Elicitation Phase Research Articles

A novel approach to elicit distributed requirements for IOT system using SVM classifier

Internet of Things (IoT) is one of the growing technologies embedded in most application systems. It aims to solve real-world problems in different environmental fields such as industry, education, healthcare etc. IoT is becoming an integral part of daily devices and technologies opening a need for efficient and novel solutions to meet functional requirements that are more complex than those in traditional requirement engineering (RE). In addition, remotely smart systems present new challenges and lack in RE process that needs a solution. IoT systems open new research issues in RE such as elicitation, analysis, specification and management of IoT RE. To solve this lack of RE new smart techniques based on AI must be applied in the elicitation RE process. This paper presents a new smart dynamic approach in the RE elicitation phase to build dynamic functional requirements based on AI models. New stakeholder expectation needs from the smart IOT system are collected and stored in the requirements dataset. These new requirements are analyzed and classified into requirement features using the Support Vector Machine classifier. These classified functional requirements are compared to the IoT system, and the positive training requirements are added to the smart functional requirement presented in the IoT system. The proposed approach shows a significant accuracy of 95.64%, where 395 features were classified and detected from 413 entered features. This paper measures the gap between stakeholder expectations and device requirements in smart systems; these proposed measures can be implemented to optimize smart device specifications for manufacturers.

Skin sensitisation elicitation: Evaluation of the general threshold and considerations for use.

Allergic contact dermatitis (ACD) is an immune response to chemical haptens, involving induction and elicitation phases. Quantitative risk assessment (QRA) reviewing the skin sensitisation potential for all ingredients and using chemical-specific induction thresholds for skin allergens remains the current best approach for the safety evaluation of consumer products. However, elicitation thresholds have utility in secondary protection for pre-sensitised consumers. The objectives were to (1) review the current elicitation threshold database, (2) evaluate whether predicted relationships between chemical induction and elicitation potencies enable elicitation threshold prediction and (3) discuss elicitation threshold utility as a secondary method of consumer protection. In total, 28 publications (with 39 elicitation datasets) were included in non-linear regression analysis to derive elicitation thresholds for 22 allergens, including fragrances, preservatives and metals. The median elicitation threshold (ED10) for the expanded database was 0.95 μg/cm2, which supports previously published general elicitation thresholds. The derived ED10 for each chemical had only weak to moderate correlation with corresponding induction thresholds, thus limiting suitability as the predictive model. Assessment of current EU fragrance allergen labelling and sensitiser labelling under the globally harmonised system in the context of general and chemical-specific elicitation thresholds shows that current practices are health protective.

Gamify4LexAmb: a gamification-based approach to address lexical ambiguity in natural language requirements.

Ambiguity is a common challenge in specifying natural language (NL) requirements. One of the reasons for the occurrence of ambiguity in software requirements is the lack of user involvement in requirements elicitation and inspection phases. Even if they get involved, it is hard for them to understand the context of the system, and ultimately unable to provide requirements correctly due to a lack of interest. Previously, the researchers have worked on ambiguity avoidance, detection, and removal techniques in requirements. Still, less work is reported in the literature to actively engage users in the system to reduce ambiguity at the early stages of requirements engineering. Traditionally, ambiguity is addressed during inspection when requirements are initially specified in the SRS document. Resolving or removing ambiguity during the inspection is time-consuming, costly, and laborious. Also, traditional elicitation techniques have limitations like lack of user involvement, inactive user participation, biases, incomplete requirements, etc. Therefore, in this study, we have designed a framework, Gamif ication for Lex ical Amb iguity (Gamify4LexAmb), for detecting and reducing ambiguity using gamification. Gamify4LexAmb engages users and identifies lexical ambiguity in requirements, which occurs in polysemy words where a single word can have several different meanings. We have also validated Gamify4LexAmb by developing an initial prototype. The results show that Gamify4LexAmb successfully identifies lexical ambiguities in given requirements by engaging users in requirements elicitation. In the next part of our research, an industrial case study will be performed to understand the effects of gamification on real-time data for detecting and reducing NL ambiguity.

Lymphatic-Dependent Modulation of the Sensitization and Elicitation Phases of Contact Hypersensitivity

Allergic contact dermatitis is a common inflammatory skin disease comprising 2 phases. During sensitization, immune cells are activated by exposure to various allergens, whereas repeated antigen exposure induces local inflammation during elicitation. In this study, we utilized mouse models lacking lymphatics in different skin regions to characterize the role of lymphatics separately in the 2 phases, using contact hypersensitivity as a model of human allergic inflammatory skin diseases. Lymphatic-deficient mice exhibited no major difference to single antigen exposure compared to controls. However, mice lacking lymphatics in both phases displayed reduced inflammation after repeated antigen exposure. Similarly, diminished immune response was observed in mice lacking lymphatics only in sensitization, whereas the absence of lymphatics only in the elicitation phase resulted in a more pronounced inflammatory immune response. This exaggerated inflammation is driven by neutrophils impacting regulatory T cell number. Collectively, our results demonstrate that skin lymphatics play an important but distinct role in the 2 phases of contact hypersensitivity. During sensitization, lymphatics contribute to the development of the antigen-specific immunization, whereas in elicitation, they moderate the inflammatory response and leukocyte infiltration in a neutrophil-dependent manner. These findings underscore the need for novel therapeutic strategies targeting the lymphatics in the context of allergic skin diseases.

Implications of Agile Values in Software Engineering for Agility in Breast Cancer Treatment: Protocol for a Comparative Study.

Breast cancer treatment has been described as a dynamic and patient-centered approach that emphasizes adaptability and flexibility throughout the treatment process. Breast cancer is complex, with varying subtypes and stages, making it important to tailor treatment plans to each patient's unique circumstances. Breast cancer treatment delivery relies on a multidisciplinary team of health care professionals who collaborate to provide personalized care and quick adaptation to changing conditions to optimize outcomes while minimizing side effects and maintaining the patient's quality of life. However, agility in breast cancer treatment has not been defined according to common agile values and described in language comprehensible to breast cancer professionals. In the rapidly evolving landscape of breast cancer treatment, the incorporation of agile values from software engineering promises to enhance patient care. Our objective is to propose agile values for breast cancer treatment adopted and adapted from software engineering. We also aim to validate how these values conform to the concept of agility in the breast cancer context through referencing past work. We applied a structured research methodology to identify and validate 4 agile values for breast cancer treatment. In the elicitation phase, through 2 interviews, we identified 4 agile values and described them in language that resonates with breast cancer treatment professionals. The values were then validated by a domain expert and discussed in the context of supporting work from the literature. Final validation entailed a domain expert conducting a walkthrough of the 4 identified agile values to adjust them as per the reported literature. Four agile values were identified for breast cancer treatment, and among them, we validated 3 that conformed to the concept of agility. The fourth value, documentation and the quality of documentation, is vital for breast cancer treatment planning and management. This does not conform to agility. However, its nonagility is vital for the agility of the other values. None of the identified agile values were validated as partially conforming to the concept of agility. This work makes a novel contribution to knowledge in identifying the first set of agile values in breast cancer treatment through multidisciplinary research. Three of these values were evaluated as conforming to the concept of agility, and although 1 value did not meet the concept of agility, it enhanced the agility of the other values. It is anticipated that these 4 agile values can drive oncology practice, strategies, policies, protocols, and procedures to enhance delivery of care. Moreover, the identified values contribute to identifying quality assurance and control practices to assess the concept of agility in oncology practice and breast cancer treatment and adjust corresponding actions. We conclude that breast cancer treatment agile values are not limited to 4. RR1-10.2196/53124.

Medical Device Software: From Requirements to Certification.

The role of software in healthcare is getting more and more pervasive. Nevertheless, manufacturers sometimes forget that these software are medical devices and must be certified according to the EU Medical Device Regulation 2017/745. In this work we propose a pipeline for developing a Medical Device Software (MDS) compliant with the regulations and certifiable. The pipeline includes the phase of requirements elicitation, risk assessment and analysis of effectiveness as key elements. The preparation of the technical file should be carried out in parallel with the MDS development. In the overall, it can be stated that the certification process starts with the conceptualization of the MDS and proceeds all along its design and implementation.

The junctional adhesion molecule-like protein (JAML) is important for the inflammatory response during contact hypersensitivity.

The junctional adhesion molecule-like protein (JAML) plays important roles in wound healing and activation of epidermal γδ T cells in mice. Whether JAML plays a role in contact hypersensitivity (CHS), the animal model of allergic contact dermatitis (ACD), is not known. To examine the role of JAML in CHS, we used various mouse models of CHS in JAML knockout (KO) and wild-type (WT) mice. Furthermore, the expression of the JAML ligand coxsackievirus and adenovirus receptor (CXADR) on keratinocytes was accessed in vitro and in vivo. JAML KO mice had a diminished inflammatory response during both the sensitization and elicitation phase of CHS and had reduced numbers of CD8+ and CD4+ T cells in the epidermis. Furthermore, interferon γ (IFNγ), interleukin 1β (IL-1β) and CXCL10 production were significantly reduced in JAML KO mice during the elicitation phase. We found that CD8+ T cells express JAML and that JAML is essential for rapid flare-up responses to contact allergens. Finally, we show that keratinocytes up-regulate the JAML ligand CXADR following exposure to contact allergens. Our study is the first to show a central role of JAML in CHS and reveals a potential new target for the treatment of ACD in humans.

Role of Innate Immunity in Allergic Contact Dermatitis: An Update.

Our understanding of allergic contact dermatitis mechanisms has progressed over the past decade. Innate immune cells that are involved in the pathogenesis of allergic contact dermatitis include Langerhans cells, dermal dendritic cells, macrophages, mast cells, innate lymphoid cells (ILCs), neutrophils, eosinophils, and basophils. ILCs can be subcategorized as group 1 (natural killer cells; ILC1) in association with Th1, group 2 (ILC2) in association with Th2, and group 3 (lymphoid tissue-inducer cells; ILC3) in association with Th17. Pattern recognition receptors (PRRs) including toll-like receptors (TLRs) and nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) in innate immune cells recognize damage-associated molecular patterns (DAMPs) and cascade the signal to produce several cytokines and chemokines including tumor necrosis factor (TNF)-α, interferon (IFN)-α, IFN-γ, interleukin (IL)-1β, IL-4, IL-6, IL-12, IL-13, IL-17, IL-18, and IL-23. Here we discuss the recent findings showing the roles of the innate immune system in allergic contact dermatitis during the sensitization and elicitation phases.

Explainable interactive evolutionary multiobjective optimization

We present a new approach to Interactive Evolutionary Multiobjective Optimization (IEMO) guided by a preference elicitation procedure inspired by artificial intelligence and designed in line with decision psychology. For a conflicting nature of objectives, a solution optimizing all objectives simultaneously does not exist and thus the best compromise solution is searched for. In the interactive search, preference elicitation phases alternate with optimization phases. In the IEMO procedure proposed in this paper, during the preference elicitation phase, the Decision Maker (DM) gets a sample of solutions from the current population and is asked to indicate relatively good solutions in this sample. Using the Dominance-based Rough Set Approach (DRSA), this information is summarized by “if ..., then ... ” decision rules which represent DM’s preferences. They are used in the next optimization phases of the IEMO to influence the crossover so as to converge towards the part of the Pareto front containing the best compromise solution. Besides guiding the search process, the decision rules can be read as arguments explaining the DM’s preferences. In this way, the proposed method implements the postulate of transparency and explainability expected from interactive procedures. The DM has a chance to understand how their answers given in the preference elicitation phase are translated into guidelines for the algorithm in the optimization phase. This is a distinctive aspect of what we call eXplainable Interactive Multiobjective Evolutionary optimization Approach (XIMEA). The presented XIMEA-DRSA method implements this approach. From the viewpoint of behavioral psychology, the decision rules support the DM to construct and learn their preferences in the course of evolutionary optimization. To check the efficiency of XIMEA-DRSA, we performed several experiments on continuous as well as combinatorial test problems, assuming the existence of an artificial DM that iteratively provides its preferences according to a known value function. The results prove that XIMEA-DRSA is converging to the most interesting part of the Pareto front, similar to an evolutionary algorithm that optimizes the value function of the artificial DM and, therefore, the latter is used as a benchmark.

Bayesian Optimization-Based Combinatorial Assignment

We study the combinatorial assignment domain, which includes combinatorial auctions and course allocation. The main challenge in this domain is that the bundle space grows exponentially in the number of items. To address this, several papers have recently proposed machine learning-based preference elicitation algorithms that aim to elicit only the most important information from agents. However, the main shortcoming of this prior work is that it does not model a mechanism's uncertainty over values for not yet elicited bundles. In this paper, we address this shortcoming by presenting a Bayesian optimization-based combinatorial assignment (BOCA) mechanism. Our key technical contribution is to integrate a method for capturing model uncertainty into an iterative combinatorial auction mechanism. Concretely, we design a new method for estimating an upper uncertainty bound that can be used to define an acquisition function to determine the next query to the agents. This enables the mechanism to properly explore (and not just exploit) the bundle space during its preference elicitation phase. We run computational experiments in several spectrum auction domains to evaluate BOCA's performance. Our results show that BOCA achieves higher allocative efficiency than state-of-the-art approaches.

A novel agile ontology engineering methodology for supporting organizations in collaborative ontology development

Ontologies can represent technological enablers for knowledge elicitation and management in different kinds of organizations, especially with the exponential growth of sources and types of data fostered by digital transformation. However, their adoption in business applications is still limited, with existing Ontology Engineering Methodologies (OEMs) lacking adequate support during knowledge elicitation, authoring and reuse phases. This paper introduces a novel agile ontology engineering methodology (AgiSCOnt) to support ontologists (especially novice ones) in ontology development workflow, fostering collaboration with domain experts in an iterative, flexible and customizable approach. AgiSCOnt combines macro-level instructions with micro-level guidance, leveraging existing techniques and a management framework to help novice ontologists throughout the whole ontology engineering process. The methodology is compared to existing OEMs and assessed with three other agile methodologies (UPONLite, SAMOD, and RapidOWL). The evaluation is conducted with a sample of novice ontologists in a learning environment on Industry 4.0 technologies. Both the development process with a methodology from a user perspective and the quality of the developed ontologies were considered in the evaluation. Preliminary results show that AgiSCOnt effectively supports authoring and reuse, with developed ontologies of good quality. It is perceived as clear and simple, while being flexible and adaptable enough, thus supporting knowledge management and sharing in industrial organizations through the documentation of the ontologies.

Mouse Models of Allergic Contact Dermatitis: Practical Aspects

Allergic contact dermatitis is a frequently observed dermatosis, especially in industrialized countries. Regarded as a classical type IV immune reaction (delayed type), the process can be separated into two pathogenetic parts: the induction phase where sensitization takes place and the elicitation phase in which inflammation is induced upon re-exposure to the same antigen. A murine model was established decades ago, which reliably reproduces both phases. Epicutaneously applied low-molecular-weight sensitizers bind to proteins (haptens) and become full antigens, which results in sensitization. Subsequent administration of the same hapten onto ear skin causes a swelling response. This reaction is antigen specific because it cannot be induced in nonsensitized mice or in sensitized mice with a different hapten. This model was used to study the mechanisms involved in allergic contact dermatitis and also was intensively utilized to study immunologic mechanisms, including antigen presentation and development of T effector or regulatory T cells. The model's major merit is its antigen specificity. It is highly reproducible, reliable, and simple to perform. In this paper, the methods of this technique are described to help researchers successfully establish this widely used model in laboratories. Describing the complex pathomechanisms underlying the model is beyond the scope of this article.

Use of Journey Maps and Personas in Software Requirements Elicitation

Requirements elicitation is a fundamental step in a software development process since it is at this stage that the software begins to be designed. In some situations, the problems related to the failure of the software development project are due to an incomplete requirements elicitation, resulting in solutions that do not understand all the necessary functionalities or do not incorporate innovation. Despite the various techniques offered by Requirements Engineering, situations such as the growing application market and the need for innovation further increase the importance of understanding the user’s different needs. In this paper, we investigated how the journey map and personas techniques are being used in requirements elicitation in both the literature and the industry, along with the advantages, disadvantages and challenges of using these techniques. We conducted systematic literature review to identify the personas and journey map techniques used in requirements elicitation in the literature and industry. In addition, we conducted a survey with 52 practitioners (software developers, users and managers) to investigate their perceptions of the use of journey maps and personas techniques in the requirements elicitation phase. Twenty-four primary studies were identified that address journey map and personas techniques in software requirements elicitation. In addition, most respondents stated that using these techniques facilitates understanding the requirements, providing better integration, collaboration and leveling of knowledge among the members of the software development teams. Our findings allow us to conclude that most of the software developers, users and managers that participated in the survey consider that the journey map and personas techniques are effective in helping understand the software requirements to be developed by the development teams.

Understanding treatment burden in hemophilia: development and validation of the Hemophilia Treatment Experience Measure (Hemo-TEM)

BackgroundTo capture the broad range of treatment burden issues experienced by adolescent and adult people with hemophilia (PWH), the Hemophilia Treatment Experience Measure (Hemo-TEM) was developed. We describe the development of this new hemophilia-specific patient-reported outcome (PRO) measure including concept elicitation, cognitive debriefing, and psychometric validation.ResultsConcept elicitation interviews were conducted with 5 clinical experts and 30 adult PWH in the United States (US). The qualitative analysis of these interviews and a review of the literature informed the PRO measure development. The project team reviewed concept endorsement rates and generated a 27-item preliminary version of the Hemo-TEM. Cognitive debriefing interviews were conducted to ensure participant understanding and item relevance in samples of (adolescent (n = 20) and adult (n = 14)) PWH in the US. The refined, validation-ready version of the Hemo-TEM included 30 items. Lastly, data from 3 clinical trials comprised the 4 analysis sets used for the psychometric validation with a sample size of N = 88. Item reduction dropped 4 items resulting in a final 26-item measure. Factor analysis generated 5 domains in the Hemo-TEM [injection difficulties (3 items), physical impact (6 items), treatment bother (7 items), interference with daily life (4 items), and emotional impact (6 items)] and a total score. All scores were reliable [internally consistent (0.84–0.88)]. For convergent validity, with the exception of one domain, all hypothesized associations were met. Preliminary sensitivity to change effect sizes were between − 0.30 and − 0.70. Meaningful change thresholds ranged from 6 points (physical impact and emotional impact) to 10 points (treatment bother) with 8 points for the Hemo-TEM total score.ConclusionsFindings from the concept elicitation, cognitive debriefing, and psychometric validation phases provide evidence that the Hemo-TEM is a well-designed, valid, and reliable measure of the burden of hemophilia treatment, including treatment impact on adolescent and adult PWH.

Explaining vegetarian and vegan dietary behavior among U.S. and Dutch samples applying a reasoned action approach

The present research applied the framework of the Reasoned Action Approach (RAA) to investigate intention formation of adopting vegetarian and vegan diets among U.S. and Dutch samples. First, a belief elicitation study was carried out to determine salient beliefs regarding both dietary behaviors. The U.S. sample (N = 59) together provided a total of 551 beliefs (298 vegetarian, 253 vegan) and the Dutch sample (N = 30) 294 beliefs (171 vegetarian, 123 vegan). Second, a regression study determined which reasoned action variables—Attitude, Perceived Norm and Perceived Control—explained Intention to adopt a vegetarian or a vegan diet for two separate samples. For both samples RAA-variables explained Intention relatively well (i.e., between 30 and 43% of the variance). For U.S. participants (N = 204), Instrumental and Experiential Attitude were significant predictors of their Intention to have a vegetarian or a vegan diet. For Dutch participants (N = 345), Instrumental and Experiential Attitude and Descriptive Norm predicted Intention to adopt a vegetarian diet. For adopting a vegan diet, Experiential Attitude was the only predicting variable for the Dutch sample. Almost all salient beliefs collected in the belief elicitation study significantly correlated with Intention to adopt diet, regardless of which RAA-variable they belonged to. Based on our findings, we critically evaluate the use of RAA in explaining behavioral Intentions, especially for behavior with a strong social component. Moreover, we show the importance of—the often not employed—belief elicitation phase and as such, discourage using only a regression approach. From a societal perspective, we argue that there is a strong need for interventions if one wants to encourage behavior change in the field of vegetarianism and veganism as—amongst others—average Intention scores were very low. In addition, we show that while the U.S. and Dutch samples, sharing Western norms and values, often overlapped, they also differed in subtle—yet potentially important—ways when it comes to motivations and cognitions with regard to vegetarian and vegan dietary behavior. Hence, interventions may have to include different content in order to be effective for these seemingly similar target groups and target behaviors.

Gathering Expert Knowledge in Process Industry

Knowledge intensive processes are often driven and constrained by mental models of experts. Especially in industrial processes, the knowledge is not explicit but tacit in many cases, which makes it difficult to provide verbal descriptions. Modeling and prediction tasks are often not compatible or differ from the view of experts if no additional knowledge regarding the process itself or important parts of the process are identified and integrated. In industrial environments, the required knowledge is present in operators, which have to deal with the task or process on a frequent basis. Including operators during the development process may increase the quality and performance as well as trust in the resulting application. Data scientists face great difficulties in eliciting and representing the knowledge of the experts in these systems for solving the given tasks. In this paper, we will provide a review of strategies and approaches for knowledge elicitation in industrial environments. The approaches focus on applicability in industrial use-cases, whereat the operators are the main source for knowledge. The differences of the approaches are highlighted and use-cases for their application are presented. Furthermore, we will provide a discussion on using these approaches at different stages during a project as usually multiple knowledge elicitation phases are required to reach a certain goal.

006 Conventional dendritic cell 2 as an activator for cytotoxic T lymphocytes in the elicitation phase of murine contact hypersensitivity

Cytotoxic T lymphocyte (CTL) has been found to be activated by cutaneous dendritic cell (DC) in inducible skin-associated lymphoid tissue (iSALT) in a murine contact hypersensitivity (CHS) model. Cutaneous DCs are classified into Langerhans cell (LC), conventional DC1 (cDC1), conventional DC2 (cDC2) and monocyte-derived DC (MoDC); however, which DC subsets activate CTL within iSALT during the elicitation phase of CHS has remained unclear. To clarify this, we used Langerin-diphtheria toxin receptor (DTR), XCR1-DTR and CD301b-DTR mice to deplete LC, cDC1 and cDC2, respectively.

Observation of hapten-induced sensitization responses for the development of a mouse skin sensitization test, including the elicitation phase

The only official method that can detect the skin sensitizing potential of chemicals, including the elicitation response, is the OECD test guideline (TG) 406. However, this guideline uses guinea pigs, which requires complex procedures. Since a simple and complete test method for evaluating skin sensitization is needed, especially for mechanistic studies of skin sensitization, this study confirmed the reactivity of mice to skin sensitizing substances. We set up a protocol involving one induction exposure of the test substance to the back skin, followed by three challenge exposures to the auricle (Protocol 2), and compared their skin sensitization responses with the results of two exposures to the auricle and back skin every 2 weeks (Protocol 1) and a local lymph node assay (TG442B). A hapten 2,4-dinitrofluorobenzene caused significant auricular thickening, skin inflammation, and enlarged auricular lymph nodes in Protocols 1 and 2. These changes were more pronounced in Protocol 2. Plasma IgE and IgG1 and gene expression of IL4, IFNγ, and perforin were significantly increased in Protocol 2. Cell proliferation in the auricular lymph nodes was observed in both protocols as in TG442B. These results indicate that Protocol 2 can be a good candidate for a relatively simple skin sensitization test.

How do requirements evolve during elicitation? An empirical study combining interviews and app store analysis

Requirements are elicited from the customer and other stakeholders through an iterative process of interviews, prototyping, and other interactive sessions. Then, requirements can be further extended, based on the analysis of the features of competing products available on the market. Understanding how this process takes place can help to identify the contribution of the different elicitation phases, thereby allowing requirements analysts to better distribute their resources. In this work, we empirically study in which way requirements get transformed from initial ideas into documented needs, and then evolve based on the inspiration coming from similar products. To this end, we select 30 subjects that act as requirements analysts, and we perform interview-based elicitation sessions with a fictional customer. After the sessions, the analysts produce a first set of requirements for the system. Then, they are required to search similar products in the app stores and extend the requirements, inspired by the identified apps. The requirements documented at each step are evaluated, to assess to which extent and in which way the initial idea evolved throughout the process. Our results show that only between 30% and 38% of the requirements produced after the interviews include content that can be fully traced to initial customer’s ideas. The rest of the content is dedicated to new requirements, and up to 21% of it belongs to completely novel topics. Furthermore, up to 42% of the requirements inspired by the app stores cover additional features compared to the ones identified after the interviews. The results empirically show that requirements are not elicited in strict sense, but actually co-created through interviews, with analysts playing a crucial role in the process. In addition, we show evidence that app store-inspired elicitation can be particularly beneficial to complete the requirements.

The acceptability, adoption, and feasibility of a music application developed using participatory design for home-dwelling persons with dementia and their caregivers. The "Alight" app in the LIVE@Home.Path trial.

Music interventions for persons with dementia can improve health and interaction with caregivers, yet the reach is often restricted to institutions. We describe the participatory design process of a prototype music application for patients affiliated with a gerontopsychiatric hospital and evaluate the acceptability, adoption, and feasibility of use for dyads of home-dwelling persons with dementia and their informal caregivers. The application "Alight" was developed following an iterative, expert-driven participatory design approach, which includes a requirement elicitation phase and two rounds of prototyping and testing in real-world settings. End users and stakeholders were involved in all steps, that is, workshops, interviews, field observation, ethnographic inquiries, and beta testing sessions with music therapists, patients, and caregivers in collaboration with a commercial music and technology company. The last prototyping and testing took place in the LIVE@Home.Path trial, a stepped-wedge multicomponent randomized controlled trial to improve resource utilization and caregiver burden in municipal dementia care during 2019-2021. Mean age of the person with dementia in the LIVE@Home.Path trial was 82 years, 62% were female, and the majority had Alzheimer's dementia (44%) of mild severity (71%). Sixty-three dyads were offered Alight in the multicomponent intervention, of which 13% (n = 8) accepted use. The dyads accepting Alight did not differ in demographic and clinical characteristics compared to those not interested. The feasibility was high among those accepting Alight, 75% (n = 6) reported a positive impact on mood, 50% (n = 4) experienced a positive impact on activity, and 50% (n = 4) gooduser-friendliness. The adoption was high with daily use or use several times a week reported by 63% (n = 5). Obstacles emerged when updating the application in homes without wireless Wi-Fi, and some participants were unfamiliar with using touchscreens. The feasibility and adoption of the application were high and accepting dyads did not differ on demographic and clinical variables from those not reached. This suggests a high potential for utilization in dementia care. This study contributes methodologically to the field of participatory design and mHealth interventions by demonstrating a specific design approach that throughout the process successfully involved researchers, industry partners, health care practitioners, and end users. ClinicalTrials.gov, NCT04043364.