Subject Matter Experts Research Articles

Potential errors during final inspection and certification process of an aircraft component

Purpose According to regulations, aircraft must be in an airworthy condition before they can be operated. To ensure airworthiness, they must be maintained by an approved component maintenance organisation. This study is aimed to identify potential errors that may arise during the final inspection and certification process of aircraft components, categorise them, determine their consequences and quantify the associated risks. Any removed aircraft components must be sent to an approved aircraft component maintenance organisation for further maintenance and issuance of European Union Aviation Safety Agency (EASA) Form 1. Thereafter, a final inspection and certification process must be conducted by certifying staff to receive an EASA Form 1. This process is crucial because any errors during this stage can result in the installation of unsafe components in an aircraft. Design/methodology/approach The Systematic Human Error Reduction and Prediction Approach (SHERPA) method was used to identify potential errors. This method involved a review of the procedures of three maintenance organisations, individual interviews with ten subject matter experts and a consensus group of 14 certifying staff from different maintenance organisations to achieve the desired results. Findings In this study, 39 potential errors were identified during the final inspection and certification process. Furthermore, analysis revealed that 48.7% of these issues were attributed to checking errors, making it the most common type of error observed. Originality/value This study pinpoints the potential errors in the final inspection and certification of aircraft components. It offers maintenance organisations a roadmap to assess procedures, implement preventive measures and reduce the likelihood of these errors.

Decentralising Climate Governance in the Global South: Lessons from Itezhi-Tezhi and the Kafue Wetlands, Zambia

This article discusses the challenges of decentralising climate governance in the Global South in the context of intensifying climate change. Using qualitative methods of data collection and analysis, we interviewed a total of 112 participants who participated in the study, including traditional leaders, ward councillors, subject-matter experts, government officials and members of the public who took part in focus group discussions. Our results show that devolution, delegation, deconcentration and privatisation have been used as strategies for decentralising climate action in the Itezhi-Tezhi District. However, these methods of decentralisation are affected by several factors, including unclear rules for elected and appointed leaders, which influence the devolution of decision-making responsibilities at the local government level. Regarding delegation, decentralising climate governance is affected by inadequate public participation, particularly in the design and execution of climate initiatives in the Kafue wetlands. Furthermore, this article shows that deconcentration is likely to affect climate governance because the national government has not deconcentrated the units for climate governance from the line ministry to the local authority. Privatisation, which has been an effective way of decentralising climate governance in the Kafue wetlands, has also been problematic due to inadequate community participation. These challenges and opportunities serve as lessons for building resilience in effective decentralised climate governance in the Kafue wetlands. This article adds to the ongoing discourse on the efficacy of decentralising climate governance in the Global South and offers valuable insights for future research in this genre of academic inquiry in Sub-Saharan Africa.

When employees understate their stress: defensive biasing in work stress surveys

PurposeThe purpose of this study is to investigate the phenomenon of defensive biasing in work stress surveys, which occurs when employees trivialize potential stressors and strains due to fear of negative consequences from their supervisors or management. This study aims to better understand the factors that influence this behavior and to develop a scale to measure it.Design/methodology/approachThe study used an online survey of 200 employees to investigate the factors influencing defensive biasing behavior. The researchers developed a scale for defensive biasing with the help of subject matter experts and derived possible factors from the literature. Participants were presented with a hypothetical scenario in which they imagined a work stress survey in their organization and were asked to answer related items. The data were analyzed using regression analysis.FindingsThe study found that defensive biasing behavior was significantly predicted by perceived anonymity and neuroticism. Participants who felt less anonymous and had higher levels of neuroticism were more likely to engage in defensive biasing. Job insecurity and trust in supervisors were not found to be significant predictors of defensive biasing.Originality/valueThis study contributes to the literature on work stress surveys by developing a scale for defensive biasing and investigating the factors that influence this behavior. The study highlights the importance of making the survey process more transparent to reduce defensive biasing and obtain trustworthy results.

Design of a Self-Measuring Device Based on Bioelectrical Impedance Analysis for Regular Monitoring of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic disease, in which permanent joint deformation is largely preventable with the timely introduction of appropriate treatment strategies. However, there is no consensus for patients with RA to monitor their progress and communicate it to the rheumatologist till the condition progresses to remission. In response to this unmet need, we proposed the design of a self-measuring device based on bioelectrical impedance analysis (BIA) for regular monitoring of inflammation levels. Twenty joints of both hands were measured to monitor trends in inflammation levels. Three electrodes were used to measure two joints of each finger. A central electrode was used for two consecutive measurements. A suitable form factor for the device was proposed for the vertical placement of the hand. To ensure the stability of measurements, an air cushion was incorporated into the back of the hand, hand containers were designed on both sides, and a mobile application was designed. We conducted a convergence-assessment experiment with five air pressures to validate the consistency and convergence of bioimpedance measurements. A heuristic evaluation of the usability around the product and mobile application was conducted in parallel by six subject matter experts and validated the design. This study underscores the significance of considering patients’ disease activity during intervals between hospital visits and introduces a novel approach to self-RA care.

Using Regularized Methods to Validate Q-Matrix in Cognitive Diagnostic Assessment

One of the central components of cognitive diagnostic assessment is the Q-matrix, which is an essential loading indicator matrix and is typically constructed by subject matter experts. Nonetheless, to a large extent, the construction of Q-matrix remains a subjective process and might lead to misspecifications. Many researchers have recognized the importance of estimating or validating the Q-matrix, but most of them focus on the conditions of relatively large sample sizes. This article aims to explore Q-matrix validation possibilities under small sample conditions and uses regularized methods to validate the Q-matrix based on the compensatory reparametrized unified model and generalized deterministic inputs, noisy “and” gate models. Simulation studies were conducted to evaluate the viability of the modified least absolute shrinkage and selection operator (Lasso) and modified smoothly clipped absolute deviation (SCAD) methods, comparing them with existing methods. Results show that the modified Lasso and the modified SCAD methods outperform the stepwise, Hull, and MLR-B methods in general, especially under the conditions of small sample sizes. While good recovery in all small sample size conditions is not guaranteed, the modified methods demonstrate advantages across various item quality conditions. Also, a real data set is analyzed to illustrate the application of the modified methods.

Tailored Incident Investigation Protocols: A Critically Needed Practice

Construction scholars and practitioners have identified a repetitive pattern of direct causes leading to both fatal and non-fatal injuries among construction workers. Over the years, direct causes such as falls, electrocutions, and being struck have consistently represented a substantial proportion of recorded and reported injuries in the United States. One potential factor contributing to this repetition is the absence of root cause investigations for incidents. Incident investigations should focus on system deficiencies and shortcomings instead of individual behaviors. While the identification of incident root causes provides the needed information to eliminate the direct causes, it is inherently complex. Recently, the use of tailored incident investigation protocols as a practical and systematically conducted method was suggested to uncover the root causes of incidents, subsequently assisting in reducing their recurrence. To illustrate the feasibility of such an approach, this article provides a step-by-step guide to creating a tailored investigation protocol for revealing the root causes of arc flash incidents by utilizing a panel of safety experts. In addition, this study demonstrates the feasibility of developing tailored investigation protocols for other common causes, such as falls and electrocutions. Tailored investigation protocols streamline the identification of potential root causes to a manageable number, relying on subject matter experts. Consequently, they enhance learning from incidents by mitigating investigators’ biases and potential lack of experience. Safety practitioners can use the method presented in this article to create tailored investigation protocols based on their working environment to improve learning for occupational injuries.

Predictive Ppk calculations for biologics and vaccines using a Bayesian approach - a tutorial.

In pharmaceutical manufacturing, especially biologics and vaccines manufacturing, emphasis on speedy process development can lead to inadequate process development, which often results in less robust commercial manufacturing process after launch. Process performance index (Ppk) is a statistical measurement of the ability of a process to produce output within specification limits over a period of time. In biopharmaceutical manufacturing, progression in process development is based on Critical Quality Attributes meeting their specification limits, lacking insight into the process robustness. Ppk is typically estimated after 15-30 commercial batches at which point it may be too late/too complex to make process adjustments to enhance robustness. The use of Bayesian statistics, prior knowledge, and input from Subject matter experts (SMEs) offers an opportunity to make predictions on process capability during the development cycle. Developing a standard methodology to assess long term process capability at various stages of development provides several benefits: provides opportunity for early insight into process vulnerabilities thereby enabling resolution pre-licensure; identifies area of the process to prioritize and focus on during process development/process characterization (PC) using a data-driven approach; and ultimately results in higher process robustness/process knowledge at launch. We propose a Bayesian-based method to predict the performance of a manufacturing process at full manufacturing scale during the development and commercialization phase, before commercial data exists. Under Bayesian framework, limited development data for the process of interest at hand, data from similar products, general SME knowledge, and literature can be carefully formulated into informative priors. The implementation of the proposed approach is presented through two examples. To allow for continuous improvement during process development, we recommend to embed this approach of using predictive Ppk at pre-defined commercialization stage-gates, for example, at completion of process development, prior to and completion of PC, prior to technology transfer runs (Engineering/Process Performance Qualification, PPQ), and prior to commercial specification setting.

A job task analysis of the authorised firearms officer - counter terrorism (AFO-CT) national role profile.

The Ministry of Defence Police recognised the requirement to develop a Physical Employment Standard (PES) for the Authorised Firearms Officer -Counter Terrorism (AFO-CT) role profile. The purpose of this study was to conduct a job task analysis to identify the most critical and physically demanding tasks performed by AFO-CT personnel. A focus group and online survey were undertaken to identify a list of job tasks. The down-selected job tasks were objectively monitored during training events to determine the most physically demanding tasks. Tasks were ranked by physical demand and additional factors (e.g., operational load, primary physical actions). Down-selected tasks were then included in a Subject Matter Experts (SME) task scenario generation workshop. The physiological demands of the resulting standardised scenarios were determined. The focus group (n = 11) identified 13 physically demanding and critical role-related tasks. The subsequent survey (n = 907) down-selected eight tasks with a 'moderate' demand or greater. Thirty AFO-CT personnel completed the eight tasks as part of routine training events. From the observed tasks, four tasks were down-selected and combined into two operationally relevant, reasonable worst-case standardised scenarios during a SME workshop. The two scenarios, 'Conduct Armed Search in the Open for an Active Shooter' and 'Victim Focussed Emergency Search' were used in subsequent phases of the research to form the basis of the AFO-CT PES. This research elucidated the most physically demanding job tasks within the AFO-CT role profile to inform the development of a MOD armed policing PES.

Analyzing Patterns of Service Utilization Using Graph Topology to Understand the Dynamic of the Engagement of Patients with Complex Problems with Health Services

Background: Providing care to persons with complex problems is inherently difficult due to several factors, including the impacts of proximal determinants of health, treatment response, the natural emergence of comorbidities, and service system capacity to provide timely required services. Providing visibility into the dynamics of patients’ engagement can help to optimize care for patients with complex problems. Method: In a previous work, graph machine learning and NLP methods were used to model the products of service system dynamics as atemporal entities, using a data model that collapsed patient encounter events across time. In this paper, the order of events is put back into the data model to provide topological depictions of the dynamics that are embodied in patients’ movement across a complex healthcare system. Result: The results show that directed graphs are well suited to the task of depicting the way that the diverse components of the system are functionally coupled—or remain disconnected—by patient journeys. Conclusion: By setting the resolution on the graph topology visualization, important characteristics can be highlighted, including highly prevalent repeating sequences of service events readily interpretable by clinical subject matter experts. Moreover, this methodology provides a first step in addressing the challenge of locating potential operational problems for patients with complex issues engaging with a complex healthcare service system.

PRODUCT INNOVATION, MARKETING INNOVATION AND BUSINESS PERFORMANCE RELATIONSHIP OF MALAYSIAN PRODUCT INDUSTRIES: MEDIATING EFFECT OF DESIGN MANAGEMENT

Due to the increasing significance of design management and innovation to business performance, it is critical for the product sectors to stay up with the world's rapid changes in economic model and technology. As a result, industrialized countries regard design management as a competency that falls under the umbrella of innovation management. The objectives of this study are to identify the relationship between product innovation and marketing innovation on the business performance of Malaysian product industries, to analyze the effect of product innovation and marketing innovation on design management of Malaysian product industries, to examine the effect of design management on the business performance of Malaysian product industries and to test the mediating effect of design management between innovation and marketing innovation. This study uses a mixed method of qualitative and quantitative research design to collect data from 386 respondents from Malaysia's product industries. Simple random sampling was utilized to acquire the required data using a verified questionnaire. Furthermore, the qualitative survey data was analyzed using the Partial Least Square Structural Equation Model (SmartPLS3-SEM) in early phase as back data for qualitative method and for qualitative concerns, the researcher is using Likert scale form for subject matter expert to validate the gathered data with the hypothesis based on the findings of this study to check on the validity of the data gathered. In accordance to this research, the researcher defines “Malaysian Product Industries” as a group of small and medium enterprises in the services, primary agriculture and Information & Communication Technology (ICT) sectors that are enterprises and private company with full-time employees not exceeding 50 or with annual sales turnover not exceeding RM5 million. This study presents empirical evidence that the effect of design management on the relationship between innovation types and business success in Malaysia's product industries could lead to increased company performance. This research could assist the product industries better their businesses by identifying critical factors that contribute to greater business performance.

Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study.

Real-time surveillance of emerging infectious diseases necessitates a dynamically evolving, computable case definition, which frequently incorporates symptom-related criteria. For symptom detection, both population health monitoring platforms and research initiatives primarily depend on structured data extracted from electronic health records. This study sought to validate and test an artificial intelligence (AI)-based natural language processing (NLP) pipeline for detecting COVID-19 symptoms from physician notes in pediatric patients. We specifically study patients presenting to the emergency department (ED) who can be sentinel cases in an outbreak. Subjects in this retrospective cohort study are patients who are 21 years of age and younger, who presented to a pediatric ED at a large academic children's hospital between March 1, 2020, and May 31, 2022. The ED notes for all patients were processed with an NLP pipeline tuned to detect the mention of 11 COVID-19 symptoms based on Centers for Disease Control and Prevention (CDC) criteria. For a gold standard, 3 subject matter experts labeled 226 ED notes and had strong agreement (F1-score=0.986; positive predictive value [PPV]=0.972; and sensitivity=1.0). F1-score, PPV, and sensitivity were used to compare the performance of both NLP and the International Classification of Diseases, 10th Revision (ICD-10) coding to the gold standard chart review. As a formative use case, variations in symptom patterns were measured across SARS-CoV-2 variant eras. There were 85,678 ED encounters during the study period, including 4% (n=3420) with patients with COVID-19. NLP was more accurate at identifying encounters with patients that had any of the COVID-19 symptoms (F1-score=0.796) than ICD-10 codes (F1-score =0.451). NLP accuracy was higher for positive symptoms (sensitivity=0.930) than ICD-10 (sensitivity=0.300). However, ICD-10 accuracy was higher for negative symptoms (specificity=0.994) than NLP (specificity=0.917). Congestion or runny nose showed the highest accuracy difference (NLP: F1-score=0.828 and ICD-10: F1-score=0.042). For encounters with patients with COVID-19, prevalence estimates of each NLP symptom differed across variant eras. Patients with COVID-19 were more likely to have each NLP symptom detected than patients without this disease. Effect sizes (odds ratios) varied across pandemic eras. This study establishes the value of AI-based NLP as a highly effective tool for real-time COVID-19 symptom detection in pediatric patients, outperforming traditional ICD-10 methods. It also reveals the evolving nature of symptom prevalence across different virus variants, underscoring the need for dynamic, technology-driven approaches in infectious disease surveillance.

Enhancing graduate employability – exploring the influence of experiential simulation learning on life skill development

ABSTRACT Skills and knowledge which increase the likelihood of university graduates finding employment is an increasingly important factor for higher education institutions. Even though subject matter expertise remains a primary objective, supporting students to build life skills that are desired by employers is essential to enhance graduate employability. Firstly, we draw on consultive interviews with 11 graduate recruiters to build a life skill ability scale. Through these interviews, we identify two constructs worth measuring (resilience and adaptability) not yet represented in extant life skill ability scales. Thereby contributing to life skills measures and their link to graduate employability. Secondly, this paper explores the influence of a team-based business simulation on the development of life skills at two higher education institutions in the UK for first- and fourth-year undergraduate students. Through a pre-survey and post-survey, this paper empirically finds that experiential learning by means of a team-based business simulation has an overwhelmingly positive influence on first-year students’ self-assessed life skill development as well as their course-specific subject matter expertise. Yet, the findings show less significant results for fourth-year students. This contributes to our understanding of business simulations as a pedagogical practice and its benefits for students beyond their education.

Pengembangan Multimedia Interaktif Berbasis Model Drill and Practice Materi Operasi Hitung Penjumlahan dan Pengurangan Bilangan Cacah Kelas IV SDN 4 Nyalian

This research aims to describe the design, determine the feasibility of interactive multimedia based on the drill and practice model, and determine the effectiveness of interactive multimedia based on the drill and practice model. The product was tested by 1 subject matter expert, 1 instructional design expert, 1 learning media design expert, as well as research subjects with 3 students in individual trials, 12 students in small group trials, and effectiveness testing using 21 students. The research model used is the ADDIE model (Analyze, Design, Development, Implementation, Evaluation). This development research uses data collection methods by observation, interviews, questionnaires and tests. The data analysis techniques used are qualitative descriptive analysis, quantitative descriptive analysis and inferential statistics. The research results obtained were (1) Interactive multimedia design using the ADDIE development model, (2) the quality of interactive multimedia by subject matter content expert testing obtained a result of 89.58% in the good category, the instructional design expert test obtained a result of 91% in the very category. good, learning media design expert tests obtained 90% results in the very good category, individual trials obtained 87.89% results in the good category, and small group trials obtained 88.85% results in the good category, (3) effectiveness of interactive multimedia Based on the results of the t-test, tcount is 5.288 and ttable is 2.085, meaning tcount > ttable, so H0 is rejected and Ha is accepted. Thus, the results of this research show that Interactive Multimedia Based on the Drill and Practice Model is feasible and effective to apply for class IV Semester I in the material of arithmetic operations for addition and subtraction of whole numbers up to 1,000.

Outcomes of total hip arthroplasty using collared versus collarless uncemented HA-coated stems: a meta-analysis.

to systematically review comparative studies reporting revision rates, clinical outcomes, or radiographic outcomes of total hip arthroplasty (THA) using collared versus collarless conventional-length uncemented hydroxyapatite (HA)-coated stems. In adherence with PRISMA guidelines, a literature search was performed on Medline, Embase, and Scopus. Comparative clinical studies were eligible if they reported outcomes of collared versus collarless uncemented HA-coated stems for primary THA. Two reviewers screened titles, abstracts, and full-texts to determine eligibility; then performed data extraction; and assessed the quality of studies according to Joanna Briggs Institute (JBI) checklist. The search returned 972 records, 486 were duplicates, and 479 were excluded after title/abstract/full-text screening. Three further studies were included from the references of eligible studies and from discussions with subject matter experts, resulting in 11 included studies. The JBI checklist indicated six studies scored ≥7 points and four studies ≥4 points. Pooled data revealed collared stems had significantly lower revision rates (OR = 0.45; 95% CI = 0.31-0.64) and subsidence (MD = -1 mm; 95% CI = -1.6--0.3), but no significant difference in intraoperative complication rates (OR = 0.94; 95% CI = 0.67-1.32) in the short term to mid-term. Unpooled data indicated that collared stems provide equivalent survival, equivalent or better outcomes, and equivalent or lower complication rates. In comparative studies, collared stems have lower revision rates than collarless stems, as well as equivalent or better clinical and radiographic outcomes. Differences could be due to a protective effect that the collar offers against subsidence, particularly in undersized or misaligned stems. Further studies are warranted to confirm long-term results and better understand differences between registry data and clinical studies.

Development of Canva-Based Interactive Teaching Materials to Enhance Students' Critical Thinking Skills in Fiqh Learning at Islamic High School

This project aims to promote critical thinking abilities among eleventh-grade students in the Social Sciences curriculum at MAN 1 Medan during Fiqh (Islamic Jurisprudence) studying, leveraging interactive teaching materials based on Canva that have been designed. This research uses Research and Development (R&D). The 4-D research design, which consists of four stages—define, design, develop, and disseminate—is used in this study's instructional material development. Thirty-three eleventh-grade Social Sciences students make up the research subjects. The interactive teaching materials based on Canva are highly valid based on the research and development findings. This is supported by the material validation score of 3.07, the subject matter expert assessment score of 3.23, and the language expert validation score of 3.30. The overall recapitulation score of 3.2 further confirms this conclusion. This suggests that the interactive educational resources created by Canva meet appropriate standards and can be utilized by educators and learners alike.

Digital Twin-Based Cyber-Attack Detection Framework for Cyber-Physical Manufacturing Systems

Smart manufacturing (SM) systems utilize run-time data to improve productivity via intelligent decision-making and analysis mechanisms on both machine and system levels. The increased adoption of cyber-physical systems in SM leads to the comprehensive framework of cyber-physical manufacturing systems (CPMS) where data-enabled decision-making mechanisms are coupled with cyber-physical resources on the plant floor. Due to their cyber-physical nature, CPMS are susceptible to cyber-attacks that may cause harm to the manufacturing system, products, or even the human workers involved in this context. Therefore, detecting cyber-attacks efficiently and timely is a crucial step toward implementing and securing high-performance CPMS in practice. This paper addresses two key challenges to CPMS cyber-attack detection. The first challenge is distinguishing expected anomalies in the system from cyber-attacks. The second challenge is the identification of cyber-attacks during the transient response of CPMS due to closed-loop controllers. Digital twin (DT) technology emerges as a promising solution for providing additional insights into the physical process (twin) by leveraging run-time data, models, and analytics. In this work, we propose a DT framework for detecting cyber-attacks in CPMS during controlled transient behavior as well as expected anomalies of the physical process. We present a DT framework and provide details on structuring the architecture to support cyber-attack detection. Additionally, we present an experimental case study on off-the-shelf 3D printers to detect cyber-attacks utilizing the proposed DT framework to illustrate the effectiveness of our proposed approach. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This work is motivated by developing a general-purpose and extensible digital twin-enabled cyber-attack detection framework for manufacturing systems. Existing works in the field consider specialized attack scenarios and models that may not be extensible in practical manufacturing scenarios. We utilize digital twin (DT) technology as a key enabler to develop a systematic and extensible framework where we identify the abnormality of a resource and detect if the abnormality is due to an attack or an expected anomaly. We provide several remarks on how our proposed framework can extend existing industrial control systems (ICS) and can accommodate further extensions. The presented DTs utilize data-driven machine learning models, physics-based models, and subject matter expert knowledge to perform detection and differentiation tasks in the context of expected anomalies and model-based controllers that control the manufacturing process between multiple setpoints. We utilize a model predictive controller on an off-the-shelf 3D printer to run the process, and stage anomalies and cyber-attacks that are successfully detected by the proposed framework.

132 Modernizing Onboarding for Clinical Research Professionals: An Interactive and Adoptable Approach

OBJECTIVES/GOALS: The Clinical Research Professionals (CRP) at Cincinnati Children’s Hospital Medical Center (CCHMC) identified and addressed gaps in a static on boarding material by transforming it into an interactive, centralized, and customizable REDCap checklist to better meet researcher needs across the institution. METHODS/STUDY POPULATION: The CRP On boarding Checklist is a tool designed to assist clinical researchers in their onboarding process at CCHMC. This tool helps CRPs determine the required/recommended trainings available to assist with skill-building and establishing job role competency. CRP supervisorsand subject matter experts were included incontent revisions, format, and transition to a RED Capsurvey. The new checklist is interactive, targets training requirements by job function, and clearly labels mandatory training. A companion document allows new CRPs to create and track their own individualized training plan. RESULTS/ANTICIPATED RESULTS: The revised CRP On boarding Checklist was launched in April 2022 and announced via email communication. Alive demonstration was presented to all CRPs during the May 2022 CRP Monthly Meeting. The checklist and companion document are linked to the internal CRP website, which is accessible institutionally. Sincelaunch, almost 100 new and internally transferring CRPs have utilized the online tool to guide their training needs. The checklist is intended to reflect real-time changes in educational offerings. In addition to feedback and change requests from the CRP community, the checklist is updated as necessary and routinely reviewed on a biannual basisby the CRP Education Committee. DISCUSSION/SIGNIFICANCE: The creation and maintenance of the CRP Onboarding Checklist is a modern and accessible way for CRPs and supervisors to explore role-applicable training and take active roles in the on boarding process. The RED Capformat allows easy sharing and adoptability to other institutions via data dictionary.

563 Team Science to Assess Effectiveness and Impact in Public Healthcare Delivery System Contracting

OBJECTIVES/GOALS: Healthcare organizations and payers are moving from accountability to effectiveness frameworks. Static vendor contracts for full-scale implementation limit organizations' ability to evaluate impact before scale-up, or to iteratively improve. Our team science innovation employs science and learning methods as systems engage vendors. METHODS/STUDY POPULATION: Our team science innovation is a method to assess and model impact of interventions at scale in healthcare delivery systems. We are integrating expertise in learning processes of an academic medical center (UCLA CTSI) with the organizational knowledge and methodological expertise of the nation’s largest Medicaid managed care plan (LA Care Health Plan), which has over 2 million members. The LA Care Advanced Analytics Lab has unique capability in machine learning, while enables deep learning of variation. Our innovative product is a template to quickly mobilize evaluation and learning for a diverse population in a varied and distributed delivery system. The template design enables rapid learning for the full-scale policy implementation often imposed by government, and in the short timeframes involved. RESULTS/ANTICIPATED RESULTS: LA Care and the UCLA CTSI partnered to provide subject matter expertise and design effective pilots for interventions such as transitional care services, complex care management, and physician home visit strategies, accounting for confounding factors affecting the intervention and outcome. So far, collaborative modeling and design has produced a successful pilot of a physician home visit program intended to reduce avoidable emergency department visits. This pilot quickly revealed several major changes that would need to be incorporated for the contracted vendor to produce results if operated at scale, further informed by machine learning, in sufficient time to inform the contracting process. There are multiple evolving applications, including housing/homelessness. DISCUSSION/SIGNIFICANCE: Integrating the large data and analytics of a large healthcare organization with learning methods from the CTSI -- including learning from variation and designs for studying impact during scale-up -- fosters academic-community team science that could significantly improve the value of our largest delivery systems, public and commercial.

The use of META (virtual simulations) in Canadian junior military leadership development

PurposeThis paper aims to explore virtual simulations, merging artificial intelligence with real-world simulations, supporting Canadian armed forces (CAF) junior military leaders (JMLs) leadership development. Our research questions are: (1) How do virtual simulations support CAF junior military leadership development within a globalized and complex environment in the 21st century? (2) Could virtual simulations support a leadership culture change through efficacious “soft skills” training? In this paper, we explore the efficacy of virtual simulations for enhancing or developing leadership in JMLs in the CAF through a four-day pilot project with twenty JMLs (n = 20).Design/methodology/approachTo assess the efficacy of virtual simulations for leadership development, we designed and studied a four-day leadership workshop for JMLs in the CAF using several virtual artificial intelligence leadership role-play simulations developed by McGraw Hill in their smart book textbook (Manning &amp; Curtis, 2022) and several non-virtual in-class simulations for comparison. We selected four twenty to thirty-minute virtual role-play simulations that synergized with the in-person morning leadership workshop. We facilitated the three-hour leadership workshops and virtual/in-class simulations over four consecutive days. We emulated the ELESS model (De Freitas &amp; Routledge, 2013) to assess soft and leadership skills.FindingsThe participants (JMLs) reported beneficial learning utility associated with the virtual simulations. Participants also expressed that further utility might be leveraged through virtual simulations incorporating greater complexity with multiple potential outcomes. They also suggested that leadership simulations designed around military situations would prove highly beneficial, something that was outside of the scope of this small pilot project.Research limitations/implicationsSince this phase of our research is a pilot project, we secured a small amount of funding to test our hypothesis that simulations enhance leadership development for JMLs. These funding limitations resulted in several constraints in the research, such as the availability of virtual simulations articulating leadership from a military perspective. However, we believed the assigned organizational leadership simulations in the McGraw Hill Smart Book ecosystem would approximate generic leadership situations enough to test the hypothesis with the JMLs. As a pilot project, our sample size was relatively small (n = 20 JMLs) since participation was voluntary amidst a busy spring season for the JMLs. Since this is a pilot project, we suggest that twenty JMLs are an adequate sampling to test the hypothesis that simulations enhance JML leadership development. We will expand the sample size in the next phase of our research as we work with the CAF to expand the pool of participants to at least forty JML participants (n = 40). We also plan to secure further funding to collaborate with subject matter experts to design virtual simulations based on Canadian military leadership scenarios.Practical implicationsThe CAF host robust simulations capabilities for combat training, but have not exploited the potential training and analytical capacity of virtual leadership simulations for leadership development within the CAF. We believe that virtual simulations provide an opportunity for the CAF to effect desired culture change through leadership development that leverages the substantial pedagogical benefits of simulations.Social implicationsThe CAF encountered several detrimental leadership scandals that eroded the reputational capital of the CAF. In the current geo-political climate of an expanding North American Treaty Organization (NATO) and threats from several international actors, the CAF seeks to expand its capabilities by adding and enhancing its human capital. However, the CAF currently experiences a significant gap in its human capital aspirations. There is a unanimous consensus that the endemic traditional culture of the CAF, as expressed in the recent explosive leadership scandals, is a deterrent to recruitment and thus weakens the CAF’s capability. The CAF targets leadership development with new leadership paradigms as pivotal to culture change. The CAF suggests that by enhancing leadership development in the CAF the new cadre of leadership will change the culture of the CAF and thereby enhance the reputational capital of the CAF. It is believed that this rejuvenated culture will lead to greater recruitment and retention, leading to a strengthened military. A strengthened military is important to provide effective support and protection for the Canadian people in these volatile and uncertain times. This expanded capacity will enable the CAF to address external military threats more effectively and also the increasing operations other than war (OOTW), such as the military support of long-term care facilities during COVID-19 or the military’s support in fighting record wildfires and the military’s support in climate change related disasters such as flooding.Originality/valueThe satisfaction measures indicated by the participants are typical evaluative measures of leadership development (Noe, 2023). These satisfaction ratings do not, however, indicate whether training has produced a change in behaviour (Brown, 2022). The implications of these outcomes for leadership education are that role-player simulations are useful leadership education and development tools because they provide a theatre of practice in which mistakes are not detrimental and serve as learning moments (Moore, 2012; Piro and O’Callaghan, 2021; Riotto, 2021). Further, the importance of role-player simulations that closely approximate the sector where leadership is experienced and practiced is perceived to enhance the experience. While the CAF invest in combat related simulations, but leadership development simulations are not as evident in the training and development array. This study seeks to assess their potential value as a leadership development tool within the wider context of character development as a leadership competency.

Summarization of Video using Audio

Abstract: Online education has emerged as a highly effective means of delivering quality education to students. Its popularity has increased due to the high-quality visual and graphical content, delivered by subject matter experts, and the convenience of learning anytime and anywhere. However, students may face time constraints that prevent them from fully engaging with the course content. To address this issue, video transcript summarizers have gained popularity. These tools extract the most important topics from a video, allowing students to understand the essence of the class without having to watch the entire video. Our system focuses on developing a module using txtai.pipeline with Python to summarize online class videos. We use Whisper, a general-purpose speech recognition model, to train our model on a large dataset of diverse audio. The model takes the URL of a video as input and uses two algorithms to summarize the content: TF-IDF and Gensim. The summarization process is subjective, and we have incorporated two prominent methods: cosine similarity and ROUGE score. The former does not require a human-generated summary for reference, while the latter does. Our results show that the efficiency obtained using cosine similarity is greater than 90% in both TF-IDF and Gensim cases. The efficiency obtained in the case of ROUGE score is between 40-50%.