Ray's Night Out

Research Background: The proliferation of technologically-based interventions and mHealth in particular have led to a need for innovative, relevant and engaging ways of presenting health messages to young people using technology. ‘Ray’s Night Out’ is a mobile health application co-designed with young people by an interdisciplinary team of researchers at Queensland University of Technology. Research Questions: The design, research, development and evaluation of ‘Ray’s Night Out’ addressed a number of research questions from across the fields of Psychology and Interactive and Visual Design. The specific design research questions addressed were: How can a mobile intervention be best designed to promote young people’s safety and wellbeing and minimise harm when consuming alcohol on a typical night out? Specifically, how can principles of interactive and visual design be effectively applied to develop innovative digital health communication solutions that empower young people as active participants in improving their health and wellbeing? Research Contribution: Innovation The mobile app, as a digital artifact, represents a new way of engaging young people in the issue of alcohol consumption and the pacing and self-care behaviours through unique interaction, visual and interface designs which resulted from the participant-led and iterative design research process. The design of the specific interactive and visual features of the app informed by participatory design data and by health research present a novel approach to preventing young people in crossing the ‘stupid line’ on a typical night out. Research Significance: The significance of the design research component within the larger interdisciplinary practices that have informed ‘Ray’s Night Out’ (e.g. field of psychology, reported through journal articles and other related outcomes), is the unique visual and interactive presentation of participant data and health concepts within the app interface and interaction design which improves and increases young people’s engagement with the health messages it contains. The global quality standard is further demonstrated by the launch on Apple iTunes: https://itunes.apple.com/us/app/rays-night-out/id978589497?mt=8 This demonstrates the application meets the high professional requirements for global release and international standards set by Apple AppStore.

'Music eScape': mHealth application

Research Background Young people’s avid use of mobile technologies in daily life has led to an increase in the design and research on mHealth (mobile health) interventions targeting young people. ‘Music eScape’ is a mobile based mood regulation app that uses an innovative approach to promoting young people’s wellbeing using music. Research Question The design, research, development and evaluation of ‘Music eScape’ addressed a number of research questions from across the fields of Psychology and Interactive and Visual Design. The specific design research question addressed was: How can interaction and visual design be utilized to promote and enable young people to effectively regulate their mood using music and how can the new design further promote their experience of empowerment, control and agency over actively directing their mood journey? Research Contribution Innovation and New Knowledge Through its unique visual interface design and interactivity, the application presents a novel approach to promoting young people’s wellbeing using music and a specific function that allows users to ‘draw’ their mood journey in order to generate a playlist. The mobile app is the first to contain a function that enables users to plan their mood journey and exercise a sense of agency, intentional choice and control over the mood shift and by extension, their wellbeing. The feature ‘drawing’ interface was designed by Oksana Zelenko using participatory design research and Russell’s circumplex model of affect (1980) to inform the key visual design concept and underpinning interaction design. Research Significance The significance of the design research component within the larger interdisciplinary practices that have informed ‘Music eScape’ (e.g. field of psychology, reported through journal articles and other related outcomes), is the unique visual and interactive presentation of participant data and music therapy research within the app interface and interaction design which improves and increases young people’s engagement with the health messages it contains. The industry quality standard is further demonstrated by the launch on Apple iTunes. This demonstrates the application meets the high professional requirements for national release and meets international standards. The app also creates a new benchmark for the quality of health apps on the market as it marks the industry release of a trialled evidence-based mHealth intervention co-designed with young people.

Beyond Wearables : Experiences and Trends in Design of Portable Medical Devices

The use of Portable Medical Devices (PMDs) has become increasingly widespread over the last few years. A combination of factors; including advances in technology, the pressure to reduce public health costs and the desire to make health solutions accessible to a wider patient base are contributing to the growth in the PMD market. Design has a clear role to play in the current and future context of the PMD landscape. In this paper, we identify emerging trends in the design of PMDs; including changes in the form, purpose and mode of use, and explore how these trends are likely to fundamentally impact the nature of healthcare and the patient experience from an experience design perspective. We conclude by identifying a research opportunity for design within the healthcare and PMD context.

Understanding consumers' decisions to adopt technology-enabled transformative services

This study extends understanding of consumers' decisions to adopt transformative services delivered via technology. It incorporates competitive effects into the model of goal-directed behavior which, in keeping with the majority of consumer decision making models, neglects to explicitly account for competition. A goal-level operationalization of competition, incorporating both direct and indirect competition, is proposed. A national web-based survey collected data from 431 respondents about their decisions to adopt mental health services delivered via mobile phone. The findings show that the extent to which consumers perceived using these transformative services to be more instrumental to achieving their goals than competition had the greatest impact on their adoption decisions. This finding builds on the limited empirical evidence for the inclusion of competitive effects to more fully explain consumers' decisions to adopt technology-based and other services. It also provides support for a broader operationalization of competition with respect to consumers' personal goals.

eHealth e a adoção da inovação em assisted living technologies : o caso das demências

RESUMO - Assistimos hoje a um contexto marcado (i) pelo progressivo envelhecimento das sociedades ocidentais, (ii) pelo aumento da prevalência das doenças crónicas, de que as demências são um exemplo, (iii) pelo significativo aumento dos custos associados a estas patologias, (iv) por orçamentos públicos fortemente pressionadas pelo controlo da despesa, (v) por uma vida moderna que dificulta o apoio intergeracional, tornando o suporte proporcionado pelos filhos particularmente difícil, (vi) por fortes expectativas relativamente à prestação de cuidados de saúde com qualidade. Teremos assim de ser capazes de conseguir melhorar os serviços de saúde, ao mesmo tempo que recorremos a menos recursos financeiros e humanos, pelo que a inovação parece ser crítica para a sustentabilidade do sistema. Contudo a difusão das Assistive Living Technologies, apesar do seu potencial, tem sido bastante baixa, nomeadamente em Portugal. Porquê? Hamer, Plochg e Moreira (2012), no editorial do International Journal of Healthcare Management, enquadram a Inovação como “podendo ser imprevisível e mesmo dolorosa, pelo que talvez possamos não ficar surpreendidos se surgirem resistências e que, inovações bastante necessárias, capazes de melhorar os indicadores de saúde, tenham sido de adoção lenta ou que tenham mesmo sido insustentáveis”. Em Portugal não há bibliografia que procure caracterizar o modelo de difusão da inovação em eHealth ou das tecnologias de vivência assistida. A bibliografia internacional é igualmente escassa. O presente projeto de investigação, de natureza exploratória, tem como objetivo principal, identificar barreiras e oportunidades para a implementação de tecnologias eHealth, aplicadas ao campo das demências. Como objetivos secundários pretendemse identificar as oportunidades e limitações em Portugal: mapa de competências nacionais, e propor medidas que possa acelerar a inovação em ALT, no contexto nacional. O projeto seguirá o modelo de um estudo qualitativo. Para o efeito foram conduzidas entrevistas em profundidade junto de experts em ALT, procurando obter a visão daqueles que participam do lado da Oferta- a Indústria; do lado da Procura- doentes, cuidadores e profissionais de saúde; bem como dos Reguladores. O instrumento utilizado para a recolha da informação pretendida foi o questionário não estruturado. A análise e interpretação da informação recolhida foram feitas através da técnica de Análise de Conteúdo. Os resultados da Análise de Conteúdo efetuada permitiram expressar a dicotomia barreira/oportunidade, nas seguintes categorias aqui descritas como contextos (i) Contexto Tecnológico, nas subcategorias de Acesso às Infraestruturas; Custo da Tecnologia; Interoperabilidade, (ii) Contexto do Valor Percecionado, nas subcategorias de Utilidade; Eficiência; Divulgação, (iii) Contexto Político, compreendendo a Liderança; Organização; Regulação; Recursos, (iv) Contexto Sociocultural, incluindo nomeadamente Idade; Literacia; Capacidade Económica, (v) Contexto Individual, incluindo como subcategorias, Capacidade de Adaptação a Novas tecnologias; Motivação; Acesso a equipamentos (vi) Contexto Específico da Doença, nomeadamente o Impacto Cognitivo; Tipologia Heterogénea e a Importância do Cuidador. Foi proposto um modelo exploratório, designado de Modelo de Contextos e Forças, que estudos subsequentes poderão validar. Neste modelo o Contexto Tecnológico é um Força Básica ou Fundamental; o Contexto do Valor Percecionado, constitui-se numa Força Crítica para a adoção de inovação, que assenta na sua capacidade para oferecer valor aos diversos stakeholders da cadeia de cuidados. Temos também o Contexto Político, com capacidade de modelar a adoção da inovação e nomeadamente com capacidade para o acelerar, se dele emitir um sinal de urgência para a mudança. O Contexto Sociocultural e Individual expressam uma Força Intrínseca, dado que elas são características internas, próprias e imutáveis no curto-prazo, das sociedade e das pessoas. Por fim há que considerar o Contexto Específico da Doença, nesta caso o das demências. Das conclusões do estudo parece evidente que as condições tecnológicas estão medianamente satisfeitas em Portugal, com evidentes progressos nos últimos anos (exceção para a interoperabilidade aonde há necessidade de maiores progressos), não constituindo portanto barreira à introdução de ALT. Aonde há necessidade de investir é nas áreas do valor percebido. Da análise feita, esta é uma área que constitui uma barreira à introdução e adoção das ALT em Portugal. A falta de perceção do valor que estas tecnologias trazem, por parte dos profissionais de saúde, doentes, cuidadores e decisores políticos, parece ser o principal entrave à sua adoção. São recomendadas estratégias de modelos colaborativos de Investigação e Desenvolvimento e de abordagens de cocriação com a contribuição de todos os intervenientes na cadeia de cuidados. Há também um papel que cabe ao estado no âmbito das prioridades e da mobilização de recursos, sendo-lhe requerida a expressão do sentido de urgência para que esta mudança aconteça. Foram também identificadas oportunidades em diversas áreas, como na prevenção, no diagnóstico, na compliance medicamentosa, na terapêutica, na monitorização, no apoio à vida diária e na integração social. O que é necessário é que as soluções encontradas constituam respostas àquilo que são as verdadeiras necessidades dos intervenientes e não uma imposição tecnológica que só por si nada resolve. Do estudo resultou também a perceção de que há que (i) continuar a trabalhar no sentido de aproximar a comunidade científica, da clínica e do doente, (ii) fomentar a colaboração entre centros, com vista à criação de escala a nível global. Essa colaboração já parece acontecer a nível empresarial, tendo sido identificadas empresas Portuguesas com vocação global. A qualidade individual das instituições de ensino, dos centros de investigação, das empresas, permite criar as condições para que Portugal possa ser país um piloto e um case-study internacional em ALT, desde que para tal pudéssemos contar com um trabalho colaborativo entre instituições e com decisões políticas arrojadas.

mHealth Analisi e sviluppo delle tecnologie applicative al giorno d’oggi

La tesi sviluppa una rassegna delle applicazioni nel campo mHealth al giorno d'oggi, analizzandone l'utilizzo pratico e lo sviluppo informatico.

Modelado de un servicio de M-Salud basado en dinámica de sistemas

En términos generales, m-salud puede definirse como el conjunto de sistemas de información, sensores médicos y tecnologías de comunicaciones móviles para el cuidado de la salud. La creciente disponibilidad, miniaturización, comportamiento, velocidades de transmisión de datos cada vez mayores y la esperada convergencia de tecnologías de red y comunicaciones inalámbricas en torno a los sistemas de salud móviles están acelerando el despliegue de estos sistemas y la provisión de servicios de m-salud, como por ejemplo, la teleasistencia móvil. El concepto emergente de m-salud conlleva retos importantes (estudios técnicos, análisis, modelado de la provisión de servicios, etc.) que hay que afrontar para impulsar la evolución de los sistemas y servicios de e-salud ofrecidos desde tecnologías de telecomunicación que utilizan acceso por cable y redes fijas, hacia configuraciones móviles e inalámbricas de última generación. En este trabajo se analizará primeramente el significado e implicaciones de m-salud y la situación en la que se encuentra; los retos a los que hay que enfrentarse para su implantación y provisión así como su tendencia. De los múltiples y diferentes servicios que se pueden proveer se ha identificado el servicio de Localización de Personas LoPe, lanzado por Cruz Roja en febrero de 2007, para teleasistencia móvil y que permite conocer en todo momento la ubicación de la persona que porta su dispositivo asociado. Orientado a personas con discapacidad, en situación de riesgo o dependencia por deterioro cognitivo, tiene como objetivo ayudarlas a recuperar su autonomía personal. La provisión de este servicio se modelará mediante dinámica de sistemas, ya que esta teoría se considera idónea para modelar sistemas complejos que evolucionan con el tiempo. El resultado final es un modelo que implementado a través de la herramienta Studio 8® de la compañía noruega Powersim Software AS nos ha permitido analizar y evaluar su comportamiento a lo largo del tiempo, además de permitirnos extraer conclusiones sobre el mismo y plantear futuras mejoras sobre el servicio. ABSTRACT. In general terms, m-health can be defined as “mobile computing, medical sensor, and communications technologies for health care.” The increased availability, miniaturization, performance, enhanced data rates, and the expected convergence of future wireless communication and network technologies around mobile health systems are accelerating the deployment of m-health systems and services, for instance, mobile telecare. The emerging concept of m-health involves significant challenges (technical studies, analysis, modeling of service provision, etc.) that must be tackled to drive the development of e-health services and systems offered by telecommunication technologies that use wired and fixed networks towards wireless and mobile new generation networks. Firstly, in this master’s thesis, the meaning and implications of m-health and its current situation are analyzed. This analysis also includes the challenges that must be tackled for the implementation and provision of m-health technologies and services and the m-health trends. Among the many different m-health services already delivered, the Localización de Personas LoPe service has been identified to work with it. This service, launched by Spanish Red Cross in February 2007, enables to locate people who carry the associated device. It’s aimed at people with disabilities, at risk or dependency due to cognitive impairment and helps them to recover their personal autonomy. The provision of this service will be modeled with system dynamics considering that this theory suits very well the modeling of complex systems which evolve over time. The final result is a system dynamics model of the service implemented with Studio 8® tool developed by Powersim Software AS, a Norwegian company. This model has allowed us to analyze and evaluate its behaviour over time, as well as to draw conclusions and to consider some future improvements in the service.

A technological framework based on automatic messaging for improving adherence of diabetic patients

En todo el mundo se ha observado un crecimiento exponencial en la incidencia de enfermedades crónicas como la hipertensión y enfermedades cardiovasculares y respiratorias, así como la diabetes mellitus, que causa un número de muertes cada vez mayor en todo el mundo (Beaglehole et al., 2008). En concreto, la prevalencia de diabetes mellitus (DM) está aumentando de manera considerable en todas las edades y representa un serio problema de salud mundial. La diabetes fue la responsable directa de 1,5 millones de muertes en 2012 y 89 millones de años de vida ajustados por discapacidad (AVAD) (OMS, 2014). Uno de los principales dilemas que suelen asociarse a la gestión de EC es la adherencia de los pacientes a los tratamientos, que representa un aspecto multifactorial que necesita asistencia en lo relativo a: educación, autogestión, interacción entre los pacientes y cuidadores y compromiso de los pacientes. Medir la adherencia del tratamiento es complicado y, aunque se ha hablado ampliamente de ello, aún no hay soluciones “de oro” (Reviews, 2002). El compromiso de los pacientes, a través de la participación, colaboración, negociación y a veces del compromiso firme, aumentan las oportunidades para una terapia óptima en la que los pacientes se responsabilizan de su parte en la ecuación de adherencia. Comprometer e involucrar a los pacientes diabéticos en las decisiones de su tratamiento, junto con expertos profesionales, puede ayudar a favorecer un enfoque centrado en el paciente hacia la atención a la diabetes (Martin et al., 2005). La motivación y atribución de poder de los pacientes son quizás los dos factores interventores más relevantes que afectan directamente a la autogestión de la atención a la diabetes. Se ha demostrado que estos dos factores desempeñan un papel fundamental en la adherencia a la prescripción, así como en el fomento exitoso de un estilo de vida sana y otros cambios de conducta (Heneghan et al., 2013). Un plan de educación personalizada es indispensable para proporcionarle al paciente las herramientas adecuadas que necesita para la autogestión efectiva de la enfermedad (El-Gayar et al. 2013). La comunicación efectiva es fundamental para proporcionar una atención centrada en el paciente puesto que influye en las conductas y actitudes hacia un problema de salud ((Frampton et al. 2008). En este sentido, la interactividad, la frecuencia, la temporalización y la adaptación de los mensajes de texto pueden promover la adherencia a un régimen de medicación. Como consecuencia, adaptar los mensajes de texto a los pacientes puede resultar ser una manera de hacer que las sugerencias y la información sean más relevantes y efectivas (Nundy et al. 2013). En este contexto, las tecnologías móviles en el ámbito de la salud (mHealth) están desempeñando un papel importante al conectar con pacientes para mejorar la adherencia a medicamentos recetados (Krishna et al., 2009). La adaptación de los mensajes de texto específicos de diabetes sigue siendo un área de oportunidad para mejorar la adherencia a la medicación y ofrecer motivación a adultos con diabetes. Sin embargo, se necesita más investigación para entender totalmente su eficacia. Los consejos de texto personalizados han demostrado causar un impacto positivo en la atribución de poder a los pacientes, su autogestión y su adherencia a la prescripción (Gatwood et al., 2014). mHealth se puede utilizar para ofrecer programas de asistencia de autogestión a los pacientes con diabetes y, al mismo tiempo, superar las dificultades técnicas y financieras que supone el tratamiento de la diabetes (Free at al., 2013). El objetivo principal de este trabajo de investigación es demostrar que un marco tecnológico basado en las teorías de cambios de conducta, aplicado al campo de la mHealth, permite una mejora de la adherencia al tratamiento en pacientes diabéticos. Como método de definición de una solución tecnológica, se han adoptado un conjunto de diferentes técnicas de conducta validadas denominado marco de compromiso de retroacción conductual (EBF, por sus siglas en inglés) para formular los mensajes, guiar el contenido y evaluar los resultados. Los estudios incorporan elementos del modelo transteórico (TTM, por sus siglas en inglés), la teoría de la fijación de objetivos (GST, por sus siglas en inglés) y los principios de comunicación sanitaria persuasiva y eficaz. Como concepto general, el modelo TTM ayuda a los pacientes a progresar a su próxima fase de conducta a través de mensajes de texto motivados específicos y permite que el médico identifique la fase actual y adapte sus estrategias individualmente. Además, se adoptan las directrices del TTM para fijar objetivos personalizados a un nivel apropiado a la fase de cambio del paciente. La GST encierra normas que van a ponerse en práctica para promover la intervención educativa y objetivos de pérdida de peso. Finalmente, los principios de comunicación sanitaria persuasiva y eficaz aplicados a la aparición de los mensajes se han puesto en marcha para aumentar la efectividad. El EBF tiene como objetivo ayudar a los pacientes a mejorar su adherencia a la prescripción y encaminarlos a una mejora general en la autogestión de la diabetes mediante mensajes de texto personalizados denominados mensajes de retroacción automáticos (AFM, por sus siglas en inglés). Después de una primera revisión del perfil, consistente en identificar características significativas del paciente basadas en las necesidades de tratamiento, actitudes y conductas de atención sanitaria, el sistema elige los AFM personalizados, los aprueba el médico y al final se transfieren a la interfaz del paciente. Durante el tratamiento, el usuario recopila los datos en dispositivos de monitorización de pacientes (PMD, por sus siglas en inglés) de una serie de dispositivos médicos y registros manuales. Los registros consisten en la toma de medicación, dieta y actividad física y tareas de aprendizaje y control de la medida del metabolismo. El compromiso general del paciente se comprueba al estimar el uso del sistema y la adherencia del tratamiento y el estado de los objetivos del paciente a corto y largo plazo. El módulo de análisis conductual, que consiste en una serie de reglas y ecuaciones, calcula la conducta del paciente. Tras lograr el análisis conductual, el módulo de gestión de AFM actualiza la lista de AFM y la configuración de los envíos. Las actualizaciones incluyen el número, el tipo y la frecuencia de mensajes. Los AFM los revisa periódicamente el médico que también participa en el perfeccionamiento del tratamiento, adaptado a la fase transteórica actual. Los AFM se segmentan en distintas categorías y niveles y los pacientes pueden ajustar la entrega del mensaje de acuerdo con sus necesidades personales. El EBF se ha puesto en marcha integrado dentro del sistema METABO, diseñado para facilitar al paciente diabético que controle sus condiciones relevantes de una manera menos intrusiva. El dispositivo del paciente se vincula en una plataforma móvil, mientras que una interfaz de panel médico permite que los profesionales controlen la evolución del tratamiento. Herramientas específicas posibilitan que los profesionales comprueben la adherencia del paciente y actualicen la gestión de envíos de AFM. El EBF fue probado en un proyecto piloto controlado de manera aleatoria. El principal objetivo era examinar la viabilidad y aceptación del sistema. Los objetivos secundarios eran también la evaluación de la eficacia del sistema en lo referente a la mejora de la adherencia, el control glucémico y la calidad de vida. Se reclutaron participantes de cuatro centros clínicos distintos en Europa. La evaluación del punto de referencia incluía datos demográficos, estado de la diabetes, información del perfil, conocimiento de la diabetes en general, uso de las plataformas TIC, opinión y experiencia con dispositivos electrónicos y adopción de buenas prácticas con la diabetes. La aceptación y eficacia de los criterios de evaluación se aplicaron para valorar el funcionamiento del marco tecnológico. El principal objetivo era la valoración de la eficacia del sistema en lo referente a la mejora de la adherencia. En las pruebas participaron 54 pacientes. 26 fueron asignados al grupo de intervención y equipados con tecnología móvil donde estaba instalado el EBF: 14 pacientes tenían T1DM y 12 tenían T2DM. El grupo de control estaba compuesto por 25 pa cientes que fueron tratados con atención estándar, sin el empleo del EBF. La intervención profesional tanto de los grupos de control como de intervención corrió a cargo de 24 cuidadores, entre los que incluían diabetólogos, nutricionistas y enfermeras. Para evaluar la aceptabilidad del sistema y analizar la satisfacción de los usuarios, a través de LimeSurvey, se creó una encuesta multilingüe tanto para los pacientes como para los profesionales. Los resultados también se recopilaron de los archivos de registro generados en los PMD, el panel médico profesional y las entradas de la base de datos. Los mensajes enviados hacia y desde el EBF y los archivos de registro del sistema y los servicios de comunicación se grabaron durante las cinco semanas del estudio. Se entregaron un total de 2795 mensajes, lo que supuso una media de 107,50 mensajes por paciente. Como se muestra, los mensajes disminuyen con el tiempo, indicando una mejora global de la adherencia al plan de tratamiento. Como se esperaba, los pacientes con T1DM recibieron más consejos a corto plazo, en relación a su estado. Del mismo modo, al ser el centro de T2DM en cambios de estilo de vida sostenible a largo plazo, los pacientes con T2DM recibieron más consejos de recomendación, en cuanto a dietas y actividad física. También se ha llevado a cabo una comparación de la adherencia e índices de uso para pacientes con T1DM y T2DM, entre la primera y la segunda mitad de la prueba. Se han observado resultados favorables para el uso. En lo relativo a la adherencia, los resultados denotaron una mejora general en cada dimensión del plan de tratamiento, como la nutrición y las mediciones de inserción de glucosa en la sangre. Se han llevado a cabo más estudios acerca del cambio a nivel educativo antes y después de la prueba, medidos tanto para grupos de control como de intervención. Los resultados indicaron que el grupo de intervención había mejorado su nivel de conocimientos mientras que el grupo de control mostró una leve disminución. El análisis de correlación entre el nivel de adherencia y las AFM ha mostrado una mejora en la adherencia de uso para los pacientes que recibieron los mensajes de tipo alertas, y unos resultados no significativos aunque positivos relacionados con la adherencia tanto al tratamiento que al uso correlacionado con los recordatorios. Por otra parte, los AFM parecían ayudar a los pacientes que no tomaban suficientemente en serio su tratamiento en el principio y que sí estaban dispuestos a responder a los mensajes recibidos. Aun así, los pacientes que recibieron demasiadas advertencias, comenzaron a considerar el envío de mensajes un poco estresante. El trabajo de investigación llevado a cabo al desarrollar este proyecto ofrece respuestas a las cuatro hipótesis de investigación que fueron la motivación para el trabajo. • Hipótesis 1 : es posible definir una serie de criterios para medir la adherencia en pacientes diabéticos. • Hipótesis 2: es posible diseñar un marco tecnológico basado en los criterios y teorías de cambio de conducta mencionados con anterioridad para hacer que los pacientes diabéticos se comprometan a controlar su enfermedad y adherirse a planes de atención. • Hipótesis 3: es posible poner en marcha el marco tecnológico en el sector de la salud móvil. • Hipótesis 4: es posible utilizar el marco tecnológico como solución de salud móvil en un contexto real y tener efectos positivos en lo referente a indicadores de control de diabetes. La verificación de cada hipótesis permite ofrecer respuesta a la hipótesis principal: La hipótesis principal es: es posible mejorar la adherencia diabética a través de un marco tecnológico mHealth basado en teorías de cambio de conducta. El trabajo llevado a cabo para responder estas preguntas se explica en este trabajo de investigación. El marco fue desarrollado y puesto en práctica en el Proyecto METABO. METABO es un Proyecto I+D, cofinanciado por la Comisión Europea (METABO 2008) que integra infraestructura móvil para ayudar al control, gestión y tratamiento de los pacientes con diabetes mellitus de tipo 1 (T1DM) y los que padecen diabetes mellitus de tipo 2 (T2DM). ABSTRACT Worldwide there is an exponential growth in the incidence of Chronic Diseases (CDs), such as: hypertension, cardiovascular and respiratory diseases, as well as diabetes mellitus, leading to rising numbers of deaths worldwide (Beaglehole et al. 2008). In particular, the prevalence of diabetes mellitus (DM) is largely increasing among all ages and constitutes a major worldwide health problem. Diabetes was directly responsible for 1,5 million deaths in 2012 and 89 million Disability-adjusted life year (DALYs) (WHO 2014). One of the key dilemmas often associated to CD management is the patients’ adherence to treatments, representing a multi-factorial aspect that requires support in terms of: education, self-management, interaction between patients and caregivers, and patients’ engagement. Measuring adherence is complex and, even if widely discussed, there are still no “gold” standards ((Giardini et al. 2015), (Costa et al. 2015). Patient’s engagement, through participation, collaboration, negotiation, and sometimes compromise, enhance opportunities for optimal therapy in which patients take responsibility for their part of the adherence equation. Engaging and involving diabetic patients in treatment decisions, along with professional expertise, can help foster a patient-centered approach to diabetes care (Martin et al. 2005). Patients’ motivation and empowerment are perhaps the two most relevant intervening factors that directly affect self-management of diabetes care. It has been demonstrated that these two factors play an essential role in prescription adherence, as well as for the successful encouragement of a healthy life-style and other behavioural changes (Heneghan et al. 2013). A personalised education plan is indispensable in order to provide the patient with the appropriate tools needed for the effective self-management of the disease (El-Gayar et al. 2013). Effective communication is at the core of providing patient-centred care since it influences behaviours and attitudes towards a health problem (Frampton et al. 2008). In this regard, interactivity, frequency, timing, and tailoring of text messages may promote adherence to a medication regimen. As a consequence, tailoring text messages to patients can constitute a way of making suggestions and information more relevant and effective (Nundy et al. 2013). In this context, mobile health technologies (mHealth) are playing significant roles in improving adherence to prescribed medications (Krishna et al. 2009). The tailoring of diabetes-specific text messages remains an area of opportunity to improve medication adherence and provide motivation to adults with diabetes but further research is needed to fully understand their effectiveness. Personalized text advices have proven to produce a positive impact on patients’ empowerment, self-management, and adherence to prescriptions (Gatwood et al. 2014). mHealth can be used for offering self-management support programs to diabetes patients and at the same time surmounting the technical and financial difficulties involved in diabetes treatment (Free et al. 2013). The main objective of this research work is to demonstrate that a technological framework, based on behavioural change theories, applied to mHealth domain, allows improving adherence treatment in diabetic patients. The framework, named Engagement Behavioural Feedback Framework (EBF), is built on top of validated behavioural techniques to frame messages, guide the definition of contents and assess outcomes: elements from the Transtheoretical Model (TTM), the Goal-Setting Theory (GST), Effective Health Communication (EHC) guidelines and Principles of Persuasive Technology (PPT) were incorporated. The TTM helps patients to progress to a next behavioural stage, through specific motivated text messages, and allow clinician’s identifying the current stage and tailor its strategies individually. Moreover, TTM guidelines are adopted to set customised goals at a level appropriate to the patient’s stage of change. The GST was used to build rules to be applied for enhancing educational intervention and weight loss objectives. Finally, the EHC guidelines and the PPT were applied to increase the effectiveness of messages. The EBF aims to support patients on improving their prescription adherence and persuade them towards a general improvement in diabetes self-management, by means of personalised text messages, named Automatic Feedback Messages (AFM). After a first profile screening, consisting in identifying meaningful patient characteristics based on treatment needs, attitudes and health care behaviours, customised AFMs are selected by the system, approved by the professional, and finally transferred into the patient interface. During the treatment, the user collects the data into a Patient Monitoring Device (PMD) from a set of medical devices and from manual inputs. Inputs consist in medication intake, diet and physical activity, metabolic measurement monitoring and learning tasks. Patient general engagement is checked by estimating the usage of the system and the adherence of treatment and patient goals status in the short and the long term period. The Behavioural Analysis Module, consisting in a set of rules and equations, calculates the patient’s behaviour. After behavioural analysis is accomplished, the AFM library and the dispatch setting are updated by the AFM Manager module. Updates include the number, the type and the frequency of messages. The AFMs are periodically supervised by the professional who also participates to the refinement of the treatment, adapted to the current transtheoretical stage. The AFMs are segmented in different categories and levels and patients can adjust message delivery in accordance with their personal needs. The EBF was integrated to the METABO system, designed to facilitate diabetic patients in managing their disease in a less intrusive approach. Patient device corresponds in a mobile platform, while a medical panel interface allows professionals to monitoring the treatment evolution. Specific tools allow professional to check patient adherence and to update the AFMs dispatch management. The EBF was tested in a randomised controlled pilot. The main objective was to examine the feasibility and acceptance of the system. Secondary objectives were also the assessment of the effectiveness of system in terms of adherence improvement, glycaemic control, and quality of life. Participants were recruited from four different clinical centres in Europe. The baseline assessment included demographics, diabetes status, profile information, knowledge about diabetes in general, usage of ICT platforms, opinion and experience about electronic devices and adoption of good practices with diabetes. Acceptance and the effectiveness evaluation criteria were applied to evaluate the performance of the technological framework. The main objective was the assessment of the effectiveness of system in terms of adherence improvement. Fifty-four patients participated on the trials. Twenty-six patients were assigned in the intervention group and equipped with mobile where the EBF was installed: 14 patients were T1DM and 12 were T2DM. The control group was composed of 25 patients that were treated through a standard care, without the usage of the EBF. Professional’s intervention for both intervention and control groups was carried out by 24 care providers, including endocrinologists, nutritionists, and nurses. In order to evaluate the system acceptability and analyse the users’ satisfaction, an online multi-language survey, using LimeSurvey, was produced for both patients and professionals. Results were also collected from the log-files generated in the PMDs, the professional medical panel and the entries of the data base. The messages sent to and from the EBF and the log-files of the system and communication services were recorded over 5 weeks of the study. A total of 2795 messages were submitted, representing an average of 107,50 messages per patient. As demonstrated, messages decrease over time indicating an overall improvement of the care plan’s adherence. As expected, T1DM patients were more loaded with short-term advices, in accordance with their condition. Similarly, being the focus of T2DM on long-term sustainable lifestyle changes, T2DM received more reminders advices, as for diet and physical activity. Favourable outcomes were observed for treatment and usage adherences of the intervention group: for both the adherence indices, results denoted a general improvement on each care plan’s dimension, such as on nutrition and blood glucose input measurements. Further studies were conducted on the change on educational level before and after the trial, measured for both control and intervention groups. The outcomes indicated the intervention group has improved its level of knowledge, while the control group denoted a low decrease. The correlation analysis between the level of adherences and the AFMs showed an improvement in usage adherence for patients who received warnings message, while non-significantly yet even positive indicators related to both treatment and usage adherence correlated with the Reminders. Moreover, the AFMs seemed to help those patients who did not take their treatment seriously enough in the beginning and who were willing to respond to the messages they received. Even though, patients who received too many Warnings, started to consider the message dispatch to be a bit stressful. The research work carried out in developing this research work provides responses to the four research hypothesis that were the motivation for the work: •Hypothesis 1: It is possible to define a set of criteria to measure adherence in diabetic patients. •Hypothesis 2: It is possible to design a technological framework, based on the aforementioned criteria and behavioural change theories, to engage diabetic patients in managing their disease and adhere to care plans. •Hypothesis 3: It is possible to implement the technological framework in the mobile health domain. •Hypothesis 4: It is possible to use the technological framework as a mobile health solution in a real context and have positive effects in terms of diabetes management indicators. The verification of each hypothesis allowed us to provide a response to the main hypothesis: The Main Hypothesis is: It is possible to improve diabetic adherence through a mHealth technological framework based on behavioural change theories. The work carried out to answer these questions is explained in this research work. The framework was developed and applied in the METABO project. METABO is an R&D project, co-funded by the European Commission (METABO 2008) that integrates mobile infrastructure for supporting the monitoring, management, and treatment of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients.

Factors associated with pregnant women's participation in a mHealth intervention in Timor-Leste

Thesis (Master's)--University of Washington, 2016-06

Text-messaging as a Tool for Medication Adherence and Behavior Change in Disease Management among Patients with Coronary Heart Disease

Background: Evidence-based medication and lifestyle modification are important for secondary prevention of cardiovascular disease but are underutilized. Mobile health strategies could address this gap but existing evidence is mixed. Therefore, we piloted a pre-post study to assess the impact of patient-directed text messages as a means of improving medication adherence and modifying major health risk behaviors among coronary heart disease (CHD) patients in Hainan, China.

Methods: 92 CVD patients were surveyed between June and August 2015 (before the intervention) and then between October and December 2015 (after 12 week intervention) about (a) medication use (b) smoking status,(c) fruit and vegetable consumption, and (d) physical activity uptake. Acceptability of text-messaging intervention was assessed at follow-up. Descriptive statistics, along with paired comparisons between the pre and post outcomes were conducted using both parametric (t-test) and non-parametric (Wilcoxon signed rank test) methods.

Results: The number of respondents at follow-up was 82 (89% retention rate). Significant improvements were observed for medication adherence (P<0.001) and for the number of cigarettes smoked per day (P=.022). However there was no change in the number of smokers who quitted smoking at follow-up. There were insignificant changes for physical activity (P=0.91) and fruit and vegetable consumption.

mHealth in Urology: A Review of Experts' Involvement in App Development

Smartphones are increasingly playing a role in healthcare and previous studies assessing medical applications (apps) have raised concerns about lack of expert involvement and low content accuracy. However, there are no such studies in Urology. We reviewed Urology apps with the aim of assessing the level of participation of healthcare professionals (HCP) and scientific Urology associations in their development.

A gestão da pessoa com hipertensão arterial na unidade móvel de saúde

Enquadramento: A gestão da doença, designadamente da hipertensão arterial (HTA) através do apoio à auto-gestão, aconselhamento motivacional, acesso à informação resultam em maior adesão terapêutica. Objetivos: Identificar os fatores que determinam a adesão ao tratamento na pessoa com HTA numa amostra comunitária. Metodologia: Estudo transversal, descritivo-correlacional, com amostra de 235 hipertensos (63,8% do género feminino), idade média 75 ± 8,14 anos, 62,6% casados e a maioria com o 1.º ciclo de escolaridade. Recorremos ao questionário com variáveis sociodemográficas, dietéticas, clínicas, motivacionais, relacionadas com os profissionais e serviços de saúde, Escala de Apgar Familiar, Questionário de Dependência Alcoólica, Questionário Internacional de Atividade Física, Questionário de Determinação da Saúde Nutricional, Escala de Autocuidado com a Hipertensão, Questionário de Crenças Sobre a Doença, Escala de Crenças Acerca dos Medicamentos, Escala de Satisfação dos Utentes com os Cuidados de Enfermagem na Unidade Móvel de Saúde, Questionário abreviado da Perceção do Cliente sobre o Ambiente Terapêutico, Questionário de Autorregulação, Escala de Competência Percebida e Escala de Medida de Adesão aos Tratamentos para colheita de dados. Resultados: A pressão arterial estava controlada em 34,5% da amostra, 28,2% homens e 38% mulheres. A MAT revelou um mínimo de 3,86 e um máximo de 6 com uma média de 5,66±0,49. As variáveis preditoras da adesão foram: controlo pessoal (p=0,005), identidade (p=0,000), ambiente terapêutico (p=0,001), alimentação geral (p=0,041), atividade física (p=0,007) e toma de medicamentos (p=0,000). Conclusões: Compreender os fatores envolvidos na gestão do tratamento permite perceber como podem os enfermeiros contribuir para melhorar a adesão ao regime terapêutico. Palavras-chave: Hipertensão arterial, gestão da doença crónica, adesão ao tratamento e adultos.

Using mobile social media and GIS in health and place research

This paper presents new research methods that combine the use of location-based, social media on mobile phones with geographic information systems (GIS) to explore connections between people, place and health. It discusses the feasibility, limitations, and benefits of using these methods, which enable real-time, location-based, quantitative data to be collected on the recreation, consumption, and physical activity patterns of urban residents in Brisbane, Queensland. The study employs mechanisms already inherent in popular mobile social media applications (Facebook, Twitter and Foursquare) to collect this data. The research methods presented in this paper are innovative and potentially applicable to an increasing number of academic research areas, as well as to a growing range of service providers that benefit from monitoring consumer behaviour, and responding to emerging changes in these patterns and trends. The ability to both collect and map objective, real-time data about the consumption, leisure, recreation, and physical activity patterns amongst urban communities has direct implications for a range of research disciplines including media studies, advertising, health promotion, social marketing, public health inequalities, and urban design.

Secure authentication procedure with mobile device for ubiquitous health environments

Medical industries have brought Information Technology (IT) in their systems for both patients and medical staffs due to the numerous benefits of IT we experience at presently. Moreover, the Mobile healthcare (M-health) system has been developed as the first step of Ubiquitous Health Environment (UHE). With the mobility and multi-functions, M-health system will be able to provide more efficient and various services for both doctors and patients. Due to the invisible feature of mobile signals, hackers have easier access to hospital networks than wired network systems. This may result in several security incidents unless security protocols are well implemented. In this paper, user authentication and authorization procedures will applied as a featured component at each level of M-health systems inthe hospital environment. Accordingly, M-health system in the hospital will meet the optimal requirements as a countermeasure to its vulnerabilities.