Iterative Design Research Articles

Label-Free and Universal CRISPR/Cas12a-Based Detection Platform for Nucleic Acid Biomarkers.

CRISPR/Cas12a has been widely used in molecular diagnostics due to its excellent trans-cleavage activity. However, conventional reporters, such as F/Q-labeled single-stranded DNA (ssDNA) reporters, enzyme-labeled reporters, and spherical nucleic acid reporters, require complex modification or labeling processes. In this study, we have developed a rapid, universal, and label-free CRISPR/Cas12a-based biomarker detection platform via designing a G-quadruplex (G4) containing a hairpin structure as the reporter. The hairpin loop design of hairpin G4 improves the cleavage efficiency of Cas12a and the signal strength of the G4 binding ligand. Meanwhile, the incorporation of a G4 binding dye (protoporphyrin IX) eliminates the need for complex modifications. The CRISPR-hairpin G4 detection platform is capable of detecting ssDNA, double-stranded DNA, genetic RNAs, and miRNAs. Moreover, this platform achieves label-free detection in clinical samples, demonstrating its practical applicability and efficiency.

Physical Activity Mobile App (CareFit) for Informal Carers of People With Dementia: Protocol for a Feasibility and Adaptation Study.

Physical activity is a critical component of both well-being and preventative health, reducing the risk of both chronic mental and physical conditions and early death. Yet, there are numerous groups in society who are not able to undertake as much physical activity as they would like to. This includes informal (unpaid) carers, with the United Kingdom national survey data suggesting that 81% would like to do more physical activity on a regular basis. There is a clear need to develop innovations, including digital interventions that hold implementation potential to support regular physical activity in groups such as carers. This study aims to expand and personalize a cross-platform digital health app designed to support regular physical activity in carers of people with dementia for a period of 8 weeks and evaluate the potential for implementation. The CareFit for dementia carers study was a mixed methods co-design, development, and evaluation of a novel motivational smartphone app to support home-based regular physical activity for unpaid dementia carers. The study was planned to take place across 16 months in total (September 1, 2022, to December 31, 2023). The first phase included iterative design sprints to redesign an initial prototype for widespread use, supported through a bespoke content management system. The second phase included the release of the "CareFit" app across Scotland through invitations on the Apple and Google stores where we aimed to recruit 50 carers and up to 20 professionals to support the delivery in total. Partnerships for the work included a range of stakeholders across charities, health and social care partnerships, physical activity groups, and carers' organizations. We explored the implementation of CareFit, guided by both Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) and the Complex Intervention Frameworks. Project processes and outcomes were evaluated using mixed methods. The barriers and enablers for professional staff to signpost and use CareFit with clients were assessed through interviews or focus groups and round stakeholder meetings. The usability of CareFit was explored through qualitative interviews with carers and a system usability scale. We examined how CareFit could add value to carers by examining "in-app" data, pre-post questionnaire responses, and qualitative work, including interviews and focus groups. We also explored how CareFit could add value to the landscape of other online resources for dementia carers. Results from this study will contribute new knowledge including identifying (1) suitable pathways to identify and support carers through digital innovations; (2) future design of definitive studies in carer populations; and (3) an improved understanding of the Reach, Effectiveness, Adoption, Implementation, and Maintenance across a range of key stakeholders. DERR1-10.2196/53727.

Implementing strong sustainability in a design process

The emergence of a post-growth era is expected that implies rethinking the production and consumption patterns with novel design models this forces higher educational institutions to reconsider their traditional ways of teaching sustainability in their curricula. Companies also need to overcome strategies that compartmentalize environment, society and economy in their industrial strategy in order to evolve in their support for the transition. The aim of this paper is to present a design process anchored in the Strong Sustainability paradigm to overcome the gap of how Strong Sustainability could be operationalised. Design Research Methodology (DRM) has been chosen as the supporting framework for the development of this project. The Design for Strong Sustainability (DfSoSy) methodology proposed, is built on three aspects of Strong Sustainability (Milieu, Regeneration, Safe and just operating space) successively applied in a sequenced iterative design process. The latter enable the integration of thought patterns associated with integrative, systemic and fractal or multi-scale thinking respectively. Moreover, the principle of sub-optimality is highlighted as a decision principle in SoSy. Results obtain has been validated as well on the pedagogical objectives as in the usefulness of the DfSoSy. The practical contribution of this study is the DfSoSy toolkit©.

Iinaaka Siinakupii Tsiniikii (Little video storyteller): co-designing digital literacy with Piikani First Nation

Tensions persist in co-designing appropriate forms of digital literacy with Indigenous peoples, particularly in contexts of settler colonialism. Given the historically extractive nature of many institutional research relations with Indigenous peoples, emphasis should be placed on community-led approaches to learn how people are adapting and adopting digital technologies. Through concepts like Niitooii (the same that is real; paralleling), Indigenous peoples offer guidance to ensure projects generate reciprocal benefits for both researchers and communities. In this context, our article documents a multi-year project to co-design a land-based camp blending Piikani (Scabby Robe People; an Indigenous People, prairie regions of Alberta, Canada and northern Montana, USA) First Nation culture with digital literacy pedagogies. Guided by Aapátohsipikáni (Northern Piikani, an Indigenous People, prairie region of Alberta, Canada) scholarship and research on Indigenous-settler relations and methodologies, we illustrate how our long-term, iterative project design generated good relations and moments of tension and transformation.

Designing a Data Dashboard for Health Departments and Overdose Fatality Review Teams

IntroductionOverdose Fatality Review (OFR) teams within health departments rely on data from multiple isolated sources to study the opioid crisis. Recently, we linked electronic health record data with state agency data to form a regional Substance Misuse Data Commons (SMDC) using privacy-preserving record linkage. Our goal in this study was to use human factors design principles to design a data dashboard for OFR teams using the linked datasets that will overcome current barriers within OFR workflows. MethodsWe utilized NASA task load surveys, semi-structured interviews, and design sessions with end users to identify data needs for an optimal dashboard design. We assessed current workloads, data collection processes, and desired future state. We subsequently performed iterative design sessions for the generation and evaluation of low-fidelity prototypes. To overcome issues with privacy and security, we used synthetic data in a cloud-based platform to represent the SMDC for simulation. ResultsEleven OFR organizers participated. Pre-dashboard surveys on existing workflow showed high mental workload associated with data aggregation and case review, identifying a need for more accessible, comprehensive data. In our low-fidelity dashboard demo with synthetic data, iterative design adjustments were made in data visualization, storyline organizations, and theme-based data aggregation across pre-hospital and hospital data. ConclusionsWe refined the data dashboard prototype into a high-fidelity version, set for further usability and human factors evaluation. We addressed privacy and security concerns through synthetic data use while the real-world data is maintained in a HIPAA-secure Azure cloud environment with access for approved users.

Looping Flexible Fluoropolymer Microcapillary Film Extends Analysis Times for Vertical Microfluidic Blood Testing.

The microfluidic measurement of capillary flow can be used to evaluate the response of biological samples to stimulation, where distance and velocity are altered. Melt-extruded multi-bored microfluidic capillaries allow for high-throughput testing with low device cost, but simple devices may limit control over sample flow when compared to the more complex "lab-on-a-chip" devices produced using advanced microfluidic fabrication methods. Previously, we measured the dynamics of global haemostasis stimulated by thrombin by dipping straight vertical microcapillaries into blood, but only the most rapid response could be monitored, as flow slowed significantly within 30 s. Here, we show an innovative method to extend both the stimulation process and flow measurement time without increasing the cost of the device by adding simple loops to the flexible extruded device. The loops enable longer time-scale measurements by increasing resistance to flow, thereby reducing the dependence on high stimulus concentrations for rapid reactions. The instantaneous velocity and equilibrium heights of straight and looped vertical microcapillary films were assessed with water, plasma and whole blood, showing that the loops create additional frictional resistances, reduce flow velocity and prolong residence times for increased time scales of the stimulation process. A modified pressure balance model was used to capture flow dynamics with the added loop. Looped devices loaded with thrombin and collagen showed an improved detection of blood stimulation responses even with lower stimulus concentrations, compared to straight vertical capillaries. Thrombin-activated blood samples in straight capillaries provided a maximum measurement zone of only 4 mm, while the looped design significantly increased this to 11 mm for much longer time scale measurements. Our results suggest that extending stimulation times can be achieved without complex microfluidic fabrication methods, potentially improving concentration-response blood stimulation assays, and may enhance the accuracy and reliability. We conclude adding a loop to low-cost extruded microfluidic devices may bring microfluidic devices closer to delivering on their promise of widespread, decentralized low-cost evaluation of blood response to stimulation in both research and clinical settings.

Towards end-to-end structure determination from x-ray diffraction data using deep learning

Powder crystallography is the experimental science of determining the structure of molecules provided in crystalline-powder form, by analyzing their x-ray diffraction (XRD) patterns. Since many materials are readily available as crystalline powder, powder crystallography is of growing usefulness to many fields. However, powder crystallography does not have an analytically known solution, and therefore the structural inference typically involves a laborious process of iterative design, structural refinement, and domain knowledge of skilled experts. A key obstacle to fully automating the inference process computationally has been formulating the problem in an end-to-end quantitative form that is suitable for machine learning, while capturing the ambiguities around molecule orientation, symmetries, and reconstruction resolution. Here we present an ML approach for structure determination from powder diffraction data. It works by estimating the electron density in a unit cell using a variational coordinate-based deep neural network. We demonstrate the approach on computed powder x-ray diffraction (PXRD), along with partial chemical composition information, as input. When evaluated on theoretically simulated data for the cubic and trigonal crystal systems, the system achieves up to 93.4% average similarity (as measured by structural similarity index) with the ground truth on unseen materials, both with known and partially-known chemical composition information, showing great promise for successful structure solution even from degraded and incomplete input data. The approach does not presuppose a crystalline structure and the approach are readily extended to other situations such as nanomaterials and textured samples, paving the way to reconstruction of yet unresolved nanostructures.

A digital tool for life cycle assessment in construction projects

The building and construction industry is responsible for around 40% of global greenhouse gas emissions, driving the urgent need for new regulations. As such, the life cycle assessment (LCA) methodology has become fundamental for evaluating environmental impacts. Despite the need for digital tools to support environmental performance evaluations, the lack of guidance on developing such tools hinders their implementation. This article presents an automated configuration approach to develop digital tools in construction, which facilitates the proactive comparison of design choices and reduces CO2 emissions. We demonstrate its application by implementing it at Heidelberg Materials Cement Sverige in Sweden. The results reveal that the LCA digital tool influences decision-making and efficiently quantifies global warming potential in the early project stages and reduces product-related CO2 emissions by up to 40%. Furthermore, the findings highlight greater accuracy in LCA calculations compared to current manual methods and quicker design iterations thanks to real-time information.

Feasibility Testing of the Bionet Sonar Ultrasound Transcutaneous Energy Transmission (UTET) System for Wireless Power and Communication of a LVAD.

To address the clinical need for totally implantable mechanical circulatory support devices, Bionet Sonar is developing a novel Ultrasonic Transcutaneous Energy Transmission (UTET) system that is designed to eliminate external power and/or data communication drivelines. UTET systems were designed, fabricated, and pre-clinically tested using a non-clinical HeartWare HVAD in static and dynamic mock flow loop and acute animal models over a range of pump speeds (1800, 2400, 3000 RPM) and tissue analogue thicknesses (5, 10, 15mm). The prototypes demonstrated feasibility as evidenced by meeting/exceeding function, operation, and performance metrics with no system failures, including achieving receiver (harvested) power exceeding HVAD power requirements and data communication rates of 10kB/s and pump speed control (> 95% sensitivity and specificity) for all experimental test conditions, and within healthy tissue temperature range with no acute tissue damage. During early-stage development and testing, engineering challenges for UTET size reduction and stable and safe operation were identified, with solutions and plans to address the limitations in future design iterations also presented.

Design and analysis of quadcopter drone frame using finite element analysis

The design and analysis of a quadcopter drone frame using finite element analysis (FEA) methods are presented in this work. The goal is to save weight and material consumption while optimising the frame's performance attributes and structural integrity. The finite element approach offers a reliable foundation for modelling the behaviour of structures under different loading scenarios, enabling effective design iterations and enhancements. Through the use of FEA, this study seeks to improve the stability, durability, and aerodynamic efficiency of the frame, which will eventually aid in the creation of more dependable and effective quadcopter drones.

Building a culture of workforce wellness using implementation science-informed strategies: A qualitative content analysis.

Successfully addressing burnout in health and human services settings is a topic of growing interest and impact in the field. Implementation science gives us strategies to build organizational readiness to create a culture of workforce wellness. This study used strategies for identifying and preparing wellness champions and building feedback loops to begin to build a culture of workforce wellness. The primary aim of this study was to assess perspectives on establishing feedback loops across all levels of the organizational hierarchy. This study took place in a community mental health organization that provides services across four different states. Champions in each state were identified and connected with leaders and teams. The champions supported the engagement of leaders and the design of feedback loops. Champions remained engaged throughout the process of assessing needs and sharing workforce wellness data. A qualitative content analysis was conducted on data collected during meetings that were intended to create organizational practice to policy feedback loops. Staff across all levels of the organizational hierarchy shared feedback and participated in facilitated reflective discussion. Participants offered several suggestions for addressing burnout. Across all participants, workplace connections were perceived as a protective factor against burnout. This implementation science strategy to help combat burnout is an effective and feasible way to include frontline staff voices and build connection and trust between leaders and staff in health and human services settings. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Lattice Boltzmann modeling of natural circulation loop with emphasis on non-Boussinesq mechanism

The natural circulation loop is crucial for the safe and stable operation of nuclear reactors and other applications. Traditional numerical algorithms, based on the Boussinesq approximation, have limitations when dealing with large temperature differences and density disparity, and they do not fully address fluid compressibility. This paper adopts the decoupled and stabilized lattice Boltzmann method (DSLBM) with a non-Boussinesq algorithm to study the natural circulation loop. The DSLBM provides a detailed flow description under large temperature and density differences, incorporating the pseudopotential multiphase model, temperature equation, and state equation, without relying on assumptions. The study examines the loop's performance under various temperature differences, central height differences, and heating source lengths, focusing on mass flow rate, driving head, and heating power. It reveals the energy performance, flow characteristics, and heat transfer properties of the loop, highlighting the physical mechanisms involved. Comparison with the empirical formulation of the incompressible equation from the theoretical aspect shows that when the temperature difference coefficient is lower than 0.15, the two methods are not much different from each other. When the temperature difference coefficient reaches 0.2, 0.3, and 0.4, the difference between the two methods is 9.47%, 19.11%, and 42.64%, respectively. Consequently, the Boussinesq approximation can be compensated by DSLBM, which proves the value of the application of the algorithm in exploiting the compressibility of fluids. The dimensionless fitting correlation with greater universality is obtained, which helps to predict the properties of the natural circulation loop with varying temperature differences, friction coefficients, and geometric structures. The research in this paper will lay the foundation for optimizing the system design of the natural circulation loop and improving energy utilization efficiency.

Robot para la educación inclusiva

This study focuses on the design, development and evaluation of an educational mobile robot, called Robot-T2, to be used in educational activities within a technical school. The main objective was to create a versatile platform that allows students to explore programming, engineering and science concepts in a practical and collaborative way. The methodology included an iterative design and testing approach, incorporating feedback from students and teachers to continually improve the functionality of the robot. The tests covered autonomous navigation, line following and object manipulation, using the OnBotJava programming software and the Control-Hub as the main interface. The results demonstrated that the Robot-T2 is highly efficient and adaptable in various educational contexts, showing remarkable precision in navigation and manipulation of objects. The design iterations significantly improved the robot's performance, enriching the educational experience and promoting active learning. In conclusion, educational robotics, represented by the Robot-T2, has great potential to enrich the teaching and learning process in technical schools, promoting teamwork, problem solving and the integration of technology in the classroom. It is hoped that this project will inspire future developments in educational robotics.

The new bridge “Lahnsteg Nauheim”, Wetzlar: slender, elegant, parametrically designed

AbstractThis paper outlines the planning of a bridge in central Germany. Scheduled for construction in mid‐2024, this new bridge is a replacement for a century‐old pedestrian bridge crossing the Lahn river.The proposed bridge will be an airtight‐welded arch bridge, employing steel cross‐sections in both the arch and tension member. Designed as a single‐span, the arches extend 48.0m over the Lahn. The two arches have a flat rise of 4.65m, supporting the roadway through 9 inclined flat steel hangers.This paper delves into the structural engineering aspects, exploring challenges inherent in the design process. An examination of the parametric design process, facilitated through 3‐D modeling in Rhino® and Grasshopper®, will be presented, along with insights into their interface with the finite element modeling software, RFEM®. This process enables an engineering approach to form‐finding and structure optimisation through iterative design checks for various elements and stages of the structural analysis.

The Use of Generative AI to Support Inclusivity and Design Deliberation for Online Instruction

Generative AI presents significant opportunities for instructional designers to revolutionize content creation and personalization in online learning environments. This paper explores how generative AI can streamline content generation processes, enhance adaptability to individual learner needs, and improve feedback mechanisms, ultimately fostering more engaging and inclusive learning experiences. Alongside its benefits, generative AI also poses ethical considerations and potential risks, such as perpetuating biases or disrupting the learning process. Navigating these complexities requires a deliberate approach to design deliberation, that involves careful analysis, discussion, and decision-making throughout the design process. This paper proposes a conceptual framework to support instructional designers in leveraging generative AI to promote inclusivity within their design deliberations, emphasizing the importance of addressing ethical considerations and engaging in iterative design practices.

Surgical instrument tray optimization process at a university hospital: A comprehensive overview

ObjectiveThis study presents the results of a surgical instrument tray optimization process implemented across all surgical specialties within the largest university hospital in Denmark. MethodsData was extracted from a comprehensive instrument optimization process including all Operating Rooms at Aarhus University Hospital. Adopting a holistic perspective, the optimization process, involved aligning instrument trays across various surgical specialties. This included: a) Reduction in number of instruments, b) Consolidation or separation of trays, c) Modularization - introducing modular trays for specific purposes, and d) Standardization - standardizing commonly used instruments across specialties. Instruments per tray, total number of instruments, and changes in the number of trays were compared against existing tray contents to identify discipline-specific changes. ResultsSome specialties made substantial alterations to tray structures, while others primarily reduced number of instruments in existing trays. Across all specialties, optimization resulted in 17 % decrease in number of tray types (p = 0.01, 95%CI:1.0–6.8), 1 % increase in total number of trays (p = 0.36, 95%CI:-11.9–4.8), 18 % decrease in number of instruments per tray (p = 0.0002, 95%CI: 3.2–7.6) and 16 % reduction in total number of instruments for all specialties (p < 0.0001, 95%CI:404–758). ConclusionThis study underscores complexity of instrument tray design. The approach employed at Aarhus University Hospital, involving interdisciplinary experts in an iterative design process, demonstrated the feasibility of redesigning instrument trays with significant reduction in content. Additionally, data suggests that reducing the number of instruments could lead to a decrease in workload within the Central Sterile Supply Specialty. This presents opportunity to minimize wasted resources and streamlining cleaning processes for unused instruments.

Mechanical modeling and parameter analysis of the docking process for probe-drogue docking mechanisms

The on-orbit probe-drogue berthing docking of two spacecraft can effectively reduce impact force and adjust for initial deviations. However, its dynamic response and influence behaviors of design parameters are extremely concerning but difficult to obtain because of its complicated structure. In this paper, a fast mechanical modeling (FMM) method is proposed to obtain the dynamic response of probe-drogue docking mechanisms during spacecraft berthing missions. Regarding the quasi-static docking process, complex dynamic docking behaviors are simplified and decoupled. The FMM method divides docking into three contact processes based on the scene of contact; it analyzes the deviation adaptive docking principle of this type of docking mechanism by establishing the kinematics and mechanics models of active and passive parts. The finite element simulations and experiments of probe-drogue berthing docking were used to compare with the proposed FMM. The comparison results of different initial deviation conditions indicate that the FMM method guarantees computation accuracy and increases computation speed by two orders of magnitude, which greatly reduces computation costs. Then this efficient FMM method was utilized to analyze the influence of key parameters, such as friction coefficient and cone angle, on the contact force and driving force of the docking mechanism. The conclusions of the parameter analysis of probe-drogue berthing docking can be used to reduce contact force and accelerate iterative design as a reference for the design of this kind of docking mechanisms, making the docking process optimized and reliable.

Polycaprolactone-based shape memory foams as self-fitting vaginal stents

There is an urgent critical need for a patient-forward vaginal stent that can prevent debilitating vaginal stenosis that occurs after pelvic radiation treatments and vaginal reconstruction. To this end, we developed a self-fitting vaginal stent based on a shape-memory polymer (SMP) foam that can assume a secondary, compressed shape for ease of deployment. Upon insertion, the change in temperature and hydration initiates foam expansion to shape fit to the individual patient and restore the lumen of the stent to allow egress of vaginal secretions. To achieve rapid actuation at physiological temperature, we investigated the effect of architecture of two photocurable, polycaprolactone (PCL) macromers. Star-PCL-tetraacrylate displayed a reduced melting temperature as compared to a linear-PCL-diacrylate. Upon fabrication into high porosity foams with emulsion-templating, both compositions displayed shape fixity (>90 %) in a crimped, temporary shape. However, only the PCL star-foams displayed shape recovery (∼84 %) at 37 °C with expansion back to its permanent shape. A custom mold and curing system were then used to fabricate the PCL star-foams into hollow, cylindrical stents. The stent was crimped to its temporary insertion shape (50 % reduction in diameter, OD ∼ 11 mm) with a custom radial crimper and displayed excellent shape fixity for deployment (> 95 %) and shape recovery (∼ 100 %). To screen vaginal stents, we developed a custom benchtop pelvic model that simulated vaginal anatomy, temperatures, and pressures with an associated computational model. The crimped SMP vaginal stent was deployed in the model and expanded to walls of the canal (∼70 % increase in cross-sectional area) in less than 5 min after irrigation with warm water. The vaginal stent demonstrated retention of vaginal caliber with less than 10 % decrease in cross-sectional area under physiological pressures. Collectively, this work demonstrates the potential for SMP foams as self-fitting vaginal stents to prevent stenosis and provides new open-source tools for the iterative design of other gynecological devices. Statement of significanceVaginal stenosis, a painful narrowing of the vaginal canal, is a common complication after pelvic radiation therapy or reconstructive surgery. To address this clinical need, we have created a self-fitting vaginal stent from a shape-memory polymer foam. The stent compresses for easy insertion and then expands to adapt to each patient's anatomy to maintain an open vaginal canal and prevent stenosis. This innovative stent provides a patient-friendly solution that could make a significant difference for women undergoing pelvic treatments by reducing pain, aiding recovery, and improving quality of life.

Managing the heat: In-Vessel Components.

The Spherical Tokamak for Energy Production (STEP) programme aims to deliver a first-of-a-kind fusion prototype powerplant (SPP). The SPP plasma places extreme heat, particle and structural loads onto the plasma-facing components (PFCs) of the divertor, limiters and inboard and outboard sections of the first wall. The PFCs must manage the heat and particle loads and wider powerplant requirements relating to safety, net power generation, tritium breeding and plant availability. To enable STEP PFC concepts to be identified that satisfy these wide-ranging requirements, an iterative design ('Decide & Iterate') methodology has been used to synchronize a prioritized set of decisions, within the fast-paced, iterative, whole plant concept design schedule. This paper details the 'Decide and Iterate' methodology and explains how it has enabled the identification of the SPP PFC concepts. These include innovative PFC solutions such as a helium-cooled discrete and panel limiter design to increase tritium breeding while providing sufficient coverage and enabling individual limiter replacement; the integration of the outboard first wall with the breeding zone to enhance fuel self-sufficiency and power generation; and the use of heavy water (D2O) within the inboard first wall and divertor PFCs to increase tritium breeding within the outboard breeding zone. This article is part of the theme issue 'Delivering Fusion Energy - The Spherical Tokamak for Energy Production (STEP)'.

Feasibility study of a telehealth school-based behavioral parent training group program for attention-deficit/hyperactivity disorder.

To evaluate the feasibility and preliminary efficacy of Telehealth Behavioral Parent Training (T-BPT), a school telehealth group intervention for attention-deficit/hyperactivity disorder (ADHD) with a companion training program for school clinicians. T-BPT was developed in an iterative three-phase design in partnership with community stakeholders during the COVID-19 pandemic. School clinicians (N = 4) delivered T-BPT over 8 weeks to parents (N = 21, groups of 5-6 per school) of children (Grades 2-5) with ADHD while simultaneously receiving training and consultation from PhD-level study trainers. A single-arm open trial was used to assess feasibility, engagement, and preliminary efficacy. Parents and school clinicians endorsed high feasibility, acceptability, and usability of T-BPT. Parent attendance was high (M = 94.6%) and a majority of parents (66.7%) attended all eight sessions. Preliminary outcomes indicate moderate to large reductions in parent-reported ADHD symptoms (ω2 = .36), functional and clinical global impairment (ω2s= .21 and .19, respectively), and distance learning challenges (ω2 = .22). Results were in line with in-person delivery, indicating promising feasibility of school telehealth BPT groups. This study also provided further support for the feasibility of the remote training model for school clinicians. Implications of the commonly endorsed barriers and benefits beyond COVID-19 and relevance to under resourced communities are also discussed.