Iterative Design Process Research Articles

LEADing Advance care conversations: Development of an intervention platform

AbstractBackgroundThe LEAD Guide ( Life‐Planning in Early Alzheimer’s Disease; Dassel et al., 2019) addresses changes in cognition and goals of care along the Alzheimer’s disease and related dementias (ADRD) continuum and anticipates the need for surrogate decision‐makers upon loss of the care recipient’s decisional abilities.MethodWe developed a preliminary interactive version of the LEAD Guide, which serves as the foundation of a self‐administered intervention designed to promote and guide community‐based ADRD dyads through a dementia‐focused ACP process. The intervention model includes the LEAD Guide, along with education/information about ACP in the context of ADRD, and interactive instructions. We developed the LEAD Intervention using an iterative design process, which relied on feedback from a 11‐member community advisory board comprised of a clinical dementia specialist, the Director and Program Manager from the State Chapter of the Alzheimer’s Association, and community‐based ADRD dyads. We used Qualtrics, a web‐based survey platform, to simulate the basic functionality and flow of the interactive web‐delivered intervention we envisioned. We then conducted extensive beta‐testing with our community advisory board through written surveys and focus groups.ResultIn general, users were enthusiastic about the LEAD Intervention and appreciated the opportunity to engage in meaningful guided ACP with their family member. Recommended revisions fell into two categories: technological (adding a progress bar, reducing the number of items per page, adding back arrows, reducing text and using more graphics/figures, closed‐captioning, video‐facilitated instructions) and personalization (using piped text that integrates participants’ names into survey items to increase a personal feel, and creating downloadable copies of participants’ LEAD Guide responses).ConclusionThe process of creating a feasible, acceptable, and efficacious intervention requires input from ADRD experts as well as community‐based caregivers and persons with mild ADRD. The iterative process that our research team engaged in with our community advisory board members provided invaluable information on how to create and revise a web‐based ACP intervention platform for community‐based ADRD dyads. We are currently enrolling 60 ADRD dyads in the revised web‐based intervention, with the goal of exploring the impact on relationship quality, decision‐making self‐efficacy, and ACP congruence within participant dyads.

Comparative Study of Conventional and Generative Design Process

Abstract: This study is a comparison of generative design and traditional design process. A generative design process is an iterative design process that uses Artificial Intelligence to generate a range of design solutions that meet the design constraints. In contrast to the conventional design process, which starts with the engineers' expertise, generative design starts with design parameters and employs AI to develop models. The cooperation of generative plans in the production and assembling departments is preferred by significant businesses nowadays. Therefore, our focus will be on generative design's simpler levels to illustrate how boundary conditions and attributes can be changed to show off contemporary applications. Because of the ease of adjustments, stronger resilience, and fewer defects that occur, generative design has shown to be a big improvement in the machine-producing side of the business. However, the creation and design of models are hampered by the additional complexity of structures. The analysis and generative design of a 4-Stroke engine piston are the subjects of this research. The suggested approach is verified using research that closely mimics a prototype used in practice. The examination's goal is to analyze and describe a comparison of two design processes and establish the advantages and disadvantages of each process and let the end user decide which process will be suitable for their applications

Cognitive Bias Modification Training Targeting Fatigue in Patients With Kidney Disease: Usability Study.

Fatigue is an important symptom for many patients, including patients with kidney disease. Cognitive biases, such as attentional bias and self-identity bias, are thought to influence fatigue. Cognitive bias modification (CBM) training is a promising technique to counter fatigue. We aimed to evaluate a CBM training among patients with kidney disease and health care professionals (HCPs) and assess acceptability and applicability in the clinical setting using an iterative design process to evaluate expectations and experiences with the training. This was a longitudinal, qualitative, and multiple stakeholder-perspective usability study in which we interviewed end users and HCPs during the prototyping phase and after the end of training. We conducted semistructured interviews with 29 patients and 16 HCPs. The interviews were transcribed and analyzed thematically. Next to a general evaluation of the training, the acceptability of the training was evaluated using the Theoretical Framework of Acceptability, and applicability was assessed by evaluating obstacles and solutions for implementation in the kidney care setting. Generally, participants were positive about the training and its applicability. The biggest negatives were doubts about effectiveness and annoyance about the repetitive character of CBM. Acceptability was judged with a mixed evaluation, with a negative evaluation of perceived effectiveness; mixed results for burden, intervention coherence, and self-efficacy; and positive results for affective attitude, ethicality, and opportunity costs. Barriers for applicability were patients' varying computer skills, subjectivity of fatigue, and integration with regular treatment (eg, the role of HCPs). Possible solutions included assigning representatives among nurses, offering training on an app, and providing assistance via a help desk. The iterative design process, including repeated waves of testing user expectations and experiences, yielded complementary data. To the best of our knowledge, this study is the first to introduce a CBM training targeting fatigue. Furthermore, this study provides one of the first user evaluations of a CBM training, both among patients with kidney disease and their care providers. Overall, the training was evaluated positively, although acceptability showed mixed results. Applicability was positive although barriers were identified. The proposed solutions require further testing, preferably following the same frameworks, as the iteration in this study contributed positively to the quality of the training. Therefore, future research should follow the same frameworks and consider stakeholders and end users in eHealth intervention design.

Survey Validation for Measuring Perceptions of Work-Related Factors That Influence Career Paths of Men and Women in Academic Anesthesiology.

Women's underrepresentation in positions of leadership in medicine has been attributed to environmental, structural, motivational, and situational factors. The purpose of this study was to design and validate a survey instrument based on these constructs, using a sample of men and women anesthesiologists from 3 urban academic medical centers. Following institutional review board review, survey domains were defined based on a literature review. Items were developed, and content validation was performed by external experts. Anesthesiologists at 3 academic institutions were invited to complete the anonymous survey. Validation measures were performed on the collected responses, including reliability, convergent, and discriminant validity. In addition, differences between men and women respondents were evaluated. Content validation by external experts yielded 38 items with 5-point Likert scales, defining 3 constructs: environmental (14 items), structural (13 items), and motivational (11 items) factors, with single-item measures on situational factors. Content validity indices used Cohen's Kappa coefficients, with 0.85 as the acceptance cutoff. Two hundred seventy-four anesthesiologists in 3 academic institutions received the online survey. One hundred fifteen responses were received (42% response rate), yielding 103 complete survey responses, of which 86 cases included gender. Cronbach's α reliability estimates for the environmental, structural, and motivational scale scores were .88, .84, and .64, respectively, after scale revision. Evidence of convergent (Pearson's r = 0.68; P < .001) and discriminant validity (Pearson's r = 0.017; P = .84) confirmed theoretical expectations. Gender group differences showed statistically significant differences in perceptions toward environmental but not toward structural and motivational factors. The iterative design and validation processes yielded a 3-scale survey instrument with parsimonious item sets. The preliminary evidence of construct validity and reliability fills a gap in the instrumentation literature for assessing gender issues in medicine. Findings were consistent with theoretical expectations. Women are more likely than men to experience challenges in the work environment for career advancement. No differences were found between men and women on perceived resources and overall motivation factors. Investigations should continue with larger and more diverse samples and medical specialties.

Integrated Flight Control System Characterization Approach for Civil High-Speed Vehicles in Conceptual Design

Recent studies have revealed that control surface deflection can cause a reduction in the aerodynamic efficiency of a hypersonic aircraft of up to 30%. In fact, the characterization of the Flight Control System is essential for the estimation of the consistent aerodynamic characteristics of the vehicle in different phases, considering the contribution of control surfaces to stability and trim. In terms of the sizing process, traditional methodologies have been demonstrated to be no longer applicable to estimations of the actuation power required for the control surfaces of a high-speed aircraft, due to their peculiar working conditions and to the characteristics of the flow to which they are exposed. In turn, numerical simulation approaches based on computational fluid dynamics or panel methods may require considerable time resources, which do not fit with the needs of the quick and reliable estimates that are typical of the early design phases. Therefore, this paper is aimed at describing a methodology to show how to anticipate the Flight Control System design for high-speed vehicles at the conceptual design stage, properly considering the interactions at vehicle level and predicting the behavior of the system throughout an entire mission. It is also a core part of the work to provide designers with an example of how neglecting the effect of trim drag can be detrimental to a reliable estimation of overall aircraft performance. The analysis, mainly focused on the longitudinal plane of the vehicle, is presented step-by-step on a specific case study, namely the STRATOFLY MR3 vehicle, a Mach 8 waverider concept for civil antipodal flights. The application of the methodology, conceived as an initial step towards an iterative Flight Control System design process, also shows that the most power-demanding phases are take-off, low supersonic acceleration, and approach, where peaks of over 130 kW are reached, while an average of 20 kW is sufficient to support deflections in a hypersonic cruise.

Designing audit and feedback dashboards for dentists to monitor their opioid prescribing

Background and objectivePrescription drug abuse is a major factor leading to drug overdose deaths in the US and dentists are one of the leading prescribers of opioid pain medication. Knowing that Audit & Feedback (A&F) dashboards are an effective tool and are used as quality improvement interventions, we aimed to develop such dashboards personalized for dental providers which could allow them to monitor their own opioid prescribing performance. MethodsIn this paper we report on the process for designing the A&F dashboards for dentists which were developed by using an iterative human-centered design process. The results obtained from each iteration were used to enrich the information needs analyses, provide function testing, and guide the design decisions of the next iteration. ResultsEngaging dentists in the development and refinement of the dashboards while using the think-aloud protocol for user-testing, provided rapid feedback and identified areas that were confusing and needed either a redesign or additional explanatory content. The final version of dashboards consisted of displaying necessary information through easy to interpret visualizations and interactive features. These included providing access to current national and organizational prescribing guidelines, displaying changes in individual prescribing behavior over time, comparing individual prescribing rate to peer group rate and target rate, displaying procedure specific prescribing, integrating patient reported post-operative dental pain experience and providing navigation and interpretation tips for users. The dashboards were easy to learn and understand for the dentists and were deemed as worth using often in dental practice. ConclusionOur research was able to demonstrate the creation of useful and usable A&F dashboards using data from electronic dental records and patient surveys, for dentists to effectively monitor their opioid prescribing behavior. Efficacy of the dashboards will be tested in future work.

Development of low-cost, weight-adjustable clofazimine mini-tablets for treatment of tuberculosis in pediatrics

Clofazimine (CFZ) is an important component of the World Health Organization's (WHO) recommended all-oral drug regimen for treatment of multi-drug resistant tuberculosis (MDR-TB). However, the lack of a dividable oral dosage form has limited the use of the drug in pediatric populations, who may require lowering of the dose to reduce the likelihood of adverse drug events. In this study, pediatric-friendly CFZ mini-tablets were prepared from micronized powder via direct compression. Rapid disintegration and maximized dissolution in GI fluids was achieved using an iterative formulation design process. Pharmacokinetic (PK) parameters of the optimized mini-tablets were obtained in Sprague-Dawley rats and compared against an oral suspension of micronized CFZ particles to examine the effect of processing and formulation on the oral absorption of the drug. Differences in maximum concentration and area under the curve between the two formulations were non-significant at the highest dosing level tested. Variability between rats prevented bioequivalence from being determined according to guidelines outlined by the Food and Drug Administration (FDA). These studies provide an important proof-of-concept for an alternative, low-cost formulation and processing approach for the oral delivery of CFZ in manner that is suitable for children as young as 6 months of age.

How applicable are attribute-based approaches for human-centered ranking creation?

Item rankings are useful when a decision needs to be made, especially if there are multiple attributes to be considered. However, existing tools do not support both categorical and numerical attributes, require programming expertise for expressing preferences on attributes, do not offer instant feedback, lack flexibility in expressing various types of user preferences, or do not support all mandatory steps in the ranking-creation workflow. In this work, we present RankASco: a human-centered visual analytics approach that supports the interactive and visual creation of rankings. The iterative design process resulted in different visual interfaces that enable users to formalize their preferences based on a taxonomy of attribute scoring functions. RankASco enables broad user groups to (a) select attributes of interest, (b) express preferences on attributes through interactively tailored scoring functions, and (c) analyze and refine item ranking results. We validate RankASco in a user study with 24 participants in comparison to a general purpose tool. We report on commonalities and differences with respect to usefulness and usability and ultimately present three personas that characterize common user behavior in ranking-creation. On the human factors side, we have also identified a series of interesting behavioral variables that have an influence on the task performance and may shape the design of human-centered ranking solutions in the future.

Welcome, How Can I Help You? Design Considerations for a Virtual Reality Environment to Support the Orientation of Online Initial Teacher Education Students

Alongside the rapid and broad uptake of online learning in higher education, fully online students report feeling isolated and disconnected from their institutions. Although formal course content may be expertly designed to engage online learners, much of the information provided to support higher education students’ orientation to the institution and to study is presented online in a written static form. Such presentations may not be accessible and engaging and may contribute to feelings of disconnection. Technologies such as virtual reality (VR) are being used in higher education to engage, motivate and connect students in their learning. This paper reports on the early design stages for a VR that aims to support initial teacher education students to connect and engage with key orienting information. The design of the VR was achieved by following a user-centred, iterative engineering design process and design principles of spatiality, interaction and narrative. The VR environment emulates the School of Education’s physical, on-campus reception area to provide an immersive experience where students have a choice in the types and format of key study information they receive. This experience was designed to be utilised in online orientation but also throughout students’ first year of study. Future research directions include collecting student responses to the VR to inform how students can be involved in enhancing the VR so that it supports their learning and sense of connection. Furthermore, future research can aim for the expansion of the VR inclusive of additional information, rooms and buildings and increased capabilities such as gamification and mobile access. This will enable the creation of a valuable teaching resource for online programs.

Investigating the applicability of human reliability analysis methods during early design stages of non-light-water nuclear power plants

Human interventions are an integral part of any system, whether through design, operation, maintenance, or upgrading. Moreover, although the reliance on human intervention in safety-related actions in advanced reactors (e.g., Generation IV) is expected to be reduced or completely replaced by automated actions, nuclear power plants (NPP) require human actions throughout their lifecycle from design, construction, operation, and decommissioning. Hence, the impacts of all operator actions are required to be captured and incorporated in the probabilistic risk assessment (PRA) of the modeled plant. Furthermore, a risk-informed and performance-based design and licensing approach expects that a PRA model, including human reliability analysis (HRA), is developed starting from the early design stages and used to inform all design iterations. However, due to the lack of details during the early design stages, HRA is often postponed until the design is mature enough. Conducting HRA in the final design stages, though adequate in capturing pre-, at-, and post-initiators, comes short of informing the design itself in the iterative design lifecycle. Moreover, due to most HRA methodologies being developed utilizing mostly the operating experience of existing light water reactors, limited guidance is available to the applicability of different HRA methodologies during the early stages of the design. Limited guidance is available, as well, on how to utilize the results of HRA in informing the design of later iterations. Hence, this study presents an investigation of the applicability of different HRA methodologies during the early stages of the design. The structure of a representative set of nine HRA methodologies is assessed against the available operating and emergency procedures within different design stages. Furthermore, these different HRA methodologies are assessed based on the availability of guidance on how to use their results to risk-inform the design in an iterative design process. Finally, the applicability of Open Preliminary Human Importance (OpenPHI) methodology, introduced specifically to implement HRA during early design stages, is assessed during the early stages of the design and compared against other methodologies.

Systemic Conception of the Data Acquisition of Digital Twin Solutions for Use Case-Oriented Development and Its Application to a Gearbox

Digital Twins are being used more and more frequently and provide information from the Real Twin for different applications. Measurements on the Real Twin are required to obtain information, which in many cases requires the installation of supplementary sensors. For their conception and design, it is particularly important that the measuring principles are selected purposefully and the appropriate sensors are integrated at the goal-oriented measuring positions without impairing the functions and other properties of the Real Twin by the integration of these sensors. In this article, a “Design for Digital Twin” approach is discussed for the systematic procedure and demonstrated using a multi-staged gearbox as a concrete example. The approach focuses on the mechanical and hardware side of the Real Twin. For the systematic conception and design of the Digital Twin solution, an understanding of the stakeholder demands and the expected use cases is necessary. Based on the stakeholder demands and use cases, the relevant product properties can be determined. Using the relevant properties, an iterative process of conception, design, and analysis takes place. The conception is carried out by means of target-oriented cause–effect analyses, taking into account systemic interrelations of the Real Twin components and systematics for the selection of measurement principles. Systemic considerations, combined with an effect graph, allow for the analysis and evaluation of disturbing factors.

Value of cognitive interviewing in the development of the weight stigma in healthcare inventory

BackgroundDespite the detrimental effects of weight stigma in healthcare, there is no widely validated measure comprehensively examining such experiences. ObjectiveWe aimed to develop and pilot test an inventory to measure patient experiences of weight stigma in healthcare, and to ensure our items were easily understood. Patient involvementDuring our iterative design process, patients assessed whether our inventory items were easy to understand and we included an open-ended comments question. MethodsWe compiled items from pre-existing tools assessing experiences of weight stigma in healthcare, and developed our own novel items. We conducted field pre-testing with a convenience sample of 48 patients at a Midwest academic internal medicine clinic. We utilized an iterative design process whereby respondents provided feedback on our inventory, we analyzed the data and made revisions, and then repeated the cycle. ResultsRespondents found some of the language in our items confusing; expressed reluctance to speculate on the motivations of healthcare providers; had difficulty with “double-barreled” questions; found some questions vague; and expressed the desire to have weight addressed in clinical encounters neither too much nor too infrequently. We altered items appropriately, and in subsequent rounds of data collection they were easier to understand. DiscussionPatients found many common weight stigma survey items and some of our novel items confusing. Our modified inventory reduces patient confusion and enhances data quality. Practical valueOur study demonstrates the value of cognitive interviewing. Furthermore, the WSHCI will be a useful tool for clinicians and research teams seeking to measure weight stigma in healthcare but first needs to be validated in a larger sample. FundingThis study was supported by the Physician Scientist Training Program, Diabetes Center T32 (DK112751), and the Clinical and Translational Science Award grant funded from the National Institutes of Health (UL1TR002537).

Reflect–Express–Transform: Investigating Speech-Based Iterative Digital Design for Young Designers

Abstract We investigate speech-based input as a means to enable reflective thinking for younger individuals (middle- and high-school students) during design iterations. Verbalization offers a unique way to externalize ideas in early design and could therefore lead to new pathways for exploration and iteration, especially for K-12 students who possess the creative potential but are not technically trained in the design process. Interactive design systems, however, by-and-large utilize sketching, multitouch, and gestural inputs. As a result, (1) there is little know-how regarding how to operationalize verbal inputs as a meaningful way to facilitate idea exploration and (2) there is little fundamental understanding of the underlying cognitive mechanisms for iteration through verbal communication. We take the initial steps toward these gaps by first designing and implementing the ShapOrator interface that takes verbal descriptions of geometric parameters (shape, size, instances) in a semi-natural language form and determines the appropriate transformations to a given design artifact modeled as a shape assembly. By using ShapOrator as our experimental setup, we conducted an in-depth observational study on ten middle- and high-school students tasked with designing spaceships. Our study revealed that participants were able to create a variety of designs while associating functional and topical contexts to their spaceships throughout the design iteration process.

A Design-Led Theory of Change for a Mobile Game App (Go Nisha Go) for Adolescent Girls in India: Multimix Methodology Study

India has one of the largest adolescent populations in the world. Yet adolescents, particularly adolescent girls, have limited access to correct sexual and reproductive health information and services. The context in which adolescent girls live is one of gender inequity where they contend with early marriage and early pregnancy and have few opportunities for quality education and labor force participation. The digital revolution has expanded the penetration of mobile phones across India, increasingly being used by adolescent girls. Health interventions are also moving onto digital platforms. Evidence has shown that applications of game elements and game-based learning can be powerful tools in behavior change and health interventions. This provides a unique opportunity, particularly for the private sector, to reach and empower adolescent girls directly with information, products, and services in a private and fun manner. The objective of this paper is to describe how a design-led Theory of Change (ToC) was formulated for a mobile game app that is not only underpinned by theories of various behavior change models but also identifies variables and triggers for in-game behavioral intentions that can be tracked and measured within the game and validated through a rigorous post-gameplay outcome evaluation. We describe the use of a multimix methodology to formulate a ToC informing behavioral frameworks and co-design approaches in our proof-of-concept product development journey. This process created a statement of hypothesis and "pathways to impact" with a continuous, cumulative, and iterative design process that included key stakeholders in the production of a smartphone app. With theoretical underpinnings of social behavior and modeling frameworks, systematic research, and other creative methods, we developed a design-led ToC pathway that can delineate complex and multidisciplinary outputs for measuring impact. The statement of hypothesis that emerged posits that "If girls virtually experience the outcomes of choices that they make for their avatar in the mobile game, then they can make informed decisions that direct the course of their own life." Four learning pathways (DISCOVER, PLAY, DECIDE, and ACT) are scaffolded on 3 pillars of evidence, engagement, and evaluation to support the ToC-led framework. It informs decision-making and life outcomes through game-based objectives and in-game triggers that offer direct access to information, products, and services. This approach of using a multimix methodology for identifying varied and multidisciplinary pathways to change is of particular interest to measuring the impact of innovations, especially digital products, that do not necessarily conform with traditional behavioral change models or standard co-design approaches. We also explain the benefits of using iterative and cumulative inputs to integrate ongoing user feedback, while identifying pathways to various impacts, and not limiting it to only the design and development phase.

Ductility-strength and strength-ductility relations for a constant yield displacement seismic design procedure

The modern engineering approach to design of structures exposed to rare but intense earthquakes allows for their inelastic response. Models and tools to rapidly but accurately assess the extent of the inelastic response of the structure and control its performance are, therefore, essential. We develop a closed-form upmu -R^{*}-S_{d,y} relation between the ductility upmu and the strength reduction factor R*, as well as its approximate inverse R*-upmu -Sd,y relation, both functions of the SDOF oscillator yield displacement Sd,y, not its vibration period T. The fundamental vibration period of the structure varies during the iterative design process focused on modifying its strength. However, the yield displacement of the structure is practically invariant with respect to the strength of the structure, as it depends primarily on its geometry and material properties. We use these relations to formulate a constant yield displacement seismic design procedure and exemplify it. Noting the structure of the developed relations, we use dimensional analysis to formulate a version of the ductility-strength and strength-ductility relations that are dimensionless and independent of the seismic hazard intensity. These novel, dimensionless master relations are the upmu -R*-H/B-upkappa ductility-strength and the R*-upmu -H/B-upkappa strength-ductility relations.

Designing Virtual Natural Environments for Older Adults: Think-Aloud Study

Spending time in natural environments is beneficial for human health, but many older adults have limited or no access to natural environments. Virtual reality technology may be a means to facilitate nature experiences, and so, there is a need for knowledge on how to design virtual restorative natural environments for older adults. The aim of this study was to identify, implement, and test older adults' preferences and ideas regarding virtual natural environments. A total of 14 older adults (mean age 75, SD 5.9 years) participated in an iterative process to design such an environment. We used think-aloud protocols and qualitative content analysis and established questionnaires that targeted usability, affective aspects, and side effects. These data guided the design decisions for incremental implementations of a prototype. The participants' preferences included trueness to reality in terms of rendition and behavior; traces of human activity and natural processes that trigger the imagination and provide believability; the ability to roam, explore, and interact with the environment; and a familiar, relatable environment that evokes memories. The iterative design process resulted in a prototype featuring many of the participants' ideas and preferences, including a seated locomotion technique, animals, a boat ride, the discovery of a boat wreck, and apple picking. The questionnaire results indicated high perceived usability, interest, and enjoyment; low pressure and tension; moderate value and usefulness; and negligible side effects. We suggested 3 principles for virtual natural environments for older adults: realness, interactivity, and relatedness. Virtual natural environments should also provide a diversity of content and activities to accommodate the heterogeneity in older adults' preferences. These results can contribute to a framework for designing virtual natural environments for older adults. However, these findings need to be tested and potentially revised in future studies.

The Development of a Hypertension Prevention and Financial-Incentive mHealth Program Using a "No-Code" Mobile App Builder: Development and Usability Study.

Regular physical activity (PA) is a key lifestyle component for hypertension prevention. Previous studies have shown that mobile health (mHealth) apps can be an effective tool for improving PA behaviors. However, adherence to and poor engagement with these apps is a challenge. A potential solution to overcome this challenge may be to combine financial incentives with innovative behavior theory, such as the Multiprocess Action Control (M-PAC) framework. Currently, there is a lack of PA financial incentive-driven M-PAC mHealth programs aimed at hypertension prevention. We aimed to describe the process of developing an 8-week mHealth PA and financial-incentive hypertension education program (Healthy Hearts) and to evaluate usability of the Healthy Hearts program. The first 2 stages of the Integrate, Design, Assess, and Share framework were used to guide the development of the Healthy Hearts program. The development process consisted of 2 phases. In phase 1, the research team met to discuss implementing the M-PAC framework to adopt an existing web-based hypertension prevention program to a mobile app. The app was developed using a no-code app development platform, Pathverse (Pathverse Inc), to help decrease overall development time. In phase 2, we created a prototype and conducted usability testing to evaluate lesson 1 of the Healthy Hearts program to further enhance the user experience. We used semistructured interviews and the mHealth App Usability Questionnaire to evaluate program acceptability and usability. Intervention development among the research team successfully created an 8-week financial-incentive hypertension education program for adults aged 40-65 years who did not currently meet the Canadian Physical Activity Guidelines (<150 minutes of moderate to vigorous PA per week). This program lasted 8 weeks and comprised 25 lessons guided by the M-PAC framework. The program used various behavior change techniques to further support PA adherence. Usability testing of the first lesson was successful, with 6 participants recruited for 2 rounds of testing. Feedback was gathered to enhance the content, layout, and design of the Healthy Hearts program to prepare the mHealth program for feasibility testing. Results of round 1 of usability testing suggested that the content delivered in the lessons was long. Therefore, the content was divided into multiple lessons before round 2 of usability testing, where feedback was only on design preferences. A minimum viable product was created with these results. The iterative development process and the usability assessments suggested by the Integrate, Design, Assess, and Share framework enabled participants to provide valuable feedback on the content, design, and layout of the program before advancing to feasibility testing. Furthermore, the use of the "no-code" app development tool enabled our team to rapidly make changes to the app based on user feedback during the iterative design process.

Abstract 5355: Elraglusib response prediction and mechanistic discovery using iterative machine learning

Abstract Elraglusib is a selective GSK-3 inhibitor that has activity on a broad array of neoplasms as well as their immune microenvironment. However the determinants of tumor response have not been elucidated. Here, we use genomic panels of cancer driver genes to predict patient response to elraglusib therapy as measured by RECIST criteria. Patient response in the Phase I 1801 trial (NCT03678883) was matched to genomic data from patient tumors, with 80 cases used to train Machine Learning models and 26 cases reserved as a test set for model evaluation. When predicting response from mutation status alone our models reached a modest accuracy of 65% in the test set, which we attributed to the sparsity of genomic data. To remedy this, we engineered pathway-based features to provide combinatorial information while ensuring feature stability. To select the optimal combination of features, we designed an iterative design process that first randomized feature combinations and then created refined models from the highest performing pathway features. This resulted in several final models with greater than 88% accuracy. We retained several models of similar accuracy to more comprehensively identify potential biomarkers and combinatorial relationships. These models were then interpreted using SHapley Additive exPlanations (SHAP) where we were able to identify highly predictive features for both the entire pan-cancer cohort and specific histologies. We found the feature constructed from the Reactome pathway “Chromatin Modifying Enzymes” frequently occurred in high performing models with a high-ranking SHAP value. This feature included genes such as SMARCA4, HDAC2, and KDM5A, and was negatively associated with patient response. Another frequently observed high-ranking pathway feature with a negative response association was based on the “Innate Immune System” Reactome pathway. Many of the features highlighted in our models were negatively associated with elraglusib response and thus could be general markers of poor prognosis. To address this, we altered our pipeline to test only positively associated features which substantially reduced our feature pool to only 285 features but still produced models with accuracies of up to 81%. Analysis of key features used by these models identified several positive markers of elraglusib including mutations in the POLE gene, which previously has been linked to DNA-damage response deficiency and anti-tumor immune response. In sum, we forecast elraglusib response for a variety of tumor histologies and simultaneously reveal potential mechanisms of elraglusib sensitivity and biological action. In future work we will investigate the utility of using POLE and other identified biomarker candidates to predict the likelihood of patient response to elraglusib, as well as whether our machine learning models will be an effective tool to guide patient stratification. Citation Format: Joseph McDermott, Taylor Weiskittel, Daniel Billadeau, Benedito Carneiro, Hu Li, Andrew Mazar. Elraglusib response prediction and mechanistic discovery using iterative machine learning. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5355.

Enhancement of Grid and Face Element Amendment in Aeroelasticity Analysis by Advanced Self-Adaptive Computing Method

This research presents a novel approach for enhancing the accuracy and efficiency of aeroelasticity analysis through the combination of grid optimization and face element amendment techniques. The study focuses on improving the precision of a low order panel method by performing piecewise linear amendment based on Computational Fluid Dynamics (CFD) aerodynamic loads data under varying angles of attack. Additionally, the distribution of face element calculating grid is optimized using visual evoked potential estimation. The proposed method addresses the limitations of traditional panel methods that heavily rely on grid distribution and offers a more robust and accurate solution. The optimized grid not only maintains the computational efficiency of the panel method but also ensures closer approximation of wing stresses to CFD data, thus enhancing the precision and efficiency of aeroelasticity optimized iterative design processes. The results obtained from this research demonstrate effective compensation for the shortcomings of the panel method and a significant improvement in the computational efficiency of aerodynamic loading in the presence of changing structural stiff parameters.

Development of a Digital Program for Training Community Health Workers in the Detection and Referral of Schizophrenia in Rural India.

This study aimed to develop and assess the acceptability of a digital program for training community health workers (CHWs) in the detection and referral of patients with schizophrenia in community settings in rural India. An iterative design process was employed. First, evidence-based content from existing community programs for schizophrenia care was incorporated into the curriculum, and reviewed by experts to ensure clinical utility and fidelity of the adapted content. Second, CHWs provided feedback on the appropriateness of language, content, and an initial prototype of the digital training program to ensure relevance for the local context. Focus group discussions were then used to understand the acceptability of the digital training prototype and to inform modifications to the design and layout. Qualitative data was analysed using a rapid thematic analysis approach based on predetermined topics pertaining to acceptability of the training content and digital platform. Development of the initial prototype involved content review by 13 subject matter experts with clinical expertise or experience accessing and receiving mental health services, and engagement of 23 CHWs, of which 11 provided feedback for contextualization of the training content and 12 participated in focus group discussions on the acceptability of the prototype. Additionally, 2 service-users with lived experience of schizophrenia contributed to initial testing of the digital training prototype and offered feedback in a focus group discussion. During contextualization of the training content, key feedback pertained to simplifying the language and presentation of the content by removing technical terms and including interactive content and images to enhance interest and engagement with the digital training. During prototype testing, CHWs shared their familiarity with similar symptoms but were unaware of schizophrenia as a treatable illness. They shared that training can help them identify symptoms of schizophrenia and connect patients with specialized care. They were also able to understand misconceptions and discrimination towards people with schizophrenia, and how to address these challenges by supporting others and spreading awareness in their communities. Participants also appreciated the digital training, as it could save them time and could be incorporated within their routine work. This study shows the acceptability of leveraging digital technology for building capacity of CHWs to support early detection and referral of schizophrenia in community settings in rural India. These findings can inform the subsequent evaluation of this digital training program to determine its impact on enhancing the knowledge and skills of CHWs.