User Involvement Research Articles

Lay User Involvement in Developing Human-centric Responsible AI Systems: When and How?

Artificial Intelligence (AI) is increasingly used in mainstream applications to make decisions that affect a large number of people. While research has focused on involving machine learning and domain experts during the development of responsible AI systems, the input of lay users has too often been ignored. By exploring the involvement of lay users, our work seeks to advance human-centric responsible AI development processes. To reflect on lay users’ views, we conducted an online survey of 1,121 people in the United Kingdom. We found that respondents had concerns about fairness and transparency of AI systems, which requires more education around AI to underpin lay user involvement. They saw a need for having their views reflected at all stages of the AI development lifecycle. Lay users mainly charged internal stakeholders to oversee the development process but supported by an ethics committee and input from an external regulatory body. We also probed for possible techniques for involving lay users more directly. Our work has implications for creating processes that ensure the development of responsible AI systems that take lay user perspectives into account.

Epistemological aspects of participatory design studies conducted in the field of health science.

To discuss the methodological aspects of participatory design, arguing for a three-phase approach and the suitability of situating participatory design within a phenomenological-hermeneutical tradition in health science. Methodological discussion based on participatory design theory, epistemology and research studies. The epistemological and methodological discussions show how the core values and key elements of participatory design align with the phenomenological-hermeneutical approach. In addition, examples of participatory design studies are provided to illustrate how it can be conducted in health science. Participatory design is a flexible framework based on genuine participation, defined by three core values: having a say, mutual learning and democratization. The iterative processes allow for adjustments in alignment with the core values and the scientific stance that defines the choice of methods, tools and techniques. A phenomenological-hermeneutic approach in participatory design studies is relevant and aligned with the core values of participatory design. Thus, this paper argues for a close integration between the participatory design methodology and the phenomenological-hermeneutic scientific approach within health science. Participatory design is a powerful methodology with core values that can co-design sustainable health technologies with potential to impact patient care and the clinical practice of nurses. When combined with qualitative research methods, patients' lived experiences serve as the foundation for improving clinical nursing practice. Discussing the epistemological aspects of participatory design provides nurse researchers with a coherent methodological understanding, essential for the continual development of nursing research. This paper discusses the research methodology of participatory design within health sciences. It aims to address the lack of understanding of the methodology, particularly within a specific scientific stance. The main finding is the elaboration on participatory design and the relevance of a phenomenological-hermeneutical approach. The paper has the potential to impact researchers, master's and PhD students, as well as others engaged in participatory design or other methodologies related to user involvement within health science. No available EQUATOR guidelines were applicable to this methodological paper, as no new data were created or analysed. There was no direct patient or public contribution, as this is a methodological paper.

Unlocking Interactive Learning: Building a Robust Quiz Portal with MERN Stack Technology"

Online learning has become increasingly popular in the digital era, necessitating innovative platforms to effectively engage students. This research outlines the development and implementation of an interactive quiz portal utilizing the MERN (MongoDB, Express.js, React.js, and Node.js) stack to enhance learning outcomes. The portal features a user-friendly interface for easy navigation and access to a diverse range of quizzes on various subjects. To ensure scalability, performance, and real-time interactions, Node.js handles backend operations, React.js manages dynamic interfaces, Express.js is used for server-side development, and MongoDB stores data. The portal includes instant feedback mechanisms, gamification elements, and personalized user profiles to enhance user motivation and involvement. Furthermore, adaptive algorithms are employed to adjust quiz content based on user proficiency levels. This paper presents the design, development, and implementation of an online test platform using the MERN (MongoDB, Express, React, and Node.js) stack. The portal functions as an all-inclusive platform for administering tests, assessments, and learning evaluations in an online setting. The portal provides smooth integration of frontend and backend activities, guaranteeing strong performance and user interaction, by utilizing the adaptability and scalability of the MERN stack. The portal enables quick development and deployment cycles with the help of MongoDB's document-based data storage, Express.js's effective middleware and routing, React.js's dynamic UI components, and Node.js's event-driven architecture. To improve user experience and learning results, features including interactive feedback mechanisms, real-time performance monitoring, quiz design and administration, and user authentication are easily integrated.

Challenging the narrative: social work students’ views on the impact of service user and carer-led pedagogy to knowledge and practice

ABSTRACT Service user and carer involvement is firmly established as an integral part of social work education in the UK, with a growing body of evidence demonstrating its beneficial effects on student learning. Calls have been made to further develop its theoretical base and evaluate its impact on students’ future practice. This article contributes to these aims, by following a cohort of undergraduate UK-based social work students. Using a focus group, the research elicited the views of the students on how classroom-based learning by people with lived experience affected their learning and practice pre-qualification. The findings are underpinned by the theme of ‘challenging the narrative’. They assert the powerful effect service user narratives have on bringing issues ‘to life’ and challenging stereotypes, as well as affecting students’ practice. However, challenging the narrative also linked to students’ reflections on what counts as ‘legitimate’ and reliable knowledge and a disconnection between University-based learning and messages received in practice. The paper argues for an ongoing critical evaluation of the impact of pedagogy led by people with lived experience, with the dual aims of identifying what benefits student learning, as well as critically dissecting power, authority and knowledge.

Capacity-building during public health emergencies: perceived usefulness and cost savings of an online training on SARS-CoV-2 real-time polymerase chain reaction (qPCR) diagnostics in low- and middle-income settings during the COVID-19 pandemic.

Upon the onset of the COVID-19 pandemic, the Public Health Laboratory Support Unit (ZIG4) at the Robert Koch Institute (RKI), the German National Public Health Institute, developed and delivered an online training on SARS-CoV-2 qPCR diagnostics to 17 partner countries in low- and middle-income countries (LMIC). This article analyses the usefulness and cost savings of this training. The authors performed a concurrent mixed-methodology study based on key informant interviews, interviewer-administered questionnaires, and document reviews. Economic costs were estimated from the perspective of RKI. Responding participants indicated that the course provided good and comprehensive information on up-to-date scientific knowledge and laboratory practice in PCR diagnostics. Respondents appreciated how the technical content of the training enhanced their ability to apply diagnostic methods in their daily work. Interviewees highlighted that the fast implementation and the low threshold of attending an online training had allowed them to quickly build skills that were crucial during, and beyond, the COVID-19 crisis. The total estimated cost of the online SARS-CoV-2 qPCR training was 61,644 euros. The total estimated cost of the equivalent face-to-face training was estimated at 267,592 euros. Programme weaknesses identified included the top-down approaches taken, lack of interactive components and opportunities to directly engage with other course participants and with teachers. An online training was developed and implemented to support RKI partner countries in SARS-CoV-2 qPCR diagnostics during the COVID-19 pandemic, thereby strengthening pandemic response and health system resilience. The training incurred in important cost savings compared to the equivalent face-to-face training. Post-pandemic studies could usefully build on these research findings and explore ways to enhance end user involvement and improve interactive features to build stronger communities of learners and facilitate exchange of information and mutual learning.

Lost years, mortality burden: the impact of COVID-19 pandemic on premature death due to road traffic accidents in a northern state in Malaysia

BackgroundThis study addresses the persistent global burden of road traffic fatalities, particularly in middle-income countries like Malaysia, by exploring the impact of the COVID-19 pandemic on Road Traffic Accident (RTA) fatalities in Perak state, Malaysia, with a secondary focus on applying Years of Life Lost (YLL) to understand the implications of these premature deaths.MethodologyThe cross-sectional study retrospectively reviewed certified RTA fatalities from 2018 to 2021, individually counting fatalities in accidents and excluding cases with incomplete death profiles. Data were collected from all Forensic Departments in the government hospitals in Perak. RTA fatalities were confirmed by medical officers/physicians following established procedures during routine procedures. A total of 2517 fatal accident and victim profiles were transcribed into data collection form after reviewing death registration records and post-mortem reports. Inferential analyses were used for comparison between pre- and during COVID-19 pandemic. The standard expected YLL was calculated by comparing the age of death to the external standard life expectancy curve taking into consideration of age and gender in Malaysia.ResultsThis study included 2207 (87.7%) of the RTA fatalities in Perak State. The analysis revealed a decreasing trend in RTA deaths from 2018 to 2021, with a remarkable Annual Percent Change (APC) of -25.1% in 2020 compared to the pre-pandemic year in 2019 and remained stable with lower APC in 2021. Comparison between pre-pandemic (2018–2019) and pandemic years (2020–2021) revealed a difference in the fatality distribution with a median age rise during the pandemic (37.7 (IQR: 22.96, 58.08) vs. 41.0 (IQR: 25.08, 61.00), p = 0.002). Vehicle profiles remained consistent, yet changes were observed in the involvement of various road users, where more motorcycle riders and pedestrian were killed during pandemic (p = 0.049). During pandemic, there was a decline in vehicle collisions, but slight increase of the non-collision accidents and incidents involving pedestrians/animals (p = 0.015). A shift in accident from noon till midnight were also notable during the pandemic (p = 0.028). YLL revealed differences by age and gender, indicating a higher YLL for females aged 30–34 during the pandemic.ConclusionThe decline in RTA fatalities during COVID-19 pandemic underscores the influence of pandemic-induced restrictions and reduced traffic. However, demographic shifts, increased accident severity due to risky behaviors and gender-specific impacts on YLL, stress the necessity for improved safety interventions amidst evolving dynamics.

Utilization and potentials of digital twins – application examples

ABSTRACT In response to global geopolitical challenges and technological advancements, systems of the German Armed Forces are undergoing redesign or adaptation to enhance combat capabilities while prioritizing soldier and civilian protection. Digital twins, virtual representations of reality, offer a systematic and efficient means to explore various factors affecting military systems. Specifically in the naval domain, digital twins can significantly improve applications, reduce design cost, and facilitate user involvement in early phases of the design process. In this paper we use the infantry fighting vehicle PUMA as an example to highlight the importance of leveraging digital twins in virtual reality to address ergonomic and operational challenges, enhance situational awareness, and optimize interaction concepts for improved military effectiveness.

Collaborative approaches in psychiatric rehabilitation: Innovations in practice.

This special section is dedicated to collaborative approaches in psychiatric rehabilitation, which are rooted in foundational values such as service user involvement and self-determination. Five articles featuring collaborative approaches are included and briefly reviewed here. These articles highlight innovations in collaborative approaches, addressing existing limitations in research and practice and advancing understanding of collaborative psychiatric care among diverse populations. They underscore the ongoing need for research and policy reform to promote more routine and widespread implementation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

From Social Barriers to Transformative Planning in Energy Transitions: Learning from Norwegian Planners’ Perspectives

This study investigates social barriers in Norwegian urban energy projects from the planner’s perspective, bridging institutional and reflexive approaches in the field of planning. Compared to technological barriers encountered in the energy transition, social barriers have received relatively little attention. While the former implies a need for hard technological fixes, social barriers cross sectoral dimensions and can potentially be transformed through strategic action during the life of a project. When planning energy transitions under the popular guise of smart and sustainable cities, social barriers arise in the context of urban experimentation, which challenges institutional constructs, participatory planning principles, and knowledge. These aspects are addressed from the planner’s perspective through analysis of planners’ experiences in seven energy pilot and demonstration sites in Norway. The results identify categories of social barriers related to the understanding of a shared vision amongst stakeholders, lowered ambitions over the course of a project, lack of user involvement, and structural constraints to planning. A framework for a deeper understanding of social barriers is proposed, extending to the notion of planners’ transformative agency to support sustainability transitions, which has the potential for future enrichment through the addition of cases and application in other fields of sustainability transitions.

Interpretable Machine Learning for Mode Choice Modeling on Tracking-Based Revealed Preference Data

Mode choice modeling is imperative for predicting and understanding travel behavior. For this purpose, machine learning (ML) models have increasingly been applied to stated preference and traditional self-recorded revealed preference data with promising results, particularly for extreme gradient boosting (XGBoost) and random forest (RF) models. Because of the rise in the use of tracking-based smartphone applications for recording travel behavior, we address the important and unprecedented task of testing these ML models for mode choice modeling on such data. Furthermore, as ML approaches are still criticized for leading to results that are hard to understand, we consider it essential to provide an in-depth interpretability analysis of the best-performing model. Our results show that the XGBoost and RF models far outperform a conventional multinomial logit model, both overall and for each mode. The interpretability analysis using the Shapley additive explanations approach reveals that the XGBoost model can be explained well at the overall and mode level. In addition, we demonstrate how to analyze individual predictions. Lastly, a sensitivity analysis gives insight into the relative importance of different data sources, sample size, and user involvement. We conclude that the XGBoost model performs best, while also being explainable. Insights generated by such models can be used, for instance, to predict mode choice decisions for arbitrary origin–destination pairs to see which impacts infrastructural changes would have on the mode share.

Automated Synthesis for the Safe Production of Organic Azides from Primary Amines.

Described herein is the development of an automated and reproducible process for the conversion of primary amines to organic azides utilizing prepacked capsules containing all the required reagents, including imidazole-1-sulfonyl azide tetrafluoroborate. Apart from manually loading the primary amine into the reaction vessel, the entire reaction and product isolation process can be achieved automatically, with no further user involvement, and delivers the desired organic azide in high purity. This practical and simple automated capsule-based method offers a convenient and safe way of generating organic azides without handling or exposure of potentially explosive reagents.

Rapid reviews methods series: guidance on rapid qualitative evidence synthesis

This paper forms part of a series of methodological guidance from the Cochrane Rapid Reviews Methods Group and addresses rapid qualitative evidence syntheses (QESs), which use modified systematic, transparent and...

The Living Lab to promote educating community development in an inclusive perspective, between innovation and participation

In recent decades, changes in productive and social dynamics have profoundly influenced socio-economic environments, which are now characterized by phenomena such as globalization, the omnipresence of technology and the loosening of social networks. These changes have led to a growing alienation of the individual from the public sphere. In this context, education must focus on fostering in both students and the community a sense of responsibility and belonging, which are essential elements for active participation in political life and building inclusive communities. In light of these premises, the paper illustrates the first steps of a research aimed at the design and implementation of an innovative system for the training of education professionals through a Living Lab, intended as an action-research approach operating between community and innovation. This approach, based on action-research, involves communities and innovation to develop a digital platform that fosters the sharing of inclusive practices. The goal is aligned with international policies and recent scientific debate, which emphasize the need for sustainable growth models that reduce inequalities and combat social exclusion. The Living Lab is configured as a methodology that enhances the involvement of end users in the design and co-creation of innovative training services. This approach not only collects data on the process itself, but implements interventions with short, medium and long-term impacts. In summary, the Living Lab represents an opportunity to develop innovative educational practices, integrating evidence-based research, professional experience and perspectives of people with disabilities, in order to create more inclusive and sustainable communities.

Protocol for the 'Supporting Young Cancer Survivors who Smoke' study (PRISM): Informing the development of a smoking cessation intervention for childhood, adolescent and young adult cancer survivors in England.

Childhood, adolescent and young adult (CAYA) cancer survivors are vulnerable to adverse late-effects. For CAYA cancer survivors, tobacco smoking is the most important preventable cause of ill-health and early death. Yet, effective strategies to support smoking cessation in this group are lacking. The PRISM study aims to undertake multi-method formative research to explore the need for, and if appropriate, inform the future development of an evidence-based and theory-informed tobacco smoking cessation intervention for CAYA cancer survivors. PRISM involves three phases of: 1) an environmental scan using multiple strategies to identify and examine a) smoking cessation interventions for CAYA cancer survivors that are published in the international literature and b) current smoking cessation services in England that may be available to, or tailorable to, CAYA cancer survivors; 2) a qualitative study involving semi-structured interviews with CAYA cancer survivors (aged 16-29 years and who are current or recent ex-smokers and/or current vapers) to explore their views and experiences of smoking, smoking cessation and vaping; and 3) stakeholder workshops with survivors, healthcare professionals and other stakeholders to consider the potential for a smoking cessation intervention for CAYA cancer survivors and what such an intervention would need to target and change. Findings will be disseminated to patient groups, healthcare professionals and researchers, through conference presentations, journal papers, plain English summaries and social media. PRISM will explore current delivery of, perceived need for, and barriers and facilitators to, smoking cessation advice and support to CAYA cancer survivors from the perspective of both survivors and healthcare professionals. A key strength of PRISM is the user involvement throughout the study and the additional exploration of survivors' views on vaping, a behaviour which often co-occurs with smoking. PRISM is the first step in the development of a person-centred, evidence- and theory-based smoking cessation intervention for CAYA cancer survivors who smoke, which if effective, will reduce morbidity and mortality in the CAYA cancer survivor population.

ParkLIV – engaging non-users in green space management

ABSTRACT Everyone has the right to feel welcome, safe and be able to access public green spaces without fear, anxiety or stress. However, the term “accessibility” is primarily used in relation to physical accessibility, while social and cultural dimensions of accessibility to urban public green spaces remains underexplored. Methods and tools for universal design and management that also meets the needs of marginalised groups, are needed. This requires involvement of both users and potential users through participatory methods, building on individual needs and perspectives. In Sweden, traditionally marginalised groups and non-users are rarely engaged in the development of public urban green spaces. Local governments may have the will, but lack resources and appropriate methods in order to do so. Research has recently described a further engagement of users as an unleashed potential in relation to planning and management of urban green spaces. Based on the study of three test beds and the use of public green space governance and management theory, we developed a process model for user participation in green space maintenance with focus on involving marginalised groups and non-users. The model balances what is theoretical optimal with what is practically feasible within the daily work of a municipal organisation. We present an empirically tested process model that can form the basis for future maintenance of urban green spaces, with the use of limited resources.

Analysis of Traditional and Agile Software Development Process for Developing Recommender Model using Machine Learning

Objective: To create an AI-powered recommendation system that is designed for IT professionals to help them choose the best software development approaches. Through the use of specified data parameters. Methods: The recommendation system will make use of machine learning algorithms and data analysis methods to examine team dynamics, project needs, and other variables. The technology will enable developers to improve the quality of products and speed up the development process by recommending suitable development methodologies. Data parameters considered for the development of the recommendation model fall into four categories: requirements, user involvement, development team, type of project, and risk associated with it. Findings: Existing recommendation systems developed by different researchers are applicable for only requirement elicitation and to recommend different phases of the development process, whereas systems that will help select development methodology are not available in the existing systems. Among the five machine learning algorithms applied in the recommender system building process, the DecisionTree Classifier and RandomForest Classifier exhibit superior performance, achieving 100% accuracy, while the Kneighbors Classifier indicates 94.74% accuracy. Novelty: This study of systems introduces a novel approach to software development methodology, a recommender system, which helps IT developers select the best appropriate development approach for the development of a software product or project based on the type of project to be built and other data parameters. Keywords: Agile, Development, Requirements, Methodology, User, Customer

Utilization of Face-to-Face Vestibular Support Groups: A Comparison to Online Group Participation.

This study compared the utilization and outcomes of face-to-face (F2F) vestibular support groups and online support communities (OSC) for individuals with vestibular disorders. We distributed a 31-question anonymous electronic survey through the Vestibular Disorders Association (VeDA) to F2F participants, categorizing user involvement in F2F, OSCs, or both and assessed impact on medical decision-making, psychosocial benefits, and goals achieved. The F2F cohort consisted of 97 individuals comprising primarily of non-Hispanic White women (mean age = 57 years, SD ± 14 years) with diagnoses including persistent postural-perceptual dizziness (19%), Meniere's disease (15%), and vestibular neuritis (13%). Most participants were diagnosed by an otolaryngologist (65%) and attended F2F meetings monthly or less frequently (78%). The OSC group comprised of 551 individuals, primarily of non-Hispanic White women, but was younger in age (mean age = 50 years, SD ± 13 years). OSC participants notably engaged more, with 36% participating on a daily basis and 32% multiple times a week. F2F participants were older (mean age 57 years vs 50 years, P < .001) and more commonly referred by medical professionals (22% F2F vs 6% OSC, P < .001). Both groups had similar achieved goals, including hearing from others with the same diagnosis (84% vs 89%, P > .05) and similar impact on medical decision-making (75% vs 78%, P > .05). More F2F participants reported increased development of coping skills (79% F2F vs 69% OSC, P = .037). OSC participants typically found the group via an online search (75%), compared to 51% for F2F. OSC participants had higher daily engagement (36%) compared to F2F (1%). F2F users are older and more commonly referred by medical professionals. Despite less frequent engagement, F2F participants reported similar influences on achieved goals, medical decision-making, and impact on psychosocial benefits. These findings highlight the importance of both F2F and OSC support groups for individuals with vestibular disorders.

Digital Mental Health for Schizophrenia and Other Severe Mental Illnesses: An International Consensus on Current Challenges and Potential Solutions.

Digital approaches may be helpful in augmenting care to address unmet mental health needs, particularly for schizophrenia and severe mental illness (SMI). An international multidisciplinary group was convened to reach a consensus on the challenges and potential solutions regarding collecting data, delivering treatment, and the ethical challenges in digital mental health approaches for schizophrenia and SMI. The consensus development panel method was used, with an in-person meeting of 2 groups: the expert group and the panel. Membership was multidisciplinary including those with lived experience, with equal participation at all stages and coproduction of the consensus outputs and summary. Relevant literature was shared in advance of the meeting, and a systematic search of the recent literature on digital mental health interventions for schizophrenia and psychosis was completed to ensure that the panel was informed before the meeting with the expert group. Four broad areas of challenge and proposed solutions were identified: (1) user involvement for real coproduction; (2) new approaches to methodology in digital mental health, including agreed standards, data sharing, measuring harms, prevention strategies, and mechanistic research; (3) regulation and funding issues; and (4) implementation in real-world settings (including multidisciplinary collaboration, training, augmenting existing service provision, and social and population-focused approaches). Examples are provided with more detail on human-centered research design, lived experience perspectives, and biomedical ethics in digital mental health approaches for SMI. The group agreed by consensus on a number of recommendations: (1) a new and improved approach to digital mental health research (with agreed reporting standards, data sharing, and shared protocols), (2) equal emphasis on social and population research as well as biological and psychological approaches, (3) meaningful collaborations across varied disciplines that have previously not worked closely together, (4) increased focus on the business model and product with planning and new funding structures across the whole development pathway, (5) increased focus and reporting on ethical issues and potential harms, and (6) organizational changes to allow for true communication and coproduction with those with lived experience of SMI. This study approach, combining an international expert meeting with patient and public involvement and engagement throughout the process, consensus methodology, discussion, and publication, is a helpful way to identify directions for future research and clinical implementation in rapidly evolving areas and can be combined with measurements of real-world clinical impact over time. Similar initiatives will be helpful in other areas of digital mental health and similarly fast-evolving fields to focus research and organizational change and effect improved real-world clinical implementation.

Optimization of Wheelchair Control via Multi-Modal Integration: Combining Webcam and EEG

Even though Electric Powered Wheelchairs (EPWs) are a useful tool for meeting the needs of people with disabilities, some disabled people find it difficult to use regular EPWs that are joystick-controlled. Smart wheelchairs that use Brain–Computer Interface (BCI) technology present an efficient solution to this problem. This article presents a cutting-edge intelligent control wheelchair that is intended to improve user involvement and security. The suggested method combines facial expression analysis via a camera with EEG signal processing using the EMOTIV Insight EEG dataset. The system generates control commands by identifying specific EEG patterns linked to facial expressions such as eye blinking, winking left and right, and smiling. Simultaneously, the system uses computer vision algorithms and inertial measurements to analyze gaze direction in order to establish the user’s intended steering. The outcomes of the experiments prove that the proposed system is reliable and efficient in meeting the various requirements of people, presenting a positive development in the field of smart wheelchair technology.

User involvement in the design of complex digital tools for employees in a large organisation

AbstractLarge organisations are designing complex technology-based tools for their staff to use. In busy workplace environments, it can be difficult to get user input about a design. This paper describes the designer and user interactions in one such organisation, gaining insights that could be useful in other similar settings. The findings are based on a set of interviews with designers and researchers within the organisation. The paper identifies the current practices and constraints involved in understanding and capturing users' needs and discusses potential solutions.