Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Anxolotl - An Anxiety Companion App

Dissertação para obtenção do Grau de Mestre em Engenharia Informática e de ComputadoresA Organização Mundial de Saúde apresentou as perturbações mentais como os maiores contribuintes para incapacidade global em 2015, com os distúrbios de ansiedade a ocuparem a sexta posição. Distúrbios de ansiedade têm um alta prevalência na sociedade, e apresentam sintomas precoces que podem ser detetados. Nesta tese, produzimos um sistema capaz de detetar sintomas de distúrbios de ansiedade antes que a doença se instale por completo. Adicionalmente, queremos dar outra opção a portadores, monitorizando o seu estado mental e oferecendo a hipótese de tratarem dos seus níveis de ansiedade antes que apareçam mais sintomas. Aqui introduzimos um sistema de saúde móvel, entitulado de Anxolotl, que pode detetar e classificar níveis de ansiedade multiclasse e detetar níveis binários de estados de pânico . A nossa solução é composta por: datacenter, com o objectivo de guardar dados fisiológicos anónimos, e aplicar modelos de aprendizagem automática; broker de mensagens, que irá providenciar escalaabilidade e habilidade de desacoplamento no sistema; aplicação móvel, que funcionará em conjunto com um wearable para capturar dados fisiológicos. A nossa applicação é capaz de detetar e monitorizar diariamente, os níveis de ansiedade e pânico do utilizador, filtrando dados dúbios com base em atividade física. A aplicação também apresenta múltiplos exercícios de respiração guiados, bem como meditações acompanhadas para vários cenários de saúde mental. O nosso modelo de deteção de ansiedade foi capaz de apresentar uma precisão de 92% e um f1-Score de 90% na classificação de ansiedade multiclasse, treinando com um dataset com 124 entradas, enquanto que o nosso modelo de deteção de pânico apresenta uma precisão de 94% e um f1-Score de 94%. Estes valores foram atingindos utilizando maioritariamente dados de ritmo cardíaco. O código dos modelos está disponível em https://github.com/nunogoms/Anxolotl-engines.World Health Organization referred that common mental health disorders were the biggest contributors to global disability during the year of 2015, with anxiety disorders occupying the 6th position. Currently, anxiety disorders have high prevalence in society, and present early symptoms that are suited to be detected. With this thesis, we intend to produce a system capable of detecting the anxiety disorder early symptoms before the onset of the full range of symptoms. Additionally, we want to give another option to people already affected, in the form of monitoring their mental health, and the ability for them to react to their anxiety state quickly. Herein, we are introducing a mobile health system — Anxolotl, that can detect and classify multi class anxiety levels and detect binary panic states. Our solution is composed by: a datacenter, intended to store anonymous physiological data and applying the machine learning models; a message broker, aiming to provide scalability and decoupling to the system; and, finally a mobile app, which will work in tandem with a wearable to capture physiological data. The app is able to track and monitor, on a daily basis, its user’s anxiety and panic levels, filtering when the data is unreliable based on activity. It also presents the users with guided breathing exercises for multiple mental health scenarios as well as some guided meditations, in an effort to help its users. The Anxiety Engine model provided a 92% accuracy and 90% f1-Score in classifying multi-class anxiety levels, training and testing with a dataset containing 124 entries, and our binary Panic Engine had an accuracy of 94% and a f1-Score of 94%. Both these scenarios were mainly achieved by using heart rate data, activity context was also used in some scenarios. The code for these models is available at https://github.com/nunogoms/Anxolotl-engines.N/

Contextual and design factors that influence the use of consumer technologies for self-management of stress by teachers

Persistent psychosocial stress is endemic in the modern workplace, including amongst secondary school teachers in England. There is intense interest in the potential role of digital technology such as apps, wearables and online programmes to support stress management but insufficient understanding of how the contexts of teachers’ work influence their use. Using a constructivist paradigm, a series of qualitative studies was conducted to understand the influence of these contextual factors. First semi-structured qualitative interviews with teachers were thematically analysed to reveal the physical, social and cultural contextual constraints on teachers’ stress management. Then to enable teachers’ choice of consumer technology for the longitudinal study, an analytical study generated a populated taxonomy of self-management strategies for stress with digital support options. This was presented in workshops to enable some informed choice. Finally, the qualitative longitudinal summer term study explored eight teachers’ experiences of using their chosen technology in their daily lives. The pandemic meant interviews were online and teachers were mainly working from home. The study was extended with six participants into the autumn term when all teachers had returned to school premises. Cross-case analysis revealed the teachers’ experiences of using technology for stress management included the explanatory power of contextually mediated data, generating awareness, permission to self-care and empathy. The findings suggest implications for self-determination theory (SDT). Thematic analysis revealed facilitators and barriers to using the technology in the school context. There are associated implications for school wellbeing support and designers, and considerations for the Unified Theory of Acceptance and Use of Technology (UTAUT). This thesis’ main contributions include unique insight into teachers’ experiences of consumer technologies for workplace stress management and the technology features that facilitate self-care. Stress awareness derived from interaction with the technology and personal data gave teachers permission to self-care. Facilitators included brief, discreet interactions and contextually relevant prompts and information. Barriers to use included insufficient technology instructions, and contextual constraints of the relentless work culture, social stigma and lack of privacy. This thesis also documents an innovative process for developing and populating a taxonomy to facilitate technology selection, including specifically for teachers managing stress. Finally, it makes recommendations of interest to designers, school leaders and policy makers seeking to improve teachers’ ability to digitally support their stress self-management

Survey on virtual coaching for older adults

Virtual coaching has emerged as a promising solution to extend independent living for older adults. A virtual coach system is an always-attentive personalized system that continuously monitors user's activity and surroundings and delivers interventions - that is, intentional messages - in the appropriate moment. This article presents a survey of different approaches in virtual coaching for older adults, from the less technically supported tools to the latest developments and future avenues for research. It focuses on the technical aspects, especially on software architectures, user interaction and coaching personalization. Nevertheless, some aspects from the fields of personality/social psychology are also presented in the context of coaching strategies. Coaching is considered holistically, including matters such as physical and cognitive training, nutrition, social interaction and mood.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 769830

Enhancing mental health with Artificial Intelligence: Current trends and future prospects

Artificial Intelligence (AI) has emerged as a transformative force in various fields, and its application in mental healthcare is no exception. Hence, this review explores the integration of AI into mental healthcare, elucidating current trends, ethical considerations, and future directions in this dynamic field. This review encompassed recent studies, examples of AI applications, and ethical considerations shaping the field. Additionally, regulatory frameworks and trends in research and development were analyzed. We comprehensively searched four databases (PubMed, IEEE Xplore, PsycINFO, and Google Scholar). The inclusion criteria were papers published in peer-reviewed journals, conference proceedings, or reputable online databases, papers that specifically focus on the application of AI in the field of mental healthcare, and review papers that offer a comprehensive overview, analysis, or integration of existing literature published in the English language. Current trends reveal AI's transformative potential, with applications such as the early detection of mental health disorders, personalized treatment plans, and AI-driven virtual therapists. However, these advancements are accompanied by ethical challenges concerning privacy, bias mitigation, and the preservation of the human element in therapy. Future directions emphasize the need for clear regulatory frameworks, transparent validation of AI models, and continuous research and development efforts. Integrating AI into mental healthcare and mental health therapy represents a promising frontier in healthcare. While AI holds the potential to revolutionize mental healthcare, responsible and ethical implementation is essential. By addressing current challenges and shaping future directions thoughtfully, we may effectively utilize the potential of AI to enhance the accessibility, efficacy, and ethicality of mental healthcare, thereby helping both individuals and communities

Enhancing Mental Health with Artificial Intelligence: Current Trends and Future Prospects

Artificial Intelligence (AI) has emerged as a transformative force in various fields, and its application in mental healthcare is no exception. Hence, this review explores the integration of AI into mental healthcare, elucidating current trends, ethical considerations, and future directions in this dynamic field. This review encompassed recent studies, examples of AI applications, and ethical considerations shaping the field. Additionally, regulatory frameworks and trends in research and development were analyzed. We comprehensively searched four databases (PubMed, IEEE Xplore, PsycINFO, and Google Scholar). The inclusion criteria were papers published in peer-reviewed journals, conference proceedings, or reputable online databases, papers that specifically focus on the application of AI in the field of mental healthcare, and review papers that offer a comprehensive overview, analysis, or integration of existing literature published in the English language. Current trends reveal AI's transformative potential, with applications such as the early detection of mental health disorders, personalized treatment plans, and AI-driven virtual therapists. However, these advancements are accompanied by ethical challenges concerning privacy, bias mitigation, and the preservation of the human element in therapy. Future directions emphasize the need for clear regulatory frameworks, transparent validation of AI models, and continuous research and development efforts. Integrating AI into mental healthcare and mental health therapy represents a promising frontier in healthcare. While AI holds the potential to revolutionize mental healthcare, responsible and ethical implementation is essential. By addressing current challenges and shaping future directions thoughtfully, we may effectively utilize the potential of AI to enhance the accessibility, efficacy, and ethicality of mental healthcare, thereby helping both individuals and communities

Use of wearable devices for health and well-being purposes among university students in Turku

Use of wearable devices with health and well-being related features has increased during the past years and the trend is predicted to continue in the following years as well. The technology in today’s devices is capable of recording number of biosignals such as blood pressure, body and/or skin temperature, and heart rate. Wearable technology is planned, for instance, to support weight management, improve cardiovascular health and help monitoring and treatment of mental health disorders. This research aimed to find out how common it was for university students in Turku, Finland, to use wearable devices, and to discover the experienced health and well-being benefits, drawbacks or challenges related to the use of wearable devices. Additional goals were to discover the factors students valued in the adoption of wearable devices and if students used the devices in cooperation with health care professionals. The research was done by utilizing mixed-methods approach combining features of quantitative and qualitive methods to study the topic in extensive manner. To answer the research questions, empiric data was collected using an online survey distributed to university students in Turku, Finland in fall 2020. The survey was distributed to students in the University of Turku and Åbo Akademi University in cooperation with the student associations in the two universities. The total survey sample resulted to 329 respondents with participants from both universities. 60 percent of the survey respondents used wearable devices and 40 percent did not. The most used device types were activity trackers, smart watches, and heart rate monitors. Almost all users of wearable devices stated they experienced health and well-being benefits from the use of the devices. The most common benefits were support in increasing physical activity, giving information about the state of users’ health, and support in improving sleep. A third of the users stated they experienced drawbacks or challenges. The most common types of the drawbacks or challenges were the device inaccuracy in signal recording, the devices causing stress to the users, and devices feeling uncomfortable or causing skin rash. When selecting the devices, the users valued the device price, appearance and usability. Surprisingly device data privacy and data security features were relatively unimportant factors for the students in comparison to them being highlighted in the wearable device literature. Finally, only a small number of wearable device users shared the device data or used the wearable devices in cooperation with the health care professionals. The research results indicate that wearable devices provide tools with a great potential to support both students and student health care professionals in improving students’ health, well-being and studying ability.Terveys- ja hyvinvointiominaisuuksia sisältävien puettavien laitteiden käyttö on kasvanut viime vuosien aikana ja trendin odotetaan jatkuvan myös tulevina vuosina. Teknologia nykyajan laitteissa kykenee mittaamaan kehon biosignaaleja, kuten verenpainetta, kehon ja/tai ihon lämpötilaa ja sykettä. Puettavaa teknologiaa on suunniteltu käytettävän esimerkiksi painonhallinnan tuessa, sydän- ja veri-suoniterveydessä ja mielenterveysongelmien hoidossa sekä seurannassa. Tämän tutkimuksen tavoitteena oli selvittää, kuinka yleistä puettavien laitteiden käyttö oli yliopisto-opiskelijoilla Turussa, Suomessa ja mitä hyötyjä, haittoja tai haasteita puettavien laitteiden käytöstä koettiin. Lisäksi tavoitteina oli selvittää, mitä tekijöitä opiskelijat arvostivat puettavien laitteiden käyttöön liittyen ja olivatko opiskelijat käyttäneet laitteita yhteistyössä terveydenhuollon ammattilaisten kanssa. Tutkimus tehtiin hyödyntäen sekamenetelmä-lähestymistapaa yhdistäen ominaisuuksia määrällisistä ja laadullisista metodeista, jotta aihetta voitiin tutkia laaja-alaisella tavalla. Tutkimuskysymyksiin vastaamiseksi kerättiin tutkimusta varten empiirinen data käyttäen internet-kyselyä, joka jaettiin yliopisto-opiskelijoille Turussa syksyllä 2020. Kysely levitettiin opiskelijoille Turun yliopistossa ja Åbo Akademissa yhteistyössä yliopistojen opiskelijajärjestöjen kanssa. Lopullinen kyselyn otos oli 329 vastaajaa sisältäen osallistujia molemmista yliopistoista. 60 prosenttia kyselyyn vastanneista käytti puettavia laitteita ja 40 prosenttia ei. Yleisimmät käy-tetyt laitetyypit olivat aktiivisuuden seurantalaitteet, älykellot ja sykemittarit. Lähes kaikki puettavien laitteiden käyttäjät olivat kokeneet terveyteen ja hyvinvointiin liittyviä hyötyjä laitteiden käytöstä. Yleisimmät hyödyt olivat tuki fyysisen aktiivisuuden lisäämisessä, tietoisuuden lisääminen käyttäjien terveydentilasta ja tuki unen parantamisessa. Kolmannes käyttäjistä vastasi, että he olivat kokeneet haittoja tai haasteita. Yleisimmät haittojen tai haasteiden tyypit olivat laitteiden epätarkkuus signaalien mittaamisessa, laitteet aiheuttivat stressiä käyttäjille ja laitteet tuntuivat epämukavilta tai aiheuttivat ihottumaa. Laitteita valittaessa käyttäjät arvostivat laitteen hintaa, ulkonäköä, ja käytettävyyttä. Yllättäen laitteiden tietosuoja- ja tietoturvaominaisuudet olivat suhteellisen merkityksettömiä tekijöitä opiskelijoille verrattuna siihen, kuinka korostettuja tekijöitä ne olivat puettavien laitteiden kirjallisuudessa. Lopuksi vain pieni osa puettavien laitteiden käyttäjistä jakoi laitteiden dataa tai käyttivät laitteita yhteistyössä terveydenhuollon ammattilaisten kanssa. Tutkimuksen tulokset osoittavat, että puettavat laitteet tarjoavat työkaluja, joilla on valtava potentiaali tukea sekä opiskelijoita, että opiskelijaterveydenhuollon ammattilaisia opiskelijoiden terveyden, hyvinvoinnin ja opiskelukyvyn kehittämisessä