Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Dementia is a neurodegenerative chronic condition characterized by a progressive decline in a person’s memory, thinking, learning skills and ability to perform activities of daily life. Currently, Dementia affects 47 million people worldwide and with numbers expecting to increase, the World Health Organization (WHO) declared it a public health priority in 2012. Smart Health Technologies (s-Health Technologies) are being developed to support People with Dementia (PwD) and their informal caregivers at home, to improve care and reduce the levels of burden and stress they can experience. However, while s-Health technologies have the potential to facilitate this, it is still unknown what are the factors influencing a successful implementation in this population. Objective: The aim of this research was to review existing literature to explore the factors influencing PwD and their informal caregivers’ adoption of s-Health technologies for home care. Methods: Following Arksey and O’Malley methodology, the present study is a scoping review that provides a narrative description of the scientific literature on factors influencing s-Health technology adoption for PwD and their informal caregivers. A search was conducted in Pubmed, Cochrane library, IEEE library, and Scopus. Publications screening was conducted by two researchers based on inclusion criteria and full-text analysis was then conducted by one researcher. The included articles were thematically analyzed by two researchers, to gain an insight into factors influencing adoption that PwD and their informal caregivers have to encounter when using s-Health Technologies. Relevant information was identified and coded. Codes were later discussed between the researchers for developing and modifying them, achieving a consensus and organized the codes into broader themes. Results: Emerging themes were built in a way that said something specific and meaningful about the research question, creating a list of emerging themes for factors influencing s-Health Technologies adoption for PwD and their informal caregivers including: attitudinal aspects (positive and negative attitudes towards technology), ethical issues, technology-related challenges, condition-related challenges and identified gaps. Finally, a list of design considerations was created based on our findings, as a guide for future research and innovation in the area of s-Health Technologies for PwD and their informal caregivers, resulting in our proposed design framework: ‘DemDesCon for s-Heatlh Technologies’. DemDesCon for s-Health Technologies addresses four domains to consider for design and developing for this population: cognitive decline domain, physical decline domain, social domain and development domain. Conclusions: Even though s-Health technologies have been used in healthcare scenarios, more work is needed for them to fully achieve their potential for use in Dementia care. Researchers, businesses and public governments need to collaborate to design and implement effective technology solutions for PwD and their informal caregivers, but the lack of clear design guidelines seems to be slowing the process. We believe that DemDesCon framework will provide them with the guidance and assistance for creating meaningful devices for home care for PwD and informal caregivers, filling a much needed space in the gap of knowledge.

Breast cancer is the most common cancer in women. The use of mobile software applications for health and wellbeing promotion has grown exponentially in recent years. We systematically reviewed the breast cancer apps available in today's leading smartphone application stores and characterized them based on their features, evidence base and target audiences. A cross-sectional study was performed to characterize breast cancer apps from the two major smartphone app stores (iOS and Android). Apps that matched the keywords "breast cancer" were identified and data was extracted using a structured form. Reviewers independently evaluated the eligibility and independently classified the apps. A total of 1473 apps were a match. After removing duplicates and applying the selection criteria only 599 apps remained. Inter-rater reliability was determined using Fleiss-Cohen's Kappa. The majority of apps were free 471 (78.63%). The most common type of application was Disease and Treatment information apps (29.22%), Disease Management (19.03%) and Awareness Raising apps (15.03%). Close to 1 out of 10 apps dealt with alternative or homeopathic medicine. The majority of the apps were intended for patients (75.79%). Only one quarter of all apps (24.54%) had a disclaimer about usage and less than one fifth (19.70%) mentioned references or source material. Gamification specialists determined that 19.36% contained gamification elements. This study analyzed a large number of breast cancer-focused apps available to consumers. There has been a steady increase of breast cancer apps over the years. The breast cancer app ecosystem largely consists of start-ups and entrepreneurs. Evidence base seems to be lacking in these apps and it would seem essential that expert medical personnel be involved in the creation of medical apps.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Multiple sclerosis (MS) is a non-curable chronic inflammatory disease of the central nervous system that affects more than 2 million people around the world. MS related symptoms impact negatively on persons with MS quality of life who need to be active in the management of their health. Mobile health apps could support these patient group offering useful tools, providing reliable information, and monitoring symptoms, among others. A previous study from this group identified needs, barriers and facilitators for the use of mHealth solutions among persons with MS. It is unknown how commercially available health apps meet these demands and needs. Objective: The main objective of this review was to assess how the features present in available MS apps met the reported needs of persons with MS. Methods: A combination of scoping review methodology and systematic assessment of features and content of mobile health apps was followed. A search strategy was defined for the two most popular app stores (Google Play and Apple Store) to identify relevant apps. Reviewers independently conducted a screening process to filter apps according to the selection criteria and inter-rater reliability was assessed through the Fleiss-Cohen’s coefficient (k=0,885). Data from the included MS apps was extracted and explored according to classification criteria. Results: An initial total of 581 potentially relevant apps was found. After removing duplicates and applying inclusion and exclusion criteria, 30 unique apps were included in the study. Most were developed by Small and Medium-sized Enterprises (SME) and were free of charge to download. Patient education features were the most prevalent among the analyzed apps. Conclusions: Currently available MS apps fail to meet the needs and demands of persons with MS. There is a need for health professionals, researchers and industry partners to collaborate in the design of mHealth solutions for persons with MS to increase adoption and engagement.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Background: The adoption and use of technology have significantly changed health care delivery. Patient experience has become a significant factor in the entire spectrum of patient-centered health care delivery. Digital health facilitates further improvement and empowerment of patient experiences. Therefore, the design of digital health is served by insights into the barriers to and facilitators of digital patient experience (PEx). Objective: This study aimed to systematically review the influencing factors and design considerations of PEx in digital health from the literature and generate design guidelines for further improvement of PEx in digital health. Methods: We performed an umbrella systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched Scopus, PubMed, and Web of Science databases. Two rounds of small random sampling (20%) were independently reviewed by 2 reviewers who evaluated the eligibility of the articles against the selection criteria. Two-round interrater reliability was assessed using the Fleiss-Cohen coefficient (k1=0.88 and k2=0.80). Thematic analysis was applied to analyze the extracted data based on a small set of a priori categories. Results: The search yielded 173 records, of which 45 (26%) were selected for data analysis. Findings and conclusions showed a great diversity; most studies presented a set of themes (19/45, 42%) or descriptive information only (16/45, 36%). The digital PEx–related influencing factors were classified into 9 categories: patient capability, patient opportunity, patient motivation, intervention technology, intervention functionality, intervention interaction design, organizational environment, physical environment, and social environment. These can have three types of impacts: positive, negative, or double edged. We captured 4 design constructs (personalization, information, navigation, and visualization) and 3 design methods (human-centered or user-centered design, co-design or participatory design, and inclusive design) as design considerations. Conclusions: We propose the following definition for digital PEx: “Digital patient experience is the sum of all interactions affected by a patient’s behavioral determinants, framed by digital technologies, and shaped by organizational culture, that influence patient perceptions across the continuum of care channeling digital health.” In this study, we constructed a design and evaluation framework that contains 4 phases—define design, define evaluation, design ideation, and design evaluation—and 9 design guidelines to help digital health designers and developers address digital PEx throughout the entire design process. Finally, our review suggests 6 directions for future digital PEx–related research.