Design Project Research Articles

Research on rock strength prediction model based on machine learning algorithm

The compressive strength of rocks is one of its mechanical characteristics. It has been a difficult problem to predict rock compressive strength conveniently and efficiently, and to solve the limitations of traditional rock compressive strength tests such as high cost, long time consumption, and reliability assurance. In this study, a data set containing 1774 groups of rock compressive strength test data was constructed through file retrieval, including 9 input parameters: rock type, temperature, confining pressure, dimension of specimen, shape of specimen, and experimental method. Eight supervised learning algorithms were used to learn the rock compressive strength test data, and eight rock compressive strength prediction models considering multiple factors were established to obtain a better method of predicting rock compressive strength. By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). Finally, four regression evaluation indicators, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2), were used to evaluate the predictive performance of the established regression models. The results showed that the best-trained model had a MAPE as low as 3.61%, MAE as low as 9.19 MPa, and R2 as high as 0.995. It is noteworthy that AdaBoost was found to be the best model for predicting rock compressive strength. This study presents a significant advancement in the field by demonstrating the effectiveness of machine learning algorithms in this context, which have not been extensively applied to rock compressive strength predictions. The findings suggest that these models can offer substantial improvements over traditional methods, not only in accuracy but also in operational efficiency. This research is important for geotechnical engineering, as accurate rock strength predictions are critical for the design and stability assessments of construction projects, ultimately contributing to safer and more cost-effective engineering solutions.

Engaging Red River Métis families in Manitoba in the development of child health resources – findings from a qualitative study

BackgroundMost research that includes Red River Métis tends to be pan-Indigenous. Grouping Métis with First Nations and Inuit can diminish their unique and diverse experiences, as well as distinctions-based approaches. Taking a step toward addressing this problem, the Manitoba Métis Federation (MMF; the national government of the Red River Métis) invited researchers within the Canadian network Translating Emergency Knowledge for Kids to partner in this research, which focuses on understanding engagement strategies that can help expose Red River Métis parents to child health research opportunities and build trust and transparency amongst research partners and participants.MethodsA qualitative descriptive approach underpinned by a participatory paradigm guided this study. Semi-structured interviews were conducted with 19 Red River Métis parents and Elders via Zoom or telephone. An inductive thematic analysis approach was used to explore patterns and themes across the data.ResultsAnalysis generated four themes: (a) show me why you are here; (b) make it easier for me to take part; (c) create welcoming spaces; and (d) it should be a give and take experience. Parents emphasized the importance of kinship and personal connections, and said they want to hear about child health study opportunities from trusted organizations. They want researchers to be transparent about their research motivations and to offer multiple ways to participate to help them fit research into their busy lives. Relational approaches within the research process (e.g., creating informal/welcoming environments, gathering over food, fostering shared learning/creative opportunities) are prominent in the findings.ConclusionThere is a dearth of research focused on the distinct experiences of Red River Métis families. Engaging Red River Métis parents early in the research process will help incorporate their preferences and perspectives into the design of a larger project to adapt child health resources. More training is needed to help researchers improve their abilities to engage in self-reflection, listen, recognize power relationships, and demonstrate trust and transparency in each research interaction. It is only through respectful and successful engagement that child health research can be relevant, applicable and positively impact Red River Métis children, families and communities.

The tesselle Project: A Collection of R Packages for Research and Teaching in Archaeology

Abstract The use of programming languages in archaeological research has witnessed a notable surge in the last decade, particularly with R, a versatile statistical computing language that fosters the development of specialized packages. This article introduces the tesselle project (https://www.tesselle.org/), a comprehensive collection of R packages tailored for archaeological research and education. The tesselle packages are centered on quantitative analysis methods specifically crafted for archaeology. They are designed to complement both general-purpose and other specialized statistical packages. These packages serve as a versatile toolbox, facilitating the exploration and analysis of common data types in archaeology—such as count data, compositional data, or chronological data—and enabling the construction of reproducible workflows. Complementary packages for visualization, data preparation, and educational resources augment the tesselle ecosystem. This article outlines the project's inception, its objectives, design principles, and key components, along with reflections on future directions.

Does Using Artificial Intelligence in Citizen Science Support Volunteers’ Learning? An Experimental Study in Ornithology

One of the oldest and largest biodiversity-related citizen science (CS) projects is eBird (https://ebird.org/home), developed by the Cornell Lab of Ornithology. It provides a mobile application for birdwatchers to record checklists of when, where, and how they have seen or heard birds. The Cornell Lab has also developed a mobile application, Merlin, which uses a deep convolutional neural network to help users automatically identify bird species from photos, sounds (converted to spectrograms), or descriptions. This research investigates how the use of machine learning (ML) classification models affects the learning of novice birders. Our participants (computer science students with no previous background in ornithology) were randomly divided into three groups: one using the eBird application and identifying bird species themselves; one using the Merlin application, which uses ML to automatically identify birds from photos or sounds; and a control group. Participants were tested on their knowledge of birds before and after participating in the project to see how using the ML classification model affected their learning. We also interviewed selected participants after the post-test to understand what they had done and what might explain the results. Our results show that novice participants who participate in a CS project for even a short time significantly improve their content knowledge of familiar birds in their neighbourhood, and that eBird users outperform Merlin users on the knowledge post-test. Although AI may improve volunteer productivity and retention, there is a risk that it may reduce their learning. Further research with different participant profiles and project designs is needed to understand how to optimise volunteer productivity, retention, and learning in AI-assisted CS projects.

Effect of Volumetric Flow Rate on Heat Transfer Characteristics of Single-Fractured Rock with Different Surface Morphology and External Temperature

The primary aim of this study is to explore how varying flow rates impact the heat transfer in single fractures, taking into account the effects of surface roughness, aperture and external temperature of the rock. Utilizing COMSOL Multiphysics, the fluid flow and heat transfer through 3D fracture models characterized by different roughness and apertures were simulated with volumetric flow rates ranging from 1 × 10−6 m3/s to 1 × 10−5 m3/s. The combined effects of these factors on key metrics, including outlet temperature, thermal breakthrough time, energy extraction efficiency, and heat transfer coefficients were systematically analyzed. The results indicate that water flow rate dominantly influences heat transfer, followed by fracture surface morphology and rock external temperature. Higher flow rates enhance both heat transfer and total heat extraction, while also increasing temperature non-uniformity, which improves overall heat extraction efficiency. Surface roughness significantly affects temperature distribution, leading to heterogeneous thermal profiles, especially in narrower fractures. Additionally, higher external temperatures and flow rates facilitate faster thermal breakthroughs by reducing thermal resistance. The interplay between surface roughness and thermal breakthrough time is intricate, with increased roughness prolonging breakthrough times in smaller apertures but potentially reducing them in larger ones. At smaller apertures, increasing the JRC from 2.29 to 17.33 results in a 1.01 to 1.20 times increase in thermal breakthrough time, whereas at larger apertures, thermal breakthrough time decreases by a factor of 1.01 to 1.29. This highlights the importance of carefully selecting fluid parameter in the design of geothermal projects to optimize heat extraction efficiency.

Supporting Human and Machine Co-Learning in Citizen Science: Lessons From Gravity Spy

We explore the bi-directional relationship between human and machine learning in citizen science. Theoretically, the study draws on the zone of proximal development (ZPD) concept, which allows us to describe AI augmentation of human learning, human augmentation of machine learning, and how tasks can be designed to facilitate co-learning. The study takes a design-science approach to explore the design, deployment, and evaluations of the Gravity Spy citizen science project. The findings highlight the challenges and opportunities of co-learning, where both humans and machines contribute to each other’s learning and capabilities. The study takes its point of departure in the literature on co-learning and develops a framework for designing projects where humans and machines mutually enhance each other’s learning. The research contributes to the existing literature by developing a dynamic approach to human-AI augmentation, by emphasizing that the ZPD supports ongoing learning for volunteers and keeps machine learning aligned with evolving data. The approach offers potential benefits for project scalability, participant engagement, and automation considerations while acknowledging the importance of tutorials, community access, and expert involvement in supporting learning.

“Youth are experts in what they need”: experiences and best practice in co-designing and implementing Fast-PrEP, a novel PrEP service for adolescents and youth in Cape Town, South Africa

IntroductionDefining the prevention needs, motivations, and gender dynamics influencing adolescent and young people’s (AYP’s) healthcare access is a key component to successful PrEP (pre-exposure prophylaxis for HIV prevention) implementation. WHO encourages a strong people-cantered approach to healthcare delivery, and this is particularly emphasized for HIV services. Enhanced youth engagement is needed to ensure that interventions are tailored to the specific needs and preferences of youth populations.DescriptionFast-PrEP is an implementation science project providing PrEP (oral, vaginal ring, and injectable) to adolescents and young people (15–29 years old) in Cape Town, South Africa. In 2020, during the planning phase of this project, a Youth Reference Group (YRG) was established to guide, co-create, monitor, and evaluate the implementation of PrEP delivery. From March to October 2023, we conducted four focus group discussions with thirty YRG members, and seven interviews with project implementers (including clinical and research staff). This study aimed to explore real-time experiences of young people and staff members and provide recommendations for best practices when setting up and engaging with YRGs.FindingsOverall, young people described their experience of being involved in the YRG as empowering. Young people felt that their voices and needs were valued when seeing their input put into action or witnessing their designs in demand creation campaigns. Young people felt that being consulted was not for tokenistic reasons, but their contribution was valuable and considered young people’s sexual health needs. Best practices included involving the YRG in every aspect of the project design and implementation, being flexible around young people’s schedules, and having engagements in spaces that are easily accessible and safe for key populations. Staff recommended upskilling the youth members in knowledge around HIV and certain ‘soft skills’ such as building self-confidence and communication skills. It was also recommended that all research and clinical staff need ongoing training and sensitization on the importance and value of youth engagement.ConclusionThe involvement of young people in the co-creation of Fast-PrEP services in all phases of service provision, has been effective in assisting to provide youth appropriate PrEP services.

Fostering students’ confidence in collaborating in transdisciplinary online problem-based learning projects: practical guidelines for educators

The primary role and value of a transdisciplinary online collaborative problem-based learning (OCPBL) project is that all disciplines fully participate in producing solutions to challenges. Acquiring the confidence to do so transcends all disciplines. The central role of educators then emerges in facilitating students’ confidence in their ability to participate and perform in OCPBL projects. This paper focuses on Phase 3 of a longitudinal ethnographic study, with the aim of consolidating practical guidelines to facilitate confident participation in an OCPBL project. Guidelines emerged from exploratory focus groups with educators as participants involved in the design and facilitation of an OCPBL project. Thematic analysis presents two sets of guidelines: achievement of the facilitation of effective OCPBL by students and student teams and guidelines for the composition and orientation of educator panels and their facilitation of confident OCPBL. The latter makes the most significant contribution to theory and practice. Our research shows that educators should, in particular, guide and support students in exploring and clearly expressing their own feelings of professional self-worth within and beyond their own disciplines while gaining insight and developing due respect for others. Most importantly, full collaboration in an experiential transdisciplinary OCPBL project requires recognition and respect for one's own and others’ disciplines, both among students and among educators. Confidence as a graduate attribute is also key to the required skill set in transdisciplinary online teams engaged in complex collaborative problem solving and value creation.

Three-dimensional embodied visibility graph analysis: Investigating and analyzing values along an outdoor path

In visibility analysis, a major focus is the relationship between people and the environment, and one of the most important spatial concepts is Isovist. Although typically represented in two dimensions in architecture, this concept has recently been computed in a three-dimensional environment. However, embodied 3D isovist Theory as developed to date does not account for locomotion. In this paper, therefore, we combine that theory with 3D visibility graph theory to develop and propose the Three-Dimensional Embodied Visibility Graph (3D E-VGA). To present and evaluate the proposed model in an architectural environment, we analyze the three-dimensional scene of a pedestrian moving along a path in an outdoor environment, specifically that of a container housing design project in Cairo known as “Sheltainer.” Further, we investigate the relationships between the t-d ratio, the v-h ratio, vertical jaggedness, connectivity, and integration values and conclude that of these the last three-vertical jaggedness, connectivity, and integration- are significantly correlated with each other. However, the relationship between v-h, t-d, and connectivity and integration values has not been determined. Therefore, analyzing both values related to embodied 3D isovist and 3D visibility graph provides us with a more comprehensive and effective analysis of pedestrians’ visual perceptions along a path.

Projective toric designs, quantum state designs, and mutually unbiased bases

Toric t-designs, or equivalently t-designs on the diagonal subgroup of the unitary group, are sets of points on the torus over which sums reproduce integrals of degree t monomials over the full torus. Motivated by the projective structure of quantum mechanics, we develop the notion of t-designs on the projective torus, which have a much more restricted structure than their counterparts on full tori. We provide various new constructions of toric and projective toric designs and prove bounds on their size. We draw connections between projective toric designs and a diverse set of mathematical objects, including difference and Sidon sets from the field of additive combinatorics, symmetric, informationally complete positive operator valued measures and complete sets of mutually unbiased bases (MUBs) from quantum information theory, and crystal ball sequences of certain root lattices. Using these connections, we prove bounds on the maximal size of dense Btmodm sets. We also use projective toric designs to construct families of quantum state designs. In particular, we construct families of (uniformly-weighted) quantum state 2-designs in dimension d of size exactly d(d+1) that do not form complete sets of MUBs, thereby disproving a conjecture concerning the relationship between designs and MUBs (Zhu 2015). We then propose a modification of Zhu's conjecture and discuss potential paths towards proving this conjecture. We prove a fundamental distinction between complete sets of MUBs in prime-power dimensions versus in dimension 6 (and, we conjecture, in all non-prime-power dimensions), the distinction relating to group structure of the corresponding projective toric design. Finally, we discuss many open questions about the properties of these projective toric designs and how they relate to other questions in number theory, geometry, and quantum information.

Designing sensory and cognitive stimulation activities with and for people living with moderate to late-stage dementia

This study addresses a participatory design project involving a researcher in the field of design and dementia, undergraduate design students, people living with moderate to late-stage dementia from a Day Centre run by Alzheimer Portugal and care workers. The project was held during four months as part of the research REMIND, and is grounded on the concept of personhood, emphasizing the importance of considering biographical features, values, interests, and culture of people with and for whom design projects are being developed. Considering the profile of the Centre’s users, the stage, and manifestations of dementia in each one, it was necessary to combine qualitative methods, which were systematically adapted according to each situation. Methods included: sensory ethnography, participatory observation, walking interviews, ethnographic field notes and interviewing. The strategies adopted in the participatory design process were designed according to the users’ aspirations and interests, prioritizing playfulness, enjoyment, and wellbeing in the moment. Sensory and cognitive stimulation games were designed with these people living with dementia and made available at the Centre for their use. The results of this project provide a basis for reflection on the ongoing research and inform future practices in this area.

Design of Car Based on 5G Network Control

The role of smart cars is pivotal, and this project designs and implements a four-wheel vehicle control system leveraging 5G communication technology. The system aims to enhance the portability of smart cars, reduce their costs, enable remote control functionality, and improve mobility to meet the needs of modern Internet of Things (IoT) applications. The system integrates an ESP8266 Wi-Fi module with the Blinker IoT platform to enable remote, real-time control of car movement via a smartphone app. Using Access Point (AP) mode for fast network configuration, users can input Wi-Fi credentials and a Blinker key through a web interface for easy setup. Through the custom app interface, users can send commands to control the car’s forward, backward, turning, and stopping actions, as well as adjust speed and operation delay. Additionally, the system includes Electrically Erasable Programmable Read-Only Memory (EEPROM) data storage to ensure the persistent saving of configuration information, and it features a remote wireless camera for external monitoring of the car’s surroundings. The Android-based remote control design allows users to monitor and control the car’s movement anytime and anywhere. Experimental results show that the system is stable, provides smooth control, operates at low cost and low power consumption, and offers good portability. Therefore, this intelligent car control system offers valuable insights for smart car development and application. It can also be integrated with popular smart homes, IoT, and other emerging technologies, offering broad application potential and promising development prospects.

Using Machine Learning CART Decision Trees for Predicting the Causes of Delays in Projects from the Construction Industry

Construction projects are complex endeavours, with potential obstacles that can cause delays which can have particularly profound implications potentially impacting on company’s financial health, business continuity and reputation. It is becoming increasingly recognised that delays are context-specific and multifaceted, requiring more industry-oriented perceptions. This work proposes the exploratory use of Machine Learning based on Classification and Regression Trees (CART) Decision Trees (DT) to assess the predictive analysis of these approaches, considering surveys (primary data) collected from 100 specialists with different backgrounds and experiences in the construction industry. Survey responses are discussed, followed by the CART DTs, which are used as predictor for clarifying underneath relationship among different variables in a project environment. The major issue presented is related to Project Design, with “The firm is not allowed to apply for an extension of contract period”, with two possible predictors, firstly, as the main factor it is found “Mistakes, inconsistencies, and ambiguities in specification and drawing”, while other aspect highlights “Poor site supervision and management by the contractor”. The results indicate that the correct use of Artificial Intelligence techniques with relevant data are potential tools to support the analysis of scenarios and avoidance of project delays in Project Management.

Environmental Monitoring and Assessment for Sustainable Construction Projects: Leveraging Lean Techniques

To increase productivity and avoid waste, the construction industry has started implementing Lean ideas and methodologies in construction projects. Due to a lack of awareness of lean practices in the preparation, design, and execution of building and infrastructure projects, lean practices are not very familiar among construction projects, which are most commonly used in the manufacturing industry. Hence, an effort has been made in this paper to provide a comprehensive review of the literature and case studies to analyze the suitability of lean practice in sustainable waste management, increased productivity, and on-time project delivery. It aims to explore the effect of improving communication and fostering collaboration among stakeholders on time, costs, and resource management. The review identified the most commonly applied lean practices, Just in Time (JIT) and Last Planner System (LPS), and linked the adoption of lean techniques within the construction sector to a total of sixteen distinct benefits for the economy, society, and the environment. According to this study, lean techniques have a strong chance of boosting productivity in the construction industry and developing a sustainable built environment, but they also need to be used widely and continuously to achieve these goals.

Guidance on the assessment of learning outcomes for those designing procedures and projects - Report of an ETPLAS Working Group.

This document provides assessment criteria for evaluation of each of the Learning Outcomes of the Modules specified (in addition to the Core Modules) for those designing procedures and projects in the Education and Training Framework guidance document by the European Commission and endorsed by the Member States Competent Authorities. This Working Group was tasked to produce these criteria by the Education & Training Platform for Laboratory Animal Science, which was funded by the European Commission to this aim. The assessment criteria address knowledge and skills (including critical thinking) expected to be acquired during education and training of persons preparing to design research procedures and projects using animals under the scope of Directive 2010/63/EU. Recognizing the diversity of expertise and experiences of those being educated and trained, we provide two levels of attainment, an ideal response and one that would be acceptable for each Learning Outcome. The balance between ideal and acceptable could be decided by the particular course providers and/or assessors, according to their local requirements. We envisage that the use of these assessment criteria by training providers and accrediting or approving bodies will help harmonize the education and training for those who will design procedures and projects using animals for scientific purposes. In Europe, this may also contribute to mutual recognition of training, and facilitate free movement of scientists.

THE ROLE OF A CLIENT-ORIENTED APPROACH IN MANAGING WEB DESIGN PROJECTS

The article is devoted to the study of the place of the client-oriented approach in the management mechanism of web design projects. In the context of the dynamic development of the digital economy, as well as increased competition in the market of services in this area, the task of adapting development processes to individual customer needs becomes urgent. The purpose of the study is to identify the most effective methods of implementing a client—oriented approach to web design project management and characterize their impact on the final result. There are contradictions in understanding the optimal level of client participation in the project: on the one hand, high customer engagement helps to ensure that their needs are met, on the other hand, it sometimes significantly slows down the development process and significantly increases costs. It was concluded that the use of a client-oriented approach, provided that there is a well-organized process of interaction with the customer, can improve the quality of services and customer satisfaction, which, in turn, contributes to the successful implementation of projects. The novelty lies in the fact that an innovative methodology "Integrative client-centered design" is proposed. It is based on the synthesis of best practices of project management, design thinking, Agile approaches adapted to the specifics of web design projects. The article will be useful for web design project managers, developers, as well as management and marketing specialists who seek to implement effective strategies for interacting with customers.

중학교 미술수업에서 사회정의 실천을 위한 사회공헌 디자인 (Philanthropy Design) 프로젝트 실행연구

This study aims to reflect on the results of the operation of the philanthropy design project for practicing social justice and to provide implications for practicing social justice through art education. Art education as a practice of social justice is not an exploration of beautiful colors or shapes, but a practice linked to life that continuously communicates and solves problems that can become social issues. Accordingly, through the philanthropy design project, problems are found in socio-cultural aspects, public interests are pursued, and problems are solved with novel and original designs. In particular, this study was designed to provide in-depth education by organically linking the content elements of knowledge and understanding, process and function, and value and attitude in the 2022 revised curriculum, ‘Teaching and Learning in School Curriculum Design and Operation.’ In the first stage (emotion), the class was developed as a student- participatory class, which provided students with a deep experience related to life. In the second stage (cognitive) area, the procedural knowledge of process and function enhanced cooperation and creative problem-solving skills, and in the third stage (behavioral) area, the ability to practice social justice linked to life was demonstrated by internalizing it in terms of values and attitudes.

The Temperature-Dependent Monotonic Mechanical Characteristics of Marine Sand–Geomembrane Interfaces

The utilization of geomembrane reinforcement technology is pervasive in marine sand foundation reinforcement projects. However, the elevated temperatures and intricate stress conditions prevalent in marine environments exert a notable influence on the mechanical characteristics of geomembrane interfaces comprising marine sand, which impedes the efficacy of geomembrane reinforcement in marine sand foundations. Nevertheless, there is a lack of research investigating the temperature-dependent interfacial mechanical performance of geomembranes and marine sand under diverse stress states. In this study, a series of monotonic shear tests were carried out on the interface between geomembranes and marine sand within a temperature range of 5 °C to 80 °C. These experiments were carried out using a self-developed large-scale temperature-controlled interfacial dynamic and static shear device. The experimental results demonstrate that temperature has a pronounced effect on the monotonic mechanical characteristics of the geomembrane–marine sand interface, which displays clear temperature dependence. The findings of this study may help in the design and optimization of offshore projects where a marine sand–polymer layer interface exists.

Capital budgeting for electrical engineering projects: A practical methodology

The paper presents the capital budgeting process and identifies key elements in the process. A standardized approach in capital budgeting by application of information technology resources for both proposal submission and documentation becomes key to success in handling large volumes. An electrical engineering distribution system design project involves the application of engineering codes and standards to stay compliant and provide safe design and construction. A model starting with proposals acceptance to evaluation and approval of capital projects was presented. The proposal stage was decoded further into assessments of the existing electrical infrastructure based on aging and engineering standards. Upon review of the standards, the proposals were accepted for evaluation and approval. For business professionals, there is a gap when working in an electrical engineering construction industry when it comes to knowing applicable engineering standards and their application. This research filled that gap by enlisting the intent of the standards review process. Although the focus was on understanding a holistic approach to electrical engineering projects, a detailed analysis of specific tasks may be designed based on the model presented in this paper. Additionally, the transmission side of projects will have a similar application of capital budgeting.

A qualitative exploration of active ingredients and mechanisms of action of an online singing programme with mothers experiencing postnatal depression during the COVID-19 pandemic: SHAPER-PNDO study

BackgroundSocial distancing restrictions and the suspension of in-person treatment and support contributed to an increase in postnatal depression during the coronavirus disease 2019 (COVID-19) pandemic. Creative health interventions can help to alleviate anxiety and depression, with studies showing that singing is particularly effective for supporting the mental health of new mothers. We adapted an in-person group singing programme (Breathe Melodies for Mums (M4M)) to online delivery during the COVID-19 pandemic to support the mental health of new mothers, and, in a feasibility study, found improvements in postnatal depression (PND) symptoms at 6-month follow up. The current qualitative study aimed to explore how and why M4M-online impacted the mental health of those taking part.MethodsWe took a theory-based approach using the INgredients iN ArTs in hEealth (INNATE) Framework of ‘active ingredients’ and the Multi-level Leisure Mechanisms Framework of ‘mechanisms of action’ to identify and categorise intervention components and change mechanisms. Iterative consensus building between three researchers was complemented by qualitative semi-structured online interviews with 24 women experiencing PND symptoms who took part in M4M-online. Data were analysed inductively using reflexive thematic analysis.ResultsConsistency was found between the online and in-person interventions in active ingredients relating to project design, content, programme management and the composition of the group. Key differences were in the social and contextual ingredients. Psychological, social and behavioural mechanisms for improved mental health and wellbeing included: (1) Increased self-confidence as a mother, (2) Increased positive emotional responses, (3) A supported exploration of self-dentity, (4) Reduced loneliness and isolation, (5) Increased social bonding and connections with family and (6) Enhanced sense of time through new routines.ConclusionsParticipating in online group singing can support new mothers experiencing PND by triggering psychological, social and behavioural responses that lead to improved mental health. Key programme features are identified which can be used to design future online creative health interventions or tailor in-person activities for remote delivery to support populations who may face practical and social barriers to attending in-person.