify in what way they support group interaction.