New technologies in health education and research

The studies in this track provided an updated overview of different technological innovation procedures in distinct health science fields. Thus, technological applications from medical imaging treatment and three-dimensional visualization to simulation systems useful in clinical practice training (simulations with mannequins, training with manual control devices, virtual reality techniques with stereo vision helmets, amongst others) are presented. The main objective of these procedures is to improve the quality of university teaching and continuing education, using the latest resources, which are starting to be implemented in different universities.info:eu-repo/semantics/publishedVersio

Development of “LvL UP”, a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders

Background: Non-communicable diseases (NCDs) and common mental disorders (CMDs) are the leading causes of death and disability worldwide. Lifestyle interventions via mobile apps and conversational agents present themselves as low-cost, scalable solutions to prevent these conditions. This paper describes the rationale for, and development of, “LvL UP”, a digital lifestyle intervention aimed at preventing NCDs and CMDs.Materials and Methods: A multidisciplinary team led the intervention design process of LvL UP, involving four phases: (i) preliminary research (stakeholder consultations, systematic market reviews), (ii) selecting intervention components and developing the conceptual model, (iii) whiteboarding (prototype development), and (iv) testing and refinement. The Multiphase Optimization Strategy and the UK Medical Research Council framework for developing and evaluating complex interventions were used to guide the intervention development.Results: The first version of LvL UP features a scalable, smartphone-based, and conversational agent-delivered holistic lifestyle intervention built around three pillars: Move More (physical activity), Eat Well (nutrition and healthy eating), and Stress Less (emotional regulation and wellbeing). Intervention components include health literacy and psychoeducational coaching sessions, daily "Life Hacks” (healthy activity suggestions), breathing exercises, and journaling. Engagement components involve motivational interviewing and storytelling to deliver the coaching sessions, as well as progress feedback and gamification. Offline materials are also offered to allow users access to essential intervention content without needing a digital device.Conclusions: The development process of LvL UP led to an evidence-based and user-informed digital health intervention aimed at preventing NCDs and CMDs. LvL UP is designed to be a scalable, engaging, prevention-oriented, holistic intervention for adults at risk of NCDs and CMDs. A feasibility study, and subsequent optimisation and randomised-controlled trials are planned to further refine the intervention and establish effectiveness. The development process described here may prove helpful to other intervention developers

Presentation of the GRIAL research group and its main research lines and projects on March 2016

[EN]Presentation of the GRIAL research group and its main research lines and projects in the Intelligent System Master Degree of University of Salamanca on March 7th, 2016

Behaviour Profiling using Wearable Sensors for Pervasive Healthcare

In recent years, sensor technology has advanced in terms of hardware sophistication and miniaturisation. This has led to the incorporation of unobtrusive, low-power sensors into networks centred on human participants, called Body Sensor Networks. Amongst the most important applications of these networks is their use in healthcare and healthy living. The technology has the possibility of decreasing burden on the healthcare systems by providing care at home, enabling early detection of symptoms, monitoring recovery remotely, and avoiding serious chronic illnesses by promoting healthy living through objective feedback. In this thesis, machine learning and data mining techniques are developed to estimate medically relevant parameters from a participant‘s activity and behaviour parameters, derived from simple, body-worn sensors. The first abstraction from raw sensor data is the recognition and analysis of activity. Machine learning analysis is applied to a study of activity profiling to detect impaired limb and torso mobility. One of the advances in this thesis to activity recognition research is in the application of machine learning to the analysis of 'transitional activities': transient activity that occurs as people change their activity. A framework is proposed for the detection and analysis of transitional activities. To demonstrate the utility of transition analysis, we apply the algorithms to a study of participants undergoing and recovering from surgery. We demonstrate that it is possible to see meaningful changes in the transitional activity as the participants recover. Assuming long-term monitoring, we expect a large historical database of activity to quickly accumulate. We develop algorithms to mine temporal associations to activity patterns. This gives an outline of the user‘s routine. Methods for visual and quantitative analysis of routine using this summary data structure are proposed and validated. The activity and routine mining methodologies developed for specialised sensors are adapted to a smartphone application, enabling large-scale use. Validation of the algorithms is performed using datasets collected in laboratory settings, and free living scenarios. Finally, future research directions and potential improvements to the techniques developed in this thesis are outlined

The effectiveness of an app with remote support to improve adherence to home exercise programs prescribed by physiotherapists: a randomised controlled trial

Question: Do people with musculoskeletal conditions better adhere to their home exercise programs (HEPs) when these are provided to them on an app with remote support compared to paper handouts? Design: Randomised, parallel-group trial with intention-to-treat analysis. Participants: Eighty participants with upper or lower limb musculoskeletal conditions who were prescribed a 4-week HEP by a physiotherapist at a tertiary teaching hospital in Australia were recruited to the trial. Participants were randomly assigned via a computer-generated concealed block randomisation procedure to either intervention (n = 40) or control (n = 40) groups between 25/02/16 and 13/01/17. Intervention: Participants in the intervention group received their HEPs on an app linked to www.physiotherapyexercises.com. They also received supplementary phone calls and motivational text messages. Participants in the control group received their HEPs as a paper handout. Outcome measures: Outcome measures were collected at baseline and at 4 weeks by blinded assessors. The primary outcome was self-reported exercise adherence. Secondary outcomes included measures of function, disability, satisfaction with service delivery and assessor-reported adherence. Results: Outcomes were available on 77 participants. Three were lost to follow up. The mean between-group difference for self-reported exercise adherence at 4-weeks was 1.3/11 points (95% CI, 0.2 to 2.3), favouring the intervention group. The mean between-group difference for the patient-specific functional scale was 0.9/11 points (95% CI, 0.1 to 1.7) in favour of the intervention group. There were no significant between-group differences for the remaining outcomes. Conclusion: Patients with musculoskeletal conditions better adhere to their HEPs when these are provided to them on an app with remote support compared to paper handouts, however, the clinical importance of this added adherence is unclear

Designing Collaborative Technology-based Interventions for Mental Health Management

In addition to the impact on public health, especially after the emergence of the COVID-19 pandemic, mental health problems have been amplified globally, leading to higher levels of anxiety and depression especially among young adults, who are among the most vulnerable populations. Due to the specific social context and newfound challenges surrounding university life, psychological distress affects university students at a disproportional higher rate when compared to the general population. With the increase in requests for university therapy services, digital mental health tools developed in conjunction with in-person therapy offer a pioneering solution for expanding the potential and reach of these services while overcoming socioeconomic, geographical, and educational barriers. This thesis explores the process of collaboratively developing a mobile applica tion named Toolbox for mental well-being self-management alongside the psychology counselling services at the University of Madeira. By exploring providers’ perspectives and concerns, this study highlights how a digital solution designed by clinicians could address daily challenges and facilitate treatment protocols. This study presents the potential a mental health app has for improving clinical interventions in the university environment and helping providers of mental health services. The integration of a mental health platform into therapeutic practices can better inform the clients’ course of treatment, particularly due to the collection and analysis of user behaviour-tracking information. It also encourages users to learn about mental health and develop a closer connection with their psychologists. From a methodological standpoint, it proposes the development of mental health app should be conducted in an adaptable process that accommodates the stakehold ers’ expertise and inputs under a cross-disciplinary approach to developing a digital platform that addresses students’ mental health.Além do impacto na saúde pública, especialmente com o surgimento da pandemia COVID-19, os problemas de saúde mental aumentaram globalmente, levando a níveis mais elevados de ansiedade e depressão principalmente entre jovens adultos, uma das populações mais vulneráveis. Devido ao contexto social e desafios que envolvem a experiência universitária, o sofrimento psicológico atinge os estudantes universitários de um modo desproporcio nalmente maior aquando comparado com a população em geral. Com o aumento dos pedidos nos serviços de apoio psicológico, as ferramentas digitais para saúde mental desenvolvidas em conjunto com a terapia presencial oferecem uma solução pioneira para ampliar o alcance destes serviços, superando barreiras socioeconómicas, geográ ficas e educacionais. Esta tese explora o processo de desenvolvimento colaborativo de uma aplicação móvel denominada Toolbox para a autogestão do bem-estar psicológico em conjunto com o serviço de psicologia da Universidade da Madeira. Ao explorar as perspetivas e preocupações dos psicólogos, este estudo evidencia o modo como uma solução digital projetada por profissionais de saúde pode ajudar a fazer face aos desafios do dia-a-dia e facilitar o processo terapêutico. Este estudo apresenta o potencial que uma app para saúde mental detém para me lhorar as intervenções clínicas em ambiente universitário, auxiliando o trabalho dos psicólogos dos serviços de apoio psicológico. A integração de uma plataforma para saúde mental em prática clinicas melhora o processo terapêutico dos clientes, especial mente aquando a recolha e análise de dados de monitorização comportamental. Estas plataformas também incentivam a aprendizagem sobre saúde mental dos utilizadores e o desenvolvimento uma ligação mais próxima com psicólogos. Do ponto de vista metodológico, este estudo propõe que o desenvolvimento de uma app para saúde mental deve ser conduzido num processo adaptativo, que acomode o conhecimento especializado e as contribuições dos parceiros de forma interdisciplinar no desenvolvimento de uma plataforma digital para a saúde mental de estudantes

Mobile Viewing and Self-Management of Patient’s Electronic Health Records (EHRs) with MyHealthCloud

Mobile computing has become one of the most dominant computer use paradigms and an essential part of the modern healthcare environment. As these applications become more sophisticated, a trend will inevitably develop towards providing comprehensive support for healthcare practitioners. According to industry estimates, by 2018, 50 percent of more than 3.4 billion smartphone and tablet users will have downloaded mobile healthcare apps. These users include healthcare professionals, consumers and patients. In the United States, the Food and Drug Administration (FDA) is encouraging the development of mobile medical applications that improve healthcare and provide consumers and healthcare professionals with valuable health information. In this thesis, we propose a novel mobile healthcare platform for the visualization and management of patients’ medical reports, named MyHealthCloud. The research offers a new approach to store, retrieve and share the medical reports for patients and doctors. This new platform maximizes the benefits of mobile health technology by providing the best possible way for healthcare professionals to share information with their patients efficiently and effectively. This thesis empirically validates the usability of the proposed approach and clearly demonstrates its usefulness, providing details of the empirical study conducted with end-users in a real environment at various hospitals

Digital innovation in Multiple Sclerosis Management

Due to innovation in technology, a new type of patient has been created, the e-patient, characterized by the use of electronic communication tools and commitment to participate in their own care. The extent to which the world of digital health has changed during the COVID-19 pandemic has been widely recognized. Remote medicine has become part of the new normal for patients and clinicians, introducing innovative care delivery models that are likely to endure even if the pendulum swings back to some degree in a post-COVID age. The development of digital applications and remote communication technologies for patients with multiple sclerosis has increased rapidly in recent years. For patients, eHealth apps have been shown to improve outcomes and increase access to care, disease information, and support. For HCPs, eHealth technology may facilitate the assessment of clinical disability, analysis of lab and imaging data, and remote monitoring of patient symptoms, adverse events, and outcomes. It may allow time optimization and more timely intervention than is possible with scheduled face-to-face visits. The way we measure the impact of MS on daily life has remained relatively unchanged for decades, and is heavily reliant on clinic visits that may only occur once or twice each year.These benefits are important because multiple sclerosis requires ongoing monitoring, assessment, and management.The aim of this Special Issue is to cover the state of knowledge and expertise in the field of eHealth technology applied to multiple sclerosis, from clinical evaluation to patient education