Program Performance Research Articles

Implementing a student-centered stroke intervention and prevention education program; evaluating motivation, cognitive load, and performance among middle school students.

In this study, we investigated the association between motivation, cognitive load, difficulty, and performance in a stroke education outreach program implemented for middle school students. Various interactive instructional activities were developed to engage students throughout the program to assess cognitive and intrinsic load arising from learner implementation of various tasks in a stroke education program for middle school kids. Performance was measured using a post-test to assess knowledge gained by the 6th, 7th, and 8th-grade middle school students. A short questionnaire was also administered to collect data on students' motivation using the ARCS model to asses attention, relevance, confidence, and satisfaction. In addition, we evaluated difficulty level and cognitive load. The relationship between performance and motivation was assessed using Pearson's correlation. In our results, there was no significant difference (p > 0.05) in performance between the 6th, 7th, and 8th-grade students. The difference in performance, cognitive load (mental effort and difficulty), or motivation between the 6th, 7th, and 8 t-grade students was not significant (p > 0.05). The correlation between motivation and performance was significant (r = 0.87, p = 0.001), while the correlation between mental effort and performance was not significant (r = 0.34, p = 0.270). Also, the correlation between difficulty and performance was not significant (r = 0.38, p = 0.361). In the ARCS motivation model, attention, and confidence received the lowest mean scores (3.9), while relevance received the highest score (4.3). Our findings reveal the importance of implementing novel activities to enhance students' motivation to improve performance in the implementation of stroke education outreach programs for middle school students.

Effect of input subsidies and extension services: Evidence from rice productivity in Bangladesh

This study examines the effect of agricultural input subsidy cards and extension services on Bangladesh’s rice productivity, using plot level panel data from three waves (2011–2019) of the Bangladesh Integrated Household Survey. To control for endogeneity of the two programs, instrumental variable and control function approaches are used. Findings reveal that access to input subsidy cards and extension services raise productivity in rice-planted plots by nearly 20% and 22%, respectively. Further, the channels and type of advisory services matter. Finally, access to input subsidy cards and extension services is more beneficial in areas prone to droughts and excessive rainfall. These findings underscore the value of complementary investments in robust extension systems, especially in vulnerable regions, to optimize the performance of input subsidy programs. Expanded extension services coupled with input subsidies can be an effective policy mix to raise productivity, strengthen climate resilience, and promote inclusive agricultural growth in Bangladesh.

Deep Learning PCA Correlation Analysis of Teacher’s Educational Technology Quality and Teacher’s Professional Competence

In contemporary education, the integration of educational technology has become crucial for enhancing teaching quality and fostering student learning outcomes. This study employs a novel approach by combining deep learning techniques with Principal Component Analysis (PCA) to explore the relationship between teachers' educational technology proficiency and their professional competence. The research leverages a dataset comprising various metrics related to teachers' usage of educational technology tools and their performance in professional development programs. Initially, the study preprocesses the data and applies deep learning models to extract high-level features from the complex and heterogeneous dataset. Subsequently, PCA is employed to reduce the dimensionality of the feature space while preserving the underlying structure and variability of the data. Through this process, latent factors representing different aspects of educational technology proficiency and professional competence are identified. The correlation analysis conducted on the reduced feature space reveals intricate relationships between teachers' competency in educational technology and their overall professional capabilities. The findings indicate that certain dimensions of educational technology quality, such as adaptability to new tools and innovative pedagogical approaches, positively correlate with measures of professional competence, including classroom management skills, student engagement, and instructional effectiveness.

Couple-Years of Protection Indicator: New Global Guidance for Updating Existing Methods and Adding New Methods.

Couple-years of protection (CYP) is an indicator that allows for monitoring and evaluating of family planning (FP) program performance through simple calculations. The CYP for each contraceptive method is calculated by multiplying the number of contraceptive commodity units distributed to clients over a 1-year period by a conversion factor that quantifies the duration of contraceptive protection provided per unit distributed. CYP calculations across methods were previously updated in 2000 and 2011, resulting in changes in methodology, factor inclusion, and specific methods. Since the 2011 update, changes and additions to the modern contraceptive method mix required new CYP conversion factors for 4 methods of contraception: Levoplant implant, progestin-only pills (POPs), Caya diaphragm, and the hormonal intrauterine device. We conducted literature reviews of both published and gray literature and consulted with experts to identify updated data on continuation rates, duration of efficacy, and method effectiveness for the 4 methods. New CYP conversion factors were calculated for the 4 methods either by using the same calculation used previously for the method considering new data or, for new methods, using calculations for similar methods. New CYP conversion factors were assigned to the 4 methods of contraception covered in this update: Levoplant, 2.5 CYP per implant inserted; POPs, 0.0833 CYP per pack (i.e., 12 cycles per CYP); Caya diaphragm, 1 CYP per device, and hormonal intrauterine device, 4.8 CYP per device inserted. CYP is an important indicator for FP programs. As new methods of contraception are developed and new evidence is generated for current methods, the indicator may need to be updated. A standard process for updating and documenting future CYP updates is recommended.

Programmatic Assessment: New Approach of Student Assessment in Medical Education of the Current Century

Over the past few decades, education programs in health professions have moved toward a competency-based paradigm throughout the world. Competency-based education (CBE) relies on the fundamental principle that predetermined outcomes (competencies) guide teaching, learning, and assessment to ensure that graduates demonstrate proficiency in key competency domains and are able to provide care for patients with high quality throughout their careers. The purpose of CBE is to transform learners into healthcare workers who have lifelong learning and are committed to professional excellence, and the necessary competencies have been created in them. In CBE, learners are usually the center of attention and are actively involved in the learning and assessment process. Providing frequent and meaningful performance feedback enables learners to shape their learning paths by identifying appropriate learning opportunities for further development. Assessment is critical in achieving the goals of CBE. However, traditional approaches to assessment, which generally focus exclusively on the summative function of assessment, are not appropriate in CBE. Assessment programs should not only ensure robust decision-making about the progress and development of learners' competence but also facilitate the production of high-quality feedback for learning and support reflective practice and the use of feedback. Therefore, to continuously improve performance in CBE, assessment programs and assessment functions should be combined and integrated for learning. Programmatic assessment is a comprehensive approach in the assessment system that is theoretically aligned with key principles of CBE, as it aims to optimize assessment for learning while ensuring informed decision-making about learners' achievement of intended outcomes. In programmatic assessment, low-stakes assessments are continuously and purposefully considered to provide meaningful feedback on the longitudinal performance of learners to develop their competencies, while high-stakes assessments are based on the meaningful aggregation of data from multiple low-stakes assessments, which are collected over longer periods of time, at different periods in different contexts, and with multiple raters. However, while programmatic assessment approaches are increasingly being accepted as essential tools in the effective implementation of CBE, various research findings have indicated that it is difficult to merge different assessment performances in programmatic assessment. Performing programmatic assessment requires a change not only in assessment design but also in instructors and learners' views and data about objective and high-quality evaluation performance. Therefore, changing the assessment culture and fundamental data is necessary. Capacity building is a key element in any change process. All stakeholders involved in programmatic assessment must develop the capabilities needed to bring about the desired change in assessment culture. However, research findings suggest that stakeholders may not always be willing or able to perform the new roles as intended for them; instead, old behaviors "simply" adapt to new environments.

New development: Great expectations—whole of government accounting: An Australian perspective of its adoption, development and future use in the current environment

IMPACT While this article focuses on the Australian experience (federal and state levels), the issues/suggestions are relevant to countries that have adopted Whole of Government Accounting (WGA) or are considering doing so. A major issue is to encourage greater attention by, and involvement of, the parliament and its committees in reviewing and examining the outcomes as an important element of accountability to the general public for the use of the resources and to show trends over time. While there has been a greater focus on individual programme performance over recent years, the WGA have rated little discussion, let alone examination and questioning. For example, the finance commentary on the latest consolidated financial statements is largely a statistical examination, not an identification /analysis, of issues of concern nor of necessary action to improve financial performance. A recent initiative taken by the Australian government and the Australian National Audit Office (ANAO) is the conduct of audits of agencies’ annual performance statements. No doubt a catalyst has been the unprecedented financial difficulties being experienced by governments.

Crossing the Finish Line but Losing the Race? Socioeconomic Inequalities in the Labor Market Trajectories of Community College Graduates

Abstract Despite decades and hundreds of billions of dollars of federal and state investment in policies to promote postsecondary educational attainment as a key lever for increasing the economic mobility of lower income populations, research continues to show large and meaningful differences in the mid-career earnings of students from families in the bottom and top income quintiles. Prior research has not disentangled whether these disparities are due to differential sorting into colleges and majors, or due to barriers that lower socioeconomic status (SES) graduates encounter during the college-to-career transition. Using linked individual-level higher education and Unemployment Insurance records for nearly a decade of students from the Virginia Community College System, we compare the labor market outcomes of higher and lower SES community college graduates within the same college, program, and academic performance level. Our analyses show that, conditional on employment, lower SES graduates earn nearly $500/quarter less than their higher SES peers one year after graduation, relative to higher SES graduate average of $10,846/quarter. The magnitude of this disparity persists through at least three years after graduation. Disparities are concentrated among non-nursing programs, in which gaps persist seven years from graduation. Our results highlight the importance of greater focus on the college-to-career transition.

Revisiting the opioid and naloxone education (ONE) program: Program evaluation using the RE-AIM model four years later

ObjectiveThe Opioid and Naloxone Education (ONE) Program focuses on community pharmacy-based patient screening and interventions to improve population health with regard to opioid use. The purpose of this paper is to reevaluate the ONE Program performance using the RE-AIM model, in comparison to the review performed in 2019. MethodsThe program performance of the ONE Program was evaluated from January 1, 2021 to December 31, 2022 was evaluated using the five domains of the RE-AIM model. Reach was defined as the proportion of patients receiving opioid prescriptions who completed the screening. Efficacy was defined as the proportion of individuals identified as at risk who received a pharmacist intervention. Adoption was defined as the proportion of community pharmacies who enrolled in the ONE Program. Implementation was defined as the proportion of pharmacies that enrolled that provided at least five patient screenings. Maintenance was defined as the proportion of pharmacies that completed at least one screening three months. These results were compared against evaluation of the program from October 12, 2018 to June 1, 2019. ResultsApproximately 7.28 % of patients receiving opioid prescriptions were screened for risk of opioid misuse and accidental overdose (Reach). Of the patients screened, 97.4 % of patients at risk for opioid misuse or accidental overdose received a pharmacist-led intervention (Efficacy). Additionally, 49.6 % of the pharmacist that enrolled in the ONE Program completed at least five screenings (79 %) and of those, 86.4 % maintained the program three months later. ConclusionsIn years four and five of implementation, the ONE Program demonstrated improvement in four of the five domains of the RE-AIM model compared to years one and two. However, Reach declined over time. This reevaluation has demonstrated the importance of longitudinal program assessment, and the possibility of improved program performance over time.

The leadership of quality strategic for improvement lecture performance toward excellence’s university

This research found the strategic leadership of quality for improving lecture performance at the university as a public service. Leadership strategic aspects have affected the lecture performance. This research uses mix methods design. This research has been developed by strategic leadership for a quality model at the University of Mataram with qualitative case study. This research found strategy leadership of quality has an effective contribution to improving the lecture, dean, and head of study’s program performance at the University of Mataram, The strategy leadership for quality has more contributions to improve the lectures and education staff of study program. The faculty leadership element, namely the dean and head of a study program, has a considerable contribution to improving the performance of the institution he leads. The dean of the faculty must be able to plan educational and research programs well, this is seen from the planning, coordination, monitoring, and evaluation of each organizational unit within the University of Mataram. Furthermore, the head of the study program must also be able to transform superior study programs, such as doctoral study programs, and doctoral study programs at the University of Mataram.

Ambulatory Long Block: A Model of Precision Education and Assessment for Internal Medicine Residents.

High-quality precision education (PE) aims to enhance outcomes for learners and society by incorporating longitudinal data and analytics to shape personalized learning strategies. However, existing educational data collection methods often suffer from fragmentation, leading to gaps in understanding learner and program performance. In this article, the authors present a novel approach to PE at the University of Cincinnati, focusing on the Ambulatory Long Block, a year-long continuous ambulatory group-practice experience. Over the last 17 years, the Ambulatory Long Block has evolved into a sophisticated data collection and analysis system that integrates feedback from various stakeholders, as well as learner self-assessment, electronic health record utilization information, and clinical throughput metrics. The authors detail their approach to data prioritization, collection, analysis, visualization, and feedback, providing a practical example of PE in action. This model has been associated with improvements in both learner performance and patient care outcomes. The authors also highlight the potential for real-time data review through automation and emphasize the importance of collaboration in advancing PE. Generalizable principles include designing learning environments with continuity as a central feature, gathering both quantitative and qualitative performance data from interprofessional assessors, using this information to supplement traditional workplace-based assessments, and pairing it with self-assessments. The authors advocate for criterion referencing over normative comparisons, using user-friendly data visualizations, and employing tailored coaching strategies for individual learners. The Ambulatory Long Block model underscores the potential of PE to drive improvements in medical education and health care outcomes.

Hypertension clinical pathway: Experience of Aseer region, Saudi Arabia.

Hypertension (HTN) is a common chronic health problem with many complications and high morbidity rates. This study aimed to describe the HTN pathway, to assess the performance of screening and registration programs, to explore the challenges and suggest solutions for those challenges. This study was conducted in primary care centers in the Aseer region, Saudi Arabia, at the end of 2022. The study consisted of three parts namely: Screening for HTN, registration of known hypertensive patients and opinions of representatives of Primary Healthcare Centers (PHCs) on challenges to the implementation of HTN pathway and suggestions for overcoming these challenges. Three Google forms were developed by the investigators to achieve the objectives of this study. The first two forms were completed by doctors and nurses at each PHC and reviewed by the leader of HTN pathway, and the third form completed by a representative of each PHC. SPSS version 26 was used for data management and analysis. Chi-square test was used to determine association between categorical variables; binary logistic regression analysis was performed to determine the correlates of being hypertensive and having good control of HTN. A total of 159,243 individuals were screened for HTN, 55% of whom were females and 94% were Saudis. The prevalence of HTN was 13%; 70% were overweight or obese and 14% had diabetes. The total registered number of patients was 55,628; 50% had good HTN control. Major challenges were inadequate health coaches, care coordinators, laboratory and radiology facilities, lack of coordination with hospitals, and ineffective appointment system. This study revealed that the current HTN pathway was successful with regard to screening and registration of patients with HTN. Many challenges need an executive plan with SMART objectives to optimize the care for HTN patients in the region.

Utilization of Information Entropy in Training and Evaluation of Students’ Abstraction Performance and Algorithm Efficiency in Programming

Utilization of Information Entropy in Training and Evaluation of Students’ Abstraction Performance and Algorithm Efficiency in Programming

How is your loyalty programme going? A framework for a loyalty programme performance indication system

One of the root causes of the failure of membership programmes introduced by many companies is the lack of a systematic performance evaluation framework that can design, monitor and evaluate membership programmes tailored to the company’s own circumstances. This paper proposes a loyalty programme performance evaluation framework called MemPIS to help use the loyalty programme as a strategic platform for digital customer management and to provide a standard for optimising a company's loyalty programme. Using the MemPIS framework, this paper emphasises profitability, stability, growth potential and activeness of membership when evaluating programmes from a financial perspective, and suitability of tier design, reward design, point design and membership operation for the evaluation of programmes from a non-financial perspective. After developing candidate evaluation indicators and measurable matrixes for each evaluated subject, these are applied to a Korean cosmetics company to test the practical validity of the research and to suggest improvements to the membership programme to the company. Weights for all evaluative perspectives, subjects and indicators evaluated were calculated through AHP analysis. This research found that MemPIS can not only reveal the problems of a company's membership programme, but also suggest directions for improvement in the future.

Cystic fibrosis newborn screening in Switzerland – evaluation and scenarios for improvement after 11 years of follow-up

BackgroundNewborn bloodspot screening (NBS) for cystic fibrosis (CF) is important for early diagnosis and treatment. However, screening can lead to false-positive results leading to unnecessary follow-up tests and distress. This study evaluated the 11-year performance of the Swiss CF-NBS programme, estimated optimal cut-offs for immunoreactive trypsinogen (IRT), and examined how simulated algorithms would change performance. MethodsThe Swiss CF-NBS is based on an IRT–DNA algorithm with a second IRT (IRT-2) as safety net. We analysed data from 2011 to 2021, covering 959,006 IRT-1 analyses and 282 children with CF. We studied performance based on European Cystic Fibrosis Society (ECFS) standards including sensitivity, specificity, positive predictive value (PPV), false negative rate, and second heel-prick tests; identified optimal IRT cut-offs using receiver operating characteristics (ROC) curves; and calculated performance for simulated algorithms with different cut-offs for IRT-1, IRT-2, and safety net. ResultsThe Swiss CF-NBS showed excellent sensitivity (96 %, 10 false negative cases) but moderate PPV (25 %). Optimal IRT-1 and IRT-2 cut-offs were identified at 2.7 (>99th percentile) and 5.9 (>99.8th percentile) z-scores, respectively. Analysis of simulated algorithms showed that removing the safety net from the current algorithm could increase PPV to 30 % and eliminate >200 second heel-prick tests per year, while keeping sensitivity at 95 %. ConclusionThe Swiss CF-NBS program performed well over 11 years but did not achieve the ECFS standards for PPV (≥30 %). Modifying or removing the safety net could improve PPV and reduce unnecessary follow-up tests while maintaining the ECFS standards for sensitivity.

Alignment of HIV Program Performance to HIV Priorities in North Eastern Region of Uganda

The purpose of this study was to assess the alignment of HIV/AIDS programming in North Eastern Uganda to the current program goals of ending HIV as a public health threat in this region by 2030, achieving 95-95-95, and eliminating HIV/AIDS stigma in the community. The study found that the state of program implementation is not well aligned to and is not on track to achieve these program goals. The region had not achieved the desired level of performance in any of the 95 targets. The first 95 (proportion of people living with HIV who their HIV status) was found to be at approximately 75%. The second 95 (proportion of those living with HIV who are on Anti-Retroviral Therapy - ART) was found to be approximately 63% and the third 95 (Viral Load Suppression among those on treatment) was at approximately 70%. This made the cascade 75-63-70, which was significantly below the 95-95-95 targets. 36% percent of the people living with HIV report feeling significant levels of stigma, which is far from the target of 0%. The study documented the key challenges that are hindering progress towards the current program goals. These include limited funding, siloed programming, insufficient coordination, lack of prioritization of HIV programs by local leaders, frequent stockouts of essential commodities, shortage of personnel, and insufficient skills among some of the existing personnel. Urgent action is needed by all stakeholders to revamp HIV programming in the region and put it on track to achieve the desired goals.

A multi-surrogate genetic programming hyper-heuristic algorithm for the manufacturing project scheduling problem with setup times under dynamic and interference environments

In this study, in order to cope with the uncertain environments and space interference scenarios encountered in the production process for a class of manufacturing projects, we propose a novel manufacturing project scheduling problem with setup times under dynamic and interference environments (MPSPST-DIE), and design a novel multi-surrogate genetic programming hyper-heuristic (HH-MGP) algorithm to address it. Firstly, MPSPST-DIE is required to make decisions on the activity schedule, resource setup and space allocation. Therefore, we modify the traditional resource based policy class that only contains the activity schedule and simulate the entire scheduling process. Secondly, a new hyper-heuristic genetic programming algorithm is designed to automatically evolve activity rules, resource setup rules and space allocation rules simultaneously. Moreover, the multi-surrogate is devised to improve the performance of the basic genetic programming (GP) algorithm. In addition, a new evolutionary learning mechanism is embedded in the multi-surrogate. Different surrogates learn from each other to complement each other’s strengths. Finally, numerical instances of the MPSPST-DIE are generated by configuring specific parameters of spatial resources and extensive numerical experiments are performed. At the same time, we implement the Taguchi experiment for the sensitivity analysis of parameters. The comparative analysis between the HH-MGP and traditional rules is performed. Further, the performance comparison between the multi-surrogate and other surrogates is also conducted. The experimental results show that the evolved rule of the HH-MGP performs better than the traditional rules for the MPSPST-DIE. The performance of the multi-surrogate model added to the GP algorithm are generally better than the single-surrogate model and no-surrogate.

Health Equity Adjustment and Hospital Performance in the Medicare Value-Based Purchasing Program

Medicare's Hospital Value-Based Purchasing (HVBP) program will provide a health equity adjustment (HEA) to hospitals that have greater proportions of patients dually eligible for Medicare and Medicaid and that offer high-quality care beginning in fiscal year 2026. However, which hospitals will benefit most from this policy change and to what extent are unknown. To estimate potential changes in hospital performance after HEA and examine hospital patient mix, structural, and geographic characteristics associated with receipt of increased payments. This cross-sectional study analyzed all 2676 hospitals participating in the HVBP program in fiscal year 2021. Publicly available data on program performance and hospital characteristics were linked to Medicare claims data on all inpatient stays for dual-eligible beneficiaries at each hospital to calculate HEA points and HVBP payment adjustments. Hospital Value-Based Purchasing program HEA. Reclassification of HVBP bonus or penalty status and changes in payment adjustments across hospital characteristics. Of 2676 hospitals participating in the HVBP program in fiscal year 2021, 1470 (54.9%) received bonuses and 1206 (45.1%) received penalties. After HEA, 102 hospitals (6.9%) were reclassified from bonus to penalty status, whereas 119 (9.9%) were reclassified from penalty to bonus status. At the hospital level, mean (SD) HVBP payment adjustments decreased by $4534 ($90 033) after HEA, ranging from a maximum reduction of $1 014 276 to a maximum increase of $1 523 765. At the aggregate level, net-positive changes in payment adjustments were largest among safety net hospitals ($28 971 708) and those caring for a higher proportion of Black patients ($15 468 445). The likelihood of experiencing increases in payment adjustments was significantly higher among safety net compared with non-safety net hospitals (574 of 683 [84.0%] vs 709 of 1993 [35.6%]; adjusted rate ratio [ARR], 2.04 [95% CI, 1.89-2.20]) and high-proportion Black hospitals compared with non-high-proportion Black hospitals (396 of 523 [75.7%] vs 887 of 2153 [41.2%]; ARR, 1.40 [95% CI, 1.29-1.51]). Rural hospitals (374 of 612 [61.1%] vs 909 of 2064 [44.0%]; ARR, 1.44 [95% CI, 1.30-1.58]), as well as those located in the South (598 of 1040 [57.5%] vs 192 of 439 [43.7%]; ARR, 1.25 [95% CI, 1.10-1.42]) and in Medicaid expansion states (801 of 1651 [48.5%] vs 482 of 1025 [47.0%]; ARR, 1.16 [95% CI, 1.06-1.28]), were also more likely to experience increased payment adjustments after HEA compared with their urban, Northeastern, and Medicaid nonexpansion state counterparts, respectively. Medicare's implementation of HEA in the HVBP program will significantly reclassify hospital performance and redistribute program payments, with safety net and high-proportion Black hospitals benefiting most from this policy change. These findings suggest that HEA is an important strategy to ensure that value-based payment programs are more equitable.

Guided inquiry-based learning to enhance student engagement, confidence, and learning.

This study explores the impact of guided inquiry-based learning (IBL) on student engagement and performance in a dental hygiene program. The research was conducted with 36 dental hygiene students, focusing on enhancing student engagement using a guided IBL methodology that could ultimately lead to improved student performance and confidence. Delivered through two interventions, pre-, post-, and delayed post-tests evaluated student performance and confidence, while the ASPECT survey assessed student engagement. The interventions included a lecture (intervention #1) and a group-based IBL worksheet activity (intervention #2). Statistical analyses using analysis of variance (ANOVA) tested the impact of these interventions on student performance and confidence-adjusted scores. Results showed significant improvements in student performance and confidence following both interventions, with notably higher gains after the IBL activity. Analysis of ASPECT survey data revealed positive perceptions of engagement, emphasizing the importance of group dynamics, instructor roles, and the activity's value. Students reported enhanced understanding and engagement through group interactions and individual study. The study also highlighted the critical role of the instructor in facilitating and guiding the IBL activity. In conclusion, the study demonstrates that guided IBL strategies can significantly enhance student confidence and performance, suggesting a sustainable impact on learning outcomes. These findings underscore the importance of active, engaged learning methodologies in healthcare education, particularly in enhancing long-term retention and understanding of complex topics. The study advocates for integrating such strategies into academic curricula to foster deeper student engagement and improved educational experiences.

On the Performance of Malleable APGAS Programs and Batch Job Schedulers

Malleability—the ability for applications to dynamically adjust their resource allocations at runtime—presents great potential to enhance the efficiency and resource utilization of modern supercomputers. However, applications are rarely capable of growing and shrinking their number of nodes at runtime, and batch job schedulers provide only rudimentary support for such features. While numerous approaches have been proposed to enable application malleability, these typically focus on iterative computations and require complex code modifications. This amplifies the challenges for programmers, who already wrestle with the complexity of traditional MPI inter-node programming. Asynchronous Many-Task (AMT) programming presents a promising alternative. In AMT, computations are split into many fine-grained tasks, which are processed by workers. This makes transparent task relocation via the AMT runtime system possible, thus offering great potential for enabling efficient malleability. In this work, we propose an extension to an existing AMT system, namely APGAS for Java. We provide easy-to-use malleability programming abstractions, requiring only minor application code additions from programmers. Runtime adjustments, such as process initialization and termination, are automatically managed by our malleability extension. We validate our malleability extension by adapting a load balancing library handling multiple benchmarks. We show that both shrinking and growing operations cost low execution time overhead. In addition, we demonstrate compatibility with potential batch job schedulers by developing a prototype batch job scheduler that supports malleable jobs. Through extensive real-world job batches execution on up to 32 nodes, involving rigid, moldable, and malleable programs, we evaluate the impact of deploying malleable APGAS applications on supercomputers. Exploiting scheduling algorithms, such as FCFS, Backfilling, Easy-Backfilling, and one exploiting malleable jobs, the experimental results highlight a significant improvement regarding several metrics for malleable jobs. We show a 13.09% makespan reduction (the time needed to schedule and execute all jobs), a 19.86% increase in node utilization, and a 3.61% decrease in job turnaround time (the time a job takes from its submission to completion) when using 100% malleable job in combination with our prototype batch job scheduler compared to the best-performing scheduling algorithm with 100% rigid jobs.

Community pharmacist-led point-of-care eGFR screening: early detection of chronic kidney disease in high-risk patients

Adherence to scheduled physician screenings for renal function monitoring in patients with chronic kidney disease (CKD) or those at high risk remains suboptimal despite the endorsement of regular screenings by several clinical practice guidelines. Our study aims to assess the effectiveness of a point-of-care CKD screening program led by these pharmacists using the PICCOLO device while recognizing the unique position of community pharmacists in primary care. We conducted an 11-month prospective point-of-care interventional research study in the United Arab Emirates to evaluate the performance of a community pharmacist-led CKD screening program for high-risk patients. Six diverse community pharmacies were selected based on staff availability, patient volume, and their offered range of services. Eligible individuals with risk factors for CKD were identified during medication evaluations. The PICCOLO Comprehensive Metabolic Panel facilitated on-site blood analysis, delivering estimated Glomerular Filtration Rate (eGFR) results within 10 to 15 min. Data also included eGFR categories, demographic information, and insights into lifestyle and health habits collected through a questionnaire. Pharmacists conducted comprehensive medication reviews and offered referrals and lifestyle guidance as part of the program. The study encompassed a total of 400 patients, with an average age of 69 ± 13.4 years within the study cohort. Notably, 38.8% (155 individuals) of the 400 patients were found to have undiagnosed CKD stages 3–5. Univariate logistic regression analysis revealed a significant association between a higher incidence of CKD stages 3–5 and factors such as older age, a history of hypertension, vascular disease, and diabetes mellitus. In the multivariate regression model, age and a history of diabetes mellitus emerged as significant predictors of an elevated risk of CKD. This study sheds light on the viability and impact of CKD screening programs conducted by community pharmacists, particularly in detecting CKD stages 3–5. The findings have implications for healthcare policies, as they can influence the enhancement of early detection and management of CKD. Moreover, these insights may catalyze focused screening initiatives and strengthen collaboration between community pharmacies and healthcare systems to benefit patients at high risk of CKD.