OBJECTIVES: To improve transmural palliative care for acutely admitted older patients, the PalliSupport transmural care pathway was developed. Implementation of this care pathway was challenging. The aim of this study was to improve understanding why the implementation partly failed.DESIGN: A qualitative process evaluation study.SETTING/PARTICIPANTS: 17 professionals who were involved in the PalliSupport program were interviewed.METHODS: Online semi-structured interviews. Thematic analysis to create themes according to the implementation framework of Grol & Wensing.RESULTS: From this study, themes within four levels of implementation emerged: 1) The innovation: challenges in current palliative care, the setting of the pathway and boost for improvement; 2) Individual professional: feeling (un)involved and motivation; 3) Organizational level: project management; 4) Political and economic level: project plan and evaluation.CONCLUSION AND IMPLICATIONS: We learned that the challenges involved in implementing a transmural care pathway in palliative care should not be underestimated. For successful implementation, we emphasize the importance of creating a program that fits the complexity of transmural palliative care. We suggest starting on a small scale and invest in project management. This could help to involve all stakeholders and anticipate current challenges in palliative care. To increase acceptance, create one care pathway that can start and be used in all care settings. Make sure that there is sufficient flexibility in time and room to adjust the project plan, so that a second pilot study can possibly be performed, and choose a scientific evaluation with both rigor and practical usefulness to evaluate effectiveness.
Explainable Artificial Intelligence (XAI) aims to provide insights into the inner workings and the outputs of AI systems. Recently, there’s been growing recognition that explainability is inherently human-centric, tied to how people perceive explanations. Despite this, there is no consensus in the research community on whether user evaluation is crucial in XAI, and if so, what exactly needs to be evaluated and how. This systematic literature review addresses this gap by providing a detailed overview of the current state of affairs in human-centered XAI evaluation. We reviewed 73 papers across various domains where XAI was evaluated with users. These studies assessed what makes an explanation “good” from a user’s perspective, i.e., what makes an explanation meaningful to a user of an AI system. We identified 30 components of meaningful explanations that were evaluated in the reviewed papers and categorized them into a taxonomy of human-centered XAI evaluation, based on: (a) the contextualized quality of the explanation, (b) the contribution of the explanation to human-AI interaction, and (c) the contribution of the explanation to human- AI performance. Our analysis also revealed a lack of standardization in the methodologies applied in XAI user studies, with only 19 of the 73 papers applying an evaluation framework used by at least one other study in the sample. These inconsistencies hinder cross-study comparisons and broader insights. Our findings contribute to understanding what makes explanations meaningful to users and how to measure this, guiding the XAI community toward a more unified approach in human-centered explainability.
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Introduction: Depression can be a serious problem in young adult students. There is a need to implement and monitor prevention interventions for these students. Emotion-regulating improvisational music therapy (EIMT) was developed to prevent depression. The purpose of this study was to evaluate the feasibility of EIMT for use in practice for young adult students with depressive symptoms in a university context. Method: A process evaluation was conducted embedded in a larger research project. Eleven students, three music therapists and five referrers were interviewed. The music therapists also completed evaluation forms. Data were collected concerning client attendance, treatment integrity, musical components used to synchronise, and experiences with EIMT and referral. Results: Client attendance (90%) and treatment integrity were evaluated to be sufficient (therapist adherence 83%; competence 84%). The music therapists used mostly rhythm to synchronise (38 of 99 times). The students and music therapists reported that EIMT and its elements evoked changes in all emotion regulation components. The students reported that synchronisation elicited meaningful experiences of expressing joy, feeling heard, feeling joy and bodily responses of relaxation. The music therapists found the manual useful for applying EIMT. The student counsellors experienced EIMT as an appropriate way to support students due to its preventive character. Discussion: EIMT appears to be a feasible means of evoking changes in emotion regulation components in young adult students with depressive symptoms in a university context. More studies are needed to create a more nuanced and evidence-based understanding of the feasibility of EIMT, processes of change and treatment integrity.
Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
Professionals van woningbouwcorporaties en gemeentes die zich bezig houden met verduurzaming hebben vragen over hergebruik van afvalhout uit hun (renovatie) projecten. De doelstelling van dit voorstel is het onderzoeken van de mogelijkheden om hout te hergebruiken door gebruik te maken van innovatieve digitale productietechnieken, en om implementatiestrategieën hiervoor te ontwikkelen voor publieke organisaties in de bouwsector, in het bijzonder woningcorporaties en gemeentes. Strategieën omvatten concrete voorstellen om a) afvalhout van woningen in te zamelen en te verwerken; b) waarde toe te voegen aan houtafvalstromen door middel van digitale productie; c) de betrokkenheid en acceptatie van huurders te vergroten bij circulaire verwerking van hout in nieuwe toepassingen; en d) goede toepassingen voor een circulaire economie te realiseren. Het project onderzoekt aard en omvang van houtafvalstromen uit woningrenovatie en identificeert de mogelijkheden voor het hergebruik van specifieke fracties daarvan voor (lokale) toepassingen. Uit voorgaande projecten blijkt dat digitale productie mogelijkheden biedt om stedelijk afval om te zetten in zinvolle circulaire producten. Digitale productie maakt de (lokale) creatie van unieke prototypen en grootschalige toepassingen mogelijk. Het onderzoek wordt uitgevoerd in vier werkpakketten. De eerste identificeert de aard van huishoudelijk houtafval (volume, houtsoort, verzamelproces) door zorgvuldig cases van Ymere en Rochdale te bestuderen. Daarnaast worden er een raamwerk van indicatoren gedefinieerd om projectresultaten te kunnen evalueren. Het tweede werkpakket onderzoekt welke toepassingen kunnen worden bedacht, gegeven de beschikbare houtfracties. In het derde werkpakket wordt een aantal case studies uitgevoerd voor concrete projecten van de deelnemende woningcorporaties. Deze applicaties hebben als doel het potentieel van digitale productie met houtafval te laten zien, rekening houdend met het perspectief van bewoners. Het biedt belangrijke inzichten in de uitvoerbaarheid van concrete toepassingen uit teruggewonnen hout. In het vierde werkpakket worden alle projectbevindingen gecombineerd in een set implementatie strategieën voor publieke organisaties in het stedelijk domein.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
