This dissertation describes a research project about the communication between communication vulnerable people and health care professionals in long-term care settings. Communication vulnerable people experience functional communication difficulties in particular situations, due to medical conditions. They experience difficulties expressing themselves or understanding professionals, and/or professionals experience difficulties understanding these clients. Dialogue conversations between clients and professionals in healthcare, which for example concern health-related goals, activity and participation choices, diagnostics, treatment options, and treatment evaluation, are, however, crucial for successful client-centred care and shared decision making. Dialogue conversations facilitate essential exchanges between clients and healthcare professionals, and both clients and professionals should play a significant role in the conversation. It is unknown how communication vulnerable people and their healthcare professionals experience dialogue conversations and what can be done to support successful communication in these conversations. The aim of this research is to explore how communication vulnerable clients and professionals experience their communication in dialogue conversations in long-term care and how they can best be supported in improving their communication in these conversations.
Background The experiences of residents who have communication difficulties such as dysphasia are largely absent from the literature. Aim To illuminate the everyday experiences of four residents with severe communication difficulties living in a residential care setting in the Netherlands. Methodology & Methods A collective case study methodology was used. Seventy-five hours of observation, interview and documentary data was gathered over six weeks. Alternative strategies of communication were developed to enable the co-creation of dialogue between participants and researcher. For example, a participant who could not talk used intentionally created artwork to share her ideas with the researcher. Findings Participants' daily experiences were characterised by struggling against the constraints of the residential setting: having to wait, having unmet needs, experiencing vulnerability and uncertainty. Participants' communication difficulties exacerbated these constraints. Their experiences of struggling were sometimes ameliorated by significant social contact with family or particular staff members, and engaging in enjoyable activities. Occasionally the experiences of enjoying the here-and-now, and being 'seen' as a person by the other, would create beautiful moments in which truly person centred engagement would occur. These moments were neither articulated nor recorded, and were thus invisible after they had occurred. Similarly, the experiences of struggling against the constraints were neither acknowledged nor recorded. Significant experiences in the lives of these four residents were therefore invisible to others. The unifying theme representing the participants' daily experiences was: That which goes unsaid. Discussion It was necessary to develop communication strategies which would by-pass the researcher's assumptions and enable participants to introduce their own ideas and opinions. This ongoing process of co-creation of dialogue required work from, and trust between, participants and researcher. What is new? Expressly seeking the views of residents with communication difficulties Successfully using process consent with participants in this situation Using intentionally created artwork during data gathering in this context What has regional, national or international relevance? The findings indicate that people with communication difficulties may not receive optimal care in residential settings in the Netherlands. Methods are described which could be used by practitioners in their everyday work, and which show facilitators or practice developers how they can help carers to engage in more effective communication with this kind of resident. Additionally, this research contributes to the international discussion about ethical participation of vulnerable people in research.
Intention of healthcare providers to use video-communication in terminal care: a cross-sectional study. Richard M. H. Evering, Marloes G. Postel, Harmieke van Os-Medendorp, Marloes Bults and Marjolein E. M. den Ouden BMC Palliative Care volume 21, Article number: 213 (2022) Cite this articleAbstractBackgroundInterdisciplinary collaboration between healthcare providers with regard to consultation, transfer and advice in terminal care is both important and challenging. The use of video communication in terminal care is low while in first-line healthcare it has the potential to improve quality of care, as it allows healthcare providers to assess the clinical situation in real time and determine collectively what care is needed. The aim of the present study is to explore the intention to use video communication by healthcare providers in interprofessional terminal care and predictors herein.MethodsIn this cross-sectional study, an online survey was used to explore the intention to use video communication. The survey was sent to first-line healthcare providers involved in terminal care (at home, in hospices and/ or nursing homes) and consisted of 39 questions regarding demographics, experience with video communication and constructs of intention to use (i.e. Outcome expectancy, Effort expectancy, Attitude, Social influence, Facilitating conditions, Anxiety, Self-efficacy and Personal innovativeness) based on the Unified Theory of Acceptance and Use of Technology and Diffusion of Innovation Theory. Descriptive statistics were used to analyze demographics and experiences with video communication. A multiple linear regression analysis was performed to give insight in the intention to use video communication and predictors herein.Results90 respondents were included in the analysis.65 (72%) respondents had experience with video communication within their profession, although only 15 respondents (17%) used it in terminal care. In general, healthcare providers intended to use video communication in terminal care (Mean (M) = 3.6; Standard Deviation (SD) = .88). The regression model was significant and explained 44% of the variance in intention to use video communication, with ‘Outcome expectancy’ and ‘Social influence’ as significant predictors.ConclusionsHealthcare providers have in general the intention to use video communication in interprofessional terminal care. However, their actual use in terminal care is low. ‘Outcome expectancy’ and ‘Social influence’ seem to be important predictors for intention to use video communication. This implicates the importance of informing healthcare providers, and their colleagues and significant others, about the usefulness and efficiency of video communication.
MULTIFILE
The growing use of digital media has led to a society with plenty of new opportunities for knowledge exchange, communication and entertainment, but also less desirable effects like fake news or cybercrime. Several studies, however, have shown that children are less digital literate than expected. Digital literacy has consequently become a key part within the new national educational policy plans titled Curriculum.nu and the Dutch research and policy agendas. This research project is focused on the role the game sector can play in the development of digital literacy skills of children. In concrete, we want to understand the value of the use of digital literacy related educational games in the context of primary education. Taking into consideration that the childhood process of learning takes place through playing, several studies claim that the introduction of the use of technology at a young age should be done through play. Digital games seem a good fit but are themselves also part of digital media we want young people to be literate about. Furthermore, it needs to be taken into account that digital literacy of teachers can be limited as well. The interactive, structured nature of digital games offers potential here as they are less dependent on the support and guidance of an adult, but at the same time this puts even more emphasis on sensible game design to ensure the desired outcome. The question is, then, if and how digital games are best designed to foster the development of digital literacy skills. By harnessing the potential of educational games, a consortium of knowledge and practice partners aim to show how creating theoretical and practical insights about digital literacy and game design can aid the serious games industry to contribute to the societal challenges concerning contemporary literacy demands.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
