Abstract Background Smoking among people with severe mental illness (SMI) is highly prevalent and strongly associated with poor physical health. Currently, evidence-based smoking cessation interventions are scarce and need to be integrated into current mental health care treatment guidelines and clinical practice. Therefore, the present study aims to evaluate the implementation and effectiveness of a smoking cessation intervention in comparison with usual care in people with SMI treated by Flexible Assertive Community Treatment (FACT) teams in the Netherlands. Methods A pragmatic, cluster-randomised controlled trial with embedded process evaluation will be conducted. Randomisation will be performed at the level of FACT teams, which will be assigned to the KISMET intervention or a control group (care as usual). The intervention will include pharmacological treatment combined with behavioural counselling and peer support provided by trained mental health care professionals. The intervention was developed using a Delphi study, through which a consensus was reached on the core elements of the intervention. We aim to include a total of 318 people with SMI (aged 18–65 years) who smoke and desire to quit smoking. The primary outcome is smoking status, as verified by carbon monoxide measurements and self-report. The secondary outcomes are depression and anxiety, psychotic symptoms, physical fitness, cardiovascular risks, substance use, quality of life, and health-related self-efficacy at 12 months. Alongside the trial, a qualitative process evaluation will be conducted to evaluate the barriers to and facilitators of its implementation as well as the satisfaction and experiences of both patients and mental health care professionals. Discussion The results of the KISMET trial will contribute to the evidence gap of effective smoking cessation interventions for people treated by FACT teams. Moreover, insights will be obtained regarding the implementation process of the intervention in current mental health care. The outcomes should advance the understanding of the interdependence of physical and mental health and the gradual integration of both within the mental health care system. Trial registration Netherlands Trial Register, NTR9783. Registered on 18 October 2021.
Aim: Participation of adolescents with autism spectrum disorder hardly occurs in settings outside of home and school. Little is known about how their participation is influenced by environmental factors. This study explored how and why adolescents with autism spectrum disorder perceive aspects of their environment as facilitators or barriers to their participation outside of home and school. Method: This explanatory case study explored the participation experiences of adolescents with autism spectrum disorder (15–21 years) from Zurich and surroundings with in-depth interviews and photo-elicitation, using photos made by the participants during activities outside of home and school. Data was analysed with a 7-step procedure. Result: The presence of two main themes seemed necessary to facilitate participation outside of home and school: “environmental prerequisites to attend activities”, which consists of five subthemes, such as “the company of trusted persons” and “the provision of knowledge and information”, and “social interchange and engagement”, which consists of three subthemes and describes how actual involvement can be supported. Conclusion: Our findings highlight the influence of trusted persons on adolescents with autism spectrum disorder, and the need to extend the support network for these adolescents to other individuals, services and society so that their participation in activities can be encouraged.
Aim: Participation of adolescents with autism spectrum disorder hardly occurs in settings outside of home and school. Little is known about how their participation is influenced by environmental factors. This study explored how and why adolescents with autism spectrum disorder perceive aspects of their environment as facilitators or barriers to their participation outside of home and school. Method: This explanatory case study explored the participation experiences of adolescents with autism spectrum disorder (15–21 years) from Zurich and surroundings with in-depth interviews and photo-elicitation, using photos made by the participants during activities outside of home and school. Data was analysed with a 7-step procedure. Result: The presence of two main themes seemed necessary to facilitate participation outside of home and school: “environmental prerequisites to attend activities”, which consists of five subthemes, such as “the company of trusted persons” and “the provision of knowledge and information”, and “social interchange and engagement”, which consists of three subthemes and describes how actual involvement can be supported. Conclusion: Our findings highlight the influence of trusted persons on adolescents with autism spectrum disorder, and the need to extend the support network for these adolescents to other individuals, services and society so that their participation in activities can be encouraged.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
-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.
Structural colour (SC) is created by light interacting with regular nanostructures in angle-dependent ways resulting in vivid hues. This form of intense colouration offers commercial and industrial benefits over dyes and other pigments. Advantages include durability, efficient use of light, anti-fade properties and the potential to be created from low cost materials (e.g. cellulose fibres). SC is widely found in nature, examples include butterflies, squid, beetles, plants and even bacteria. Flavobacterium IR1 is a Gram-negative, gliding bacterium isolated from Rotterdam harbour. IR1 is able to rapidly self-assemble into a 2D photonic crystal (a form of SC) on hydrated surfaces. Colonies of IR1 are able to display intense, angle-dependent colours when illuminated with white light. The process of assembly from a disordered structure to intense hues, that reflect the ordering of the cells, is possible within 10-20 minutes. This bacterium can be stored long-term by freeze drying and then rapidly activated by hydration. We see these properties as suiting a cellular reporter system quite distinct from those on the market, SC is intended to be “the new Green Fluorescent Protein”. The ability to understand the genomics and genetics of SC is the unique selling point to be exploited in product development. We propose exploiting SC in IR1 to create microbial biosensors to detect, in the first instance, volatile compounds that are damaging to health and the environment over the long term. Examples include petroleum or plastic derivatives that cause cancer, birth defects and allergies, indicate explosives or other insidious hazards. Hoekmine, working with staff and students within the Hogeschool Utrecht and iLab, has developed the tools to do these tasks. We intend to create a freeze-dried disposable product (disposables) that, when rehydrated, allow IR1 strains to sense and report multiple hazardous vapours alerting industries and individuals to threats. The data, visible as brightly coloured patches of bacteria, will be captured and quantified by mobile phone creating a system that can be used in any location by any user without prior training. Access to advice, assay results and other information will be via a custom designed APP. This work will be performed in parallel with the creation of a business plan and market/IP investigation to prepare the ground for seed investment. The vision is to make a widely usable series of tests to allow robust environmental monitoring for all to improve the quality of life. In the future, this technology will be applied to other areas of diagnostics.
