A Model to Define an eHealth Technological Ecosystem for Caregivers

The ageing of world population has a direct impact on the health and care systems, as it means an increase in the number of people needing care which leads to higher care costs and the need for more resources. In this context, informal caregivers play an important role as they enable dependent persons to stay at home and thus reduce care costs. However, long-term continuous care provision has also an impact in the physical and mental health of the caregivers. Moreover, geographical barriers make it difficult for caregivers to accessing psychoeducation as a way to alleviate their problems. To support caregivers in their needs and provide specialized training, technology plays a fundamental role. The present work provides the theoretical basis for the development of a technological ecosystem focused on learning and knowledge management processes to develop and enhance the caregiving competences of formal and informal caregivers, both at home and in care environments. In particular, a platform-specific model to support the definition of the ecosystem based on Open Source software components is presented, along with a Business Model Canvas to define the business structure as part of the human elements of the technological ecosystem

Modelling the business structure of a digital health ecosystem

[EN]The current trend in digital solutions for the health sector is to move from fragmented services to progressively more integrated services provided by multiple stakeholders through technological ecosystem platforms. However, the business model is scarcely taken into account at the early stages of development of this type of ecosystems specially in the health sector. In the present paper a general approach towards the exploitation of a technological ecosystem focused on caregivers is presented. It follows the Business Process Model and Notation (BPMN) in order to develop different ecosystem’s exploitation alternatives, taking into account the ecosystem stakeholders and their main value propositions. This serves as a starting data model in the software development process from which different business exploitation alternatives can be elaborated

Integrating Emotion Recognition Tools for Developing Emotionally Intelligent Agents

Emotionally responsive agents that can simulate emotional intelligence increase the acceptance of users towards them, as the feeling of empathy reduces negative perceptual feedback. This has fostered research on emotional intelligence during last decades, and nowadays numerous cloud and local tools for automatic emotional recognition are available, even for inexperienced users. These tools however usually focus on the recognition of discrete emotions sensed from one communication channel, even though multimodal approaches have been shown to have advantages over unimodal approaches. Therefore, the objective of this paper is to show our approach for multimodal emotion recognition using Kalman filters for the fusion of available discrete emotion recognition tools. The proposed system has been modularly developed based on an evolutionary approach so to be integrated in our digital ecosystems, and new emotional recognition sources can be easily integrated. Obtained results show improvements over unimodal tools when recognizing naturally displayed emotions

Older people and eHealth service use An exploration of a complex learning and care ecosystem in the rural areas of Finnish Lapland

Tämä väitöskirja kohdistuu ikäihmisten (yli 60-vuotiaiden) arkeen digitalisoituvien sosiaali- ja terveyspalveluiden näkökulmasta. Tutkimuksen yleisenä tavoitteena on selvittää, kuinka harvaan asutuilla alueilla asuvat ikäihmiset ja heidän sosiaaliset verkostonsa käyttävät kotihoidon tarjoamia eTerveyspalveluita (eHealth services) oppimisen ja hoivan ekosysteemissä. eTerveyspalveluiden käytön tavoitteena on tukea ja helpottaa ikäihmisten sekä heidän hoitajiensa ja läheistensä terveyttä, hyvinvointia ja arkea parantamalla sosiaali- ja terveyspalveluiden saavutettavuutta ja laatua sekä vähentämällä niiden kustannuksia. eTerveyspalveluiden käyttö herättää myös suuren määrään inhimillisiä eettisiä kysymyksiä. Yksityiskohtaisemmin tutkimuksen tavoitteena on (1) lisätä tietoisuutta digitaalisesta osaamisesta eTerveyspalveluiden käytön oppimisessa ja käytössä, (2) selventää, millä tavalla oppimisprosessi on osa eTerveyspalveluiden kotouttamista, (3) rakentaa teoreettis-käsitteellinen malli eTerveyspalveluiden oppimiseen ja käyttöön, ja (4) antaa kehitysehdotuksia eTerveyspalveluiden suunnittelulle ja toteuttamiselle. Nämä tavoitteet saavutetaan kolmen teoreettisen lähestymistavan kautta. Oppimisen ja hoivan ekosysteemi muodostaa tutkimukselle perustan, hahmottaen ikäihmisten eTerveyspalveluiden oppimista ja käyttöä neljästä eri näkökulmasta: käytännön, sosiaalisen, kulttuurisen ja symbolisen kontekstin kautta. Digitaalisen osaamisen ja teknologian kotouttamisen käsitteet keskittyvät siihen prosessiin, miten ikäihmiset oppivat käyttämään ja käyttävät eTerveyspalveluita arjessaan. Sosiaalisen konstruktivismin paradigmasta ohjaa tutkimuksen suunnittelua soveltuvin osin. Tutkimuksen metodologinen lähestymistapa on laadullinen, sisältäen kirjallisuuskatsauksen ja empiirisiä aineistoja. Väitöskirja perustuu kolmeen osatutkimukseen, joista jokainen on julkaistu erillisenä artikkelina. Ensimmäinen osatutkimus on systemaattinen kirjallisuuskatsaus. Se sisältää 31 empiiristä tutkimusta ikäihmisten erilaisten eTerveyspalveluiden käytöstä ja käytön oppimisesta 12 eri maassa harvaan asutuilla alueilla ja niiden ulkopuolella. Toinen ja kolmas osatutkimus sijoittuvat Suomen Lapin harvaan asutuille alueille. Lääkeannostelupalvelun (osatutkimus II) sekä ikäihmisille seuraa tarjoavan puhelin- ja videoneuvottelupalvelun (osatutkimus III) käyttöä ja käytön oppimista tutkin tapaustutkimuksen keinoin. Lääkeannostelupalvelututkimukseen osallistui palvelua käyttäviä ikäihmisiä (n=2), lähihoitajia (n=4) ja muita terveydenhuollon ammattilaisia (n=2). Lääkeannostelupalvelun tutkimisessa hyödynnettiin etnografista tutkimusotetta: semi-strukturoitujen haastatteluiden lisäksi palvelun käyttöä havainnoitiin ja palveluun kuuluvasta lääkeannostelurobotista otettiin kuvia ikäihmisten kotona. Puhelin- ja videoneuvottelupalvelua koskeviin semi-strukturoituihin haastatteluihin osallistui palvelua käyttäviä ikäihmisiä (n=2), vapaaehtoistyöntekijöitä (n=2) sekä palvelun koordinaattori. Osatutkimusten aineistot analysoitiin induktiivisen ja deduktiivisen temaattisen lähestymistavan avulla. Väitöskirjan kokoavat havainnot syntyivät osatutkimusten keskeisten tulosten metasynteesistä. Metasynteesin tuloksena saatiin selville, että oppimisen ja hoivan ekosysteemin käytännön kontekstiin liittyen eTerveyspalveluiden kotouttamiseen vaikuttaa eniten niiden käytettävyys ja toimivuus sekä palveluiden yhteensopivuus käyttäjien kulttuurisesti rakentuneiden yhteisöllisten käytäntöjen kanssa. Tutkimuksessa havaittiin, että oppimisen ja hoivan ekosysteemin sosiaalisen kontekstin keskiössä on oppimisyhteisö, jonka ikäihmiset muodostavat yhdessä läheisasiantuntijoiden, ammattilaisten ja eTerveysteknologioiden kanssa. Oppimisyhteisö mahdollistaa eTerveyspalveluiden oppimiseen ja käyttöön tarvittavan digitaalisen osaamisen jaettuna, sosiaalisena osaamisena sekä eTerveyspalveluiden kotouttamisen sosiaalisena prosessina. eTerveyspalveluiden kotouttamisen myötä sosiaali- ja terveydenhuollon ammattilaiset ja vapaaehtoistyöntekijät ovat saaneet uuden roolin eTerveyspalveluita käyttävien ikäihmisten oppimisen ohjaajina. Pedagoginen tuki eTerveyspalveluiden kotouttamisen suunnitteluun olisi tarpeen. Oppimisen ja hoivan ekosysteemin kulttuuriseen kontekstiin liittyvät tulokset osoittivat, että ikäihmisten kulttuuritaustan merkitys eTerveyspalveluiden oppimiselle ja käytölle on kaksijakoinen. Toisaalta tulokset osoittavat kulttuurisesti yhteensopivia käytäntöjä harvaan asutuilla alueilla asuvien lappilaisten eTerveyspalveluiden oppimisesta ja käytöstä. Toisaalta jokainen maaseudulla asuva eTerveyspalvelun käyttäjä on yksilö riippumatta hänen kulttuuritaustastaan, ja täten he yhdessä muodostavat hyvin heterogeenisen ryhmän eTerveyspalveluiden käyttäjiä. eTerveyspalveluiden käyttäjien lisäksi tutkimuksessa havaittiin myös ikäihmisiä, jotka eivät käytä eTerveyspalveluita. Heitä tulisi tutkia tarkemmin oppimisen ja hoivan ekosysteemissä. Havainnot oppimisen ja hoivan ekosysteemin symboliseen kontekstiin liittyen osoittavat, että eTerveyspalvelut ovat uusia ja hyödyllisiä palveluita maaseudulle, mutta saman aikaisesti ne aiheuttavat haittaa ja huolta ikäihmisille. eTerveyspalveluiden oppiminen ja käyttö tuottaa ikäihmisille sekä positiivisia että negatiivisia tunteita. Tämän tutkimuksen teoreettiset löydökset osoittavat, että oppimisen ja hoivan ekosysteemi on soveltuva lähetymistapa eTerveyspalvelujen käytön tutkimukseen. Lisäksi löydäkset vahvistavat ajatusta siitä, että eTerveyspalveluiden käyttö oppimisen ja hoivan ekosysteemissä ei ole kertaluonteista, ainoastaan palvelun käyttöönoton yhteydessä tapahtuva asia, vaan se jatkuu läpi koko kotouttamisprosessin vaatien monentyyppistä digitaalista osaamista ja sosiaalista tukea. Tästä syystä eTerveyspalvelujen kotouttamisprosessi tulee tunnistaa samanaikaisesti jaetuksi, sosiaaliseksi oppimisprosessiksi. Tässä väitöskirjassa käytetyn teoreettisen viitekehyksen ja kokoavien tulosten pohjalta esitellään uusi teoreettis-käsitteellinen eTerveyspalveluiden oppimisen ja käytön malli. Malli havainnollistaa eTerveyspalveluiden oppimisen ja käytön moniulotteisuutta, ja sitä voidaan hyödyntää eTerveyspalveluiden suunnittelussa ja kotouttamisessa sekä analyyttisenä työkaluna tutkimustarkoituksiin. Väitöskirjan kokoavien tulosten pohjalta on asetettu myös käytännöllisiä ja poliittisia kehitysehdotuksia eTerveyspalveluiden sunnitteluun ja toteuttamiseen palveluiden kehittäjille ja tarjoajille sekä sosiaali- ja terveysalan päättäjille.The general aim of the current dissertation is to explore digital home-care service use (eHealth) from the perspective of rural older people and their social networks in a complex learning and care ecosystem. The use of eHealth services aims to support and facilitate the health, well-being, and everyday lives of older people and their caregivers by improving the accessibility, quality, and affordability of social and health care services. The use of eHealth services also raises many ethical questions related to human dignity. In particular, the current research aims to (1) increase the knowledge of digital competence in eHealth learning and use, (2) clarify in what way the learning process is part of eHealth service domestication, (3) construct a theoretical-conceptual model for eHealth learning and use, and (4) set development proposals for eHealth design and implementation. The aims are achieved through three theoretical approaches. The learning and care ecosystem provides the basis for the research, constructing older people’s eHealth learning and use through practical, social, cultural, and symbolic contexts. The concepts of digital competence and technology domestication focus on the process of how older people learn to use and use eHealth services in everyday situations. A social constructivism paradigm guides the research design as applicable. The methodological approach of the research is qualitative and includes a literature review and empirical data. The dissertation is based on three substudies, each of which is reported in a separate article. The systematic literature review (substudy I) included 31 empirical studies of older people’s learning and use of different eHealth services in 12 different countries in rural and nonrural settings. It provided background information for the research. The other two substudies took place in rural Finnish Lapland. Learning and use of a robotic medication-dispensing service (substudy II) and a phone and video conferencing service (substudy III) were investigated through a case study approach. For substudy II, older people (n = 5), practical nurses (n = 4), and other health care professionals (n = 2) participated. Substudy II utilized ethnography: in addition to semistructured interviews, the use of the service was observed, and photographs of a medication-dispensing robot were taken at older people’s homes. For substudy III, semistructured interviews with older people (n = 2), volunteer workers (n = 2), and a service coordinator were conducted. The gathered data were analyzed through inductive and deductive thematic approaches. The overarching findings of the dissertation were formed through a metasynthesis of the key findings of the substudies. Based on the findings, in terms of the practical context of the learning and care ecosystem, the eHealth domestication process is most affected by the usability and functionality of eHealth services and their compatibility of the service with users’ culturally situated social practices. According to the findings, in the center of the social context of the learning and care ecosystem, there is a learning community that older people form together with warm experts, professionals, and eHealth technologies. The learning community enables the digital competence required for eHealth learning and use as a distributed social activity and the domestication of eHealth services as a social process. With the domestication of eHealth services, social and health care professionals and volunteer workers have taken on a new role as learning instructors for older eHealth users. Pedagogical support for planning eHealth domestication would be necessary. The findings related to the cultural context of the learning and care ecosystem demonstrated that the meaning of the older people’s cultural backgrounds for eHealth service use in the learning and care ecosystem is twofold. On the one hand, culturally congruent practices can be found in the rural Lappish older people’s learning and use of eHealth services. On the other hand, despite older people’s cultural backgrounds, each rural eHealth service user is an individual, and together, they form a very heterogenous group of eHealth service users. In addition to eHealth users, the study also identified eHealth nonusers, who should be further investigated in the learning and care ecosystem. Finally, the overarching findings related to the symbolic context of the learning and care ecosystem indicate that eHealth services are new and needed services for rural areas yet also a source of inconvenience and concern for older people. Learning and use of eHealth services generated both positive and negative emotions for older people. The theoretical findings of the research showed that learning and care ecosystem framework is an applicable approach for the study of the use of eHealth. In addition, the reseach demonstrated that learning to use eHealth services in the learning and care ecosystem is not a one-time experience that only happens when the service is introduced, but continues throughout the entire domestication process, requiring different types of digital competence and social support. Thus, the domestication process of eHealth services should be recognized simultaneously a distributed social learning process. Based on the theoretical framework utilized in the present research and the overarching findings, a new theoretical-conceptual model of eHealth learning and use, called Learning and Care Ecosystem in eHealth Use, was introduced. The model demonstrates the complex nature of eHealth learning and use and can be utilized when designing and domesticating eHealth services or as an analytical tool for research purposes. Finally, the overarching findings allowed the setting of several practical and political development proposals for eHealth design and implementation for eHealth service developers and providers and for social and health care policy makers

Business Model Canvas defined in the paper: A model to define an eHealth technological ecosystem for caregivers

Business Model Canvas as defined in the paper: "A model to define an eHealth technological ecosystem for caregivers

Automatic generation of software interfaces for supporting decisionmaking processes. An application of domain engineering & machine learning

[EN] Data analysis is a key process to foster knowledge generation in particular domains or fields of study. With a strong informative foundation derived from the analysis of collected data, decision-makers can make strategic choices with the aim of obtaining valuable benefits in their specific areas of action. However, given the steady growth of data volumes, data analysis needs to rely on powerful tools to enable knowledge extraction. Information dashboards offer a software solution to analyze large volumes of data visually to identify patterns and relations and make decisions according to the presented information. But decision-makers may have different goals and, consequently, different necessities regarding their dashboards. Moreover, the variety of data sources, structures, and domains can hamper the design and implementation of these tools. This Ph.D. Thesis tackles the challenge of improving the development process of information dashboards and data visualizations while enhancing their quality and features in terms of personalization, usability, and flexibility, among others. Several research activities have been carried out to support this thesis. First, a systematic literature mapping and review was performed to analyze different methodologies and solutions related to the automatic generation of tailored information dashboards. The outcomes of the review led to the selection of a modeldriven approach in combination with the software product line paradigm to deal with the automatic generation of information dashboards. In this context, a meta-model was developed following a domain engineering approach. This meta-model represents the skeleton of information dashboards and data visualizations through the abstraction of their components and features and has been the backbone of the subsequent generative pipeline of these tools. The meta-model and generative pipeline have been tested through their integration in different scenarios, both theoretical and practical. Regarding the theoretical dimension of the research, the meta-model has been successfully integrated with other meta-model to support knowledge generation in learning ecosystems, and as a framework to conceptualize and instantiate information dashboards in different domains. In terms of the practical applications, the focus has been put on how to transform the meta-model into an instance adapted to a specific context, and how to finally transform this later model into code, i.e., the final, functional product. These practical scenarios involved the automatic generation of dashboards in the context of a Ph.D. Programme, the application of Artificial Intelligence algorithms in the process, and the development of a graphical instantiation platform that combines the meta-model and the generative pipeline into a visual generation system. Finally, different case studies have been conducted in the employment and employability, health, and education domains. The number of applications of the meta-model in theoretical and practical dimensions and domains is also a result itself. Every outcome associated to this thesis is driven by the dashboard meta-model, which also proves its versatility and flexibility when it comes to conceptualize, generate, and capture knowledge related to dashboards and data visualizations

Multi-Method Framework for Development of Systemic, Technology-Driven Capability Concepts

Emerging technologies shape the operations of many commercial and military organisations, including the Australian Defence Force. Current capability development processes, grounded in the principles of systems engineering, focus on capability gaps rather than opportunities, often locking in incremental improvements but not transformative changes enabling new capabilities and processes. Furthermore, traditional systems engineering is framed in a way that equates capability with product, leading to single-technology stove-piped processes. By contrast, the study presented in this thesis seeks to design a methodological framework for development of systemic, technology-driven capability concepts that recognise capability as an emergent property of complex systems. The study draws on the body of knowledge in systems thinking and multi-method operations research to design the methodological framework and apply, evaluate and refine it across five concept development workshops within a multi-case study. The study findings support reducing the focus on current processes, use of boundary-mitigating steps to improve generation of ideas, and evolution of technology use cases during concept development. Higher-level, operational concepts are found to be more complex than lower-level tactical concepts; cyclical processes that include resupply produce concepts with higher dynamic complexity. Elicitation of impacts is shaped by the available time and discussion prompts. Importantly, concepts are best framed in terms of capability rather than technology, as capabilities are enabled by multiple interacting technological elements. This is reflected in the novel formalism of technological ecosystem maps, which reframes the discussion of capability options towards capability effects generated by technology groupings. For operations researchers seeking to design real-life interventions, the study demonstrates a traceable process of methodological evolution, with a novel application of boundary critique as the analytical lens for improvement. For capability developers, the study provides a fit-for-purpose methodology for exploring the opportunities presented by emerging technologies, intended to complement the existing capability development processes. The formalism of technological ecosystems lays the groundwork for reframing of capability development towards a more holistic framework, emphasising integration, sustainment, and long-term management of capability elements