Supporting reflection and creative thinking by carers of older people with dementia

This vision paper frames requirements engineering as a creative problem solving process. Its purpose is to enable requirements researchers and practitioners to recruit relevant theories, models, techniques and tools from creative problem solving to understand and support requirements processes more effectively. It uses 4 drivers to motivate the case for requirements engineering as a creative problem solving process. It then maps established requirements activities onto one of the longest-established creative problem solving processes, and uses these mappings to locate opportunities for the application of creative problem solving in requirements engineering. The second half of the paper describes selected creativity theories, techniques, software tools and training that can be adopted to improve requirements engineering research and practice. The focus is on support for problem and idea finding - two creative problem solving processes that our investigation revealed are poorly supported in requirements engineering. The paper ends with a research agenda to incorporate creative processes, techniques, training and tools in requirements projects

360 Quantified Self

Wearable devices with a wide range of sensors have contributed to the rise of the Quantified Self movement, where individuals log everything ranging from the number of steps they have taken, to their heart rate, to their sleeping patterns. Sensors do not, however, typically sense the social and ambient environment of the users, such as general life style attributes or information about their social network. This means that the users themselves, and the medical practitioners, privy to the wearable sensor data, only have a narrow view of the individual, limited mainly to certain aspects of their physical condition. In this paper we describe a number of use cases for how social media can be used to complement the check-up data and those from sensors to gain a more holistic view on individuals' health, a perspective we call the 360 Quantified Self. Health-related information can be obtained from sources as diverse as food photo sharing, location check-ins, or profile pictures. Additionally, information from a person's ego network can shed light on the social dimension of wellbeing which is widely acknowledged to be of utmost importance, even though they are currently rarely used for medical diagnosis. We articulate a long-term vision describing the desirable list of technical advances and variety of data to achieve an integrated system encompassing Electronic Health Records (EHR), data from wearable devices, alongside information derived from social media data.Comment: QCRI Technical Repor

Development of an evidence-based medicine mobile application for the use in medical education

BACKGROUND: Evidence-based medicine (EBM) is a methodology that is being incorporated into more medical school curricula. Boston University School of Medicine was one of early adopters of Evidence Based Medicine in the United States. A growing concern in the medical community was that the complexities of applying EBM might be lost when students enter into their clinical rotations, thus there is a need for development of a tool to help reinforce the EBM principles. METHODS: The research team in collaboration with the designers of the Finding Information Framework, a custom-made EBM finding information tool, worked to develop a mobile application to help reinforce the framework for medical students. The app was designed with both Apple and PC operating systems in mind. Key features that were identified from current literature to provide the most user-friendly mobile application. Thus, the research team specifically utilized iOS and Android platforms as both platforms have a centralized app store, possess the highest volume of medical apps available, and are most widely used in the United States by medical students. RESULTS: The Finding Information Framework was a custom-made tool developed to guide new users of EBM, and help them to apply the principles in practice. The mobile application served an added convenience by allowing easy access and fast utilization of the EBM tools. The app was designed on an Android platform first due to its open-source OS and ease in app development to new programmers. Initially, the user-friendly web-based tool, App Inventor (AI), powered by Massachusetts Institute of Technology was evaluated to program the pilot Android app. Using both the AI Component Designer and the Block Editor, several problems were encountered in AI, such as the simplicity of the program and the lack of freedom in design. This moved the project to create the app natively and with a collaborative effort with the BU's Global App Initiative club. Initially, a wireframe was built using Balsamiq. Subsequently, the Android app was built using Android SDK and the iOS app was built in XCode with Objective C; both platforms had design sections prepared in Sketch, Adobe Photoshop and Illustrator. The last and final step was to obtain Boston University branding privileges for the app. CONCLUSION: The research team identified necessary features based on research to build a user-friendly, professional mobile application of an information mastery framework that can be used off-line. The app is called FIF as it is the title of the information mastery tool designed by BUSM EBM-VIG. With a clear mobile interface, it will be beneficial to the learning and training of medical students in EBM

M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

Monitoring and detection of agitation in dementia: towards real-time and big-data solutions

The changing demographic profile of the population has potentially challenging social, geopolitical, and financial consequences for individuals, families, the wider society, and governments globally. The demographic change will result in a rapidly growing elderly population with healthcare implications which importantly include Alzheimer type conditions (a leading cause of dementia). Dementia requires long term care to manage the negative behavioral symptoms which are primarily exhibited in terms of agitation and aggression as the condition develops. This paper considers the nature of dementia along with the issues and challenges implicit in its management. The Behavioral and Psychological Symptoms of Dementia (BPSD) are introduced with factors (precursors) to the onset of agitation and aggression. Independent living is considered, health monitoring and implementation in context-aware decision-support systems is discussed with consideration of data analytics. Implicit in health monitoring are technical and ethical constraints, we briefly consider these constraints with the ability to generalize to a range of medical conditions. We postulate that health monitoring offers exciting potential opportunities however the challenges lie in the effective realization of independent assisted living while meeting the ethical challenges, achieving this remains an open research question remains.Peer ReviewedPostprint (author's final draft

The Use of Data Collected from mHealth apps to inform Evidence-based Quality Improvement: An Integrative Review:Using data from mHealth apps to inform Evidence-based Quality Improvement

© 2019 Sigma Theta Tau International Background: The global acceptance and use of technology in health care has resulted in an abundance of mobile health (mHealth) applications (apps) available for use in the delivery and improvement of care. With so many apps available to patients and clinicians, it is important to understand how data from apps are being used to inform quality improvement in practice. Aim: The aim of this integrative review is to establish current knowledge of how mHealth apps are used to produce data to inform quality improvement in health care. Methods: Scopus, Web of Science, CINAHL, and Medline Plus Full Text databases were searched for peer-reviewed papers written in English. The inclusion criteria comprised of full-text, empirical research studies relating to mobile health application use (not development) in clinical care. Results: Nineteen studies met inclusion criteria. The functions of the apps outlined in the studies can be summarized into four different categories: communication, illness management, clinical management, and education/information. The types of data collected by the apps included numerical, textual, photographic, and graphical with several apps able to collect a variety of data types. Analysis of the studies showed that although data collection is rarely outlined as the explicit purpose of mHealth apps, data collected through such technology are and can be used to inform practice change both in real time and retrospectively. Linking Evidence to Action: This review highlights while this is an emerging area, data obtained from mHealth apps can and are being used to inform quality improvement in health care. Further research is required in this area to adequately understand how data from mHealth apps can be used to produce quality improvement, specifically in relation to nursing. This review also highlights a need for the development of apps that aim to capture data to inform quality improvement, particularly from the patient perspective

Interventions for Childhood Obesity: Evaluating Technological Applications Targeting Physical Activity Level and Diet

Overweight and obese children have increased risks for multiple preventable diseases and conditions which can impair their physiological health and significantly increases the overall cost of their healthcare. Free mobile applications and technology for weight loss, dietary tracking, and physical activity may be quite useful for monitoring nutritional intake and exercise to facilitate weight loss. If so, nurses are well positioned to recommend such tools as part of their efforts to prevent childhood obesity and help children and parents better manage childhood obesity when it is present. However, there are no guidelines that nurses can use to determine what applications or technologies are most beneficial to children and their parents. The purpose of this project is to develop such guidelines based on a review of the scientific literature published in the last 5 years. Articles regarding healthy-lifestyle promoting mobile applications and technological approaches to health and fitness interventions were identified by searching articles indexed by CINAHL, Psychinfo, Medline, ERIC, IEEE Xplore, and Academic Search Premier. Identified articles were assessed using Melnyk’s hierarchy of evidence and organized into tables so that implications for research and suggestions for practice could be made

Feasibility and performance of a device for automatic self-detection of symptomatic acute coronary artery occlusion in outpatients with coronary artery disease : a multicentre observational study

Background Time delay between onset of symptoms and seeking medical attention is a major determinant of mortality and morbidity in patients with acute coronary artery occlusion. Response time might be reduced by reliable self-detection. We aimed to formally assess the proof-of-concept and accuracy of self-detection of acute coronary artery occlusion by patients during daily life situations and during the very early stages of acute coronary artery occlusion. Methods In this multicentre, observational study, we tested the operational feasibility, specificity, and sensitivity of our RELF method, a three-lead detection system with an automatic algorithm built into a mobile handheld device, for detection of acute coronary artery occlusion. Patients were recruited continuously by physician referrals from three Belgian hospitals until the desired sample size was achieved, had been discharged with planned elective percutaneous coronary intervention, and were able to use a smartphone; they were asked to perform random ambulatory selfrecordings for at least 1 week. A similar self-recording was made before percutaneous coronary intervention and at 60 s of balloon occlusion. Patients were clinically followed up until 1 month after discharge. We quantitatively assessed the operational feasibility with an automated dichotomous quality check of self-recordings. Performance was assessed by analysing the receiver operator characteristics of the ST difference vector magnitude. This trial is registered with ClinicalTrials.gov, number NCT02983396. Findings From Nov 18, 2016, to April 25, 2018, we enrolled 64 patients into the study, of whom 59 (92%) were eligible for self-applications. 58 (91%) of 64 (95% CI 81.0-95.6) patients were able to perform ambulatory self-recordings. Of all 5011 self-recordings, 4567 (91%) were automatically classified as successful within 1 min. In 65 balloon occlusions, 63 index tests at 60 s of occlusion in 55 patients were available. The mean specificity of daily life recordings was 0.96 (0.95-0.97). The mean false positive rate during daily life conditions was 4.19% (95% CI 3.29-5.10). The sensitivity for the target conditions was 0.87 (55 of 63; 95% CI 0.77-0.93) for acute coronary artery occlusion, 0.95 (54 of 57; 0.86-0.98) for acute coronary artery occlusion with electrocardiogram (ECG) changes, and 1.00 (35 of 35) for acute coronary artery occlusion with ECG changes and ST-segment elevation myocardial infarction criteria (STEMI). The index test was more sensitive to detect a 60 s balloon occlusion than the STEMI criteria on 12-lead ECG (87% vs 56%; p<0.0001). The proportion of total variation in study estimates due to heterogeneity between patients (I-2) was low (12.6%). The area under the receiver operator characteristics curve was 0.973 (95% CI 0.956-0.990) for acute coronary artery occlusion at different cutoff values of the magnitude of the ST difference vector. No patients died during the study. Interpretation Self-recording with our RELF device is feasible for most patients with coronary artery disease. The sensitivity and specificity for automatic detection of the earliest phase of acute coronary artery occlusion support the concept of our RELF device for patient empowerment to reduce delay and increase Survival without overloading emergency services. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd