Developed Model Research Articles

Examining the fidelity of implementation of SKIP Cymru (Successful kinaesthetic instruction for pre-schoolers- Wales) by early childhood teachers in Wales following a programme of professional development

ABSTRACT Purpose Early childhood is a crucial time to develop fundamental motor skills (FMS) such as throwing, running and kicking (Goodway, J. D., J. C. Ozmun, and D. L. Gallahue. 2019. Understanding Motor Development: Infants, Children, Adolescents, Adults. Jones & Bartlett Learning.). Existing research into the play-based early childhood curricular in Wales found that children were not making progress in learning object control skills (Wainwright, N., J. Goodway, M. Whitehead, A. Williams, and D. Kirk. 2018. “Laying the Foundations for Physical Literacy in Wales: The Contribution of the Foundation Phase to the Development of Physical Literacy.” Physical Education and Sport Pedagogy 23 (4): 431–444. https://doi.org/10.1080/17408989.2018.1455819.). This was a concern as object control skill competency is critical to physical activity later in childhood and adolescence (Barnett, L. M., E. Van Beurden, P. J. Morgan, L. O. Brooks, and J. R. Beard. 2009. “Childhood Motor Skill Proficiency as a Predictor of Adolescent Physical Activity.” Journal of Adolescent Health 44 (3): 252–259. https://doi.org/10.1016/j.jadohealth.2008.07.004.). Therefore, SKIP (Successful Kinaesthetic Instruction for Pre-schoolers) – Cymru (Welsh word for Wales), a programme of professional development was developed based on the evidence-based work of SKIP by Goodway and colleagues (Goodway, J. D., J. C. Ozmun, and D. L. Gallahue. 2019. Understanding Motor Development: Infants, Children, Adolescents, Adults. Jones & Bartlett Learning.) to address the gaps in teacher knowledge. A limitation of previous SKIP and motor development literature is the lack of evaluation of the teacher’s fidelity to implementation. Ensuring fidelity of implementation (FoI) is a critical indicator of quality intervention programmes. Thus, this study examined the extent to which teachers could implement a 10-week SKIP-Cymru programme with fidelity with ongoing mentoring following a programme of professional development. Method Participants: Early childhood teachers (N = 5), with no prior experience of SKIP Cymru, from 4 Welsh schools took part in the study. Mentors (N = 2) supported the teacher’s implementation of SKIP Cymru following the one-day professional development workshop. Quantitative data were collected using fidelity checklists for both the Teacher Workshop and the implementation of SKIP Cymru. Descriptive statistics of fidelity data were calculated. Results The results for the Teacher Workshop found that 100% of the content was delivered in relation to the Core Instructional Principles, Practices and Expectations of the SKIP-Cymru, and teachers learned the key outcomes. The average teacher fidelity for implementation of SKIP Cymru was 67.80% (ranging between 39% and 89%). On average the teachers delivered 16.4 out of the 20 lessons. The mentors supported the teachers for an average of 7.4 lessons out of the 10 lessons. Conclusion This study demonstrates that it is possible to train teachers to deliver a developmentally appropriate motor skills programme. Nevertheless, it was evident from the inconsistencies in implementation that teachers needed more in-depth knowledge, and specifically a lot more time to develop the pedagogical and instructional skills needed to optimize the impacts of SKIP Cymru on children. It is recommended that the current model of professional development needs to be re-evaluated, with consideration being given to either more in-depth training for mentors or more in-depth accredited training for the teachers that would negate the need for mentoring and have a bigger impact on the teacher’s pedagogy and delivery.

Volatile organic compound analysis of malignant pleural mesothelioma chorioallantoic membrane xenografts

Malignant pleural mesothelioma (MPM) is an aggressive cancer associated with asbestos exposure. MPM is often diagnosed late, at a point where limited treatment options are available, but early intervention could improve the chances of successful treatment for MPM patients. Biomarkers to detect MPM in at-risk individuals are needed to implement early diagnosis technologies. Volatile organic compounds (VOCs) have previously shown diagnostic potential as biomarkers when analysed in MPM patient breath. In this study, chorioallantoic membrane (CAM) xenografts of MPM cell lines were used as models of MPM tumour development for VOC biomarker discovery with the aim of generating targets for investigation in breath, biopsies or other complex matrices. VOC headspace analysis of biphasic or epithelioid MPM CAM xenografts was performed using solid-phase microextraction and gas chromatography-mass spectrometry. We successfully demonstrated the capture, analysis and separation of VOC signatures from CAM xenografts and controls. A panel of VOCs was identified that showed discrimination between MPM xenografts generated from biphasic and epithelioid cells and CAM controls. This is the first application of the CAM xenograft model for the discovery of VOC biomarkers associated with MPM histological subtypes. These findings support the potential utility of non-invasive VOC profiling from breath or headspace analysis of tissues for detection and monitoring of MPM.

Design optimization and simulation of a 3D printed cable-driven continuum robot using IKM-ANN and nTop software

The first aspect of the paper focuses on presenting the innovative design of a new continuum robot, which was initially conceptualized using SolidWorks and then brought to life through 3D printing. This section illustrates the construction process, detailing the wiring method and the separator between each section of the robot. A key feature of the newly proposed design is the ball-like shape on the upper side of each disk, allowing each disk to rotate freely and gracefully in conjunction with the next one. To further enhance the design, the disk was optimized using nTopology software, an AI-based solution that reduces weight while maintaining performance. This modern engineering tool proved to be instrumental in addressing engineering challenges effectively. Subsequently, both the original and optimized disks were fabricated using 3D printing technology. In addition to the physical construction, the study employed an Artificial Neural Network (ANN) coupled with Particle Swarm Optimization (PSO) to simulate the developed model by solving its inverse kinematic model. The findings from this research have paved the way for a new continuum robot design that can be trained using the ANN-PSO method. Furthermore, the powerful nTopology tool was demonstrated to be capable of skillfully optimizing any given components without sacrificing performance.

Travel distance estimation of landslide-induced debris flows by machine learning method in Nepal Himalaya after the Gorkha earthquake

Debris flows are more likely to be triggered in the earthquake-strike areas with a widespread presence of unstable slopes, causing severe casualties and changing the surrounding natural topography. In such scenario, estimating the travel distance of debris flows becomes crucial to understand the hazardous areas. Therefore, a hybrid machine learning model (GA-XGBoost) was employed to achieve a reliable estimation of debris-flow travel distance. This model was applied to the Nepal Himalayas, the site of the 2015 Gorkha earthquake. We selected four geomorphological factors for travel distance estimation. They are the volume of failure mass (VL), the height difference between the material source center and end point of movement mass (H), the mean gradient of the travel path (J), and the mean curvature of the travel path (C). Furthermore, to eliminate the noise information and enhance stability of input data, a principal component analysis (PCA) was used to generate three principal components (PC1, PC2, and PC3) from the selected factors to serve as input variables of model development. The performance of this model was evaluated using the assessment indexes, resulting in a mean absolute percentage error (MAPE) of 8.71%, a root mean square error (RMSE) of 144.3 m, and a mean absolute error (MAE) of 86.1 m. Four empirical approaches were also introduced for comparison analysis. Our proposed model has proven to be superior and effective, as the estimated results closely match the actual values. All the results affirm the suitability of our developed model for estimating the travel distance of landslide-induced debris flows following a strong earthquake.

Exploring the impact of makerspace-based learning materials on students’ computational thinking skills: Using machine learning to address challenges in smart coffee agroforestry

This research aimed to develop teaching materials to improve students' computational thinking skills in solving smart coffee agroforestry problems through machine learning, using the RBL-STEM makerspace. Computational thinking skill goes beyond coding and programming and is related to the students' higher-order thinking skills. This research uses the ADDIE development model in developing the learning materials. The learning material products consist of assessment instruments, students' worksheets, and lesson plans. The research employed questionnaires, validation sheets (including content, construct, programming, and language), and observation sheets to collect data regarding the instruments' effectiveness, practicality, and validity. We evaluated the effectiveness of the teaching materials in a single classroom using a paired-test, examining the significant difference between the pre-test and post-test scores. The research subjects are 42 students of the Science Education Department at the University of Jember for the academic year 2023-2024. The average overall score, including content, construct, programming, and language, is 92.97%. The results show that the learning materials satisfy in all aspects. We did in-depth interviews with some selected students at low, medium, and high levels of computational thinking skills and compared the interview results using NVIVO software to making project maps. Furthermore, the score of paired t-test shows α-value = 0.003< 0.05. We concluded that RBL-STEM makerspace learning materials significantly contribute to the development of students’ computational thinking skills. It implies that the learning materials developed in this research are ready to be used in the learning activities to foster students' computational thinking skills.

Nonlinear impact of automobile industry agglomeration on CO2 emission: Incorporating urban characteristics in China

Despite the increasing economic benefits generated by the cluster effect of the automotive industry, CO2 emissions have become a serious challenge in the “3060” dual-carbon context. There are significant uncertainties regarding the impact of automotive industry agglomeration on urban CO2 emissions, including quantifying impact thresholds and understanding the sensitivity of different agglomeration patterns. This study explores how automotive industry agglomeration impacts CO2 emissions across 278 Chinese cities, and uncover the impact patterns based on varying city characteristics. The results show that the technology agglomeration of the automobile industry exhibits a nonlinear “U-shaped” impact on CO2 emissions with a threshold value of 0.4267, while the scale agglomeration shows a nonlinear inverted “U-shaped” impact with a threshold value of 0.1206. In low-carbon demonstration cities, technology agglomeration has the most significant impact, with fluctuations ranging from −14.65% to 16.12%. In contrast, transitional cities are most affected by scale agglomeration, with a fluctuation range of −18.1%–11.19%. Besides, the results indicate that China's automobile industry development programs tend to relocate economic activities from highly agglomerated low-carbon demonstration cities to potential development cities with lower levels of agglomeration and other transitioning cities. Lastly, the results reconfirm that developing automotive industry development models based on cities' characteristics can enhance the environmental benefits of industrial agglomeration.

Development of Statistical Downscaling Model Based on Volterra Series Realization, Principal Components, Climate Classification, and Ridge Regression

This paper applied the fuzzy function approach, combined with the ridge regression model, to produce daily rainfall projections from large-scale climate variables. This study developed a statistical downscaling model based on principal components, c-means fuzzy clustering, Volterra series, and ridge regression. The model is known, hereafter as SDC2R2. In the developed downscaling model, the use of ridge regression, instead of multiple linear regression, is proposed to downscale daily rainfall with wide range (WR) predictors. The WR predictors were applied to sufficiently incorporate climate change signals. The developed model also captured the non-linear interactions of the climate variables by applying the transformation of Volterra series realization over WR predictors. This transformation was performed by applying principal components as orthogonal filters. Further, these principal components were clustered by using c-means clustering and non-linear transformations were applied on these membership functions, to improve the prediction ability of the model. The reanalysis of climate data from the National Centres for Environmental Prediction (NCEP) was used to develop the model and was validated by using the Global Climate Model (GCM) for four locations in the Manawatu River basin. The developed model was used to obtain future daily rainfall projections from three Representative Concentrative Pathways (RCP 2.6, RCP 4.5, and RCP 8.5) scenarios from the Canadian Earth System Model (CanESM2) GCM. The performance of the model was compared with a widely used statistical downscaling model (SDSM). It was observed that the model performed better than SDSM in downscaling rainfall on a daily basis. Every scenario indicated that there is a probability of obtaining high future rainfall frequency. The results of this study provide valuable information for decision-makers since climate change may potentially impact the Manawatu basin.

Finite element analysis of plates by an accurate strain-based element

Plates analysis has been a very important research area for a long time. In this perspective, in this paper, finite element analysis of thin plates in bending is carried out using a new four node strain-based plate element. The strain-based approach and Kirchhoff theory for thin plates have been used to create the strain field of this element. This approach consists in having a displacement field from a proposed strain field. This developed model contains essential degrees of freedom at each corner node which are three, one displacement and two rotations. The displacement field is based on the assumed functions for various deformations which satisfy the compatibility equations, and the displacement functions are obtained by integrating these deformation functions. The numerical validation of this developed element was held through several examples from the literature. The obtained results from these numerical tests prove the good accuracy and performance of this element.

Urban growth simulation and scenario projection for the arid regions using heuristic cellular automata

Arid regions tend to form compact urban patterns that have significant implications on urban growth and future urban patterns. Spatial simulation and projection using cellular automata (CA)-based models are important for achieving sustainable urban development in arid regions. In response to this need, we developed a new CA model (GSA-CA) using the gravitational search algorithm (GSA) to capture and project urban growth patterns in arid regions. We calibrated the GSA-CA model for the arid city of Urumqi in Northwest China from 2000 to 2010, and validated the model from 2010 to 2020, and then applied to project urban growth in 2040. The results indicated that the optimal performance of the model was achieved when the fraction of the population was 0.5. GSA-CA achieved an overall accuracy of 98.42% and a figure of merit (FOM) of 43.03% for the year 2010, and an overall accuracy of 98.52% with FOM of 37.64% for 2020. The results of the study help to adjust urban planning and development policies. The developed model has the potential to be employed in simulating urban growth and future scenarios in arid regions globally, including Northwest China and Africa.

Comparative analysis of cortical anatomy inmale participants with internet gaming disorder or tobacco use disorder: Insights fromnormative modeling.

Research on individual differences in brain structural features of internet gaming disorder (IGD) and established addictions such as tobacco use disorder (TUD) is currently limited. This study utilized normative modeling to analyze the cortical thickness (CT) development patterns of male patients with IGD and TUD, aiming to provide further insights into whether IGD qualifies as an addiction. Surface-based brain morphometry (SBM) was used to calculate CT from T1-weighted magnetic resonance imaging data of 804 male participants (665 healthy individuals, 68 IGD and 71 TUD). Gaussian process regression was employed to generate normative models of CT development. Deviation maps were produced to depict deviations of IGD and TUD participants from the typical developmental patterns. Both addiction groups exhibited widespread cortical thinning, particularly in regions such as the bilateral temporal pole and medial orbitofrontal cortex. The TUD group demonstrated a higher degree of individualization and limited spatial overlap compared to the IGD group. Opposite trends in CT changes were observed between the two groups in the bilateral pericalcarine cortex and pars triangularis. These findings regarding the similarities and differences between IGD and TUD provide support for the idea that IGD shares common features with substance-related addictions and contribute to a deeper understanding of the neural mechanisms underlyingIGD.

Contribution of geometrical infill pattern on mechanical behaviour of 3D manufactured polylactic acid specimen: Experimental and numerical analysis

Additive manufacturing is regarded as a very efficient fabrication technique since it permits the manufacturing of any three-dimensional product. The present work determines the effect of various infill pattern on the mechanical properties in term of tensile strength, yield strength and hardness of poly-lactic acid (PLA) samples fabricated by fused deposition modeling method. The mechanical behaviour of the 3D-printed PLAs investigated using dog-bone specimens with six distinct infill patterns: line, triangle, tri-hexagon, cubic, octet, and gyroid. The mechanical characteristics were evaluated using the uniaxial tensile test and shore D type hardness tester. The strain and deformation criteria were employed to substantiate the ductile and brittle characteristics. The fractural surface morphology analyzed using the field emission scanning electron microscope. Nonlinear Finite Element Analysis (FEA) was employed to simulate the uniaxial tensile test and establish a Yeoh third order hyperelastic material model for the predictions of the stress-strain response. This model is chosen for its precise ability to predict the nonlinear stress-strain responses for significant deformation and is crucial in applications that involve high degrees of flexibility and elasticity, such as in tire modeling, polymer and elastomer analysis, sports equipment designing, 3D printed components etc. Results revealed that the cubic infill had a maximum tensile strength 32.648 ± 1.42 MPa and octet infill had a minimum tensile strength 22.373 ± 0.79 MPa. The majority of experimental data indicated a brittle behaviour for line-infilled, but triangular, trihexagonal, cubic, octet, and gyroid infill patterns demonstrated ductile behaviour. In comparison to other geometrical infills, cubic shown relatively superior mechanical responses. Consequently, the geometrical infill effect plays a significant role in finding the appropriate mechanical property for industrial applications. The developed material model possesses potential utility in non-linear FEA investigations pertaining to 3D printed PLA objects that are predicted to sustain tensile strength.

Development and application of a WebGIS-based prediction system for multi-criteria decision analysis of porcine pasteurellosis

Porcine pasteurellosis is an infectious disease caused by Pasteurella multocida (P. multocida), which seriously endangers the healthy development of pig breeding industry. Early detection of disease transmission in animals is a crucial early warning for humans. Therefore, predicting risk areas for disease is essential for public health authorities to adopt preventive measures and control strategies against diseases. In this study, we developed a predictive model based on multi-criteria decision analysis (MCDA) and assessed risk areas for porcine pasteurellosis in the Chinese mainland. By using principal component analysis, the weights of seven spatial risk factors were determined. Fuzzy membership function was used to standardize all risk factors, and weight linear combination was used to create a risk map. The sensitivity of the risk map was analyzed by calculating the mean of absolute change rates of risk factors, as well as calculating an uncertainty map. The results showed that risk areas for porcine pasteurellosis were predicted to be locate in the south-central of the Chinese mainland, including Sichuan, Chongqing, Guangdong, and Guangxi. The maximum standard deviation of the uncertain map was less than 0.01and the ROC results showed that the prediction model has moderate predictive performance with the area under the curve (AUC) value of 0.80 (95% CI 0.75–0.84). Based on the above process, MCDA was combined with WebGIS technology to construct a system for predicting risk areas of porcine pasteurellosis. Risk factor data was directly linked to the developed model, providing decision support for disease prevention and control through monthly updates.

Advanced regression model fitting to experimental results in case of the effect of grinding conditions on a cutting force with the planer technical knives

The use of well-fit models enables users to make better decisions and draw accurate insights, so in this article a multi-step procedure for establishing regression functions for experimental data is presented. This was inspired by the need to determine well-fitted models for the results of the study of the relationship between the input factors of the grinding process of planer knives and the measured grinding power, as well as in relation to the knife cutting force. The sharpening process was carried out under various conditions, making it possible to assess their influence on the results and select the most favorable technological parameters to prepare the knives for operation. The equations adjusted by Excel or other basic methods require additional verification if the mathematical formula and values of the model coefficients correspond to the data and the physical meaning. For this purpose, one-, two- and three-factor analyses were performed to eliminate redundant factors and introduce significant interactions between input parameters. Additional analyses of variance and Tukey, Levene and Brown-Forsythe tests were used to determine the general form of the model. Detailed form of nonlinear models was worked out by comparing the distribution of residuals, looking for outliers and evidence of the presence or absence of collinearity, as well as by determining the values of additional model quality indicators, such as Akaike Information Criterion, Cook’s distance and Variance Inflation Factor. The models presented include a categorization variable (grinding type) and are presented graphically in the form of surface plots. With reference to the technological processes studied, a discussion of the physical significance of the developed models and the influence of the input factors on the model output value was conducted. The analyzes additionally include an evaluation of the model factors using prediction slice plots.

Teaching Reform of RFID Principles and Application Course with Information Industry Integration for System Capability Cultivation

The rapid development of the domestic information industry ecosystem has put forward higher requirements for the quality of computer talent training in colleges and universities. In response to the current issues of outdated course content and lagging teaching strategies in RFID principles and application courses at applied undergraduate institutions, measures have been proposed to promote the cultivation of talent for the autonomous and controllable RFID industry, taking the system capability as the main line. Under the guidance of the engineering education certification standards, based on the Tyler curriculum development model, domestic RFID platforms are introduced into the classroom. Through innovative reforms of the objectives, content, methods, and evaluation system of the RFID principles and application courses, the integration into the information industry ecosystem is actively promoted, enhancing the effective integration of the education chain, industry chain, innovation chain, and talent chain, contributing to the national strategy of independent control.

Ensuring Cybersecurity in Action Electronic Commerce Enterprises in the Conditions of Implementation of the Sustainable Development Model

Ensuring Cybersecurity in Action Electronic Commerce Enterprises in the Conditions of Implementation of the Sustainable Development Model

Analysis of transient heat conduction in tubes under convective boundary conditions

AbstractIn this work, six analytical solutions are given to estimate the energy exchange by transient conduction in pipes with convection conditions. The developed models were adjusted for an interval from 0.2 to 0.8, dimensionless Fourier (Fo) and Biot (Bi) numbers, from 0.05 to 50 and 0.005 to 50, respectively. In each case, 616 tests of temperature distributions were computed using the Heisler approximate method (HAM) and the exact models proposed, for different combinations of . For the comparison made between the analytical solutions and the HAM, 3696 tests were used, detecting that the HAM correlates with the analytical method with an average deviation of and for 71.2%, and 90.4% of the different values of combinations evaluated. The best fit was found for Case 5, with a mean deviation of and for 81.1% and 92.3% of the data used, respectively, while the weaker fit was detected for Case 2, with a mean deviation of and for 67.9% and 88.2% of the available tests.

Strengthening facility-based integrated emergency care services for time sensitive emergencies at all levels of healthcare in India: An implementation research study protocol

BackgroundThe healthcare system in India is tiered and has primary, secondary and tertiary levels of facilities depending on the complexity and severity of health challenges at these facilities. Evidence suggests that emergency services in the country is fragmented. This study aims to identify the barriers and facilitators of emergency care delivery for patients with time-sensitive conditions, and develop and implement a contextually relevant model, and measure its impact using implementation research outcomes.MethodsWe will study 85 healthcare facilities across five zones of the country and focus on emergency care delivery for 11 time-sensitive conditions. This implementation research will include seven phases: the preparatory phase, formative assessment, co-design of Model “Zero”, co-implementation, model optimization, end-line evaluation and consolidation phase. The “preparatory phase” will involve stakeholder meetings, approval from health authorities and the establishment of a research ecosystem. The “formative assessment” will include quantitative and qualitative evaluations of the existing healthcare facilities and personnel to identify gaps, barriers and facilitators of emergency care services for time-sensitive conditions. On the basis of the results of the formative assessment, context-specific implementation strategies will be developed through meetings with stakeholders, providers and experts. The “co-design of Model ‘Zero’” phase will help develop the initial Model “Zero”, which will be pilot tested on a small scale (co-implementation). In the “model optimization” phase, iterative feedback loops of meetings and testing various strategies will help develop and implement the final context-specific model. End-line evaluation will assess implementation research outcomes such as acceptability, adoption, fidelity and penetration. The consolidation phase will include planning for the sustenance of the interventions.DiscussionIn a country such as India, where resources are scarce, this study will identify the barriers and facilitators to delivering emergency care services for time-sensitive conditions across five varied zones of the country. Stakeholder and provider participation in developing consensus-based implementation strategies, along with iterative cycles of meetings and testing, will help adapt these strategies to local needs. This approach will ensure that the developed models are practical, feasible and tailored to the specific challenges and requirements of each region.

The Development of Interactive Powerpoint Learning Media to Increase Students’ Critical Thinking Ability

Mathematics learning can develop students' creativity to solve problems in various life situations. Learning mathematics helps train students to think critically and creatively to solve problems. Considering the reality on the ground and the importance of critical thinking skills. from an early age. One effort to develop critical thinking abilities is to use media directed at these abilities. The method used in this research is research and development, with a modified 4-D development model in three stages, namely determination, design and development. This research aims to determine the development of interactive teaching materials assisted by power points, on Statistics material. The subjects of this research were 3 mathematics teachers at SMP Mutiara 4 Bandung. The instrument for developing teaching materials uses interview instruments. The teaching materials validated by three validators have a total score on the interactive power point of 275 with a maximum ideal score of 300 and have a percentage of 92.31% in the valid category based on the teaching material criteria. The validator's assessment of the interaction strength score shows that the percentage score for each aspect and the total percentage score are both in the valid category. Based on the research and development process and results, the following conclusions were obtained. Developing learning media using interactive Powerpoint, critical thinking skills are within valid criteria. The results obtained can be tested on junior high school or MTs students in accordance with the considerations and assessments of validator experts.

WP3.14 - A Single Unit Service Review in Northern Ireland: The Ever-increasing Acute Surgical Take and the Need for Service Adaptation

Abstract Aims Referrals to the on-call general surgeons in the unit has increased significantly over the past year. Staff levels and hospital resources have not changed to reflect this increasing demand on the service. Our aim is to evaluate the increase in numbers and develop a strategic plan for resolution. Methods A database of referrals to the on-call surgical team was developed using the daily handover records. Two periods of data collection were undertaken, each lasting a duration of 30 days, taking place approximately one year apart. Patient demographics and clinical information was gathered using our electronic care record and electronic notes record. Data gathered included diagnosis, treatment, investigations, interventions, length of stay, suitability for ambulation and follow up. Results The total number of patients referred to the on-call team during cycle one was 233, compared with 405 in cycle two; this is a 74% increase in referrals. During the windows of data collection, 75% of patients with an unscheduled admission did not undergo any intervention and 80% were deemed suitable for ambulation. Conclusion Increasing demands on the NHS require a forward-thinking approach to how we provide an acute surgical service. This study demonstrates that a large proportion of patients are suitable for an ambulatory model of care and development of this service would be a valuable adjunct to the unit. To propose an ambulatory service providing urgent surgical assessment would be an asset to the Trust; potential outcomes would include improving the patient experience, reducing inpatient admissions and bed days, with the associated cost-saving.

Using Systems Engineering and Implementation Science to Design an Implementation Package for Preoperative Comprehensive Geriatric Assessment Among Older Adults Having Major Abdominal Surgery: Protocol for a 3-Phase Study.

Older Americans, a growing segment of the population, have an increasing need for surgical services, and they experience a disproportionate burden of postoperative complications compared to their younger counterparts. A preoperative comprehensive geriatric assessment (pCGA) is recommended to reduce risk and improve surgical care delivery for this population, which has been identified as vulnerable. The pCGA optimizes multiple chronic conditions and factors commonly overlooked in routine preoperative planning, including physical function, polypharmacy, nutrition, cognition, mental health, and social and environmental support. The pCGA has been shown to decrease postoperative morbidity, mortality, and length of stay in a variety of surgical specialties. Although national guidelines recommend the use of the pCGA, a paucity of strategic guidance for implementation limits its uptake to a few academic medical centers. By applying implementation science and human factors engineering methods, this study will provide the necessary evidence to optimize the implementation of the pCGA in a variety of health care settings. The purpose of this paper is to describe the study protocol to design an adaptable, user-centered pCGA implementation package for use among older adults before major abdominal surgery. This protocol uses systems engineering methods to develop, tailor, and pilot-test a user-centered pCGA implementation package, which can be adapted to community-based hospitals in preparation for a multisite implementation trial. The protocol is based upon the National Institutes of Health Stage Model for Behavioral Intervention Development and aligns with the goal to develop behavioral interventions with an eye to real-world implementation. In phase 1, we will use observation and interviews to map the pCGA process and identify system-based barriers and facilitators to its use among older adults undergoing major abdominal surgery. In phase 2, we will apply user-centered design methods, engaging health care providers, patients, and caregivers to co-design a pCGA implementation package. This package will be applicable to a diverse population of older patients undergoing major abdominal surgery at a large academic hospital and an affiliate community site. In phase 3, we will pilot-test and refine the pCGA implementation package in preparation for a future randomized controlled implementation-effectiveness trial. We anticipate that this study will take approximately 60 months (April 2023-March 2028). This study protocol will generate (1) a detailed process map of the pCGA; (2) an adaptable, user-centered pCGA implementation package ready for feasibility testing in a pilot trial; and (3) preliminary pilot data on the implementation and effectiveness of the package. We anticipate that these data will serve as the basis for future multisite hybrid implementation-effectiveness clinical trials of the pCGA in older adults undergoing major abdominal surgery. The expected results of this study will contribute to improving perioperative care processes for older adults before major abdominal surgery. DERR1-10.2196/59428.