To evaluate the usability of the COMPASS application with mixed-methodology, using a citizen science approach. Parents/tutors of 10-11 years old children attending a primary school in Barcelona, Spain, were invited to take part in the study. We conducted semi-structured interviews on a subset (n = 7) of participants, two weeks after using the app for the first time. A list of suggestions of improvement was extracted from the interviews. The System Usability Scale (SUS, range 0-100) was administered to all participants before and after the improvements were implemented. We provide both a quantitative analysis (t-test of change in SUS scores) and a qualitative thematic analysis of the interviews. A total of 22 participants were included in the study. The mean score before implementation of changes was 68.5 (Standard deviation, SD = 11.1), and improved to 73.1 (10.5) (p-value = 0.025). Regarding the qualitative assessment, we obtained 24 codes and grouped them into 3 categories. It uncovered problems in the installation phase and the main barriers to use: lack of time and the need for the app to evolve. The new version of COMPASS, improved by taking into account the participants' comments and suggestions, was more usable than the initial version.
Several studies have shown that, due to their features, mobile applications have a great potential to address mental health in depression and anxiety. We carried out a systematic review of publications from the last 10 years: from 1 January 2010 until 31 March 2020. Systematic reviews and meta-analyses related to the research question were also selected to identify other potentially eligible studies. The literature search in selected databases returned a total of 3,011 records from which a total of 22 articles were finally selected. The main conclusion of the study is that most of the scientific evidence found supports the hypothesis that mobile applications significantly improve the symptoms associated with depression and anxiety. Therefore, their effectiveness as a digital tool in the treatment of such health problems is proven. However, further studies and further evaluations of mobile applications are required (also in other languages) to incorporate this resource into the healthcare context. In addition, since mobile applications allow reinforcing concepts such as patient empowerment, shared decision-making and health literacy, their use would be highly positive for depression and anxiety, where there is a strong element of self-managing the disease.
Healthcare has been shifting toward individuals participating in decision-making and empowered to be active in their treatment, and health monitoring. The term "participatory health informatics" (PHI) started to appear in literature. A clear definition of PHI is missing, and facets of PHI still have to be shaped. The objective of this paper is to offer a definition of PHI considering themes and technologies that make healthcare participatory. We searched Pubmed, ACM Digital Library, IEEE Xplore, EMBASE, and conference proceedings for articles that reported about use of information technology or informatics in the context of PHI. We performed qualitative synthesis and reported summary statistics. 39 studies were eligible after screening 382 titles and abstracts and reviewing 82 full texts. The top 5 person-centered key themes related to PHI included empowerment, decision-making, informed patient, collaboration, and disease management. Finally, we propose to define PHI as multidisciplinary field that uses information technology as provided through the web, smartphones, or wearables to increase participation of individuals in their care process and to enable them in self-care and shared decision-making. Goals to be achieved through PHI include maintaining health and well-being; improving the healthcare system and health outcomes; sharing experiences; achieving life goals; and self-education.
Chronic pain is common in young people aged 10-14 years. Interdisciplinary, clinician-delivered treatments, while effective, are often criticized for failing to be readily accessible. Mobile health applications (mHealth apps) have been proposed as effective treatment adjuncts that address these challenges, while meeting the needs of tech-savvy young people. The objectives of this study were to co-create a mHealth app with consumers and health care professionals and evaluate the acceptability and feasibility of the resulting mHealth app (myPainPal). A phased, qualitative approach within a consumer engagement framework was employed. Interviews with young people (n = 14), parents (n = 12) and health care professionals (n = 8) identified key health needs that formed the underlying structure of the myPainPal app. Testing showed that the app is an acceptable and feasible platform to facilitate young people's self-management of chronic pain. The myPainPal app has the potential to positively influence young people's experiences of chronic pain. Further testing in controlled settings is required.
This paper presents a model of a smart healthcare service for stress management in dental patients during the interventions. The main goal is to provide dental clinics with a model that enables introducing a stress management service into everyday practice and provides patients with a better experience in a typically stressful situation. The approach is based on employing wearable sensors for monitoring physiological parameters, and a mobile application for progressive muscle relaxation therapy. Dental patients were divided into experimental and control groups. Participants from the experimental group were treated with progressive muscle relaxation through mobile health application with audio content, and patients from the control group were not exposed to any relaxation method. Heart rate was measured in both groups through three test phases: pre-intervention, intervention, and post-intervention. Evaluation of the anxiety level was performed using the STAI test. Results show that the measured heart rate in the post-intervention phase is lower than in the intervention phase in both testing groups, as well as in the pre-intervention phase. STAI scores were significantly higher in the control group through all test phases. The research found that the proposed system applied to dentist patients may relieve their anxiety symptoms and decrease stress level, which improves the patients' experience and leads to higher patients' satisfaction.
The mortality rate of heart disease continues to rise each year: developing mechanisms to reduce mortality from heart disease is a top concern in today's society. Heart sound auscultation is a crucial skill used to detect and diagnose heart disease. In this study, we propose a heart sound signal classification algorithm based on a convolutional neural network. The algorithm is based on heart sound data collected in the clinic and from medical books. The heart sound signals were first preprocessed into a grayscale image of 5 seconds. The training samples were then used to train and optimize the convolutional neural network; obtaining a training result with an accuracy of 95.17% and a loss value of 0.23. Finally, the convolutional neural network was used to test the test set samples. The results showed an accuracy of 94.80%, sensitivity of 94.29%, specificity of 95.54%, precision of 93.44%, F1_score of 93.84%, and an AUC of 0.943. Compared with other algorithms, the accuracy and sensitivity of the algorithms were improved. This shows that the method used in this study can effectively classify heart sound signals and could prove useful in assisting heart sound auscultation.
The main objective of this work is to define a common shared conceptual model that describes the health care environment using the ContSys standard, harmonizing it with the social care and assistive domotics concepts. The development of this model supports the integration of services, the interoperability among systems and the continuity of care across domains.Starting from the identification and extraction of the portion of the ContSys model suitable for the healthcare part, the article provides the methodology adopted to extend it with social and home automation concepts and to integrate them in a unique framework that supports the continuity of care.The integrated model defined in this paper has been adopted in the design phase of an interoperable open platform, called Health@Home, that organizes the provision of a set of health, social and home automation integrated services provided at home.Our model is a starting point to analyze the various determinants of wellbeing able to guarantee a high-level individual's quality of life. At the moment the Health@Home system is at the implementation phase.
The intensive care unit (ICU) is a stressful and complex environment in due to its dynamic nature and severity of admitted patients. EHR interface design can be cumbersome and lead to prolonged times to complete tasks. This paper investigated the relationship between a prominent EHR interface design and interruptions with physician's efficiency during patient chart review at ICU Pre-Rounds. We conducted a live observation of ICU physicians in a 30-bed MICU at a tertiary, southeastern medical center. Directly after the observation sessions, the physicians completed a modified System Usability Scale (SUS) survey. A total of 52 EHR patient chart reviews were observed at the MICU Pre-rounds. There was statistically significant positive correlation between time spent to review patient EHR with both number of scrolling(p-value<0.0001) across EHR interface; and with number of visited EHR screens (p-value=0.0444). There was positive correlation between number of interruptions with time spent to review patient EHR during ICU prerounds. EHR design and the occurrence of interruptions lead to reduced physician-EHR efficiency levels. We report that the number of scrolling and visited screens executed by physicians to gather the required information was associated with increased screen time and consequently decreased physician efficiency.