Purpose: This study explores limitations in communication in daily life of children with developmental language disorder (DLD) from their parents' perspective as well as communicative abilities and social functioning in the classroom from their teacher's perspective. Furthermore, differences between children with mixed receptive–expressive disorder and children with expressive-only disorder in communication in daily life and social functioning are studied. Method: Data were collected through questionnaires completed by parents and teachers of children (5–6 years old) who attended schools for special education for DLD. Language test scores were retrieved from school records. Parents of 60 children answered open-ended questions about situations and circumstances in which their child was most troubled by language difficulties. Teachers of 83 children rated communicative abilities, social competence, and student–teacher relationship. Results: Parents reported communication with strangers as most troublesome and mentioned the influence of the mental state of their child. Parents considered limitations in expressing oneself and being understood and not being intelligible as core difficulties. Teachers rated the children's communicative abilities in the school context as inadequate, but their scores concerning social competence and the quality of teacher–child relationships fell within the normal range. Children with receptive–expressive disorder experienced limitations in communication in almost all situations, whereas those with expressive disorder faced limitations in specific situations. Children with receptive–expressive disorder were also significantly more limited in their communicative abilities and social competence at school than children with expressive disorder. No differences were found between the two groups in the quality of the teacher–child relationship. Conclusions: The results confirm that children with DLD face significant challenges in a variety of communicative situations. We found indications that children with receptive–expressive disorder experience more severe limitations than children with expressive disorder. The involvement of parents and teachers in evaluating a child's communicative ability provides valuable and clinically relevant information.
Background: Falls in stroke survivors can lead to serious injuries and medical costs. Fall risk in older adults can be predicted based on gait characteristics measured in daily life. Given the different gait patterns that stroke survivors exhibit it is unclear whether a similar fall-prediction model could be used in this group. Therefore the main purpose of this study was to examine whether fall-prediction models that have been used in older adults can also be used in a population of stroke survivors, or if modifications are needed, either in the cut-off values of such models, or in the gait characteristics of interest. Methods: This study investigated gait characteristics by assessing accelerations of the lower back measured during seven consecutive days in 31 non fall-prone stroke survivors, 25 fall-prone stroke survivors, 20 neurologically intact fall-prone older adults and 30 non fall-prone older adults. We created a binary logistic regression model to assess the ability of predicting falls for each gait characteristic. We included health status and the interaction between health status (stroke survivors versus older adults) and gait characteristic in the model. Results: We found four significant interactions between gait characteristics and health status. Furthermore we found another four gait characteristics that had similar predictive capacity in both stroke survivors and older adults. Conclusion: The interactions between gait characteristics and health status indicate that gait characteristics are differently associated with fall history between stroke survivors and older adults. Thus specific models are needed to predict fall risk in stroke survivors.
Loneliness among young adults is a growing concern worldwide, posing serious health risks. While the human ecological framework explains how various factors such as socio-demographic, social, and built environment characteristics can affect this feeling, still, relatively little is known about the effect of built environment characteristics on the feelings of loneliness that young people experience in their daily life activities. This research investigates the relationship between built environment characteristics and emotional state loneliness in young adults (aged 18–25) during their daily activities. Leveraging the Experience Sampling Method, we collected data from 43 participants for 393 personal experiences during daily activities across different environmental settings. The findings of a mixed-effects regression model reveal that built environment features significantly impact emotional state loneliness. Notably, activity location accessibility, social company during activities, and walking activities all contribute to reducing loneliness. These findings can inform urban planners and municipalities to implement interventions that support youngsters’ activities and positive experiences to enhance well-being and alleviate feelings of loneliness in young adults. Specific recommendations regarding the built environment are (1) to create spaces that are accessible, (2) create spaces that are especially accessible by foot, and (3) provide housing with shared facilities for young adults rather than apartments/studios.
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Building Blocks for Liveable Neighbourhoods. Four suburbs in the province of Noord-Brabant are case-studies for a new method of urban development. Participation and scenario's are the starting point. The tools for local stakeholders to (literally) shape their own future environment are the end result.Societal issue: Gap between the plannend world and the daily life in city neighbourhoods. People are eager to take responsibility for their living environment but have no tools or knowledge to do it.Benefit to society: The method developed in this design research project enables the different stakeholders to connect, align and be effective in shaping their common future living environment.
PBL is the initiator of the Work Programme Monitoring and Management Circular Economy 2019-2023, a collaboration between CBS, CML, CPB, RIVM, TNO, UU. Holidays and mobility are part of the consumption domains that PBL researches, and this project aims to calculate the environmental gains per person per year of the various circular behavioural options for both holiday behaviour and daily mobility. For both behaviours, a range of typical (default) trips are defined and for each several circular option explored for CO2 emissions, Global warming potential and land use. The holiday part is supplied by the Centre for Sustainability, Tourism and Transport (CSTT) of the BUas Academy of Tourism (AfT). The mobility part is carried out by the Urban Intelligence professorship of the Academy for Built Environment and Logistics (ABEL).The research question is “what is the environmental impact of various circular (behavioural) options around 1) holidays and 2) passenger mobility?” The consumer perspective is demarcated as follows:For holidays, transportation and accommodation are included, but not food, attractions visited and holiday activitiesFor mobility, it concerns only the circular options of passenger transport and private means of transport (i.e. freight transport, business travel and commuting are excluded). Not only some typical trips will be evaluated, but also the possession of a car and its alternatives.For the calculations, we make use of public databases, our own models and the EAP (Environmental Analysis Program) model developed by the University of Groningen. BUAs projectmembers: Centre for Sustainability, Tourism and Transport (AT), Urban Intelligence (ABEL).
-Chatbots are being used at an increasing rate, for instance, for simple Q&A conversations, flight reservations, online shopping and news aggregation. However, users expect to be served as effective and reliable as they were with human-based systems and are unforgiving once the system fails to understand them, engage them or show them human empathy. This problem is more prominent when the technology is used in domains such as health care, where empathy and the ability to give emotional support are most essential during interaction with the person. Empathy, however, is a unique human skill, and conversational agents such as chatbots cannot yet express empathy in nuanced ways to account for its complex nature and quality. This project focuses on designing emotionally supportive conversational agents within the mental health domain. We take a user-centered co-creation approach to focus on the mental health problems of sexual assault victims. This group is chosen specifically, because of the high rate of the sexual assault incidents and its lifetime destructive effects on the victim and the fact that although early intervention and treatment is necessary to prevent future mental health problems, these incidents largely go unreported due to the stigma attached to sexual assault. On the other hand, research shows that people feel more comfortable talking to chatbots about intimate topics since they feel no fear of judgment. We think an emotionally supportive and empathic chatbot specifically designed to encourage self-disclosure among sexual assault victims could help those who remain silent in fear of negative evaluation and empower them to process their experience better and take the necessary steps towards treatment early on.
